[Characteristics of moxibustion in Dragon Gate Stone Inscription prescriptions].

The Dragon Gate Stone Inscription prescriptions are the earliest surviving stone inscriptions of medical formulas in China, covering various departments such as internal medicine, surgery, gynecology, pediatrics and ophthalmology. By reviewing 28 moxibustion prescriptions recorded in the Dragon Gate Stone Inscriptions, the following application characteristics are summarized: moxibustion mainly treats acute diseases such as mania, deficiency-cold syndrome, and jaundice; in terms of point selection, specific points such as the thirteen ghost points, eight influential points, and front-mu points are used, emphasizing the extraordinary meridians such as governor vessel and conception vessel, as well as specific single acupoints with unique therapeutic effects; in clinical application, it follows the principle of treating according to syndrome differentiation, uses multiple acupoints simultaneously, employs food-medicine homology, and adjusts the moxibustion dosage according to individual conditions. The Dragon Gate Stone Inscription prescriptions reflect that the application of moxibustion therapy during the Northern Wei to Tang Dynasty period had already reached a relatively mature level, indicating a high level of proficiency in moxibustion techniques during that time.

Design of Ultra-Compact and Multifunctional Optical Logic Gate Based on Sb2Se3-SOI Hybrid Platform.

Optical logic devices are essential functional devices for achieving optical signal processing. In this study, we design an ultra-compact (4.92 × 2.52 µm2) reconfigurable optical logic gate by using inverse design method with DBS algorithm based on Sb2Se3-SOI integrated platform. By selecting different amorphous/crystalline distributions of Sb2Se3 via programmable electrical triggers, the designed structure can switch between OR, XOR, NOT or AND logic gate. This structure works well for all four logic functions in the wavelength range of 1540-1560 nm. Especially at the wavelength of 1550 nm, the Contrast Ratios for XOR, NOT and AND logic gate are 13.77 dB, 11.69 dB and 3.01 dB, respectively, indicating good logical judgment ability of the device. Our design is robust to a certain range of fabrication imperfections. Even if performance weakens due to deviations, improvements can be obtained by rearranging the configurations of Sb2Se3 without reproducing the whole device.

Gamma-Irradiation-Induced Electrical Characteristic Variations in MoS2 Field-Effect Transistors with Buried Local Back-Gate Structure.

The impact of radiation on MoS2-based devices is an important factor in the utilization of two-dimensional semiconductor-based technology in radiation-sensitive environments. In this study, the effects of gamma irradiation on the electrical variations in MoS2 field-effect transistors with buried local back-gate structures were investigated, and their related effects on Al2O3 gate dielectrics and MoS2/Al2O3 interfaces were also analyzed. The transfer and output characteristics were analyzed before and after irradiation. The current levels decreased by 15.7% under an exposure of 3 kGy. Additionally, positive shifts in the threshold voltages of 0.50, 0.99, and 1.15 V were observed under irradiations of 1, 2, and 3 kGy, respectively, compared to the non-irradiated devices. This behavior is attributable to the comprehensive effects of hole accumulation in the Al2O3 dielectric interface near the MoS2 side and the formation of electron trapping sites at the interface, which increased the electron tunneling at the MoS2 channel/dielectric interface.

Analysis of 3D Channel Current Noise in Small Nanoscale MOSFETs Using Monte Carlo Simulation.

As field effect transistors are reduced to nanometer dimensions, experimental and theoretical research has shown a gradual change in noise generation mechanisms. There are few studies on noise theory for small nanoscale transistors, and Monte Carlo (MC) simulations mainly focus on 2D devices with larger nanoscale dimensions. In this study, we employed MC simulation techniques to establish a 3D device simulation process. By setting device parameters and writing simulation programs, we simulated the raw data of channel current noise for a silicon-based metal-oxide-semiconductor field-effect transistor (MOSFET) with a 10 nm channel length and calculated the drain output current based on these data, thereby achieving static testing of the simulated device. Additionally, this study obtained a 3D potential distribution map of the device channel surface area. Based on the original data from the simulation analysis, this study further calculated the power spectral density of the channel current noise and analyzed how the channel current noise varies with gate voltage, source-drain voltage, temperature, and substrate doping density. The results indicate that under low-temperature conditions, the channel current noise of the 10 nm MOSFET is primarily composed of suppressed shot noise, with the proportion of thermal noise in the total noise slightly increasing as temperature rises. Under normal operating conditions, the channel current noise characteristics of the 10 nm MOSFET device are jointly characterized by suppressed shot noise, thermal noise, and cross-correlated noise. Among these noise components, shot noise is the main source of noise, and its suppression degree decreases as the bias voltage is reduced. These findings are consistent with experimental observations and theoretical analyses found in the existing literature.

Feasibility study of ultra-low-head hydro turbines for energy extraction from shallow waterways.

Ultra-low-head turbines can harness energy from previously deemed unsuitable sites, including natural and man-made locations like shallow estuaries, marine canals, and industrial waterways. Various hydro-turbine concepts were evaluated for their potential to extract power from these areas. These turbines can generate renewable energy for utilization in remotely located areas. A horizontal-axis screw turbine concept, horizontal and vertical Savonius turbine concepts, axial turbine concepts, and a gate turbine concept were investigated in the present study using computational fluid dynamic tools. Reynolds Averaged Navier Stokes equations with a shear stress transport model are used to calculate the flow field. The numerical methodology is then verified with previously published data. The turbine performances were compared and the design feasibility was analyzed to find the most effective turbine design which can extract the maximum energy. The gate turbine concept exhibited a significant power output with high efficiency while the screw turbine showed the lowest performance among the tested designs. The horizontal Savonius turbine displayed enhanced performance with an increment of 23.25 % compared to the screw turbine. An additional parametric study is conducted on the gate turbine namely, the number of runner blades, and the gate installation angle. The 3-bladed gate turbine installed at a 14° gate angle showed superior power output and efficiency than other hydrokinetic turbines.

Self-Aligned Edge Contact Process for Fabricating High-Performance Transition-Metal Dichalcogenide Field-Effect Transistors.

The persistent challenges encountered in metal-transition-metal dichalcogenide (TMD) junctions, including tunneling barriers and Fermi-level pinning, pose significant impediments to achieving optimal charge transport and reducing contact resistance. To address these challenges, a pioneering self-aligned edge contact (SAEC) process tailored for TMD-based field-effect transistors (FETs) is developed by integrating a WS2 semiconductor with a hexagonal boron nitride dielectric via reactive ion etching. This approach streamlines semiconductor fabrication by enabling edge contact formation without the need for additional lithography steps. Notably, SAEC TMD-based FETs exhibit exceptional device performance, featuring a high on/off current ratio of ∼108, field-effect mobility of up to 120 cm2/V·s, and controllable polarity─essential attributes for advanced TMD-based logic circuits. Furthermore, the SAEC process enables precise electrode positioning and effective minimization of parasitic capacitance, which are pivotal for attaining high-speed characteristics in TMD-based electronics. The compatibility of the SAEC technique with existing Si self-aligned processes underscores its feasibility for integration into post-CMOS applications, heralding an upcoming era of integration of TMDs into Si semiconductor electronics. The introduction of the SAEC process represents a significant advancement in TMD-based microelectronics and is poised to unlock the full potential of TMDs for future electronic technologies.

Semiconducting Properties of Delaminated Titanium Nitride Ti4N3Tx MXene with Gate-Tunable Electrical Conductivity.

MXenes have garnered significant attention due to their atomically thin two-dimensional structure with metallic electronic properties. However, it has not yet been fully achieved to discover semiconducting MXenes to implement them into gate-tunable electronics such as field-effect transistors and phototransistors. Here, a semiconducting Ti4N3Tx MXene synthesized by using a modified oxygen-assisted molten salt etching method under ambient conditions, is reported. The oxygen-rich synthesis environment significantly enhances the etching reaction rate and selectivity of Al from a Ti4AlN3 MAX phase, resulting in well-delaminated and highly crystalline Ti4N3Tx MXene with minimal defects and high content of F and O, which led to its improved hydrophobicity and thermal stability. Notably, the synthesized Ti4N3Tx MXene exhibited p-type semiconducting characteristics, including gate-tunable electrical conductivity, with a current on-off ratio of 5 × 103 and a hole mobility of ∼0.008 cm2 V-1 s-1 at 243 K. The semiconducting property crucial for thin-film transistor applications is evidently associated with the surface terminations and the partial substitution of oxygen in the nitrogen lattice, as corroborated by density functional theory (DFT) calculations. Furthermore, the synthesized Ti4N3Tx exhibits strong light absorption characteristics and photocurrent generation. These findings highlight the delaminated Ti4N3Tx as an emerging two-dimensional semiconducting material for potential electronic and optoelectronic applications.

Ternary Content-Addressable Memory Based on a Single Two-Dimensional Transistor for Memory-Augmented Learning.

Ternary content-addressable memory (TCAM) is promising for data-intensive artificial intelligence applications due to its large-scale parallel in-memory computing capabilities. However, it is still challenging to build a reliable TCAM cell from a single circuit component. Here, we demonstrate a single transistor TCAM based on a floating-gate two-dimensional (2D) ambipolar MoTe2 field-effect transistor with graphene contacts. Our bottom graphene contacts scheme enables gate modulation of the contact Schottky barrier heights, facilitating carrier injection for both electrons and holes. The 2D nature of our channel and contact materials provides device scaling potentials beyond silicon. By integration with a floating-gate stack, a highly reliable nonvolatile memory is achieved. Our TCAM cell exhibits a resistance ratio larger than 1000 and symmetrical complementary states, allowing the implementation of large-scale TCAM arrays. Finally, we show through circuit simulations that in-memory Hamming distance computation is readily achievable based on our TCAM with array sizes up to 128 cells.

Utilizing the Fujimori Gate Flap for the Reconstruction of Squamous Cell Carcinoma: A Case Report.

The surgical treatment of oral squamous cell carcinoma (SCC) results in tissue defects caused by the removal of the cancerous tissue. There are various reconstruction options available for lip construction. Harvesting the flap to reconstruct these defects undoubtedly results in substantial morbidity. Lip reconstruction can be performed more efficiently and with reduced side effects by utilizing flaps, which can minimize donor site morbidity and shorten surgical harvesting time. We are reporting a case involving a 52-year-old male with SCC of the lip who presented without any comorbidity. This case report describes the careful lip reconstruction using the Fujimori gate flap technique following complete surgical excision of the lesion.

Designing a Novel Temperature- and Noncanonical Amino Acid-Controlled Biological Logic Gate in Escherichia coli.

Genetic code expansion (GCE) is a powerful strategy that expands the genetic code of an organism for incorporating noncanonical amino acids into proteins using engineered tRNAs and aminoacyl-tRNA synthetases (aaRSs). While GCE has opened up new possibilities for synthetic biology, little is known about the potential side effects of exogenous aaRS/tRNA pairs. In this study, we investigated the impact of exogenous aaRS and amber suppressor tRNA on gene expression in Escherichia coli. We discovered that in DH10ß ΔcyaA, transformed with the F1RP/F2P two-hybrid system, the high consumption rate of cellular adenosine triphosphate by exogenous aaRS/tRNA at elevated temperatures induces temperature sensitivity in the expression of genes regulated by the cyclic AMP receptor protein (CRP). We harnessed this temperature sensitivity to create a novel biological AND gate in E. coli, responsive to both p-benzoylphenylalanine (BzF) and low temperature, using a BzF-dependent variant of E. coli chorismate mutase and split subunits of Bordetella pertussis adenylate cyclase. Our study provides new insights into the unexpected effects of exogenous aaRS/tRNA pairs and offers a new approach for constructing a biological logic gate.

MARes-Net: multi-scale attention residual network for jaw cyst image segmentation.

Jaw cyst is a fluid-containing cystic lesion that can occur in any part of the jaw and cause facial swelling, dental lesions, jaw fractures, and other associated issues. Due to the diversity and complexity of jaw images, existing deep-learning methods still have challenges in segmentation. To this end, we propose MARes-Net, an innovative multi-scale attentional residual network architecture. Firstly, the residual connection is used to optimize the encoder-decoder process, which effectively solves the gradient disappearance problem and improves the training efficiency and optimization ability. Secondly, the scale-aware feature extraction module (SFEM) significantly enhances the network's perceptual abilities by extending its receptive field across various scales, spaces, and channel dimensions. Thirdly, the multi-scale compression excitation module (MCEM) compresses and excites the feature map, and combines it with contextual information to obtain better model performance capabilities. Furthermore, the introduction of the attention gate module marks a significant advancement in refining the feature map output. Finally, rigorous experimentation conducted on the original jaw cyst dataset provided by Quzhou People's Hospital to verify the validity of MARes-Net architecture. The experimental data showed that precision, recall, IoU and F1-score of MARes-Net reached 93.84%, 93.70%, 86.17%, and 93.21%, respectively. Compared with existing models, our MARes-Net shows its unparalleled capabilities in accurately delineating and localizing anatomical structures in the jaw cyst image segmentation.

High-throughput screen to identify and optimize NOT gate receptors for cell therapy.

Logic-gated engineered cells are an emerging therapeutic modality that can take advantage of molecular profiles to focus medical interventions on specific tissues in the body. However, the increased complexity of these engineered systems may pose a challenge for prediction and optimization of their behavior. Here we describe the design and testing of a flow cytometry-based screening system to rapidly select functional inhibitory receptors from a pooled library of candidate constructs. In proof-of-concept experiments, this approach identifies inhibitory receptors that can operate as NOT gates when paired with activating receptors. The method may be used to generate large datasets to train machine learning models to better predict and optimize the function of logic-gated cell therapeutics.

Selective Chromogenic Chemosensors for Arsenite Anion: A Facile Approach to Analyzing Arsenite in Honey, Milk, and Water samples.

In this study, two chemosensors, N5R1 and N5R2, based on 5-(4-nitrophenyl)-2-furaldehyde, with varying electron-withdrawing groups, were synthesized and effectively employed for the colorimetric selective detection of arsenite anions in a DMSO/H2O solvent mixture (8:2, v/v). Chemosensors N5R1 and N5R2 exhibited a distinct color change upon binding with arsenite, accompanied by a spectral shift toward the near-infrared region (Δλmax exceeding 200 nm). These chemosensors established stability between a pH range 6-12. Among them, N5R2 displayed the lowest detection limit of 17.63 ppb with a high binding constant of 2.6163×105 M⁻1 for arsenite. The binding mechanism involved initial hydrogen bonding between the NH binding site and the arsenite anion, followed by deprotonation and an intramolecular charge transfer (ICT) mechanism. The mechanism was confirmed through UV and 1H NMR titrations, cyclic voltammetric studies, and theoretical calculations. The interactions between the sensor and arsenite anions were further analyzed using global reactivity parameters (GRPs). Practical applications were demonstrated through the utilization of test strips and molecular logic gates. Real water samples, honey, and milk samples were successfully analyzed by both chemosensors for the sensing of arsenite.

An optimised CRISPR Cas9 and Cas12a mutagenesis toolkit for Barley and Wheat.

BACKGROUND: CRISPR Cas9 and Cas12a are the two most frequently used programmable nucleases reported in plant systems. There is now a wide range of component parts for both which likely have varying degrees of effectiveness and potentially applicability to different species. Our aim was to develop and optimise Cas9 and Cas12a based systems for highly efficient genome editing in the monocotyledons barley and wheat and produce a user-friendly toolbox facilitating simplex and multiplex editing in the cereal community. RESULTS: We identified a Zea mays codon optimised Cas9 with 13 introns in conjunction with arrayed guides driven by U6 and U3 promoters as the best performer in barley where 100% of T0 plants were simultaneously edited in all three target genes. When this system was used in wheat > 90% of T0 plants were edited in all three subgenome targets. For Cas12a, an Arabidopsis codon optimised sequence with 8 introns gave the best editing efficiency in barley when combined with a tRNA based multiguide array, resulting in 90% mutant alleles in three simultaneously targeted genes. When we applied this Cas12a system in wheat 86% & 93% of T0 plants were mutated in two genes simultaneously targeted. We show that not all introns contribute equally to enhanced mutagenesis when inserted into a Cas12a coding sequence and that there is rationale for including multiple introns. We also show that the combined effect of two features which boost Cas12a mutagenesis efficiency (D156R mutation and introns) is more than the sum of the features applied separately. CONCLUSION: Based on the results of our testing, we describe and provide a GoldenGate modular cloning system for Cas9 and Cas12a use in barley and wheat. Proven Cas nuclease and guide expression cassette options found in the toolkit will facilitate highly efficient simplex and multiplex mutagenesis in both species. We incorporate GRF-GIF transformation boosting cassettes in wheat options to maximise workflow efficiency.

Algorithm prediction of single particle irradiation effect based on novel TFETs.

In order to predict the single particle irradiation of tunnel field effect transistor (TFET) devices, a deep learning algorithm network model was built to predict the key characterization parameters of the single particle transient. Computer aided design (TCAD) technique is used to study the influence of single particle effect on the novel stacked source trench gate TFET device. The results show that with the increase of drain voltage, incident width of heavy ions (less than 0.04µm), and linear energy transfer, the drain transient current and collected charge also increase. The prediction results of deep learning algorithm show that the relative error percentage of drain current pulse peak (IDMAX) and collected charge (Qc) is less than 10%, and the relative error percentage of most predicted values is less than 1%. Comparison experiments with five traditional machine learning methods (support vector machine, decision tree, K-nearest algorithm, ridge regression, linear regression) show that the deep learning algorithm has the best performance and has the smallest average error percentage. This data-driven deep learning algorithm model not only enables researchers who are not familiar with semiconductor devices to quickly obtain the transient data of a single particle under any conditions; at the same time, it can be applied to digital circuit design as a data-driven device model reflecting the reliability of single particle transient. The application of deep learning in the field of device irradiation prediction has a highly promising prospect in the future.

Logic Computing Field-Effect Transistors Based on a Monolayer WSe2 Homojunction for the Semi-adder and Decoder.

Two-dimensional reconfigurable field-effect transistors (FETs) are promising candidates for next-generation computing hardware. However, exploring the cascade design of FETs for logic computing remains challenging. Here, by using density functional theory combined with the nonequilibrium Green's function method, we design a 5 nm split-gate FET based on a monolayer WSe2 homojunction, which can implement dynamic polarity control in different gate configurations. The series array of two FETs shows a functional family of logic gates (NOR, AND, XOR, A̅B, and AB̅), and the semi-adder designed by the logic functions AND and XOR reduces the number of transistors by 66.7%. The parallel array of two FETs demonstrates reconfigurable logic gates with NAND/OR/A̅+B/A+B̅ quadruple functions, which can realize the decoding function of 00-11 in the decoder. The cascade design of the electrically tunable FETs helps to tackle the logic device downscaling and integration dilemmas.

Segmentation and Estimation of Fetal Biometric Parameters using an Attention Gate Double U-Net with Guided Decoder Architecture.

The fetus's health is evaluated with the biometric parameters obtained from the low-resolution ultrasound images. The accuracy of biometric parameters in existing protocols typically depends on conventional image processing approaches and hence, is prone to error. This study introduces the Attention Gate Double U-Net with Guided Decoder (ADU-GD) model specifically crafted for fetal biometric parameter prediction. The attention network and guided decoder are specifically designed to dynamically merge local features with their global dependencies, enhancing the precision of parameter estimation. The ADU-GD displays superior performance with Mean Absolute Error of 0.99 mm and segmentation accuracy of 99.1 % when benchmarked against the well-established models. The proposed model consistently achieved a high Dice index score of about 99.1 ± 0.8, with a minimal Hausdorff distance of about 1.01 ± 1.07 and a low Average Symmetric Surface Distance of about 0.25 ± 0.21, demonstrating the model's excellence. In a comprehensive evaluation, ADU-GD emerged as a frontrunner, outperforming existing deep-learning models such as Double U-Net, DeepLabv3, FCN-32s, PSPNet, SegNet, Trans U-Net, Swin U-Net, Mask-R2CNN, and RDHCformer models in terms of Mean Absolute Error for crucial fetal dimensions, including Head Circumference, Abdomen Circumference, Femur Length, and BiParietal Diameter. It achieved superior accuracy with MAE values of 2.2 mm, 2.6 mm, 0.6 mm, and 1.2 mm, respectively.

Multiplex Expression Cassette Assembly: A flexible and versatile method for building complex genetic circuits in conventional vectors.

The manipulation of multiple transcription units for simultaneous and coordinated expression is not only key to building complex genetic circuits to accomplish diverse functions in synthetic biology, but is also important in crop breeding for significantly improved productivity and overall performance. However, building constructs with multiple independent transcription units for fine-tuned and coordinated regulation is complicated and time-consuming. Here, we introduce the Multiplex Expression Cassette Assembly (MECA) method, which modifies canonical vectors compatible with Golden Gate Assembly, and then uses them to produce multi-cassette constructs. By embedding the junction syntax in primers that are used to amplify functional elements, MECA is able to make complex constructs using only one intermediate vector and one destination vector via two rounds of one-pot Golden Gate assembly reactions, without the need for dedicated vectors and a coherent library of standardized modules. As a proof-of-concept, we modified eukaryotic and prokaryotic expression vectors to generate constructs for transient expression of green fluorescent protein and ß-glucuronidase in Nicotiana benthamiana, genome editing to block monoterpene metabolism in tomato glandular trichomes, production of betanin in tobacco and synthesis of ß-carotene in Escherichia coli. Additionally, we engineered the stable production of thymol and carvacrol, bioactive compounds from Lamiaceae family plants, in glandular trichomes of tobacco. These results demonstrate that MECA is a flexible, efficient and versatile method for building complex genetic circuits, which will not only play a critical role in plant synthetic biology, but also facilitate improving agronomic traits and pyramiding traits for the development of next-generation elite crops.

An emerging quaternary semiconductor nanoribbon with gate-tunable anisotropic conductance.

Two-dimensional noble transition metal chalcogenide (NTMC) semiconductors represent compelling building blocks for fabricating flexible electronic and optoelectronic devices. While binary and ternary compounds have been reported, the existence of quaternary NTMCs with a greater elemental degree of freedom remains largely unexplored. This study presents the pioneering experimental realization of a novel semiconducting quaternary NTMC material, AuPdNaS2, synthesized directly on Au foils through chemical vapor deposition. The ribbon-shaped morphology of the AuPdNaS2 crystal can be finely tuned to a thickness as low as 9.2 nm. Scanning transmission electron microscopy reveals the atomic arrangement, showcasing robust anisotropic features; thus, AuPdNaS2 exhibits distinct anisotropic phonon vibrations and electrical properties. The field-effect transistor constructed from AuPdNaS2 crystal demonstrates a pronounced anisotropic conductance (σmax/σmin = 3.20) under gate voltage control. This investigation significantly expands the repertoire of NTMC materials and underscores the potential applications of AuPdNaS2 in nano-electronic devices.

PET digitization chain for Monte Carlo simulation in GATE.

Objective. We introduce a versatile methodology for the accurate modelling of PET imaging systems via Monte Carlo simulations, using the Geant4 application for tomographic emission (GATE) platform. Accurate Monte Carlo modelling involves the incorporation of a complete analytical signal processing chain, called the digitizer in GATE, to emulate the different count rates encountered in actual positron emission tomography (PET) systems.Approach. The proposed approach consists of two steps: (1) modelling the digitizer to replicate the detection chain of real systems, covering all available parameters, whether publicly accessible or supplied by manufacturers; (2) estimating the remaining parameters, i.e. background noise level, detection efficiency, and pile-up, using optimisation techniques based on experimental single and prompt event rates. We show that this two-step optimisation reproduces the other experimental count rates (true, scatter, and random), without the need for additional adjustments. This method has been applied and validated with experimental data derived from the NEMA count losses test for three state-of-the-art SiPM-based time-of-flight (TOF)-PET systems: Philips Vereos, Siemens Biograph Vision 600 and GE Discovery MI 4-ring.Main results. The results show good agreement between experiments and simulations for the three PET systems, with absolute relative discrepancies below 3%, 6%, 6%, 7% and 12% for prompt, random, true, scatter and noise equivalent count rates, respectively, within the 0-10 kBq·ml-1activity concentration range typically observed in whole-body18F scans.Significance. Overall, the proposed digitizer optimisation method was shown to be effective in reproducing count rates and NECR for three of the latest generation SiPM-based TOF-PET imaging systems. The proposed methodology could be applied to other PET scanners.