Signal Flow Research Articles

The MT1 receptor as the target of ramelteon neuroprotection in ischemic stroke.

Stroke is the leading cause of death and disability worldwide. Novel and effective therapies for ischemic stroke are urgently needed. Here, we report that melatonin receptor 1A (MT1) agonist ramelteon is a neuroprotective drug candidate as demonstrated by comprehensive experimental models of ischemic stroke, including a middle cerebral artery occlusion (MCAO) mouse model of cerebral ischemia in vivo, organotypic hippocampal slice cultures ex vivo, and cultured neurons in vitro; the neuroprotective effects of ramelteon are diminished in MT1-knockout (KO) mice and MT1-KO cultured neurons. For the first time, we report that the MT1 receptor is significantly depleted in the brain of MCAO mice, and ramelteon treatment significantly recovers the brain MT1 losses in MCAO mice, which is further explained by the Connectivity Map L1000 bioinformatic analysis that shows gene-expression signatures of MCAO mice are negatively connected to melatonin receptor agonist like Ramelteon. We demonstrate that ramelteon improves the cerebral blood flow signals in ischemic stroke that is potentially mediated, at least, partly by mechanisms of activating endothelial nitric oxide synthase. Our results also show that the neuroprotection of ramelteon counteracts reactive oxygen species-induced oxidative stress and activates the nuclear factor erythroid 2-related factor 2/heme oxygenase-1 pathway. Ramelteon inhibits the mitochondrial and autophagic death pathways in MCAO mice and cultured neurons, consistent with gene set enrichment analysis from a bioinformatics perspective angle. Our data suggest that Ramelteon is a potential neuroprotective drug candidate, and MT1 is the neuroprotective target for ischemic stroke, which provides new insights into stroke therapy. MT1-KO mice and cultured neurons may provide animal and cellular models of accelerated ischemic damage and neuronal cell death.

Modulating the dynamics of NFκB and PI3K enhances the ensemble-level TNFR1 signaling mediated apoptotic response

Cell-to-cell variability during TNFα stimulated Tumor Necrosis Factor Receptor 1 (TNFR1) signaling can lead to single-cell level pro-survival and apoptotic responses. This variability stems from the heterogeneity in signal flow through intracellular signaling entities that regulate the balance between these two phenotypes. Using systematic Boolean dynamic modeling of a TNFR1 signaling network, we demonstrate that the signal flow path variability can be modulated to enable cells favour apoptosis. We developed a computationally efficient approach “Boolean Modeling based Prediction of Steady-state probability of Phenotype Reachability (BM-ProSPR)” to accurately predict the network’s ability to settle into different phenotypes. Model analysis juxtaposed with the experimental observations revealed that NFκB and PI3K transient responses guide the XIAP behaviour to coordinate the crucial dynamic cross-talk between the pro-survival and apoptotic arms at the single-cell level. Model predicted the experimental observations that ~31% apoptosis increase can be achieved by arresting Comp1 – IKK* activity which regulates the NFκB and PI3K dynamics. Arresting Comp1 – IKK* activity causes signal flow path re-wiring towards apoptosis without significantly compromising NFκB levels, which govern adequate cell survival. Priming an ensemble of cancerous cells with inhibitors targeting the specific interaction involving Comp1 and IKK* prior to TNFα exposure could enable driving them towards apoptosis.

SARS-CoV-2 Spike Protein Intensifies Cerebrovascular Complications in Diabetic hACE2 Mice through RAAS and TLR Signaling Activation.

Diabetics are more vulnerable to SARS-CoV-2 neurological manifestations. The molecular mechanisms of SARS-CoV-2-induced cerebrovascular dysfunction in diabetes are unclear. We hypothesize that SARS-CoV-2 exacerbates diabetes-induced cerebrovascular oxidative stress and inflammation via activation of the destructive arm of the renin-angiotensin-aldosterone system (RAAS) and Toll-like receptor (TLR) signaling. SARS-CoV-2 spike protein was injected in humanized ACE2 transgenic knock-in mice. Cognitive functions, cerebral blood flow, cerebrovascular architecture, RAAS, and TLR signaling were used to determine the effect of SARS-CoV-2 spike protein in diabetes. Studies were mirrored in vitro using human brain microvascular endothelial cells treated with high glucose-conditioned media to mimic diabetic conditions. Spike protein exacerbated diabetes-induced cerebrovascular oxidative stress, inflammation, and endothelial cell death resulting in an increase in vascular rarefaction and diminished cerebral blood flow. SARS-CoV-2 spike protein worsened cognitive dysfunction in diabetes compared to control mice. Spike protein enhanced the destructive RAAS arm at the expense of the RAAS protective arm. In parallel, spike protein significantly exacerbated TLR signaling in diabetes, aggravating inflammation and cellular apoptosis vicious circle. Our study illustrated that SAR-CoV-2 spike protein intensified RAAS and TLR signaling in diabetes, increasing cerebrovascular damage and cognitive dysfunction.

The Effects of Free Breathing on Cerebral Venous Flow: A Real-Time Phase Contrast MRI Study in Healthy Adults.

Quantifying the effects of free breathing on cerebral venous flow is crucial for understanding cerebral circulation mechanisms and clinical applications. Unlike conventional cine phase-contrast MRI sequences (CINE-PC), real-time phase-contrast MRI sequences (RT-PC) can provide a continuous beat-to-beat flow signal that makes it possible to quantify the effect of breathing on cerebral venous flow. In this study, we examined 28 healthy human participants, comprising of 14 males and 14 females. Blood flows in the right/left internal jugular veins in the extracranial plane and the superior sagittal sinus (SSS) and straight sinus in the intercranial plane were quantified using CINE-PC and RT-PC. The first objective of this study was to determine the accuracy of RT-PC in quantifying cerebral venous flow, relative to CINE-PC. The second, and main objective, was to quantify the effect of free breathing on cerebral venous flow, using a time-domain multiparameter analysis method. Our results showed that RT-PC can accurately quantify cerebral venous flow with a 2 × 2 mm2 spatial resolution and 75 ms/image time resolution. The mean flow rate, amplitude, stroke volume, and cardiac period of cerebral veins were significantly higher from the mid-end phase of expiration to the mid-end phase of inspiration. Breathing affected the mean flow rates in the jugular veins more than those in the SSS and straight sinus. Furthermore, the effects of free breathing on the flow rate of the left and right jugular veins were not synchronous. These new findings provide a useful reference for better understanding the mechanisms of cerebral circulation.

1-to-N terahertz integrated switches enabling multi-beam antennas

Implementing terahertz circuits and system designs relies on integrating reconfigurable devices such as switches, to fulfill a critical role in controlling and manipulating the flow of terahertz signals on the chip. Although there have been several demonstrations of on–off switching in the terahertz range, there have been no demonstrations of 1-to-N switching, to our knowledge. This pronounced lack of dynamically reconfigurable routing has severely limited the achievable complexity of terahertz systems. To address this, we propose 1-to-N switches made of cascaded disk resonators integrated into a substrateless silicon waveguide platform. A single switch can be controlled via photoexcitation using a low-power 658-nm laser focused onto the disk resonator, turning off the resonance and inhibiting coupling into a crossing port. The measurement results demonstrate that the proposed switch has low insertion loss, which can be attributed to the inherently low dissipation of the platform. The proposed on–off switch achieves a maximum insertion loss of 1.2 dB, and the maximum extinction ratio of the switch is 16.1 dB with 1.5 GHz of bandwidth. Furthermore, a 1-to-3 switch is monolithically integrated together with a Luneburg lens in order to project each of its output ports to a different far-field direction and, thereby, translate the switching operation into a form of reconfigurable beam control for future applications.

Detection of Clostridium perfringens Using Novel Methods Based on Recombinase-Aided Amplification Assay-Assisted CRISPR/Cas12a System

Clostridium perfringens is a highly versatile pathogen of humans and animals. Rapid and sensitive detection methods for C. perfringens are urgently needed for the timely implementation of control. In this study, to provide novel promising methods for the detection of C. perfringens, two rapid, sensitive, and instrument-free C. perfringens detection methods based on recombinase-aided amplification (RAA) assay and clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated protein 12a (CRISPR/Cas12a) system were developed depending on fluorescence signal (RAA-CRISPR/Cas12a-FL) and lateral flow strip (RAA-CRISPR/Cas12a-LFS), respectively. The limit of detection of the RAA-CRISPR/Cas12a-FL and RAA-CRISPR/Cas12a-LFS methods is 2 copies and 20 copies of C. perfringens genomic DNA per reaction, respectively, and the whole process can be completed in 1 hr. Moreover, these two methods show no cross-reactivity with nontarget bacteria, which were used as a negative control to evaluate the specificity of two developed methods in the detection of C. perfringens and have 100% consistent with real-time polymerase chain reaction tests for 12 clinical samples collected from 2 Chinese Milu at Beijing Milu Ecological Research Center and 6 spiked samples from human blood and stool. Overall, the constructed C. perfringens detection methods, RAA-CRISPR/Cas12a-FL and RAA-CRISPR/Cas12a-LFS, have great potential as a novel detection scheme for the early diagnosis of C. perfringens infection in humans and animals.

Polypoidal Choroidal Vasculopathy: Evaluation Based on 3-Dimensional Reconstruction of OCT Angiography

Three-dimensional (3D) reconstruction using swept-source OCT angiography (SS-OCTA) can provide insights into the nature and structure of polypoidal choroidal vasculopathy (PCV) and its component parts, the polypoidal lesion (PL) and the branching neovascular network (BNN). This study aims to describe novel observations of PCV using 3D reconstruction of SS-OCTA, and to compare these observations with similar images of type I macular neovascularization (MNV) typical neovascular age-related macular degeneration (nAMD). Clinical case series. Patients with PCV in either eye from clinical studies conducted in a tertiary retina center. Images with prespecified SS-OCTA imaging protocol were obtained and reconstructed in 3D. Forty neovascularization lesions (30 PCV and 10 typical nAMD) based on SS-OCTA were analyzed. The following 3 specific features were evaluated: (1) the pattern of flow signal within the PLs as either homogenous or showing internal vascular architecture; (2) the configuration of the BNN as hypermature, mature, or immature; and (3) the spatial arrangement of the PLs in relation to the BNN. Comparisons were made between PCV and typical nAMD. All PLs exhibited internal vascular architecture in the form of coil-like loops and none exhibited homogenous flow. Small focal nodules were present within this internal vascular architecture in 70% of PLs. Branching neovascular networks exhibited a hypermature/mature configuration (100 vs. 50%, P < 0.01) and were associated with thicker choroid compared with typical nAMD type 1 MNV (238.7 ± 104.3 vs. 155.6 ± 49.2, P= 0.02). The BNN and PL were located at distinct anteroposterior planes in 81% of the eyes. We identified proliferating vasculature in both the PL and the BNN. Comparison of the configuration suggests that the BNN represents a more chronic and inactive lesion than the PL. Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Sonographic Findings of Vascular Signals for Retained Products of Conception in Women Following First-Trimester Termination of Pregnancy

ObjectivesTo evaluate the occurrence of retained products of conception (RPOC) after termination of pregnancy in the first trimester and to assess the vascular signals with transvaginal ultrasonography (TVUS) examination in the detection of retained products. MethodsA retrospective cohort study was performed using TVUS examination in patients following termination of pregnancy. In cases of RPOC, 3 scales of vascular signal were identified: type 1, no or small amount, spot flow signals; type 2, medium amount, strip-like flow signals; type 3, rich amount, circumferential-like flow signals. The correlation between vascular signals and placenta accreta spectrum (PAS) staging was proposed by sonography and histopathology findings. ResultsThe 3 vascular patterns were differently distributed within non-RPOC as well as RPOC patients with and without PAS: type 1 vascular signal detection rates of non-RPOC and RPOC were 97.8% (262/268) and 28.1% (18/64), respectively. Of 64 cases of RPOC, 48.4% (31/64) of the patients had type 2 vascular signals. Vascular signals were enhanced in RPOC with PAS patients whose diagnosis was confirmed by histopathology. ConclusionsThe vascularity (amount of flow), vascular pattern (spot, strip- or circumferential-like flow), and the flow penetrating myometrium were significant findings for distinguishing concomitant RPOC with and without PAS. Additionally, RPOC may contribute to PAS progression, or PAS and RPOC in coordination strengthen the observed vascular signals.

Endothelial cells differentially sense laminar and disturbed flows by altering the lipid order of their plasma and mitochondrial membranes.

Endothelial cells (ECs) experience two different blood flow patterns: laminar and disturbed flow. Their responses to laminar flow contribute to vascular homeostasis, whereas their responses to disturbed flow result in EC dysfunction and vascular diseases. However, it remains unclear how ECs differentially sense laminar and disturbed flow and trigger signaling that elicits different responses. Here, we showed that ECs differentially sense laminar and disturbed flows by altering the lipid order of their plasma and mitochondrial membranes in opposite directions. This results in distinct changes in mitochondrial function, namely, increased adenosine triphosphate (ATP) production for laminar flow and increased hydrogen peroxide (H2O2) release for disturbed flow, leading to ATP- and H2O2-mediated signaling, respectively. When cultured human aortic ECs were subjected to laminar or disturbed flow in flow-loading devices, the lipid order of their plasma membranes immediately decreased in response to laminar flow and increased in response to disturbed flow. Laminar flow also decreased the lipid order of mitochondrial membranes and increased mitochondrial ATP production. In contrast, disturbed flow increased the lipid order of mitochondrial membranes and increased the release of H2O2 from the mitochondria. The addition of cholesterol to the cells increased the lipid order of both membranes and abrogated laminar flow-induced ATP production, while treatment of the cells with a cholesterol-depleting reagent, methyl-β cyclodextrin, decreased the lipid order of both membranes and abolished disturbed flow-induced H2O2 release, indicating that changes in the membrane lipid order and/or cholesterol content are closely linked to flow-induced changes in mitochondrial functions.NEW & NOTEWORTHY How vascular endothelial cells (ECs) differentially sense laminar and disturbed flows and trigger intracellular signaling remains unclear. Here, we show that EC plasma membranes act as mechanosensors to discriminate between laminar and disturbed flows by undergoing opposite changes in their lipid order. Similar lipid order changes occur simultaneously in the mitochondrial membranes, which are linked to changes in mitochondrial function, that is, increased ATP production for laminar flow and increased H2O2 release for disturbed flow.

A theory to model pseudo steady state water production and predict long-term water recovery from fractured reservoirs

The environmental and economic impact of hydraulic fracturing technology in the energy industry remains a growing concern due to large water consumption and poor water recovery in return. In this study, we propose a novel theory to describe and model the drive mechanisms (fracture closure and fluid expansion) responsible for long-term water recovery from hydraulically fractured reservoirs. In the literature, pseudo steady state (PSS) flow of water has been explained and modelled under the assumption of negligible fluid influx from matrix, referred to as "supercharge conditions". The preliminary flowback data analysis of 8 different unconventional reservoirs from North America in this study shows 1) water PSS flow signature is also observed after fluid breakthrough into fractures, and 2) it can be modelled mathematically, verified with long-term field data, and validated with numerical simulation results. These observations suggest that oil and water develop different networks or flow paths through fractures. With time, oil network expands and water network shrinks. Therefore, water continues to be produced from the fractures as oil saturation increases in the fractures with expansion of oil network due to fracture pressure decline. Based on this theory, an integrated semi-analytical workflow is developed by accounting for the changes in the volumes and compressibilities of both fracture and fluid. The workflow was applied on early production data (150–200 days) from six multi-fractured horizontal wells in Eagle Ford. The results show that the workflow can use the early-time data to accurately estimate long-term water recovery (325–475 days) from fractured reservoirs (within 6 % of measured field data). However, frequent long shut-ins during the course of long-term production increases the uncertainty in water recovery prediction.

Noise reduction and characteristic analysis of fluid signal in the jet impact‐negative pressure deamination reactor based on wavelet transform

AbstractThe jet impact‐negative pressure deamination reactor (JI‐NPDR) is a new type of continuous and efficient deamination equipment. The study of the random flow pattern of porous jet impingement in the reactor under negative pressure conditions is an important issue. In this work, the signal processing method based on wavelet transform is used to analyze the characteristics of random flow signals in the reactor. Meanwhile, an analog similar signal is built and three sets of Gaussian white noise with various signal‐to‐noise ratios are employed via the MATLAB platform. Based on the adjustment of threshold function, threshold, decomposition level and other parameters of wavelet transform, the noise ratio (SNR) and mean squared error (MSE) are used to evaluate the wavelet denoising effect. And then, the optimal denoising scheme for the obtained signal will be applied in processing the vacuum flow signal collected inside the deamination reactor. Subsequently, the 8‐layer wavelet decomposition is investigated by using sym7 as the wavelet basis, soft threshold function, and heursure threshold for signal denoising. Then, the analog signal is fed back through the results of the actual signal denoising, and the number of wavelet decomposition layers is adjusted from 8 to 9 layers to optimize the original wavelet denoising combination. By analyzing the low‐frequency and high‐frequency parts of the signal spectrum before and after denoising, it was found that wavelet transform can effectively denoise the fluid signal in the reactor.

-Memory Computing Based Reliable and High Speed Schmitt trigger 10T SRAM cell design

Static random access memories (SRAM) are useful building blocks in various applications, including cache memories, integrated data storage systems, and microprocessors. The von Neumann bottleneck difficulties are solved by in-memory computing. It eliminates unnecessary frequent data transfer between memory and processing units simultaneously. In this research, the replica-based 10T SRAM design for in-memory computing (IMC) is designed by adapting the word line control scheme in 14nm CMOS technology. In order to achieve high reading and writing capability, the Schmitt trigger inverter was used for energy-saving and stable use. To speed up the writing process of the design, a single transistor is inserted between the cross-coupled inverters. In addition, to increase the node capacity, the voltage boosting circuitry is emphasized. The adaptive word line control scheme was utilized by integrating the replica column based circuit. The Replica approach regulates signal flow through the core by using a dummy column and a dummy row in RAM. To demonstrate the viability of the suggested design, the simulated outcomes are contrasted with those of existing designs. The various performance metrics examined are Read Static Noise Margin (RSNM), Write (WSNM), Hold (HSNM), Read Access Delay (RAD), Write Access Delay (WAD), Read performance and Write performance the varying supply voltage is evaluated.

Imaging Features of Alveolar Soft Part Sarcoma: Single Institution Experience and Literature Review.

Alveolar soft part sarcoma (ASPS) is an extremely rare and aggressive soft-tissue sarcoma (STS) subtype with poor prognosis and limited response to radiation therapy and chemotherapy. Prompt recognition and referral to sarcoma centers for appropriate management are crucial for patients' survival. The purpose of this study was to report ASPS pre-treatment imaging features and to examine the existing literature on this topic. Twelve patients (7 women, 5 men-mean age 27.1 ± 10.7 years) were included from our single-center experience. Ultrasonography (US), computed tomography (CT), and magnetic resonance imaging (MRI) available were reviewed according to an analysis grid incorporating features from the latest research on STS. Clinical, histological, and outcome data were collected. MRI was available in 10 patients (83.3%), US in 7 patients (58.3%), and CT in 3 patients (25%). Mean longest tumor diameter was 7.6 ± 2.9 cm, and all tumors were deeply seated. Large peritumoral feeding vessels were systematically found and identified on ultrasonography (7/7), MRI (10/10), and CT (3/3). US revealed a well-defined heterogeneous hypoechoic pattern, with abundant flow signals in all patients (7/7). In all patients, MRI showed mildly high signal intensity (SI) on T1-WI and high SI on T2-WI and peritumoral edema. Moreover, flow-voids (due to arteriosus high-flow) into the peritumoral/intratumoral feeding vessels were detected in the MRI fluid-sensitive sequences of all patients. At baseline, whole-body contrast-enhanced CT revealed metastases in 8/12 (66.7%) patients. A pre-treatment longest diameter > 5 cm was significantly associated with distant metastases at diagnosis (p = 0.01). A maximum diameter > 5 cm represents a risk of metastatic disease at diagnosis (odds ratio = 45.0000 (95% CI: 1.4908-1358.3585), p = 0.0285). In the comprehensive literature review, we found 14 articles (case series or original research) focusing on ASPS imaging, with a total of 151 patients included. Merging our experience with the data from the existing literature, we conclude that the hallmark of ASPS imaging at presentation are the following characteristics: deep location, a slight hyperintense MRI SI on T1-WI and a hyperintense SI on T2-WI, numerous MRI flow voids, high internal vascularization, and large peritumoral feeding vessels.

Pipelined Memristive neural network analog-to-digital converter

This paper designs a pipelined memristive neural network ADCs. Cascade the sub stages of memristive neural network ADC with pipeline structure to improve the conversion accuracy of memristive neural network ADC. First, the signal flow of the pipeline architecture is optimized, and the compatibility between the 4 bit memristive neural network ADC and the pipeline architecture is solved. Secondly, the application of random disturbance circuits in pipeline architecture was analyzed. Combining the calibration circuit with the pipeline DAC to reduce the power consumption of the calibration circuit. Finally, the circuit model of memristive neural network ADC is built and compared with the existing memristive neural network ADC. The results indicate that the pipeline structure ADC designed in this chapter has the advantage of adaptive calibration in terms of calibration function.

Evaluation of testicular blood flow during testicular torsion surgery in children using the indocyanine green-guided near-infrared fluorescence imaging technique.

This study investigates the feasibility of the indocyanine green-guided near-infrared fluorescence (ICG-NIRF) imaging technique in evaluating testicular blood flow during testicular torsion (TT) surgery in pediatric cases. We retrospectively analyzed the eight pediatric patients with TT who underwent surgery in our hospital between February and July 2023. The intraoperative two-step method of ICG-NIRF imaging and testicular incision was used to evaluate the testicular blood flow, followed by a selection of different surgical methods. The removed testes were pathologically examined after surgery, and all patients were followed up 1 month after surgery to evaluate testicular blood flow using gray-scale ultrasound and color Doppler flow imaging (CDFI). Eight pediatric TT patients aged 1-16 years, with a median age of 11.5 years, were enrolled. Time from the onset ranged from 4 to 72 h (mean 26.13 ± 25.09 h). A total of eight testes were twisted, including four on the left side and four on the right side. The twisting direction of the testes was clockwise in four cases and counterclockwise in four cases. The rotation of torsion was 180°-1,080° (mean 472.5° ± 396°). There was no statistically significant difference in the imaging time between the four patients with testicular blood vessel imaging on both the torsional and normal sides (P > 0.05). The postoperative recovery was uneventful, with no complications during the follow-up period of 1 month. The postoperative histopathological results of three patients who underwent orchiectomy showed extensive hemorrhage, degeneration, and necrosis of the testicular tissue. Among the five patients who underwent orchiopexy, a gray-scale ultrasound and CDFI examinations showed uniform internal echo of the testes and normal blood flow signals in four patients. One patient with no testicular blood vessel imaging on the torsional side showed uneven internal echo of the testis and no blood flow signals. ICG-NIRF imaging is a feasible method to evaluate testicular blood flow during TT surgery. Testicular blood vessel imaging within 5 minutes after ICG injection might be the basis for testicular retention during TT surgery.

Value of micro-flow imaging and high-definition micro-flow imaging in differentiating malignant and benign breast lesions

To evaluate the value of non-contrast micro-flow imaging (MFI) and high-definition micro-flow imaging (HD-MFI) in differentiating malignant and benign breast lesions. One hundred and thirty-three patients with 138 breast lesions (80 benign and 58 malignant lesions) were examined using colour Doppler flow imaging (CDFI), MFI, and HD-MFI before biopsy, with blood flow signals graded into four types (grade 0, 1, 2, and 3) and penetrating vessels evaluated. The micro-vascular patterns of MFI and HD-MFI were evaluated and classified into five patterns: avascular, line-like, tree-like, root hair-like, and crab claw-like pattern. The diagnostic efficiency of micro-vascular patterns was analysed. Moreover, ultrasound Breast Imaging Reporting and Data System (BI-RADS) 4A lesions were also re-assessed according to the micro-vascular patterns of MFI or HD-MFI. The capability of detecting blood flow and penetrating vessels from high to low was HD-MFI, MFI, and CDFI, respectively (p<0.05). Rich blood flow signals, penetrating vessels, and root hair-like or crab claw-like pattern were more likely in malignant breast lesions, while few blood flow signals, tree-like pattern were mostly in benign lesions (p<0.05). The diagnostic efficiency of HD-MFI and MFI were higher than CDFI (p>0.05). MFI could reduce unnecessary biopsy of 52 US BI-RADS 4A lesions but with two malignancies missed, while 56 ultrasound BI-RADS 4A lesions could be downgraded by HD-MFI with none malignancies missed. MFI and HD-MFI can detect more blood flow in breast lesions than CDFI, and could help distinguish benign and malignant breast lesions. HD-MFI could reduce the unnecessary biopsy of US BI-RADS 4A lesions without missed malignancy.

Heterogeneous Traffic Flow Signal Control and CAV Trajectory Optimization Based on Pre-Signal Lights and Dedicated CAV Lanes

This paper proposes a control system to address the efficiency and pollutant emissions of heterogeneous traffic flow composed of human-operated vehicles (HVs) and connected and automated vehicles (CAVs). Based on the comprehensive collection of information on the flow of heterogeneous traffic, the control system uses a two-layer optimization model for signal duration calculation and CAV trajectory planning. The upper model optimizes the phase duration in real time based on the actual total number and type of vehicles entering the control adjustment zone, while the lower model optimizes CAV lane-changing strategies and vehicle acceleration optimization curves based on the phase duration optimized by the upper model. The target function accounts for reducing fuel usage, carbon emission lane-changing costs, and vehicle travel delays. Based on the Webster optimal cycle formula, an improved cuckoo algorithm with strong search performance is created to solve the model. The numerical data confirmed the benefits of the suggested signal control and CAV trajectory optimization method based on pre-signal lights and dedicated CAV lanes for heterogeneous traffic flow. Intersection capacity was significantly enhanced, CAV average fuel consumption, carbon emission and lane-changing frequency were significantly reduced, and traffic flow speed and delay were significantly improved.

Imaging diagnosis and evaluation of radiation-induced intestinal injury

Radiation-induced intestinal injury significantly impacts the quality of life and even prognosis of patients. Timely diagnosis and accurate assessment are crucial in clinical practice. Imaging examinations play a vital role in the diagnosis and evaluation of radiation-induced intestinal injury. CT offers fast scanning speed and wide coverage but has limited soft tissue resolution. On the other hand, MRI offers superior soft tissue resolution, along with the capability for multi-sequence and multi-parameter imaging, and the ability to assess the effect of tumor treatment. However, its scanning range is restricted. Endorectal ultrasound enables observation of rectal wall thickness, submucosal blood flow signals, and the development of micro-ulcers and fistulas. The key imaging features of radiation-induced intestinal injury include intestinal wall thickening, layered enhancement on contrast-enhanced scans, fistula formation, and abscess formation, and so on. Previous studies have established correlations between certain imaging features and the severity as well as prognosis of the disease. Nonetheless, these imaging features lack specificity, and require differentiation from tumors, ischemic changes, and other intestinal inflammatory lesions, considering the patient's radiotherapy history in conjunction with the imaging findings.

Radix-22 Algorithm for the Odd New Mersenne Number Transform (ONMNT)

This paper introduces a new derivation of the radix-22 fast algorithm for the forward odd new Mersenne number transform (ONMNT) and the inverse odd new Mersenne number transform (IONMNT). This involves introducing new equations and functions in finite fields, bringing particular challenges unlike those in other fields. The radix-22 algorithm combines the benefits of the reduced number of operations of the radix-4 algorithm and the simple butterfly structure of the radix-2 algorithm, making it suitable for various applications such as lightweight ciphers, authenticated encryption, hash functions, signal processing, and convolution calculations. The multidimensional linear index mapping technique is the conventional method used to derive the radix-22 algorithm. However, this method does not provide clear insights into the underlying structure and flexibility of the radix-22 approach. This paper addresses this limitation and proposes a derivation based on bit-unscrambling techniques, which reverse the ordering of the output sequence, resulting in efficient calculations with fewer operations. Butterfly and signal flow diagrams are also presented to illustrate the structure of the fast algorithm for both ONMNT and IONMNT. The proposed method should pave the way for efficient and flexible implementation of ONMNT and IONMNT in applications such as lightweight ciphers and signal processing. The algorithm has been implemented in C and is validated with an example.

State evaluation method for complex task network models

This paper focuses on the assessment of non-complete states in complex task networks and establishes an online capability boundary assessment model based on real-time feature parameters. By utilizing multivariate heterogeneous state features for data mining and pattern recognition, we delve into virtual sample generation technology using an overall diffusion trend approach. This starts by examining the validity of sample data and analyzing the relevance of data acquired within the feature space. Building on this foundation, the overall diffusion trend method is applied to generate virtual sample input that aligns with the sampling distribution characteristics of avionics system equipment. To address non-complete state evaluation in complex task networks, we design a comprehensive model. This model involves constructing a system signal flow block diagram and a structural diagram depicting the available capacity of subsystems and the overall system tasks. The establishment of unknown function relationships in signal connections is achieved through a fusion of neural network and fuzzy logic systems. Finally, an intelligent optimization algorithm is employed to determine system parameters. Utilizing this neuro-fuzzy system in simulation, we attain real-time system responses and evaluate the output regarding the available capacity of system tasks.