Feedback Network Research Articles

SFF-Siam: A New Oracle Bone Rejoining Method Based on Siamese Network.

The rejoining of oracle bone rubbings is a fundamental topic in oracle bone inscriptions (OBIs) research. However, the traditional oracle bone (OB) rejoining methods are not only time-consuming and laborious but difficult to apply to large-scale OB rejoining. We proposed a simple OB rejoining model (SFF-Siam) to handle this challenge. First, the similarity feature fusion module (SFF) is designed to combine two inputs and make them relate to each other, then a backbone feature extraction network is used to evaluate the similarity between inputs, and the forward feedback network (FFN) outputs the probability that two OB fragments can be rejoined. Extensive experiments demonstrate that the SFF-Siam achieved a good effect in OB rejoining. The average accuracy of the SFF-Siam network reached 96.4 % and 90.1 % in our benchmark datasets, respectively. It provides valuable data for promoting the use of OBIs in conjunction with AI technology.

Gaseous signaling molecule H2S as a multitasking signal molecule in ROS metabolism of Oryza sativa under thiocyanate (SCN−) pollution

The induction of disruption in the electronic transport chain by thiocyanate (SCN−) leads to an excessive generation of reactive oxygen species (ROS) within rice (Oryza sativa). Hydrogen sulfide (H2S) assumes a crucial role as a gaseous signaling molecule, holding significant potential in alleviating SCN−-related stress. Nevertheless, there remains a dearth of understanding regarding the intricate interplay between H2S and ROS in Oryza sativa amidst SCN− pollution. In this investigation, a hydroponics-based experiment was meticulously devised to explore how H2S-mediated modifications influence the genetic feedback network governing ROS metabolism within the subcellular organelles of Oryza sativa when exposed to varying effective concentrations (EC20: 24 mg SCN/L; EC50: 96 mg SCN/L; EC75: 300 mg SCN/L) of SCN−. The findings unveiled the enhanced capacity of Oryza sativa to uptake SCN− under H2S + SCN− treatments in comparison to SCN− treatments alone. Notably, the relative growth rate (RGR) of seedlings subjected to H2S + SCN− exhibited a superior performance when contrasted with seedlings exposed solely to SCN−. Furthermore, the application of exogenous H2S yielded a significant reduction in ROS levels within Oryza sativa tissues during SCN− exposure. To elucidate the intricacies of gene regulation governing ROS metabolism at the mRNA level, the 52 targeted genes were categorized into four distinct types, namely: initial regulatory ROS generation genes (ROS-I), direct ROS scavenging genes (ROS-II), indirect ROS scavenging genes (ROS-III), and lipid oxidation genes (ROS-IV). On the whole, exogenous H2S exhibited the capacity to activate the majority of ROS-I ∼ ROS-IV genes within both Oryza sativa tissues at the EC20 concentration of SCN−. However, genetic positive/negative feedback networks emphasized the pivotal role of ROS-II genes in governing ROS metabolism within Oryza sativa. Notably, these genes were predominantly activated within the cytoplasm, chloroplasts, mitochondria, peroxisomes, and the cell wall.

Construction of a Programmable Feedback Network with Continuously Activatable Molecular Beacon Fluorescence for One-Step Quantification of Long Noncoding RNAs in Clinical Breast Tissues.

Long noncoding RNAs (lncRNAs) are key regulators in numerous pathological and physiological processes, and their aberrant expression is implicated in many diseases. Herein, we develop a programmable feedback network with continuously activatable molecular beacon (MB) fluorescence for one-step quantification of mammalian-metastasis-associated lung adenocarcinoma transcript 1 (lncRNA MALAT1) in clinical breast tissues. We introduce a functional MB with three domains, including a substrate for lncRNA MALAT1 recognition, a template for strand displacement amplification (SDA), and a reporter for signal output with FAM fluorescence being quenched by BHQ1. When MALAT1 is present, it recognizes and unfolds the MB, leading to the recovery of FAM fluorescence. Once the MB is opened, multiple rounds of SDA reaction are automatically initiated by recruiting primer, KF DNA polymerase, and Nt.BbvCI nicking enzyme, inducing the opening of more MBs and the dissociation of more FAM/BHQ1 pairs. Consequently, a feedback network is constructed through multicycle cascade SDA, achieving the exponential accumulation of fluorescence signals for accurate quantification of MALAT1. In this assay, only two oligonucleotides (i.e., MB and primer) are involved for the establishment of a feedback amplification network, greatly simplifying the design of the reaction system. Moreover, this assay requires only one step to realize the isothermal exponential amplification for real-time monitoring of MALAT1 with attomolar sensitivity. This assay displays single-base mismatch selectivity with high anti-interference capability, and it can further quantify endogenous MALAT1 at the single-cell level and differentiate MALAT1 expression between breast cancer patient tissues and healthy person tissues.

Ghost-free multi-exposure high dynamic range imaging based on feedback network

Ghost-free multi-exposure high dynamic range imaging based on feedback network

Influence of cortical inhibition on auditory efferents in humans

Auditory activity in humans is influenced by feedback networks in the brain. The final leg of this pathway originates in the brainstem and plays an important role in protecting and aiding communication in competing noise. Previous studies have used auditory and/or visual attention tasks to manipulate cortical activity when exploring its influence on the periphery via the auditory efferent system. Using subjective attention does not control for variability across individuals in attentional state, alertness, and arousal. Hence, a consensus on the relationship between cortical activity and how it influences more caudal efferent reflexes is still needed. Here we describe the first assay to non-invasively influence the human auditory cortex activity using repetitive transcranial magnetic stimulation and measure its consequence on peripheral structures using otoacoustic emissions. We hypothesized that depressing brain activity temporarily affects auditory functioning. By instigating a virtual cortical lesion in normal hearing participants, we were able to characterize the influence that the auditory cortex has on the sensory cells in the cochlea, mediated via the medial olivocochlear reflex. Our results will open avenues for further research into new diagnostic and therapeutic approaches for hearing disorders.

An S-band MMIC LNA in GaAs 0.15-μm pHEMT

The study adopts a monolithic microwave integrated circuit (MMIC) low-noise amplifier (LNA) applied in S-band was designed using ADS simulation software, GaAs 0.15-um pseudomorphic high electron mobility transistor (pHEMT) process. The LNA small signal gain is greater than 30.8 dB, gain flatness is ±0.45 dB, noise coefficient is less than 1.5 dB, input and output return loss is greater than 10 dB, and the chip area is 1.2*2.4 mm2. The low noise amplifier is composed of a two-stage cascade structure. Gain flatness, gain control, and bandwidth broadening are improved by RLC negative feedback network. The minimum noise coefficient circle and maximum gain circle are narrowed by adding negative feedback to achieve better noise coefficient and gain.

A novel person re-identification network to address low-resolution problem in smart city context

We argue that accurate person re-identification is a vital problem for urban public monitoring systems in the smart city context. Since images captured from different cameras have arbitrary resolutions resulting in resolution mismatch, this work proposes a model that takes arbitrary images and converts them to a pre-defined fixed resolution. The model then passes the images to a super-resolution network, producing high-resolution images. We employ a feedback network to generate more realistic super-resolution images, which are fed to the re-identification network to acquire a unique descriptor to disclose the person’s identity. We outperformed in all measures against other state-of-the-art methods.

CSI Feedback Model Based on Multi-Source Characterization in FDD Systems.

In wireless communication, to fully utilize the spectrum and energy efficiency of the system, it is necessary to obtain the channel state information (CSI) of the link. However, in Frequency Division Duplexing (FDD) systems, CSI feedback wastes part of the spectrum resources. In order to save spectrum resources, the CSI needs to be compressed. However, many current deep-learning algorithms have complex structures and a large number of model parameters. When the computational and storage resources are limited, the large number of model parameters will decrease the accuracy of CSI feedback, which cannot meet the application requirements. In this paper, we propose a neural network-based CSI feedback model, Mix_Multi_TransNet, which considers both the spatial characteristics and temporal sequence of the channel, aiming to provide higher feedback accuracy while reducing the number of model parameters. Through experiments, it is found that Mix_Multi_TransNet achieves higher accuracy than the traditional CSI feedback network in both indoor and outdoor scenes. In the indoor scene, the NMSE gains of Mix_Multi_TransNet are 4.06 dB, 4.92 dB, 4.82 dB, and 6.47 dB for compression ratio η = 1/8, 1/16, 1/32, 1/64, respectively. In the outdoor scene, the NMSE gains of Mix_Multi_TransNet are 3.63 dB, 6.24 dB, 4.71 dB, 4.60 dB, and 2.93 dB for compression ratio η = 1/4, 1/8, 1/16, 1/32, 1/64, respectively.

Radiation-hardened-by-design preamplifier with binary weighted current source for radiation detector

This paper presents a radiation-hardened-by-design preamplifier that utilizes a self-compensation technique with a charge-sensitive amplifier (CSA) and replica for total ionizing dose (TID) effects. The CSA consists of an operational amplifier (OPAMP) with a 6-bit binary weighted current source (BWCS) and feedback network. The replica circuit is utilized to compensate for the TID effects of the CSA. Two comparators can detect the operating point of the replica OPAMP and generate appropriate signals to control the switches of the BWCS. The proposed preamplifier was fabricated using a general-purpose complementary metal-oxide-silicon field effect transistor 0.18 μm process and verified through a test up to 230 kGy (SiO2) at a rate of 10.46 kGy (SiO2)/h. The code of the BWCS control circuit varied with the total radiation dose. During the verification test, the initial value of the digital code was 39, and a final value of 30 was observed. Furthermore, the preamplifier output exhibited a maximum variation error of 2.39%, while the maximum rise-time error was 1.96%. A minimum signal-to-noise ratio of 49.64 dB was measured.

A social media analytics-based approach to customer-centric reverse logistics management of electronic devices: A case study on notebooks

With the advancement of technology, the rate of replacement of unused electronic devices by consumers has increased. Throwing away these devices wastes the scarce natural resources used in their production and also has harmful effects on the environment. Using the concept of reverse logistics leads to the reduction of waste of electronic products such as laptops and the reuse of their parts. To implement the reverse logistics process in the production process, companies need to know which parts of their products have problems or breakdowns when used by consumers so that they can make the right decision about reusing, repairing or recycling the returned product parts. In this paper, the most effective decision-making strategies in reverse logistics based on consumer feedback are discussed. The result of using this model presented in this research is reducing costs and increasing producer productivity, which will ultimately lead to consumer satisfaction. This paper focuses on social media data to gather consumer feedback to optimize the decision-making process in reverse logistics through a data analytics approach. A case study is conducted on Twitter data regarding consumer opinions about MacBook Pro and MacBook Air. By using DEMATEL and network analysis techniques, factors affecting the improvement of the quality of MacBooks have been prioritized. The results showed that the proposed approach can help manufacturers by (a) finding effective features on consumers' behaviour and attitudes through their feedback in social networks, (b) identifying how factors influence each other (c) prioritizing factors, to establish the reverse logistics process which leads to increase consumer satisfaction and improve their performance.

Design, Implementation, and Characterization of a Compact Lock-in Add-on for Low-Frequency Impedance Measurements

Impedance measurements are crucial in a variety of applications, from the characterization of lithium batteries, microbial fuel cells, and biosensors to the study of polymers and material degradation, where strict requirements have to be met in terms of frequency bandwidth and current level. Here, we present a cost-effective compact solution for ultra-low-frequency impedance measurements, operating in a wide range, from 1 mHz to 250 kHz. Coupled to a lock-in amplifier, the designed circuit is based on a Howland current pump cascaded by a precision current divider in order to set the conversion factor at 100 nA/V, 1 μA/V, or 100 μA/V. Therefore, it is possible to generate very low-current signals to measure resistive impedances up to 100 MΩ. In addition, a feedback network is inserted to null the voltage drift induced by leakage currents and offset voltages, thus allowing the measurement of low-capacitance loads, experimentally tested down to 10 nF. Remarkably, the feedback network allows to perform measurements also in the presence of high voltage bias of the load and experimental results performed up to 60 V demonstrate the excellent stability of the designed system, thus a high voltage compliance. The proposed circuit is particularly interesting for the conditioning of both resistive and capacitive sensors and it is likely to be an effective solution for the implementation of a portable instrument for measuring signals from biosensors.

Auditory brainstem mechanisms likely compensate for self-imposed peripheral inhibition

Feedback networks in the brain regulate downstream auditory function as peripheral as the cochlea. However, the upstream neural consequences of this peripheral regulation are less understood. For instance, the medial olivocochlear reflex (MOCR) in the brainstem causes putative attenuation of responses generated in the cochlea and cortex, but those generated in the brainstem are perplexingly unaffected. Based on known neural circuitry, we hypothesized that the inhibition of peripheral input is compensated for by positive feedback in the brainstem over time. We predicted that the inhibition could be captured at the brainstem with shorter (1.5 s) than previously employed long duration (240 s) stimuli where this inhibition is likely compensated for. Results from 16 normal-hearing human listeners support our hypothesis in that when the MOCR is activated, there is a robust reduction of responses generated at the periphery, brainstem, and cortex for short-duration stimuli. Such inhibition at the brainstem, however, diminishes for long-duration stimuli suggesting some compensatory mechanisms at play. Our findings provide a novel non-invasive window into potential gain compensation mechanisms in the brainstem that may have implications for auditory disorders such as tinnitus. Our methodology will be useful in the evaluation of efferent function in individuals with hearing loss.

Abstract P2106: Transforming Growth Factor β-dependent Regulation Of Cardiomyocyte Maturation

Transforming growth factor β (TGFβ) is a secreted growth factor that is sequestered to the ECM as a latent complex and released in response to cardiac stress. Once released, TGFβ is required for conversion of quiescent fibroblasts to myofibroblasts that support cardiac repair and fibrosis through production of ECM components. While these functional features of TGFβ are well known, the fibroblast-independent effector functions of TGFβ in the heart are unknown. We hypothesized that TGFβ is a critical ECM-cell cross talk mediator in the heart whereby cardiomyocyte -generated TGFβ communicates with fibroblasts to program the composition and stability of the ECM in a reinforcing feedback network. We found that deletion of TGFβ ligands ( Tgfb1 , Tgfb2 , and Tgfb3 ) from cardiomyocytes with an α-MHC-Cre transgene ( Tgfb123 fl/fl -αMHC-Cre ), but not a fibroblast-specific targeted allele ( Tgfb123 fl/fl -Tcf21-MCM ), results in cardiac dysfunction. These results suggest that cardiomyocytes (CMs) are the predominant source of TGFβ in the heart at baseline and that perhaps celltypes beyond the fibroblast were also involved. Interestingly, fibroblast numbers and ECM deposition are increased in Tgfb123 fl/fl -αMHC-Cre hearts and with acute injury hearts from these mice produce shorter, disorganized collagen fibers. Gene expression profiling of Tgfb123 fl/fl -αMHC-Cre hearts at 6 weeks of age demonstrates defective cardiomyocyte maturation. Indeed, Tgfb123 fl/fl -αMHC-Cre hearts are dysmorphic at neonatal day 1 and cardiomyocytes from these hearts remain in cell cycle for a longer duration with greater levels of mononucleation. However, deleting TGFβ receptors I/II or Smad2/3 from CMs does not recapitulate this phenotype suggesting that TGFβ is not driving CM maturation in an autocrine manner. Instead, these findings indicate that TGFβ functions as a critical cross-talk mediator to fibroblasts to establish proper ECM organization and content that drives CM maturation.

Dynamic Output Feedback and Neural Network Control of a Non-Holonomic Mobile Robot.

This paper presents the design and synthesis of a dynamic output feedback neural network controller for a non-holonomic mobile robot. First, the dynamic model of a non-holonomic mobile robot is presented, in which these constraints are considered for the mathematical derivation of a feasible representation of this kind of robot. Then, two control strategies are provided based on kinematic control for this kind of robot. The first control strategy is based on driftless control; this means that considering that the velocity vector of the mobile robot is orthogonal to its restriction, a dynamic output feedback and neural network controller is designed so that the control action would be zero only when the velocity of the mobile robot is zero. The Lyapunov stability theorem is implemented in order to find a suitable control law. Then, another control strategy is designed for trajectory-tracking purposes, in which similar to the driftless controller, a kinematic control scheme is provided that is suitable to implement in more sophisticated hardware. In both control strategies, a dynamic control law is provided along with a feedforward neural network controller, so in this way, by the Lyapunov theory, the stability and convergence to the origin of the mobile robot position coordinates are ensured. Finally, two numerical experiments are presented in order to validate the theoretical results synthesized in this research study. Discussions and conclusions are provided in order to analyze the results found in this research study.

A Reconfigurable Tri-Mode Frequency-Locked Loop Readout Circuit for Biosensor Interfaces.

In this article, a frequency-locked loop (FLL) based multimodal readout integrated circuit (IC) for interfacing with off-chip temperature, electrochemical, and pH sensors is presented. By reconfiguring its switched-capacitor feedback network, the readout circuit is able to measure resistance, current, and voltage without additional active analog front-end circuits. A prototype IC was fabricated in a 0.18 μm CMOS process. Measured results show that when measuring resistance, the input-referred resistance resolution is 10.5 Ω for 100 Hz integration bandwidth. Using an off-chip thermistor, the readout circuit covers a temperature range of 0-75 °C and achieves an equivalent temperature resolution of 16.4 mKrms. In current mode, the readout circuit has an input range of 0.5μA and an input-referred current noise as low as 40.6 pArms for 100 Hz bandwidth. Interfacing with an on-chip potentiostat, glucose chronoamperometry is demonstrated. In voltage mode, a minimum input-referred voltage noise of 31.7 μVrms is achieved, and the IC can measure a pH range from 1.6 to 12 using a commercial pH probe. At a 1.2 V supply, power consumption of the readout circuit is below 10 μW for all three measurement modes. Additionally, the prototype IC includes an integrated wireless transmitter that implements on-off keying modulation, and a wireless multimodal sensing system utilizing the FLL-based readout circuit is demonstrated.

Distributed Leadership Promotes Teacher Self-Efficacy in Multicultural Classrooms Through School Capacity Building: A Multilevel SEM Approach Using U.S. Teaching and Learning International Survey

Purpose : This study examines the direct and indirect effects of distributed leadership on teacher self-efficacy in multicultural classrooms (TSMC) through school capacity building, specifically teacher team innovativeness and a feedback network. Research Design : Using data from the Teaching and Learning International Survey 2018, this study employs a 2-2-1 multilevel structural equation modeling to account for the nested data structure (teachers nested within schools). Latent variables are constructed, and their validity is tested, followed by an analysis of the relationships among distributed leadership, teacher team innovativeness, a feedback network, and TSMC. Findings: This study finds that distributed leadership has an indirect-only mediation effect on TSMC via a feedback network but not via teacher team innovativeness. The effect of distributed leadership on TSMC is fully mediated by a feedback network. In addition, the study shows that distributed leadership is positively associated with a feedback network and teacher team innovativeness. Conclusions : This study contributes to our understanding of the role of distributed leadership in fostering school capacity building and promoting TSMC. Given the increasing diversity in schools, it is crucial for school leaders to prepare teachers to teach students in multicultural classrooms. The findings suggest that school leaders can enhance teachers’ efficacy in teaching students from diverse backgrounds by facilitating their participation in school improvement processes and establishing a collective feedback network where teachers receive feedback from various sources. These results emphasize the importance of distributed leadership in equipping teachers for culturally responsive teaching in multicultural classrooms.

Best practice guidance for antibiotic audit and feedback interventions in primary care: a modified Delphi study from the Joint Programming Initiative on Antimicrobial resistance: Primary Care Antibiotic Audit and Feedback Network (JPIAMR-PAAN)

BackgroundPrimary care is a critical partner for antimicrobial stewardship efforts given its high human antibiotic usage. Peer comparison audit and feedback (A&F) is often used to reduce inappropriate antibiotic prescribing. The design and implementation of A&F may impact its effectiveness. There are no best practice guidelines for peer comparison A&F in antibiotic prescribing in primary care.ObjectiveTo develop best practice guidelines for peer comparison A&F for antibiotic prescribing in primary care in high income countries by leveraging international expertise via the Joint Programming Initiative on Antimicrobial Resistance—Primary Care Antibiotic Audit and Feedback Network.MethodsWe used a modified Delphi process to achieve convergence of expert opinions on best practice statements for peer comparison A&F based on existing evidence and theory. Three rounds were performed, each with online surveys and virtual meetings to enable discussion and rating of each best practice statement. A five-point Likert scale was used to rate consensus with a median threshold score of 4 to indicate a consensus statement.ResultsThe final set of guidelines include 13 best practice statements in four categories: general considerations (n = 3), selecting feedback recipients (n = 1), data and indicator selection (n = 4), and feedback delivery (n = 5).ConclusionWe report an expert-derived best practice recommendations for designing and evaluating peer comparison A&F for antibiotic prescribing in primary care. These 13 statements can be used by A&F designers to optimize the impact of their quality improvement interventions, and improve antibiotic prescribing in primary care.

Wideband SiGe-HBT Low-Noise Amplifier with Resistive Feedback and Shunt Peaking.

In this work, the design of a wideband low-noise amplifier (LNA) using a resistive feedback network is proposed for potential multi-band sensing, communication, and radar applications. For achieving wide operational bandwidth and flat in-band characteristics simultaneously, the proposed LNA employs a variety of circuit design techniques, including a voltage-current (shunt-shunt) negative feedback configuration, inductive emitter degeneration, a main branch with an added cascode stage, and the shunt-peaking technique. The use of a feedback network and emitter degeneration provides broadened transfer characteristics for multi-octave coverage and a real impedance for input matching, respectively. In addition, the cascode stage pushes the band-limiting low-frequency pole, due to the Miller capacitance, to a higher frequency. Lastly, the shunt-peaking approach is optimized for the compensation of a gain reduction at higher frequency bands. The wideband LNA proposed in this study is fabricated using a commercial 0.13 μm silicon-germanium (SiGe) BiCMOS process, employing SiGe heterojunction bipolar transistors (HBTs) as the circuit's core active elements in the main branch. The measurement results show an operational bandwidth of 2.0-29.2 GHz, a noise figure of 4.16 dB (below 26.5 GHz, which was the measurement limit), and a total power consumption of 23.1 mW under a supply voltage of 3.3 V. Regarding the nonlinearity associated with large-signal behavior, the proposed LNA exhibits an input 1-dB compression (IP1dB) point of -5.42 dBm at 12 GHz. These performance numbers confirm the strong viability of the proposed approach in comparison with other state-of-the-art designs.

Multi-Scale Feature Residual Feedback Network for Super-Resolution Reconstruction of the Vertical Structure of the Radar Echo

The vertical structure of radar echo is crucial for understanding complex microphysical processes of clouds and precipitation, and for providing essential data support for the study of low-level wind shear and turbulence formation, evolution, and dissipation. Therefore, finding methods to improve the vertical data resolution of the existing radar network is crucial. Existing algorithms for improving image resolution usually focus on increasing the width and height of images. However, improving the vertical data resolution of weather radar requires a focus on improving the elevation angle resolution while maintaining distance resolution. To address this challenge, we propose a network for super-resolution reconstruction of weather radar echo vertical structures. The network is based on a multi-scale residual feedback network (MR-FBN) and uses new multi-scale feature residual blocks (MSRB) to effectively extract and utilize data features at different scales. The feedback network gradually generates the final high-resolution vertical structure data. In addition, we propose an elevation upsampling layer (EUL) specifically for this task, replacing the traditional image subpixel convolution layer. Experimental results show that the proposed method can effectively improve the elevation angle resolution of weather radar echo vertical structure data, providing valuable help for atmospheric detection.

A millimeter‐wave broadband power amplifier with a tree‐like transistor structure using 0.15‐μm GaAs technology

AbstractIn this paper, a millimeter‐wave broadband high‐efficiency power amplifier (PA) for Ka‐band (26–32 GHz) using 0.15‐μm GaAs pseudomorphic high‐electron‐mobility transistor process is proposed. The PA utilizes a three‐stage cascade structure and adopts an RC series feedback network, which expands the bandwidth and ensures the circuit stability. To improve the output power and efficiency of the circuit, a tree‐like transistor structure is proposed. The power amplifier, it can provide 23.6 dBm output P1dB with 33.1% power‐added efficiency at 28 GHz with high linearity. The maximum small signal gain can reach 27 dB with 3‐dB bandwidth from 24 to 33 GHz for the measured results.