Deep learning-based optimal adaptive regulation pathway of algal blooms in urban rivers under long-term uncertainties.

Interoceptive sensibility mediates emotional dysregulation: Insights from individuals with Bipolar II Depression.

Secretory expression and fermentation optimization of recombinant porcine epidermal growth factor in Saccharomyces cerevisiae.

Mapping emotional feeling in the body: A tripartite framework for understanding the embodied mind.

As the semiconductor industry advances toward lower technology nodes, the adoption of multi-voltage designs within channel-based SoC architecture presents both significant opportunities and complex challenges, particularly in the context of stringent power optimization requirements. These designs inherently introduce complex issues related to voltage domain transitions, which are critical to managing signal integrity and timing closure. Transition phenomena between voltage domains represent a major concern, directly impacting the chip’s power, performance, and area (PPA) metrics. This paper provides an in-depth analysis of transition mechanisms in multi-voltage channel-based SoC designs, identifying root causes and quantifying their effects on timing and signal integrity. It further proposes robust, practical methodologies and design techniques to mitigate transition-related issues, ensuring these solutions integrate seamlessly without compromising design integrity or chip specifications. By systematically addressing the intricacies of multi-voltage transitions in channel-based SoCs, we deliver comprehensive and efficient strategies validated through real-world implementations.

Digital Video Broadcasting-Terrestrial second generation (DVB-T2) systems are increasingly deployed for high quality terrestrial broadcasting. However, low Signal-to-Noise Ratio (SNR) conditions in urban and fringe coverage areas pose significant challenges, resulting in elevated Bit Error Rates (BER) and degraded service reliability. Forward Error Correction (FEC) techniques, particularly Low-Density Parity-Check (LDPC) and Bose Chaudhuri Hocquenghem (BCH) codes, play a crucial role in mitigating transmission errors and ensuring robust communication. This study investigates a systematic approach to optimizing LDPC and BCH FEC schemes to enhance transmission reliability and minimize BER under low-SNR conditions in DVB-T2 networks. Using simulation-based analyses, the study evaluates multiple LDPC code rates (e.g., 1/2, 2/3, 3/4) in combination with BCH codeword lengths and error-correcting capabilities. Results indicate that an optimized LDPC (64800, 32400) configuration combined with a BCH (255, 239) code significantly reduces BER, achieving approximately 10⁻⁵ at an SNR of 2 dB, compared to a BER of 10⁻³ using standard DVB-T2 FEC configurations. Additionally, iterative decoding algorithms for LDPC were fine-tuned to balance convergence speed and error correction performance, demonstrating a 25% reduction in decoding iterations without compromising reliability. The analysis also explores trade-offs between redundancy, throughput and latency, highlighting the practical considerations for real-world deployment. The findings underscore that strategic optimization of LDPC/BCH FEC parameters is critical for maintaining broadcast quality in low-SNR scenarios. By enhancing error resilience and reducing BER, the proposed approach improves signal integrity, supports consistent reception in fringe areas and maximizes spectrum efficiency. This work provides a foundation for adaptive FEC strategies in future DVB T2 systems, enabling broadcasters to deliver reliable high-definition content even under challenging channel conditions.

The increasing demand for data-intensive artificial intelligence and machine learning applications has exposed the limitations of traditional Von Neumann architectures, especially in resource-constrained environments like Unmanned Aerial Vehicle (UAV) communication systems. This work introduces an advanced in-memory computing model leveraging an 8T SRAM-based architecture combined with a multi-logic sense amplifier to perform arithmetic operations directly within the memory array. By embedding processing into the memory, this approach significantly reduces data transfer overhead, resulting in lower latency and improved energy efficiency – key requirements for UAV systems. Additionally, a novel lightweight and energy-efficient signal processing method is proposed. This architecture enables real-time signal filtering, effectively minimizing noise and enhancing signal integrity while meeting the compactness and scalability demands of UAV systems. Simulation results demonstrate significant reductions in power consumption and latency across a range of arithmetic operations, with robust performance maintained under varying process, voltage, and temperature conditions. This transformative design offers a practical and efficient solution for next-generation aerial communication technologies, ensuring high-quality communication and efficient data processing in critical UAV applications.

Abstract In order to optimize the stability of integrated circuit interconnect, four graphene nanoribbon-carbon nanotube mixed structures (GCMS) are proposed in this work, viz. GCMS-1, GCMS-2, GCMS-3, and GCMS-4. The electrical modeling on the mixed structure is performed. The electrical parameters are extracted and the transfer function is derived with ABCD matrix. The Nyquist criterion is adopted for analyzing the stability, and the method to optimize stability is investigated. The signal integrity analysis is conducted and the impact of crosstalk on the stability is also studied. Research has found that the stability increases with extended length and elevated temperature. Reducing the thickness of graphene can effectively improve the stability. Reducing the diameter of multi-walled carbon nanotube can also increase the stability of GCMS-2, GCMS-3, and GCMS-4 interconnects. Reducing the diameter of single-walled carbon nanotube can increase the stability of GCMS-1 interconnect, while increasing that can increase the stability of GCMS-3 and GMCS-4 interconnects. The mixed structures surpass graphene nanoribbon in stability and outperform single-walled carbon nanotube bundle in eye diagram quality, integrating the advantages of these two materials. The odd mode crosstalk can improve the stability, and the mixed structures are less affected by crosstalk than carbon nanotube and graphene nanoribbon.

BackgroundWhile amyloid correlates with white matter hyperintensities, tau distinctly impacts white matter microstructure through axonal injury from its prion‐like spread. Tau accumulation and white matter microstructural decline begin prior to clinical symptom onset, emphasizing their pivotal role in AD manifestation. Autosomal dominant AD (ADAD) has a relatively uniform phenotype that can be leveraged to investigate the preclinical relationship between tau accumulation and white matter microstructural health. Those with ADAD exhibit early pathology with few age‐related comorbidities, and the high penetrance of ADAD mutations enables precise disease staging relative to expected symptom onset.MethodUsing data from the Dominantly Inherited Alzheimer Network, we characterized white matter integrity in ADAD mutation‐carriers and non‐carrier siblings using fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity. Tract‐based spatial statistics summarized these metrics across the brain, and we evaluated the emergence of abnormality relative to disease stage. Probabilistic tractography was conducted and summary white matter indices were extracted from the cingulum bundle and uncinate fasciculus, tracts connected to hubs of tau accumulation.ResultWhole‐brain analyses indicated that symptomatic mutation‐carriers have significantly different white matter microstructure compared to asymptomatic mutation‐carriers and non‐carriers. In mutation‐carriers, these abnormalities emerged concurrently with progression in symptomatic status. In contrast, our tract‐of‐interest analyses observed differences in white matter microstructure for all mutation‐carriers compared to non‐carriers. These changes within the cingulum bundle and uncinate fasciculus were determined to emerge five years prior to expected year of symptom onset.ConclusionWhile global white matter differences are detected between mutation‐carriers and non‐carriers close to symptom onset, tracts that are adjacent to regions of significant tau accumulation show microstructural abnormality much earlier. This confirms that ADAD white matter decline does not occur uniformly across the brain, and may suggest a spatial correlation with tau. The timing of tract‐specific decline may also support that white matter damage occurs downstream of tau accumulation and spread. Given that white matter is critically important for transduction and integration of signals across disparate brain regions, the continued characterization of tau and white matter progression may provide important insight into the mechanism through which tau drives cognitive symptom onset in ADAD.

Head direction (HD) signals function as the brain’s internal compass. They are organized as an attractor and anchor to the environment via visual landmarks. Here, we examine how thalamic HD signals and visual information from the retrosplenial cortex combine in the presubiculum. We find that monosynaptic excitatory connections from anterior thalamic nucleus and from retrosplenial cortex converge on single layer 3 pyramidal neurons in the dorsal portion of mouse presubiculum. Independent dual-wavelength photostimulation of these inputs in slices leads to action potential generation preferentially for near-coincident inputs, indicating that layer 3 neurons can transmit a visually matched HD signal to medial entorhinal cortex. Layer 4 neurons, which innervate the lateral mammillary nucleus, form a second step in the association of HD and landmark signals. They receive little direct input from thalamic and retrosplenial axons. We show that layer 4 cells are excited di-synaptically, transforming regular spiking activity into bursts of action potentials, and that their firing is enhanced by cholinergic agonists. Thus, a coherent sense of orientation involves projection-specific translaminar processing in the presubiculum, where neuromodulation facilitates landmark updating of HD signals in the lateral mammillary nucleus.

Head direction (HD) signals function as the brain's internal compass. They are organized as an attractor and anchor to the environment via visual landmarks. Here, we examine how thalamic HD signals and visual information from the retrosplenial cortex combine in the presubiculum. We find that monosynaptic excitatory connections from anterior thalamic nucleus and from retrosplenial cortex converge on single layer 3 pyramidal neurons in the dorsal portion of mouse presubiculum. Independent dual-wavelength photostimulation of these inputs in slices leads to action potential generation preferentially for near-coincident inputs, indicating that layer 3 neurons can transmit a visually matched HD signal to medial entorhinal cortex. Layer 4 neurons, which innervate the lateral mammillary nucleus, form a second step in the association of HD and landmark signals. They receive little direct input from thalamic and retrosplenial axons. We show that layer 4 cells are excited di-synaptically, transforming regular spiking activity into bursts of action potentials, and that their firing is enhanced by cholinergic agonists. Thus, a coherent sense of orientation involves projection-specific translaminar processing in the presubiculum, where neuromodulation facilitates landmark updating of HD signals in the lateral mammillary nucleus.

Transcriptional regulatory proteins, including transcription factors (TFs) and chromatin modifiers, must act inside cell nuclei, but membrane-bound transcription factors (MBTFs) are first anchored in membranes before nuclear translocation. Known MBTFs are vital for processes from myelin expression (MYRF) to cholesterol homeostasis (SREBP), yet their overall diversity remains uncharted. We hypothesized that additional membrane-bound transcriptional regulators (MBTRs) might exist, so we developed a bioinformatics screen to prioritize membrane proteins that are likely to regulate transcription. Our approach leverages domain composition by positing that surprising domain combinations suggest novel biological functions. We searched for rare but evolutionarily conserved pairings of transmembrane domains with domains likely involved in transcriptional regulation. Our method rediscovered known MBTFs and membrane-bound histone kinases, and identified novel MBTR candidates, including transmembrane histone N-acetyltransferases, a putative new subclass of MBTFs that share MYRF's DNA-binding domain, and the prolactin regulatory element-binding protein PREB (SEC12). Assays using recombinant PREB demonstrated that the transmembrane domain is the determinant of PREB subcellular localization, governing its distribution between the membrane and the nucleus in mouse embryonic stem cells. These findings underscore the utility of our method and provide a framework for investigating MBTRs that likely facilitate the integration of extracellular signals with transcriptional responses.

This paper revisits the general definition of signal integrity (SI) engineering to include relevant considerations applied to RF stages (front- and/or back-end) of wireless system compliant devices such as Bluetooth, ZigBee, mobile phone etc. Apart from traditionally viewed (baseband) impairments specific to digital waveforms, possible artifacts caused by RF-stage electromagnetics that influence the SI undesirably are identified. Hence, SI is redefined more comprehensively to include RF contexts. Relevant ADSTM-based simulation results on transmit-receive (TR)-switch performance in a CMOS-VLSI based Bluetooth circuit are presented and discussed.

Millimeter Wave (mm-wave) technology is required to assure widespread wireless communication and provides the rapid development of the Internet-of-Things (IoT) framework, which combines emergent technologies like virtual reality (VR), artificial intelligence (due to AI). CMOS technology faces challenges due to its inherently high-output conductance and velocity saturation, which exacerbate device parasitic and substrate failures. Therefore, the Design of The Single-Ended-to-Differential Low-Noise Amplifier Using DCLCT in Millimeter-Wave IoT (DCLT-SEDLNA-CMOS) is proposed in this paper. Initially, the signals from IoT applications are fed into a Single-Ended-to-Differential Low-Noise Amplifier (SEDLNA) to amplify weak signals received from antennas while minimizing noise, thereby enhancing the performance of the system. The SEDLNA uses a Dual-Channel Loosely Coupled Transformer (DCLCT) primarily for impedance matching between the signal source and the amplifier, which effectively minimizes the overall noise figure (NF) and also improves signal integrity. The use of 65 nm Complementary Metal–Oxide–Semiconductor (CMOS) technology in designing the SEDLNA allows for the integration of multiple functions on a single chip in IoT applications. CMOS technology is advantageous due to its low-power consumption and cost-effectiveness. The proposed DCLT-SEDLNA-CMOS method is implemented, and the performance metrics, such as voltage gain, frequency response, and energy consumption, are examined. Performance of the DCLT-SEDLNA-CMOS approach attains 22.12%, 21.46%, and 24.34% higher voltage gain, 26.75%, 24.34%, and 23.45% higher frequency response, when compared with existing techniques, such as CMOS-VGLNA, DPT-MPA, and DNC-LNA, respectively.

Transient receptor potential channels in chondrocyte homeostasis and pathophysiology: From molecular mechanisms to translational therapeutics.

In acoustic target detection using an unmanned underwater vehicle (UUV), platform self-noise and ambient noise emerge as dominant constraints on detection performance. In complex acoustic environments, flow noise, propeller noise, and ambient noise exhibit distinct spectral and spatial characteristics. Their partial overlap with target signals in frequency and spatial domains leads to degradation in noise suppression performance. To address this issue, this paper investigates the characteristics of signals and noise during UUV motion. While platform self-noise and ambient noise remain relatively stable, the incidence angle of signal varies with the platform's heading angle. This paper exploits this phenomenon to achieve signal-noise separation and develop a method for suppressing complex noise. The goal is to enhance the detection performance of weak targets. Experimental results demonstrate that the proposed method requires little prior information, effectively suppresses complex noise, and does not compromise the integrity of the target signal.

VEGF and its receptors expression in relation to reduced vasculature phenotype in heme oxygenase 1 knockout mouse embryos.

The pollen exine serves as a protective barrier and signaling interface essential for male fertility in flowering plants. Its precise patterning depends on coordinated interactions between microspores and tapetal cells. While the CLAVATA3/EMBRYO SURROUNDING REGION-related 19 (CLE19) peptide has been identified as a microspore-derived "brake" that restricts tapetal activity to maintain exine developmental homeostasis, how CLE19 integrates with hormonal signaling pathways remains poorly understood. Here, we demonstrate that CLE19 attenuates brassinosteroid (BR) signaling output by engaging a defined BSL-BIN2-BES1 signaling cascade. Through quantitative phosphoproteomic analysis, we identified that CLE19 affects the phosphorylation of multiple BR signaling components, including BSL-type phosphatases BSL1/2/3, the GSK3-like kinase BIN2, and the transcription factor BES1. We show that CLE19 is perceived by its receptor PXL1, which directly interacts with BSL-type phosphatases to activate the GSK3-like kinase BIN2, leading to phosphorylation of BES1 at serine residues S219 and S223. Functional analyses using phospho-dead and phospho-mimic BES1 variants confirm that CLE19-dependent phosphorylation controls BES1 nuclear export and degradation, ultimately suppressing BR-responsive transcriptional outputs required for pollen exine patterning. Together, our findings define a peptide-hormone signaling axis that regulates transcription factor activity through post-translational regulation, providing mechanistic insight into how developmental robustness is maintained via intercellular signal integration in plant reproduction.

Methodological innovation in chiral sensing with machine learning and multi-modal signal integration for tryptophan

GIGANTEA (GI) integrates photoperiod and temperature signals to regulate flowering. Under high temperatures, suppression of GI liquid-liquid phase separation promotes flowering. This illustrates how plants coordinate photoperiodic and thermosensory cues to fine-tune development. GI also links stress responses and circadian control, highlighting its central role in environmental signal integration.