Search Results (76)

While circuit parameter optimization has matured significantly, the systematic discovery of novel circuit topologies remains a bottleneck in analog design automation. This work presents SymXplorer, an open-source Python framework designed for automated topology exploration through symbolic modeling of analog components. The framework enables a component-agnostic approach to architecture-level synthesis, integrating stability analysis and higher-order filter exploration within a streamlined API. By modeling non-idealities as lumped parameters, the framework accounts for physical constraints directly within the symbolic analysis. To facilitate circuit sizing, SymXplorer incorporates a multi-objective optimization toolbox featuring Bayesian optimization and evolutionary algorithms for simulation-in-the-loop evaluation. Using this framework, we conduct a systematic search for differential Common-Gate (CG) Bandpass Transimpedance Amplifier (TIA) topologies tailored for 5G New Radio (NR) Radio-over-Fiber applications. We propose a novel, orthogonally tunable Bandpass TIA architecture identified by the tool. Implementation in 65 nm CMOS technology demonstrates the efficacy of the framework. Post-layout results exhibit a tunable gain of 30–50 dB$\Omega$, a center frequency of 3.5 GHz, and a tuning range of 500 MHz. The design maintains a power consumption of less than 400 $\mathsf{\mu }$W and an input-referred noise density of less than 50 pA/$\sqrt{\mathrm{Hz}}$ across the passband. Finally, we discuss how this symbolic framework can be integrated into future agentic EDA workflows to further automate the analog design cycle. SymXplorer is open-sourced to encourage innovation in symbolic-driven analog design automation. Full article

This article presents an advanced processing workflow for a Seismic While Drilling (SWD) dataset acquired using Distributed Acoustic Sensing (DAS) in a cross-well setting at the Otway International Test Centre (OITC) in Victoria, Australia, where no pilot signals were recorded. Recording the drill bit signature enables and simplifies the decoding of passive seismic signals emitted by the drill bit while drilling. In conventional SWD, a measured drill bit signature is used to correlate passive seismic recordings and to determine source trigger times, analogous to vibroseis processing. Without this reference, both source timing and signature must be inferred from the recorded wavefield. This can typically be achieved by backpropagating the recorded seismic data over short time windows, estimating the source location and trigger time based on the peak RMS energy in space and time. However, to simplify the processing of SWD data, a data processing workflow is presented, guided by travel time and seismic modelling, which transforms passive SWD data into active equivalents. The transformed data can then be used to characterize the subsurface by implementing travel time tomography and cross-well imaging. The results demonstrate reliable velocity and structural information can be recovered from DAS-based SWD data without pilot measurements, enabling simplified and scalable deployment of passive seismic while-drilling workflows. Full article

Background/Objectives: Following lumbar fusion procedures, adjacent segment degeneration (ASD) at cranial levels presents as a well-documented long-term complication, manifesting through recurrent pain, neurological deficits, and progressive functional decline. The prone single-position technique for lateral lumbar interbody fusion (PSP-LLIF) streamlines surgical workflow by eliminating the need for intraoperative patient repositioning; however, comprehensive evidence supporting its clinical and radiological effectiveness in managing cranial ASD remains insufficient. Material and Methods: This retrospective cohort study examined 30 consecutive patients presenting with symptomatic cranial adjacent segment disease who were treated with PSP-LLIF at a single institution. Patient-reported outcome measures included visual analog scale (VAS) assessments for axial and radicular pain, alongside the Oswestry Disability Index (ODI) for functional status evaluation. Radiological parameters included overall and segmental lumbar lordotic measurements, anterior and posterior disk height, fusion status, and instrumentation-related complications. Results: At 12-month postoperative evaluation, substantial clinical improvements were demonstrated. Mean VAS reductions measured 4.7 points for axial pain and 6.5 points for radicular pain, while ODI decreased by 28.5 points (p < 0.05). Radiological assessment demonstrated mean increases of 6.3° in lumbar lordosis and 5.1° in segmental lordosis, along with significant gains in both anterior and posterior disk height (p < 0.05). Solid fusion was radiographically confirmed at all instrumented levels. Temporary postoperative neurological symptoms developed in several patients but resolved spontaneously without requiring revision surgery. Conclusions: PSP-LLIF yields substantial clinical benefit and reliable radiological correction in patients with symptomatic cranial ASD. Optimal outcomes necessitate rigorous adherence to position-specific technical modifications, particularly maintenance of perpendicular fluoroscopic trajectories and implementation of continuous neural monitoring to account for prone-induced anatomical shifts. This approach represents a viable treatment strategy for patients with symptomatic cranial ASD. Full article

Background and Objectives: Implant-associated complications, including foreign-body responses and infection risk, remain major concerns in reconstructive and aesthetic breast surgery. Antimicrobial polymer coatings have been proposed as potential preventive strategies, but early-stage development requires simple and ethically refined in vivo models. This pilot study aimed to (i) establish a practical workflow for applying PLGA–vancomycin coatings onto PTFE substrates used as experimental analogs for smooth silicone implants, and (ii) develop a small-animal implantation protocol for short-term evaluation of surgical feasibility and local tissue tolerability. Materials and Methods: PLGA microparticles and PLGA–vancomycin microparticles were prepared using a double-emulsion solvent-evaporation method and applied onto PTFE discs. Particle size and polydispersity were assessed based on dynamic light scattering (DLS), and surface charge was measured via zeta potential. A bilateral subcutaneous implantation model was used in four Wistar rats, each receiving a PTFE disc coated with PLGA-only on one side and a disc coated with PLGA–vancomycin on the other. Animals were monitored for postoperative recovery, wound appearance, and general condition. After four weeks, implants and surrounding tissues were harvested for macroscopic and preliminary histological evaluation. Results: Both PLGA-only and PLGA–vancomycin microparticles showed submicron mean hydrodynamic diameters and moderately polydisperse distributions typical for double-emulsion formulations. All animals recovered normally, maintained stable body weight, and exhibited no macroscopic signs of adverse reactions. Preliminary histology showed early fibrous capsule formation with mild inflammatory infiltrate around both types of coated implants, without qualitative differences observed in this pilot setting. Conclusions: This preliminary study demonstrates the feasibility of applying PLGA-only and PLGA–vancomycin coatings onto PTFE implant analogs and establishes a reproducible, minimal-use rat model for short-term evaluation of local tissue tolerability. The protocol provides a practical foundation for future work on coating stability, drug-release kinetics, antibacterial activity, and long-term tissue responses on medical-grade silicone substrates. Full article

This work presents a unified framework for multiobjective analog circuit optimization that combines surrogate modeling, uncertainty-aware evolutionary search, and adaptive high-fidelity verification. The approach integrates ensemble regressors and graph-based surrogate models with a closed-loop multi-fidelity controller that selectively invokes SPICE evaluations based on predictive uncertainty and diversity criteria. The framework includes reproducible caching, metadata tracking, and process- and Dask-based parallelism to reduce redundant simulations and improve throughput. The methodology is evaluated on four CMOS operational-amplifier topologies using NSGA-II, NSGA-III, SPEA2, and MOEA/D under a uniform configuration to ensure fair comparison. Surrogate-Guided Optimization (SGO) replaces approximately 96.5% of SPICE calls with fast model predictions, achieving about a 20× reduction in total simulation time while maintaining close agreement with ground-truth Pareto fronts. Multi-Fidelity Optimization (MFO) further improves robustness through adaptive verification, reducing SPICE usage by roughly 90%. The results show that the proposed workflow provides substantial computational savings with consistent Pareto-front quality across circuit families and algorithms. The framework is modular and extensible, enabling quantitative evaluation of analog circuits with significantly reduced simulation cost. Full article

This study presents the digitization and integration of Kazakhstan’s legacy gravimetric maps at a scale of 1:200,000 into a modern geospatial database using ArcGIS. The primary objective was to convert analog gravity data into a structured, queryable, and spatially analyzable digital format to support contemporary geoscientific applications, including geoid modeling and regional geophysical analysis. The project addresses critical gaps in national gravity coverage, particularly in underrepresented regions such as the Caspian Sea basin and the northeastern frontier, thereby enhancing the accessibility and utility of gravity data for multidisciplinary research. The methodology involved a systematic workflow: assessment and selection of gravimetric maps, raster image enhancement, georeferencing, and digitization of observation points and anomaly values. Elevation data and terrain corrections were incorporated where available, and metadata fields were populated with information on the methods and accuracy of elevation determination. Gravity anomalies were recalculated, including Bouguer anomalies (with densities of 2.67 g/cm³ and 2.30 g/cm³), normal gravity, and free-air anomalies. A unified ArcGIS geodatabase was developed, containing spatial and attribute data for all digitized surveys. The final deliverables include a 1:1,000,000-scale gravimetric map of free-air gravity anomalies for the entire territory of Kazakhstan, a comprehensive technical report, and supporting cartographic products. The project adhered to national and international geophysical mapping standards and utilized validated interpolation and error estimation techniques to ensure data quality. The validation process by the modern gravimetric surveys also confirmed the validity and reliability of the digitized historical data. This digitization effort significantly modernizes Kazakhstan’s gravimetric infrastructure, providing a robust foundation for geoid modeling, tectonic studies, and resource exploration. Full article

This study examines how hand-drawn comics became a site of critical and creative resistance during fieldwork at Artist Village Aso 096k in rural Japan. The international artists in residence initially came to learn about the professional environment of the Japanese manga (comics) industry and to publish original works. However, the corporate-led system revealed barriers that constrained their early careers. In response, I employed Arts-Based Research (ABR) to invite the artists to create comics by hand, in contrast to the digital tools central to their daily workflow. This shift from digital to material practice foregrounded the affective and epistemological potentials of slowness, irrevocability, and embodied storytelling. The analog process functioned not only as an introspective tool for artists but also as a form of care that resisted the restrictive logic of Japan’s immigration policy. I argue that reflective drawing, as a situated and material practice, provides new ways of navigating social precarity. By centering comics as a research method, this study calls for renewed attention to the ethics and politics of artistic labor—particularly for international artists whose social and economic stability is increasingly threatened by xenophobic discourse. Full article

Objectives: The aim of this in vitro study was to evaluate the accuracy of intraoral impressions obtained using the Trios 3Shape^® (3Shape Trios, Copenaghen, Denmark) and Carestream CS 3600™ (Carestream Dental, Stuttgart, Germany) scanners, compared with traditional polyvinyl siloxane (PVS) impressions. A laboratory scanner served as the gold standard. Materials and Methods: The study was based on 3D-printed master models derived from partially edentulous clinical cases previously treated at our department (2017–2022). All cases required at least two implants. Data analysis was performed using one-way ANOVA and two-sample Z-tests (α = 0.05) to compare mean deviations and variability. Results: All techniques demonstrated high accuracy, with deviations from the reference point below 30 μm. The digital intraoral scanners (Trios 3Shape^® and Carestream CS 3600^®) showed superior accuracy compared with PVS analog impressions, with no statistically significant difference between the two IOS systems. Conclusions: Within the limitations of this in vitro study, both IOS systems and PVS analog impressions achieved clinically acceptable accuracy. Digital systems exhibited improved performance in terms of mean deviation and consistency. The higher accuracy and consistency of digital impressions may translate into improved clinical efficiency and prosthetic fit in implant rehabilitations. From a clinical perspective, these in vitro findings suggest that digital impressions may enhance prosthetic fit and workflow efficiency, though further in vivo validation is required. Clinical significance: This study supports the reliability of intraoral scanning compared with conventional impressions in implant-supported rehabilitations. By demonstrating high intrinsic accuracy, these findings contribute to optimizing digital workflows in implant dentistry and reinforce the potential of intraoral scanning in static computer-guided, flapless implant surgery. Trial registration: Ethical approval and trial registration were not applicable to the present in vitro investigation, as no patients were directly involved in the experimental phase. The digital data used to generate the laboratory master models originated from a separate clinical study conducted at ASST Santi Paolo e Carlo, Milan (Ethics Committee approval no. 1361, 12 July 2017; ClinicalTrials.gov registration, Unique Protocol ID 1361). Full article

Background: Thoracic paravertebral block (TPVB) is an established component of multimodal analgesia and enhanced recovery pathways following thoracoscopic lung resection. A surgeon-performed, thoracoscopy-guided approach has been proposed to improve intraoperative workflow, but high-quality comparative data are limited. Methods: In this single-center, randomized, non-inferiority trial, adult patients undergoing thoracoscopic lobectomy or segmentectomy received either thoracoscopy-guided TPBV (T-TPVB) conducted by surgeons or ultrasound-guided TPBV (U-TPVB) conducted by anesthesiologists. Blocks were performed at the end of surgery at the T4 and T7 vertebra levels, using 10 mL of 0.5% ropivacaine per level. The primary outcome was dynamic pain during coughing at 1–6 h postoperatively (visual analog scale, VAS). Secondary outcomes included resting/dynamic pain scores, opioid consumption over 48 h, block-related complications, and procedural time. Results: Seventy-three patients were included in the intention-to-treat analysis. Mean dynamic VAS scores at 1–6 h were 3.3 (T-TPVB) and 3.1 (U-TPVB), with a mean difference of 0.2 (95% CI: −0.3 to 0.7), meeting the non-inferiority criterion (margin 0.9). Secondary outcomes, including pain trajectories and opioid consumption, were comparable between groups. Procedural time was significantly shorter in the T-TPVB group, with no differences in complication rates. Conclusions: Surgeon-performed thoracoscopy-guided TPVB was non-inferior to the standard ultrasound-guided technique for early postoperative pain after thoracoscopic lung resection. Both methods provided comparable analgesic efficacy and safety profiles, while T-TPVB significantly reduced procedural time. This approach may support streamlined perioperative workflows and optimize enhanced recovery protocols in thoracic surgery. (Trial registration number, KCT0006471). Full article

Renin, a key aspartic protease central to the renin–angiotensin–aldosterone system (RAAS), remains a therapeutic target for hypertension despite the withdrawal of the only approved direct renin inhibitor, Aliskiren, due to unfavorable drug–drug interactions and safety concerns. Here, we report a computational protein design-driven evaluation of (S)-3-((3-(1H-imidazol-1-yl)propyl)amino)-2-(((S)-1-carboxy-2-(cyclooctanecarboxamido)ethyl)amino)-3-oxopropanoic acid (N-CDAH), a novel lipophilic cyclooctanoyl- derivative, as a next-generation renin inhibitor scaffold. This scaffold was designed based on the rationale of leveraging the carnosine like backbone while optimizing lipophilicity and metabolic stability. Pharmacokinetic, ADME, and toxicity predictions (SwissADME, pkCSM) revealed greater predicted aqueous solubility, enhanced metabolic stability, and significantly reduced off-target liabilities compared with Aliskiren (specifically, non-inhibition of major CYP isoforms). Molecular docking (AutoDock Vina binding affinity: −8.08 kcal/mol; Maestro Induced Fit Docking score: −11.149 kcal/mol) and molecular dynamics simulations confirmed favorable binding interactions, conformational adaptability, and complex stability within the renin active site. To contextualize its performance within the broader chemical space, the diastereomeric analog of N-CDAH as well as structurally related compounds identified through SwissSimilarity were also examined using computational workflow. The MD analysis (200 ns) demonstrated that the inhibitor is anchored via a dual stabilization mechanism: hydrophobic enclosure coupled with persistent ionic interactions. These integrative in silico results highlight the potential of this derivative to overcome Aliskiren’s pharmacological shortcomings, providing a strong computational rationale for experimental validation and underscoring the role of structure-based drug design in antihypertensive drug discovery. Full article

Phytohormones are key signaling molecules that regulate plant growth, stress adaptation, and fruit ripening. However, their low abundance and structural diversity complicate accurate quantification in food matrices. This study presents a validated LC–MS/MS method for the simultaneous detection of seven phytohormones in tomato fruit, including two synthetic analogs that mimic natural auxins and cytokinins. Method optimization focused on extraction efficiency, solid-phase cleanup, and mobile phase composition, achieving high recovery (85–95%) and reduced matrix effects. Chromatographic separation was performed on a C18 column, with detection by triple quadrupole mass spectrometry in MRM mode. The method demonstrated excellent linearity (R² > 0.98), precision, and robustness, with detection limits as low as 0.05 ng/mL for abscisic acid and 6-benzylaminopurine. Validation followed US-FDA and EC 2021/808 guidelines, ensuring regulatory compliance and analytical reliability. Analysis of tomato samples from five geographic origins revealed significant differences in phytohormone profiles, particularly in abscisic and salicylic acids, highlighting the method’s ability to capture biologically and agriculturally relevant variation. This workflow offers a sensitive, transferable platform for monitoring bioactive compounds in tomatoes and other food crops, supporting post-harvest quality assessment and food metabolomics research. Full article

Advances in digital dental technologies have transformed implant therapy from analog, stepwise processes into advanced, data-driven workflows spanning diagnosis, planning, surgery, and prosthetic delivery. Contemporary digital implantology integrates multiple techniques, tools, and multimodal datasets into comprehensive diagnostic models and treatment workflows, enhancing implant placement accuracy, procedural efficiency, patient experience, and interdisciplinary coordination. However, integration remains constrained by fragmented datasets, diverse software platforms, and parallel surgical and prosthetic streams. These interfaces often require manual user intervention to convert, process, and align data, thereby increasing the risk of data loss, artifact generation, misalignment, and error accumulation, which may impact implant and prosthetic restorative outcomes. Similarly, implant and prosthetic planning steps continue to rely on subjective, non-standardized user input, requiring advanced experience and training. This narrative review synthesizes current evidence and technical developments in digital implant dentistry based on literature searches in PubMed, Scopus, and Web of Science, with emphasis on publications from 2010 onward, prioritizing systematic reviews, randomized clinical trials, and technical reports focusing on key technological innovations. It presents the current state of the art in digital implantology and identifies major workflow interfaces that constrain seamless, end-to-end integration. This part I summarizes contemporary tools and approaches in digital implant technology. In contrast, Part II of this series will address the emerging roles of artificial intelligence and robotics in overcoming these limitations and advancing toward fully integrated digital implant prosthodontic workflows. Overall, current digital implant workflows are clinically reliable and are equivalent to, or often superior to, conventional approaches in terms of efficiency and accuracy. Nevertheless, their full potential remains limited by persistent software, data, and process interface barriers. Full article

Background: This retrospective comparative clinical study aimed to evaluate the performance of digital versus conventional impression techniques in the fabrication of implant-supported prosthetic restorations. Materials and Methods: A total of 40 cases were included: 20 impressions obtained with conventional elastomeric materials (polyvinyl siloxane and polyether), and 20 impressions acquired digitally using two intraoral scanners (TRIOS 3 and Medit i700). All patients received partial fixed implant restorations and were documented across all stages of prosthetic treatment. Accuracy and passive fit were assessed using radiographic measurements and the Sheffield test. Linear distances (mm) at the implant–abutment interface, chairside time (min), and VAS scores (1–10) were analyzed. Clinical efficiency was evaluated based on procedural steps, chairside time, and adjustment frequency. Patient satisfaction was assessed through a structured 10-item Visual Analog Scale (VAS) questionnaire. Results: Results showed a lower misfit rate in the digital group (15%) compared to the conventional group (25%), with no final-stage misfits in digital cases. Digital workflows demonstrated shorter impression times, fewer procedural steps, and reduced the need for prosthetic adjustments. Patient satisfaction scores were significantly higher in the digital group across all VAS parameters (p < 0.001), particularly in comfort and esthetic satisfaction. Conclusions: These findings support the use of digital impressions as a clinically efficient and patient-preferred alternative to conventional methods for partial implant restorations. However, conventional impressions remain a viable option in settings where digital technology is not available. Further studies with larger sample sizes and long-term follow-up are recommended to assess outcomes in full-arch rehabilitation. Full article

Background: TRPC6 is recognized as a therapeutically relevant cation channel, whose activation is governed by specific ligand–pocket interactions. Methods: An integrated in silico workflow was employed, comprising structure-based docking, 100-nanosecond molecular dynamics (MD) simulations, and MM-GBSA calculations. Benzoic-acid–based compounds were designed and prioritized for binding to the TRPC6 pocket, using a known literature agonist as a reference for benchmarking. Results: Within the compound series, BT11 was found to exhibit a representative interaction profile, characterized by a key hydrogen bond with Trp680 (~64% occupancy), persistent salt-bridge interactions with Lys676 and Lys698, and π–π stacking with Phe675 and Phe679. A favorable docking score (−11.45 kcal/mol) was obtained for BT11, along with a lower complex RMSD during MD simulations (0.6–4.8 Å), compared with the reference compound (0.8–7.2 Å). A reduction in solvent-accessible surface area (SASA) after ~60 ns was also observed, suggesting decreased water penetration. The most favorable binding energy was predicted for BT11 by MM-GBSA (−67.72 kcal/mol), while SOH95 also ranked highly and slightly outperformed the reference. Conclusions: These convergent computational analyses support the identification of benzoic-acid–derived chemotypes as potential TRPC6 ligands. Testable hypotheses are proposed, along with structure–activity relationship (SAR) guidelines, to inform experimental validation and guide the design of next-generation analogs. Full article

The integration of AI-driven optimization into Electronic Design Automation (EDA) enables smarter and more adaptive circuit design, where symmetry and asymmetry play key roles in balancing performance, robustness, and manufacturability. This work presents a model-driven optimization methodology for sizing low-phase-noise LC voltage-controlled oscillators (VCOs) at 5 GHz, targeting Wi-Fi, 5G, and automotive radar applications. The approach uses the EKV transistor model for analytical CMOS device characterization and applies a diverse set of metaheuristic algorithms for both single-objective (phase noise minimization) and multi-objective (joint phase noise and power) optimization. A central focus is on how symmetry—embedded in the complementary cross-coupled LC-VCO topology—and asymmetry—introduced by parasitics, mismatch, and layout constraints—affect optimization outcomes. The methodology implicitly captures these effects during simulation-based optimization, enabling design-space exploration that is both symmetry-aware and robust to unavoidable asymmetries. Implemented in CMOS 180 nm technology, the approach delivers designs with improved phase noise and power efficiency while ensuring manufacturability. Yield analysis confirms that integrating symmetry considerations into metaheuristic-based optimization enhances performance predictability and resilience to process variations, offering a scalable, AI-aligned solution for high-performance analog circuit design within EDA workflows. Full article