Seth mounts a rich and persuasive case that human consciousness cannot be understood without life's distinctive machinery - autopoiesis, allostatic control, predictive processing under the free-energy principle, and substrate-entangled dynamics. I agree that this undercuts the expectation that humanlike consciousness will "come for free" with more intelligent machines. However, we should also be cautious about drawing extrapolations from features of biological consciousness - even essential features - to the possibility of exotic forms of consciousness in artificial systems.

This study investigates instability mechanisms in soft rocky coastal cliffs through an integrated numerical framework that couples computational fluid dynamics (CFD) with the finite-discrete element method (FDEM), applied to the tuffaceous cliffs of Ventotene Island (Italy). The modelling strategy systematically explores the role of structural predisposition, marine erosion, wave-induced loading, thermal forcing, and time-dependent strength degradation in controlling cliff stability and failure evolution. The results show that neither gravity loading nor basal undercutting alone can reproduce realistic failure mechanisms, even in the presence of a DFN. Progressive rock failure (PRF) emerges only when basal erosion is explicitly coupled with inward-migrating strength degradation, implemented using a simplified fatigue-based S-N approach. Under the considered lithology and the present Mediterranean climatic conditions, wave impacts and thermal forcing induce predominantly elastic or sub-critical mechanical responses and do not directly trigger failure. However, wave-induced dynamic perturbations concentrate displacements in fractured cliff sectors, suggesting a preparatory role through fatigue and stress redistribution, with potential triggering effects once critical degradation thresholds are approached. Thermal forcing becomes mechanically effective only under amplified temperature excursions or in lithologies with higher thermal sensitivity. The coupled CFD-FDEM approach is therefore interpreted as a process-based, exploratory framework that captures the dynamic response of coastal cliffs to realistic environmental boundary conditions, rather than as a direct predictor of wave-driven collapse. The methodology provides a physically grounded and transferable framework for investigating multi-forcing interactions, damage accumulation, and PRF in coastal cliffs, offering new insights into the mechanisms governing coastal instability and long-term cliff evolution.

Photolithography, a cornerstone of semiconductor manufacturing, faces persistent challenges in lift-off processes, particularly regarding solvent usage, sidewall adhesion, and limited pattern fidelity. While dry lift-off and bilayer resist schemes provide promising alternatives, conventional approaches often rely on multiple materials and exhibit uncontrollable undercut profiles. Here, we report a universal bilayer photoresist strategy that uses a single material and enables solvent-free, high-yield dry lift-off. By integrating surface modification and UV pre-exposure (222 nm), our method allows precise control of the undercut structure and maintains full compatibility with subsequent processes such as sputtering and dry lift-off. Experiments demonstrate robust multiscale patterning capability, achieving from wafer-scale down to 17 nm features, with a 100% yield, high density (line width: spacing = 5:4), and clean sidewalls without residue. This strategy also enables high-resolution quantum dot patterning and is compatible with the fabrication of pixelated perovskite micro-LEDs, highlighting its potential for optoelectronic applications including displays, optical encryption, and anti‑counterfeiting.

Decentralized, farmer-scale biochar production can valorize agricultural residues for soil amendment and carbon storage while avoiding the feedstock-transport burden of centralized pyrolysis. This study compared three low-capital, field-deployable kiln architectures for an on-farm self-supply user: an open flame-curtain Traditional Oregon Kiln (TOK, Type A), a Controlled-Draft Flame-Curtain Kiln (CDFC, Type B), and an Indirect-Heat Fine-Feedstock Retort (IHFRt, Type C). A unified techno-economic model was parameterized with experimental yields and charring times for corn cob, corn stalk, and sorghum stover (n=15 batches per kiln). At a 50kg batch, 100dyr[-1] of operation, a wage of 16.50USDh[-1], and a 7% discount rate over a 10-yr life, the estimated minimum selling prices (MSP, oven-dry basis) were 3.06USDkg[-1] (Type A), 2.60USDkg[-1] (Type B), and 1.74USDkg[-1] (Type C). Capital cost was small (876-1416 USD, <3% of levelized cost), whereas labor contributed more than 95% of operating cost and dominated sensitivity. Type C achieved the lowest MSP because its passive charring phase decoupled operator hours from conversion time, raising biochar output per labor hour by 80%. Against the 3USDkg[-1] to 5USDkg[-1] U.S. retail price for comparable specialty biochar, Type C undercut even the low end and Type A remained competitive at the upper end. A 10,000-draw Monte Carlo left Type C the lowest-cost architecture in 99.9% of draws, with the full Type C < Type B < Type A ordering preserved in 86%. A paired life-cycle assessment of kiln emissions and the soil-organic-carbon foregone by residue removal is the necessary next step before net climate benefits can be claimed.

Xue and Chen et al.'s review connects AI-derived CT features of lung ground-glass nodule adenocarcinoma to driver gene status. Three aspects are missing. There is no stated search strategy no databases, date range, or inclusion criteria despite drawing on more than 150 references, so readers cannot tell whether weaker or null results were sought out or just left aside. Individual studies are cited by their best accuracy or AUC figures, from approximately 0.64 to above 0.95, with no attempt to weigh them by sample size, design, or validation status. The framing does not match the evidence the review cites: the text calls AI transformative, but a systematic review it references reports a mean AUC of only ~0.64 for driver gene prediction from imaging. None of this undercuts the review's usefulness as a starting map of the field, but a stated search process, some quality-weighting of the cited numbers, and framing that matches the aggregate evidence would make it more reliable.

As a critical step in micro- and nanofabrication, the resist lift-off process plays an important role in enabling pattern transfer and device integration. The challenge lies in achieving resist removal without compromising the integrity or functionality of underlying materials. Conventional wet lift-off approaches rely on hazardous solvents and high energy consumption. They also suffer from solvent-induced swelling, which limits compatibility with many sensitive functional materials. Here, we develop a dry lift-off process based on interfacial adhesion modulation, applicable to sensitive optoelectronic materials such as perovskite quantum dots and PEDOT:PSS. The lift-off behavior of the resist was further validated through mechanical and interfacial fracture theoretical analyses. High-density patterns of both perovskite quantum dots and PEDOT:PSS were achieved across diverse substrates at a resolution of 5 µm, over wafer-scale areas (up to 4 inches), with a lift-off yield approaching 100%. Furthermore, the introduction of an undercut architecture in PEDOT:PSS improves structural integrity while preserving electrical conductivity. This work provides a scalable, efficient, and environmentally benign route for the large-area, high-fidelity patterning of sensitive functional materials.

Measurement errors can catastrophically bias parameter estimates in models to correlate nanoscale properties and structures, undercutting a foundation of nanoscience and nanotechnology. In a general solution to this latent problem, we derive a method-of-moments correction for least-squares estimates of correlative model parameters. Our correction applies to many relations of dependent and independent variables, subject to many types of measurement errors of the independent variable. Focusing on the prevalent power-law model to correlate optical intensity and nanoparticle size, we test the limits of accuracy of our correction and study the use of either reference size distributions or sizing uncertainty estimates to inform a measurement error model. We critically evaluate representative measurements of various nanoparticles, impacting the conclusions of several studies and changing expectations of intensity scaling exponents for nanoscale optical inferences. Our correction is immediately available, highly interpretable, and broadly applicable to gain reliable insights and prevent future mistakes.

Digital twins have transformed design and verification workflows in engineering, yet their adoption within medical device development remains limited. Conventional build-and-test approaches restrict design space exploration and often delay identification of mechanically critical risks. This paper presents a case study on the development of a calibrated, design-phase behavioral digital twin for a capsule-based biomedical delivery system used in dentistry, with the annular snap-fit nozzle-to-body interface selected as a representative mechanically sensitive feature. Empirical testing, analytical snap-fit theory and nonlinear Finite Element Analysis (FEA) were integrated to characterize mating force, strain and structural safety during assembly. Strong pre-calibration agreement was observed between the analytical and numerical models and back-calculation of an effective polymer-to-polymer coefficient of friction (μ = 0.12) reduced prediction error relative to empirical measurements to within experimental repeatability, establishing a validated behavioral digital twin. Design optimization employed a Taguchi orthogonal array to efficiently explore strain-constrained geometric variation. Results identified undercut depth, governed by nozzle inner diameter, as the dominant contributor to retention strength. An optimized configuration achieved a 65%-75% increase in mating force relative to the baseline design while remaining within permissible strain limits. Numerical verification predicted peak mating force of 190 N and identified localized stress concentrations in the nozzle neck region, highlighting reinforcement requirements before production tooling. Physical verification and validation of the optimized system confirmed the predicted increase in structural performance. Consistent with the digital twin maturity continuum, the framework is positioned as a design-phase, behavioral digital twin. It operates with offline one-way physical-to-digital data flow during the product realization stage, with automated bidirectional synchronization identified as the next stage of development. These findings demonstrate how digital twins can shift biomedical device development from reactive validation towards predictive, manufacturability-aware design, strengthening patient safety, clinician confidence and regulatory assurance in Class II medical devices.

Cleft lip and palate (CLP) is the most prevalent congenital craniofacial anomaly and is frequently associated with dental anomalies and compromised maxillary anatomy. Complete edentulism in adolescents with CLP is exceedingly uncommon, and its concurrent presentation with bilateral auricular agenesis and nasal hypoplasia represents a rare clinical scenario. A 17-year-old male patient with surgically corrected bilateral CLP, congenital bilateral auricular agenesis, and a congenital nasal defect presented with complete edentulism of both arches. Comprehensive prosthodontic rehabilitation was performed. Intraoral restoration was accomplished using conventional heat-polymerized acrylic resin complete dentures, fabricated following meticulous border molding, definitive elastomeric impressions, and semiadjustable articulator mounting. Extraoral defects were restored using room-temperature vulcanizing silicone prostheses: a spectacle-frame-retained bilateral auricular prosthesis fabricated via a three-piece mold design to accommodate complex anatomical undercuts, and an adhesive-retained nasal prosthesis fabricated via a two-piece mold with putty protection of the nasal apertures. Intrinsic colorimetric matching was achieved using a systematic pigment incorporation technique. At the one-, three-, six-, and 12-month follow-up visits, the patient and guardian reported improvements in mastication, speech, social confidence, and overall satisfaction with the rehabilitation. This case illustrates that a structured, multidisciplinary prosthodontic approach integrating conventional complete dentures with custom-fabricated silicone maxillofacial prostheses can reliably restore orofacial function and esthetics in young patients with complex congenital craniofacial deficits, including those in resource-limited clinical settings.

Agency says closing the research center will improve efficiency, but skeptics argue it will undercut research critical to farmers.