We present a new input-to-state-stability analysis for a class of normal form systems with unknown control directions using a recently introduced global extremum seeking algorithm in the presence of disturbances. Our new state transformation and Lyapunov analysis based on a quadratic Lyapunov function for the averaged system are a departure from previous averaging-based approaches, and cover general classes of nonlinear systems including generalized chains of integrators, providing less conservative bounds on the dither frequency compared with earlier results. Our numerical examples illustrate the effectiveness of our analysis. We also prove a robustness property for the algorithm under small time-varying delays.
LLMs have become thinking companions for hundreds of millions worldwide, and they often do remarkable work. But their satisfaction-optimized design produces suppressed inquiry: the tendency for LLMs to inhibit rather than facilitate users' questioning process. LLMs appear fluent, confident, and seemingly all-knowing, their near-instant and polished output making non-LLM work feel unacceptably tedious and less eloquent. They affirm rather than interrogate users' assumptions, producing output that is deceptively adequate—shallower, less original, and less carefully reasoned than it appears. Seemingly competent systems also reduce vigilance and the monitoring impulse that independent judgment requires. Their responses also confine users within the frame they establish, narrowing what users think to ask. These costs are self-concealing: detecting them requires the very engagement that they suppress. And repeated delegation gradually atrophies users' capacity to reason independently. Three converging pressures make correction difficult: commercial incentives that reward satisfaction over substance, LLMs’ tendency to revert to satisfaction-optimized defaults even when users push back, and a societal drift toward less-effortful engagement. We propose a research agenda to deepen the understanding of suppressed inquiry and how to counter it, to move closer to the remarkable thinking partners LLMs promised to be.
Soil spectroscopy enables the rapid, non-destructive estimation of key soil properties, but it conventionally relies on air-dried samples measured against a white reference (WR, ≈100% reflectance) panel. When soils are wet, refractive-index and multiple-scattering effects darken the surface and suppress diagnostic absorptions, while the wide dynamic range of the WR panel further compresses these low-reflectance features; this reduces predictive accuracy and hinders the harmonisation of spectra acquired under different moisture conditions. Because each reference panel is treated as the 100% reference for its own measurement session, replacing WR with a lower-albedo panel is an acquisition-stage radiometric transformation that expands the effective dynamic range for low-reflectance (wet or dark) targets without modifying the soil sample itself. This study therefore re-evaluates calibration practice under wet conditions and tests whether lower-albedo gray (GR, mid-reflectance ≈50%) and black (BR, low-reflectance ≈20%) reference panels improve the prediction of soil constituents relative to WR, without drying. Using 3928 samples from the Israeli Legacy and Israeli Soil Spectral Libraries, robust dry-soil models (WR) were first established for soil organic carbon (SOC), dithionite-extractable Fe (Fe_d), and CaCO₃, confirming high accuracy under air-dried conditions but substantial degradation at 20% moisture regardless of reference panel when trained only on dry spectra. To isolate calibration effects, 91 soils (training) were adjusted to 20% gravimetric moisture to develop wet-condition models, which were then applied to 223 independent soils at 20% moisture under WR, GR, and BR calibration. GR consistently yielded the highest performance (SOC R² = 0.66 vs. 0.48 for WR; Fe_d R² = 0.75 vs. 0.67; CaCO₃ R² = 0.83 vs. 0.79), with concurrent RMSE reductions. When the GR-trained wet library (20%) was applied across 5–30% moisture, GR-based measurements maintained robust accuracy, whereas WR remained unstable and BR showed attribute-dependent variability. We conclude that constructing a dedicated wet spectral library at ≈ 20% gravimetric moisture using a gray reference panel provides a practical and transferable acquisition-stage strategy for wet-soil evaluation within the tested soils and moisture range. As the study is laboratory-based, the approach is presented as a proof of concept that warrants field validation.
Purpose Digital replantation is traditionally guided by injury mechanism, functional priority, ischemia time, and patient factors. Pediatric age is commonly considered a favorable indication, whereas advanced age is often assumed to reduce candidacy. We examined associations of age and area-level zone improvement plan (ZIP) -income quartile with digital replantation following complete traumatic thumb or other-finger amputation. Methods The National Inpatient Sample was queried from 2016 to 2021 for hospitalizations with complete traumatic upper-extremity amputations, including thumb, other-finger, wrist-region, and hand amputation. The primary analytic cohort was limited to complete thumb and other-finger amputations; wrist and hand amputations were retained only for descriptive context. The primary outcome was digital replantation during the included hospitalization, identified using prespecified International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) and Procedure Coding System (ICD-10-PCS) Reattachment procedure codes. Analyses used survey-weighted multivariable logistic regression to account for National Inpatient Sample discharge weights, strata, and hospital clusters. The model adjusted for patient demographics (age group, sex, race, payer, ZIP-income quartile), injury-related factors (digit group and additional injury diagnosis), and system-level characteristics (transfer-in status, hospital size, teaching status, region, weekend admission, and year). Results The primary digital cohort included 1,458 unweighted hospitalizations, representing 7,290 weighted hospitalizations nationally. Digital replantation was coded in 361 unweighted hospitalizations (weighted n = 1,805; 24.8%). In the adjusted model, higher area-level ZIP-income quartile was associated with digital replantation: compared with quartile 1, adjusted odds ratios (aORs) were 1.52 for quartile 2 (95% CI, 1.06–2.18), 1.83 for quartile 3 (95% CI, 1.24–2.70), and 2.23 for quartile 4 (95% CI, 1.44–3.44). Transfer-in status (aOR, 1.98; 95% CI, 1.49–2.62) and thumb amputation (aOR, 2.15; 95% CI, 1.64–2.81) were also associated with digital replantation. In contrast, no age category was statistically associated with digital replantation after adjustment. Children aged 0–12 years had an aOR of 0.96 (95% CI, 0.53–1.74), adolescents aged 13–17 years had an aOR of 0.84 (95% CI, 0.40–1.75), and adults aged 65 years or older had an aOR of 0.64 (95% CI, 0.32–1.27). Conclusions Among included hospitalizations, higher area-level ZIP-income quartile, transfer-in status, and thumb involvement were associated with digital replantation after adjustment for measured covariates. No age category was statistically associated with digital replantation after adjustment. These findings suggest that patterns of digital replantation may reflect not only anatomic factors but also area-level socioeconomic context and referral-related characteristics. Because the database lacked detailed information on injury mechanism, technical candidacy, comorbidity, and geographic access, these associations cannot distinguish differences in replantation candidacy from differences in referral access or treatment selection. Type of study/level of evidence Prognostic III.
The 16th Acromegaly Consensus Conference in September 2024 updated recommendations on diagnosis and treatment of acromegaly comorbidities. Since the 2020 acromegaly comorbidity management guideline was published, new evidence has emerged on novel and known comorbidities and new treatment approaches. Forty-three experts in the management of acromegaly reviewed the current literature and assessed changes in clinical practice standards and management. Current outcome goals were considered and updated, with a focus on the impact of current and emerging treatments of these comorbidities. Participants assessed factors that determine pharmacological choices, as well as use of specific agents in the management of the most relevant acromegaly comorbidities. We present consensus recommendations highlighting optimization of evidence-based acromegaly comorbidities management.
