Search Results (189)

In recent years, deep learning has driven remarkable progress in remote sensing change detection (CD); however, practical deployment is still hindered by two limitations. First, CD results are easily degraded by imaging-induced uncertainties—mixed pixels and blurred boundaries, radiometric inconsistencies (e.g., shadows and seasonal illumination changes), and slight residual misregistration—leading to pseudo-changes and fragmented boundaries. Second, prevailing methods follow a static one-pass inference paradigm and lack an explicit feedback mechanism for adaptive error correction, which weakens generalization in complex or unseen scenes. To address these issues, we propose a feedback-driven CD framework that integrates a dual-branch U-Net with deep reinforcement learning (RL) for pixel-level probabilistic iterative refinement of an initial change probability map. The backbone produces a preliminary posterior estimate of change likelihood from multi-scale bi-temporal features, while a PPO-based RL agent formulates refinement as a Markov decision process. The agent leverages a state representation that fuses multi-scale features, prediction confidence/uncertainty, and spatial consistency cues (e.g., neighborhood coherence and edge responses) to apply multi-step corrective actions. From an imaging and interpretation perspective, the RL module can be viewed as a learnable, self-adaptive imaging optimization mechanism: for high-risk regions affected by blurred boundaries, radiometric inconsistencies, and local misalignment, the agent performs feedback-driven multi-step corrections to improve boundary fidelity and spatial coherence while suppressing pseudo-changes caused by shadows and illumination variations. Experiments on four datasets (CDD, SYSU-CD, PVCD, and BRIGHT) verify consistent improvements. Using SiamU-Net as an example, the proposed RL refinement increases mIoU by 3.07, 2.54, 6.13, and 3.1 points on CDD, SYSU-CD, PVCD, and BRIGHT, respectively, with similarly consistent gains observed when the same RL module is integrated into other representative CD backbones. Full article

Central business district (CBD) hospitals must sustain reliable pressure relationships in critical rooms while reducing whole-facility carbon under tight space and disruption constraints. We developed an ontology-grounded semantic digital twin that normalizes building automation system (BAS) and building management system (BMS) telemetry into a unified semantic store consistent with Brick Schema, enabling portable asset discovery via query and thereby supporting forecasting, anomaly detection, and multi-objective optimization without dependence on vendor point naming conventions. Whole-facility impacts were verified using International Performance Measurement and Verification Protocol Option C–style measurement and verification with an S0-calibrated baseline model and residual-based savings attribution. Relative to the baseline (S0), the intervention (S3) produced a step increase in the critical-room pressure-compliance pass rate, tighter room-to-corridor differential-pressure (ΔP) control across airborne infection isolation and open room strata, and intent-aligned ventilation delivery (air changes per hour ratio distribution concentrated near unity; p < 0.05 where letter groups differ). Operational-state discrimination improved (AUC 0.649→0.696) and issue-resolution times shortened (left-shifted cumulative distribution function), indicating reduced service burden. Option C verification showed energy residuals shifting negative under S3, consistent with net savings versus baseline expectations. Across progressive maturity (S0→S3), time-to-value and burden fractions decreased, carbon intensity (tCO₂e m⁻²) decreased, long-tail exposure compressed (log-scale horizon), and composite performance indices increased (p < 0.05). These results demonstrate a verifiable pathway to pressure-reliable, decarbonized hospital operations at the whole-facility boundary while making the semantic layer’s utility explicit through query-driven, ontology-grounded asset discovery. We present an IPMVP Option-C–verifiable semantic digital-twin governance framework that links audited operational evidence (telemetry → actions → verification) to whole-facility energy and carbon outcomes while maintaining critical-room pressure-relationship reliability. Optimization benchmarking (including quantum annealing) is used as supporting decision-support evaluation, rather than as the central contribution. Full article

Real-time trajectory forecasting for curling stones is essential for on-ice decision support, yet prior work often emphasizes offline analysis, fixed-window predictors, or physics-driven models that require additional measurements, and it rarely reports end-to-end feasibility under edge-computing constraints (latency and memory). This leaves a practical gap between accurate trajectory reconstruction and deployable rink-side guidance. To bridge this gap, we propose an online forecaster based on low-dimensional $(x,y)$ coordinate streams and a lightweight attention-enhanced Long Short-Term Memory (LSTM) architecture optimized for edge devices. The model uses a four-second sliding window (240 frames at 59.94 Hz) to predict fifteen seconds of future positions (900 frames) in a single multi-step forward pass, and an overlapping publication scheme is adopted to retain longer temporal context and stabilize continuous updates. We further provide a TensorFlow Lite (TFLite) conversion and quantization workflow to support on-device inference. Quantitatively, experiments on the CurlTracer dataset (1033 throws at 59.94 Hz) show that the proposed attention–LSTM achieves trajectory-level MAE/MdAE of 0.25/0.22 m over the full prediction horizon, improving over a plain LSTM (0.30/0.24 m) and a physics-based pivot-slide baseline (3.52/3.54 m). At two checkpoints, the first-step MAE/MdAE are 0.14/0.11 m and the mid-step MAE/MdAE are 0.21/0.18 m. For real-time feasibility, on a Raspberry Pi 4B the per-window latency is approximately 0.25 s (including I/O and post-processing), while CPU benchmarks show that TFLite variants provide 7–8× speedups over the original Keras runtime with only minor accuracy loss (e.g., window-level MAE 0.30–0.41 m across FP32/DRQ/FP16/INT8). Qualitatively, representative trajectory visualizations show good agreement in near/mid horizons and reasonable stopping-region guidance, supporting integration with a stone-mounted interface for actionable feedback. Full article

Noise degrades both EEG and gait signals, and classical IIR filters (Butterworth, Chebyshev, elliptic) involve trade-offs between passband flatness, ripple, and roll-off. This study compared a novel exponential “Reza” filter with these designs for neural and locomotor data. We analyzed an open-source mobile brain–body imaging dataset with EEG and gait data from 49 healthy adults (EEG: $256$-channel, $512 \mathrm{H}\mathrm{z}$; IMUs: six APDM Opals, $128 \mathrm{H}\mathrm{z}$). EEG channels were grand-averaged and band-pass filtered at $0.5–50 \mathrm{H}\mathrm{z}$, while IMU axes were averaged and band-pass filtered at $0.5–5 \mathrm{H}\mathrm{z}$. The outcomes were signal-to-noise ratio SNR (dB) and band-integrated Welch PSD ($\mathrm{E}\mathrm{E}\mathrm{G}:0.5–50 \mathrm{H}\mathrm{z}; \mathrm{I}\mathrm{M}\mathrm{U}:0.5–5 \mathrm{H}\mathrm{z}$). Repeated-measures ANOVAs tested the effect of filter types (Butterworth, Chebyshev I, elliptic, Reza) with Bonferroni-adjusted post hoc tests for the six pairwise filter comparisons (${\alpha }_{adj} = 0.0083$). We reported partial eta-squared ($\eta p^2$) as the ANOVA effect size. For EEG, PSD did not differ among filters $(p = 0.146)$, whereas SNR differed strongly $(p<0.001)$: Chebyshev and elliptic yielded the highest mean SNR and did not differ from each other, while both exceeded Butterworth, Reza was the lowest. For IMU, both SNR $(p< 0.001$) and PSD $(p< 0.001)$ differed: Reza produced the highest mean SNR (significantly exceeding elliptic and Chebyshev), while Butterworth exceeded Chebyshev; meanwhile, IMU PSD showed a clear ordering with Reza retaining the most motion-band power, followed by Butterworth, then Chebyshev, with elliptic retaining the least. These results showed that filter choice materially shapes EEG and gait outcomes. For EEG, Chebyshev maximized SNR, while elliptic and Reza maintained comparable fidelity. For IMU gait signals, Reza matched Butterworth for denoising and preserved more signal power. Therefore, filter choice should be guided by the target outcome (SNR vs. band power) rather than a single default design. Full article

The brewing process generates substantial by-products rich in potentially bioactive compounds (e.g., polyphenols and fermentation metabolites), providing a sustainable and appealing source of cosmetic ingredients. Oil-in-water (O/W) emulsions containing 20% (w/w) aqueous extracts from Bionda Triplo Malto beer, wort, and key brewing by-products (hops, yeast, and spent grain) were developed and evaluated using a combined in vitro–in vivo approach. Aqueous extracts were first screened on human immortalized dermal fibroblasts (BJ-5ta) at 0.25–1 mg/mL for cytocompatibility and antioxidant activity. Within this concentration range, no significant changes in cell viability or intracellular antioxidant capacity under UV stress were detected, suggesting cytocompatibility but limited inherent activity. When incorporated into O/W emulsions and tested at an active-equivalent concentration of 10 mg/mL, the formulations increased fibroblast metabolic activity and antioxidant response. In contrast, free extracts at 10 mg/mL showed concentration-dependent cytotoxicity for some matrices, with beer- and yeast-based emulsions demonstrating the strongest effects. The emulsions exhibited good physicochemical stability (pH ~5.7–6.2; viscosity 4750–5150 mPa·s), passed the ISO 11930:2012 challenge test, and were well tolerated in patch testing. In a double-blind, randomized split-forearm study on 50 healthy volunteers over 30 days, beer, yeast, and spent grain-based formulations improved skin parameters versus baseline. TEWL decreased (e.g., beer: 16.22 ± 5.12 to 10.77 ± 2.22 mg·m⁻²·h⁻¹; yeast: 16.29 ± 5.66 to 10.18 ± 1.08; spent grain: 14.45 ± 4.34 to 11.66 ± 2.28), hydration increased (beer: 35.15 ± 5.93 to 42.26 ± 3.78; yeast: 33.27 ± 4.87 to 42.92 ± 2.48; spent grain: 34.22 ± 5.19 to 41.16 ± 3.17, and elasticity improved for beer and yeast formulations (62.33 ± 3.27 to 70.24 ± 2.12 N/m) and yeast (61.21 ± 4.72 to 72.13 ± 5.55 N/m). Based on these findings, brewing-derived ingredients demonstrate potential as cosmetic actives, with formulation critically determining their clinical efficacy. Full article

In object detection, annotation cost and computational efficiency are important factors in iterative model improvement under standard benchmark settings. Active learning (AL) addresses this challenge by selecting informative samples for labeling; however, many detection-oriented AL methods incur substantial overhead due to repeated inference (e.g., augmentation-based consistency). This paper introduces Uncertainty3D, a lightweight uncertainty proxy designed for standard CNN-based object detectors. It leverages native pre-NMS predictions to estimate sample informativeness using a single forward pass. We propose a tri-dimensional formulation that captures inconsistencies in position, scale, and category across proposal-consistent predictions. Experiments on PASCAL VOC and MS COCO using representative CNN-based detectors (Faster R-CNN and RetinaNet) show competitive mAP versus representative baselines and about 3–$4\times$ faster uncertainty estimation than augmentation-based baselines. Full article

Clove (Syzygium aromaticum (L.) Merr. & L.M. Perry) essential oil (EO)-based nanoemulsions may have a promising future in eco-friendly herbicide development. Clove EO was found to have a high eugenol content of 87.27%. Organic-solvent-free nanoemulsions using clove EO as a bioactive ingredient were fabricated using ultrasonication and microfluidization emulsification methods. Fourier-transform infrared spectroscopy confirmed that both emulsification methods did not affect the EO components. The droplet size of optimized nanoemulsions was determined using dynamic light scattering. The smallest size of 66.9 nm was obtained by microfluidization at 20,000 psi and eight passes. Additionally, the smallest droplet size for a sonicated nanoemulsion was 103.9 nm, obtained by ultrasonication at 20% for 6 min. Transmission electron microscopy confirmed the droplet sizes of both optimized nanoemulsions. In a storage test, both optimized nanoemulsions were stored at 4 °C for at least four weeks. Finally, both nanoemulsions were evaluated on pre-emergence herbicidal activities against Echinochloa crus-galli. The results showed that both nanoemulsions inhibited E. crus-galli germination and seedling growth, and additionally, inhibited seed imbibition and α-amylase activity. Micro-morphological and ultrastructural analysis was observed using a scanning electron microscope and an energy dispersive X-ray spectrometer (SEM-EDS). SEM-EDS micrographs of the treated seeds showed that the seed structure was damaged, especially the endosperm, leading to the inhibition of seed germination. Full article

Intrusion detectors are often evaluated using average metrics at unconstrained thresholds, yet deployments require explicit control over false alarms. We investigate zero-day (out-of-distribution, OOD) intrusion detection under a target-FPR calibrated protocol, where a threshold is set on benign validation traffic to satisfy a target false positive rate α and transferred, unchanged, to a seen-test and OOD-test. Using CICIDS2017-derived host-session nodes aggregated in 1 min and 5 min windows, we compare tabular baselines, message-passing GNNs on a rule-based graph, and employ a method that builds a k-nearest-neighbor similarity graph with lightweight feature pre-smoothing. Robustness is measured using the OOD violation ratio, percentile tail risk, and feasibility under explicit false-alarm budgets. Base-graph GNNs exhibit heavy-tailed false-alarm amplification under OOD shifts: at α = 0.001, the p95 violation ratio reaches 68.50 (1 m) and 67.95 (5 m). In contrast, the proposed method reduces p95 to 3.41 (1 m) and 1.15 (5 m) and improves budget feasibility. We further verify robustness beyond a single held-out family by evaluating additional unseen-family splits (e.g., DDoS and DDoS+DoS) under the same calibrated operating point. We also quantify deployment-oriented cost via edge-list size and practical parsing/loading time. These findings suggest that similarity-based graphs with light pre-smoothing improve deployability under distribution shifts. Full article

This work explores the mechanical responses of 3D-printed periodic arch-inspired structures (PASs) and PASs doped with NdFeB powder to advance their application in lightweight structural load-bearing and future structure–function integration. Three PAS configurations were fabricated via digital light processing (DLP), and magnetic PASs (MPASs) were produced by dispersing NdFeB powder (1–3 g/200 mL) into photosensitive resin. Under quasi-static compression, key mechanical properties—Young’s modulus (E), yield strength (σ_y), and compressive strength (σ_c)—of non-magnetic PASs increase linearly with relative density (ρ* = 0.18–0.48): for PAS22, E rises from 68.1 to 200.3 MPa (+194%), σ_y from 2.18 to 6.75 MPa (+210%), and σ_c from 2.98 to 9.07 MPa (+204%). Under dynamic impact (~100 s⁻¹), mechanical enhancement is even more pronounced: E of PAS22 surges to 814.8 MPa (3.2× higher than quasi-static), and σ_c reaches 11.54 MPa. Finite element simulations reveal that the Ideal Plastic Model best predicts quasi-static brittle fracture, whereas the Hardening Function Model captures dynamic behavior most accurately. Stress and plastic strain concentrate at the straight–arc junctions—identified as critical weak points. MPASs exhibit higher stiffness and yield strength (e.g., E of MPAS22 up to 896.5 MPa under impact) but lower compressive strength (e.g., 11.01 MPa vs. 11.54 MPa for NMPAS22), attributed to NdFeB-induced brittleness that shifts the failure mode from “local damage accumulation” to “rapid overall failure”. This study establishes quantitative doping–structure–property correlations, providing design guidelines for next-generation functional arch-inspired metamaterials toward magnetically responsive, load-bearing applications. Full article

We present E-CAHORS—a compact mid-infrared open-path diode-laser spectrometer designed for the simultaneous measurement of carbon dioxide, methane, and water vapor concentrations in the near-surface atmospheric layer. These measurements, combined with simultaneous data from a three-dimensional anemometer, can be used to determine fluxes using the eddy-covariance method. The instrument utilizes two interband cascade lasers operating at 2.78 µm and 3.24 µm within a novel four-pass M-shaped optical cell, which provides high signal power and long-term field operation without requiring active air sampling. Two detection techniques—tunable diode laser absorption spectroscopy (TDLAS) and a simplified wavelength modulation spectroscopy (sWMS)—were implemented and evaluated. Laboratory calibration demonstrated linear responses for all gases (R² ≈ 0.999) and detection precisions at 10 Hz of 311 ppb for CO₂, 8.87 ppb for CH₄, and 788 ppb for H₂O. Field tests conducted at a grassland site near Moscow showed strong correlations (R = 0.91 for CO₂ and H₂O, R = 0.74 for CH₄) with commercial LI-COR LI-7200 and LI-7700 analyzers. The TDLAS mode demonstrated lower noise and greater stability under outdoor conditions, while sWMS provided baseline-free spectra but was more sensitive to power fluctuations. E-CAHORS combines high precision, multi-species sensing capability with low power consumption (10 W) and a compact design (4.2 kg). Full article

Background: Among hormone therapy options for menopause, subcutaneous estradiol pellets offer sustained hormone release, avoid first-pass hepatic metabolism, and maintain a near-physiological estradiol-to-estrone ratio. Despite clinical use since the 1940s, standardized protocols remain lacking. Methods: We performed a critical narrative review following SANRA criteria. PubMed, Scopus, Embase, and LILACS were searched from 1949 to 2024 for randomized trials, cohort studies, and case series on estradiol pellets and outcomes in symptom control, bone health, pharmacokinetics, and safety. Animal studies, editorials, and reports without primary clinical data were excluded. Results: Following an initial peak within the first week, pellets maintain stable serum estradiol levels within the early-to-mid follicular range (50–113 pg/mL depending on dose) for four to six months, with a near-physiological E2:E1 ratio of approximately 1.5:1. The 25 mg dose achieves mean levels of 50–70 pg/mL, effectively controls vasomotor symptoms, and increases bone mineral density. Compared with oral estradiol, pellets bypass hepatic first-pass metabolism, resulting in neutral or favorable metabolic and thrombotic profiles. Compared with transdermal therapy, pellets provide more predictable pharmacokinetics, especially in women with low skin absorption. Safety concerns, including bleeding, tachyphylaxis, and supraphysiological levels, are mainly associated with excessive dosing, premature reimplantation, or lack of endometrial protection in women with a uterus. Conclusions: Estradiol pellets are an effective option for women with poor transdermal absorption, low adherence to daily regimens, or surgical menopause. Safety depends on clinical management with individualized dosing, adequate endometrial protection, and laboratory monitoring. Long-term comparative studies are needed to standardize protocols and support broader evidence-based use. Full article

Importance: The coronavirus disease 2019 (COVID-19) was the third leading cause of mortality in the United States for three years in a row. The genetic contributions to disease severity remain unclear and many previously identified single nucleotide polymorphisms (SNPs) have not been replicated nor linked with functional significance. Objective: To identify SNPs associated with mortality among hospitalized COVID-19 patients supplemented by expression quantitative trait loci (eQTL) evidence to infer plausible functional mechanisms related to COVID-19 severity. Design: A quality-controlled genome-wide association study (GWAS) supported by robust gene-level omnibus kernel association tests (SKAT-O), functional prediction, and eQTL analyses of the top GWAS signal. Setting: Massachusetts General Hospital (MGH). Participants: 370 adult ICU patients with SARS-CoV-2 infection and acute hypoxemic respiratory failure and floor patients with mild hypoxemia managed with supplemental oxygen consecutively admitted to MGH between March and June 2020 (Surge 1), and January and March 2021 (Surge 2) with baseline clinical characteristics and demographics collected. Exposures: Low-pass genotyped SNPs from whole blood and aggregated SNP-sets of potential disease susceptibility loci with $\pm$500 kb flanking regions. Main Outcomes & Measures: Genome-wide individual SNP associations and SNP-set associations with mortality outcomes from 370 severe COVID-19 cases. Results: After LD pruning (<0.8) and false discovery rate adjustment (<0.05), we identified rs7420371 G>A of the receptor transporter protein 5 (RTP5) gene as the top independent signal significantly associated with 30- and 60-day mortality among severe COVID-19 patients (OR, 2.32; 95% CI, 1.59–3.39; p = 4.92 × 10⁻⁹ and OR, 2.06; 95% CI, 1.43–2.97; p = 5.43 × 10⁻⁸, respectively). SKAT-O analyses on the RTP5 SNP-set showed associations with both mortality outcomes (p = 5.90 × 10⁻⁵ and 6.17 × 10⁻⁵, respectively). eQTL analysis showed rs7420371 A allele significantly upregulated the mRNA expression of RTP5 in 266 cerebellum tissues, in 277 cerebellar hemisphere tissues, and in 270 cerebral cortex samples. Conclusions & Relevance: We discovered a novel, independent, and potentially functional SNP RTP5 rs7420371 G>A to be significantly associated with COVID-19 mortality. The A allele is significantly associated with elevated mRNA expression of RTP5 in the brain, an important protein coding gene that modulates olfactory binding and taste perceptions in response to SARS-CoV-2 infection. Full article

Introduction: Percutaneous renal biopsy (PRB) is the gold standard for diagnosing nephropathies, but it carries a risk of bleeding complications, mainly perinephric hematomas (PHs). While PH incidence is often reported, the significance of PH size remains insufficiently explored. This scoping review systematically mapped the evidence on PH size after ultrasound-guided PRB in adults, focusing on imaging modalities, measurement methods, the definition of ‘large’ PH, factors influencing PH size, and its clinical implications. Materials and Methods: Following the Joanna Briggs Institute methodology, we searched PubMed/MEDLINE, Embase, Cochrane CENTRAL, and Scopus through 27 August 2025. Eligible studies included at least 50 adult subjects undergoing ultrasound-guided PRB with quantitative, imaging-based assessment of PH size. Results: Fifty-one studies met the inclusion criteria. Almost all relied on ultrasound, with only one using computed tomography. PH size was measured using heterogeneous methods, most often one-dimensional diameters, less frequently surface area or volumetry, with no standardization. Reported PH frequencies varied substantially across studies (1.1–85%), likely reflecting differences in imaging protocols, timing, and reporting thresholds. Several studies proposed PH size thresholds (e.g., diameter ≥ 2–3 cm, volume ≥ 40–85 mL) linked to adverse outcomes such as transfusion or hemodynamic instability. Factors associated with larger PHs included needle gauge, number of passes, impaired kidney function, coagulopathy, and certain histopathologies. Conclusions: PH size has prognostic value beyond incidence alone. Standardized measurement and reporting are needed to clarify its clinical relevance after PRB. Full article

Introduction: We aimed to clarify the influence of the thrombus composition on ischemic stroke endovascular thrombectomy (EVT) efficiency by utilizing various staining methods for patients that presented with occlusions of the middle cerebral artery (MCA). Methods: Between September 2017 and May 2021, we analyzed thrombi retrieved during endovascular thrombectomy EVT in patients with acute ischemic stroke due to middle cerebral artery (MCA) occlusion. Patients with reperfusion failure, intracranial atherosclerotic occlusions, and inadequate staining were excluded. The thrombus composition was stratified using three staining techniques—Hematoxylin and Eosin (H&E), Martius Scarlet Blue (MSB) staining, and immunohistochemistry (IHC) for red blood cells (RBCs), white blood cells (WBCs), fibrin (Fibrin II), and platelets (CD41). Associations between EVT efficiency outcomes and the thrombus composition were evaluated. Results: During the study period, thrombus was available for analysis in 159 patients. A total of 59 patients were included in the main analysis. Increases in the trichotomized RBS tertiles were associated with decreases in the components of various platelet/other components but not for fibrin. A modified first pass effect (mFPE) of the modified Thrombolysis in Cerebral Infarction perfusion scale (mTICI) 2b or higher was associated with larger thrombus surface area (16.0 ± 11.6 vs. 47.4 ± 62.3 mm², p = 0.005), a higher MSB fibrin content (29.8 ± 10.7 vs. 21.3 ± 10.9%, p = 0.002), and IHC fibrin (28.5 ± 14.5 vs. 20.1 ± 11.4%, p = 0.008). There was a marginal association between the mTICI 2b mFPE and lower MSB platelet/other components (27.6 ± 20.9 vs. 34.4 ± 14.9%, p = 0.078). The discrepancy between MSB platelet/others and IHC platelets was greater in the mFPE (-) group, suggesting that components other than platelets may contribute to EVT resistance. A mFPE of mTICI 2c or higher was associated with greater thrombus surface area (17.8 ± 11.9 vs. 37.7 ± 55.0 mm², p = 0.015) and MSB fibrin (32.1 ± 10.3 vs. 22.8 ± 11.0%, p = 0.002). There was a marginal reverse association between the mTICI 2c mFPE and MSB RBCs (33.4 ± 20.2% vs. 41.5 ± 17.3%, p = 0.062). There was no significant association between final near-complete reperfusion and the thrombus composition. Conclusions: In patients presenting with occlusions of the MCA, a higher thrombus fibrin content is associated with better EVT efficiency. Both a higher MSB platelet/other components and RBC content may have a negative influence on EVT efficiency. These results may help identify preprocedural biomarkers beyond the conventional assessment of RBCs, WBCs, and fibrin compositions, which could guide decision-making during mechanical thrombectomy. Full article

Background/Objectives: The aim of this study was to establish the relationship between target size and the required diagnostic PET maximum standard uptake value (SUVmax) thresholds needed for successful Biology-guided Radiotherapy (BgRT) delivery on RefleXion X1 PET-linac. The current clinical eligibility recommendation is an SUVmax ≥ 6 at simulation, but the RefleXion system subsequently evaluates Activity Concentration (AC), which must exceed 5 kBq/mL for successful BgRT planning. Methods: A custom 3D-printed phantom containing six spherical targets (8 to 20 mm diameter) was used with varying target-to-background ratios (5:1 to 20:1) of 18F-FDG to systematically achieve a range of SUVmax values for each target size. Images were acquired on Siemens Biograph mCT for SUVmax quantification and RefleXion X1 for AC measurements. Twenty-four BgRT plans were evaluated, and delivery accuracy was validated using ArcCHECK. Additionally, retrospective data from 18 patients across four institutions were analyzed to validate the phantom-derived findings. Results: The PET-linac successfully planned treatments for 13/24 experiments, all achieving an AC > 5 kBq/mL. SUVmax requirements varied by target size: 16–20 mm targets required an SUVmax > 6, consistent with current recommendations, while smaller targets required higher thresholds (e.g., 13 mm: SUVmax > 10, and 11 mm: SUVmax > 15). 8 and 9 mm targets failed to meet AC requirements even at SUVmax 14. Successful deliveries maintained acceptable accuracy, with gamma passing rates of 92.4% ± 5.0% (3%/2 mm) and 97.6% ± 1.9% (3%/3 mm). Analysis revealed that Volume (cc) × SUVmax > 11 consistently predicted successful BgRT planning across all target sizes. This threshold was validated using multi-institutional PET-CT patient data (mean: 11.36, 95% CI: 9.1–12.9), correctly predicting treatment eligibility in 15 of 18 cases. Conclusions: Target size significantly influences BgRT eligibility. We derived a new criterion, Volume(cc) × SUVmax > 11 (95% CI: 9.1–12). Full article