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Maternal oxytocin mitigates offspring autism-like phenotypes and oxytocin system alterations through improved maternal care
Dynamic Adaptive Interfaces Enable Zn-Iodine Hydrogel Batteries with High Areal Capacity and Low Self-Discharge
Explainability guided model collapse mitigation for synthetic data driven wireless decision systems
Those who forget
Programmable Surface Catalyzed Heterogeneous Nucleation Enables “Double-Cable” Light-Harvesting Supramolecular Polymers
A robust biometric system using wrist and dorsal vein images for person authentication
How to advance revolutionary science: high turnover, high risk and a licence to fail
Reversible Nucleolar Complex Coacervation by Short Cationic Peptides
Pressure surge and blade torque during shutdown of in-pipe drag-based turbines
Breast cancer driver genes found by screening chromosome aberrations in vivo
Aligning Chemical Kinetics with Crystallization Enables Millimeter-Scale Single Crystals of Conductive MOFs
A continuous differential evolution algorithm for solving uncapacitated facility location problems
Robust $${\text{Z}}_{{{\text{eff}}}}$$-mapping in composites via joint beam-hardening and detector-response correction
Abstract Quantitative effective atomic number ( $$Z_{eff}$$ ) inversion in energy-resolved X-ray projection imaging is affected by beam hardening and detector-response-induced spectral distortion. In this study, we propose a joint beam-hardening and detector-response correction framework for thickness-decoupled $$Z_{eff}$$ inversion. A folded-spectrum forward model was established by incorporating the polychromatic X-ray source spectrum, material-dependent attenuation, and the detector response matrix of the energy-resolved photon-counting detector. Based on this model, a response-corrected spectral database was constructed using Monte Carlo simulation. The spectral mass-attenuation linearisation method was then used to reduce the nonlinear attenuation behavior caused by beam hardening, followed by $$Z_{eff}$$ inversion through reliability-weighted least-squares spectral matching. Experimental validation was performed using standard low to middle $$Z_{eff}$$ materials with theoretical $$Z_{eff}$$ values ranging from 6.5 to 13.0 under four mass-thickness conditions $$\rho t$$ = 3.0–9.0 g/cm 2 . The results showed improved thickness stability and quantitative agreement within the calibrated material and thickness range. The method was further applied to carbon-fiber-reinforced polymer specimens containing aluminium foil and optical-fiber inclusions. The resulting $$Z_{eff}$$ maps provided material-dependent contrast beyond conventional grayscale attenuation, suggesting the potential of the proposed framework for qualitative or semi-quantitative material discrimination in composite non-destructive testing.
Tunable Microporous Bimetallic Carboxylate-Pyrazolate Metal–Organic Frameworks for CO <sub>2</sub> Capture
A privacy-aware healthcare framework with model pattern-deviation detection for heart-disease prediction using L2-GNAE and PDDP
Abstract Sensitive patient data protection is essential to ensure medical reliability in healthcare. Yet, the traditional studies didn’t analyze the deviation in the shared model pattern, thus resulting in poor diagnosis. Therefore, this article proposes a privacy-aware healthcare framework with model pattern deviation detection for Heart Disease (HD) prediction using L2 Gini Norm Auto-Encoder (L2-GNAE) and Polynomial Differential Decay Privacy (PDDP). Firstly, the patients are registered into the healthcare applications, followed by data sensing, data encryption, and hash code generation. Meanwhile, to authenticate the data integrity, the data decryption and hash code verification are done. During testing, the verified data is subjected to the trained proposed local model for HD prediction. Next, to perform model privacy, PDDP is used. Afterward, to effectively classify the HD, the Triple Gated Lipschitz Recurrent Unit (TGLRU) is utilized. Also, the local model gradients are updated in the global model, where L2-GNAE is utilized to detect the deviations in the shared model pattern. If the deviation is detected, then the alert is sent to the hospital; otherwise, the model update is carried out. The experimental testing of the proposed framework is done by using the “Heart Disease Prediction Dataset”. From the validation, the proposed framework achieves 99.2145% accuracy, 99.0237% precision, and 99.1046% F-measure during HD prediction. Thus, the proposed work significantly outperforms the traditional works by obtaining a high security level (256 bits) with enhanced privacy-preserved HD prediction in healthcare maintenance.
Inhalable Polymeric PROTAC Nanococktail for Targeted Protein Degradation in Idiopathic Pulmonary Fibrosis
Neonatal hypoxic ischemia in rats induces myelin injury and structural lateralization of sensorimotor connectivity
Abstract Neonatal hypoxic ischemia (HI) around the birth impairs structural and functional networks in the whole brain, leading residual motor impairment necessary for therapeutic intervention. Myelin, which is essential for sensorimotor functional improvement, increases around the birth but is susceptible to HI. However, the involvement of myelin injury in the structural network changes in the brain after HI remains unclear. To investigate this issue, we clarified the relationship between the brain’s structural network and myelin injury by using HI rat model. The HI rat model was established by transecting the right common carotid artery (CCA) and exposure to a hypoxic environment containing 8% oxygen for 90 minutes. Using ex vivo diffusion tensor imaging (DTI) and immunohistology, the changes in myelin sheaths in the corpus callosum (CC) and the structural network of the whole brain were analyzed. HI rats showed significantly decreased fractional anisotropy and increased radial diffusivity in the CC ipsilateral to CCA transection compared with the Sham group (n = 6/group, p < 0.05, respectively). Immunohistology revealed a decreased myelin density in the ipsilateral CC of HI rats compared with the Sham group ( n = 6/group, p < 0.05). Furthermore, in structural connectome analysis, HI rats showed significantly decreased connectivity in the ipsilateral hemisphere compared with Sham group ( p < 0.01). Particularly, the ipsilateral M1-S1 and bilateral S1-striatum connectivity of HI rats showed significantly reduced tract numbers compared with Sham rats ( p < 0.05, respectively). These results suggest myelin damage following HI disrupts structural connectivity in the ipsilateral hemisphere, including the M1-S1 and S1-striatum connectivity. Furthermore, these findings identified the S1-centered structural network alterations as key contributors to brain dysfunction, such as motor impairment, after HI, and could highlight these networks as potential targets for therapeutic interventions to promote functional recovery.
Repetitive Ethylene Insertion into the Pd–OAc Bond: Synthesis of Heterotelechelic Polyethylene and Effective Copolymerization of Ethylene with Vinyl or Allyl Acetate
Cloud point thermodynamics and phase behavior of EVOH–DMSO systems for selective polymer recycling
Abstract Understanding phase behavior of polymer-solvent mixtures is crucial for applications ranging from plastic recycling to crude oil extraction from reservoirs. One method for investigating polymer-solvent solution behavior is through understanding the cloud point thermodynamics. In this study, the cloud points of three different grades of ethylene vinyl alcohol (EVOH) copolymers (27 mol%, 32 mol%, and 48 mol% ethylene content) are characterized in dimethyl sulfoxide solutions for two conditions: isobaric-non-isothermal and isothermal-non-isobaric. Notably, increasing ethylene content in the EVOH copolymer shifts the cloud point to higher temperatures and pressures. Additionally, cloud points for EVOH in DMSO/Water (solvent-antisolvent) mixtures were characterized to optimize solvent use and polymer recovery. The combined cloud point data is used to construct a working phase diagram, delineating an EVOH grade-based separation zone, defining a boundary between homogenous and phase separated regions. These results contribute to our understanding of EVOH solution phase behavior and are critical for optimizing solvent requirements for selective polymer recycling technologies, enhancing dissolution efficiency, and sustainability in polymer processing. Furthermore, insights into the phase separation behavior of EVOH support more efficient separation strategies in multilayer packaging systems, enabling targeted extraction of EVOH from complex waste streams and facilitating high-purity recovery for reuse.