The diagnosis of fetal micrognathia with two-dimensional and real-time three-dimensional color Doppler ultrasound.

Background: The study describes the diagnose of fetal micrognathia by the two-dimensional and real-time three-dimensional color doppler ultrasound, and evaluates its clinical value.

Methodology: The case group comprised 100 fetuses with highly suspected mandibular deformity, and the control group consisted of 100 normal fetuses. Various ultrasonic equipments and multimedia data processing system were used to obtain 2D and 3D images of fetal mandible, and the Biparietal Diameter (BPD) and Fetal Mandibular Longitudinal Diameter (FML) were measured.

Topochemical photocycloaddition in two-dimensional lead-halide coordination polymers with tunable phosphorescence.

Topochemical transformation in which the parent structural motifs are preserved has become a powerful strategy to access new advanced materials. Solid-state topochemical conversion in a single-crystal-to-single-crystal (SCSC) fashion is particularly attractive as it provides design principles with unequivocal structural details. Here, we report a series of two-dimensional (2D) lead-halide coordination polymers with bipyridyl ethylene (bpe) ligands that can undergo quantitative SCSC [2 + 2] photocycloaddition.

Flex multimode neural network for complete optical computation.

Compact and efficient photonic integrated circuits (PICs) are promising route to solving modern computing challenges. Traditional PICs using cascaded Mach-Zehnder Interferometers (MZIs) or micro-ring resonators (MRRs) are limited to rigid linear matrix operations, requiring electronics for data compression, nonlinear activation, and post-processing. The dependence on electronic processing counteracts the advantages brought by photonics.

Identification and validation of pyroptosis patterns in AML via comprehensive bioinformatics analysis.

Pyroptosis, a lytic inflammatory cell death mechanism, plays dual roles in tumorigenesis, but its clinical relevance in acute myeloid leukemia (AML) remains poorly understood. Through an integrative analysis of 40 pyroptosis-related genes in newly diagnosed AML patients (TCGA, n = 151) and healthy controls (GTEx, n = 386), we identified 32 genes with aberrant expression. Among these, 9 genes were found to be significant prognostic markers, including ELANE (protective), and CASP1, CHMP4B, BAK1, and CHMP2A (risk), which retained their prognostic significance after adjusting for age and gender.

Replace2Self: Self-Supervised Denoising Based on Voxel Replacing and Image Mixing for Diffusion MRI.

Low signal to noise ratio (SNR) remains one of the limitations of diffusion weighted (DW) imaging. How to suppress the influence of noise on the subsequent analysis about the tissue microstructure is still challenging. This work proposed a novel self-supervised learning model, Replace2Self, to effectively reduce spatial correlated noise in DW images.

Hydrophobic Metal-Formate Composites for Efficient CO Capture.

Carbon capture, utilization, and sequestration (CCUS) have emerged as pivotal mitigation strategies in addressing climate change induced by greenhouse gas emissions. In this pursuit, our objective is to enhance the efficacy of adsorptive CO capture by harnessing state-of-the-art framework sorbents engineered for exceptional CO selectivity, high intrinsic stability in the presence of moisture, and facile regeneration. To this end, a series of ultramicroporous mixed aluminum and iron formate framework materials, Fe-ALFs, were synthesized.

Self-supervised arbitrary-scale super-angular resolution diffusion MRI reconstruction.

Background: Diffusion magnetic resonance imaging (dMRI) is currently the unique noninvasive imaging technique to investigate the microstructure of in vivo tissues. To fully explore the complex tissue microstructure at sub-voxel scale, diffusion weighted (DW) images along many diffusion gradient directions are usually acquired, this is undoubtedly time consuming and inhibits their clinical applications. How to estimate the tissue microstructure only from DW images acquired with few diffusion directions remains a challenge.

Cooperative multi-task learning and interpretable image biomarkers for glioma grading and molecular subtyping.

Deep learning methods have been widely used for various glioma predictions. However, they are usually task-specific, segmentation-dependent and lack of interpretable biomarkers. How to accurately predict the glioma histological grade and molecular subtypes at the same time and provide reliable imaging biomarkers is still challenging.

Predicting thermodynamic stability of inorganic compounds using ensemble machine learning based on electron configuration.

Machine learning offers a promising avenue for expediting the discovery of new compounds by accurately predicting their thermodynamic stability. This approach provides significant advantages in terms of time and resource efficiency compared to traditional experimental and modeling methods. However, most existing models are constructed based on specific domain knowledge, potentially introducing biases that impact their performance.

The mode detangler.

Astrophotonics aims to transfer photonic technology to the development of compact astronomical instruments. However, light coupling from a multimode fiber, typically adopted in modern observatories, to a single-mode photonic device still poses a challenge. Though a photonic lantern can enable this transition in a low-loss way, it requires that the number of single-mode fibers (SMFs) at the output is the same as the number of guided modes in the multimode fiber, resulting in a cumbersome fan-out of many single-mode devices to be connected.

Deep learning method with integrated invertible wavelet scattering for improving the quality ofcardiac DTI.

Respiratory motion, cardiac motion and inherently low signal-to-noise ratio (SNR) are major limitations ofcardiac diffusion tensor imaging (DTI). We propose a novel enhancement method that uses unsupervised learning based invertible wavelet scattering (IWS) to improve the quality ofcardiac DTI.Our method starts by extracting nearly transformation-invariant features from multiple cardiac diffusion-weighted (DW) image acquisitions using multi-scale wavelet scattering (WS).

Enhancing multiple myeloma staging: a novel cell death risk model approach.

The prognostication of survival trajectories in multiple myeloma (MM) patients presents a substantial clinical challenge. Leveraging transcriptomic and clinical profiles from an expansive cohort of 2,088 MM patients, sourced from the Gene Expression Omnibus and The Cancer Genome Atlas repositories, we applied a sophisticated nested lasso regression technique to construct a prognostic model predicated on 28 gene pairings intrinsic to cell death pathways, thereby deriving a quantifiable risk stratification metric. Employing a threshold of 0.

EO nonlinear function generator.

An electro-optical programmable nonlinear function generator (PNFG) is developed on a multimode waveguide with four parallel thermal electrodes. The current on one electrode is chosen as the input, while the rest serve as function-defining units to modulate the multimode interference. The electro-thermo-optical effects are analyzed step by step and the impact on the eigenmode properties is derived.

0D Pyramid-intercalated 2D Bimetallic Halides with Tunable Electronic Structures and Enhanced Emission under Pressure.

Hybrid metal halides are emerging semiconductors as promising candidates for optoelectronics. The pursuit of hybridizing various dimensions of metal halides remains a desirable yet highly complex endeavor. By utilizing dimension engineering, a diverse array of new materials with intrinsically different electronic and optical properties has been developed.

The evolution of data pricing: From economics to computational intelligence.

Data pricing, which aids in articulating the worth and advantages of data and encourages its opening, sharing, and circulation, is an indispensable component of data trading. Studies pertinent to the topic of data pricing are continuously developing. To undertake a thorough analysis of the literature in data pricing, we use bibliometric and statistical methods for the first time.

Hydrogen Storage with Aluminum Formate, ALF: Experimental, Computational, and Technoeconomic Studies.

Long-duration storage of hydrogen is necessary for coupling renewable H with stationary fuel cell power applications. In this work, aluminum formate (ALF), which adopts the ReO-type structure, is shown to have remarkable H storage performance at non-cryogenic (>120 K) temperatures and low pressures. The most promising performance of ALF is found between 120 K and 160 K and at 10 bar to 20 bar.

As-Grown Miniaturized True Zero-Order Waveplates Based on Low-Dimensional Ferrocene Crystals.

As basic optical elements, waveplates with anisotropic electromagnetic responses are imperative for manipulating light polarization. Conventional waveplates are manufactured from bulk crystals (e.g.

Noncryogenic Air Separation Using Aluminum Formate Al(HCOO) (ALF).

Separating oxygen from air to create oxygen-enriched gas streams is a process that is significant in both industrial and medical fields. However, the prominent technologies for creating oxygen-enriched gas streams are both energy and infrastructure intensive as they use cryogenic temperatures or materials that adsorb N from air. The latter method is less efficient than the methods that adsorb O directly.

Self-supervised structural similarity-based convolutional neural network for cardiac diffusion tensor image denoising.

Background: Diffusion tensor imaging (DTI) is a promising technique for non-invasively investigating the myocardial fiber structures of human heart. However, low signal-to-noise ratio (SNR) has been a major limit of cardiac DTI to prevent us from detecting myocardium structure accurately. Therefore, it is important to remove the effect of noise on diffusion weighted (DW) images.

Achieving Near-unity Photoluminescence Quantum Yields in Organic-Inorganic Hybrid Antimony (III) Chlorides with the [SbCl ] Geometry.

Hybrid organic-inorganic antimony halides have attracted increasing attention due to the non-toxicity, stability, and high photoluminescence quantum yield (PLQY). To shed light on the structural factors that contribute to the high PLQY, five pairs of antimony halides with general formula A SbCl and A Sb Cl are synthesized via two distinct methods and characterized. The A SbCl type adopts square pyramidal [SbCl ] geometry with near-unity PLQY, while the A Sb Cl adopts seesaw dimmer [Sb Cl ] geometry with PLQY≈0 %.

Variable Temperature Behaviour of the Hybrid Double Perovskite MAKBiCl.

Perovskite-related materials show very promising properties in many fields. Pb-free perovskites are particularly interesting, because of the toxicity of Pb. In this study, hybrid double perovskite MAKBiCl (MA = methylammonium cation) was found to have interesting variable temperature behaviours.