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Due to the relentless exploitation of nonrenewable resources, humanity is faced with a resource depletion crisis in the coming decades and serious environmental issues. Achieving efficient removal and upcycling of pollutants (ERUP) may become a potential strategy to address these issues. Wastewater, characterized by its large production volume and fluidity, can easily cause widespread environmental pollution through natural water networks. Due to solubility constraints, pollutants in wastewater typically exhibit low concentrations and complex compositions, thereby impeding effective recovery. Therefore, achieving ERUP in wastewater is both highly significant and extremely challenging. Unlike conventional wastewater treatment strategies that are focused on removing pollutants, ERUP strategies can not only realize the efficient removal of pollutants from water but also convert pollutants into valuable and functional products. Herein, we enumerated the latest research progress on ERUP in wastewater and highlighted studies that demonstrate the simultaneous achievement of pollutant removal and the direct conversion of these contaminants into high-efficiency catalysts, hydrogen energy, electrical energy, and other high-value chemicals. Finally, we identified the problems and challenges in the development of ERUP in wastewater and outlined potential research directions for future studies. [ABSTRACT FROM AUTHOR]

Myopia is a serious threat to eye health and can even cause blindness. It is important to grade myopia and carry out targeted intervention. Nowadays, various studies using deep learning models based on optical coherence tomography (OCT) images to screen for high myopia. However, since regions of interest (ROIs) of pre-myopia and low myopia on OCT images are relatively small, it is rather difficult to use OCT images to conduct detailed myopia grading. There are few studies using OCT images for more detailed myopia grading. To address these problems, we propose a novel attention-based multi-scale feature fusion network named AMFF for myopia grading using OCT images. The proposed AMFF mainly consists of five modules: a pre-trained vision transformer (ViT) module, a multi-scale convolutional module, an attention feature fusion module, an Avg-TopK pooling module and a fully connected (FC) classifier. Firstly, unsupervised pre-training of ViT on the training set can better extract feature maps. Secondly, multi-scale convolutional layers further extract multi-scale feature maps to obtain more receptive fields and extract scale-invariant features. Thirdly, feature maps of different scales are fused through channel attention and spatial attention to further obtain more meaningful features. Lastly, the most prominent features are obtained by the weighted average of the highest activation values of each channel, and then they are used to classify myopia through a fully connected layer. Extensive experiments show that our proposed model has the superior performance compared with other state-of-the-art myopia grading models. [ABSTRACT FROM AUTHOR]

The existing physical layer security schemes, which are based on the key generation model and the wire-tap channel model, achieve security by utilizing channel reciprocity entropy and noise entropy, respectively. In contrast, we propose a novel secure transmission framework that combines noise entropy with reciprocity entropy, achieved by inserting reciprocity entropy into the frozen bits of polar codes. Note that in real-world scenarios, when eavesdroppers employ polynomial-time attacks, the bit error rate (BER) increases due to the introduction of computational entropy. To achieve indistinguishability security, we convert the practical physical layer security metric, BER, into the average min-entropy, a widely accepted concept in cryptography. The simulation results demonstrate that the eavesdropper's BER can be significantly increased without compromising the communication performance of the legitimate receiver. Under concrete parameters we selected, when compared to the joint scheme of physical layer key generation and one time pad, the modular semantically-secure scheme based on the wire-tap channel model, and the simple channel entropy combination scheme, our scheme achieves a message rate approximately 1.2 times, 3.8 times, and 1.4 times better, respectively. Experimental testing validates the feasibility of our scheme. [ABSTRACT FROM AUTHOR]

Atmospheric radiation is a major branch of atmospheric physics that encompasses the fundamental theories of atmospheric absorption, particle scattering (aerosols and clouds), and radiative transfer. Specifically, the simulations of atmospheric gaseous absorption and scattering properties of particles are the essential components of atmospheric radiative transfer models. Atmospheric radiation has important applications in weather, climate, data assimilation, remote sensing, and atmospheric detection studies. In Part I, a comprehensive review of the progress in the field of gas absorption and particle scattering research over the past 30 years with a particular emphasis on the contributions from Chinese scientists is presented. The review of gas absorption includes the construction of absorption databases, the impact of different atmospheric absorption algorithms on radiative calculations, and their applications in weather and climate models and remote sensing. The review on particle scattering starts with the theoretical and computational methods and subsequently explores the optical modeling of aerosols and clouds in remote sensing and atmospheric models. Additionally, the paper discusses potential future research directions in this field. [ABSTRACT FROM AUTHOR]

As a highly vascular eye part, the choroid is crucial in various eye disease diagnoses. However, limited research has focused on the inner structure of the choroid due to the challenges in obtaining sufficient accurate label data, particularly for the choroidal vessels. Meanwhile, the existing direct choroidal vessel segmentation methods for the intelligent diagnosis of vascular assisted ophthalmic diseases are still unsatisfactory due to noise data, while the synergistic segmentation methods compromise vessel segmentation performance for the choroid layer segmentation tasks. Common cascaded structures grapple with error propagation during training. To address these challenges, we propose a cascade learning segmentation method for the inner vessel structures of the choroid in this paper. Specifically, we propose Transformer-Assisted Cascade Learning Network (TACLNet) for choroidal vessel segmentation, which comprises a two-stage training strategy: pre-training for choroid layer segmentation and joint training for choroid layer and choroidal vessel segmentation. We also enhance the skip connection structures by introducing a multi-scale subtraction connection module designated as MSC, capturing differential and detailed information simultaneously. Additionally, we implement an auxiliary Transformer branch named ATB to integrate global features into the segmentation process. Experimental results exhibit that our method achieves the state-of-the-art performance for choroidal vessel segmentation. Besides, we further validate the significant superiority of the proposed method for retinal fluid segmentation in optical coherence tomography (OCT) scans on a publicly available dataset. All these fully prove that our TACLNet contributes to the advancement of choroidal vessel segmentation and is of great significance for ophthalmic research and clinical application. [ABSTRACT FROM AUTHOR]

Purpose: To optimize chemotherapy regimens and improve the effectiveness of chemotherapy combined with immunotherapy, a PET tracer specifically targeting the stimulator of interferon genes (STING), denoted as [18F]FBTA was used to monitor the early changes in tumor immunogenicity after chemotherapy in colorectal cancer (CRC) mice. Methods: The toluene sulfonate precursor was labeled with 18F to produce the STING targeted probe—[18F]FBTA. [18F]FBTA-PET imaging and biodistribution were performed using CRC mice treated with oxaliplatin (OXA) or cisplatin (CDDP). CRC mice were also treated with low (CDDP-LD: 1 mg/kg) or medium (CDDP-MD: 2.5 mg/kg) doses of CDDP, and subjected to PET imaging and biodistribution. The effects of different chemotherapeutic agents and different doses of CDDP on tumor innate immunity were verified by flow cytometry and immunohistochemistry. Results: PET imaging of CRC mice exhibited notably enhanced tumor uptake in the early phase of chemotherapy with treatment with OXA (3.09 ± 0.25%ID/g) and CDDP (4.01 ± 0.18%ID/g), especially in the CDDP group. The PET-derived tumor uptake values have strong correlations with STING immunohistochemical score. Flow cytometry showed both agents led to DCs and macrophages infiltration in tumors. Compared with OXA, CDDP treatment recruits more DCs and macrophages in CRC tumors. Both CDDP-LD and CDDP-MD treatment elevated uptake in CRC tumors, especially in CDDP-MD group. Immunohistochemistry and flow cytometry confirmed CDDP-MD treatment recruits more DCs and macrophages than CDDP-LD treatment. Conclusion: Overall, the STING-targeted tracer—[18F]FBTA was demonstrated to monitor early changes in tumor immunogenicity in CRC mice after chemotherapy. Besides, the STING-targeted strategy may help to select the appropriate chemotherapy regimen, including chemotherapeutic agents and doses, which further improve clinical decision making for combination immunotherapy after chemotherapy for CRC. [ABSTRACT FROM AUTHOR]

Purpose: Prognostic prediction is crucial to guide individual treatment for locoregionally advanced nasopharyngeal carcinoma (LA-NPC) patients. Recently, multi-task deep learning was explored for joint prognostic prediction and tumor segmentation in various cancers, resulting in promising performance. This study aims to evaluate the clinical value of multi-task deep learning for prognostic prediction in LA-NPC patients. Methods: A total of 886 LA-NPC patients acquired from two medical centers were enrolled including clinical data, [18F]FDG PET/CT images, and follow-up of progression-free survival (PFS). We adopted a deep multi-task survival model (DeepMTS) to jointly perform prognostic prediction (DeepMTS-Score) and tumor segmentation from FDG-PET/CT images. The DeepMTS-derived segmentation masks were leveraged to extract handcrafted radiomics features, which were also used for prognostic prediction (AutoRadio-Score). Finally, we developed a multi-task deep learning-based radiomic (MTDLR) nomogram by integrating DeepMTS-Score, AutoRadio-Score, and clinical data. Harrell's concordance indices (C-index) and time-independent receiver operating characteristic (ROC) analysis were used to evaluate the discriminative ability of the proposed MTDLR nomogram. For patient stratification, the PFS rates of high- and low-risk patients were calculated using Kaplan–Meier method and compared with the observed PFS probability. Results: Our MTDLR nomogram achieved C-index of 0.818 (95% confidence interval (CI): 0.785–0.851), 0.752 (95% CI: 0.638–0.865), and 0.717 (95% CI: 0.641–0.793) and area under curve (AUC) of 0.859 (95% CI: 0.822–0.895), 0.769 (95% CI: 0.642–0.896), and 0.730 (95% CI: 0.634–0.826) in the training, internal validation, and external validation cohorts, which showed a statistically significant improvement over conventional radiomic nomograms. Our nomogram also divided patients into significantly different high- and low-risk groups. Conclusion: Our study demonstrated that MTDLR nomogram can perform reliable and accurate prognostic prediction in LA-NPC patients, and also enabled better patient stratification, which could facilitate personalized treatment planning. [ABSTRACT FROM AUTHOR]

Purpose: Ankylosing spondylitis (AS) is a chronic inflammatory disease of the axial spine; however, the quantitative detection of inflammation in AS remains a challenge in clinical settings. We aimed to investigate the feasibility of using a specific P2X7R-targeting 18F-labeled tracer [18F]GSK1482160 for positron emission tomography (PET) imaging and the quantification of AS. Methods: The radioligand [18F]GSK1482160 was obtained based on nucleophilic aliphatic substitution. Dynamic [18F]GSK1482160 and [18F]FDG micro-PET/CT imaging were performed on AS mice (n = 8) and age-matched controls (n = 8). Tracer kinetics modeling was performed using Logan's graphical arterial input function analysis to quantify the in vivo expression of P2X7R. The post-PET tissues were collected for hematoxylin–eosin (H&E), immunohistochemical (IHC), and immunofluorescence (IF) staining. Results: [18F]GSK1482160 PET/CT imaging revealed that the specific binding in the ankle joint and sacroiliac joint (SIJ) of the AS at 8 weeks group (BPNDankle−AS−8W (non-displaceable binding potential of the ankle) 3.931 ± 0.74; BPNDSIJ−AS−8W (BPBD of the SIJ) 4.225 ± 0.84) were significantly higher than the controls at 8 weeks group (BPNDankle−Ctr−8W 0.325 ± 0.15, BPNDSJJ−Ctr−8W 0.319 ± 0.17) respectively, and the AS at 14 weeks group (BPNDankle−AS−14W 12.212 ± 2.25; BPNDSJJ−AS−14W 13.389 ± 3.60) were significantly higher than the controls at 14 weeks group (BPNDankle−Ctr−14W 0.204 ± 0.16, BPNDSJJ−Ctr−14W 0.655 ± 0.35) respectively. The four groups had no significant difference in the [18F]FDG uptake of ankle and SIJ. IHC and IF staining revealed that the overexpression of P2X7R was colocalized with activated macrophages from the ankle synovium and spinal endplate in mice with AS, indicating that quantification of P2X7R may contribute to the understanding of the pathogenesis of inflammation in human AS. Conclusion: This study developed a novel P2X7R-targeting PET tracer [18F]GSK1482160 to detect the expression of P2X7R in AS mouse models and provided powerful non-invasive PET imaging and quantification for AS. [ABSTRACT FROM AUTHOR]

The Learning With Errors (LWE) problem is widely used in lattice-based cryptography, which is the most promising post-quantum cryptography direction. There are a variety of LWE-solving methods, which can be classified into four groups: lattice methods, algebraic methods, combinatorial methods, and exhaustive searching. The Blum–Kalai–Wasserman (BKW) algorithm is an important variety of combinatorial algorithms, which was first presented for solving the Learning Parity With Noise (LPN) problem and then extended to solve LWE. In this paper, we give an overview of BKW algorithms for solving LWE. We introduce the framework and key techniques of BKW algorithms and make comparisons between different BKW algorithms and also with lattice methods by estimating concrete security of specific LWE instances. We also briefly discuss the current problems and potential future directions of BKW algorithms. [ABSTRACT FROM AUTHOR]

Purpose: Here, we aim to identify a CEACAM5-targeted nanobody and demonstrate its application in positron emission tomography (PET) imaging and near-infrared (NIR) fluorescence imaging in colorectal cancer (CRC). Methods: Immunohistochemistry was applied to verify CEACAM5 expression in CRC and metastatic lymph nodes (mLNs). CEACAM5-targeted nanobodies were obtained by immunization of human CEACAM5 protein in a dromedary, followed by several rounds of phage screenings. Immunofluorescence staining and flow cytometry was carried out to determine the binding affinity of the nanobodies. The nanobodies were radiolabeled by coupling 18F-SFB for PET imaging of CRC subcutaneous xenografts and lymph node metastasis (LNM). IRDye800CW (IR800) were conjugated to form NIR probes for NIR imaging in CRC subcutaneous models. Results: CEACAM5 was overexpressed in either human CRC tissues or mLNs. A CEACAM5 targeted nanobody, Nb41 was successfully generated, with excellent in vitro binding properties. Incorporation of albumin binding domain (ABD) did not affect the affinity of Nb41. In vivo imaging showed that both 18F-FB-Nb41 and 18F-FB-Nb41-ABD showed obvious accumulation in the tumor. Due to the longer retention in the blood, 18F-FB-Nb41-ABD enrichment in tumors was significantly delayed but higher compared to 18F-FB-Nb41. Both 18F-FB-Nb41 and 18F-FB-Nb41-ABD showed prominent LNM enrichment. Similarly, the IR800-conjugated nanobodies Nb41-IR800 and Nb41-ABD-IR800 exhibited superior imaging effects in subcutaneous models, while Nb41-ABD-IR800 exhibited higher fluorescence intensity in the tumor accompanied with a remarkedly delay compared to Nb41-IR800. Conclusion: Collectively, we presented the identification and in vivo validation of a CEACAM5-targeted nanobody and a fused nanobody with an ABD, which enabled to the non-invasive visualization of malignancy of CRC using PET imaging and NIR imaging in subcutaneous models as well as LNM models. [ABSTRACT FROM AUTHOR]

Radiative transfer simulations and remote sensing studies fundamentally require accurate and efficient computation of the optical properties of non-spherical particles. This paper proposes a deep learning (DL) scheme in conjunction with an optical property database to achieve this goal. Deep neural network (DNN) architectures were obtained from a dataset of the optical properties of super-spheroids with extensive shape parameters, size parameters, and refractive indices. The dataset was computed through the invariant imbedding T-matrix method. Four separate DNN architectures were created to compute the extinction efficiency factor, single-scattering albedo, asymmetry factor, and phase matrix. The criterion for designing these neural networks was the achievement of the highest prediction accuracy with minimal DNN parameters. The numerical results demonstrate that the determination coefficients are greater than 0.999 between the prediction values from the neural networks and the truth values from the database, which indicates that the DNN can reproduce the optical properties in the dataset with high accuracy. In addition, the DNN model can robustly predict the optical properties of particles with high accuracy for shape parameters or refractive indices that are unavailable in the database. Importantly, the ratio of the database size (∼127 GB) to that of the DNN parameters (∼20 MB) is approximately 6810, implying that the DNN model can be treated as a highly compressed database that can be used as an alternative to the original database for real-time computing of the optical properties of non-spherical particles in radiative transfer and atmospheric models. [ABSTRACT FROM AUTHOR]

Purpose: Early diagnosis of sepsis-associated encephalopathy (SAE) is essential for the treatment and prognosis of septic patients. Static PET and MRI have shown promise for early diagnosis, while pharmacokinetic parameters from dynamic PET may provide better quantification for SAE. This study aims to compare the performance of dynamic 2-deoxy-2-[18F]fluoro-D-glucose ([18F]F-FDG) PET and multiparametric MRI in early imaging SAE with a view to providing guidance for the early diagnosis of SAE. Procedures: Dynamic [18F]F-FDG-PET/CT scans and multiparametric MRI were performed in SAE mice induced by LPS. Standardized uptake value (SUV) was measured in static scan images and [18F]F-FDG pharmacokinetic parameters were analyzed with two-tissue compartment model and Patlak plot. MRI relative signal intensity (rT1) derived from T1-weighted images (pre and post contrast) and 4 parameters originating from diffusion-weighted data were measured. Results: Both SUV and dephosphorylation rate constant (k4) increased in SAE model as early as 6 h post sepsis induction, while k4 increased with the relative value (SAE/normal) significantly stronger than that of SUV. Moreover, the net influx constant (Ki) showed significant decrease in SAE as early as 6 h compared with normal mice. Increased signal intensity was identified in T1-weighted contrast enhanced images and rT1 value increased at 12 h post induction. Diffusion tensor imaging (DTI) revealed fractional anisotropy (FA) decreased at 12 h and 24 h in external capsule (ec) and declined axial diffusivity (AD) was shown in white matter at 24 h. Conclusions: The dynamic PET (k4) was more sensitive than static PET (SUV) for early diagnosis of SAE and declined Ki was firstly found in murine SAE, which indicated the advantage of dynamic PET/CT in early detection and differential diagnosis of SAE. While MRI has a higher soft tissue resolution than PET/CT and can classify more subtle brain areas, the comprehensive utilization of the two modalities is helpful for managing SAE. [ABSTRACT FROM AUTHOR]

Purpose: Sigma-1 receptor (Sig-1R), a chaperone that resides at the mitochondrion-associated endoplasmic reticulum (ER) membrane, is an ER stress biomarker. It is thought that ER stress plays a critical role in the progression of metabolic-associated fatty liver disease (MAFLD). The aim of this study was to evaluate a positron emission tomography (PET) tracer [18F]F-TZ3108 targeting Sig-1R for MAFLD. Procedures: The mouse model of MAFLD was established by feeding high-fat diet (HFD) for 12 weeks. Dynamic (0–60 min) PET/CT scans were performed after intravenous injection of 2-deoxy-2[18F]fluoro-D-glucose ([18F]-FDG) and [18F]F-TZ3108. Tracer kinetic modeling was performed for quantification of the PET/CT imaging of the liver. Post-PET biodistribution, the liver tissue western blotting (WB), and immunofluorescence (IF) were performed to compare the expression of Sig-1R levels in the organs harvested from both MAFLD and age-matched control mice. Results: The micro PET/CT imaging revealed a significantly decreased uptake of [18F]F-TZ3108 in the livers of the MAFLD group compared to the healthy controls, while the uptake of [18F]-FDG in the livers was not significantly different between the two groups. Based on the tracer kinetic modeling, the binding disassociate rate (k4) for [18F]F-TZ3108 was significantly increased in MAFLD group compared to healthy controls. The volume distribution (VT), and the non-displacement binding potential (BPND) revealed significantly decrease in MAFLD compared to healthy controls respectively. The post-PET biodistribution (%ID/g) of [18F]F-TZ3108 in the livers of MAFLD mice was significantly reduced nearly twofold than that in the livers of control mice. WB and IF experiments further confirmed the reduction of Sig-1R expression in the MAFLD group. Conclusions: The expression of Sig-1R in the liver, measured by the PET tracer, [18F]F-TZ3108, was significantly decreased in mouse model of MAFLD. The [18F]F-TZ3108 PET/CT imaging may provide a novel means of visualization for ER stress in MAFLD or other diseases in vivo. [ABSTRACT FROM AUTHOR]

Metamaterials with artificial optical properties have attracted significant research interest. In particular, artificial magnetic resonances with non-unity permeability tensor at optical frequencies in metamaterials have been reported. However, only non-unity diagonal elements of the permeability tensor have been demonstrated to date. A gyromagnetic permeability tensor with non-zero off-diagonal elements has not been observed at the optical frequencies. Here we report the observation of gyromagnetic properties in the near-infrared wavelength range in a magneto-plasmonic metamaterial. The non-zero off-diagonal permeability tensor element causes the transverse magneto-optical Kerr effect under s-polarized incidence that otherwise vanishes if the permeability tensor is not gyromagnetic. By retrieving the permeability tensor elements from reflection, transmission, and transverse magneto-optical Kerr effect spectra, we show that the effective off-diagonal permeability tensor elements reach 10−3 level at the resonance wavelength (~900 nm) of the split-ring resonators, which is at least two orders of magnitude higher than magneto-optical materials at the same wavelength. The artificial gyromagnetic permeability is attributed to the change in the local electric field direction modulated by the split-ring resonators. Our study demonstrates the possibility of engineering the permeability and permittivity tensors in metamaterials at arbitrary frequencies, thereby promising a variety of applications of next-generation nonreciprocal photonic devices, magneto-plasmonic sensors, and active metamaterials. Optical gyromagnetic properties are not observed in natural or metamaterials to date. Here, the authors experimentally demonstrated optical gyromagnetic properties in a magneto-plasmonic metamaterial, realizing the long-sought bi-gyrotropic medium. [ABSTRACT FROM AUTHOR]

In this paper, we study the hybrid dual attack over learning with errors (LWE) problems for any secret distribution. Prior to our work, hybrid attacks are only considered for sparse and/or small secrets. A new and interesting result from our analysis shows that for most cryptographic use cases a hybrid dual attack outperforms a standalone dual attack, regardless of the secret distribution. We formulate our results into a framework of predicting the performance of the hybrid dual attacks. We also present a few tricks that further improve our attack. To illustrate the effectiveness of our result, we re-evaluate the security of all LWE related proposals in round 3 of NIST's post-quantum cryptography process, and improve the state-of-the-art cryptanalysis results by 2-15 bits, under the BKZ-core-SVP model. [ABSTRACT FROM AUTHOR]

As the key link connecting the earth's spheres, continental weathering plays an important role in regulating the global biogeochemical cycle and long-term climate change. Siliciclastic sediments derived from large river basins can record continental weathering and erosion signals, and are thus widely used to investigate weathering processes. However, sediment grain size, hydrodynamic sorting and sedimentary recycling complicate the interpretation of sediment weathering proxies. This study presents elemental and lithium isotope compositions of estuarine surface sediments (SS) and suspended particulate matters (SPM) collected from the Changjiang (Yangtze River) Estuary. Based on a simple mass balance model, the proportions of different end-members (i.e., igneous rocks, modern weathering products and inherited weathering products) in sediments were quantitatively calculated and thus the silicate weathering process can be estimated. Overall, the sediments in the Changjiang Estuary are mainly eroded from un-weathered rock fragments (>60%), while modern weathering products account for less than 40%. The fine-grained SPM contain more shale components (52–66%), and the modern weathering products account for 21–40%. Comparatively, the coarse-grained surface sediments contain more un-weathered igneous rock fragments (63–84%) and less modern weathering products (only 4–18%). The comparison of δ7Li values with the weathering proxy (Chemical Index of Alteration, CIA) suggests that sediment weathering intensity declines with increasing proportion of un-weathered igneous rock fragments. Additionally, the occurrence of inherited weathering products (i.e., shale) in modern sediments makes it a challenge to simply use CIA and δ7Li as indicators of weathering intensity. This study confirms that fine-grained particles are more suitable for tracing contemporary weathering process, albeit with the influence of sedimentary recycling. Lithium isotopes combining with the mass balance model can quantitatively constrain the continental weathering processes in large river basins. [ABSTRACT FROM AUTHOR]

Ankle–foot orthoses (AFOs) are devices prescribed to improve mobility in people with neuromuscular disorders. Traditionally, AFOs are manually fabricated by an orthotist based on a plaster impression of the lower leg which is modified to correct for impairments. This study aimed to digitally analyse this manual modification process, an important first step in understanding the craftsmanship of AFO fabrication to inform the digital workflows (i.e. 3D scanning and 3D printing), as viable alternatives for AFO fabrication. Pre- and post-modified lower limb plaster casts of 50 children aged 1–18 years from a single orthotist were 3D scanned and registered. The Euclidean distance between the pre- and post-modified plaster casts was calculated, and relationships with participant characteristics (age, height, AFO type, and diagnosis) were analysed. Modification maps demonstrated that participant-specific modifications were combined with universally applied modifications on the cast's anterior and plantar surfaces. Positive differences (additions) ranged 2.12–3.81 mm, negative differences (subtractions) ranged 0.76–3.60 mm, with mean differences ranging from 1.37 to 3.12 mm. Height had a medium effect on plaster additions (rs = 0.35). We quantified the manual plaster modification process and demonstrated a reliable method to map and compare pre- and post-modified casts used to fabricate children's AFOs. [ABSTRACT FROM AUTHOR]

Two-dimensional (2D) transition metal dichalcogenides (TMDs) with tantalizing layer-dependent electronic and optical properties have emerged as a paradigm for integrated flat opto-electronic devices, but their widespread applications are hampered by challenges in deterministic fabrication with demanded shapes and thicknesses, as well as light field manipulation in such atomic-thick layers with negligible thicknesses compared to the wavelength. Here we demonstrate ultra-sensitive light field manipulation in full visible ranges based on MoS2 laser prints exfoliated with nanometric precisions. The nontrivial interfacial phase shifts stemming from the unique dispersion of MoS2 layers integrated on the metallic substrate empower an ultra-sensitive resonance manipulation up to 13.95 nm per MoS2 layer across the entire visible bands, which is up to one-order-of-magnitude larger than their counterparts. The interlayer van der Waals interactions and the anisotropic thermal conductivity of layered MoS2 films endow a laser exfoliation method for on-demand patterning MoS2 with atomic thickness precision and subwavelength feature sizes. With this, nanometric flat color prints and further amplitude-modulated diffractive components for binocular stereoscopic images can be realized in a facile and lithography-free fashion. Our results with demonstrated practicality unlock the potentials of, and pave the way for, widespread applications of emerging 2D flat optics. The authors demonstrate fidelity colour prints and binocular stereoscopic images in multilayer MoS2 integrated on an Au substrate, showing nanometric layer sensitivity in the Fabry-Perot resonance changed by a facile laser recipe. [ABSTRACT FROM AUTHOR]

Circular RNAs (circRNAs) have been reported to play important roles in human cancers. Circular RNA homeodomain interacting protein kinase 3 (Circ-HIPK3) was investigated to be involved in tumorigenesis. However, the functions of circ-HIPK3 in oral squamous cell carcinoma (OSCC) remain vague. The expression of circ-HIPK3, microRNA (miR)-381-3p and Yes-associated protein1 (YAP1) was detected by qRT-PCR or western blot. Cell proliferation, apoptosis, invasion and migration were measured by MTT assay, flow cytometry, or transwell assay. The dual-luciferase reporter assay was employed to test the target correlations miR-381-3p and circ-HIPK3 or YAP1. Murine xenograft model was established to conduct in vivo assay. Circ-HIPK3 was elevated in OSCC tissues and cell lines, and decrease of circ-HIPK3 suppressed OSCC cell proliferation, invasion, migration and induced apoptosis in vitro as well as inhibited tumor growth in vivo. Rescue assay indicated circ-HIPK3 silence mediated OSCC progression inhibition by sponging miR-381-3p, which was a target of circ-HIPK3. Furthermore, miR-381-3p directly interacted with YAP1 and miR-381-3p inhibition could attenuate YAP1 deletion-induced suppression on cell malignant biological behavior in OSCC. Meanwhile, co-expression analysis showed circ-HIPK3 could regulate YAP1 expression by competing for miR-381-3p. Circ-HIPK3 contributed to OSCC growth and development through regulating YAP1 expression by sponging miR-381-3p, indicating a promising therapeutic strategy for OSCC. [ABSTRACT FROM AUTHOR]

Forward radiative transfer models (RTM) are an indispensable tool for quantitative applications of satellite radiometers, e.g., for data calibration, instrument development, retrieval, and so on. In this study, we develop an accurate and efficient RTM for radiometers onboard Fengyun satellites, namely FYRTM (RTM for Fengyun Radiometers). Correlated k-distribution models are developed to improve the computational efficiency for gas absorption, and the effects of cloud and aerosol multiple scattering and emission are accelerated with pre-computed look-up tables. FYRTM is evaluated with a rigorous simulation based on discrete ordinate radiative transfer model (DISORT) as well as a popular fast forward model, i.e., the Community Radiative Transfer Model (CRTM). Results indicate that FYRTM-based simulations are two to three orders of magnitudes faster than the DISORT-based simulations. Compared to the rigorous model, FYRTM relative errors are within 2% at solar channels, and brightness temperatures (BT) differences are within 1 K at infrared channels. Compared with CRTM, FYRTM is computationally similar at solar channels, but three times faster at infrared channels. Furthermore, simulated reflectances/BTs using FYRTM are in a good agreement with the satellite observations. Overall, FYRTM is capable to simulate satellite observations under different atmospheric conditions, and can be extended to other radiometers onboard the Fengyun satellites (both geostationary and polar-orbiting satellites). It is expected to play important roles in future applications with Fengyun observations. [ABSTRACT FROM AUTHOR]

In this study, four functional β-cyclodextrin derivatives including amidoxime linear-linked and cross-linked β-cyclodextrin/acrylonitrile/acrylic terpolymer (l-CD-AO-AA and c-CD-AO-AA), citric acid cross-linked poly-β-cyclodextrin (PCD), amidoxime cross-linked β-cyclodextrin and acrylonitrile–acrylic block copolymer (CD-b-AO-AA) were synthesized and properties of β-CD derivatives were characterized by FT-IR, SEM, TGA and element analysis. The effect of solid liquid ratio of the adsorbents, ionic strength, pH, contact time, initial concentration of U(VI), adsorption temperature, selective adsorption for different metal ions and the reasonable desorption conditions were studied. It was found when content of U(VI) was 22 mg/L, the four functional materials l-CD-AO-AA, c-CD-AO-AA, PCD and CD-AO-b-AA completely adsorbed U(VI) at 0.06 g/L (R ≈ 97%), 0.10 g/L (R ≈ 96%), 0.08 g/L (R ≈ 94%) and 0.52 g/L (R ≈ 94%), respectively. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this study is to evaluate the efficacy of intracameral preservative-free triamcinolone acetonide (TA) on reducing inflammatory reactions after pediatric cataract surgery. Methods: Researches were comprehensively searched in PubMed, Embase, and the Cochrane Central Register of Controlled Trials up to 30 November, 2019. Data of interest were extracted and analyzed by Review Manager 5.2. The primary outcome was cell deposits. The secondary outcomes included posterior synechias, fibrinous anterior chamber reaction, visual axis obscuration, and posterior capsule opacification. The odds ratio (OR), weight mean difference (WMD), and their 95% confidence intervals (95% CI) were used to assess the strength of the association. Results: In total, 45 articles were obtained. Finally, 5 studies with a total of 308 eyes were enrolled in this meta-analysis. Among these, 134 eyes underwent intracameral TA treatment and 174 eyes did not. In intracameral TA treatment group, the incidence of cell deposits (OR = 0.35, 95% CI 0.16–0.76, P = 0.008), posterior synechias (OR = 0.44, 95% CI 0.23–0.86, P = 0.02), and fibrinous anterior chamber reaction (OR = 0.12, 95% CI 0.01–1.05, P = 0.05) were lower compared to those in patients without intracameral TA treatment. Meanwhile, the incidence of visual axis obscuration (OR = 0.10, 95% CI 0.01–0.85, P = 0.04) and posterior capsule opacification (OR = 0.09, 95% CI 0.02–0.55, P = 0.009) were also reduced significantly. The intraocular pressure (IOP) was evaluated at the first month postoperatively (WMD = 0.84 mmHg, 95% CI 0.14–1.53, P = 0.02), but within the normal range. There was no difference of IOP between two groups at 6 months or above after operation (P = 0.93). Conclusions: The intracameral preservative-free TA in pediatric cataract surgery contributed to much less inflammatory reaction with the normal IOP range. [ABSTRACT FROM AUTHOR]

At photonic Dirac points, electromagnetic waves are governed by the same equations as two-component massless relativistic fermions. However, photonic Dirac points are known to occur in pairs in "photonic graphene" and other similar photonic crystals, which necessitates special precautions to excite only one valley state. Systems hosting unpaired photonic Dirac points are significantly harder to realize, as they require broken time-reversal symmetry. Here, we report on the observation of an unpaired Dirac point in a planar two-dimensional photonic crystal. The structure incorporates gyromagnetic materials, which break time-reversal symmetry; the unpaired Dirac point occurs when a parity-breaking parameter is fine-tuned to a topological transition between a photonic Chern insulator and a conventional photonic insulator phase. Evidence for the unpaired Dirac point is provided by transmission and field-mapping experiments, including a demonstration of strongly non-reciprocal reflection. This unpaired Dirac point may have applications in valley filters and angular selective photonic devices. Observing the photonic analogue of an unpaired Dirac point is hard, as it requires breaking the time-reversal symmetry. Here, the authors use gyromagnetic materials to do that, and thus succeed in observing an unpaired Dirac point in a planar photonic crystal operating at microwave frequencies. [ABSTRACT FROM AUTHOR]

Purpose: Our aim was to develop an interactive 3D direct volume rendering (DVR) visualization solution to interpret and analyze complex, serial multi-modality imaging datasets from positron emission tomography–computed tomography (PET–CT). Methods: Our approach uses: (i) a serial transfer function (TF) optimization to automatically depict particular regions of interest (ROIs) over serial datasets with consistent anatomical structures; (ii) integration of a serial segmentation algorithm to interactively identify and track ROIs on PET; and (iii) parallel graphics processing unit (GPU) implementation for interactive visualization. Results: Our DVR visualization more easily identifies changes in ROIs in serial scans in an automated fashion and parallel GPU computation which enables interactive visualization. Conclusions: Our approach provides a rapid 3D visualization of relevant ROIs over multiple scans, and we suggest that it can be used as an adjunct to conventional 2D viewing software from scanner vendors. [ABSTRACT FROM AUTHOR]

We study the Imbert-Fedorov (IF) effect in Kretschmann configuration with anisotropic metamaterial to explore a flexible method to enhance and modulate IF shift. The physical mechanism for large IF shifts in an anisotropic waveguide based on spin-orbit angular momentum coupling is explained. The influences of metamaterial thickness, anisotropy, and loss on IF shift are systematically discussed. This provides a theoretical prediction of IF shift in a Kretschmann configuration which is verified by simulation results in semiconductor metamaterial waveguide. The simulation results show that both metamaterial anisotropy and loss contributes significantly to the IF shift. Thus, reducing the loss and enhancing the metamaterial anisotropy are necessary and important measures to realize enhanced IF effect in the proposed Kretschmann configuration. [ABSTRACT FROM AUTHOR]

Segmentation of regions of interest (ROIs) in medical images is an important step for image analysis in computer-aided diagnosis systems. In recent years, segmentation methods based on fully convolutional networks (FCNs) have achieved great success in general images. FCN performance is primarily due to it leveraging large labeled datasets to hierarchically learn the features that correspond to the shallow appearance as well as the deep semantics of the images. However, such dependence on large dataset does not translate well into medical images where there is a scarcity of annotated medical training data, and FCN results in coarse ROI detections and poor boundary definitions. To overcome this limitation, medical image-specific FCN methods have been introduced with post-processing techniques to refine the segmentation results; however, the performance of these methods is reliant on the appropriate tuning of a large number of parameters and dependence on data-specific post-processing techniques. In this study, we leverage the state-of-the-art image feature learning method of generative adversarial network (GAN) for its inherent ability to produce consistent and realistic images features by using deep neural networks and adversarial learning concept. We improve upon GAN such that ROI features can be learned at different levels of complexities (simple and complex), in a controlled manner, via our proposed dual-path adversarial learning (DAL). The outputs from our DAL are then augmented to the learned ROI features into the existing FCN training data, which increases the overall feature diversity. We conducted experiments on three public datasets with a variety of visual characteristics. Our results demonstrate that our DAL can improve FCN-based segmentation methods and outperform or be competitive in performances to the state-of-the-art methods without using medical image-specific optimizations. [ABSTRACT FROM AUTHOR]

As a result of recycling, the mineralogical and chemical compositions of riverine sediments may reflect the combined effects of the present-day weathering regime as well as previous weathering and diagenetic alteration history. River sediments can be interpreted as a mixture of non-weathered bedrock-of igneous, metamorphic, or sedimentary origin-and solids formed by the modern weathering system. The correlation between the weathering proxies chemical index of alteration and weathering index of Parker offers an approach to distinguish fine suspended particles, coarse bedload sediments, and recycled sediments under the influence of quartz dilution. Recycling of cation-depleted source rocks formed during past geological weathering episodes may have great impacts on the weathering indices of sediments from the Changjiang (Yangzte) and Zhuoshui Rivers. Special caution is required when using chemical weathering indices to investigate the intensity of chemical weathering registered in fluvial sediments. To minimize the effect of hydrodynamic sorting or sediment recycling, we suggest that the fine sediments (e.g. suspended particles and <2 μm fractions of bedload sediments) in rivers better reflect the average of weathered crust in catchments and the terrigenous end-member in marginal seas. [ABSTRACT FROM AUTHOR]

The automated segmentation of regions of interest (ROIs) in medical imaging is the fundamental requirement for the derivation of high-level semantics for image analysis in clinical decision support systems. Traditional segmentation approaches such as region-based depend heavily upon hand-crafted features and a priori knowledge of the user. As such, these methods are difficult to adopt within a clinical environment. Recently, methods based on fully convolutional networks (FCN) have achieved great success in the segmentation of general images. FCNs leverage a large labeled dataset to hierarchically learn the features that best correspond to the shallow appearance as well as the deep semantics of the images. However, when applied to medical images, FCNs usually produce coarse ROI detection and poor boundary definitions primarily due to the limited number of labeled training data and limited constraints of label agreement among neighboring similar pixels. In this paper, we propose a new stacked FCN architecture with multi-channel learning (SFCN-ML). We embed the FCN in a stacked architecture to learn the foreground ROI features and background non-ROI features separately and then integrate these different channels to produce the final segmentation result. In contrast to traditional FCN methods, our SFCN-ML architecture enables the visual attributes and semantics derived from both the fore- and background channels to be iteratively learned and inferred. We conducted extensive experiments on three public datasets with a variety of visual challenges. Our results show that our SFCN-ML is more effective and robust than a routine FCN and its variants, and other state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Scheduling is a major concern in construction planning and management, and current construction simulation research typically targets the shortest total duration. However, uncertainties are inevitable in actual construction, which may lead to discrepancies between the actual and planned schedules and increase the risk of total duration delay. Therefore, developing a robust construction scheduling technique is of vital importance for mitigating disturbance and improving completion probability. In the present study, the authors propose a robustness analysis method that involves underground powerhouse construction simulation based on the Markov Chain Monte Carlo (MCMC) method. Specifically, the MCMC method samples construction disturbances by considering the interrelationship between the states of parameters through a Markov state transition probability matrix, which is more robust and efficient than traditional sampling methods such as the Monte Carlo (MC) method. Additionally, a hierarchical simulation model coupling critical path method (CPM) and a cycle operation network (CYCLONE) is built, using which construction duration and robustness criteria can be calculated. Furthermore, a detailed measurement method is presented to quantize the robustness of underground powerhouse construction, and the setting model of the time buffer is proposed based on the MCMC method. The application of this methodology not only considers duration but also robustness, providing scientific guidance for engineering decision making. We analyzed a case study project to demonstrate the effectiveness and superiority of the proposed methodology. [ABSTRACT FROM AUTHOR]

Salvianolic acid (Sal A) is a water-soluble compound extracted from Radix Salvia miltiorrhiza (danshen), which has been widely used to treat acute hepatitis and hepatic damage in traditional Chinese medicine. The aim of the present study was to delineate the antiapoptotic signaling pathways involved in Sal A's hepato-protective action in hepatocyte LO2 cells and to further elucidate the mechanism by which Sal A elicits the antiapoptotic effects on hepatocytes. Here, the study showed that Sal A had antiapoptotic effects on the TNF-α/ d-GalN-treated LO2 cells. Moreover, Western blotting demonstrated that the levels of p-eIF2α, ATF4, GRP78, CHOP and caspase-4 were markedly decreased in Sal A group. Additionally, the decrease of the cell mitochondrial membrane permeability and increase of ΔΨm were detected in Sal A-treated cells by high-content screening (HCS) analysis. And the levels of cleaved-caspase-9, cleaved-caspase-3, apoptosis-inducing factor (AIF), Apaf-1, and Cytc (cyto) were downregulated, while Cytc (mito) was upregulated by Sal A via Western blotting. Furthermore, the decreased levels of Bax/Bcl-2 ratio and calcium release were measured in Sal A-treated cells. In summary, Sal A attenuates TNF-α- and d-GalN-induced both ER stress and mitochondrial-dependent apoptosis by suppression of Bax/Bcl-2 ratio and prevention of calcium release, which support the notion that Sal A could be developed into a novel hepatic protectant. [ABSTRACT FROM AUTHOR]

The East China Sea (ECS) is a river-dominated epicontinental sea, linking the Asian continent to the northwestern Pacific via the large rivers originating from Tibetan Plateau. The relevant huge influx of riverine detritus has developed unique sedimentary systems in the ECS during the Quaternary, offering ideal terrestrial archives for reconstructing Quaternary paleoenvironmental changes and studying land-sea interactions. Overall, two characteristic river systems dominate the sedimentary systems and sediment source to sink transport patterns in the ECS, represented by the Changjiang (Yangtze River) and Huanghe (Yellow River) for the large river system and Taiwan rivers for the small river system. Given this, the sediments derived from both river systems bear distinct features in terms of parent rock lithology, provenance weathering and sediment transport. Previous studies mostly focus on either the 'source' discrimination or the 'sink' records of the sedimentary system in the ECS, while the source to sink process linking the land and sea, in particular its time scale, has been poorly understood. Here we introduce a newly-developed dating technique, the 'comminution age' method, which offers a quantitative constraint on the time scale of sediment transfer from its ultimate source to the final depositional sink. This novel method is of great significance for improving our understanding on the earth surface processes including tectonic-climate driven weathering, and sediment recycling in relation to landscape evolution and marine environmental changes. The application of comminution age method in the ECS will provide important constraints on sediment source-to-sink process and more evidences for the construction of late Quaternary paleoenvironmental changes under these unique sedimentary systems. [ABSTRACT FROM AUTHOR]

Presented is a review of the radiative properties of ice clouds from three perspectives: light scattering simulations, remote sensing applications, and broadband radiation parameterizations appropriate for numerical models. On the subject of light scattering simulations, several classical computational approaches are reviewed, including the conventional geometric-optics method and its improved forms, the finite-difference time domain technique, the pseudo-spectral time domain technique, the discrete dipole approximation method, and the T-matrix method, with specific applications to the computation of the single-scattering properties of individual ice crystals. The strengths and weaknesses associated with each approach are discussed. With reference to remote sensing, operational retrieval algorithms are reviewed for retrieving cloud optical depth and effective particle size based on solar or thermal infrared (IR) bands. To illustrate the performance of the current solar- and IR-based retrievals, two case studies are presented based on spaceborne observations. The need for a more realistic ice cloud optical model to obtain spectrally consistent retrievals is demonstrated. Furthermore, to complement ice cloud property studies based on passive radiometric measurements, the advantage of incorporating lidar and/or polarimetric measurements is discussed. The performance of ice cloud models based on the use of different ice habits to represent ice particles is illustrated by comparing model results with satellite observations. A summary is provided of a number of parameterization schemes for ice cloud radiative properties that were developed for application to broadband radiative transfer submodels within general circulation models (GCMs). The availability of the single-scattering properties of complex ice habits has led to more accurate radiation parameterizations. In conclusion, the importance of using nonspherical ice particle models in GCM simulations for climate studies is proven. [ABSTRACT FROM AUTHOR]

The aim of this paper was to investigate the correlations between magnetic resonance imaging (MRI) features and vascular endothelial growth factor (VEGF) in hepatocellular carcinoma (HCC). Thirty-six patients with HCC included in this study underwent dynamic contrast-enhanced MR imaging and diffusion-weighted MR imaging. Signal intensity characteristics of HCCs were reviewed independently by two experienced radiologists. ADC maps were automatically computed. VEGF expression was evaluated by immunohistochemical staining. The grades of the VEGF expression were correlated inversely with the ADC values of the HCCs ( r = −0.435, p = 0.008). Intensity heterogeneity correlated with VEGF expression ( r = 0.571, p = 0.039). There is a significant correlation between the intensity of arterial enhancement and VEGF expression ( r = −0.386, p = 0.02). However, no correlation was found between the VEGF grades and the intensity of enhancement in the hepatic portal venous and late phases, as well as equilibrium phase. Our results indicate that ADC value on DW-MRI, the signal intensity in arterial phase and intensity heterogeneity correlate with the degree of VEGF expression in hepatocellular carcinomas. [ABSTRACT FROM AUTHOR]