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In this study, three levels of grape load (15, 20, and 25 spikes/m shelf) were set for the primary wine grape cultivar ‘Cabernet Sauvignon’. The effect of different harvest times, four growth stages according to the Eichhorn-Lorenz scale: E-L35, E-L36, E-L37, and E-L38 was investigated on the compositions of organic acids, monomeric phenols and volatile compounds and sensory quality of wine. The results showed that at the E-L38 stage, the total acid of grape berries in the medium-load group significantly increased, while the opposite was true for the low- and high-load groups. For all groups, the total acid content of wine peaked at the E-L35 stage and reached its lowest point at the E-L37 stage. The total phenol content reached its peak at the E-L36 stage, and then decreased rapidly. Under the low-load condition, the sensory quality of wine produced from early harvested grapes was superior to that of late harvested grapes, whereas the opposite result was found at the high load. The typicality and richness of wine were significantly improved with the delay of harvest time, samples J-20-6 (medium load + E-L37) and J-20-7 (medium load + E-L38) outperforming all other samples. The overall sensory score of sample J-20-5 (medium load + E-L36) was the highest, and the total volatile content and sensory richness score of sample J-25-7 (high load + E-L38) were the highest among all tested samples. Thus, meticulous regulation of grape load and harvest time holds substantial promise for enhancing wine quality.

This study examines the regional co-funding network as a novel framework for advancing high-quality fundamental research amid systemic reforms in science funding. Based on provincial joint funding data from Mainland China retrieved via the WoS-SCIE and SSCI databases (2013–2022), an interprovincial co-funding network was constructed. Social network analysis, kernel density estimation, and fixed-effects regression analysis were employed to explore the evolution of regional location advantages and their impact on technological innovation. The findings reveal that the co-funding network has become increasingly balanced over time, significantly enhancing the location-based innovation advantages of individual provinces and strengthening the network's overall capacity to foster innovation. This improved equilibrium has positively influenced regional scientific output, demonstrating that a province's position within the co-funding network—particularly its individual location advantage—plays a pivotal role in advancing technological progress. However, persistent disparities in regional collaboration and development remain, underscoring the need for more coordinated strategies to address uneven growth dynamics. By introducing the co-funding network as an analytical lens, this study uncovers the hidden channels of resource synergy and their influence on regional innovation. The results provide actionable insights for optimizing co-funding mechanisms and enhancing interprovincial collaboration to maximize innovation potential in China. [ABSTRACT FROM AUTHOR]

The combination of volatile compounds endows wines with unique aromatic characteristics and is closely related to their geographical origins. In the pursuit of origin identification and the subdivision of homogeneous production areas, clarifying the characteristics of production areas is of great significance for improving wine quality and commercial value. In this study, GC×GC-TOFMS technology was used to analyze the aroma characteristics of "Cabernet Sauvignon" wines from 26 wineries in the Helan (HL), Yinchuan (YC), Yongning (YN), Qingtongxia (QTX), and Hongsibu (HSP) sub-producing areas in the eastern foothills of Helan Mountain in Ningxia, China. The results indicate a gradual increase in relative humidity from the southern part of Ningxia, with the YN sub-region showing optimal fruit development and the QTX region having the highest maturity. A total of 184 volatile compounds were identified, with 36 compounds with an OAV > 1, crucial for the aroma profiles of primarily fermentation-derived alcohols and esters. An aromatic vector analysis revealed that "floral" and "fruity" notes are the primary characteristics of Cabernet Sauvignon wines from the Helan Mountain East region, with lower maturity aiding in the retention of these aromas. By constructing a reliable OPLS-DA model, it was determined that 15 substances (VIP > 1) played a crucial role in identifying production areas, among which phenylethyl alcohol and isoamyl alcohol were the main contributors. In addition, a Pearson correlation analysis showed a negative correlation between sunlight duration during the growing season and benzyl alcohol accumulation, while a significant positive correlation was observed during the ripening period. Due to the critical role of phenyl ethanol in identifying producing areas, this further demonstrates that sunshine conditions may be a key factor contributing to the differences in wine flavor across regions. This study offers a theoretical foundation for understanding the relationship between climatic factors and flavor characteristics, addressing the issue of wine homogenization in small production areas, clarifying typical style characteristics, and establishing a traceability technology system based on characteristic aroma. [ABSTRACT FROM AUTHOR]

Objective. The textures and detailed structures in computed tomography (CT) images are highly desirable for clinical diagnosis. This study aims to expand the current body of work on textures and details preserving convolutional neural networks for low-dose CT (LDCT) image denoising task. Approach. This study proposed a novel multi-scale feature aggregation and fusion network (MFAF-net) for LDCT image denoising. Specifically, we proposed a multi-scale residual feature aggregation module to characterize multi-scale structural information in CT images, which captures regional-specific inter-scale variations using learned weights. We further proposed a cross-level feature fusion module to integrate cross-level features, which adaptively weights the contributions of features from encoder to decoder by using a spatial pyramid attention mechanism. Moreover, we proposed a self-supervised multi-level perceptual loss module to generate multi-level auxiliary perceptual supervision for recovery of salient textures and structures of tissues and lesions in CT images, which takes advantage of abundant semantic information at various levels. We introduced parameters for the perceptual loss to adaptively weight the contributions of auxiliary features of different levels and we also introduced an automatic parameter tuning strategy for these parameters. Main results. Extensive experimental studies were performed to validate the effectiveness of the proposed method. Experimental results demonstrate that the proposed method can achieve better performance on both fine textures preservation and noise suppression for CT image denoising task compared with other competitive convolutional neural network (CNN) based methods. Significance. The proposed MFAF-net takes advantage of multi-scale receptive fields, cross-level features integration and self-supervised multi-level perceptual loss, enabling more effective recovering of fine textures and detailed structures of tissues and lesions in CT images. [ABSTRACT FROM AUTHOR]

Yan 73 (Vitis vinifera) is a dyed grape variety cultivated in China. Currently, most studies have focused on the mechanism of anthocyanins or the impact of anthocyanins as auxiliary color varieties on wine color. There is little research on its direct use or direct processing of products such as juice. In order to investigate the effects of different processing methods on the juice of Yan 73 grapes, the physicochemical and functional properties, as well as the sensory indexes of the juice, were analyzed by using thermal pasteurization (TP), thermosonication (TS), TS combined with nisin (TSN), TS combined with ε-Polylysine (TSε), irradiation (IR), and high hydrostatic pressure (HHP). The physicochemical indexes, functional properties, and sensory indexes of Smoke 73 grape juice were determined and analyzed. The results of the study showed that among the seven sterilization methods, total polyphenol content (TPC) in juice was significantly increased in all treatments except HHP. TPC was the highest in TP (3773.33 mg GAE/L). Total anthocyanin content (TAC) was increased except IR5, and TSN (1202.67 mg/L) had the highest TAC. In terms of color, TP (a* = 36.57, b* = 19.70, L* = 14.81, C* = 41.55, h° = 28.30, ΔE = 5.9) promotes the dissolution of anthocyanins because of high temperatures, which basically improves all the color indicators of grape juice and makes the color of grape juice more vivid. After HHP treatment, the color (ΔE = 1.72) and aroma indicators are closer to the grape juice itself. The Entropy weight-TOPSIS, CRITIC-Topsis, and PCA integrated quality evaluation models showed that all selected TP as the best integrated quality. [ABSTRACT FROM AUTHOR]

Texture and color distortion are common in existing learning‐based dehazing algorithms, and it is argued that one of the major reasons is that the shallow features of fog images are underutilized, and the deep features of fog images are insufficient for single image dehazing. In order to provide more texture and color information for image restoration, more shallow features need to be added in the process of image decoding. Therefore, a multi‐scale feature fusion pyramid attention network (PAN) for single image dehazing is proposed. In PAN, combined with the attention mechanism, a shallow and deep feature fusion (SDF) strategy is designed. SDF considers multi‐scale as well as channel‐level fusion to provide feature information under different receptive fields while also highlighting important channels, such as texture and color information. DC is designed as a latent space mapping module to learn a mapping relationship between the latent space representation of the hazy image at low resolution and the corresponding latent space representation of the haze‐free image. Additionally, network deconvolution (ND) and deformed convolution network (DCN) are introduced into PAN. The ND module can remove pixel‐wise and channel‐wise correlation of features, reduce data redundancy to obtain sparse representation of features, and speed up network convergence. The DCN module can use its adaptive receptive field to focus on the area of interest for calculation and play a role in texture feature enhancement. Finally, the perceptual loss is chosen as the regularization item of the loss function, which makes style features of the restored image closer to the real fog‐free image. Extensive experiments reveal that the proposed PAN outperforms other existing dehazing methods on real‐world and synthetic datasets. [ABSTRACT FROM AUTHOR]

Simple Summary: Vitamin A is an anti-inflammatory vitamin and essential for the health of humans and animals. Necrotic enteritis is an enteric inflammatory disease in poultry caused by Clostridium perfringens infection. Due to the ban on using antibiotics in feed, necrotic enteritis has caused great economic losses in poultry production. Previous observations indicated that phospholipase C secreted by C. perfringens might interfere with the transformation of vitamin A into retinoic acid via the stimulation of prostaglandin E2 production, which impaired the modulation of vitamin A on immune responses. Therefore, the present study investigated the effects of dietary supplementation with a large dose of vitamin A on the immune responses and vitamin A metabolism in broilers suffering from necrotic enteritis and explored the underlying mechanisms. The results showed that vitamin A supplementation in chicken diets improved hepatic vitamin A deposition and modulated the expression of Th2 cell-related cytokines in the jejunum and spleen. In addition, dietary supplementation with vitamin A inhibited the expression of genes involved in the Janus kinase/signal transducer and activator of the transcription pathway and genes encoding retinoic acid receptors in the spleen of broilers. The present study indicated the modulatory effects of vitamin A supplementation in diets on the immune responses and vitamin A metabolism in necrotic enteritis-challenged broilers. Necrotic enteritis (NE) is an important enteric inflammatory disease of poultry, and the effects of vitamin A (VitA) on NE birds are largely unknown. The present study was conducted to investigate the effects of VitA on the immune responses and VitA metabolism of NE broilers as well as the underlying mechanisms. Using a 2 × 2 factorial arrangement, 336 1-day-old Ross 308 broiler chicks were randomly assigned to 4 groups with 7 replicates. Broilers in the control (Ctrl) group were fed a basal diet without extra VitA supplementation. Broilers in the VitA group were fed a basal diet supplemented with 12,000 IU/kg of VitA. Birds in NE and VitA + NE groups were fed corresponding diets and, in addition, co-infected with Eimeria spp. and Clostridium perfringens on days 14 to 20. Samples of the blood, jejunum, spleen and liver were obtained on day 28 for analysis, and meanwhile, lesion scores were also recorded. The results showed that NE challenge increased lesion score in the jejunum and decreased serum glucose, total glyceride, calcium, phosphorus and uric acid levels (p < 0.05). VitA supplementation reduced the levels of serum phosphorus, uric acid and alkaline phosphatase in NE-challenged birds and increased serum low-density lipoprotein content and the activity of aspartate aminotransferase and creatine kinase (p < 0.05). Compared with the Ctrl group, the VitA and NE groups had higher mRNA expression of interferon-γ in the jejunum (p < 0.05). NE challenge up-regulated mRNA expression of interleukin (IL)-13, transforming growth factor-β4, aldehyde dehydrogenase (RALDH)-2 and RALDH-3 in the jejunum, while VitA supplementation increased jejunal IL-13 mRNA expression and hepatic VitA content, but down-regulated splenic IL-13 mRNA expression (p < 0.05). The VitA + NE group had higher serum prostaglandin E2 levels and the Ctrl group had higher splenic RALDH-3 mRNA expression than that of the other three groups (p < 0.05). NE challenge up-regulated jejunal retinoic acid receptor (RAR)-β and retinoid X receptor (RXR)-α as well as splenic RAR-α and RAR-β mRNA expression (p < 0.05). VitA supplementation up-regulated jejunal RAR-β expression but down-regulated mRNA expression of RXR-α, RXR-γ, signal transducers and activators of transcription (STAT) 5 and STAT6 in the spleen (p < 0.05). Moreover, compared with the Ctrl group, the VitA and NE groups had down-regulated mRNA expression of jejunal and splenic Janus kinase (JAK) 1 (p < 0.05). In conclusion, NE challenge induced jejunal injury and expression of Th2 and Treg cell-related cytokines and enhanced RALDH and RAR/RXR mRNA expression, mainly in the jejunum of broilers. VitA supplementation did not alleviate jejunal injury or Th2 cell-related cytokine expression; however, it improved hepatic VitA deposition and inhibited the expression of RALDH-3, RXR and the JAK/STAT signaling pathway in the spleen of broilers. In short, the present study suggested the modulatory effects of vitamin A on the immune responses and vitamin A metabolism in broiler chickens challenged with necrotic enteritis. [ABSTRACT FROM AUTHOR]

Lithium batteries are widely used in power storage and new energy vehicles due to their high energy density and long cycle life. The accurate and real-time estimation for the state-of-charge (SoC) and the state-of-health (SoH) of lithium batteries is of great significance to improve battery life, reliability, and utilization efficiency. In this paper, three cascaded fractional-order sliding-mode observers (FOSMOs) are designed for the estimation of SoC by observing the terminal voltage, the polarization voltage, and the open-circuit voltage of a lithium cell, respectively. Furthermore, to calculate the value of the SoH, two FOSMOs are developed to estimate the capacity and internal resistance of the lithium cell. The control signals of the observers are continuous by utilizing fractional-order sliding manifolds without low-pass filters. Compared with the existing sliding-mode observers for SoC and SoH, weaker chattering, faster response, and higher estimation accuracy are obtained in the proposed method. Finally, the experiment tests demonstrate the validity and feasibility of the proposed observer design method. [ABSTRACT FROM AUTHOR]

Simple Summary: Coccidia and C. perfringens are the main accomplices in broiler necrotizing enteritis (NE), and NE causes oxidative stress and intestinal damage in broilers, which will result in huge economic losses to the poultry industry. Vitamin A (VA) is an essential micronutrient of the diet, and the beneficial effects of VA on vision, growth, and development have been intensively investigated. At present, the effects of VA on intestinal barrier and antioxidant functions in broilers have not been systematically reported. The present study was conducted to investigate the effects of dietary supplementation with vitamin A on the antioxidant and intestinal barrier function of broilers co-infected with coccidia and C. perfringens (CCP). Our outcomes showed that dietary VA might help a little with intestinal barrier function; nonetheless, it failed to alleviate the negative effects of CCP on the antioxidant function in broilers. Our study has guiding significance for the dose of VA in the diet of broilers, and it might arouse readers' strong interest. Necrotic enteritis (NE) impairs poultry production and causes great economic loss. The nutritional regulation of diets has the potential to alleviate NE. The present study was conducted to investigate the effects of dietary supplementation with vitamin A (VA) on the antioxidant and intestinal barrier function of broilers co-infected with coccidia and C. perfringens (CCP). In a 2 × 2 factorial arrangement, 336 one-day-old Ross 308 broilers were divided into four treatments with two levels of VA (0 or 12,000 IU/kg) and challenged with or without CCP. The animal trial lasted for 42 days. The results showed that dietary supplemental VA improved body weight gain (BWG) and the feed intake (FI), and the FI was negatively affected by CCP. Additionally, the levels of catalase (CAT) in the serum, total superoxide dismutase (T-SOD), and CAT in the jejunum and glutathione peroxidase (GSH-Px) in the liver decreased with the CCP challenge (p < 0.05). The mRNA levels of SOD, CAT, GSH-Px1, and GSH-Px3 in the liver and jejunum were upregulated by the CCP challenge (p < 0.05). In addition, the level of serum diamine oxidase (DAO), and the mRNA level of ZO-1 were also upregulated with the CCP challenge. Dietary supplementation with VA contributed to the intestinal villi height and the mRNA level of Mucin-2 in the jejunum (p < 0.05). Additionally, dietary VA had the ability to alleviate the upregulation of SOD in the liver and SOD, CAT, GSH-Px1, GSH-Px3, ZO-1, and claudin-1 in the jejunum with the CCP challenge (p < 0.05). However, the mRNA level of GSH-Px3 and the levels of SOD in the liver and jejunum were downregulated with the VA supplementation in the diet. In conclusion, dietary VA improved the growth performance and the intestinal barrier function; nonetheless, it failed to alleviate the negative effects of CCP on the antioxidant function in broilers. [ABSTRACT FROM AUTHOR]

Optical coherence tomography (OCT) angiography has drawn much attention in the medical imaging field. Binarization plays an important role in quantitative analysis of eye with optical coherence tomography. To address the problem of few training samples and contrast‐limited scene, we proposed a new binarization framework with specific‐patch SVM (SPSVM) for low‐intensity OCT image, which is open and classification‐based framework. This new framework contains two phases: training model and binarization threshold. In the training phase, firstly, the patches of target and background from few training samples are extracted as the ROI and the background, respectively. Then, PCA is conducted on all patches to reduce the dimension and learn the eigenvector subspace. Finally, the classification model is trained from the features of patches to get the target value of different patches. In the testing phase, the learned eigenvector subspace is conducted on the pixels of each patch. The binarization threshold of patch is obtained with the learned SVM model. We acquire a new OCT mice eye (OCT‐ME) database, which is publicly available at https://mip2019.github.io/spsvm. Extensive experiments were performed to demonstrate the effectiveness of the proposed SPSVM framework. [ABSTRACT FROM AUTHOR]

Wide attention has been focused on cryogenic CMOS (cryo-CMOS) operation because of its promising improvement of devices’ and circuits’ performance and wide application prospects. However, hot carrier degradation (HCD) limits the long-term reliability of cryo-CMOS. This article investigates HCD in 0.18 $\mu \text{m}$ bulk CMOS at cryogenic temperature down to 4.2 K. Particularly, the relationship between HCD and the current overshoot phenomenon and the influence of substrate bias on HCD are discussed. Besides, we predict the lifetime of the device at 77 K and 4.2 K. It is concluded that cryogenic NMOS cannot reach the ten years’ commercial standard lifetime at standard $V_{DD}$. And it is predicted that the reliability requirements can be reached when $V_{DD} \leq 1.768$ V and 1.734 V at 77 K and 4.2 K, respectively. Differently, the lifetime of PMOS is long enough even at low temperatures. [ABSTRACT FROM AUTHOR]

The extremely low threshold voltage (${V}_{\text {TH}}$) of native MOSFETs (${V}_{\text {TH}}~\approx $ 0 V@300 K) is conducive to the design of cryogenic circuits. Previous research on cryogenic MOSFETs mainly focused on the standard threshold voltage (SVT) and low threshold voltage (LVT) MOSFETs. In this article, we characterize native MOSFETs within the temperature range from 300 to 4.2 K. The cryogenic ${V}_{\text {TH}}$ increases up to ~0.25 V (W/L = 10/ $10~\mu \text{m}$) and the improved subthreshold swing (SS) ≈ 14.30 mV/dec@4.2 K. The OFF-state current (${I}_{ \mathrm{\scriptscriptstyle OFF}}$) and the gate-induced drain leakage (GIDL) effect are ameliorated greatly. The step-up effect caused by the substrate charge and the transconductance peak effect caused by the energy quantization in different sub-bands are also discussed. Based on the EKV model, we modified the mobility calculation equations and proposed a compact model of large-size native MOSFETs suitable for the range of 300-4.2 K. The mobility-related parameters are extracted via a machine learning (ML) approach, and the temperature dependences of the scattering mechanisms are analyzed. This work is beneficial to both the research on cryogenic MOSFETs’ modeling and the design of cryogenic CMOS circuits for quantum chips. [ABSTRACT FROM AUTHOR]

The valuable structure features in full-dose computed tomography (FdCT) scans can be exploited as prior knowledge for low-dose CT (LdCT) imaging. However, lacking the capability to represent local characteristics of interested structures of the LdCT image adaptively may result in poor preservation of details/textures in LdCT image. This paper aims to explore a novel prior knowledge retrieval and representation paradigm, called adaptive prior features assisted restoration algorithm, for the purpose of better restoration of the low-dose lung CT images by capturing local features from FdCT scans adaptively. The innovation lies in the construction of an offline training database and the online patch-search scheme integrated with the principal components analysis (PCA). Specifically, the offline training database is composed of 3-D patch samples extracted from existing full-dose lung scans. For online patch-search, 3-D patches with structure similar to the noisy target patch are first selected from the database as the training samples. Then, PCA is applied on the training samples to retrieve their local prior principal features adaptively. By employing the principal features to decompose the noisy target patch and using an adaptive coefficient shrinkage technique for inverse transformation, the noise of the target patch can be efficiently removed and the detailed texture can be well preserved. The effectiveness of the proposed algorithm was validated by CT scans of patients with lung cancer. The results show that it can achieve a noticeable gain over some state-of-the-art methods in terms of noise suppression and details/textures preservation. [ABSTRACT FROM PUBLISHER]

As is known, noises in calibrated and log-transformed projection data of low-mA (or low-dose) CT protocol follow approximately a non-stationary Gaussian distribution. In this study, we further demonstrate that some isolated noise points would not satisfy the above observation. Hence, we propose a noise reduction scheme which includes isolated data removal and segmentation-based filtering. In this scheme, an isolated data removal algorithm is first adopted to remove isolated data such that the remaining sinogram data approximately follows a Gaussian distribution. Secondly, image segmentation technique is employed for segmenting sinogram image into different segments in which pixels with similar intensities are grouped, and the segmentation-based adaptive statistical sinogram smoothing technique is proposed with different smoothness parameters applied to different segments for adaptively filtering. The effectiveness of the proposed method is validated by both computer simulations and experimental studies. The gain of the proposed approach over other methods is quantified by noise-resolution tradeoff curves. [ABSTRACT FROM PUBLISHER]

Simple Summary: Fungal and bacterial fermentation improves the nutritional quality of soybean meal (SBM). The beneficial effects of fermented soybean meal (FSBM) on growth performance and gut health of broiler chickens have been demonstrated. However, FSBM is usually used in pre-starter diets of broiler chickens due to the high cost. In the present study, the SBM in diets was partially replaced by FSBM to evaluate its effect on the growth performance, carcass traits, and meat quality of broiler chickens. The growth performance and major carcass traits were not significantly affected by FSBM treatments. Different levels (2.5%, 5.0%, and 7.5%) of FSBM supplementation influenced the meat color, pH, nutritional composition, and antioxidant properties. The improvement of meat quality would extend the shelf life of meat and increase consumer acceptability to chicken. The 2.5% FSBM was recommended in a broiler diet. The usage of fermented soybean meal (FSBM) in poultry feed is limited due to the high cost. The present study was conducted to examine the carcass traits and meat quality of broiler chickens that were fed diets with partial replacement of soybean meal (SBM) with FSBM. The 336 one-day-old chicks were assigned to four groups with 0% (control), 2.5%, 5.0%, and 7.5% FSBM addition in corn-SBM-based diets. Compared with the control, 2.5% and 5.0% FSBM decreased leg muscle yield, breast drip loss, and cooking loss (p < 0.05). The 7.5% FSBM increased the ultimate pH of breast and thigh muscles, and all FSBM treatments decreased muscle lightness and breast malondialdehyde content (p < 0.05). The 2.5% FSBM increased breast total superoxide dismutase activity, while 7.5% FSBM reduced breast hydrogen peroxide level (p < 0.05). All FSBM treatments elevated breast contents of bitter and sour tasting amino acids, and 2.5% and 7.5% FSBM increased breast glutamic acid and total free amino acids (p < 0.05). The 5.0% and 7.5% FSBM elevated thigh isoleucine and leucine contents (p < 0.05). In conclusion, FSBM replacing SBM affected meat quality with the decrease of lightness and increase of pH, water-holding capacity, antioxidant properties, and free amino acids. [ABSTRACT FROM AUTHOR]

Background: Low-dose computed tomography (LDCT) scans can effectively reduce the radiation damage to patients, but this is highly detrimental to CT image quality. Deep convolutional neural networks (CNNs) have shown their potential in improving LDCT image quality. However, the conventional CNN-based approaches rely fundamentally on the convolution operations, which are ineffective for modeling the correlations among nonlocal similar structures and the regionally distinct statistical properties in CT images. This modeling deficiency hampers the denoising performance for CT images derived in this manner., Methods: In this paper, we propose an adaptive global context (AGC) modeling scheme to describe the nonlocal correlations and the regionally distinct statistics in CT images with negligible computation load. We further propose an AGC-based long-short residual encoder-decoder (AGC-LSRED) network for efficient LDCT image noise artifact-suppression tasks. Specifically, stacks of residual AGC attention blocks (RAGCBs) with long and short skip connections are constructed in the AGC-LSRED network, which allows valuable structural and positional information to be bypassed through these identity-based skip connections and thus eases the training of the deep denoising network. For training the AGC-LSRED network, we propose a compound loss that combines the L 1 loss, adversarial loss, and self-supervised multi-scale perceptual loss., Results: Quantitative and qualitative experimental studies were performed to verify and validate the effectiveness of the proposed method. The simulation experiments demonstrated the proposed method exhibits the best result in terms of noise suppression [root-mean-square error (RMSE) =9.02; peak signal-to-noise ratio (PSNR) =33.17] and fine structure preservation [structural similarity index (SSIM) =0.925] compared with other competitive CNN-based methods. The experiments on real data illustrated that the proposed method has advantages over other methods in terms of radiologists' subjective assessment scores (averaged scores =4.34)., Conclusions: With the use of the AGC modeling scheme to characterize the structural information in CT images and of residual AGC-attention blocks with long and short skip connections to ease the network training, the proposed AGC-LSRED method achieves satisfactory results in preserving fine anatomical structures and suppressing noise in LDCT images., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-23-194/coif). The authors have no conflicts of interest to declare., (2023 Quantitative Imaging in Medicine and Surgery. All rights reserved.)

Perfusion computed tomography (PCT) is critical in detecting cerebral ischemic lesions. PCT examination with low-dose scans can effectively reduce radiation exposure to patients at the cost of degraded images with severe noise and artifacts. Tensor total variation (TTV) models are powerful tools that can encode the regional continuous structures underlying a PCT object. In a TTV model, the sparsity structures of the contrast-medium concentration (CMC) across PCT frames are assumed to be isotropic with identical and independent distribution. However, this assumption is inconsistent with practical PCT tasks wherein the sparsity has evident variations and correlations. Such modeling deviation hampers the performance of TTV-based PCT reconstructions. To address this issue, we developed a novel c ontrast- m edium a nisotropy- a ware t ensor t otal v ariation (CMAA-TTV) model to describe the intrinsic anisotropy sparsity of the CMC in PCT imaging tasks. Instead of directly on the difference matrices, the CMAA-TTV model characterizes sparsity on a low-rank subspace of the difference matrices which are calculated from the input data adaptively, thus naturally encoding the intrinsic variant and correlated anisotropy sparsity structures of the CMC. We further proposed a robust and efficient PCT reconstruction algorithm to improve low-dose PCT reconstruction performance using the CMAA-TTV model. Experimental studies using a digital brain perfusion phantom, patient data with low-dose simulation and clinical patient data were performed to validate the effectiveness of the presented algorithm. The results demonstrate that the CMAA-TTV algorithm can achieve noticeable improvements over state-of-the-art methods in low-dose PCT reconstruction tasks.