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Aquaculture mapping is essential for monitoring and managing aquaculture resources. However, accurately geotargeting individual aquaculture ponds from medium-resolution remote sensing imagery remains challenging, and convolutional deep learning methods for identifying aquaculture ponds require labor-intensive pixel-level annotations. This paper presents a novel weakly-supervised learning method to derive pixel-level labels from image-level annotations for aquaculture ponds. Our approach uses iterative anti-adversarial attacks to refine localization results from multi-scale class activation maps (CAMs). The improved method integrates two regularization methods guided by aquaculture features to form a joint loss function for adversarial samples: discriminative water region suppression and non-aquaculture water class suppression. We also propose an aquaculture feature termed CFNDWI to constrain the localization results and generate high-quality pseudo-labels. As a result, the pseudo-labels are used to train semantic segmentation networks for accurately identifying aquaculture ponds. We evaluated the performance of our method using commonly-used backbones on 10 m Sentinel-2 imagery. Our method achieves Intersection over Union (IoU) values of 0.618–0.655 for pseudo-label generation, and IoU values of 0.664–0.708 for semantic segmentation, outperforming state-of-the-art weakly-supervised methods and public datasets. The effectiveness of each module of our method was also testified through ablation experiments. Our method leverages knowledge-driven aquaculture features to guide the data-driven adversarial learning process, addressing the lack of high-quality aquaculture datasets for model training. The code for implementing our method will be accessible at https://github.com/designer1024/WSLM-AQ.

Zirconium alloys are widely used as structural materials in civil power reactors, nuclear-powered aircraft carriers, nuclear submarines and space vehicles as well as medical materials due to their excellent nuclear properties and biocompatibility. Zirconium alloys serving in harsh environments are also facing the risk of corrosion failure. Due to the special characteristics of the service environment of the material itself, it is more difficult to simulate and test zirconium alloy corrosion, and to get effective answers to many questions. The corrosion of zirconium alloys includes uniform corrosion, nodular corrosion, stress corrosion and microbial corrosion. Its corrosion is also affected by the material composition, heat treatment process, surface roughness, oxide film composition, pH value of the solution, irradiation, thermal and hydro chemical environments as well as temperature, and other factors, and the protective measures include coatings and corrosion inhibitors and other ways. To further improve the corrosion resistance of zirconium alloys, it is suggested that in the future the study should be conducted in the following aspects: 1) The concentration of solid-solution elements in the zirconium alloy matrix; 2) The type of second-phase elements, grain size and distribution; 3) The growth mechanism of the oxide film; 4) The mode of bacterial attachment and the growth behaviors of the biofilm.

Coherent plane-wave compounding (CPWC) has attracted significant attention in preclinical research and clinical diagnosis. However, a trade-off exists in CPWC between the image quality and frame rate. Null subtraction imaging (NSI), as a novel beamforming method, can realize high-quality imaging with enhanced lateral resolution and suppressed grating lobes. This study explores NSI to reduce the number of emissions while preserving the imaging quality. The performance of the proposed method is assessed using the Plane-Wave Imaging Challenge in Medical Ultrasound datasets, including phantom and in vivo datasets. The results verify the potential of NSI in terms of frame rate improvement compared to the conventional delay and sum beamforming method. NSI with 5 and 15 plane-wave emissions is evaluated. For example, for the experimental phantom datasets, NSI with 15 plane-wave emissions improves the lateral full-width at half maximum by 0.10 in comparison to DAS with 75 plane-wave emissions. Moreover, the corresponding contrast ratio and generalized contrast-to-noise ratio increase from 25.11 to 31.19 dB and 0.63 to 0.68, respectively, indicating contrast improvement. Thus, compared to DAS with 75 plane-wave emissions, the proposed method accelerates data acquisition by a factor of 5, resulting in remarkable frame rate improvement.

AbstractContext Sinisan (SNS) has been used to treat psychosomatic diseases of the digestive system. But little is known about how SNS affects water immersion restraint stress (WIRS).Objective To study the effects of SNS on colonic tissue injury in the WIRS model.Materials and methods Forty-eight Kunming (KM) mice were randomized into 6 groups (n = 8): The control and WIRS groups receiving deionized water; the SNS low-dose (SL, 3.12 g/kg/d), SNS middle-dose (SM, 6.24 g/kg/d), SNS high-dose (SH, 12.48 g/kg/d), and diazepam (DZ, 5 mg/kg/d) groups; each with two daily administrations for 5 consecutive days. The 5 treatment groups were subjected to WIRS for 24 h on day 6. The effects of SNS on colon tissue injury caused by WIRS were assessed by changes in colon histology, inflammatory cytokines, brain-gut peptides, and tight junction (TJ) proteins levels. 16S rRNA gene sequencing was used to detect the regulation of the gut microbiota.Results SNS pretreatment significantly reduced TNF-α (0.75- to 0.81-fold), IL-6 (0.77-fold), and IFN-γ (0.69-fold) levels; and increased TJ proteins levels, such as ZO-1 (4.06- to 5.27-fold), claudin-1 (3.33- to 5.14-fold), and occludin (6.46- to 11.82-fold). However, there was no significant difference between the levels of substance P (SP) and vasoactive intestinal peptide (VIP) in the control and WIRS groups. SNS regulated the composition of gut microbiota in WIRS mice.Conclusion The positive effects of SNS on WIRS could provide a theoretical basis to treat stress-related gastrointestinal disorders.

Oligoasthenospermia is the primary cause of infertility. However, there are still enormous challenges in the screening of critical candidates and targets of oligoasthenospermia owing to its complex mechanism. In this study, stem cell factor (SCF), c-kit, and transient receptor potential vanilloid 1 (TRPV1) biosensors were successfully established and applied to studying apoptosis and autophagy mechanisms. Interestingly, the detection limit reached 2.787 × 10−15 g/L, and the quantitative limit reached 1.0 × 10−13 g/L. Furthermore, biosensors were used to investigate the interplay between autophagy and apoptosis. Schisandrin A is an excellent candidate to form a system with c-kit similar to SCF/c-kit with a detection constant (KD) of 5.701 × 10−11 mol/L, whereas it had no affinity for SCF. In addition, it also inhibited autophagy in oligoasthenospermia through antagonizing TRPV1 with a KD of up to 4.181 × 10−10 mol/L. In addition, in vivo and in vitro experiments were highly consistent with the biosensor. In summary, high-potency schisandrin A and two potential targets were identified, through which schisandrin A could reverse the apoptosis caused by excessive autophagy during oligoasthenospermia. Our study provides promising insights into the discovery of effective compounds and potential targets via a well-established in vitro-in vivo strategy.

Abstract Purpose Aerobic exercise has shown beneficial effects in the prevention and treatment of non-alcoholic fatty liver disease (NAFLD). Nevertheless, the regulatory mechanism is not turely clear. Therefore, we aim to clarify the possible mechanism by investigating the effects of aerobic exercise on NAFLD and its mitochondrial dysfunction. Methods NAFLD rat model was established by feeding high fat diet. and used oleic acid (OA) to treat HepG2 cells. Changes in histopathology, lipid accumulation, apoptosis, body weight, and biochemical parameters were assessed. In addition, antioxidants, mitochondrial biogenesis and mitochondrial fusion and division were assessed. Results The obtained in vivo results showed that aerobic exercise significantly improved lipid accumulation and mitochondrial dysfunction induced by HFD, activated the level of Sirtuins1 (Srit1), and weakened the acetylation and activity of dynamic-related protein 1 (Drp1). In vitro results showed that activation of Srit1 inhibited OA-induced apoptosis in HepG2 cells and alleviated OA-induced mitochondrial dysfunction by inhibiting Drp1 acetylation and reducing Drp1 expression. Conclusion Aerobic exercise alleviates NAFLD and its mitochondrial dysfunction by activating Srit1 to regulate Drp1 acetylation. Our study clarifies the mechanism of aerobic exercise in alleviating NAFLD and its mitochondrial dysfunction and provides a new method for adjuvant treatment of NAFLD.

Automatic cell counting provides an effective tool for medical research and diagnosis. Currently, cell counting can be completed by transmitted-light microscope, however, it requires expert knowledge and the counting accuracy which is unsatisfied for overlapped cells. Further, the image-translation-based detection method has been proposed and the potential has been shown to accomplish cell counting from transmitted-light microscope, automatically and effectively. In this work, a new deep-learning (DL)-based two-stage detection method (cGAN-YOLO) is designed to further enhance the performance of cell counting, which is achieved by combining a DL-based fluorescent image translation model and a DL-based cell detection model. The various results show that cGAN-YOLO can effectively detect and count some different types of cells from the acquired transmitted-light microscope images. Compared with the previously reported YOLO-based one-stage detection method, high recognition accuracy (RA) is achieved by the cGAN-YOLO method, with an improvement of 29.80%. Furthermore, we can also observe that cGAN-YOLO obtains an improvement of 12.11% in RA compared with the previously reported image-translation-based detection method. In a word, cGAN-YOLO makes it possible to implement cell counting directly from the experimental acquired transmitted-light microscopy images with high flexibility and performance, which extends the applicability in clinical research.

Cancer patients commonly suffer from loneliness, poor spiritual status, and fear of death; however, these evaluations are rarely revealed in urological cancer patients. Thus, this study aimed to assess the loneliness, spiritual well-being, and death perception, as well as their risk factors in urological cancer patients. A total of 324 urological (including renal, bladder, and prostate) cancer patients and 100 healthy controls were included. The University of California and Los Angeles loneliness scale (UCLA-LS), functional assessment of chronic illness therapy-spiritual well-being (FACIT-Sp), and death attitude profile-revised (DAP-R) scores were evaluated. The results showed that the UCLA-LS score was higher, but the FACIT-Sp score was lower in urological cancer patients than in healthy controls. According to the DAP-R score, fear of death, death avoidance, and approaching death acceptance were elevated, but neutral acceptance was lower in urological cancer patients than in healthy controls. Among urological cancer patients, the UCLA-LS score was highest but the FACIT-Sp score was lowest in bladder cancer patients; regarding the DAP-R score, fear of death and death avoidance were highest, but approaching death acceptance was lowest in bladder cancer patients. Interestingly, single/divorced/widowed status, bladder cancer diagnosis, higher pathological grade, surgery, systemic treatment, and local treatment were independent factors for higher UCLA-LS score or lower FACIT-Sp score. In conclusion, urological cancer (especially bladder cancer) patients bear increased loneliness and reduced spiritual well-being; they also carry higher fear of death, death avoidance, and approaching death acceptance but lower neutral acceptance of death.

BackgroundBrain gray matter alterations in patients with trigeminal neuralgia (TN) have been detected in prior neuroimaging studies, but the results are heterogeneous. The current study conducted coordinate-based meta-analyses across neuroimaging studies, aiming to find the pattern of brain anatomic and functional alterations in patients with TN.MethodsWe performed a systematic literature search of PubMed, Embase, and Web of Science to identify relevant publications. A multimodal meta-analysis for whole-brain voxel-based morphometry (VBM) studies and functional imaging studies in TN was performed using anisotropic effect size-based signed differential mapping.ResultsThe meta-analysis comprised 10 VBM studies with 398 TN patients and 275 healthy controls, and 13 functional magnetic resonance imaging studies with 307 TN patients and 264 healthy controls. The multimodal meta-analysis showed conjoint structural and functional brain alterations in the right fusiform gyrus and inferior temporal gyrus, bilateral thalamus, left superior temporal gyrus, left insula, and inferior frontal gyrus. The unimodal meta-analysis showed decreased gray matter volume alone in the left putamen, left postcentral gyrus, and right amygdala as well as only functional abnormalities in the left cerebellum, bilateral precuneus, and left middle temporal gyrus.ConclusionThis meta-analysis revealed overlapping anatomic and functional gray matter abnormalities in patients with TN, which may help provide new insights into the neuropathology and potential treatment biomarkers of TN.

Litsea cubeba, which is found widely distributed across the Asian region, functions as both an economic tree and a medicinal plant with a rich historical background. Previous investigations into its chemical composition and biological activity have predominantly centered on volatile components, leaving the study of non-volatile components relatively unexplored. In this study, we employed UPLC-HRMS technology to analyze the non-volatile components of L. cubeba branches and leaves, which successfully resulted in identifying 72 constituents. Comparative analysis between branches and leaves unveiled alkaloids, organic acids, and flavonoids as the major components. However, noteworthy differences in the distribution of these components between branches and leaves were observed, with only eight shared constituents, indicating substantial chemical variations in different parts of L. cubeba. Particularly, 24 compounds were identified for the first time from this plant. The assessment of antioxidant activity using four methods (ABTS, DPPH, FRAP, and CUPRAC) demonstrated remarkable antioxidant capabilities in both branches and leaves, with slightly higher efficacy observed in branches. This suggests that L. cubeba may act as a potential natural antioxidant with applications in health and therapeutic interventions. In conclusion, the chemical composition and antioxidant activity of L. cubeba provides a scientific foundation for its development and utilization in medicine and health products, offering promising avenues for the rational exploitation of L. cubeba resources in the future.

Abstract Background Measurement of the posterior tibial slope (PTS) angle has important applications in total knee replacement surgery, high tibial osteotomy, and anterior cruciate ligament reconstruction. This study aimed to determine the mean PTS of knee joints in healthy Chinese adults, and provide data to guide knee surgery in China. Methods A retrospective analysis of 1257 (n = 1233, 50.4% male) plain X-ray films of participants aged 25–59 years was performed. The picture archiving and communication system was used for PTS measurement. The PTS was defined as the angle between the vertical line of the tangent of the anterior tibial cortex of the proximal tibia, and the tangent line of the tibial cortex. Two imaging physicians conducted the PTS measurements independently, and both the inter- and intraclass correlation coefficients (ICCs) were calculated. Results The mean PTS value was 7.68 ± 3.84° (range: 0–21°). The left PTS was significantly smaller in males than in females (7.22 ± 3.89 vs 8.05 ± 3.60; P = 0.005). Additionally, the PTS in participants aged 25–29 years was significantly larger than that in the other age groups (Left side: 8.64 ± 3.73 vs 6.92 ± 3.42, 7.42 ± 3.75, 7.53 ± 3.98; P

Background: Electrocardiogram (ECG) and carotid ultrasound (CUS) are important tools for the diagnosis and prediction of cardiovascular disease (CVD). This study aimed to investigate the associations between ECG and CUS parameters and explore the feasibility of assessing carotid health with ECG.Methods: This cross-sectional cohort study enrolled 319 healthy Chinese subjects. Standard 12-lead ECG parameters (including the ST-segment amplitude [STA]), CUS parameters (intima-media thickness [IMT] and blood flow resistance index [RI]), and CVD risk factors (including sex, age, and systolic blood pressure [SBP]) were collected for analysis. Participants were divided into the high-level RI group (average RI ≥ 0.76, n = 171) and the normal RI group (average RI < 0.76, n = 148). Linear and stepwise multivariable regression models were performed to explore the associations between ECG and CUS parameters.Results: Statistically significant differences in sex, age, SBP, STA and other ECG parameters were observed in the normal and the high-level RI group. The STA in lead V3 yielded stronger significant correlations (r = 0.27–0.42, p < 0.001) with RI than STA in other leads, while ECG parameters yielded weak correlations with IMT (|r| ≤ 0.20, p < 0.05). STA in lead V2 or V3, sex, age, and SBP had independent contributions (p < 0.01) to predicting RI in the stepwise multivariable models, although the models for IMT had only CVD risk factors (age, body mass index, and triglyceride) as independent variables. The prediction model for RI in the left proximal common carotid artery (CCA) had higher adjusted R2 (adjusted R2 = 0.31) than the model for RI in the left middle CCA (adjusted R2 = 0.29) and the model for RI in the right proximal CCA (adjusted R2 = 0.20).Conclusion: In a cohort of healthy Chinese individuals, the STA was associated with the RI of CCA, which indicated that ECG could be utilized to assess carotid health. The utilization of ECG might contribute to a rapid screening of carotid health with convenient operations.

The Sendai Framework for Disaster Risk Reduction 2015–2030 (SFDRR) proposed seven targets comprising 38 quantified indicators and various sub-indicators to monitor the progress of disaster risk and loss reduction efforts. However, challenges persist regarding the availability of disaster-related data and the required resources to address data gaps. A promising way to address this issue is the utilization of Earth observation (EO). In this study, we proposed an EO-based disaster evaluation framework in service of the SFDRR and applied it to the context of tropical cyclones (TCs). We first investigated the potential of EO in supporting the SFDRR indicators, and we then decoupled those EO-supported indicators into essential variables (EVs) based on regional disaster system theory (RDST) and the TC disaster chain. We established a mapping relationship between the measurement requirements of EVs and the capabilities of EO on Google Earth Engine (GEE). An end-to-end framework that utilizes EO to evaluate the SFDRR indicators was finally established. The results showed that the SFDRR contains 75 indicators, among which 18.7% and 20.0% of those indicators can be directly and indirectly supported by EO, respectively, indicating the significant role of EO for the SFDRR. We provided four EV classes with nine EVs derived from the EO-supported indicators in the proposed framework, along with available EO data and methods. Our proposed framework demonstrates that EO has an important contribution to supporting the implementation of the SFDRR, and that it provides effective evaluation solutions.

Abstract Although hyperglycemia is associated with worse outcomes after aneurysmal subarachnoid hemorrhage (aSAH), there is no consensus on the optimal glucose control metric, acceptable in-hospital glucose ranges, or suitable insulin regimens in this population. In this single-center retrospective cohort study of aSAH patients, admission glucose, and hospital glucose mean (MHG), minimum (MinG), maximum (MaxG), and variability were compared. Primary endpoints (mortality, complications, and vasospasm) were assessed using multivariate logistic regressions. Of the 217 patients included, complications occurred in 83 (38.2%), 124 (57.1%) had vasospasm, and 41 (18.9%) died. MHG was independently associated with (p

PURPOSE: Aneurysmal recurrence represents a significant drawback of endovascular coiling, particularly in aneurysms that have previously ruptured. Given the high recurrence rate of coiled aneurysms and particularly the risk of posttreatment rupture in previously ruptured aneurysms that have been treated by coiling, the question of how best to treat ruptured aneurysms that recur postcoiling remains. MATERIALS AND METHODS: We conducted a retrospective analysis of twenty patients who underwent pipeline embolization of previously ruptured, coiled cerebral aneurysms. RESULTS: Pipeline embolization device (PED) treatment resulted in complete aneurysmal occlusion in 10 patients (62.5%) at first angiographic follow-up, and 11 patients (68.75%) at last follow-up. No PED-related complications were encountered and there were no peri-procedural or postprocedural hemorrhages, or symptomatic ischemic events following flow diversion. CONCLUSIONS: PED as a second-line treatment is a safe and effective modality for achieving aneurysmal occlusion in recurrent, previously ruptured, primarily coiled aneurysms. Additionally, a staged coil-to-PED approach may be considered for the management of acutely ruptured aneurysms to achieve aneurysmal obliteration in an effort to mitigate recurrence, and reduce the amount of postprocedural studies.

An acoustic hologram is crucial in various acoustics applications. The reconstruction accuracy of the acoustic field from the hologram is important for determining the performance of the acoustic hologram system. However, challenges remain in acoustic hologram reconstruction where the conventional reconstruction methods generally lack accuracy, complexity, and flexibility. Although the deep learning (DL)–based method has been used to overcome these limitations, it needs the labeled training data to optimize the network with a supervised strategy. To address the problem, we put forward a new unsupervised DL-based reconstruction method in this work, termed PhysNet-AH, which is implemented by integrating a convolutional neural network with a physical model representing the process of acoustics hologram formation. The results demonstrate that we only need to provide PhysNet-AH with a single acoustic field recorded from the hologram, the network parameters can be optimized automatically without the labeled training data, and finally implement the acoustic hologram reconstruction with high accuracy, in terms of SSIM and mean squared error indicators. Furthermore, with the trained model, the robustness and generalization capability of PhysNet-AH have also been well-demonstrated by reconstructing the acoustic fields from different diffraction distances or different datasets. As a result, PhysNet-AH opens the door for fast, accurate, and flexible acoustic hologram–based applications.

BackgroundNeuroimaging studies have shown gray matter structural and functional alterations in patients with idiopathic blepharospasm (iBSP) but with variations. Here we aimed to investigate the specific and common neurostructural/functional abnormalities in patients with iBSP.MethodsA systematic literature search from PubMed, Web of Science and Embase was conducted to identify relevant publications. We conducted separate meta-analysis for whole-brain voxel-based morphometry (VBM) studies and for functional imaging studies, and a multimodal meta-analysis across VBM and functional studies in iBSP, using anisotropic effect size-based signed differential mapping.ResultsThe structural database comprised 129 patients with iBSP and 144 healthy controls whilst the functional database included 183 patients with iBSP and 253 healthy controls. The meta-analysis of VBM studies showed increased gray matter in bilateral precentral and postcentral gyri, right supplementary motor area and bilateral paracentral lobules, while decreased gray matter in right superior and inferior parietal gyri, left inferior parietal gyrus, left inferior temporal gyrus, left fusiform gyrus and parahippocampal gyrus. The meta-analysis of functional studies revealed hyperactivity in right dorsolateral superior frontal gyrus, left thalamus and right fusiform gyrus, while hypoactivity in left temporal pole, left insula, left precentral gyrus, bilateral precuneus and paracentral lobules, right supplementary motor area and middle frontal gyrus. The multimodal meta-analysis identified conjoint anatomic and functional changes in left precentral gyrus, bilateral supplementary motor areas and paracentral lobules, right inferior occipital gyrus and fusiform gyrus.ConclusionsThe patterns of conjoint and dissociated gray matter alterations identified in the meta-analysis may enhance our understanding of the pathophysiological mechanisms underlying iBSP.

We demonstrate the nondestructive evaluation by means of directional ultrasound emitted from a planar metasurface. The ultrasound metasurface is designed to generate the collimated and directional ultrasound efficiently in a planar configuration, which is endowed with the full-2π-range phase manipulation ability and high transmittance up to 80%. We employ the directional emission based on the ultrasound metasurface to innovate the traditional nondestructive evaluation methods, benefited from the freely controlled directivity and the superior fitness to sample surface of the planar metasurface. Merits of this innovative application are evidenced by the remarkable accuracy (higher than 98%) in the thickness evaluation, and precise detection (accuracy higher than 96%) of the special defect inside the V-shaped workpiece which is intractable to be inspected conventionally. The implementation of the metasurface-based directional ultrasound emission in the nondestructive evaluation bears the advantages of high coupling efficiency, superior fitness, high accuracy, and applicability to special defect, providing new solutions to the challenges in conventional defect detection and promotes the development in the nondestructive evaluation applications.

Objective:This study investigated the COVID-19-prevention knowledge and practices of healthcare workers (HCWs), their psychological states concerning the return to work, and their trust and requirements in using traditional Chinese medicine (TCM) to prevent and treat COVID-19. It is hoped that the study can serve as a reference for policy making during the resumption of work in other countries or regions experiencing similar situations.Methods:This study comprised a quantitative cross-sectional online survey design. Purposive sampling and Cluster sampling were used to recruit all HCWs working in public hospitals in Huangzhou District, Huanggang City, Hubei Province, China. From April 23 to May 14, 2020, surveys were sent electronically to all 13 public hospitals in this area.Results:In total, 2,079 responses were received and 2,050 completed forms were included. After analysis, 47.9 and 46.6% of HCWs indicated that they possessed very good knowledge or good knowledge of preventative measures, respectively. Multivariable log-binomial regression indicated that male, tertiary hospital, medical staff, and undergraduate/postgraduate qualification were associated with good knowledge. Good knowledge was also well-correlated with good practice (OR: 3.277; 95% CI: 2.734–3.928; P < 0.01). 59.8% of HCWs reported worries about resuming work; especially asymptomatic infections. The Self-Rating Anxiety Scale (SAS) indicated that 10.8% of participants had mild anxiety, 1.5% moderate anxiety, and 0.1% severe anxiety. Female, divorced/widowed, and working in a high risk hospital (the Huangzhou District People's Hospital was used for throat swab examinations of returning workers) were risk factors for concerns about resuming work and anxiety symptoms. However, good preventive knowledge was a protective factor for anxiety. HCWs' trust in using TCM to treat COVID-19 was significantly higher than their trust in using TCM for prevention (P < 0.001). Regarding preferences for preventative TCM products, oral TCM granules were the most preferred (62.4%). HCWs also indicated they wanted to know more about the clinical efficacy, applicable population, and adverse reactions of preventative TCM products (89.3, 81.1, and 81.4%, respectively).Conclusion:While HCWs had good knowledge of COVID-19 preventative measures, this did not eliminate the psychological impact of resumption of work. Promotion of COVID-19 prevention knowledge reduces the risk of infection, and alleviates the worries and anxiety symptoms of HCWs about resuming work (especially in administrative staff, those with low education, and those working in primary hospitals). Additional psychological support is required for female HCWs, divorced/widowed HCWs, and those working in high-risk hospitals. Finally, systematic trials of preventative TCM products are recommended.

Aquaculture plays a key role in achieving Sustainable Development Goals (SDGs), while it is difficult to accurately extract single-object aquaculture ponds (SOAPs) from medium-resolution remote sensing images (Mr-RSIs). Due to the limited spatial resolutions of Mr-RSIs, most studies have aimed to obtain aquaculture areas rather than SOAPs. This study proposed an object-oriented method for extracting SOAPs. We developed an iterative algorithm combining grayscale morphology and edge detection to segment water bodies and proposed a segmentation degree detection approach to select and edit potential SOAPs. Then a classification decision tree combining aquaculture knowledge about morphological, spectral, and spatial characteristics of SOAPs was constructed for object filter. We selected a 707.26 km2 study region in Sri Lanka and realized our method on Google Earth Engine (GEE). A 25.11 km2 plot was chosen for verification, where 433 SOAPs were manually labeled from 0.5 m high-resolution RSIs. The results showed that our method could extract SOAPs with high accuracy. The relative error of total areas between extracted result and the labeled dataset was 1.13%. The MIoU of the proposed method was 0.6965, representing an improvement of between 0.1925 and 0.3268 over the comparative segmentation algorithms provided by GEE. The proposed method provides an available solution for extracting SOAPs over a large region and shows high spatiotemporal transferability and potential for identifying other objects.

Population distribution data with high spatiotemporal resolution are of significant value and fundamental to many application areas, such as public health, urban planning, environmental change, and disaster management. However, such data are still not widely available due to the limited knowledge of complex human activity patterns. The emergence of location-based service big data provides additional opportunities to solve this problem. In this study, we integrated ambient population data, nighttime light data, and building volume data; innovatively proposed a spatial downscaling framework for Baidu heat map data during work time and sleep time; and mapped the population distribution with high spatiotemporal resolution (i.e., hourly, 100 m) in Beijing. Finally, we validated the generated population distribution maps with high spatiotemporal resolution using the highest-quality validation data (i.e., mobile signaling data). The relevant results indicate that our proposed spatial downscaling framework for both work time and sleep time has high accuracy, that the distribution of the population in Beijing on a regular weekday shows “centripetal centralization at daytime, centrifugal dispersion at night” spatiotemporal variation characteristics, that the interaction between the purpose of residents’ activities and the spatial functional differences leads to the spatiotemporal evolution of the population distribution, and that China’s “surgical control and dynamic zero COVID-19” epidemic policy was strongly implemented. In addition, our proposed spatial downscaling framework can be transferred to other regions, which is of value for governmental emergency measures and for studies about human risks to environmental issues.

Circulating tumor cells (CTCs) have important applications in clinical practice on early tumor diagnosis, prognostic prediction, and treatment evaluation. Platinum-based chemotherapy is a fundamental treatment for non-small cell lung cancer (NSCLC) patients who are not suitable for targeted drug therapies. However, most patients progressed after a period of treatment. Therefore, revealing the genetic information contributing to drug resistance and tumor metastasis in CTCs is valuable for treatment adjustment. In this study, we enrolled nine NSCLC patients with platinum-based chemotherapy resistance. For each patient, 10 CTCs were isolated when progression occurred to perform single cell–level whole-exome sequencing (WES). Meanwhile the patients’ paired primary-diagnosed formalin-fixed and paraffin-embedded samples and progressive biopsy specimens were also selected to perform WES. Comparisons of distinct mutation profiles between primary and progressive specimens as well as CTCs reflected different evolutionary mechanisms between CTC and lymph node metastasis, embodied in a higher proportion of mutations in CTCs shared with paired progressive lung tumor and hydrothorax specimens (4.4–33.3%) than with progressive lymphatic node samples (0.6–11.8%). Functional annotation showed that CTCs not only harbored cancer-driver gene mutations, including frequent mutations of EGFR and TP53 shared with primary and/or progressive tumors, but also particularly harbored cell cycle–regulated or stem cell–related gene mutations, including SHKBP1, NUMA1, ZNF143, MUC16, ORC1, PON1, PELP1, etc., most of which derived from primary tumor samples and played crucial roles in chemo-drug resistance and metastasis for NSCLCs. Thus, detection of genetic information in CTCs is a feasible strategy for studying drug resistance and discovering new drug targets when progressive tumor specimens were unavailable.

Objective: the purpose of this paper was to investigate the effect of spectral computation methods on the estimation of the four ultrasonic backscatter parameters, namely, the apparent integrated backscatter (AIB), the zero frequency intercept of apparent backscatter (FIAB), the frequency slope of apparent backscatter (FSAB), and the backscatter spectral centroid shift (SCS) from the backscattered signal of interest (SOI), and their subsequent correlations with cancellous bone parameter [bone volume/total volume (BV/TV)]. Methods: ultrasonic backscatter measurements were performed on 26 bovine cancellous bone specimens using a 1.0-MHz focused transducer. Four spectral estimation algorithms, including the classical periodogram, the autoregressive (AR) Burg algorithm, the AR covariance algorithm, and the AR modified covariance algorithm, were used to calculate the ultrasonic parameters. Influence of the signal's delay time (T1) and its length (T2) on the strength of correlation between BV/TV and backscatter parameters was also studied. Results: the results have demonstrated that the AR-based estimators provide much more reliable and stronger correlations between the BV/TV and backscatter parameters than the classical periodogram. Recommendations for choosing SOI were also suggested. Conclusion: these results indicate that the AR-based method has a promising potential to enhance the performance of evaluation and diagnosis of the cancellous bone using the ultrasonic backscatter method. Significance: the enhancement of the correlation may provide a positive impact on the ultrasonic backscatter method to diagnose and monitor the bone quantity.

Metabolic bone disease (MBD) impacts the prognosis of premature infants. There is an urgent need for a portable, noninvasive, and radiation-free method for assessing neonatal bone status. The objective of this study is to evaluate the feasibility of the ultrasonic backscatter technique for assessing and monitoring cancellous bone status in neonates. Ultrasonic backscatter measurements were performed on 766 infants at birth and followed up weekly during hospitalization, utilizing transducers with central frequencies of 3.5 MHz and 5.0 MHz. Backscatter parameters, including apparent integrated backscatter (AIB), frequency intercept of apparent backscatter (FIAB), and frequency slope of apparent backscatter (FSAB) were calculated. Correlations were analyzed with both anthropometric and biochemical indices. We found that AIB (|r| = 0.40-0.47, p

Ultrasonic imaging provides a non-invasive way to diagnose brain disease. However, due to imaging degradation effects from the phase-aberration and reverberation, it is still challenging to achieve an accurate transcranial imaging. The objective of this work is to improve the quality of transcranial imaging. To this end, a ray theory based transcranial phase correction method was proposed to correct the phase abberation induced by cranial bones. With the pre-knowledge of the shape and longitudinal velocity of the cranial bones, the corrected phases are derived by solving eikonal equation (ray-theory). The Ideal Synthetic Aperture Focusing Technique (I-SAFT) is applied for signal acquisitions in simulations and in-vitro phantom experiment with one-element transmitting and all-element receiving method. Dynamic focusing is achieved at each imaging position with I-SAFT and the transcranial imaging distortion is modified with the proposed phase correction method. Simulations and experiments show that the imaging distortion of target circular phantoms was corrected, and the imaging quality is improved after the phase correction. With the proposed method, the average error of the central position of target phantoms decreases from 1.98 mm to 0.21 mm, the eccentricity of fitted ellipse averagely decreases from 0.63 to 0.19, and the average maximum luminance contrast of phantoms improves from 37.36dB to 42.41dB. It is illustrated that the proposed ray-theory based phase correction method might be useful for intracranial imaging.

The evaluation of mortality in earthquake-stricken areas is vital for the emergency response during rescue operations. Hence, an effective and universal approach for accurately predicting the number of casualties due to an earthquake is needed. To obtain a precise casualty prediction method that can be applied to regions with different geographical environments, a spatial division method based on regional differences and a zoning casualty prediction method based on support vector regression (SVR) are proposed in this study. This study comprises three parts: (1) evaluating the importance of influential features on seismic fatality based on random forest to select indicators for the prediction model; (2) dividing the study area into different grades of risk zones with a strata fault line dataset and WorldPop population dataset; and (3) developing a zoning support vector regression model (Z-SVR) with optimal parameters that is suitable for different risk areas. We selected 30 historical earthquakes that occurred in China’s mainland from 1950 to 2017 to examine the prediction performance of Z-SVR and compared its performance with those of other widely used machine learning methods. The results show that Z-SVR outperformed the other machine learning methods and can further enhance the accuracy of casualty prediction.