High Consistency Research Articles

A Parallax Shift Effect Correction Based on Cloud Top Height for FY-4A Lightning Mapping Imager (LMI)

The Lightning Mapping Imager (LMI) onboard the Fengyun-4A (FY-4A) satellite is the first independently developed satellite-borne lightning imager in China. It enables continuous lightning detection in China and surrounding areas, regardless of weather conditions. The FY-4A LMI uses a Charge-Coupled Device (CCD) array for lightning detection, and the accuracy of lightning positioning is influenced by cloud top height (CTH). In this study, we proposed an ellipsoid CTH parallax correction (ECPC) model for lightning positioning applicable to FY-4A LMI. The model utilizes CTH data from the Advanced Geosynchronous Radiation Imager (AGRI) on FY-4A to correct the lightning positioning data. According to the model, when the CTH is 12 km, the maximum deviation in lightning positioning caused by CTH in Beijing is approximately 0.1177° in the east–west direction and 0.0530° in the north–south direction, corresponding to a horizontal deviation of 13.1558 km, which exceeds the size of a single ground detection unit of the geostationary satellite lightning imager. Therefore, it is necessary to be corrected. A comparison with data from the Beijing Broadband Lightning Network (BLNET) and radar data shows that the corrected LMI data exhibit spatial distribution that is closer to the simultaneous BLNET lightning positioning data. The coordinate differences between the two datasets are significantly reduced, indicating higher consistency with radar data. The correction algorithm decreases the LMI lightning location deviation caused by CTH, thereby improving the accuracy and reliability of satellite lightning positioning data. The proposed ECPC model can be used for the real-time correction of lightning data when CTH is obtained at the same time, and it can be also used for the post-correction of space-based lightning detection with other cloud top height data.

Evaluation of glomerular filtration rate estimation equations based on serum creatinine in healthy Chinese children and adolescents: a nationwide cross-sectional study

BackgroundSeveral equations for glomerular filtration rate (GFR) estimation based on serum creatinine (SCr) have been proposed for children, but most were developed among patients with kidney disease. The association between...

A novel method of carotid artery wall imaging: black-blood CT

ObjectivesTo evaluate the application of black-blood CT (BBCT) in carotid artery wall imaging and its accuracy in disclosing stenosis rate and plaque burden of carotid artery.MethodsA total of 110 patients underwent contrast-enhanced CT scan with two phases, and BBCT images were obtained using contrast-enhancement (CE)-boost technology. Two radiologists independently scored subjective image quality on black-blood computerized tomography (BBCT) images using a 4-point scale and then further analyzed plaque types. The artery stenosis rate on BBCT was measured and compared with CTA. The plaque burden on BBCT was compared with that on high-resolution intracranial vessel wall MR imaging (VW-MR imaging). The kappa value and intraclass correlation coefficient (ICC) were used for consistency analysis. The diagnostic accuracy of BBCT for stenosis rate and plaque burden greater than 50% was evaluated by AUC.ResultsThe subjective image quality scores of BBCT had good consistency between the two readers (ICC = 0.836, p < 0.001). BBCT and CTA had a good consistency in the identification of stenosis rate (p < 0.001). There was good consistency between BBCT and VW-MR in diagnosis of plaque burden (p < 0.001). As for plaque burden over 50%, BBCT had good sensitivity (93.10%) and specificity (73.33%), with an AUC of 0.950 (95%CI 0.838–0.993). Compared with CTA, BBCT had higher consistency with VW-MR in disclosing low-density plaques and mixed plaques (ICC = 0.931 vs 0.858, p < 0.001).ConclusionsBBCT can not only display the carotid artery wall clearly but also accurately diagnose the stenosis rate and plaque burden of carotid artery.Clinical relevance statementBlack-blood CT, as a novel imaging technology, can assist clinicians and radiologists in better visualizing the structure of the vessel wall and plaques, especially for patients with contraindication to MRI.Key Points• Black-blood CT can clearly visualize the carotid artery wall and plaque burden.• Black-blood CT is superior to conventional CTA with more accurate diagnosis of the carotid stenosis rate and plaque burden features.

Value of biplane transrectal ultrasonography plus micro-flow imaging in preoperative T staging and rectal cancer diagnosis in combination with CEA/CA199 and MRI

BackgroundRectal cancer is one of the most common malignant tumors and has a high incidence rate and fatality rate. Accurate preoperative T staging of rectal cancer is critical for the selection of appropriate rectal cancer treatment. Various pre-operative imaging methods are available, and the identification of the most accurate method for clinical use is essential for patient care. We investigated the value of biplane transrectal ultrasonography (TRUS) combined with MFI in preoperative staging of rectal cancer and explored the value of combining TRUS plus MFI with CEA/CA199 and MRI.MethodsA total of 87 patients from Daping Hospital with rectal cancer who underwent TRUS examination plus MFI were included. Grades of MFI were determined by Alder classification. Among the total patients, 64 underwent MRI and serum CEA/CA199 tests additionally within one week of TRUS. Pathological results were used as the gold standard for cancer staging. Concordance rates between TRUS, MRI, and CEA/CA199 for tumors at different stages were compared.ResultsThere were no significant differences between the Alder classification and pathological T staging. The concordance rate of TRUS and MFI for rectal cancer T staging was 72.4% (K = 0.615, p < 0.001). Serum CEA and CA199 levels were significantly different in tumors at different stages and increased progressively by pathological stage (p < 0.001); the accuracy rate was 71.88% (K = 0.599, p < 0.001), while that of MRI was 51.56% (K = 0.303, p < 0.001), indicating that TRUS had higher consistency in the preoperative T staging of rectal cancer. The combination of TRUS, MRI, and CEA/CA199 yielded an accuracy rate of 90.6%, which was higher than that of any method alone.ConclusionsPreoperative T staging of rectal cancer from biplane TRUS plus MFI was highly consistent with postoperative pathological T staging. TRUS combined with MRI and serum CEA/CA199 had a greater value in the diagnosis of rectal cancer and a higher diagnostic rate than any examination alone.

Improving Global Subseasonal to Seasonal Precipitation Forecasts Using a Support Vector Machine‐Based Method

AbstractSubseasonal to seasonal (S2s) precipitation forecasts provide great potential for hydrological forecasting at an extended range. The study proposed a support vector machine (SVM) regression‐based method to improve S2s precipitation forecasts from the European Center for Medium‐Range Weather Forecasts (ECMWF) across the globe (60°N to 60°S). Results suggested that the SVM‐based method significantly improved ECMWF daily precipitation forecasts in representing the spatiotemporal variation of precipitation with higher consistency and reduced errors when compared against observations. Furthermore, the SVM‐based method enhanced the probabilistic skill of ECMWF forecasts, providing improved ranked probability skill score (RPSS) for real‐time forecasts in 2020 (e.g., RPSSECMWF = −0.03 and RPSSrg3 = 0.08 for lead week 1). The most substantial improvement from the SVM‐based method is witnessed in regions with complex terrains where ECMWF yielded the worst skill, such as the Andes mountain range, Congo River Basin, and the Tibet Plateau. However, the SVM‐based post‐processing method did not alter the characteristics of precipitation forecasts regarding climate zone and lead time. Both ECMWF and post‐processed forecasts showed higher skill in the temperate and continental climate zones when the lead time is shorter than 2 weeks. In comparison, low‐latitude regions exhibited higher predictability when the lead time is longer than 5 weeks, which is attributed to the slow variation of boundary conditions such as the El Niño‐Southern Oscillation (ENSO).

Energy saving potential of interstage screen fractionation for production of board grade BCTMP

Over the last few decades, the continuing decline in mechanical pulp-based grades has led pulp producers to modify operations and implement measures to reduce production costs in order to stay competitive. In spite of a considerable effort to reduce energy consumption, the latter is still a major portion of production costs in the process of making bleached chemithermomechanical pulp (BCTMP). In this study, we evaluated the impact of interstage screening fractionation (ISSF) and secondary refining strategy for producing BCTMP with the objective of reducing refining energy consumption while maintaining or improving bulk and strength properties. In the first step and to establish a baseline for a mill’s existing configuration, the collected primary refined pulp and reject streams from the ISSF were refined in a high consistency (HC) refiner to target freeness levels. The accepts and refined rejects streams were recombined, and their properties were compared to those of the refined primary pulp. The results showed that, at a given freeness of 400 mL and compared to the control case (without fractionation), the ISSF using an 0.070 in. basket followed by rejects refining could lead to about 25% energy saving in the second stage HC refining. Handsheet properties showed that utilization of ISSF could produce BCTMP with higher bulk and similar average fiber length and tear index. However, a slight reduction in tensile strength was observed. In the second set of trials, the primary refined pulp and the rejects from the ISSF using the 0.070 in. basket were refined by a low-consistency (LC) refiner. The results showed that, at the same freeness of 400 mL and compared to refined primary pulp, the ISSF saved about 26% in net LC refining energy. At a specific edge load (SEL) of 0.4 J/m, the produced pulp had similar bulk and strength properties compared to those of the control sample. A higher SEL of 0.6 J/m in LC refining could further decrease net refining energy consumption; however, it also led to reduction in fiber length, bulk, and strength properties.

Visual perception-oriented quality assessment for high dynamic range stereoscopic omnidirectional video system

High dynamic range stereoscopic omnidirectional video (HSOV) system provides users with an immersive visual experience, but the distortions generated in the process of visual content generation, coding, and visualization also brings challenges to visual quality assessment. This paper proposes a visual perception-oriented quality metric for HSOV system. Considering the computational efficiency, for frames within each second, several key frames are selected so that features reflecting distortions can be extracted from the viewports and equi-angular cubemap (EAC) projection surfaces of these frames. In viewport feature extraction module, the sum and difference maps of the left and right views of the key frames are used to simulate the binocular perception. Considering that distortions will affect the structure, color and statistical properties of the image, the gradient, local binary pattern and statistical features are extracted, respectively. To reduce projection distortion, EAC projection is used to instead of other projections normally used in quality assessment, and the Sigma domain feature extraction and color feature extraction are performed on EAC projection map. In temporal feature extraction module, wavelet decomposition is used to perform temporal domain bandpass filtering on partial continuous frames to calculate the naturalness features. Finally, the above features of the frames at different scales are pooled through random forest model to predicate the quality score of HSOV. Experimental results on the NBU-HSOVD dataset show that the proposed metric is superior to some blind image/video quality assessment metrics and has higher consistency with the human visual perception.

Validating ASHS-T1 automated entorhinal and transentorhinal cortical segmentation in Alzheimer's disease

The current study aimed to validate entorhinal and transentorhinal cortical volumes measured by the automated segmentation tool Automatic Segmentation of Hippocampal Subfields (ASHS-T1). The study sample comprised 34 healthy controls (HCs), 37 individuals with amnestic mild cognitive impairment (aMCI), and 29 individuals with Alzheimer's disease (AD) dementia from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Entorhinal and transentorhinal cortical volumes were assessed using ASHS-T1, manual segmentation, as well as a widely used automated segmentation tool, FreeSurfer v6.0.1. Mean differences, intraclass correlation coefficients, and Bland–Altman plots were computed. ASHS-T1 tended to underestimate entorhinal and transentorhinal cortical volumes relative to manual segmentation and FreeSurfer. There was variable consistency and low agreement between ASHS-T1 and manual segmentation volumes. There was low-to-moderate consistency and low agreement between ASHS-T1 and FreeSurfer volumes. There was a trend toward higher consistency and agreement for the entorhinal cortex in the aMCI and AD groups compared to the HC group. Despite the differences in volume measurements, ASHS-T1 was sensitive to entorhinal and transentorhinal cortical atrophy in both early and late disease stages. Based on the current study, ASHS-T1 appears to be a promising tool for automated entorhinal and transentorhinal cortical volume measurement in individuals with likely underlying AD.

Study on a semi-resolved CFD-DEM method for rod-like particles in a gas-solid fluidized bed

Based on a semi-resolved CFD-DEM coupling method, this study proposed a method that uses the minimum distance between the fluid grid and the particle boundary as a reference value to determine the degree of influence of the target fluid grid on the particle's drag force. A fluidized bed of rod-like particles was chosen as a typical case to investigate the effect of different fluid grid scales on various fluidized bed characteristic parameters. The calculation performance of the semi-resolved and unresolved CFD-DEM coupling algorithm on key fluidized bed characteristic parameters such as average pressure drop, particle frequency distribution with bed height, and particle orientation distribution were compared. It was found that the semi-resolved CFD-DEM coupling algorithm gradually obtained results with higher consistency with decreasing fluid grid scale for key parameters such as particle frequency distribution with bed height, particle orientation distribution, and time-history mixing index, exhibiting a phenomenon similar to grid independence in fluid simulation. By comparing with experimental results, it was verified that the semi-resolved CFD-DEM coupling algorithm can be applied to simulate multi-granular gas-solid systems with fluid grid scales equivalent to particle scales. This algorithm solves the limitation of fluid grid scale in the unresolved CFD-DEM coupling framework and improves the grid adaptability of the CFD-DEM coupling simulation algorithm.

Artificial intelligence can accurately distinguish IgA nephropathy from diabetic nephropathy under Masson staining and becomes an important assistant for renal pathologists.

Hyperplasia of the mesangial area is common in IgA nephropathy (IgAN) and diabetic nephropathy (DN), and it is often difficult to distinguish them by light microscopy alone, especially in the absence of clinical data. At present, artificial intelligence (AI) is widely used in pathological diagnosis, but mainly in tumor pathology. The application of AI in renal pathological is still in its infancy. Patients diagnosed as IgAN or DN by renal biopsy in First Affiliated Hospital of Zhejiang Chinese Medicine University from September 1, 2020 to April 30, 2022 were selected as the training set, and patients who diagnosed from May 1, 2022 to June 30, 2022 were selected as the test set. We focused on the glomerulus and captured the field of the glomerulus in Masson staining WSI at 200x magnification, all in 1,000 × 1,000 pixels JPEG format. We augmented the data from training set through minor affine transformation, and then randomly split the training set into training and adjustment data according to 8:2. The training data and the Yolov5 6.1 algorithm were used to train the AI model with constant adjustment of parameters according to the adjusted data. Finally, we obtained the optimal model, tested this model with test set and compared it with renal pathologists. AI can accurately detect the glomeruli. The overall accuracy of AI glomerulus detection was 98.67% and the omission rate was only 1.30%. No Intact glomerulus was missed. The overall accuracy of AI reached 73.24%, among which the accuracy of IgAN reached 77.27% and DN reached 69.59%. The AUC of IgAN was 0.733 and that of DN was 0.627. In addition, compared with renal pathologists, AI can distinguish IgAN from DN more quickly and accurately, and has higher consistency. We constructed an AI model based on Masson staining images of renal tissue to distinguish IgAN from DN. This model has also been successfully deployed in the work of renal pathologists to assist them in their daily diagnosis and teaching work.

Comparative Study of the Crystal Structure and Simulated 3D Structure of the Hsp90N‐Inhibitor Complex

AbstractThe crystal structure of a target‐ligand plays an indispensable role in rational drug design, structural optimization, and understanding the molecular interaction mechanism. For drug targets without crystal structures, the simulated 3D structure will provide an alternative important reference. However, the credibility of the simulated structure and its difference from the real crystal structure deserve deep consideration. The complex crystal structures of the target Hsp90N and its four small molecular inhibitors has previously been successfully determined. Herein, computer‐aided molecular docking technology is applied to predict complex 3D structures, and the comparison between the simulated 3D structures and crystal structures is analyzed. Compared with the complex crystal structures, the simulated 3D structures of the four groups have higher consistency with the main chains, whereas the branch chains, binding modes of inhibitors, and molecular interactions are different in detail. Thus, the simulated 3D complex structure can provide useful information to guide drug design and structural optimization of inhibitors when the crystal structure is missing, but it cannot replace the crystal structure and should be used with caution.

Genomic profiling of cerebrospinal fluid ctDNA to characterize molecular features and monitor intracranial responses of patients with osimertinib-resistant non-small cell lung cancer with leptomeningeal metastases.

e21095 Background: Leptomeningeal metastasis (LM) indicates an unfavorable prognosis in non-small cell lung cancer (NSCLC). Due to the blood-brain barrier, plasma is not an ideal medium to evaluate osimertinib resistance mechanisms in patients with LM. This study aimed to use cerebrospinal fluid (CSF) as a source of ctDNA for characterizing molecular features and monitoring intracranial responses from patients with leptomeningeal metastases who progressed on osimertinib. Methods: From Jan 2020 to Nov 2022, 65 patients with advanced NSCLC, including 32 osimertinib-treated patients, 6 other TKI-treated patients, and 27 treatment-naïve patients, in Beijing Tiantan Hospital were enrolled in this study. CSF obtained via lumbar puncture was used for targeted sequencing and cytologic analysis. In parallel, paired plasma from 35 patients was also subjected to targeted sequencing. Results: Among 65 patients, the overall positive rate of CSF ctDNA was 77% (50/65), 94% (34/36) in patients with LM, and 55% (16/29) in patients with brain parenchymal metastases (p = 0.0002). CSF ctDNA analysis had a higher consistency with the cytologic diagnosis of LM than imaging. Among the patients cytologic diagnosed with LM, 94% (32/34) of the patients had positive CSF ctDNA analysis at the same time, while the positive diagnostic rate of imaging was only 39% (13/33). EGFR alteration was found in 97% (29/30) CSF of patients with LM who progressed on Osimertinib, including L858R (67%), exon19 deletion (17%), T790M (10%), L861Q (7%), G719X (7%) and L747X (7%). Other recurrent genes discovered in the CSF were TP53 (73%), PIK3CA (43%), ERBB2 (33%), POLE (33%), ALK (27%), BRCA2 (27%), BRAF (23%), BRCA1 (23%), RB1 (20%) and PALB (20%). In the 35 paired CSF-plasma pairs, more alterations were uniquely found in CSF than in plasma (71% vs 17%), and only 12% of alterations were shared. Serial surveillance of CSF ctDNA in 7 cases of LM patients treated with osimertinib found that the VAF of CSF ctDNA showed a highly consistent trend with the tumor cell fraction of cytology. Conclusions: For NSCLC patients with LM, liquid biopsy of CSF is more sensitive than plasma to characterize osimertinib-resistant mechanisms and guide follow-up treatment. Serial surveillance of CSF ctDNA dynamics may reflect the intracranial tumor responses, which still needs to be validated in a large sample size.

Mayonnaises from fresh or frozen egg yolk with rapeseed and sesame oils -the influence of egg yolk freezing and storage time and oils ratio

The rheological behavior of some mayonnaise varieties prepared from liquid egg yolks, fresh or frozen, whose oily phase is made up of mixtures of sesame oil and rapeseed oil was studied in the current paper. The study examined the influence of the freezing time of the egg yolk, of the ratio between the two types of oil, as well as of the storage time, on the rheological parameters (apparent viscosity, consistency coefficient, flow behavior index). It has been shown that all types of mayonnaise present non-Newtonian behavior (pseudoplastic), because the values of the flow behavior index established from the specific mathematical models (Ostwald de Waele and Herschel-Bulkley) are sub-unit, and the apparent viscosity decreases with the increase of the shear rate. Mayonnaises prepared from frozen egg yolks and those with an oily phase in which sesame oil is predominant, have a higher consistency. The oxidation stability was evaluated by determining the acid values, which increase slightly with the freezing time of the egg yolk and with the amount of sesame oil in the oily phase. From the color tests carried out in the CIELAB color space, the characteristic parameters L*, a* and b* were determined and the lightness of the mayonnaise was assessed.

Green banana biomass (Musa spp.) as a natural food additive in artisanal tomato sauce

This study aimed to prepare artisanal tomato sauce (TSC, control) containing 10% (TS10) or 20% (TS20) of whole green banana biomass (GBB). Tomato sauce formulations were evaluated for storage stability, sensory acceptability, and color and sensory parameters correlations. Data were subjected to Analysis of Variance, followed by the comparison of means by Tukey's test (p < 0.05 and p < 0.01). Correspondence analysis was used to assess the responses to a Check-All-That-Apply questionnaire. A significant effect was observed (p > 0.05) for the interaction between storage time and GBB addition on all physicochemical parameters. GBB reduced titratable acidity and total soluble solids (p < 0.05), possibly because of its high content of complex carbohydrates. All tomato sauce formulations had adequate microbiological quality for human consumption after preparation. Sauce consistency increased with increasing GBB concentrations, improving the sensory acceptance of this attribute. All formulations achieved the minimum threshold for overall acceptability (70%). A thickening effect was observed with the addition of 20% GBB, resulting in significantly (p < 0.05) higher body, higher consistency, and reduced syneresis. TS20 was described as firm, very consistent, light orange in color, and very smooth. The results support the potential of whole GBB as a natural food additive.

CT-based radiomics can identify physiological modifications of bone structure related to subjects' age and sex.

Radiomics of vertebral bone structure is a promising technique for identification of osteoporosis. We aimed at assessing the accuracy of machine learning in identifying physiological changes related to subjects' sex and age through analysis of radiomics features from CT images of lumbar vertebrae, and define its generalizability across different scanners. We annotated spherical volumes-of-interest (VOIs) in the center of the vertebral body for each lumbar vertebra in 233 subjects who had undergone lumbar CT for back pain on 3 different scanners, and we evaluated radiomics features from each VOI. Subjects with history of bone metabolism disorders, cancer, and vertebral fractures were excluded. We performed machine learning classification and regression models to identify subjects' sex and age respectively, and we computed a voting model which combined predictions. The model was trained on 173 subjects and tested on an internal validation dataset of 60. Radiomics was able to identify subjects' sex within single CT scanner (ROC AUC: up to 0.9714), with lower performance on the combined dataset of the 3 scanners (ROC AUC: 0.5545). Higher consistency among different scanners was found in identification of subjects' age (R2 0.568 on all scanners, MAD 7.232years), with highest results on a single CT scanner (R2 0.667, MAD 3.296years). Radiomics features are able to extract biometric data from lumbar trabecular bone, and determine bone modifications related to subjects' sex and age with great accuracy. However, acquisition from different CT scanners reduces the accuracy of the analysis.

Mapping Phenology of Complicated Wetland Landscapes through Harmonizing Landsat and Sentinel-2 Imagery

Wetlands are important CO2 sinks and methane sources, and their seasonality and phenological cycle play an essential role in understanding the carbon budget. However, given the spatial heterogeneity of wetland landscapes and the coarser spatial resolution of satellites, the phenological retrievals of wetlands are challenging. Here we examined the phenology of wetlands from 30 m harmonized Landsat/Sentinel-2 (LandSent30) and 500 m MODIS satellite observations using the ground phenology network PhenoCam as a benchmark. This study used all 11 available wetland PhenoCam sites (about 30 site years), covering diverse wetland types from different climate zones. We found that the LandSent30-based phenology results were in overall higher consistency with the PhenoCam results compared to MODIS, which could be related to the better explanation capacity of LandSent30 data in the heterogeneous landscapes of wetlands. This also means that the LandSent30 has an advantage over the 500 m MODIS regarding wetland vegetation phenological retrievals. It should be noted that the LandSent30 did not show a greatly improved performance, which could be related to the specificity and complexity of the wetlands landscape. We also illustrated the potential effects of the location and observation direction of PhenoCam cameras, the selection of Region of Interest (ROI), as well as the landscape composition of the site. Overall, this study highlights the complexity of wetland phenology from both ground and remote sensing observations at different scales, which paves the road for understanding the role of wetlands in global climate change and provides a basis for understanding the real phenological changes of wetland surfaces.

Dorsal Hand Vein Pattern Recognition: A Comparison between Manual and Automatic Segmentation Methods.

Various techniques for dorsal hand vein (DHV) pattern extraction have been introduced using small datasets with poor and inconsistent segmentation. This work compared manual segmentation with our proposed hybrid automatic segmentation method (HHM) for this classification problem. Manual segmentation involved selecting a region-of-interest (ROI) in images from the Bosphorus dataset to generate ground truth data. The HHM combined histogram equalization and morphological and thresholding-based algorithms to localize veins from hand images. The data were divided into training, validation, and testing sets with an 8:1:1 ratio before training AlexNet. We considered three image augmentation strategies to enlarge our training sets. The best training hyperparameters were found using the manually segmented dataset. We obtained a good test accuracy (91.5%) using the model trained with manually segmented images. The HHM method showed slightly inferior performance (76.5%). Considerable improvement was observed in the test accuracy of the model trained with the inclusion of automatically segmented and augmented images (84%), with low false acceptance and false rejection rates (0.00035% and 0.095%, respectively). A comparison with past studies further demonstrated the competitiveness of our technique. Our technique can be feasible for extracting the ROI in DHV images. This strategy provides higher consistency and greater efficiency than the manual approach.

How consistently do species leaf-out or flower in the same order? Understanding the factors that shape this characteristic of plant communities.

Plant species are frequently reported to undergo leaf-out and flowering in a consistent order from 1year to the next; however, only a limited number of these findings arise from studies encompassing many species or sites. Here, we evaluate the consistency in the order species leafed out in the northeastern United States using observations contributed to the USA National Phenology Network's Nature's Notebook platform. We repeated this analysis for flowering, evaluating a total of 132 species across 84 sites. We documented a relatively high degree of consistency in the order of both events among individual plants, with higher consistency in flowering. A small number of species pairs exhibited very high consistency in phenological order across several sites. The majority of species pairs exhibited variability in how consistently they underwent either leaf-out or flowering from site to site, which could be the result of either plastic or locally adaptive responses. Our investigation revealed that neither functional type nor seasonal position played a major role in shaping how consistently species leafed out or flowered in the same order. Instead, we found the number of days separating the events and interannual variability in timing to be the most influential factors driving the consistency in ordering.

Depth-Perception-Based Representation in Holistic Rating on ESL Essay Writing

This paper proposes to use depth perception to represent raters’ decision in holistic evaluation of ESL essays, as an alternative medium to conventional form of numerical scores. The researchers verified the new method’s accuracy and inter/intra-rater reliability by inviting 24 ESL teachers to perform different representations when rating 60 essays written by Chinese ESL learners. During numerical representation, the raters expressed their evaluation in the form of numbers, while with the DP-based method, the raters expressed their evaluation by marking distances with nail tags on a wood ruler with hidden scale marks. Then the researchers translated the distance results into numbers and compared the accuracy and inter/intra-rater consistency of the two approaches by referring to these essays’ criteria scores from eight expert raters. The results showed that DP-based method could improve raters’ performance, producing more similar results to experts’ scores, with higher consistency both among different raters and within the same individual rater.

Natural and miscellaneous agents for the prevention of acute radiation dermatitis: a systematic review and meta-analysis.

This systematic review and meta-analysis aimed to evaluate the available literature describing the efficacy of natural and miscellaneous agents in preventing acute radiation dermatitis (RD) in cancer patients. OVID MedLine, Embase, and Cochrane literature databases were searched from 1946 to January 2023 for randomized controlled trials studying the use of natural and miscellaneous agents to prevent RD. RevMan 5.4 was used for the meta-analysis to calculate the pooled effect sizes and 95% confidence intervals (CI) using the random effects analysis. For the systematic review and meta-analysis, 19 and 16 studies were included, respectively. Of the five studied natural products (aloe vera, oral enzymes, olive oil, calendula, and curcumin), only oral enzymes and olive oil significantly reduced the incidence of Radiation Therapy Oncology Group grade 2+ (RR: 0.42, 95%CI 0.30-0.58, p < 0.00001, RR: 0.66, 95% CI 0.51-0.85, p = 0.001, resp.). The oral enzymes also reduced the grade 3+ RD incidence (RR: 0.18, 95%CI 0.06-0.55, p = 0.003). The other agents demonstrated no significant effect. This review and meta-analysis on natural and miscellaneous agents in preventing RD in cancer patients demonstrated that oral enzymes and olive oil prevented RD severity. However, evidence supporting natural agents to prevent RD is inconsistent, mainly because of low studies numbers, low-quality study designs, and small sample sizes. Therefore, concrete conclusions cannot be made. Research on (new) natural or miscellaneous agents should focus on a randomized controlled double-blinded study design with a large patient population, a higher consistency in research methods, and clinician- and patient-reported outcomes.