Shape Index Research Articles

Research on a Panoramic Image Stitching Method for Images of Corn Ears, Based on Video Streaming

Background: Corn is the main grain crop grown in China, and the ear shape index of corn is an important parameter for breeding new varieties, including ear length, diameter, row number of ears, row number of grains per ear, and so on. Objective: In order to solve the problem of limited field of view associated with computer detection of the corn ear shape index against a complex background, this paper proposes a panoramic splicing method for corn ears against a complex background, which can splice 10 corn ear panoramic images at the same time, to improve information collection efficiency, display comprehensive information, and support data analysis, so as to realize automatic corn seed examination. Methods: A summary of corn ear panoramic stitching methods under complex backgrounds is presented as follows: 1. a perceptual hash algorithm and histogram equalization were used to extract video frames; 2. the U-Net image segmentation model based on transfer learning was used to predict corn labels; 3. a mask preprocessing algorithm was designed; 4. a corn ear splicing positioning algorithm was designed; 5. an algorithm for irregular surface expansion was designed; 6. an image stitching method based on template matching was adopted to assemble the video frames. Results: The experimental results showed that the proposed corn ear panoramic stitching method could effectively solve the problems of virtual stitching, obvious stitching seams, and too-high similarity between multiple images. The success rate of stitching was as high as 100%, and the speed of single-corn-ear panoramic stitching was about 9.4 s, indicating important reference value for corn breeding and disease and insect detection. Discussions: Although the experimental results demonstrated the significant advantages of the panoramic splicing method for corn ear images proposed in this paper in terms of improving information collection efficiency and automating corn assessment, the method still faces certain challenges. Future research will focus on the following points: 1. addressing the issue of environmental interference caused by diseases, pests, and plant nutritional status on the measurement of corn ear parameters in order to enhance the stability and accuracy of the algorithm; 2. expanding the dataset for the U-Net model to include a wider range of corn ears with complex backgrounds, different growth stages, and various environmental conditions to improve the model’s segmentation recognition rate and precision. Recently, our panoramic splicing algorithm has been deployed in practical applications with satisfactory results. We plan to continue optimizing the algorithm and more broadly promote its use in fields such as corn breeding and pest and disease detection in an effort to advance the development of agricultural automation technology.

Association of “a body shape index” with the risk of developing colorectal cancer in U.S. patients with metabolic syndrome: evidence from the NHANES 1999–2018

BackgroundColorectal cancer (CRC) is the third most common cancer worldwide and presents a significant challenge to public health. Metabolic syndrome (MetS) is a condition that is predominantly characterized by abdominal obesity and metabolic abnormalities such as hypertension, hyperglycemia, and hyperlipidemia, and it is one of the critical risk factors for CRC. Traditional anthropometric measures have limitations in accurately assessing the risk associated with abdominal obesity. This study aimed to investigate the association between “A Body Shape Index” (ABSI) and the risk of developing CRC among individuals with MetS utilizing data from the National Health and Nutrition Examination Survey (NHANES).MethodsThis cross-sectional study conducted a statistical analysis of all adult participants who met the diagnostic criteria for MetS in the NHANES data from 1999 to 2018. The ABSI was calculated to quantify abdominal obesity. ABSI is derived from a formula that incorporates waist circumference (WC), body mass index (BMI), and height, and is calculated as ABSI = WC / (BMI^(2/3) × Height^(1/2)). Multivariate logistic regression modeling was used to examine the independent association between ABSI and CRC incidence. Receiver Operating Characteristic (ROC) curves were employed to analyze the ability of ABSI compared to traditional metrics in identifying CRC risk.ResultsThis study involved 16,018 MetS patients with a mean age of 51.8 years, of whom 50.3% were male and 49.7% were female. Logistic regression adjusted for confounders revealed a significant association between an elevated ABSI and an increased risk of developing CRC (odds ratio (OR): 1.433, 95% confidence interval (CI): 1.116 to 1.841; P = 0.005). ROC analyses confirmed that the predictive accuracy of the ABSI for the risk of developing CRC area under the curve (AUC): (0.668, 95% CI: 0.624 to 0.713) surpassed that of traditional measurement methods.ConclusionAmong individuals with MetS, the ABSI is linked to an elevated risk of developing CRC. Compared with traditional anthropometric indices, the ABSI is a superior predictive marker for the risk of developing CRC.

A New Parameter-Free Slope Unit Division Method That Integrates Terrain Factors

With increasing research on geological hazards and the development of geographic information technology, slope units play an increasingly important role in landslide susceptibility assessment and prevention work. The scientific and reasonable division of slope units directly impacts the accuracy and practicality of analysis results. Despite the significant progress in slope unit division techniques, most existing methods still have certain limitations, such as a strong dependence on manually set thresholds during the division process, resulting in low levels of automation and efficiency. To address this issue, a new parameter-free slope unit extraction algorithm that integrates terrain factors, called Terrain Factor Parameter-Free Slope Unit Division (TFPF-SU), is introduced. This eliminates the issue of manually setting parameter thresholds during the slope unit division process. This algorithm fully utilizes the terrain information provided by digital elevation models (DEMs) to accurately calculate the curvature, slope, and aspect data for each point. On the basis of the inherent consistency principles among slope, aspect, and curvature, object-oriented image segmentation technology is used to achieve slope unit division. We select Dongchuan District in Yunnan Province, China, as a test area to verify the TFPF-SU algorithm and conduct a detailed comparative analysis and validation of the results with those obtained via traditional hydrological analysis methods from both qualitative and quantitative perspectives. In the quantitative analysis, we utilize the size and shape of the slope units. The results indicate the following: ① the slope units obtained with the TFPF-SU method are more uniform in size, avoiding issues with oversized or irregularly shaped units; ② the slope unit shapes obtained with the TFPF-SU method are more reasonable, with about 70% of the units falling within a reasonable shape index range, compared to only about 32% with the hydrological method; and ③ the slope units produced by the TFPF-SU method align more closely with terrain authenticity, exhibiting a higher degree of topographical conformity.

Identification of SNPs and INDELS associated with duck egg quality traits through a genome-wide association analysis

Egg quality traits are economically important in the poultry industry. To explore the genetic architecture and identify potential candidate genes, a genome-wide association study (GWAS) was performed for 13 egg quality traits using data from whole-genome sequencing of 299 Longyan Shan-ma female ducks, including 12 quantitative traits and one qualitative trait, eggshell color (ESC; white, light green, green). From estimation of pedigree genetic parameters, heritability (h2) ranged from 0.022 to 0.996 for the 12 quantitative traits, with the highest h2 (0.996) for eggshell color a* value (ESCA) and the lowest h2 (0.022) for egg yolk percentage relative to EW. A total of 8,874 single nucleotide polymorphism (SNP)-based significant associations (1.0 × 10-6) and 247 insertion-deletion (indel)-based significant associations (1.00 × 10-5) were identified, including 5,980 SNPs and 159 indel markers. From 5,924 SNPs and 143 indels associated with ESC traits, 181 potential candidate genes were identified, and most significant SNPs and indels (P < 1.0 × 10-20) were located at 1.86 Mb (44.29-46.15 Mb) on chromosome 4. The top SNP (chr4:45325309:C>A; P = 7.97 × 10-43) and the top indel (chr4:45299595:delTTCCACTCCAC; P = 4.20 × 10-36) for the ESC a* value were within two known ESC candidate genes; ATP-binding cassette subfamily G member 2 (ABCG2) and protein kinase cGMP-dependent 2 (PRKG2). Of 56 SNPs and 16 indels associated with other egg quality traits, 46 potential candidate genes were identified including synapse differentiation-inducing 1-like (SYNDIG1L) for EW, and core histone macro-H2A.1 (LOC101795967) and neurogenin 1 (NEUROG1) for egg shape index; and four genes including collagen type VI alpha 3 chain (COL6A3), lysine demethylase 7A (KDM7A), LOC101802169, and sperm-associated antigen 16 (SPAG16) for egg yolk weight and the percentage of yolk to total egg weight. Of the 46 genes, the molecular functions of 22 are related to protein binding, indicating important roles in the formation of egg quality traits. Our findings provide new insight into the genetic basis of egg quality traits in ducks.

PERTURBATION IN MEANDER BEHAVIOUR OF A SUBTROPICAL RIVER IN INDIA UNDER VARIABLE NATURAL AND ANTHROPOGENIC CONTROLS

Meander morphology is perturbed worldwide by human interventions to a certain extent in the Anthropocene. To this end, the present study aims to investigate the meander behaviour, including its deformations, of the Kopai River, a subtropical river in India in the last 50 years (1970-2020). A total of 394 loops (134 loops each in 1970 and 1995 and 126 loops in 2020) were selected for the four river reaches – the upper, middle-upper, middle-lower, and lower reaches. The meandering behaviour was assessed using Mueller’s sinuosity index (SI), meander form index, meander shape index, and radius/wavelength ratio. The study found a higher meandering tendency in the lower and upper reaches controlled by fluvial hydraulics, and topographic factors. However, the middle reaches were comparatively stable. The meander loops along the middle reaches regular meander is the dominant meander type, however, more than 50% of meander loops for the lower reaches were intense meander types. Positive extensions were the predominant type of meander deformation in all the reaches. However, few negative extensions are found in the middle-upper and lower reaches, while irregular changes and cut-offs were only found in the lower reach. Thus, the upper and lower reaches exhibited more natural controls dotted with regular meander progression. The middle reaches characterized by higher Bouguer anomaly and steep basement gradient led to channel confinement. Besides, profuse sand mining and the brick kiln industries are perturbing the meander beahviour through human channel straightening, dwarfing the meander evolution in the middle reaches.

Methionine supplementation regulates eggshell quality and uterine transcriptome in late-stage broiler breeders

This study aimed to compare the effects of dietary methionine (Met) and 2-hydroxy-4-(methylthio)-butanoate (HMTBA) on the eggshell quality of broiler breeder hens and elucidate the mechanism of Met in improving eggshell quality from the perspectives of eggshell microstructure and shell gland physiological function. A total of 720 WOD188 broiler breeder hens at 40 wk old were assigned to 3 groups, with 8 replicates per group and 30 birds per replicate. Over 7 weeks, birds were fed a basal diet or the same diet supplemented with 0.15% Met or 0.17% HMTBA. Our findings revealed significant improvements in the Met group for egg shape index, shell thickness, breaking strength, and fracture toughness (P < 0.05), whereas the HMTBA group showed no significant improvements (P > 0.05). Met supplementation increased calcium and phosphorus levels in both serum and shell gland tissue (P < 0.05), and enhanced Ca2+ ATPase activity in shell gland tissue (P < 0.05). Histomorphological changes included enhanced mucosal fold dimensions and increased epithelial height in the shell gland (P < 0.05). Met also improved eggshell ultrastructure, resulting in a thicker effective layer and broader mammillae with fewer type B structures (P < 0.05). The mRNA levels for genes regulating eggshell ultrastructure, such as OC-116, CALB1, and ITM2C, were significantly upregulated in the Met group (P < 0.05). Transcriptome analysis identified 248 differentially upregulated genes in the Met group, primarily linked to the non-canonical Wnt/Ca2+ signaling pathway, crucial for calcium ion transport and cellular proliferation. This research highlights that Met supplementation improves eggshell quality by enhancing calcium transport and cellular proliferation in uterine function, particularly through the modulation of WNT11 and CALB1, influencing calcium deposition and ultrastructural development.

The Relationship between Mercury and Selenium in the Eggshell and Egg Content of the Whiskered Tern (Chlidonias hybridus)

Mercury and its compounds do not have beneficial biological roles in living organisms. In contrast, selenium, within permissible limits, is an essential micronutrient and antioxidant. There is an antagonistic relationship between mercury and selenium. Therefore, the molar ratio of selenium to mercury is used as an appropriate index. Measuring the mercury in the environment without considering the protective effects of selenium does not accurately reflect the risks posed by mercury. This study aimed to measure the mercury, selenium, and the molar ratio Se:Hg in the shell and content of the eggs of the Whiskered Tern (Chlidonias hybridus) in northern Iran. After the onset of egg laying, one egg was collected from each nest (38 eggs in total). The results showed that the concentration of mercury in the egg shell was higher, while the concentration of selenium and the molar ratio Se:Hg were higher in the egg content. A molar ratio Se:Hg in both the eggshell and the egg content indicates a positive effect of selenium in reducing the risks associated with mercury toxicity. The parameters of egg shape index, egg weight, and clutch size did not have a significant effect on the concentrations of mercury, selenium, and the molar ratio Se:Hg in the shell and egg content. There was a significant negative correlation between the concentration of mercury in the shell and the molar ratio Se:Hg in both the shell and egg content. The lack of a positive correlation between the concentrations of mercury or selenium in the shell and egg content suggests that the transferability of heavy metals from the egg to the embryo in the egg content cannot be confirmed.

Association of weight-adjusted waist index (WWI) and a body shape index (ABSI) with serum neurofilament light chain levels in a national study of U.S. adults

ObjectiveThis study explored how the weight-adjusted waist index (WWI) and a body shape index (ABSI) are related to serum neurofilament light chain (sNfL) levels among U.S. adults. We aimed to evaluate sNfL, which plays key roles in neuronal injury in neurological diseases, given its understudied connection to obesity.MethodsWe used cross-sectional data from the 2013–2014 National Health and Nutrition Examination Survey (NHANES) of people with complete information on the weight-adjusted waist index (WWI), a body shape index (ABSI), and serum neurofilament light chain (sNfL). Multiple linear regression analysis allowed us to investigate the separate connections among the WWI, ABSI, and sNfL. Moreover, interaction testing and subgroup analysis were performed to improve the general validity of our results. To assess any nonlinear correlations, we also performed threshold effect analysis and smoothed curve fitting.ResultsWWI and ABSI were positively linked with sNfL (WWI: β = 0.05, 95% CI 0.01–0.09; ABSI: β = 1.65, 95% CI 3.53–13.72). There was no clear reliance on this association according to subgroup analysis and interaction tests. Smoothed curve fitting and saturation effects also demonstrated nonlinear associations between WWI and ABSI and sNfL, with inflection points of 10.38 and 0.38, respectively.ConclusionIn the adult American population, while the WWI and ABSI are linearly positively correlated with serum neurofilament light protein (sNfL), the effect size is greater for the ABSI. This correlation provides fresh evidence connecting obesity to neurological conditions, deepening our comprehension of the extensive health impacts associated with obesity.Level of Evidence Level I, experimental studies.

Utility of Anthropometric Indexes for Detecting Metabolic Syndrome in Resource-Limited Regions of Northwestern China: Cross-Sectional Study.

Anthropometric indexes offer a practical approach to identifying metabolic syndrome (MetS) and its components. However, there is a scarcity of research on anthropometric indexes tailored to predict MetS in populations from resource-limited regions. This study aimed to examine the association between 8 easy-to-collect anthropometric indexes and MetS, and determine the most appropriate indexes to identify the presence of MetS for adults in resource-limited areas. A total of 10,520 participants aged 18-85 years from Ningxia Hui Autonomous Region, China, were included in this cross-sectional study. Participants were recruited through a stratified sampling approach from January 1, 2020, to December 31, 2021. MetS was defined using the International Diabetes Federation (IDF) criteria. Eight anthropometric indexes were examined, including BMI, waist-to-height ratio (WHtR), weight-adjusted waist index (WWI), conicity index, a body shape index (ABSI), lipid accumulation products (LAP), visceral obesity index (VAI), and the triglyceride-glucose (TyG) index. Logistic regression analysis and restricted cubic splines (RCSs) were applied to identify the association between the anthropometric indexes. The receiver operating characteristic curve and the area under the curve (AUC) were analyzed to identify and compare the discriminative power of anthropometric indexes in identifying MetS. The Youden index was used to determine a range of optimal diagnostic thresholds. Logistic regression analysis was applied to identify the association between the anthropometric indexes. A total of 3324 (31.60%) participants were diagnosed with MetS. After adjusting for age, ethnicity, current residence, education level, habitual alcohol consumption, and tobacco use, all the 8 indexes were positively correlated with the risks of MetS (P<.05). LAP presented the highest adjusted odds ratios (adjOR 35.69, 95% CI 34.59-36.80), followed by WHtR (adjOR 29.27, 95% CI 28.00-30.55), conicity index (adjOR 11.58, 95% CI 10.95-12.22), TyG index (adjOR 5.53, 95% CI 5.07-6.04), BMI (adjOR 3.88, 95% CI 3.71-4.05), WWI (adjOR 3.23, 95% CI 3.02-3.46), VAI (adjOR 2.11, 95% CI 2.02-2.20), and ABSI (adjOR 1.71, 95% CI 1.62-1.80). Significantly nonlinear associations between the 8 indexes and the risk of MetS (all Pnonlinear<.001) were observed in the RCSs. WHtR was the strongest predictor of MetS for males (AUC 0.91, 95% CI 0.90-0.92; optimal cutoff 0.53). LAP were the strongest predictor of MetS for females (AUC 0.89, 95% CI 0.89-0.90; optimal cutoff 28.67). Statistical differences were present between WHtR and all other 7 anthropometric indexes among males and overall (all P<.05). In females, the AUC values between LAP and BMI, WWI, ABSI, conicity index, VAI, and TyG index were significantly different (P<.001). No statistical difference was observed between LAP and WHtR among females. According to 8 anthropometric and lipid-related indices, it is suggested that WHtR and LAP are the most appropriate indexes for identifying the presence of MetS in resource-limited areas.

Diurnal Variation Reveals the Characteristics and Influencing Factors of Cool Island Effects in Urban Blue-Green Spaces

Urban blue-green space cooling island effect (BGCI) is effective in improving the thermal comfort of residents. However, there is little knowledge regarding the diurnal variation of BGCIs and the influencing factors. Therefore, we selected Beijing as the study area and used ECOSTRESS LST data and the inflection–maximum perspective method to explore the diurnal variation of BGCIs. Additionally, we investigated diurnal variations in the relative influence of the characteristics of the blue-green space itself, as well as the surrounding 2D and 3D landscape metrics using boosted regression tree model. The results indicated that BGCIs displayed distinct diurnal patterns. BGCIs progressively increased from sunrise to midday, decreased thereafter to sunset, reached its peak around midday, and diminished to a relatively low level and constant intensity at night. BGCIs of water bodies exhibited a significantly higher intensity compared to vegetation during the day, particularly around midday, with a difference in mean cooling intensity (CI) of 1.06 °C and mean cooling distance (CD) of 63.27 m, while the differences were minimal at night with a difference in mean CI of 0.02 °C and mean CD of 9.64 m. The features of vegetation had a more significant impact on BGCIs during the day, particularly around midday (CI: 32.30% around midday and 13.86% at night), while the 3D metrics influenced BGCIs more at night (CI: 26.40% around midday and 35.81% at night). The features of water bodies had a greater impact during the midday (52.87% around midday and 10.46% at night), with the landscape metrics of surrounding water bodies playing a more important role at night (15.56% around midday and 38.28% at night). The effect of tree height, shape index of vegetation, and surrounding building coverage ratio of water bodies on BGCIs exhibited opposite trends around midday and at night. Optimizing the landscape surrounding blue-green spaces is more cost-effective than the blue-green spaces themselves for nighttime thermal comfort, especially in 3D urban landscapes. These findings emphasize the imperative and essentiality of exploring diurnal variations in BGCIs, providing valuable information for mitigating UHI effects.

The predictive power of conventional and novel obesity indices in identifying metabolic syndrome among the southern Iranian populations: findings from PERSIAN cohort study

BackgroundMetabolic syndrome (MetS) contributes to an increased risk of cardiovascular diseases. Traditional metrics like body mass index (BMI) have limitations in discerning fat distribution. The purpose of this study was to evaluate the diagnostic accuracy of traditional and novel anthropometric indices in metabolic syndrome and its components in the south coast of Iran.MethodsIn this cross-sectional study, 2694 adults aged 35 to 70 were included. Comprehensive anthropometric and biochemical data were collected and analyzed. There were eight anthropometric indices evaluated in this study, including a body shape index (ABSI), body mass index (BMI), waist circumference (WC), waist-hip ratio (WHR), body roundness index (BRI), abdominal volume index (AVI), weight-adjusted waist index (WWI) and waist-height ratio (WHtR).ResultsWHtR (AUC: 0.766 for males, 0.799 for females), BRI (AUC: 0.766 for males, 0.799 for females), and AVI (AUC: 0.769 for males, 0.793 for females) were the best predictors of MetS. ABSI had the weakest correlation with metabolic variables.ConclusionsAVI, WHtR, BRI, and WHR were superior to other measures as anthropometric indexes for determining MetS and its components. The study contributes valuable insights into the utility of traditional and novel metrics in clinical practice, highlighting the need for standardized diagnostic approaches and further research in diverse populations.

ESTRADIOL IMPACTS MÜLLER GLIA AND ENDOTHELIAL CELL RESPONSES IN HYPERGLYCEMIC MICROENVIRONMENTS WITH ADVANCED GLYCATION END PRODUCTS

Diabetic retinopathy is a leading cause of vision loss in working adults, with disproportionate impact on women with lowered estrogen. Sex hormones and their receptors are significant to neuroprotection of the inner blood-retinal barrier (iBRB), a tissue that regulates transport across the neuroretina and vasculature. Moreover, high glucose levels in diabetes lead to the formation of advanced glycation end products (AGEs), which promote inflammation and iBRB breakdown to result in vision loss. This study examined the effects of supplemental estradiol on cell reactivity and cell barrier resistance within an in vitro model of hyperglycemia. Changes in morphology and expression of reactive oxygen species were examined when cells were exposed to a hyperglycemic medium containing AGEs, with and without supplemental estradiol. Cell morphology was assessed via changes in cell area and cell shape index, while intracellular ROS levels were measured using a ROS-sensitive dye. In addition, trans endothelial resistance (TEER) assays were used to measure changes in cell barrier function in response to hyperglycemic conditions, with and without supplemental estradiol. Results show that ROS levels in Müller glia in hyperglycemic conditions significantly decreased in response to supplemental estradiol. The estradiol further increased the resistivity of Müller glia and endothelial cell barriers cultured in high glucose and AGEs. This project illustrates the restorative effects of estradiol in collective responses of cell barriers formed by endothelial cells and Müller glia.

Online Task Switching and Scheduling Method for Attitude–Orbit–Shape-Distributed Control of Large Space Ring Structures

The attitude, orbit, and shape control actuators of large space structures on orbits are functional overlapping and task coupled, resulting in actuator redundancy and high-energy consumption. This paper explores the integrated attitude–orbit–shape control problem of large space ring structures and proposes an online task switching and scheduling method for multiple actuators of space structures (OTSS-MASS). An adaptive allocation framework is proposed for the task switching of distributed actuators. The objectives of attitude–orbit–shape control are decomposed into attitude adjustment, orbit change, and shape maintenance tasks through a task decomposition algorithm. Task value estimation models are designed to guide a greedy task allocation of actuators. The adaptive allocation framework achieves online task reconfiguration for multiple distributed actuators, thereby enhancing the maneuverability of large space structures, improving actuator work efficiency, and reducing energy consumption in orbit. Simulation results demonstrate that OTSS-MASS outperforms the conventional actuator distribution methods. The overall effectiveness is improved by over 24% in terms of the comprehensive index, time index, trajectory index, and shape index.

Assessment of active tectonics based on GIS and statistical model: A case study of upper Alaknanda catchment (western Himalaya, India)

Due to continuing deformation of the Earth’s crust, degradation and aggradation processes, the upper part of the Alaknanda basin lying in the Garhwal Himalaya, India, is considered to be tectonically active. Active tectonics in this region made a considerable impact on the drainage system and the topographic expression. Using a digital elevation model (DEM) with a resolution of 30 m * 30 m and based on eight geomorphic indices [hypsometric integral (HI), drainage texture (Dt), asymmetry factor (AF), ruggedness number (Rd), circularity ratio (Rc), valley floor width/height ratio (Vfw), lemniscate coefficient (k) and basin shape index (Bs)], we evaluated active tectonics. Application of Index of Active Tectonic (IAT) and clustering model disclose the sub-watersheds in the southern part covering watersheds 16, 17 and near Badrinath sub-watershed 4, 9 and 8 are tectonically highly active (Class-1, 1.500-1.781). Cluster analysis defines two prominent clusters of sub-watersheds: 2, 4,14 and 15 in cluster 1; and 6, 7, 8 and 18 in cluster 2. Cluster 1 includes sub-watersheds 2, 4, 14, 15, and 16 and very high, high, and moderate IAT magnitudes. Sub-watersheds 6, 7, 8, and 18 are included in Cluster 2, which has very high and high tectonic activity

Genome-wide association study identifies key quantitative trait loci (QTL) for fruit morphometric traits in avocado (Persea spp.)

BackgroundAvocado, a fruit crop renowned for its high nutritional value, has seen a steadily increasing market demand. However, breeding efforts for avocados have lagged those for other commercial fruits due to limited genomic research and germplasm resources. To address this shortfall, a genome-wide association study was conducted on 122 avocado accessions from the United States Department of Agriculture (USDA) Agricultural Research Service (ARS) Subtropical Horticultural Research Station (SHRS) germplasm collection. The study aimed to identify genetic markers and regions associated with various morphometric traits in avocado fruits, including fruit weight, length, width, diameter, seed weight, seed length, seed width, fruit seed ratio (FSR), and fruit shape index (FSI).ResultsLeveraging 4,226 high-quality single nucleotide polymorphism (SNP) markers obtained from genotyping arrays, fifteen markers were identified with strong associations with these traits, utilizing Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway (BLINK) and Fixed and random model Circulating Probability Unification (FarmCPU) models. Gene annotation analyses within a 200-kb window in the vicinity of significant SNPs revealed several genes associated with various metabolic pathways suggesting that some of them likely determine these fruit quality traits, which needs to be verified and validated. Our results, which were conducted at one location, provide directions for conducting future studies using high-resolution genotyping and long-term multi-year and multi-location trait evaluations for precisely identifying the causal SNP(s) and genes associated with these traits.ConclusionsThese markers reported in this manuscript provide valuable tools for applying marker-assisted selection (MAS) in avocado breeding programs aimed at enhancing fruit quality and value.

Fetal gestational age prediction via shape descriptors of cortical development.

Gyrification is the intricate process through which the mammalian cerebral cortex develops its characteristic pattern of sulci and gyri. Monitoring gyrification provides valuable insights into brain development and identifies potential abnormalities at an early stage. This study analyzes the cortical structure in neurotypical and pathological (spina bifida) fetuses using various shape descriptors to shed light on the gyrification process during pregnancy. We compare morphometric properties encoded by commonly used scalar point-wise curvature-based signatures-such as mean curvature (H), Gaussian curvature (K), shape index (SI), and curvedness (C)-with multidimensional point-wise shape signatures, including spectral geometry processing methods like the Heat Kernel Signature (HKS) and Wave Kernel Signature (WKS), as well as the Signature of Histograms of Orientations (SHOT), which combines histogram and signature techniques. These latter signatures originate from computer graphics techniques and are rarely applied in the medical field. We propose a novel technique to derive a global descriptor from a given point-wise signature, obtaining GHKS, GWKS, and GSHOT. The extracted signatures are then evaluated using Support Vector Regression (SVR)-based algorithms to predict fetal gestational age (GA). GSHOT better encodes the GA to other global multidimensional point-wise shape signatures (GHKS, GWKS) and commonly used scalar point-wise curvature-based signatures (C, H, K, SI, FI), achieving a prediction R 2 of 0.89 and a mean absolute error of 6 days in neurotypical fetuses, and a R 2 of 0.64 and a mean absolute error of 10 days in pathological fetuses. GSHOT provides researchers with an advanced tool to capture more nuanced aspects of fetal brain development and, specifically, of the gyrification process.

Random generation of three-dimensional realistic ballast particles using generative adversarial networks

Natural ballast particles exhibit a wide array of shape characteristics and follow complex probability distributions, which are difficult to quantify using explicit formulas due to their implicit nature. Traditional methods for generating ballast particles are limited to shapes that adhere to specific shape indices. In this study, generative adversarial networks (GANs) were utilized to randomly generate realistic three-dimensional (3D) ballast particles. Representative ballast particle shapes were captured using 3D structured light scanning technology. The scanned shapes were then voxelized and augmented to create a comprehensive dataset representing various ballast particle shapes. This dataset served to train the generator and discriminator components of the GANs. The trained generator successfully produced 2,000 detailed 3D ballast particles. Further refinement of these particles was achieved using Gaussian blur, followed by the Laplace smoothing algorithms and marching cubes algorithm for surface reconstruction. The authenticity of the generated ballast particles was validated by comparing their shape indices with those of natural ballast particles, thus demonstrating the effectiveness of the trained GANs model. The generated ballast particles are suitable for use as templates in discrete element method (DEM) simulations, specifically for clumps and polyhedrons.

Using a Light Gradient-Boosting Machine–Shapley Additive Explanations Model to Evaluate the Correlation Between Urban Blue–Green Space Landscape Spatial Patterns and Carbon Sequestration

Global ecosystems are facing challenges posed by warming and excessive carbon emissions. Urban areas significantly contribute to carbon emissions, highlighting the urgent need to improve their ability to sequester carbon. While prior studies have primarily examined the carbon sequestration benefits of single green or blue spaces, the combined impact of urban blue–green spaces (UBGSs) on carbon sequestration remains underexplored. Meanwhile, the rise of machine learning provides new possibilities for assessing this nonlinear relationship. We conducted a study in the Yangzhou urban area, collecting Landsat remote sensing data and net primary productivity (NPP) data at five-year intervals from 2001 to 2021. We applied the LightGBM-SHAP model to systematically analyze the correlation between UBGSs and NPP, extracting key landscape metrics. The results indicated that landscape metrics had varying impacts on NPP. At the patch and type level, the Percentage of Landscape was significantly positively correlated with NPP in green space, while the contiguity index and fractal dimension index favored carbon sequestration under certain conditions. The contribution of blue space was lower, with some indicators exhibiting negative correlations. At the landscape level, the contagion index and aggregation index of UBGS had positive effects on NPP, while the division index and landscape shape index were negatively correlated with NPP. The results enhance the understanding of the relationship between UBGS and carbon sequestration, and provide a reference for urban planning.

Bioclimatic variables affect seed mass and seedling traits of four Gymnocalycium (Cactaceae) species along elevational gradients

Differences in climatic factors associated with elevation can lead to natural selection for local adaptation in species with a wide distribution range, with some regenerative characteristics changing along the gradient. Most Cactaceae species occur in heterogeneous environments, mainly in mountains. The increasing severity of environmental conditions along elevational gradients could affect seed size, influencing seedling growth. The main aims of the study were to analyse whether seed mass, and seedling size and shape are related to elevational gradients in different populations of four species of the genus Gymnocalycium and to evaluate the relationship between seed mass and bioclimatic variables. Populations of four species of Gymnocalycium (G. andreae, G. erinaceum, G. monvillei and G. mostii) were sampled; the populations were located along three different elevation gradients, with each population corresponding to an elevational class (extremes and intermediate sites). At each elevational site, mature fruits were collected and seed mass and seedling traits were measured. A shape index was calculated by dividing height by width. A value of 1 represents 'globose' seedlings, while increasing values indicate that the seedlings become 'columnar'. The Pearson correlation coefficient was calculated to analyse the relationship between seed mass and seedling size variables. Linear models were used to analyse seed size and seedling shape. First, with elevation as a predictor and then for seed mass, the 19 bioclimatic variables were extracted from WorldClim. The results show that seed mass was positively correlated with seedling shape index, and with seedling height and width. Differences in seed mass among populations were explained by the species and the gradient where they lived, as well as by the environmental variables mean temperature of the coldest quarter, precipitation of the wettest month, and precipitation of the driest month. In conclusion, the intraspecific analyses of the four Gymnocalycium species revealed that the seedling shape patterns were similar across all species in relation to elevation. However, seed mass varied with elevation differently for each species. These findings suggest that each species possesses unique characteristics that enable them to thrive in varying climatic conditions along elevational gradients.

Association of Body Roundness Index and A Body Shape Index with Obstructive Sleep Apnea: insights from NHANES 2015-2018 data.

This study examines the relationship between several anthropometric indices-Body Roundness Index (BRI), A Body Shape Index (ABSI), Waist-to-Weight Index (WWI), Waist Circumference (WC), and Body Mass Index (BMI)-and the prevalence of Obstructive Sleep Apnea (OSA) using data from the National Health and Nutrition Examination Survey (NHANES) spanning 2015 to 2018. A retrospective cross-sectional analysis of 7,004 adult participants was conducted using NHANES 2015-2018 data. Multivariable-adjusted logistic regression models were employed to assess the association between BRI, ABSI, and OSA. Non-linear relationships were explored via smooth curve fitting and threshold effect analysis using a two-part linear regression model. Subgroup analyses identified sensitive populations, and the discriminatory power of the indices in screening OSA was assessed using Receiver Operating Characteristic (ROC) curves. The analysis revealed a significant positive association between BRI and OSA, with a threshold effect observed at a BRI of 4.3. Below this threshold, OSA risk increased with higher BRI; however, no significant association was found above this threshold. Similarly, ABSI demonstrated a threshold effect at 8.2, with OSA risk positively associated to the left and negatively associated to the right. Subgroup analyses indicated stronger associations in younger and non-diabetic populations. ROC analysis identified BRI as a promising predictive tool for OSA, with an AUC of 0.64 (95% CI: 0.62-0.65). BRI demonstrates significant potential as a predictive index for OSA incidence, warranting further large-scale prospective studies to validate these findings.