Wide Space Research Articles

Effects of Different Row Spacing on the Nutritional Value of Quinoa Silage

Climate changes in the world cause an increase in arid areas and saline soils, and at the same time, the increase in extreme climate and soil conditions restricts land use efficiency. In these areas, it becomes difficult to provide silage feed for animals. Therefore, the search for alternative forage plants is also increasing. Quinoa (Chenepodium quinoa Willd.) plant, which is resistant to arid, cold and salty soils, has an important alternative plant potential for silage production in extreme climate and soil conditions. For this purpose, a research was conducted on the silage nutrition values of 2 quinoa varieties (Cherry Vanilla and Read Head) grown at 4 different row spacing distances (17.5, 35.0, 52.5, 70.0 cm). In the research, It is aimed to determine crude ash content (CA), crude protein (CP), acid detergent fiber (ADF), neutral detergent fiber (NDF), dry matter digestibility (DMD), dry matter consumption (DMI) and relative feed value (RFV), which have important nutritional values for animals. As a result of the research, it was determined that sowing seeds at different row spacings had a significant effect on CP, NDF, DMI and RFV of quinoa silage. There was no significant difference in the nutritional values of quinoa silage between varieties (except CP). According to the results of the research, it was determined that sowing with wide row spacing increased the nutritional value of quinoa silage.

Controlling the Selectivity of Electrocatalytic NO Reduction through pH and Potential Regulation on Single-Atom Catalysts.

Electrocatalytic nitrogen oxide reduction (NOxRR) emerges as an effective way to bring the disrupted nitrogen cycle back into balance. However, efficient and selective NOxRR is still challenging partly due to the complex reaction mechanism, which is influenced by experimental conditions such as pH and electrode potential. Here, we have studied the enzyme-inspired iron single-atom catalysts (Fe-N4-C) and identified that the selectivity roots in the first step of the nitric oxide reduction. Combining the constrained molecular dynamics (MD) simulations with the quasi-equilibrium approximation, the effects of electrode potential and pH on the reaction free energy were considered explicitly and predicted quantitatively. Systematic heat maps for selectivity between single-N and N-N-coupled products in a wide pH-potential space are further developed, which have reproduced the experimental observations of NOxRR. The approach presented in this study allows for a realistic simulation of the electrocatalytic interfaces and a quantitative evaluation of interfacial effects. Our results in this study provide valuable and straightforward guidance for selective NOx reduction toward desired products by precisely designing the experimental conditions.

Evaluation of echocardiography and computed tomography characteristics related to aortic valve replacement technique through the right anterior thoracotomy at the 2nd intercostal space

Objective: evaluate echocardiographic and computed tomography characteristics related to minimally invasive aortic valve replacement technique through the right anterior thoracotomy at the 2nd intercostal space. Methods: study on 74 patients undergoing aortic valve replacement surgery through the right anterior thoracotomy at the 2nd intercostal space at Hanoi Heart Hospital and 108 Military Central Hospital, from October 2019 to December 2022. Patients underwent preoperative echocardiography and multiple slices computed tomography to assess the lessons of aortic valve, valve annulus diameter, and intercostal space width. Results: The ratio of aortic valve stenosis is 55.4%, stenosis combined with regurgitation is 31.1%, and aortic regurgitation is 13.5%. The average valve annulus diameter on computed tomography scans is 26.5 ± 3.1 mm (smallest 20; largest 36); average 2nd intercostal space width 18.1 ± 3.1 mm (smallest 11; largest 25). Valve annulus diameter measured by computed tomography correlates closely with actual prosthetic valve size (r = 0.54, p < 0.001); measured by echocardiography had a weak correlation and not statistically significant. The prosthetic valve size to be replaced is smaller than the valve annulus diameter measured on computed tomography, with an average of 4.8 ± 2.7 mm in aortic valve stenosis, 5.7 ± 2.0 mm in combined stenosis and regurgitation, and 7.2 ± 2.9 mm in aortic regurgitation, in which the difference between valve stenosis and regurgitation is statistically significant (p = 0.01). Conclusions: Minimally invasive aortic valve replacement technique through the 2nd intercostal space right thoracotomy, with cutting the 3rd rib, is suitable for Vietnamese anatomy. Valve annulus diameter measured by computed tomography has a good linear correlation and can be a predictor for prosthetic valve size before surgery.

Collagen XIII Is the Key Molecule of Neurovascular Junctions in the Neuroendocrine System

Introduction: Axons of magnocellular neurosecretory cells project from the hypothalamus to the posterior lobe (PL) of the pituitary. In the PL, a wide perivascular space exists between the outer basement membrane (BM), where nerve axons terminate, and the inner BM lining the fenestrated capillaries. Hypothalamic axon terminals and outer BMs in the PL form neurovascular junctions. We previously had found that collagen XIII is strongly localized in the outer BMs. In this study, we investigated the role of collagen XIII in the PL of rat pituitaries. Methods: We first studied the expression of Col13a1, the gene encoding the α1 chains of collagen XIII, in rat pituitaries via quantitative real-time polymerase chain reaction and in situ hybridization. We observed the distribution of COL13A1 in the rat pituitary using immunohistochemistry and immunoelectron microscopy. We examined the expression of Col13a1 and the distribution of COL13A1 during the development of the pituitary. In addition, we examined the effects of water deprivation and arginine vasopressin (AVP) signaling on the expression of Col13a1 in the PL. Results: Col13a1 was expressed in NG2-positive pericytes, and COL13A1 signals were localized in the outer BM of the PL. The expression of Col13a1 was increased by water deprivation and was regulated via the AVP/AVPR1A/Gαq/11 cascade in pericytes of the PL. Conclusion: These results suggest that pericytes surrounding fenestrated capillaries in the PL secrete COL13A1 and are involved in the construction of neurovascular junctions. COL13A1 is localized in the outer BM surrounding capillaries in the PL and may be involved in the connection between capillaries and axon terminals.

A Novel Approach to Raman Distributed Temperature-Sensing System for Short-Range Applications.

A novel approach to the development of Distributed Temperature-Sensing (DTS) systems based on Raman Scattering in Multimode optical fibers operating at around 800 nm is presented, focusing on applications requiring temperature profile measurement in the range of a few hundreds of meters. In contrast to the standard Raman DTS systems, which aim to shorten the pulse space width as much as possible to improve the precision of measurement, the novel approach studied in this work is based on the use of pulses with a space width that is approximately equal to the distance covered by the fiber under test. The proposed technique relies on numerical post-processing to obtain the temperature profile measurement with a precision of about ±3 °C and a spatial resolution of 8 m, due to the transaction phases of the optical pulses. This solution simplifies the electronic circuit development, also minimizing the required laser peak power needed compared to the typical narrow pulse techniques.

Effect of Meniscal Tear Patterns and Preoperative Cartilage Status on Joint Space Width After Medial Opening-Wedge High Tibial Osteotomy

Background: Medial opening-wedge high tibial osteotomy (MOWHTO) is performed to treat young adults with medial compartment knee osteoarthritis associated with varus deformity. However, factors influencing joint space width (JSW) vary according to the type of medial meniscal tear and have not yet been completely elucidated. Purpose: To examine changes in JSW according to the type of medial meniscal tear after MOWHTO and analyze the influencing factors. Study Design: Cohort study; Level of evidence, 3. Methods: This study was conducted on 134 patients who underwent MOWHTO for medial osteoarthritis and were followed up for >2 years. The patients were classified into 3 groups based on medial meniscal status: intact, nonroot tear, and root tear. The authors then measured the JSW preoperatively and at 3 months, 6 months, 1 year, and >2 years postoperatively; analyzed whether the change in JSW varied according to meniscal status; and determined the association of these changes with the preoperative cartilage grade of the medial femoral condyle (MFC) and medial tibial plateau (MTP). International Knee Documentation Committee (IKDC) scores were used to evaluate clinical function. Results: Of the 134 patients, the medial meniscus was intact in 29 patients, a nonroot tear was observed in 58 patients, and a root tear was observed in 47 patients. Postoperatively, JSW increased for all groups, but the timing of the increase varied between the groups (P < .001). JSW increased the most 6 months postoperatively in the intact group and 3 months postoperatively in the nonroot tear and root tear groups (P < .001). Additionally, the increase in JSW was the greatest in the root tear group. Preoperatively, MFC and MTP cartilage status differed among the groups; MTP status did not affect the JSW, but MFC status did (P < .001). The IKDC score increased from the preoperative to postoperative time point in all groups, but there was no significant difference between groups. Conclusion: The authors observed that the amount and timing of increase in JSW were dependent on the pattern of medial meniscal tear observed when MOWHTO was performed. In addition, the cartilage grade of MFC before surgery was associated with changes in JSW. The IKDC score was not significantly different between groups. However, a longer follow-up period is needed to analyze the correlation with the meniscal tear pattern and JSW.

Assessment of Mesiobuccal Canals in Endodontically Treated Teeth in Indore Population by Cone Beam Computed Tomography: A Cross-Sectional Study.

Owing to the complicated anatomical nature of maxillary molars, untreated root canals may directly affect the outcome of root canal therapy. Therefore, cone beam computed tomography (CBCT) scanis an important tool in the evaluation of root canal systems, particularly for the detection of the second mesiobuccal(MB2) canalin maxillary molars. The current study was undertaken to detect and evaluate filled/unfilled MB2 canals in endodontically treated, asymptomatic maxillary molars, and its correlation with periapical pathology by utilizing cone beam computed tomography (CBCT). A retrospective study of 80 CBCTs of patients underwent scanning for various treatment modalities, with asymptomatic endodontically treated permanent maxillary first molars selected. Data collection occurred between January and June 2023. CBCT machine used was KODAK 9000 (Rochester, NY: Carestream Health) (Complementary Metal Oxide Semiconductor {CMOS} sensor, continuous mode and 12-28 sec scan time, 90-500 μm voxel size, and 5x3.5 cm field of view {FOV}). The axial images at mid-root level were used to assess the presence of the MB2 canal. The study included 39 (48.8%) right maxillary first molars and 41 (51.3%) left maxillary first molars. Overall, in 62 (77.5%) maxillary first molars, MB2 was missed by the practicing dentist, and in 13 (16.3%) maxillary first molars MB2 canal was not present. Of all the maxillary first molars with MB2 canal (n=67), 53 (79.1%) canals had a periapical infection, five (7.5%) showed widening of periodontal ligament space whereas nine (13.4%) had no abnormality. MB2 canals were present in the majority of cases and most of the unfilled MB2 canals showed evidence of periapical radiolucencies and showed a direct impact on the prognosis.

A novel hippo swarm optimization: for solving high-dimensional problems and engineering design problems

Abstract In recent years, scholars have developed and enhanced optimization algorithms to tackle high-dimensional optimization and engineering challenges. The primary challenge of high-dimensional optimization lies in striking a balance between exploring a wide search space and focusing on specific regions. Meanwhile, engineering design problems are intricate and come with various constraints. This research introduces a novel approach called Hippo Swarm Optimization (HSO), inspired by the behavior of hippos, designed to address high-dimensional optimization problems and real-world engineering challenges. HSO encompasses four distinct search strategies based on the behavior of hippos in different scenarios: starvation search, alpha search, margination, and competition. To assess the effectiveness of HSO, we conducted experiments using the CEC2017 test set, featuring the highest dimensional problems, CEC2022 and four constrained engineering problems. In parallel, we employed 14 established optimization algorithms as a control group. The experimental outcomes reveal that HSO outperforms the 14 well-known optimization algorithms, achieving first average ranking out of them in CEC2017 and CEC2022. Across the four classical engineering design problems, HSO consistently delivers the best results. These results substantiate HSO as a highly effective optimization algorithm for both high-dimensional optimization and engineering challenges.

An Efficiency Boost for Genetic Algorithms: Initializing the GA with the Iterative Approximate Method for Optimizing the Traveling Salesman Problem—Experimental Insights

The genetic algorithm (GA) is a well-known metaheuristic approach for dealing with complex problems with a wide search space. In genetic algorithms (GAs), the quality of individuals in the initial population is important in determining the final optimal solution. The classic GA using the random population seeding technique is effective and straightforward, but the generated population may contain individuals with low fitness, delaying convergence to the best solution. On the other side, heuristic population seeding strategies provide the advantages of producing individuals with high fitness and encouraging rapid convergence to the optimal solution. Using background information on the problem being solved, researchers have developed several population seeding approaches. In this paper, to enhance the genetic algorithm efficiency, we propose a new method for the initial population seeding based on a greedy approach. The proposed method starts by adding four extreme cities to the route, creating a loop, and then adding each city to the route through a greedy strategy that calculates the cost of adding every city to different locations along the route. This method identifies the best position to place the city as well as the best city to add. Employing local constant permutations improves the resultant route even more. Together with the suggested approach, we examine the GA’s effectiveness while employing conventional population seeding methods like nearest-neighbor, regression-based, and random seeding. Utilizing some of the well-known Traveling Salesman Problem (TSP) examples from the TSPLIB, the standard library for TSPs, tests were conducted. In terms of the error rate, average convergence, and time, the experimental results demonstrate that the GA that employs the suggested population seeding technique performs better than other GAs that use conventional population seeding strategies.

Dual-energy X-ray absorptiometry derived knee shape may provide a useful imaging biomarker for predicting total knee replacement: Findings from a study of 37,843 people in UK Biobank

ObjectiveWe aimed to create an imaging biomarker for knee shape using knee dual-energy x-ray absorptiometry (DXA) scans and investigate its potential association with subsequent total knee replacement (TKR), independently of radiographic features of knee osteoarthritis and established risk factors. MethodsUsing a 129-point statistical shape model, knee shape (expressed as a B-score) and minimum joint space width (mJSW) of the medial joint compartment (binarized as above or below the first quartile) were derived. Osteophytes were manually graded in a subset of images and an overall score was assigned. Cox proportional hazards models were used to examine the associations of B-score, mJSW and osteophyte score with TKR risk, adjusting for age, sex, height and weight. ResultsThe analysis included 37,843 individuals (mean age 63.7 years). In adjusted models, B-score was associated with TKR: each unit increase in B-score, reflecting one standard deviation from the mean healthy shape, corresponded to a hazard ratio (HR) of 2.25 (2.08, 2.43), while a lower mJSW had a HR of 2.28 (1.88, 2.77). Among the 6719 images scored for osteophytes, mJSW was replaced by osteophyte score in the most strongly predictive model for TKR. In ROC analyses, a model combining B-score, osteophyte score, and demographics outperformed a model including demographics alone (AUC ​= ​0.87 vs 0.73). ConclusionsUsing statistical shape modelling, we derived a DXA-based imaging biomarker for knee shape that was associated with kOA progression. When combined with osteophytes and demographic data, this biomarker may help identify individuals at high risk of TKR, facilitating targeted interventions.

The relationship between simulated sub-millimeter and near-infrared images of sagittarius A* from a magnetically arrested black hole accretion flow

Abstract Sagittarius A* (Sgr A*), the supermassive black hole at the center of the Milky Way, undergoes large-amplitude near-infrared (NIR) flares that can coincide with the continuous rotation of the NIR emission region. One promising explanation for this observed NIR behavior is a magnetic flux eruption, which occurs in three-dimensional General Relativistic Magneto-Hydrodynamic (3D GRMHD) simulations of magnetically arrested accretion flows. After running two-temperature 3D GRMHD simulations, where the electron temperature is evolved self-consistently along with the gas temperature, it is possible to calculate ray-traced images of the synchotron emission from thermal electrons in the accretion flow. Changes in the gas dominated (σ = b2/2ρ &amp;lt; 1) regions of the accretion flow during a magnetic flux eruption reproduce the NIR flaring and NIR emission region rotation of Sgr A* with durations consistent with observation. In this paper, we demonstrate that these models also predict that large (1.5x - 2x) size increases of the sub-millimeter (sub-mm) and millimeter (mm) emission region follow most NIR flares by 20 - 50 minutes. These size increases occur across a wide parameter space of black hole spin (a = 0.3, 0.5, −0.5, 0.9375) and initial tilt angle between the accretion flow and black hole spin axes θ0 (θ0 = 0○, 16○, 30○). We also calculate the sub-mm polarization angle rotation and the shift of the sub-mm spectral index from zero to -0.8 during a prominent NIR flare in our high spin (a = 0.9375) simulation. We show that, during a magnetic flux eruption, a large (∼10rg), magnetically dominated (σ &amp;gt; 1), low density, and high temperature “bubble” forms in the accretion flow. The drop in density inside the bubble and additional electron heating in accretion flow between 15 rg- 25 rg leads to a sub-mm size increase in corresponding images.

Improving cellular analysis throughput of lens-free holographic microscopy with circular Hough transform and convolutional neural networks

In recent years, lens-free Digital In-Line Holographic Microscopy (DIHM) has become an essential tool for in-vitro experiments. Specifically, it offers many innovative approaches to the characterization of cancer cell assays, which are pioneering studies in the prevention and treatment of cancer, the most common disease of our time. With DIHM, images with very high resolution, high magnification coefficient, and wide FOV can be obtained. However, the success of the DIHM is directly dependent on the successful coordination of the imaging and analysis processes. This study proposes a combined approach of circular Hough transform (CHT) and Convolutional Neural Network (CNN) algorithms to improve the cellular analysis aspect of DIHM. The design, installation, and testing of the DIHM for cellular imaging are presented. Resolution analyses of the microscopy system are presented using a standard USAF 1951 resolution slide. MCF-7 cell lines were imaged with the designed microscope at various concentrations. CHT was used in the wide search space to detect the particles in the cell slides. The proposed method detected all overlapping cells and non-cell particles in the images. CNN was used to classify particles as living, dead, and noncell cells. A GPU-based GUI has been designed to perform imaging and analysis operations. The performance of the proposed method is statistically compared with a reference system using various performance metrics. The accuracy of the model is calculated as %99.92 and also the results obtained with the proposed method show more than R2=0.99 correlation with a reference system. The results of the proposed method have improved the analytical performance of DIHM in in-vitro cell cancer cell line experiments. In addition, the method contributes to the analysis of high-resolution images.

Ultrastructural Analysis of Large Japanese Field Mouse (Apodemus speciosus) Testes Exposed to Low-Dose-Rate (LDR) Radiation after the Fukushima Nuclear Power Plant Accident.

Since the Fukushima Daiichi Nuclear Power Plant (FDNPP) accident, great attention has been paid to the impact of chronic low-dose-rate (LDR) radiation exposure on biological systems. The reproductive system is sensitive to radiation, with implications connected to infertility. We investigated the testis ultrastructure of the wild large Japanese field mouse (Apodemus speciosus) from three areas contaminated after the FDNPP accident, with different levels of LDR radiation (0.29 µSv/h, 5.11 µSv/h, and 11.80 µSv/h). Results showed good preservation of the seminiferous tubules, comparable to the unexposed animals (controls), except for some ultrastructural modifications. Increases in the numerical density of lipid droplet clusters in spermatogenic cells were found at high levels of LDR radiation, indicating an antioxidant activity rising due to radiation recovery. In all groups, wide intercellular spaces were found between spermatogenic cells, and cytoplasmic vacuolization increased at intermediate and high levels and vacuolated mitochondria at the high-level. However, these findings were also related to the physiological dynamics of spermatogenesis. In conclusion, the testes of A. speciosus exposed to LDR radiation associated with the FDNPP accident showed a normal spermatogenesis, with some ultrastructural changes. These outcomes may add information on the reproductive potential of mammals chronically exposed to LDR radiation.

Membership determination in open clusters using the DBSCAN Clustering Algorithm

In this paper, we apply the machine learning clustering algorithm Density Based Spatial Clustering of Applications with Noise (DBSCAN) to study the membership of stars in twelve open clusters (NGC 2264, NGC 2682, NGC 2244, NGC 3293, NGC 6913, NGC 7142, IC 1805, NGC 6231, NGC 2243, NGC 6451, NGC 6005 and NGC 6583) based on Gaia DR3 Data. This sample of clusters spans a variety of parameters like age, metallicity, distance, extinction and a wide parameter space in proper motions and parallaxes. We obtain reliable cluster members using DBSCAN as faint as G∼20 mag and also in the outer regions of clusters. With our revised membership list, we plot color-magnitude diagrams and we obtain cluster parameters for our sample using ASteCA and compare it with the catalog values. We also validate our membership sample by spectroscopic data from APOGEE and GALAH for the available data. This paper demonstrates the effectiveness of DBSCAN in membership determination of clusters.

Enhanced extreme events in three cascade-coupled semiconductor lasers

Extreme events (EEs) are rare and unpredictable, as have been observed in nature. Up to now, manipulating EEs has remained a challenge. Here, we experimentally observe the enhancement of EEs in a three cascade-coupled semiconductor laser system. Specifically, a continuous-wave optical injection semiconductor laser acts as the chaotic source with rare EEs, which is subsequently injected into a second laser for increasing the number of EEs. Interestingly, we find that the number and region size of EEs can be further enhanced by sequentially injecting into a third laser, i.e., a cascade-injection structure. Our experimental observations are in good agreement with the numerical results, which indicate that EEs can be significantly enhanced in wide injection parameter space due to the cascade-injection effect. Furthermore, our simulations show that the evoluation of the regions with enhanced EEs may be associated with the noise considered.

Dense turbulent suspensions at a liquid interface

The nexus between turbulence, particle interaction and interfacial tension is virtually unexplored, despite being highly relevant to a wealth of industrial and environmental settings. Here we investigate it by conducting experiments on non-Brownian spherical particles at the interface of turbulent liquid layers. The latter are electromagnetically stirred in a quasi-two-dimensional apparatus, while the particles are individually tracked. By systematically varying interfacial conditions, turbulence intensity, particle size and concentration from dilute to dense, we map the system behaviour over a wide parameter space. We reveal how the dynamics is governed by the balance of drag, capillarity and lubrication. Based on their scaling, we propose a phase diagram comprising three distinct regimes, characterized by widely different levels of clustering and fluctuating energy of the particles. This is quantitatively confirmed by the experimental results.

Diurnal Warm Layers in the Ocean: Energetics, Nondimensional Scaling, and Parameterization

Abstract Diurnal warm layers (DWLs) form near the surface of the ocean on days with strong solar radiation, weak to moderate winds, and small surface-wave effects. Here, we use idealized second-moment turbulence modeling, validated with large-eddy simulations (LES), to study the properties, dynamics, and energetics of DWLs across the entire physically relevant parameter space. Both types of models include representations of Langmuir turbulence (LT). We find that LT only slightly modifies DWL thicknesses and other bulk parameters under equilibrium wave conditions, but leads to a strong reduction in surface temperature and velocity with possible implications for air–sea coupling. Comparing tropical and the less frequently studied high-latitude DWLs, we find that LT has a strong impact on the energy budget and that rotation at high latitudes strongly modifies the DWL energetics, suppressing net energy turnover and entrainment. We identify the key nondimensional parameters for DWL evolution and find that the scaling relations of Price et al. provide a reliable representation of the DWL bulk properties across a wide parameter space, including high-latitude DWLs. We present different sets of revised model coefficients that include the deepening of the DWL due to LT and other aspects of our more advanced turbulence model to describe DWL properties at midday and during the DWL temperature peak in the afternoon, which we find to occur around 1500–1630 local time for a broad range of parameters.

High‐Throughput Study of the Phase Constitution of the Thin Film System Mg–Mn–Al–O

The increasing importance of recycling makes the recovery of valuable elements from slags interesting. The concept of engineered artificial minerals aims at the formation of phase(s) with a high content of the to‐be‐recovered element(s) from slags of pyrometallurgical recycling processes. For this, understanding the phase constitution of the slag systems, such as the spinel‐forming subsystem Mg–Mn–Al–O from Li‐ion battery recycling, is of great importance. Herein, the phase constitution is investigated using a thin film materials library (ML) that covers the composition space (Mg14−69Mn11−38Al14−74)Ox. High‐throughput energy‐dispersive X‐ray spectroscopy and X‐ray diffraction confirm the formation of the spinel solid solution phase for a wide composition space. The Mn oxidation state is shown to be a mixture of Mn2+ and Mn3+ by analyzing Mn 2p3/2 spectra from X‐ray photoelectron spectroscopy. For one measurement area of the ML containing equal atomic amounts of Mg, Mn, and Al, transmission electron microscopy shows columnar spinel grains with Mg, Mn, and Al evenly distributed. Based on these results, it is suggested that the high likelihood of spinel formation in slags can be influenced by controlling the Mn oxidation state to allow the formation of desirable engineered artificial minerals for Li recovery.

Effectiveness of Occlusal Splint Therapy in Moderating Temporomandibular Joint Disorders With Joint Displacement: A Retrospective Analysis Using Cone Beam Computed Tomography.

Background Temporomandibular joint disorders (TMD) represent a prevalent group of conditions impacting the temporomandibular joint. Among the therapeutic interventions, occlusal splint therapy has gained recognition for its potential to address TMD symptoms, particularly in cases involving joint displacement. Objective This study aims to investigate the effectiveness of occlusal splint therapy in cases of moderate TMD with joint displacement, focusing on changes in condylar position, joint morphology, and patient-reported outcomes. Methods A retrospective analysis was conducted involving 148 participants who underwent occlusal splint therapy between January 2018 and December 2020. Data were collected through cone beam computed tomography (CBCT) imaging for precise assessments of condylar position and joint morphology. Ethical approval was obtained, and participants provided informed consent. Baseline characteristics, medical history, and TMD severity were recorded. Occlusal splint therapy included individualized fabrication, occlusal analysis, adjustments for optimal fit, and prescribed wear schedules. Follow-up included CBCT scans at specified intervals (three months and six months), with participant-reported outcomes collected. The data analysis was conducted using IBM SPSS Statistics for Windows, Version 22.0 (Released 2013; IBM Corp., Armonk, NY, USA). Paired t-tests or nonparametric equivalents were employed to assess changes in condylar position and joint morphology. Subgroup analyses were conducted to explore potential factors influencing treatment outcomes. The significance level was set at p < 0.05 for all statistical tests. Results The entire cohort (n = 148) had a mean age of 32.5 years (± 8.1), with a balanced gender distribution. Changes in condylar position revealed a statistically significant improvement (p = 0.03), with a mean decrease of 0.2 mm posttreatment. Joint morphology changes indicated increased joint space width (p = 0.01), improved disc position (p = 0.02), and nonsignificant alterations in bony structures (p = 0.10). Patient-reported outcomes demonstrated significant improvements in pain levels, jaw functionality, and satisfaction (all p < 0.001). Age and gender subgroup analyses showed consistent improvements in condylar position, joint morphology, and patient-reported outcomes across different groups. Conclusion Occlusal splint therapy demonstrated effectiveness in improving condylar position, joint morphology, and patient-reported outcomes in cases of moderate TMD with joint displacement. The findings underscore the potential of occlusal splint therapy as a viable intervention for managing TMD, providing valuable insights for clinicians and researchers.

SoybeanTracer: An In-Field scene property-based framework for high-throughput soybean canopy coverage extraction and evaluation

Soybean is a crucial plant-based protein and vegetable oil source for the global population and a significant cereal-oil dual-purpose crop. Extracting soybean canopy coverage, subsequently implementing evaluation in a low-cost, high-throughput and accurate manner, is highly valuable for soybean breeding and yield increase. Although the utilization of RGB remote sensing images for soybean analysis offers distinct advantages in terms of its cost effectiveness, there are still issues to be addressed. Specifically, the in-field scene properties of soybean canopy data have rarely been developed and there is a gap in automatic evaluation of soybean canopy coverage. For purpose of tackling these pending issues, this study proposed SoybeanTracer, a novel framework designed to achieve accurate soybean canopy coverage extraction and enable specialized evaluation with low cost and high throughput. The proposed framework comprised two components: Soybean Canopy Segmentation Network (SCSNet) and an agronomic soybean coverage evaluation system. Specifically, SCSNet employed a feature extraction network integrating the homogeneity within plot regions and soybean distribution characteristics. To further address the segmentation challenge of soybean plants with sparse growth posed by genotypes, a soybean multiscale feature fusion module was designed. As a result, SCSNet achieved a mean intersection over union (mIoU) and mean pixel accuracy (mPA) of 89.39% and 94.42%, respectively, on soybean canopy segmentation. Therefore, accurate and low-cost extraction of soybean canopy coverage was achieved through the use of RGB remote sensing data. Furthermore, the soybean canopy coverage evaluation system proposed in this study encompassed five levels, characterized by wider spacing at the two ends and narrower spacing in the middle. This agronomic evaluation system had been effectively implemented on 196 plots. The variance in the pairwise levels of the coverage evaluation results demonstrated the robustness of the evaluation system. SoybeanTracer could indeed help to extract soybean canopy coverage and provide valuable reference for implementing soybean genotype selection, laying a useful foundation for other crops in similar scientific tasks. The source code and trained models were available at https://github.com/KLoAS-Research/SCSNet-SoybeanTracer.