Scanning Area Research Articles

Comparison of Ganglion Cell Layer and Ganglion Cell/Inner Plexiform Layer Measures for Detection of Early Glaucoma

To test the hypothesis that macular ganglion cell layer (GCL) measurements detect early glaucoma with higher accuracy than ganglion cell/inner plexiform layer (GCIPL) thickness measurements. Cross-sectional study. The first cohort included 58 glaucomatous eyes with visual field mean deviation (MD) ≥ -6 dB and 125 normal eyes. The second cohort included 72 glaucomatous and 73 normal/glaucoma suspect (GS) eyes with scans able to create GCL/GCIPL deviation maps. In the first cohort, 8× 8 GCL and GCIPL grids were exported and 5 superior and inferior sectors were defined. Global and sectoral GCL and GCIPL measures were used to predict glaucoma. In the second cohort, proportions of scan areas with abnormal (< 5% and < 1% cutoffs) and supernormal (> 95% and > 99% cutoffs) thicknesses on deviation maps were calculated. The extents of GCL and GCIPL abnormal areas were used to predict glaucoma. Extents of abnormal GCL/GCIPL regions and areas under receiver operating characteristic curves (AUROC) for prediction of glaucoma were compared between GCL or GCIPL measures. The average ± standard deviation MDs were -3.7 ± 1.6 dB and -2.7 ± 1.8 dB in glaucomatous eyes in the first and second cohorts, respectively. Global GCIPL thickness measures (central 18°× 18° macular region) performed better than GCL for early detection of glaucoma (AUROC, 0.928 vs. 0.884, respectively; P=0.004). Superior and inferior sector 3 thickness measures provided the best discrimination with both GCL andGCIPL (inferior GCL AUROC, 0.860 vs. GCIPL AUROC, 0.916 [P= 0.001]; superior GCL AUROC, 0.916 vs. GCIPL AUROC, 0.900 [P= 0.24]). The extents of abnormal GCL regions at a 1% cutoff in the central elliptical area were 17.5± 22.2% and 6.4 ± 10.8% in glaucomatous and normal/GS eyes, respectively, versus 17.0 ± 22.2% and 5.7± 10.5%, respectively, for GCIPL (P= 0.06 for GCL and 0.002 for GCIPL). The extents of GCL and GCIPL supernormal regions were mostly similar in glaucomatous and normal eyes. The best performance for prediction of glaucoma in the second cohort was detected at a P value of < 1% within the entire scan for both GCL and GCIPL (AUC, 0.681 vs. 0.668, respectively; P= 0.29). Macular GCL and GCIPL thicknesses are equivalent for identifying early glaucoma with current OCT technology. This is likely explained by limitations of inner macular layer segmentation and concurrent changes within the inner plexiform layer in early glaucoma.

Development of fast photoacoustic and ultrasound imaging system based on slider-crank scanner for small animals and humans study

Integrated photoacoustic and ultrasound (PAUS) imaging is a potential imaging method that provides simultaneous in vivo functional, and anatomical information. Several PAUS scanner systems have already been reported, but they are limited to fixed scanning range, low scanning speed, bulky size, unsustainable for long-term use. Here, we report a low-cost fast dual photoacoustic and ultrasound imaging system (F-PAUSM) based on custom-made slider-crank and ball-screw mechanisms. This custom-slider-crank mechanism is versatile in terms of changing the scanning range corresponding to a suitable B-scan frame rate for difference scanning areas. F-PAUSM allows us to stably capture wide scanning ranges of 10, 18, and 26 mm corresponding to maximum B-scan frame rates of 30, 26, and 18 Hz, respectively. To demonstrate the capability of the F-PAUSM system, a dragonfly wing, nude mouse ear, and human fingertip are imaged successfully. Furthermore, the numerical analysis is conducted to estimate the fatigue life of the custom-made mechanical parts, then demonstrate that the F-PAUSM system can operate stably for long time in nominal operating conditions. These results demonstrate the potential applications of the F-PAUSM system in biomedical imaging.

Retrogradation in radiation-synthesized cassava starch/acrylic acid super water absorbent and its effect on gel stability

The effects of long-term storage and retrogradation on the stability of the gel properties of radiation-synthesized super water absorbents (SWA) made from cassava starch and acrylic acid were explored in this study. Fourier-transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), differential scanning calorimetry (DSC), and transmission electron microscopy (TEM) analyses were used to explore the retrogradation phenomenon. TEM and scanning area electron diffraction (SAED) images revealed the presence of starch nanocrystallites and increase of crystalline state in SWA matrix after 24 months storage. FT-IR peak ratios and enthalpy changes in DSC analysis also confirmed retrogradation of aged SWA samples. However, no sharp peak was observed in XRD diffractograms which is mainly due to the nanostarches present in the SWA. The most critical property affected by starch retrogradation in SWA is the degree of swelling. The degree of swelling of SWA was greatly reduced from 148 to 30 g/g while the gel fraction remained stable after 24 mos. The aged SWA samples with low degree of swelling due to retrogradation returned to their high and stable soil water content after 15 d in unsterile pure garden soil. Despite being exposed to high energy gamma radiation of starch with acrylic acid to form SWA, wherein possible oxidation and chemical modification of starch may take place, retrogradation can still occur. Lowering the storage temperature evidently suppressed the effect of starch retrogradation in SWA. Suppression of starch retrogradation in the optimized SWA is crucial to prolong its marketable life.

Correlation Analysis between Retention of Gd-DTPA in the Cystic Area of Brain Metastasis and MRI Signs.

Objective The aim of this study is to investigate gadolinium-diethylenetriaminepentacetate (Gd-DTPA) retention in the cystic area of brain metastasis and its correlation with MRI signs. Methods Clinical and MRI data of 76 patients with brain metastasis in the cystic area were collected. The contrast signal intensity (CSI) of the cystic area and edema area in the plain scan, enhanced scan, and plain scan after enhancement within 1 month (hereafter referred to as “enhanced plain scan”) were analyzed to determine whether Gd-DTPA was retained in these areas. The lesions with higher CSI values on the enhanced plain scan were classified as the Gd-DTPA retention group and the remaining lesions as the Gd-DTPA-free group. The two groups were compared to determine significant differences in primary lesion type, tumor size, tumor location, capsule wall thickness and morphology, peritumoral edema, and renal function. Results A total of 123 lesions were detected. The CSI of the enhanced plain scan exceeded that of the plain scan and enhanced scan in the cystic area (P < 0.05). There were 54 lesions (43.9%) with Gd-DTPA retention in the cystic area and 69 lesions (56.1%) without Gd-DTPA retention. Significant differences were observed in tumor size and cystic wall thickness between the two groups (P < 0.05), while no significant differences in primary lesion type, cystic wall shape, peritumoral edema, or function were observed. Conclusion The retention of Gd-DTPA was found in the cystic area of some brain metastases, which was correlated with tumor size and cystic wall thickness.

Abstract 3219: Changes and intra-individual reliability in computed tomography image-assessed adiposity and skeletal muscles areas after breast cancer surgery

Abstract Background: Levels of adiposity and skeletal muscles are prognostic indicators in breast cancer patients; however, data are limited on temporal changes in body composition, particularly in different densities of muscles, before and after mastectomy. Objectives: We examined the change in CT-assessed adipose tissue and different density of skeletal muscle areas using a high-resolution segmentation method in breast cancer patients before and after surgery. Methods: This study included 50 newly-diagnosed breast cancer patients who had taken CT scans before and after surgery. We analyzed their third lumbar (L3) CT images to measure the areas of adipose tissue and five-level (from very-high-density to very-low-density) skeletal muscle components. We assessed mean and percent changes in areas using paired t-test and calculated the intra-class correlation (ICC). Results: Patients’ mean age at diagnosis was 58.3 (SD=12.5) years. The mean duration between scans was 591 (SD=537) days. There was a significant decrease in the areas of subcutaneous adipose tissue (mean change= -36.17 cm2, 11.72% decrease, p=0.029), total adipose tissue (mean change= -45.64 cm2, 10.18% decrease, p=0.032), and very-high-density muscle (mean change= -0.37 cm2, 11.08% decrease, p=0.010). The ratio of total adipose tissue and total skeletal muscle decreased from 3.67 to 3.32 after surgery (mean change= -0.36, 9.81% decrease, p=0.061). There was a strong correlation in adipose tissues and skeletal muscle areas of pre-and post-surgery scans taken within 3 years apart (ICC=0.802 to 0.999, all p&amp;lt;0.05), but the correlations were attenuated in scans taken &amp;gt;3 years apart (ICC = -0.055 to 0.738, all p&amp;gt;0.05). Conclusion: In this sample of breast cancer patients who have undergone surgery, there was a significant decrease in subcutaneous adipose tissues, total adipose tissues, and very-high-density muscle areas over time. Body composition assessed by CT images is reliable for a 3- year period involving breast cancer surgery. These findings serve as a baseline for prospective studies examining the impact of these changes on breast cancer outcomes. Keywords: Adipose tissue, skeletal muscle, computed tomography scans, breast cancer, surgery Citation Format: Livingstone Aduse-Poku, Dheeraj Gopireddy, Mauricio Henandez, Chandana Lall, Joel Divaker, Sara Falzarano, Shahla Masood, Weizhou Zhang, Susmita Datta, Jiang Bian, Ting-Yuan David Cheng. Changes and intra-individual reliability in computed tomography image-assessed adiposity and skeletal muscles areas after breast cancer surgery [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3219.

In Vitro Comparison of Three Intraoral Scanners for Implant-Supported Dental Prostheses.

With continuing technological developments, there have been advances in the field of fixed prosthetics, particularly in impression-taking techniques. These technological advances mean that a wide variety of diagnostic and/or rehabilitation possibilities can be explored without the need for physical models. The aim of this study was to evaluate the accuracy of three intraoral scanners used in oral implant rehabilitation using an extraoral scanner as a reference and varying the scanning area. Three models representing different clinical scenarios were scanned 15 times by each intraoral scanner and three times by the extraoral scanner. The readings were analyzed and overlaid using engineering software (Geomagic® Control X software (Artec Europe, Luxembourg)). Statistically significant differences in accuracy were found between the three intraoral scanners, iTero® (Align Technology Inc., San Jose, CA, USA), Medit® (Medit®: Seoul, Korea), and Planmeca® (Planmeca®: Helsinki, Finland). In all clinical scenarios, the iTero® scanner had the best trueness (24.4 μm), followed by the Medit® (26.4 μm) and Planmeca® (42.1 μm). The Medit® showed the best precision (18.00 μm) followed by the iTero® (19.20 μm) and Planmeca® (34.30 μm). We concluded that the iTero® scanner had the highest reproducibility and accuracy in the clinical setting.

Effects of indium composition on the surface morphological and optical properties of InGaN/GaN heterostructures

PurposeThis study aims to investigate the effects of indium composition on surface morphology and optical properties of indium gallium nitride on gallium nitride (InGaN/GaN) heterostructures.Design/methodology/approachThe InGaN/GaN heterostructures were grown on flat sapphire substrates using a metal-organic chemical vapour deposition reactor with a trimethylindium flow rate of 368 sccm. The indium composition of the InGaN epilayers was controlled by applying different substrate temperatures. The surface morphology and topography were observed using field emission scanning electron microscope (F.E.I. Nova NanoSEM 450) and atomic force microscopy (Bruker Dimension Edge) with a scanning area of 10 µm × 10 µm, respectively. The compositional analysis was done by Energy Dispersive X-Ray Analysis. Finally, the ultraviolet-visible (UV-Vis) spectrophotometer (Agilent Technology Cary Series UV-Vis-near-infrared spectrometer) was measured from 200 nm to 1500 nm to investigate the optical properties of the samples.FindingsThe InGaN/GaN thin films have been successfully grown at three different substrate temperatures. The indium composition reduced as the temperature increased. At 760 C, the highest indium composition was obtained, 21.17%. This result was acquired from the simulation fitting of ω−2θ scan on (0002) plane using LEPTOS software by Bruker D8 Discover. The InGaN/GaN shows significantly different surface morphologies and topographies as the indium composition increases. The thickness of InGaN epilayers of the structure was ∼300 nm estimated from the field emission scanning electron microscopy. The energy bandgap of the InGaN was 2.54 eV – 2.79 eV measured by UV-Vis measurements.Originality/valueIt can be seen from this work that changes in substrate temperature can affect the indium composition. From all the results obtained, this work can be helpful towards efficiency improvement in solar cell applications.

Synthetic silico-metallic mineral particles SSMMP: A new option for CO2 capture and CO2/N2 separation from post-combustion technology

A new class of solid adsorbents based on pristine and ionic liquid (IL) functionalized synthetic silico-metallic mineral particles (SSMMP) for CO2 capture and CO2/N2 separation are presented. Pristine particles were submitted to hydrothermal treatment producing synthetic talc. Samples were characterized by thermal analyses (TGA), specific surface area measurements (BET), infrared spectroscopy (FTIR), Raman spectroscopy, X-ray diffraction(XRD), NMR spectroscopy, and scanning electron microscopy (SEM). Values for specific surface areas varied from 5 m2/g for a sample with high IL content to 354 m2/g for pristine SSMMP. Samples presented distinct morphology as well as sorption capacities. IL and its increased concentration in the samples negatively influenced CO2 sorption capacity but played an essential role in CO2/N2 selectivity. The best results were obtained from CO2 sorption values for SSMMP-M1 without IL of 2.07 mmol CO2/g at 1 bar and 4.93 mmol CO2/g at 30 bar. In addition, a selectivity of 16.94 for the CO2/N2 mixture was achieved for SSMMP-5%-Im(nBu)-I sample. SSMMP particles are easy to obtain with low-cost starting materials used in the low energy and CO2-free emission synthesis process. The sorption/desorption cycles proved the stability for both pristine and IL functionalized samples.

The Effect of Pegcetacoplan Treatment on Photoreceptor Maintenance in Geographic Atrophy Monitored by Artificial Intelligence–Based OCT Analysis

To investigate the therapeutic effect of intravitreal pegcetacoplan on the inhibition of photoreceptor (PR) loss and thinning in geographic atrophy (GA) on conventional spectral-domain OCT (SD-OCT) imaging by deep learning-based automated PR quantification. Post hoc analysis of a prospective, multicenter, randomized, sham (SM)-controlled, masked phase II trial investigating the safety and efficacy of pegcetacoplan for the treatment of GA because of age-related macular degeneration. Study eyes of 246 patients, randomized 1:1:1 to monthly (AM), bimonthly (AEOM), and SM treatment. We performed fully automated, deep learning-based segmentation of retinal pigment epithelium (RPE) loss and PR thickness on SD-OCT volumes acquired at baseline and months 2, 6, and 12. The difference in the change of PR loss area was compared among the treatment arms. Change in PR thickness adjacent to the GA borders and the entire 20° scanning area was compared between treatment arms. Square-root transformed PR loss area in μm or mm, PR thickness in μm, and PR loss/RPE loss ratio. A total of 31 556 B-scans of 644 SD-OCT volumes of 161 study eyes (AM 52, AEOM 54, SM 56) were evaluated from baseline to month 12. Comparison of the mean change in PR loss area revealed statistically significantly less growth in the AM group at months 2, 6, and 12 than in the SM group (-41 μm ± 219 vs. 77 μm ± 126; P= 0.0004; -5 μm ± 221 vs. 156 μm ± 139; P < 0.0001; 106 μm ± 400 vs. 283 μm ± 226; P= 0.0014). Photoreceptor thinning was significantly reduced under AM treatment compared with SM within the GA junctional zone, as well as throughout the 20° area. A trend toward greater inhibition of PR loss than RPE loss was observed under therapy. Distinct and reliable quantification of PR loss using deep learning-based algorithms offers an essential tool to evaluate therapeutic efficacy in slowing disease progression. Photoreceptor loss and thinning are reduced by intravitreal complement C3 inhibition. Automated quantification of PR loss/maintenance based on OCT images is an ideal approach to reliably monitor disease activity and therapeutic efficacy in GA management in clinical routine and regulatory trials.

Potential application of hyperspectral imaging in food grain quality inspection, evaluation and control during bulk storage

The presence of impurities in food grains greatly impact their grades and quality as well as their overall acceptance. Additionally, bulk grains storage is subject to deterioration and losses through factors that could be biological (insects, fungi, mites, mould, rodents) or environmental (temperature, moisture and relative humidity). Several techniques ranging from manual methods (human sensory) to microbiological and chemical tests have been employed in carrying out quality assessments to control deterioration in stored bulk grains. However, it is often challenging, time-consuming and expensive to discriminately identify grain contaminants in store using the traditional methods, especially when they are physically and sometimes visually similar. The hyperspectral imaging, an emerging technique that combines the technology of conventional imaging (computer vision), radiometry and spectroscopy to simultaneously obtain both spatial and spectral information from a sample is potentially a viable approach. Studies on the application of this technology to food grain quality inspection during bulk storage appears to be scanty. Herein a comprehensive review on the applicability of hyperspectral imagining for food grain quality assessment is presented and its potential for application in grain quality inspection, evaluation and control during bulk storage is provided. Specifically, the work presents the basic theory and principles of hyperspectral imaging, and its recent uses in quality and safety inspection of agro-food products. It highlights and discusses the potential and possible approaches in the application of the technology for food grains quality inspection, evaluation and control during bulk storage. Particularly, hyperspectral imaging systems utilizing line or area scanning were considered capable and proposed for application in bulk grain storage quality inspection. Existing literature showed that most studies on the application of hyperspectral imaging for grain quality assessment were majorly focused on wheats. Future research should consider other grains. • Hyperspectral imaging is an emerging method of obtaining spatial and spectral data. • It is potentially a viable approach for food quality investigation. • Its application in grain quality evaluation during bulk storage is discussed. • Line or area scanning is possible approach for achieving the above purpose.

Characteristics, formation mechanism and influence on physical properties of carbonate minerals in shale reservoirs of Wufeng-Longmaxi formations, Sichuan Basin, China

The characteristics, formation mechanisms, and influences on physical properties of carbonate minerals in shale reservoirs of Wufeng-Longmaxi formations in Sichuan Basin are systematically investigated by utilizing electron probe microscope with spectrometer and energy spectrometer, combined with physical properties and whole rock X-diffraction and organic carbon data. The research yielded the findings that follow: First, the main carbonate minerals are calcite, dolomite, and ferriferous dolomite. Calcite is a single mineral that fills the siliceous shell cavity of radiolarians and exists between mineral particles. Ferriferous dolomite always rings dolomite, which is a single mineral that is present among mineral particles and aggregates. Second, calcite is produced by microorganisms that secrete calcium carbonate in the surface of seawater. The siliceous skeleton cavity of radiolarian and seawater both precipitate calcite, which partially dissolves while settling in seawater before depositing on the seabed and being preserved by burial. Thirdly, the dolomite is a diagenetic mineral formed on the water–sediment interface with physiological activities of sulfate bacteria, and the ferriferous dolomite is produced by methanogenic metabolism during the initial burial of muddy sediments. Fourthly, organic carbon, pyrite, quartz, and clay minerals are closely related to reservoir physical properties, while carbonate has no effect on porosity and permeability as a whole. Future research on shale reservoir diagenesis should make use of the in-situ detection and element area scanning, in particular with the spectrogram from electron probe microscope technology, which provides typical petrological evidences for the study of characteristics, formation mechanism, and influence on physical properties of carbonate minerals in shale reservoirs.

Effect of ionic strength on amorphous carbon during chemical mechanical planarization

A hard mask is an essential to prevent pattern collapse resulting from leaning, wiggling, or other defects. It is critical to achieve high removal rates of hard masks. The process of amorphous carbon chemical mechanical planarization (CMP) forms OH radicals on the surface by an oxidation and breaks bonds in the weakest area. Electrolytes with different ionic strengths were added, to facilitate the formation of OH radicals. When electrolytes were added, the removal rates increased by approximately 2.3 times over those without any additives. The increase in surface roughness is another significant factor. The roughness increased in all cases. In particular, a mixed slurry achieved the best results, with a mean surface roughness value of 0.147 nm for a scanning area of 5 × 5 μm2. Thus, the ionic strength of the electrolyte is critical in the CMP of amorphous carbon.

Secretory Vesicle and Glucoamylase Distribution in Aspergillus niger and Macromorphology in Regions of Varying Shear Stress.

In technical fermentations, filamentous microorganisms are exposed to different forms of mechanical stress, among which shear stress is prevalent in turbulent broths. Whereas small-scale bioreactors allow for realistic turbulent flow field conditions, they are not well-suited to investigate the fungal response to shear stress in more detail, as they only reveal the integral effect of a highly dynamic stress stimulus. Therefore, the widely used model system for producing constant, but rather low shear forces, the parallel plate flow chamber, is extended in this work by adding a backward-facing step (BFS). The BFS induces vortex shedding in the wake of the step and brings out distinct areas of different shear stress levels at the bottom of the chamber where mycelia grow. This allows for a stress-dependent analysis of growing cells using a confocal laser-scanning microscope. As the real stress cannot be measured in the experiment, the wall shear stress is estimated numerically using computational fluid dynamics (CFD). As a first application of the experimental setup, the relative biomass concentration, the relative amount of secretory vesicles and the relative amount of the chosen product glucoamylase produced by the filamentous fungus Aspergillus niger were measured. The obtained area scans show homogeneous mycelia growth in areas of low stress and cloud-like patterns downstream of the predicted flow reattachment length where high shear stress dominates. Quantitative analysis of the time course suggests that the amount of available secretory vesicles inside of A. niger decreases when the shear stress is increased, despite that no significant differences in biomass production could be found. In contrast, the highest level of glucoamylase was reached for intermediate volumetric flow rates, i.e., levels of shear stress.

ROAD CONDITION ASSESSMENT FROM AERIAL IMAGERY USING DEEP LEARNING

Abstract. Terrestrial sensors are commonly used to inspect and document the condition of roads at regular intervals and according to defined rules. For example in Germany, extensive data and information is obtained, which is stored in the Federal Road Information System and made available in particular for deriving necessary decisions. Transverse and longitudinal evenness, for example, are recorded by vehicles using laser techniques. To detect damage to the road surface, images are captured and recorded using area or line scan cameras. All these methods provide very accurate information about the condition of the road, but are time-consuming and costly. Aerial imagery (e.g. multi- or hyperspectral, SAR) provide an additional possibility for the acquisition of the specific parameters describing the condition of roads, yet a direct transfer from objects extractable from aerial imagery to the required objects or parameters, which determine the condition of the road is difficult and in some cases impossible. In this work, we investigate the transferability of objects commonly used for the terrestrial-based assessment of road surfaces to an aerial image-based assessment. In addition, we generated a suitable dataset and developed a deep learning based image segmentation method capable of extracting two relevant road condition parameters from high-resolution multispectral aerial imagery, namely cracks and working seams. The obtained results show that our models are able to extraction these thin features from aerial images, indicating the possibility of using more automated approaches for road surface condition assessment in the future.

Comparison of Three Prototypes of PPG Sensors for Continual Real-Time Measurement in Weak Magnetic Field.

This paper is focused on investigation of three developed prototypes of sensors based on the photoplethysmography (PPG) principle for continual measurement of the PPG signal in the magnetic field environment with the inherent radiofrequency and electromagnetic disturbance. The tested prototypes differ in the used optical part of the PPG sensor and their working mode, control unit, power supply, and applied Bluetooth (BT) communication methods. The main aim of the current work was motivated by finding suitable and universal parameter settings for PPG signal real-time recording in different working mode conditions. Comparative measurements in laboratory conditions by certified commercial pulse oximeter and blood pressure monitor (BPM) devices show good stability and proper accuracy of finally determined heart rate values. The supplementary investigation certifies the necessity of the placement of the pressure cuff of the BPM device on the opposite arm than the tested PPG sensor. Measurement experiments inside the scanning area of the running weak field magnetic resonance scanner verify proper function and practical usability of sensed PPG signals for further processing and analysis in all three prototype cases. Additional testing shows that the BT transmission in the scanning area has no visible influence on the quality of the finally obtained scanner images.

Development of Scanning Acoustic Microscopy System for Evaluating the Resistance Spot Welding Quality

ABSTRACT Scanning acoustic microscopy (SAM) system (TSAM-400) was designed and developed for evaluating the quality of resistance spot welding (RSW) joints of 1.5 mm-thick SUS 316 stainless steel sheets under different welding parameters. Indentation and nugget information (diameter and shape) were used for evaluating the RSW quality. SAM A-scan signals were used to calculate the indentation. The nugget diameter was determined in the C-scan image. Internal information (nugget shape, splashes, and defects) was visualized in the B- and C-scan images. In addition, the spot weld area was treated to examine the surface topography effect. The nugget diameters of treated and untreated areas were measured and compared to conclude that the surface topography effect can be neglected in the quality evaluation by SAM system. By implementing TSAM-400, some specimens were successfully tested with a scanning area of 55 × 15 mm2, and a scanning time of 33.5 s corresponding to a B-scan frame rate of 4.5 Hz, and a resolution of 0.1 × 0.1 mm2. Finally, the good input parameters for welding two 1.5 mm-thick SUS 316 were determined by analyzing the results from TSAM-400.

A New Method for Quantifying 3D Skeletal Morphology in Living Subjects Using Low‐Dose Stereo Radiographs

Accurate and repeatable assessments of three‐dimensional (3D) skeletal morphology are critical to interpretations of vertebrate functional anatomy. In skeletal specimens, these goals can be accomplished using in‐silico models derived from 3D laser scan, photogrammetry, or computed tomography (CT) data. Assessments of skeletal morphology in living subjects, especially humans, are more challenging and are often either cost‐prohibitive (e.g., magnetic resonance) or expose subjects to high doses of ionizing radiation (e.g., CT). Here, we present a new, open‐source method for assessing 3D skeletal morphology using ultra‐low dose biplanar radiographs. Biplanar radiographs were obtained using an EOS Imaging System (EOS Imaging, Inc., Paris, France). A custom‐built calibration frame with radiopaque markers was scanned using this system on multiple days in multiple positions inside the scanning space. We quantified the 3D coordinates of markers by placing landmarks at the center of each marker in both anterior‐posterior and lateral radiographs. Landmark data for each scan were collected independently by two observers to determine inter‐observer error. 3D coordinates of landmarks in each scan differed by &lt;1 mm between observers, suggesting strong repeatability in assessing morphology of living subjects. To assess distortion in EOS images, we constructed a second calibration device, a flat plate with radiopaque markers at the corners of three squares with 10 cm, 20 cm, and 30 cm sides, respectively, surrounding an origin point. The calibration plate was scanned with the origin point at the center of the scan area and the sides of the squares parallel to the detectors. We identified distortion at the edges of EOS images which could significantly impact measurements on skeletal features near the margins of the scan area (i.e., hips, pelvis, lower limbs) and developed a method to mathematically correct for resulting distortion in landmark data. Finally, we demonstrate this method using measurements of iliac blade and spinous process orientation in a sample of living human participants. This method will be applicable to studies of multiple human cohorts, including symptomatic and asymptomatic groups, as well as to other biplanar radiograph platforms and study organisms.

Influence of nacelle-lidar scanning patterns on inflow turbulence characterization

Nacelle lidars with different number of beams, scanning configurations and focus distances are simulated for characterizing the inflow turbulence. Lidar measurements are simulated within 100 turbulence wind fields described by the Mann model. The reference wind turbine has a rotor diameter of 52 m. We assume homogeneous frozen turbulence over the lidar scanning area. The lidar-derived Reynolds stresses are computed from a least-square procedure that uses radial velocity variances of each of the beams and compared with those from a simulated sonic anemometer at turbine hub height. Results show that at least six beams, including one beam with a different opening angle, are needed to estimate all Reynolds stresses. Enlarging the beam opening angle improves the accuracy and uncertainty in turbulence estimation more than increasing the number of beams. All simulated lidars can estimate the along-wind variance accurately. This work provides guidance on designing and utilizing nacelle lidars for inflow turbulence characterization.

MMA: The Fight Against Sleep Apnea

IntroductionAffecting approximately one billion people worldwide, obstructive sleep apnea (OSA) occurs when an individual’s airway self‐obstructs during sleep. Persons suffering OSA are generally less healthy and are more likely to develop a myriad of conditions known collectively as Metabolic Syndrome. One OSA solution is maxillomandibular advancement surgery (MMA), involving maxillomandibular complex (MMC) repositioning. While the surgery reports an 87‐100% success rate, the mechanisms of how MMA reduces OSA is not as clear. Further, a proportion of patients are dissatisfied with their appearance after the procedure. This project aims to simulate ventilation in cadavers who have undergone MMA surgery using an incremental MMA approach to measure airway resistances and relate these changes to resulting facial alteration.SurgeryThe MMA procedures were performed by the same dental surgeon. The oral distraction devices (KLS Martin, Florida) were left intact for the entirety of the experiment for manual jaw advancements. For each dependent variable, the MMC was advanced from 0mm to 14mm in 2mm increments.VentilationA patient ventilator (LTV 1000 Pulmonetics, Minnesota) simulated ventilation at each MMA increment. Tidal volumes (TV) were calculated for each cadaver at 6ml/kg of body mass, over the same breathing frequency (12 breaths/minute), resulting in constant air flow rates. At each advancement of the MMC, airway resistance (R) is calculated using breath‐by‐breath analysis of peak inspiratory pressure and plateau pressure at each flow rate. A minimum of 10 breaths were used to calculate R at each MMA increment.Facial ScansAfter every ventilation condition, topographical scans measured 3D changes in the face (Space Spider Scanner, Artec, California). Scan areas of interest extended from hyoid to infraorbital foramen and to the tragi, laterally. The 3D meshes enable calculation of discreet skin surface alterations at each MMA increment and comparisons to baseline topography. Comparing incremental changes to baselines as percentages, a facial alteration index (∆F%) allows comparisons across individuals.DiscussionDetermination of cadaveric breath‐by‐breath airway forces during MMA is novel and ongoing. Preliminary results (n=1, F, 27yrs, 46kg) demonstrate inverse relationships between incremental MMA and R. With each 2mm MMA, R decreased an average of 4.3 cmH2O/L/s (r = ‐0.82). The foundation of the change in R is supported by an average decrease in peak inspiratory pressure of 3.67 cmH2O (r = ‐0.95) and an average decrease in plateau pressure of 2.81 cmH2O (r = ‐0.97) with each 2mm MMA. Use of ∆F% analysis enables demonstration of the relationship between MMA, airway resistance, and resultant facial alteration. The combined approaches are hypothesized to predict relationships between airway resistance and facial alteration at each level of MMA. Determination of this relationship will be a powerful tool, enabling surgeon and patient to be involved in informed decision‐making.

Weedy Rice Classification Using Image Processing and a Machine Learning Approach

Weedy rice infestation has become a major problem in all rice-growing countries, especially in Malaysia. Challenges remain in finding a rapid technique to identify the weedy rice seeds that tend to pose similar taxonomic and physiological features as the cultivated rice seeds. This study presents image processing and machine learning techniques to classify weedy rice seed variants and cultivated rice seeds. A machine vision unit was set up for image acquisition using an area scan camera for the Red, Green and Blue (RGB) and monochrome images of five cultivated rice varieties and a weedy rice seed variant. Sixty-seven features from the RGB and monochrome images of the seed kernels were extracted from three primary parameters, namely morphology, colour and texture, and were used as the input for machine learning. Seven machine learning classifiers were used, and the classification performance was evaluated. Analyses of the best model were based on the overall performance measures, such as the sensitivity, specificity, accuracy and the average correct classification of the classifiers that best described the unbalanced dataset. Results showed that the best optimum model was developed by the RGB image using the logistic regression (LR) model that achieved 85.3% sensitivity, 99.5% specificity, 97.9% accuracy and 92.4% average correct classification utilising all the 67 features. In conclusion, this study has proved that the features extracted from the RGB images have higher sensitivity and accuracy in identifying the weedy rice seeds than the monochrome images by using image processing and a machine learning technique with the selected colour, morphological and textural features.