Row Direction Research Articles

Ascorbic Acid Derivatives in the Sauvignon Blanc Cultivar (Vitis vinifera L.) During Berry Development in the Wellington and Elgin Regions

The exposure of grapevines to unfavourable conditions such as drought, high or low temperature andpathogenic attack increases the production of reactive oxygen species, thus inducing oxidative stress.One of the most important non-enzymatic antioxidants is ascorbic acid, which is used by plants toprotect themselves against these toxic oxygen intermediates. DHA, DKG and threonate are ascorbic acidmetabolites that are found during ascorbic acid catabolism. This study was done in two regions, the onein Wellington, classified as a warmer climate, and the other in Elgin, classified as a cooler climate. Ineach region, two Sauvignon blanc vineyard blocks were selected, with north to south and east to west rowdirections. Vines were monitored during the growing season to investigate the trends in the development ofascorbic acid metabolites in both regions. Canopy management practices were done at different ripeningstages. Grape berries were sampled at different phenological stages according to the Eichhorn Lorenzscale: E-L 32, E-L 34, E-L 35, E-L 37 and E-L 38. Ascorbic acid derivative concentrations in the two regionsvaried significantly in that Elgin showed higher concentrations than Wellington at E-L 32 and E-L 38. Boththe cool and warm regions had high concentrations of threonate, with no significant difference amongstages of ripeness. The DHA, DKG and threonate levels were the highest at the E-L 32 phenological stagefor both regions, with no significant differences among the other phenological stages, especially for DHAderivative concentrations. No significant effect on the DHA, DKG and threonate levels of the grapes wasobserved between row directions in each region.

High-Resolution Phase-Only Holographic 3D Display Based on Light Field Images Rendered in the Frequency Domain

Phase-only holograms are more attractive than the amplitude holograms for the higher energy utilization and the possibility to realize on-axis holographic 3D display without conjugate image. In this study, we propose a high-resolution phase-only holographic 3D display using the light field images rendered in the frequency domain. The high-resolution phase-only hologram contains a large number of elemental phase-only holograms (EPHs), and each EPH is calculated from the light field image of the corresponding viewing point in frequency domain through weighted GS (Gerchberg-Saxton) algorithm. Parallel calculation is performed to speed up the calculation in the row direction and the previous EPH is used as the initial phase for the current EPH calculation in order to improve the display quality due to the great similarity between adjacent light field images. Two high-resolution phase-only holograms both with the size of 64 mm×64 mm and the resolution of 200k×200k pixels were calculated and printed by our homemade holographic printer. The full-parallax and high quality 3D displays were verified by optical experiments, which have the potential to be applied in holographic advertising and other fields.

Pixelated Photoinduced Discharge Readout X-Ray Detector Using 450-nm LED Line Beam

This paper describes a study on a novel X-ray detector with photoinduced discharge (PID) readout devices. Especially, we demonstrated optical scanning X-ray imaging devices based on intrinsic hydrogenated amorphous silicon (i-a-Si:H) PID readout layer, on which a pixelated metal layer, molybdenum, is formed as a charge accumulation layer of 200 μm pitch for clearly defining the pixel in the lateral and longitudinal directions. We decided to use i-a-Si:H as a readout layer instead of amorphous selenium(a-Se) layer because the material of a-Se does not withstand standard wet fabrication processes like lift-off wet process. An X-ray absorption layer of 500 μm thick a-Se is formed by a thermal evaporation process. To optically switch on the i-a-Si:H PID readout layer, we use a narrow line-beam with a beam width of 50 μm consisting of a blue LED array, optical films, and GRIN lens array. The pixelated PID readout X-ray detector is 512×512 image resolutions with a 200 μm pitch, and the overall active dimension is 10.24 cm ×10.24 cm. The sensitivity of the pixelated PID readout X-ray detector is 302 pC/cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ·mR at Normal X-ray Tube conditions (IEC66220-1). According to MTF measurement results, the value of MTF0.1(10%) is measured at near 2.5 1/mm in the column direction scanning while the value is measured at 1.9-2.5 1/mm in the row direction scanning.

Integration of Two-Dimensional Kernel Principal Component Analysis Plus Two-Dimensional Linear Discriminant Analysis with Convolutional Neural Network for Finger Vein Recognition

High complexity and low recognition rate are two common problems with the current finger vein recognition methods. To solve these problems, this paper integrates two-dimensional kernel principal component analysis (K2DPCA) plus two-dimensional linear discriminant analysis (2DLDA) (K2DPCA+2DLDA) into convolutional neural network (CNN) to recognize finger veins. Considering the row and column correlations of the finger vein image matrix and the classes of finger vein images, the authors adopted K2DPCA and 2DLDA separately for dimensionality reduction and extraction of nonlinear features in row and column directions, producing a dimensionally reduced compressed image without row or column correlation. Taking the dimensionally reduced compressed image as the input, the CNN was introduced to learn higher-level features, making finger vein recognition more accurate and robust. The public dataset of Finger Vein USM (FV-USM) Database was adopted for experimental verification. The results show that the proposed approach effectively overcome the common defects of original image feature extraction: the insufficient feature description, and the redundancy of information. When the training reached 120 epochs, the model basically realized stable convergence, with the loss approaching zero and the recognition rate reaching 97.3%. Compared with two-directional two-dimensional Fisher principal component analysis ((2D)2FPCA), our strategy, which integrates K2DPCA+2DLDA with CNN, achieved a very high recognition rate of finger vein images.

A mathematical programming method for constructing the shortest interconnection VLSI arrays

Mesh-connected processor array is an extensively investigated architecture in parallel processing. Massive studies have addressed the problem of using reconfiguration algorithms to solve the fault tolerance of faulty mesh-connected processor arrays. However, the subarrays generated by the previous studies still contain large interconnection length, which will lead to the increase of capacitance, power dissipation and dynamic communication cost. First, a mathematical model is established for the array reconfiguration. Then, the proposed method treats the interconnections between each PEs as a function with different integer variables, which can be solved by using effective integer programming techniques. Finally, an effective solver is called to find the optimal solution. Simulation results show that the proposed method can reduce the interconnection length of the array in the row and column directions simultaneously, thereby generating a subarray with the shortest interconnection length. On a 32 × 32 host array with fault density of 30%, the total interconnection length of the subarray can be reduced by 8.36% compared with state-of-the-art, and the average interconnection length can be reduced by 39.30%, which is more closer to the lower bound.

AlCl3-Dosed Si(100)-2 × 1: Adsorbates, Chlorinated Al Chains, and Incorporated Al

The adsorption of AlCl$_{3}$ on Si(100) and the effect of annealing the AlCl$_{3}$-dosed substrate was studied to reveal key surface processes for the development of atomic-precision acceptor-doping techniques. This investigation was performed via scanning tunneling microscopy (STM), X-ray photoelectron spectroscopy (XPS), and density functional theory (DFT) calculations. At room temperature, AlCl$_{3}$ readily adsorbed to the Si substrate dimers and dissociated to form a variety of species. Annealing of the AlCl$_{3}$-dosed substrate at temperatures below 450 $^{\circ}$C produced unique chlorinated aluminum chains (CACs) elongated along the Si(100) dimer row direction. An atomic model for the chains is proposed with supporting DFT calculations. Al was incorporated into the Si substrate upon annealing at 450 $^{\circ}$C and above, and Cl desorption was observed for temperatures beyond 450 $^{\circ}$C. Al-incorporated samples were encapsulated in Si and characterized by secondary ion mass spectrometry (SIMS) depth profiling to quantify the Al atom concentration, which was found to be in excess of 10$^{20}$ cm$^{-3}$ across a $\sim$2.7 nm thick $\delta$-doped region. The Al concentration achieved here and the processing parameters utilized promote AlCl$_{3}$ as a viable gaseous precursor for novel acceptor-doped Si materials and devices for quantum computing.

Responses of runoff and soil erosion to planting pattern, row direction, and straw mulching on sloped farmland in the corn belt of northeast China

Runoff loss and soil erosion are the main factors threatening grain production in the corn belt of northeast China (CBNC) and are closely related to the planting pattern, row direction, and practice of straw mulching. A 4-year (2017–2020) field experiment was conducted under natural rainfall conditions from 2017 to 2020 to ascertain the effects of the planting pattern, including continuous corn (C), perennial alfalfa (A), and soybean-corn rotation (S-C); row direction including parallel slope (PS) and cross slope (CS); and practice of straw mulching (marked by the subscript SM) on runoff and soil erosion from sloped farmland in the CBNC. Runoff depth and the amount of soil loss under continuous corn with parallel-slope cultivation (PSC) were higher than those of alfalfa with parallel-slope cultivation (PSA) and soybean-corn rotation with parallel-slope cultivation (PSS-PSC) during 2017–2020. Cross-slope planting (CSA, CSC, and CSS-CSC) reduced runoff loss by 7.8–23.3% and the amount of soil erosion by 15.9–73.7% when compared to parallel-slope planting (PSA, PSC, and PSS-PSC). The CSA treatment generated the least runoff depth and soil erosion amount among CSA, CSC, and CSS-CSC. Straw mulching (PSCSM and PSSSM-PSCSM) decreased runoff by 82.6–85.5% and reduced the amount of soil erosion by 87.9–91.5% relative to not using straw mulching treatments (PSC and PSS-PSC). Therefore, cross-slope cultivation and straw mulching can significantly reduce surface runoff and soil erosion on slope farmland. The CSA treatment and the practice of straw mulching were recommended for soil and water conservation in the CBNC.

Design and analysis of various bidirectional 2DPCAs in feature partitioning framework

In this paper, we present various of bidirectional 2DPCAs in feature partitioning framework. To capture hybrid variations of images with optimal feature dimensions, we propose bidirectional sub-image PCA (Bi-SIMPCA), bidirectional flexible PCA (Bi-FLPCA), bidirectional extended SIMPCA (Bi-ESIMPCA) and bidirectional extended FLPCA (Bi-EFLPCA). The Bi-SIMPCA operates on a set of partitioned sub-images of original image and extracts the 2DPCA feature by simultaneously considering the row and column directions of sub-images. Bi-SIMPCA neglects the cross-correlation across sub-images. The Bi-FLPCA further improves the Bi-SIMPCA by removing the redundant features using cross-correlation across sub-images. The Bi-ESIMPCA instead operates on the sub-images of an image and the same whole image simultaneously and extracts the 2DPCA features along row and column directions. Bi-ESIMPCA lacks the global cross-correlation across sub-images and whole images. The Bi-EFLPCA further improves the Bi-ESIMPCA by reducing the redundant features using global correlation across sub-images and whole images. The issues, such as summarization of variance, space and time complexities of the proposed methods are investigated as well. The simulation results using YALE and ORL facial datasets with variable image resolutions show the superior performance of Bi-EFLPCA method with respect to feature dimensionality, memory efficiency, recognition accuracy, and speed over the existing variation of bidirectional 2DPCAs.

Individual tree crown detection from high spatial resolution imagery using a revised local maximum filtering

Accurate tree density and location are important information for optimizing the management and production of forest. Combination of remote sensing techniques and local maximum (LM) filtering algorithm provides a feasible approach to individual tree crown detection, but still faces high error under complicate canopy structure. In this study, a revised LM (RLM) algorithm is presented and evaluated for identifying individual trees from four high spatial-resolution images. Instead of a moving window technique, the RLM algorithm finds crown center seeds by searching local maximal in the transects along row and column directions of the image. Each of final crown centers is then searched using a variable window centered at the crown center seed. Strategies for splitting and merging crowns are implemented in the RLM algorithm to reduce false detection. Result showed that accuracy of the RLM algorithm was more sensitive to its minimum crown length parameter (CLmin). The RLM algorithm driven by the CLmin estimates achieved high overall accuracies between 85% and 91% and low commission (9–14%) and omission errors (8–15%) for the four images. Splitting and merging strategies implemented in the RLM algorithm effectively reduced commission and omission errors. These results indicate that the RLM algorithm is a feasible method with well-defined parameters for automatically detecting individual trees with satisfactory detection accuracy.

Tripartite Graph Regularized Latent Low-Rank Representation for Fashion Compatibility Prediction

In recent years, an increasing online shopping demand has greatly promoted the innovation and development of the fashion industry. Visual fashion analysis has become a prospective research topic in computer vision and multimedia fields. Among these studies, fashion compatibility analysis is required in many real applications, such as fashion recommendation, matching, and retrieval. However, learning fashion compatibility is nontrivial, not only due to the uncertain and sparse dependencies among fashion items but also the latent and mutual associations among multiple factors such as color, texture, style, and functionality. To better predict fashion compatibility, in this paper, we proposed a tripartite graph regularized latent low-rank representation method, named TGRLLR, for fashion compatibility prediction. In TGRLLR, to learn more low-dimensional and effective representations, we considered the latent low-rank representation by decomposing the original feature matrix in both the column and row directions to tackle the problem of insufficient observations. On this basis, we simultaneously exploited different regularization strategies to encode the structured correlations among features, the high-order relationships among items, and the geometrical structures of outfits for more informative representations. Extensive experiments conducted on a real-world dataset demonstrate the effectiveness of our proposed method compared with state-of-the-art methods.

Long-term monitoring of soil bulk density and erosion rates in two Prunus Persica (L) plantations under flood irrigation and glyphosate herbicide treatment in La Ribera district, Spain

Early season fruit production for the northern European market is highly intensive in fertilization, machinery, irrigation and the use of herbicides. Those conditions increase the soil losses and soil compaction and threaten the Sustainable Goals for Development of the United Nations by 2030. Long-term soil erosion measurements are necessary to determine the sustainability of agriculture managements. Moreover, soil erosion on flood irrigation land is a topic that request more surveys and research as rainfed sloping terrains attracted all the attention of scientists and research investment. Improved Stock Unearthing Method (ISUM) was applied to two 15 years-old herbicide treated fields of Saturn peaches (Prunus persica var. platycarpa) to determine long-term soil erosion rates (2004–2019). Using ISUM, a 1 mm thick nylon rope (700 mm length) was used to connect trees perpendicular to the direction of rows at the height of the graft. To detection soil lowering, the vertical distance of the rope to the soil surface was measured at 10 cm intervals along the rope. The ring method (264 samples at 0–6 cm) was used to determine the soil bulk density, which was in average 1.15 gr cm−3 for both plots. There was found a compaction in the centre of both plots due to the pass of machinery with mean bulk density values of 1.23 gr cm−3, meanwhile underneath of the trees, the soil bulk density was 1.05 gr cm−3. The topography survey carried out with ISUM (2508 sampling points) informed that flood irrigation redistributed the soil from the upper to the lower field position, where a sedimentation layer was measured. We found that the two studied fields showed a contrasted response, with low soil erosion values in Benimodo and high in L'Alcúdia study sites. Soil erosion rates were in average 1.46 Mg ha−1 yr−1 and 8.02 Mg ha−1 yr−1 for Benimodo and L'Alcúdia, respectively. However, the maps development using ISUM allow to inform that the pattern of soil redistribution is similar for both fields as the highest soil lowering was found in the upper field part, where the flood discharge detach soil particles. In the lower field position sedimentation takes place. The dataset allows us to conclude that soil erosion in Saturn peaches fields is non-sustainable and more soil conservation management should be applied to reduce the soil erosion rates due to the bare soils as a consequence of the use of herbicides. This research informs that soil erosion in flood irrigated fields is a relevant process that needs more investigations around the world, where 94% of the irrigated land is under flood or furrow irrigation, and where irrigation is growing year after year.

Stainless microfluidic probe with 2D-array microapertures

A microfluidic probe (MFP) does not require physical walls for flow channels, enabling application of a chemical solution in an open space by injecting and aspirating the solution. However, in conventional MFP fabrication methods, the use of a 2D aperture array at narrow intervals to enhance the function of treatment remains limited. In this study, we developed a stainless MFP (stMFP) to produce a 2D aperture array at narrow intervals. The stMFP was developed using a stacking technique in which stainless steel substrates fabricated by photolithography and a wet etching process were stacked and bonded through thermal diffusion. This process resulted in a 6-row and 8-column aperture array with an aperture size of 100 × 150 µm and a narrow interval of 50 µm. The surface treatment area was evaluated by biopatterning of a fluorescent antibody. The results showed that the stMFP biopatterned a minimum treatment area of 3.3 × 103 µm2, which could be controlled between 5.1 × 104 µm2 and 3.0 × 105 µm2 by changing the aperture arrangement. In addition, when two types of fluorescent antibodies were alternately injected in the row direction, six independent treatment areas of 6.1 × 104 µm2 were formed over a wide area of 3.8 × 105 µm2. Furthermore, biopatterning using a 4 × 4 aperture array showed that a 2D treatment area with 4-rows and 2-columns can be produced with an area of 4.5 × 105 µm2. A single stMFP can form various 2D treatment patterns, which is expected to realize high-performance bioprocessing in the field of biology.

Effect of Stitch Orientation on Tensile and Flexural Bending Mechanical Properties and Damage Mechanisms of Glass/Epoxy Composites Laminate

This study aims to investigate the effect of stitch row directions on tensile and flexural bending mechanical properties of composite laminates reinforced by glass-fabric. For the fabrication of stitched laminates, a polyester thread was used to stitch the dry fabric glass in fourth cases (longitudinal stitch 0°, transversal stitch 90°, multi-stitching 0°/90°, and 45°/-45° stitch) with 4 mm stitch spacing. The responses of stitched laminates specimens subject to the tests mentioned were compared to the unstitched laminates and discussed. According to our results, the effect of stitching plays opposite roles on the tensile property by decreasing of about 45% and 36% in tensile strength and longitudinal modulus compared to unstitched specimens, respectively. However, an increasing approximately 11.69% to 20.25% in flexural strength found in samples stitched along 0° and multi-stitching 0°/90°, due to the stitch lines through-thickness by arrests temporally of cracks propagation and the delamination progressively propagate between layers.

Generating row–column field experimental designs with good neighbour balance and even distribution of treatment replications

AbstractBlocking is a standard strategy for improving the precision of randomized experimental designs. In field trials, it is usually beneficial to impose blocks in both row and column directions. A common problem with classical randomized row–column designs is that replications of a treatment may be clustered and that some pairs of treatments appear next to each other rather more often than others. Such patterns adversely affect certain design properties which we refer to as neighbour balance (NB) and evenness of distribution (ED), and they may be particularly harmful if some of the treatments are very susceptible to environmental stresses. Here, we consider an experimental design strategy for blocked experiments that achieves good NB&amp;ED properties. The approach is exemplified using five examples, spanning non‐resolvable and resolvable replicated designs as well as partially replicated designs.

Plant Counting of Cotton from UAS Imagery Using Deep Learning-Based Object Detection Framework

Assessing plant population of cotton is important to make replanting decisions in low plant density areas, prone to yielding penalties. Since the measurement of plant population in the field is labor intensive and subject to error, in this study, a new approach of image-based plant counting is proposed, using unmanned aircraft systems (UAS; DJI Mavic 2 Pro, Shenzhen, China) data. The previously developed image-based techniques required a priori information of geometry or statistical characteristics of plant canopy features, while also limiting the versatility of the methods in variable field conditions. In this regard, a deep learning-based plant counting algorithm was proposed to reduce the number of input variables, and to remove requirements for acquiring geometric or statistical information. The object detection model named You Only Look Once version 3 (YOLOv3) and photogrammetry were utilized to separate, locate, and count cotton plants in the seedling stage. The proposed algorithm was tested with four different UAS datasets, containing variability in plant size, overall illumination, and background brightness. Root mean square error (RMSE) and R2 values of the optimal plant count results ranged from 0.50 to 0.60 plants per linear meter of row (number of plants within 1 m distance along the planting row direction) and 0.96 to 0.97, respectively. The object detection algorithm, trained with variable plant size, ground wetness, and lighting conditions generally resulted in a lower detection error, unless an observable difference of developmental stages of cotton existed. The proposed plant counting algorithm performed well with 0–14 plants per linear meter of row, when cotton plants are generally separable in the seedling stage. This study is expected to provide an automated methodology for in situ evaluation of plant emergence using UAS data.

A Single Slope ADC With Row-Wise Noise Reduction Technique for CMOS Image Sensor

This paper presents a novel technique for single slope analog to digital converter (SSADC) to suppress the rowwise noise in CMOS image sensor. A sample switch is used in the current-steering DAC to reduce the noise introduced by bias circuits, which will deteriorate the characteristic of uniformity in the row direction. The sample switch can fix the voltage which biases the current source in the current-steering DAC when generating a ramp to avoid the ramp fluctuation in the time domain. The digital correlated double sampling is used to reduce the non-uniformity in column-level ADCs. The CMOS image sensor prototype is fabricated in 110nm 1P3M process. The 10-bit SSADC achieves DNL of -0.20 / +0.15 LSB and INL of -1.35 / +0.91 LSB at a sampling frequency of 29.2 KHz. It is proved that the row-wise noise is reduced from 764μVrmsto 163μVrmsat a frame rate of 228 fps using the proposed sample switch structure. The prototype photos taken by the sensor show that the row-wise noise is reduced under the low-illumination circumstance effectively.

Husk Leaf Senescence Characteristics of Spring Maize (Zea mays L.) Cultivated in Two Row Directions and Three Plant Spacings in Northeast China

Row direction and plant spacing influence crop senescence. An experiment was conducted to analyze the effect of row direction and plant spacing on the husk leaf senescence. Physiological indicators related to husk leaf senescence at days after silking (DAS) 12, 22, and 40 were investigated under two row directions (east to west and south to north, abbreviated as EW and SN, respectively) and three plant patterns (single rows spaced at 65 cm, 40 cm twin rows spaced at 90 cm between the paired rows of narrow–wide rows, and 40 cm twin rows spaced at 160 cm between the paired rows of narrow–wide rows, abbreviated as SR, WN1, and WN2, respectively). Row direction affects the chlorophyll content and dehydration rate according to our results. Superoxide dismutase activity at DAS 22, catalase (CAT) activity at DS, and abscisic acid (ABA) concentrations at DAS 12, 22, and 40 were significantly affected by plant spacing. The CAT activities of WN1 and WN2 were significantly higher than those of SR, and WN2 had a lower ABA concentration than WN1 and SR. Our results suggest that row direction from SN and plant spacing from WN1 and WN2 were the suitable conditions for delaying the senescence of husk leaves of maize in the experimental site.

Validation of synthesized normal-resolution image data generated from high-resolution acquisitions on a commercial CT scanner.

To validate a normal-resolution (NR) simulation (NRsim) algorithm that uses high-resolution (HR) or super-high resolution (SHR) acquisitions on a commercial HR computed tomography (CT) scanner by comparing image quality between NRsim-generated images and actual NR images. NRsim is intended to allow direct comparison between normal-resolution CT and HR/SHR reconstructions in clinical investigations, without repeating exams. The Aquilion Precision CT (Canon Medical Systems Corporation) HR CT scanner has three resolution modes resulting from detector binning in the channel (x-y) and row (z) directions. For NR, each detector element is 0.5mm×0.5mm along the channel and row directions, 0.25mm×0.5mm for HR, and 0.25mm×0.25mm for SHR. The NRsim algorithm simulates NR acquisitions from HR or SHR acquisitions (termed NRHR and NRSHR , respectively) by downsampling the pre-log raw data in the channel direction for the HR acquisitions and in the channel and row direction for the SHR acquisition. The downsampled data are then reconstructed using the same process as NR. The axial modulation transfer function (MTF), slice sensitivity profile (SSP), and CT number accuracy were measured using the Catphan 600 phantom, and the three-dimensional noise power spectrum (NPS) was measured in water-equivalent phantoms for standard protocols across a range of size-specific dose estimates (SSDE): head (6.2-29.8mGy), lung (2.2-18.2mGy), and body (5.6-19.4mGy). The MTF and NPS measurements were combined to estimate low-contrast detectability (LCD) using a non-prewhitening model observer with an eye filter for a 5-mm disk with 10HU contrast. All metrics were compared for NR, NRHR , and NRSHR images reconstructed using filtered back projection (FBP) and an iterative reconstruction algorithm (AIDR3D). We chose a 15% error threshold as a reasonable definition of success for NRsim when compared against actual NR based on published studies showing that a just-noticeable difference in image noise level for human observers is typically <15%. The axial MTF and SSPs for NRsim were in good agreement with NR demonstrated by a maximum difference of 5.1% for the MTF at 10% and 50% across materials (air, Teflon, LDPE, and polystyrene) and a maximum SSP difference of 2.2%. Noise magnitude differences were within 15% across the SSDE levels with the exception of below 4.5mGy for the lung protocol with FBP. The relative RMSE of normalized NPS comparisons were all <15%. Differences in CT numbers for NRsim reconstructions were within 2HU of NR. LCD for NRsim was within 15% of NR with the exception of NRSHR for the lung protocol SSDE levels below 3.7mGy with FBP. NRsim, an algorithm for simulating NR acquisitions using HR and SHR raw data, was introduced and shown to generate images with spatial resolution, noise, HU accuracy, and LCD largely equivalent to scans acquired using an actual NR acquisition. At SSDE levels below ~5mGy for the lung protocol, differences in noise magnitude and LCD for NRSHR were >15% which defines a region where NRsim degrades due to contributions from electronic noise.

Receive/Transmit Aperture Selection for 3D Ultrasound Imaging with a 2D Matrix Transducer

Recently, we realized a prototype matrix transducer consisting of 48 rows of 80 elements on top of a tiled set of Application Specific Integrated Circuits (ASICs) implementing a row-level control connecting one transmit/receive channel to an arbitrary subset of elements per row. A fully sampled array data acquisition is implemented by a column-by-column (CBC) imaging scheme (80 transmit-receive shots) which achieves 250 volumes/second (V/s) at a pulse repetition frequency of 20 kHz. However, for several clinical applications such as carotid pulse wave imaging (CPWI), a volume rate of 1000 per second is needed. This allows only 20 transmit-receive shots per 3D image. In this study, we propose a shifting aperture scheme and investigate the effects of receive/transmit aperture size and aperture shifting step in the elevation direction. The row-level circuit is used to interconnect elements of a receive aperture in the elevation (row) direction. An angular weighting method is used to suppress the grating lobes caused by the enlargement of the effective elevation pitch of the array, as a result of element interconnection in the elevation direction. The effective aperture size, level of grating lobes, and resolution/sidelobes are used to select suitable reception/transmission parameters. Based on our assessment, the proposed imaging sequence is a full transmission (all 80 elements excited at the same time), a receive aperture size of 5 and an aperture shifting step of 3. Numerical results obtained at depths of 10, 15, and 20 mm show that, compared to the fully sampled array, the 1000 V/s is achieved at the expense of, on average, about two times wider point spread function and 4 dB higher clutter level. The resulting grating lobes were at −27 dB. The proposed imaging sequence can be used for carotid pulse wave imaging to generate an informative 3D arterial stiffness map, for cardiovascular disease assessment.

Influence of ridges for planting sweet potato on symbiotic ecological factors, photosynthetic abilities and population yield in relay intercropping system

Sweet potato (Ipomoea batatas L.) relay intercropping with maize exposes sweet potato to weak levels of sunlight due to the shadow maize creates during the symbiotic period. The insufficient light accordingly causes slow growth and development of vines and leaves of sweet potato in its early stage. The planting density and row direction of maize, the width of the intercropping strip, and the lodging type of sweet potato may form various photo conditions that influence sweet potato. The objective of this experiment was to research the effects of different ridging types on sweet potato and to elucidate the mechanisms of ecological conditions, photosynthetic physiology and intercropping benefits. The results indicated that, contrast to the one wide-ridge with planting two rows of sweet potato and two narrow ridges with planting two rows, mound planting was more superior in many aspects. Through mound planting sweet potato showed a larger range of temperature in air and soil, higher net photosynthetic rate, more active enzymes related with photosynthesis, and more benefits of relay intercropping.