Rectangular Region Research Articles

Basic Survey Scheduling for the Wide Field Survey Telescope (WFST)

Aiming at improving the survey efficiency of the Wide Field Survey Telescope, we have developed a basic scheduling strategy that takes into account the telescope characteristics, observing conditions, and weather conditions at the Lenghu site. The sky area is divided into rectangular regions, referred to as “tiles,” with a size of 2.°577 × 2.°634 slightly smaller than the focal area of the mosaic CCDs. These tiles are continuously filled in annulars parallel to the equator. The brightness of the sky background, which varies with the moon phase and distance from the moon, plays a significant role in determining the accessible survey fields. Approximately 50 connected tiles are grouped into one block for observation. To optimize the survey schedule, we perform simulations by taking into account the length of exposures, data readout, telescope slewing, and all relevant observing conditions. We utilize the Greedy Algorithm for scheduling optimization. Additionally, we propose a dedicated dithering pattern to cover the gaps between CCDs and the four corners of the mosaic CCD array, which are located outside of the 3° field of view. This dithering pattern helps to achieve relatively uniform exposure maps for the final survey outputs.

Load-Balancing Routing for LEO Satellite Network with Distributed Hops-Based Back-Pressure Strategy.

With the expansion of user scale in LEO satellite networks, unbalanced regional load and bursty network traffic lead to the problem of load disequilibrium. A distributed hops-based back-pressure (DHBP) routing is proposed. DHBP theoretically derives a fast solution for the minimum end-to-end propagation hops between satellite nodes in inclined-orbit LEO satellite networks; hence, link weights are determined based on remaining hops between the next hop and destination satellites. In order to control the number of available retransmission paths, the permitted propagation region is restricted to a rectangular region consisting of source-destination nodes to reduce the propagation cost. Finally, DHBP is designed distributedly, to realize a dynamic selection of the shortest link with low congestion and balanced traffic distribution without obtaining the whole network topology. Network simulation results demonstrate that DHBP has higher throughput and lower delay under high load conditions compared with state-of-the-art routing protocols.

Influence of oblique proximal ulnar osteotomy on humeral intracondylar fissures in 35 spaniel breed dogs.

To investigate the effects of oblique proximal ulnar osteotomy (PUO) on the healing of humeral intracondylar fissure (HIF) in spaniel breed dogs. Clinical retrospective study. A total of 51 elbows from 35 spaniel dogs. An oblique PUO was performed in dogs diagnosed with HIF. The degree of healing of HIF was subjectively and objectively assessed on preoperative and long-term follow-up CT imaging. Objective assessment was performed by measuring the bone density in Hounsfield units (HU) of a rectangular region of interest (ROI) encompassing the entire hypoattenuated humeral fissure. Major and minor complications were recorded. A total of 24 partial and 27 complete HIFs were diagnosed. The follow-up CT scan was performed at a median 18.5 months (range 10-49 months). Subjective assessment confirmed partial or complete healing of the HIF in 41 elbows (80.3%). Objective assessment confirmed a difference in mean HU of the HIF's ROI between preoperative (HU 640) and last follow-up CT images (HU 835) (p = .001). Young dogs (<14 months) had the highest increase in HU of the HIF's ROI. Major complications occurred in five dogs (6 limbs) of which four were related to the lack of healing of the fissure (7.8%). Oblique PUO resulted in partial or complete healing of HIF and pain resolution in the majority of dogs. This study introduces an innovative approach to achieve healing of the HIF in the dog, which may help reduce the high complication rate traditionally associated with the use of transcondylar screws.

Numerical research on liquid water removal mechanism and the influence of pore structure on water removal rate based on real pore GDL structure during shutdown purge of fuel cell

This paper establishes a two-phase flow model of the real pore structure to explore the liquid water removal process during the shutdown purge. The Monte Carlo algorithm is used to randomly throw circles in the rectangular region to simulate the two-dimensional interface of the real GDL pore structures. The real pore structure with different porosity is established by change the number of random circles to explore the influence of porosity on the liquid water removal process. A solid mechanical model is established to explore the variation of GDL under the effect of assembly force. The equivalent model of the compressed real pore GDL is established to explore the effect of the assembly force on the removal of liquid water during the shutdown purge stage. The results show that the liquid water under the ribs is difficult to remove during the removal of liquid water, affecting the speed of liquid water removal. The reduction of GDL porosity is conducive to the diffusion of air and the displacement of liquid water, thus improving the removal speed of liquid water. The assembly force can reduce the porosity below the rib, and effectively promote the removal speed of liquid water below the rib.

Analysis of the Efficacy of Elastography in Comparison with Dynamic Renal Nuclear Scintigraphy in the Evaluation of Unilateral Pelvi–Ureteric Junction Obstruction

IntroductionIn hydronephrosis due to pelviureteric junction obstruction (PUJO), an obstruction to urine flow may lead to increased pelvic pressure, which may cause interstitial fibrosis and renal impairment. Recently, there have been reports on renal pelvic assessment using ultrasound elastography (USE). This study was conducted to see if USE can evaluate PUJO and if it can be correlated to the findings of the dynamic renal nuclear scan. Material and methodsIn this observational study, only patients with unilateral PUJO underwent acoustic radiation force impulse (ARFI) elastography. A rectangular region of interest (ROI) measuring 5 × 10 mm was positioned on the cortex region of the upper, mid, and lower poles of the affected kidney. Three valid measurements were obtained, from which a mean value was calculated. A dynamic renal nuclear scan using Technetium-99m ethylene dicysteine (EC or TC99 m EC) was obtained and split renal function (SRF) was used for comparison. ResultsIn the group of 20 patients, the mean age was 3.37 years. The mean SRF of the affected kidney was 26.65 %, and the corresponding USE value was 0.45 kpa. The Spearman's rho correlation coefficient for SRF and USE was 1 and 0.672, respectively (p = 0.001). Elastography was not feasible if SRF was less than 20 %. ConclusionUSE may be able to comment on the renal functional status of hydronephrosis. If USE is reported as non-feasible, it may suggest that renal function is grossly compromised. It may serve as an alternative diagnostic modality for renal functional evaluation. Level of evidenceLevel II, Prospective Cohort Study.

Two‐Dimensional Analytical Solution for Transient Flow in Unsaturated Soils Considering Hydromechanical Coupling

AbstractThis paper presents a two‐dimensional solution for unsaturated transient seepage flow in a trapezoidal region using analytical solutions for flow in a series of rectangular regions. The coupled formulation considers the interaction among fluid flow due to differences in head and displacement of soil particles. The solution in each rectangular region is derived using Laplace Transform and Discrete Fourier Series for two top boundary conditions: specified pressure head and specified flow rate. The accuracy of the proposed solution is verified by comparing the results against those attained from the finite difference method. The proposed solution is applied to two example problems, demonstrating its efficacy and accuracy. The findings show a significant difference in the coupled and uncoupled results for fine‐grained soils possessing a small Gardner's coefficient. Additionally, the uncoupled pressure heads advanced quicker to a steady state than the coupled ones for soils with a small Gardner's coefficient. The coupling effect becomes less prominent as Gardner's coefficient increases. This study is the first attempt in the literature to provide a solution for unsaturated flow in a trapezoidal or non‐rectangular domain using analytical solution techniques, which can better represent complex real‐world applications (e.g., slopes, embankments, dams).

Interobserver variability in the determination of bone mineral density in Hounsfield units from differently configured fields of measurement in the cancellous bone of vertebral bodies from elderly body donors

BackgroundDue to the absence of suitable diagnostic procedures, osteoporosis (OP) is frequently detected late or not at all. Many elderly persons undergo computed tomographies (CT). The routine determination of Hounsfield units (HU) in bone as a part of these examinations could close a gap here. MethodsSpines were extracted from 22 body donors, fixed in a PVC water phantom, and subjected to a high-resolution CT investigation. Cancellous bone was examined and its bone mineral density measured in HU from cervical vertebra 3 to lumbar vertebra 5 (484 vertebral bodies). On sagittal sections, a circular and a rectangular region of interest (ROI) were defined in mid-vertebral cancellous bone, positioned manually, and the measurements were performed by three experienced radiologists. Bone mineral density (BMD), measured in mg/cm3, was used to determine the presence of OP. ResultsAll of the spines were osteoporotic. In the presence of a BMD below 60 mg/cm3 and HU values below 63.36 in lumbar vertebrae, there were significantly more vertebral body fractures in the thoracic and thoracolumbar spine. No difference was observed between the manually positioned circular and rectangular regions of interest (ROI) on the sagittal CT section (p > 0.05). Similar HU counts were obtained by the individual examiners (p > 0.05). The following formula was used to determine QCT values on a non-contrasted CT of the spine: QCT = 0.6 × HU + 13.7. ConclusionsMeasurement of the density of cancellous bone in HU can be used to determine BMD for estimating demineralization. Quantitative BMD values in mg/cm3, which can be calculated from the HU data, concur well with QCT values.

Optimizing two‐variable gamma accelerated degradation tests with a semi‐analytical approach

AbstractIn this paper, we provide a semi‐analytical approach to determine the optimal designs for two‐variable gamma accelerated degradation tests under three criteria: ‐optimality, ‐optimality, and ‐optimality. We first use general equivalence theorem to prove that the optimal approximate designs only allocate test units at the four vertices of a rectangular design region, and the corresponding optimal proportion of total number of measurements at each stress level is derived. Next, we apply the concept of prescribed accuracy level and total experimental cost to further determine optimal integer designs. More specifically, a numerical approach is used to resolve the number of test units and number of measurements at each stress level. Finally, an example is presented to illustrate the proposed procedure and compare the efficiency of optimal designs under three optimal criteria.

Knee synovial fluid flow and heat transfer, a power law model

For the purpose of understanding, the governing system of partial differential equations for synovial fluid flow velocity and temperature distribution in the knee joint has been successfully solved for the first time. Therefore, such an article is shedding light on the convective diffusion of the viscous flow along the articular surfaces of the joints through the introduction of power-law fluids with different features of permeability, and stagnation point flow along a magnetic field. Henceforth, the frictional energy causes the knee joint’s temperature to increase. By way of filtration, heated synovial fluid reaches the articular cartilage and provides heat to the bone and cartilage. The lubricant in the joint cavity is properly mixed with this cooled fluid. A rectangular region flow and diffusion model is used to define the issue, thermal diffusion and flow inside the intra-articular gap, as well as flow and thermal diffusion within the porous matrix covering the approaching bones at the joint. Using the similarity solution approach, the linked mixed boundary value problem is addressed. The fluid has been shown to resist moving into or out of the cartilage in certain sick and/or aging synovial joints, causing the temperature to increase. By changing the values of the parameters from their usual levels, it is observed that the temperature did increase in aged and sick joints which impact cartilage and/or synovial fluid degradation.

Regression-based rectangular multivariate normal prediction regions for setting reference regions

Reference intervals are among the most widely used decision-making tools in the medical field, and are invaluable in the interpretation of laboratory test results. Moreover, when several biochemical analytes are needed to diagnose the same condition, a multivariate reference region is necessary to take the correlations among the analytes into account. Traditionally, multivariate reference regions have been constructed as ellipsoidal in shape. Since such regions are difficult to interpret and cannot detect the outlyingness of a specific analyte, many authors prefer rectangular regions. Reference intervals and regions may also depend on covariates such as age and sex. The covariate values are often random quantities since they are typically not controlled in reference interval determination studies. In this study, we propose procedures to construct rectangular multivariate reference regions that incorporate random covariate information. The reference regions are computed in a multivariate normal setting, using a prediction region criterion. A parametric bootstrap approach is employed to compute the prediction factor. Numerical results show that the parametric bootstrap approach is quite accurate, with coverage probabilities close to the desired nominal value. Finally, we apply the proposed methods to real-life data from a study to compute covariate-dependent reference regions for insulin-like growth factors.

Tracking by segmentation with future motion estimation applied to person-following robots.

Person-following is a crucial capability for service robots, and the employment of vision technology is a leading trend in building environmental understanding. While most existing methodologies rely on a tracking-by-detection strategy, which necessitates extensive datasets for training and yet remains susceptible to environmental noise, we propose a novel approach: real-time tracking-by-segmentation with a future motion estimation framework. This framework facilitates pixel-level tracking of a target individual and predicts their future motion. Our strategy leverages a single-shot segmentation tracking neural network for precise foreground segmentation to track the target, overcoming the limitations of using a rectangular region of interest (ROI). Here we clarify that, while the ROI provides a broad context, the segmentation within this bounding box offers a detailed and more accurate position of the human subject. To further improve our approach, a classification-lock pre-trained layer is utilized to form a constraint that curbs feature outliers originating from the person being tracked. A discriminative correlation filter estimates the potential target region in the scene to prevent foreground misrecognition, while a motion estimation neural network anticipates the target's future motion for use in the control module. We validated our proposed methodology using the VOT, LaSot, YouTube-VOS, and Davis tracking datasets, demonstrating its effectiveness. Notably, our framework supports long-term person-following tasks in indoor environments, showing promise for practical implementation in service robots.

Utility of machine learning for identifying stapes fixation on ultra-high-resolution CT.

Imaging diagnosis of stapes fixation (SF) is challenging owing to a lack of definite evidence. We developed a comprehensive machine learning (ML) model to identify SF on ultra-high-resolution CT. We retrospectively enrolled 109 participants (143 ears) and divided them into the training set (115 ears) and test set (28 ears). Stapes mobility (SF or non-SF) was determined by surgical inspection. In the ML analysis, rectangular regions of interest were placed on consecutive axial slices in the training set. Radiomic features were extracted and fed into the training session. The test set was analyzed using 7 ML models (support vector machine, k nearest neighbor, decision tree, random forest, extra trees, eXtreme Gradient Boosting, and Light Gradient Boosting Machine) and by 2 dedicated neuroradiologists. Diagnostic performance (sensitivity, specificity and accuracy, with surgical findings as the reference) was compared between the radiologists and the optimal ML model by using the McNemar test. The mean age of the participants was 42.3 ± 17.5years. The Light Gradient Boosting Machine (LightGBM) model showed the highest sensitivity (0.83), specificity (0.81), accuracy (0.82) and area under the curve (0.88) for detecting SF among the 7 ML models. The neuroradiologists achieved good sensitivities (0.75 and 0.67), moderate-to-good specificities (0.63 and 0.56) and good accuracies (0.68 and 0.61). This model showed no statistical differences with the neuroradiologists (P values 0.289-1.000). Compared to the neuroradiologists, the LightGBM model achieved competitive diagnostic performance in identifying SF, and has the potential to be a supportive tool in clinical practice.

Rectangular and radial region of interests on the edge of cylindrical phantom for spatial resolution measurement

&lt;span lang="EN-US"&gt;The purpose of this study was to evaluate the effect of rectangular region of interest (ROI) size on modulation transfer function (MTF), to develop the radial ROI, and to compare both ROIs performances for MTF measurement using a cylindrical polymethyl methacrylate (PMMA) phantom. The PMMA phantom used in this study was rotated 45°. Four rectangular ROIs and a radial ROI were created to measure the MTF value. The rectangular ROI sizes were 3×41, 21×41, 41×41, and 61×41 pixels; each was placed at upper phantom edge. The radial ROI’s length was 41 pixels and placed at several points in phantom edge. The MTF calculation was automatically conducted using MATLAB. The MTFs from rectangular ROIs and radial ROI were then compared. The comparison of the MTF measurement was also conducted using three different filters. The MTF which used radial ROI was smoother than those of rectangular ROI for all filters. This indicated that radial ROI was more resistant to noise than rectangular ROI. Rectangular ROI with the 41×41 pixels had similar 50% and 10% MTF values with the radial ROI. The MTF value which was obtained using radial ROI is more accurate and robust than those obtained using rectangular ROI.&lt;/span&gt;

An Analytic Solution for 2D Heat Conduction Problems with Space–Time-Dependent Dirichlet Boundary Conditions and Heat Sources

This study proposes a closed-form solution for the two-dimensional (2D) transient heat conduction in a rectangular cross-section of an infinite bar with space–time-dependent Dirichlet boundary conditions and heat sources. The main purpose of this study is to eliminate the limitations of the previous study and add heat sources to the heat conduction system. The restriction of the previous study is that the values of the boundary conditions and initial conditions at the four corners of the rectangular region should be zero. First, the boundary value problem of 2D heat conduction system is transformed into a dimensionless form. Second, the dimensionless temperature function is transformed so that the temperatures at the four endpoints of the boundary of the rectangular region become zero. Dividing the system into two one-dimensional (1D) subsystems and solving them by combining the proposed shifting function method with the eigenfunction expansion theorem, the complete solution in series form is obtained through the superposition of the subsystem solutions. Three examples are studied to illustrate the efficiency and reliability of the method. For convenience, the space–time-dependent functions used in the examples are considered separable in the space–time domain. The linear, parabolic, and sine functions are chosen as the space-dependent functions, and the sine, cosine, and exponential functions are chosen as the time-dependent functions. The solutions in the literature are used to verify the correctness of the solutions derived using the proposed method, and the results are completely consistent. The parameter influence of the time-dependent function of the boundary conditions and heat sources on the temperature variation is also investigated. The time-dependent function includes exponential type and harmonic type. For the exponential time-dependent function, a smaller decay constant of the time-dependent function leads to a greater temperature drop. For the harmonic time-dependent function, a higher frequency of the time-dependent function leads to a more frequent fluctuation of the temperature change.

Numerical Study on the Optimal Thermally Affected Region of a Buried Oil Pipeline.

Crude oil pipeline transportation is usually a closed process under a certain depth of burial, and the condition of oil in the pipeline changes with the continuous decline of temperature during the transportation process. The safety and energy consumption of pipeline transportation are closely related to the accurate prediction of oil temperature. It is a popular technique to use the thermally affected region to overcome the problem of an unclosed calculation domain caused by the semi-infinite soil around the pipeline. However, there is no clear and unified guidance on the thermally affected region at present, and improper region size may lead to a loss of the accuracy of the pipeline system. Therefore, our study answers two questions about the optimal form of the thermally affected region and its economic scope of application. The coupled solution of heat transfer and flow in a tridimensional numerical model is carried out, and the thermodynamic influences of the geometric shape and range of the thermally affected region on the buried pipeline system are investigated. The results show that the rectangular region is more suitable for the modeling of buried oil pipelines, and a region with 16 m width and 9 m height is recommended for the conventional case.

A Constraint Programming Solution to the Guillotine Rectangular Cutting Problem

The guillotine rectangular cutting problem deals with a single rectangular plate of raw material and a collection of rectangular items to be cut from the plate. Each item is associated with a profit and a demand. The problem searches for a feasible layout of a subset of items on the plate so as to maximize the total profit of selected items. The guillotine constraint restricts feasible layouts to those that can be obtained via guillotine edge-to-edge cuts that run parallel to an edge of the plate. We propose a novel constraint programming model that is suitable for guillotine cutting with an arbitrary number of stages of alternating horizontal and vertical guillotine cuts. This is an assignment-based model that models guillotine cuts using a constant number of rectangular regions, with some regions allocated to items. It treats the entire plate as a primary region and decides on the guillotine cuts required to split the regions recursively till they produce space for the items. To speed the search, the model explores the strength of cumulative scheduling relaxations of the cutting problem. Our model is a successful alternative to more traditional mixed-integer linear programming (MILP) models. It outperforms a number of state-of-the-art MILPs on a set of small and moderate size benchmark instances and proves optimality for several instances that remain challenging for these MILPs.

Field-Oriented Predictive Control Structure for Synchronous Reluctance Motors

This paper presents a cascade predictive control structure based on field-oriented control (FOC) in the dq rotor reference frame for the synchronous reluctance machine (SynRM). The constant d-axis current control strategy was used, and thus, the electromagnetic torque was directly controlled by the q-axis current. Because the model of the two axes of currents from the inner loop is a coupled non-linear multivariable one, to control in a non-interaction and linear way the two currents, their decoupling was achieved through feedforward components. Following the decoupling, two independent monovariable linear systems resulted for the two current dynamics that were controlled using model predictive control (MPC) algorithms, considering their ability to automatically handle the state bounds. The most important bounds for SynRM are the limits imposed on currents and voltages, which in the dq plane correspond to a circular limit. To avoid computational effort, linear limitations were adopted through polygonal approximations, resulting in rectangular regions in the dq plane. For the outer loop that controls the angular speed with a constrained MPC algorithm, the q-axis current closed-loop dynamics and the torque linear equation were considered. To evaluate the performance of the proposed cascade predictive control structure, a simulation study using MPC controllers versus PI ones was conducted.

Precise asymmetric power‐splitter (1.7:1) by using nano‐pixel waveguide

AbstractPower‐splitter is one of the fundamental elements for photonic integrated circuits. Y‐junction, multi‐mode‐interference (MMI), and directional coupler may have been widely used as power splitter; however, the design theory to realize precise asymmetric splitting ratio is not well established. In addition, the device length is relatively long and less robustness in general. To realize a power splitter with a desired splitting ratio, the authors used a nano‐pixel structure. Nano‐pixel structures consist of an array of pixels in which the rectangular waveguide region is divided into many nano‐scale regions. The implemented devices were realized in an area of 3.2 μm × 3.4 μm. The device exhibited precise asymmetric splitting of 1.7:1 successfully at 1550 nm.

Deep Learning for Predicting Distant Metastasis in Patients with Nasopharyngeal Carcinoma Based on Pre-Radiotherapy Magnetic Resonance Imaging.

Accurate pre-treatment prediction of distant metastasis in patients with Nasopharyngeal Carcinoma (NPC) enables the implementation of appropriate treatment strategies for high-risk individuals. To develop and assess a Convolutional Neural Network (CNN) model using pre-therapy Magnetic Resonance (MR) imaging to predict distant metastasis in NPC patients. We retrospectively reviewed data of 441 pathologically diagnosed NPC patients who underwent complete radiotherapy and chemotherapy at Renmin Hospital of Wuhan University (Hubei, China) between February 2012 and March 2018. Using Adobe Photoshop, an experienced radiologist segmented MR images with rectangular regions of interest. To develop an accurate model according to the primary tumour, Cervical Metastatic Lymph Node (CMLN), the largest area of invasion of the primary tumour, and image segmentation methods, we constructed intratumoural and intra-peritumoural datasets that were used for training and test of the transfer learning models. Each model's precision was assessed according to its receiver operating characteristic curve and accuracy. Generated high-risk-related Grad-Cams demonstrated how the model captured the image features and further verified its reliability. Among the four models, all intra-peritumoural datasets performed better than the corresponding intratumoural datasets, with the CMLN intra-peritumoural dataset exhibiting the best performance (average area under the curves (AUCs) = 0.88). There was no significant difference between average AUCs of the Max and NPC tumour datasets. AUCs of the eight datasets for the four models were higher than those of the Tumour-Node-Metastasis staging system (AUC=0.67). In most datasets, the xception model had higher AUCs than other models. The efficientnet-b0 and xception models efficiently extracted high-risk features. The CNN model predicted distant metastasis in NPC patients with high accuracy. Compared to the primary tumour, the CMLN better predicted distant metastasis. In addition to intratumoural data, peritumoural information can facilitate the prediction of distant metastasis. With a larger sample size, datasets of the largest areas of tumour invasion may achieve meaningful accuracy. Among the models, xception had the best overall performance.

Faster goal-oriented shortest path search for bulk and incremental detailed routing

We develop new algorithmic techniques for VLSI detailed routing. First, we improve the goal-oriented version of Dijkstra’s algorithm to find shortest paths in huge incomplete grid graphs with edge costs depending on the direction and the layer, and possibly on rectangular regions. We devise estimates of the distance to the targets that offer better trade-offs between running time and quality than previously known methods, leading to an overall speed-up. Second, we combine the advantages of the two classical detailed routing approaches—global shortest path search and track assignment with local corrections—by treating input wires (such as the output of track assignment) as reservations that can be used at a discount by the respective net. We show how to implement this new approach efficiently.