Variable Positions Research Articles

Development of a dual point humidity sensor using POF based on twisted fiber structure

The humidity has often been measured through a single point sensor. Where, the humidity could be varied at different locations as well as depending on environmental conditions. The present paper developed the dual point humidity measuring sensor by using a polymer optical fiber (POF) based on a single illuminating fiber. The sensor’s basic structure is to twist two fibers and bend them at a certain radius. However, the dual point sensor is developed through the cascading of twisted micro bend (TMB-1 and TMB-2). The twisting of fibers couples the light from one fiber to another fiber through the side coupling method. An increase in the humidity level leads to a change in the reflective index, which helps to get variation in coupled light intensity. To measure the humidity, the dual point sensors are placed into the control humidity chamber at two random positions. The power reading variation is significantly linear when the humidity level increases from 30 to 80%. The sensor has a fast response of about 1 s and a recovery time of about 4 s. Furthermore, the chemical coating is applied to improve the sensor’s sensitivity. Between 30 and 80% range of humidity, the both sensors of dual point TMB-1 and TMB-2 have appropriate sensitivity and detection limits, which is about 680.8 nW/% and 763.9 nW/% and 1.37% and 1.98%, respectively. To measure the humidity at variable positions, the present dual points humidity sensor is well-stable, easy, and straightforward, which uses a less expensive method.

Numerical Investigation of Butterfly Valve Performance in Variable Valve Sizes, Positions and Flow Regimes

Reliability and efficiency of valves are necessary for precise control and sufficient heat-flow to heat application plants for the integrated energy systems of nuclear power plants (NPPs). Strategic Management Analysis Requirement and Technology (SMART) valves’ ability to control flow and assess environmental parameters stands out for these requirements. Their ability to sustain the downstream flow rate, prevent reverse flow, and maintain pressure in the heat transport loop is much more efficient with the integration of sensors and intelligent algorithms. For assessing valve performance and monitoring, mechanical design and operating conditions are two important parameters. In this study, the butterfly valves of three different sizes are simulated with water and steam using STAR-CCM+ in various flow regimes and positions to analyze performance parameters to strategize an automated control system for efficiently balancing the heat–transport network. Also, flow behavior is studied using velocity and pressure fields for valve–body geometry optimization. It can be observed, through performance parameters, that the valves are suitable for operation between 30° and 90° positions with significantly low loss coefficients and high flow coefficients, and the performance parameters follow a certain pattern in both water and steam flow in each scenario.

CPAK classification detect the real knee joint apex position in less than half of the knees.

Accurate assessment of the knee joint line is essential for surgeries involving the knee. The knee joint line obliquity (KJLO) is a radiological measurement that evaluates the position of the knee joint relative to the ground and is frequently used in preoperative planning and clinical follow-up. On the other hand, coronal plane alignment of the knee (CPAK) classifications assesses the joint line as the summation of the medial proximal tibial angle (MPTA) and mechanical lateral distal femoral angle (mLDFA). The purpose of this study is to determine the concordance of these two measurement techniques. This cross-sectional study evaluated the long-leg standing radiographs (LSRs) of 164 healthy knees. The extremity KJLO and CPAK classification JLO were measured twice by twoobservers at 8-week intervals. The knee joint line apex positions (proximal, neutral and distal) of the two measurement techniques are compared (concordance or discordant). The intraobserver and interobserver reliability were examined using the intraclass correlation coefficient (ICC). Possible causes of the discordant were evaluated with univariate and multivariate logistic regression analysis. CPAK classification detected the KJLO apex position in 70 extremities (42.7%) only. Subgroups CPAK JLO detected 13.6% of the proximal apex, 20.4% of the neutral, and 90.7% of the distal apex (p < 0.01). Upon multivariate logistic regression analysis, the variable KJLO apex position (proximal, neutral vs. distal, odds ratio (OR) = 10.291, 95% confidence interval [CI] = 2.225-25.656, and (p < 0.01) was determined as a risk factor for discordant. The CPAK JLO measurement technique can be misleading in defining the KJLO apex position and the concordance between them is less than 50%. It has a high tendency to misleadingly predict proximal and neutral apex positions, which can potentially have negative implications for assessing the joint line. Level I.

Seam tracking and gap bridging during robotic laser beam welding via grayscale imaging and wobbling

The use of laser beam welding with robotic manipulators is expanding towards wider industrial applications as the system availability increases with reduced capital costs. Conventionally, laser welding requires high positioning and coupling accuracy. Due to the variability in the part geometry and positioning, as well as the thermal deformation that may occur during the process, joint position and fit-up are not always acceptable nor predictable a-priori if simple fixtures are used. This makes the passage from virtual CAD/CAM environment to real production site not trivial, limiting applications where short part preparations are a need like small-batch productions. Solutions that render the laser welding operations feasible for production series with non-stringent tolerances are required to serve a wider range of industrial applications. Such solutions should be able to track the seam as well as tolerating variable gaps formed between the parts to be joined. In this work, an online correction for robot trajectory based on a greyscale coaxial vision system with external illumination and an adaptive wobbling strategy are proposed as means to increase the overall flexibility of a manufacturing plant. The underlying vision algorithm and control architectures are presented; the robustness of the system to poor illumination conditions and variable reflection conditions is also discussed. The developed solution employed two control loops: the first is able to change the robot pose to follow varying trajectories; the second, able to vary the amplitude of circular wobbling as a function of the gap formed in butt-joint welds. Demonstrator cases on butt-joint welds with AISI 301 stainless steel with increased complexity were used to test the efficacy of the solution. The system was successfully tested on 2 mm thick, planar stainless-steel sheets at a maximum welding speed of 25 mm/s and yielded a maximum positioning and yaw-orientation errors of respectively 0.325 mm and 4.5°. Continuous welds could be achieved with up to 1 mm gaps and variable seam position with the developed control method. The acceptable weld quality could be maintained up to 0.6 mm gap in the employed autogenous welding configuration.

Experimental, numerical and analytical studies on full-scale cold-formed steel center-sheathed shear walls subjected to combined loading

Conventional cold-formed steel wall systems suffer from low lateral loading-carrying capacities and stiffnesses, which represent the main barrier to their use in multi-story buildings. To address it, a cold-formed steel center-sheathed shear wall (CFSCSSW) system with higher lateral load-carrying capacity and better lateral structural performance is proposed. This paper presents experimental, numerical, and analytical studies on the behavior of the proposed CFSCSSW subjected to combined vertical and horizontal loads. Firstly, a full-scale test was conducted, with the test setup, loading procedures and measuring instrument reported in detail. The obtained test results, including the load-carrying capacity, failure mode and strains, were fully analyzed. Then, finite element modeling was conducted to simulate the experimental observations, and parametric studies were carried out to investigate the influences of different geometric and loading parameters on the behavior of CFSCSSWs. Finally, a three-strip model with a variable position on end studs (TSM-VPC) was proposed for CFSCSSWs and shown to accurately simulate the direction of the tensile field within the sheathing and also resulted in high accuracy in calculating the load-carrying capacities, followed by a design example.

2.5D UNet with context-aware feature sequence fusion for accurate esophageal tumor semantic segmentation

Segmenting esophageal tumor from computed tomography (CT) sequence images can assist doctors in diagnosing and treating patients with this malignancy. However, accurately extracting esophageal tumor features from CT images often present challenges due to their small area, variable position, and shape, as well as the low contrast with surrounding tissues. This results in not achieving the level of accuracy required for practical applications in current methods. To address this problem, we propose a 2.5D context-aware feature sequence fusion UNet (2.5D CFSF-UNet) model for esophageal tumor segmentation in CT sequence images. Specifically, we embed intra-slice multiscale attention feature fusion (Intra-slice MAFF) in each skip connection of UNet to improve feature learning capabilities, better expressing the differences between anatomical structures within CT sequence images. Additionally, the inter-slice context fusion block (Inter-slice CFB) is utilized in the center bridge of UNet to enhance the depiction of context features between CT slices, thereby preventing the loss of structural information between slices. Experiments are conducted on a dataset of 430 esophageal tumor patients. The results show an 87.13% dice similarity coefficient, a 79.71% intersection over union and a 2.4758 mm Hausdorff distance, which demonstrates that our approach can improve contouring consistency and can be applied to clinical applications.

Use of a wax bite for accurate lateral skull radiographs

CPD/Clinical Relevance: The reader will learn a method of simplifying the process of taking a lateral skull radiograph with the mandible in a reproducible position in patients who have a variable jaw closure position.

Data and physics-driven modeling for fluid flow with a physics-informed graph convolutional neural network

A physics-informed graph convolutional network (PINN-GCN) data-driven model was proposed to solve steady-state fluid flows with various geometries. A GCN guarantees a data-driven model that adapts to irregularly structured or unstructured mesh data. In addition, the mean squared residuals of the governing equations in partial differential forms and boundary conditions are introduced into the loss function of the network model, the Physics-Informed Neural Network (PINN) increases the knowledge of the physical rules of the model, enhances the model accuracy even with sparse training data. With nine training cases containing approximately 2000 spatial point data individually, PINN-GCN could accurately predict the physical flow field over a two-dimensional object of variable size, achieving above 98.6% for mean accuracy. With five training data cases, the model could predict flow over a cylinder with variable position, achieving above 98.2% for mean accuracy. Moreover, the PINN-GCN framework can produce high-resolution predictions, even with low-resolution field training data. Furthermore, the PINN-GCN prediction speed was approximately 1000 times faster than that of the numerical simulations. Thus, the proposed model can rapidly predict high-resolution flow fields using a physics-informed, grid- and geometry-adaptive, data-driven model.

Cross-Layer and Cross-Sample Feature Optimization Network for Few-Shot Fine-Grained Image Classification

Recently, a number of Few-Shot Fine-Grained Image Classification (FS-FGIC) methods have been proposed, but they primarily focus on better fine-grained feature extraction while overlooking two important issues. The first one is how to extract discriminative features for Fine-Grained Image Classification tasks while reducing trivial and non-generalizable sample level noise introduced in this procedure, to overcome the over-fitting problem under the setting of Few-Shot Learning. The second one is how to achieve satisfying feature matching between limited support and query samples with variable spatial positions and angles. To address these issues, we propose a novel Cross-layer and Cross-sample feature optimization Network for FS-FGIC, C2-Net for short. The proposed method consists of two main modules: Cross-Layer Feature Refinement (CLFR) module and Cross-Sample Feature Adjustment (CSFA) module. The CLFR module further refines the extracted features while integrating outputs from multiple layers to suppress sample-level feature noise interference. Additionally, the CSFA module addresses the feature mismatch between query and support samples through both channel activation and position matching operations. Extensive experiments have been conducted on five fine-grained benchmark datasets, and the results show that the C2-Net outperforms other state-of-the-art methods by a significant margin in most cases. Our code is available at: https://github.com/zenith0923/C2-Net.

Laparoscopic Management of Adrenal and Extra-Adrenal Pheochromocytoma

Background and Purpose Laparoscopic management of extra-adrenal pheochromocytoma requires meticulous surgical procedures because of the variable anatomic position and/or proximity to major blood vessels and the potential catecholamine surge during operation. We present our experiences with laparoscopic management of extra-adrenal pheochromocytoma and compare the intraoperative hemodynamics with those during laparoscopic resection of adrenal pheochromocytoma. Patients and Methods We retrospectively reviewed the medical records of 3 patients who underwent laparoscopic management of extra-adrenal pheochromocytoma (retrocaval, n=1; interaortocaval, n=1; periadrenal, n=1) and 24 patients who underwent laparoscopic management of adrenal pheochromocytoma between June 2005 and June 2023. We also evaluated fluctuations in blood pressure (BP) reported during both surgeries. Results The tumors were successfully resected under laparoscopic guidance in both groups, and one patient had converted to open surgery. Intraoperative hypertension (BP&gt;200 mm Hg) was observed in 1 extra-adrenal pheochromocytoma and 13 adrenal pheochromocytoma patients, whereas intraoperative hypotension (BP &lt;80 mm Hg) was observed in 1 extra-adrenal pheochromocytoma and 12 adrenal pheochromocytoma patients. Conclusion Laparoscopy is the method of choice for extra-adrenal resection because it is feasible and reproducible with appropriate preoperative planning, similar to adrenal resection.

Design and mathematical modeling of DNG metamaterial having six-band capabilities with high effective medium ratio

ABSTRACT In this paper, six-band double negative (DNG) metamaterial with a substantially high effective medium ratio (EMR) under the S and C microwave band is designed and investigated for multiple microwave applications. The proposed metamaterial unit cell consists of four Plus Appended Split Ring Resonator (PASRR) cells, which are combined with variable sides and positions by plus (+) shape stubs at the centre. All four Plus Appended Split Ring Resonator (PASRR) cells are mutually coupled with each other to vary the electrical length to achieve hexa Bands DNG characteristics in a lossy FR-4 epoxy substrate with the thickness of 1.5748 mm. A parameter extraction method has been used to extract effective permittivity (ε eff), permeability (μ eff) and refractive index (n). Moreover, the equivalent circuit model is obtained. Ansys HFSSTM software & Keysight ADSTM software are used to obtain the simulated and theoretical results, respectively, which agree measured with simulated and theoretical results.

Determination of plastic deformation with variable ultrasonic excitation positions

For highly stressed mechanical components, information regarding the beginning of plastic deformation is of enormous importance. Therefore, nondestructive testing and structural health monitoring techniques are essential to examine said components and to make statements concerning the mechanical integrity. In this work, dislocation theory was extended and combined with ultrasonic wave excitation to obtain dislocations in isotropic materials. In the analytical derivation, the ultrasonic longitudinal waves were sent in different propagation directions relative to the uniaxial tensile load. The derived nonlinearity coefficients enabled the investigation as a function of these angles. The evaluated coefficient behaviour allows for statements about the position of the ultrasonic excitation relative to the tensile load to be made. Furthermore, a signature could be derived from which the degree of plasticity can be determined if a reference measurement is available. The newly derived coefficients and their behaviour make it possible to efficiently detect the beginning of plastic deformation and to predict the position of the applied load vector.

Real-Time Non-Invasive Imaging and Detection of Spreading Depolarizations through EEG: An Ultra-Light Explainable Deep Learning Approach.

A core aim of neurocritical care is to prevent secondary brain injury. Spreading depolarizations (SDs) have been identified as an important independent cause of secondary brain injury. SDs are usually detected using invasive electrocorticography recorded at high sampling frequency. Recent pilot studies suggest a possible utility of scalp electrodes generated electroencephalogram (EEG) for non-invasive SD detection. However, noise and attenuation of EEG signals makes this detection task extremely challenging. Previous methods focus on detecting temporal power change of EEG over a fixed high-density map of scalp electrodes, which is not always clinically feasible. Having a specialized spectrogram as an input to the automatic SD detection model, this study is the first to transform SD identification problem from a detection task on a 1-D time-series wave to a task on a sequential 2-D rendered imaging. This study presented a novel ultra-light-weight multi-modal deep-learning network to fuse EEG spectrogram imaging and temporal power vectors to enhance SD identification accuracy over each single electrode, allowing flexible EEG map and paving the way for SD detection on ultra-low-density EEG with variable electrode positioning. Our proposed model has an ultra-fast processing speed (<0.3 sec). Compared to the conventional methods (2 hours), this is a huge advancement towards early SD detection and to facilitate instant brain injury prognosis. Seeing SDs with a new dimension - frequency on spectrograms, we demonstrated that such additional dimension could improve SD detection accuracy, providing preliminary evidence to support the hypothesis that SDs may show implicit features over the frequency profile.

The interaction between heterochrony and mechanical forces as main driver of floral evolution.

Heterochrony acts as a fundamental process affecting the early development of organisms in creating a subtle shift in the timing of initiation or the duration of a developmental process. In flowers this process is linked with mechanical forces that cause changes in the interaction of neighbouring floral organs by altering the timing and rate of initiation of organs. Heterochrony leads to a delay or acceleration of the development of neighbouring primordia, inducing a change in the morphospace of the flowers. As changes in the timing of development may affect organs differently at different stages of development, these shifts eventually lead to major morphological changes such as altered organ positions, fusions, or organ reductions with profound consequences for floral evolution and the diversification of flowers. By concentrating on early developmental stages in flowers it is possible to understand how heterochrony is responsible for shifts in organ position and the establishment of a novel floral Bauplan. However, it remains difficult to separate heterochrony as a process from pattern, as both are intimately linked. Therefore it is essential to connect different patterns in flowers through the process of developmental change.Examples illustrating the importance of heterochronic shifts affecting different organs of the flower are presented and discussed. These cover the transition from inflorescence to flower through the interaction of bracts and bracteoles, the pressure exercised by the perianth on the androecium and gynoecium, the inversed influence of stamens on petals, and the centrifugal influence of carpels on the androecium. Different processes are explored, including the occurrence of obdiplostemony, the onset of common primordia, variable carpel positions, and organ reduction and loss.

Two characterizations of the dense rank

In this paper, we have considered the dense rank for assigning positions to alternatives in weak orders. If we arrange the alternatives in tiers (i.e., indifference classes), the dense rank assigns position 1 to all the alternatives in the top tier, 2 to all the alternatives in the second tier, and so on. We have proposed a formal framework to analyze the dense rank when compared to other well-known position operators, such as the standard, modified and fractional ranks. As the main results, we have provided two different axiomatic characterizations which determine the dense rank by considering position invariance conditions along horizontal extensions (duplication), as well as through vertical reductions and movements (truncation, and upward or downward independency).

Chloromonas fuhrii sp. nov. (Chlorophyceae), a cosmopolitan alga from colored snow

ABSTRACT The modern concept of the genus Chloromonas includes a subclade of species found exclusively in snow. We describe Chloromonas (Cr.) fuhrii sp. nov., a new member of this clade, which is closely related to Cr. muramotoi from Japan. The new species is characterised by the absence of a stigma, pyrenoid, and defined papilla, ready loss of flagella in culture, and a single lobed chloroplast. Strains of Cr. fuhrii have been sourced from green, orange, and pink/red snow. The species has been found in Svalbard, Antarctica, and New Zealand, with most genetic variation occurring in Svalbard. The minimal variation present in New Zealand strains suggests a relatively recent arrival. Secondary structure models for ITS2 in the new species demonstrate a separation from Cr. muramotoi due to one CBC. The nine New Zealand strains isolated showed no variation in ITS2 but four variable base positions in ITS1. Inclusion of the single Antarctic and four Svalbard strains resulted in 14 variable positions in ITS2 and 69 in ITS1, with the sequences remaining alignable. The ITS data showed a strong biogeographic signal, both in total in an unrooted tree, and using ITS2 alone with Cr. muramotoi as an outgroup. The absence of a stigma in this species prompted a survey of the literature, showing that stigma absence in Chloromonas is strongly associated with the snow habitat, occurring at about 10 times the rate observed in other habitats, perhaps owing to the difficulty of phototaxis in snow with abundant reflected light.

PEXEL is a proteolytic maturation site for both exported and non-exported Plasmodium proteins.

Obligate intracellular malaria parasites dramatically remodel their erythrocyte host through effector protein export to create a niche for survival. Most exported proteins contain a pentameric Plasmodium export element (PEXEL)/host-targeting motif that is cleaved in the parasite ER by the aspartic protease Plasmepsin V (PMV). This processing event exposes a mature N terminus required for translocation into the host cell and is not known to occur in non-exported proteins. Here, we report that the non-exported parasitophorous vacuole protein UIS2 contains a bona fide PEXEL motif that is processed in the P. falciparum blood stage. While the N termini of exported proteins containing the PEXEL and immediately downstream ~10 residues are sufficient to mediate translocation into the RBC, the equivalent UIS2 N terminus does not promote the export of a reporter. Curiously, the UIS2 PEXEL contains an unusual aspartic acid at the fourth position, which constitutes the extreme N-terminal residue following PEXEL cleavage (P1', RIL↓DE). Using a series of chimeric reporter fusions, we show that Asp at P1' is permissive for PMV processing but abrogates export. Moreover, mutation of this single UIS2 residue to alanine enables export, reinforcing that the mature N terminus mediates export, not PEXEL processing per se. Prompted by this observation, we further show that PEXEL sequences in the N termini of other non-exported rhoptry proteins are also processed, suggesting that PMV may be a more general secretory maturase than previously appreciated, similar to orthologs in related apicomplexans. Our findings provide new insight into the unique N-terminal constraints that mark proteins for export.IMPORTANCEHost erythrocyte remodeling by malaria parasite-exported effector proteins is critical to parasite survival and disease pathogenesis. In the deadliest malaria parasite Plasmodium falciparum, most exported proteins undergo proteolytic maturation via recognition of the pentameric Plasmodium export element (PEXEL)/host-targeting motif by the aspartic protease Plasmepsin V, which exposes a mature N terminus that is conducive for export into the erythrocyte host cell. While PEXEL processing is considered a unique mark of exported proteins, we demonstrate that PEXEL motifs are present and processed in non-exported proteins. Importantly, we show that specific residues at the variable fourth position of the PEXEL motif inhibit export despite being permissive for processing, reinforcing that features of the mature N terminus, and not PEXEL cleavage, identify cargo for export. This opens the door to further inquiry into the nature and evolution of the PEXEL motif.

Coupled effect of injection position variation on gas exchange stability of a free-piston engine

Gas exchange fluctuations may lead to operation instability of the free-piston engine (FPE), because the engine has a coupling effect between the gas exchange and the piston motion, which is different from a conventional engine. It is, therefore, important to study the gas exchange instability to ensure the stable operation of the engine. This study focuses the effect of variable piston position when injecting on the gas exchange stability of a looped scavenging FPE, and a systematic full-cycle gas exchange model is presented by developing a dynamic model, a combustion model, and a multidimensional scavenging model. Meanwhile, an iterative method between motion and scavenging is used to solve the model numerically for gas exchange simulation, and the effects of variable piston position when injecting on piston motion, thermodynamic in cylinder, and gas exchange process are studied. The results indicate that retarding injection induces instability of gas exchange duration which first increases and then decreases, and there is an injection position which is most conducive to the increase of capture efficiency of gas exchange, although the scavenging efficiency is lowest under this condition. This result also suggests that more complete exhaust may be achieved by a different injection position.

Rockburst prevention by microwave destressing: a numerical investigation

Rockbursts are a complex phenomenon characterized by a violent ejection of rock fragments from the free face of deep underground mines. Due to the sudden, disruptive, and complex nature of these events, accurate predictions of rockbursts are difficult. Therefore, geotechnical intervention is imperative to prevent the occurrence of a rockburst. The scenarios of microwave destressing is introduced here as an application method to potentially prevent their occurrence. To understand the influences of microwave destressing, such as microwave exposure duration, spatial layout, and geometric parameters of the microwave preconditioned zone (MPZ), on the occurrence of a rockburst, numerical simulation was conducted based on an impact-induced rockburst model. The feasibility of microwave destressing technology was validated numerically. This paper also provides guidance for the utilization of microwave destressing in practice. Discontinuous MPZ is suitable for a known blasting source with a fixed position, and continuous MPZ can be applied for a working condition with multiple blasting sources with variable positions. A closer distance of MPZ from the free face results in a better microwave destressing effect. However, the closer distance of MPZ from the free face also introduces more negative influences on the static stability of surrounding rock.

Path planning for robots in preform weaving based on learning from demonstration

AbstractA collision-free path planning method is proposed based on learning from demonstration (LfD) to address the challenges of cumbersome manual teaching operations caused by complex action of yarn storage, variable mechanism positions, and limited workspace in preform weaving. First, by utilizing extreme learning machines (ELM) to autonomously learn the teaching data of yarn storage, the mapping relationship between the starting and ending points and the teaching path points is constructed to obtain the imitation path with similar storage actions under the starting and ending points of the new task. Second, an improved rapidly expanding random trees (IRRT) method with adaptive direction and step size is proposed to expand path points with high quality. Finally, taking the spatical guidance point of imitation path as the target direction of IRRT, the expansion direction is biased toward the imitation path to obtain a collision-free path that meets the action yarn storage. The results of different yarn storage examples show that the ELM-IRRT method can plan the yarn storage path within 2s–5s when the position of the mechanism changes in narrow spaces, avoiding tedious manual operations that program the robot movements, which is feasible and effective.