Short Line Research Articles

A High Efficiency Broadband Gallium Nitride Power Amplifier with Harmonic Control technology

ABSTRACT In order to meet the requirements of high efficiency and broadband for the wireless communication system, a high efficiency and broadband gallium nitride power amplifier (PA) is designed and verified. Using the step-matching structure, its bandwidth has been improved. Furthermore, its input matching network is constructed by connecting several microband lines serially to reduce the matching Q value. Meanwhile, the harmonic control network is designed as the output matching network, which is built by a quarter-wave (λ/4) line open circuit and short circuit microwave lines in parallel. Thus, its drain efficiency (DE)can be improved. This design is simulated and tested at 2.2–3 GHz with the gallium nitride (GaN) process. After measuring, it attains an output power (Pout) of 39.5–41.5 dBm, Gain of 10.5–12.5 dB, DE of 65.1%–78.3% with power added efficiency (PAE) of 64.8%–76.2%.

A compact dual‐band bandpass filter based on coupled stub‐loaded square ring resonators by using transversal signal‐interaction concepts

AbstractIn this paper, a novel dual‐band wideband bandpass filter (BPF) based on transversal signal‐interaction concepts with a wide upper stopband is proposed and investigated. The designed specification of two passbands can be managed and satisfied based on the independent controllable fractional bandwidth of the two passbands and the centered frequencies. The centered frequencies of dual‐band BPF are, respectively, 0.79 GHz (ƒ1) and 1.24 GHz (ƒ2) with 3 dB fraction bandwidths of 26.54% and 11.3%. Two transmission paths consisting of coupled stub‐loaded square ring resonators and anti‐coupled shorted lines are used to realize signal cancellation of multiple transmission path signal transmission from Port 1 to Port 2. Eleven transmission zeros (TZs) modify harmonic suppression up to 10 ƒ1 with stopband rejection higher than 15 dB. Butterworth lumped notch network and step impedance resonator (SIR) are also utilized to improve the selectivity and harmonic suppression. A compact filter with a circuit size of 0.08λg × 0.08λg is implemented and tested. Good agreement between simulation and measured results verifies the reliability of the designing scheme.

Analytical solution of conductor tensile force in asymmetrical spans used in overhead power lines and substations with influence of tension insulators

Introduction. Designing electrical substations involves analyzing the horizontal tensile force in flexible tension conductors under varying temperatures. These temperature changes affect the conductor’s length and forces. Problem. Existing methods for calculating horizontal tensile force in conductors often focus on symmetric spans or require complex finite element modeling (FEM), which is impractical for routine substation design. Asymmetric spans with tension insulators present a more complex challenge that current solutions do not adequately address. Purpose. Universal analytical solution and algorithm for calculating the horizontal tensile forces in conductors in asymmetric spans with tension insulators used in power substations or short overhead power line spans. The solution is designed to be easily implementable in software without requiring complex tools or extensive FEM. Methodology. The methodology involves deriving an analytical solution based on the catenary curve formed by the conductor between attachment points at different heights. The analysis includes calculating the conductor’s length for a given tensile force and using a state change equation to determine forces under new temperature conditions. Validation is performed using FEM calculations. Results. The proposed solution was validated against FEM models with varying height differences (5 m and 15 m) and conductor temperatures (–30 °C, –5 °C, +80 °C). The results showed a minimal error (less than 0.15 %) between the analytical solution and FEM results, demonstrating high accuracy. Originality. This paper presents a novel analytical solution to the problem of calculating tensile forces in asymmetric spans with tension insulators. Unlike existing methods, our solution is straightforward and easily implementable in any programming language. Practical value. The solution is practical for routine design tasks in electrical substations or short overhead power lines. Especially in power substations, accurate tensile forces are needed not only for mechanical design and sag calculations but also for calculating the dynamic effects of short-circuit currents. References 23, tables 4, figures 3.

The consequence of ignoring load modeling on the circuit breaker selection in densely-meshed sub-transmission systems

In this paper, the selection of circuit breakers for a densely-meshed sub-transmission system with relatively short transmission lines is investigated. The results highlight the significance of modeling the load at the end of lines for accurately calculating the transient recovery voltage (TRV) following the short-circuit current interruption. According to IEEE standards, assuming load modeling at the end of the transmission lines can result in a maximum discrepancy of 20 % in the calculated TRV. Supposing that the load modeling leads to a moderating effect on the calculated TRV, the difference is considered as a safety margin, and load modeling is ignored. Nevertheless, the results presented here illustrate that this assumption strongly depends on characteristics of the studied network and the load type. In a network possessing the characteristics outlined in this paper, even a passive load as small as 15 % of the nominal capacity can significantly moderate the calculated TRV, with impacts reaching up to 38 %. Conversely, modeling an active load may result in a more severe TRV than if it were disregarded. The simulation results indicate that for networks with transmission lines longer than 70 km, neglecting to model passive loads on the transmission lines still yields sufficiently accurate calculations of TRV.

Integrated optimization of worker assignment, batch splitting and scheduling for a hybrid assembly line-seru production system

This paper studies an integrated optimization problem of worker assignment, batch splitting and scheduling for a hybrid assembly line-seru production system, which includes multiple serus and a short assembly line. The worker assignment involves assigning each multi-skilled worker to a seru or the assembly line, and assigning the worker tasks to perform. The batch splitting determines the number of subbatches split for each batch, the size of each subbatch, and in which seru the production of each subbatch is performed. The batch scheduling aims to optimize the process sequences of batches in serus and on the assembly line. For the integrated optimization problem, we propose a mixed-integer nonlinear programming model that minimizes the makespan. To solve large-scale instances of the problem, we develop a tailored hybrid variable neighborhood search algorithm with a four-layer solution coding scheme and four novel neighborhood structures. We validate the effectiveness of our model and solution algorithm on two sets of instances. The experimental results indicate that the proposed hybrid metaheuristic achieves a significant reduction in makespan, with an improvement of up to 20.94% compared to the solutions obtained by the Gurobi optimization solver within one hour. In addition, we demonstrate the advantage of optimized batch splitting by comparing it with no batch splitting and equal-size batch splitting strategies in the literature.

Knockdown of α-Enolase (ENO1) to Suppress Glycolytic Pathway in Human Hepatocellular Carcinoma Cell Line (HepG2)

ABSTRACT Hepatocellular carcinoma therapies which are potentially curative depend on early diagnosis, but unfortunately only 20% is the 5-year survival rate of liver cancer despite of various treatment methods which progress continuously. Patients with hepatocellular carcinoma presenting with late stage disease despite established screening guidelines for patients at risk because of asymptomatic nature of this disease so finding effective treatments are imperative. Alpha-enolase has been noticed to be commonly over-expressed in tumors including hepatocellular carcinoma, it is one of the leading regulators of the Warburg effect, so plays an important role in carcinogenesis and tumor maintenance. In this study the cell line α-enolase short interference RNA was successfully constructed. In the α-enolase short interference RNA cell lines, messenger RNA and protein expression of α-enolase were lower than those in negative control and blank control groups. The pyruvate level was significantly inhibited, the proliferation ability was significantly suppressed. Our data provide strong evidence that α-enolase short interference RNA can efficiently suppress glycolysis pathway and thus the proliferation of Hep G2, which may provide a novel gene therapy for hepatocellular carcinoma.

Reduced Training Data for Laser Ultrasound Signal Interpretation by Neural Networks

The performance of machine learning algorithms is conditioned by the availability of training datasets, which is especially true for the field of nondestructive evaluation. Here we propose one reconfigurable specimen instead of numerous reference specimens with known, unchangeable defect properties, which are usually complicated to fabricate. It consist of a shape memory polymer foil with temperature-dependent Young’s modulus and ultrasound attenuation. This open a possibility to generate a reconfigurable defect by projecting a heating laser in the form of a short line on the specimen surface. Ultrasound is generated by a laser pulse at one fixed position and detected by a laser vibrometer at another fixed position for 64 different defect positions and 3 different configurations of the specimen. The obtained diversified datasets are used to optimize the neural network architecture for the interpretation of ultrasound signals. We study the performance of the model in cases of reduced and dissimilar training datasets. In our first study, we classify the specimen configurations with the defect position being the disturbing parameter. The model shows high performance on a dataset of signals obtained at all the defect positions, even if trained on a completely different dataset containing signals obtained at only few defect positions. In our second study, we perform precise defect localization. The model becomes robust to the changes in the specimen configuration when a reduced dataset, containing signals obtained at two different specimen configurations, is used for the training process. This work highlights the potential of the demonstrated machine learning algorithm for industrial quality control. High-volume products (simulated by a reconfigurable specimen in our work) can be rapidly tested on the production line using this single-point and contact-free laser ultrasonic method.

Value chain analysis of Eucalyptus poles in around Bahir Dar, Northwestern Ethiopia

Value chain development is critical for ensuring the benefits of rapidly evolving plantation forests, such as Eucalyptus. This study examines the value chain of Eucalyptus poles, focusing on the investigation of actors and their roles, the benefit margin and value added to each actor, as well as the potential opportunities and challenges. A total of 194 (157 tree growers and 37 other actors) were selected using a multistage purposive random sampling technique. The study used value chain analysis and gross margin to explore Eucalyptus pole marketing lines, their functions, and estimate cost and value-added distributions. The results revealed direct actors, including tree growers, workers, traders, transporters, and exporting agents, and indirect actors (government, brokers, service providers, etc.). Around 18 Eucalyptus pole marketing lines were identified, with 80 % of the poles transacted in the major three lines. The Eucalyptus pole business is profitable for all involved. But not all have received an equal share of the benefits along the chain. Tree growers generated the highest value in the shortest lines, and traders reaped the highest benefit from the longer chain. Traders captured the highest percentage of the domestic price, while tree producers captured the least. A lack of access to market information, storage space, government and NGO support, inter-actor cooperation, the external effects of Eucalyptus, and the absence of land segregation have hampered the sector's development. Policy interventions should prioritize cluster planting, storage space provision, and cooperative creations to enhance community livelihoods and the sustainable management of Eucalyptus plantations. This study focuses on the Eucalyptus pole value chain due to its market significance, strategic relevance, market dynamics, actor profiles, and marketing systems associated with Eucalyptus poles. However, it still advocates for further research on Eucalyptus charcoal to understand its value chain dynamics and the broader Eucalyptus industry ecosystem.

UMPL- VINS: Generalized SLAM for multi-scene metaverse applications

The use of line features to improve the localization accuracy of point-based visual inertial SLAM (VINS) is of increasing interest because of the additional constraints they can provide on the scene structure. It is found that although the introduction of line features improves the accuracy of relative position estimation in some scenes due to the additional constraints, the two constraints only achieve an equalization for the estimated relative position. Therefore, in some environments two constraints can reduce the accuracy of the single-feature constraint algorithm and also make the real-time performance of the system more challenging. To address such issues, in this paper, we design a generalized SLAM system with point-line features that can be applied to multiple metaverse scenarios. We first enhance the image frames used for feature extraction by eliminating motion blur frames through the fuzzy metric method and mutation modeling of velocity and rotation. Then we improve the traditional line detection model by short line fusion, uniform distribution of line features, and refinement of edge features to obtain high-quality line features for building SLAM. Finally, based on the application of point features and line features for different scenes, a point and line feature separation-union model is proposed. In addition, we design a transformation model for line-point features to enhance the processing of point-line features. Experimental results on EuRoc, TUM_VI, KITTI, PennCOSYVIO and our own recorded dataset prove that the method proposed in this paper realizes a generalized SLAM with point and line features applied to multi-scenes with good advantages.

An Optimization Strategy for Truncating Ultralong Bus Lines Integrated with Metro Networks

For most ultralong bus lines, low punctuality rates and vehicle bunching are two main challenges. One potential strategy to solve these two problems is to split an ultralong line into two or three shorter lines according to historical passenger flow patterns as well as other presetting objectives and constraints. Thus, in this paper, a multiobjective optimization model is first established in consideration of both passenger flow distribution and coline metro networks. Then, the optimal truncated stop is determined by estimating the model results generated by enumerating each potential bus stop derived from related metro stops. The nondominated sorting genetic algorithm II (NSGA-II) is applied to solve the model efficiently. A case study conducted on a real bus line associated with metro networks in Beijing, China, demonstrates the efficiency of the optimization strategy adoption in terms of operating cost and passenger travel time, even with a slight increase in passenger cost. Besides, the multivehicle type is also referred in the experiments to verify economic efficiency to reduce operational costs.

Evaluation of the operational curve for heat storage technology using n-octacosane/low-density as a binding material

Heat storage technology has a critical role for a number of applications involving renewable thermal energy (such as solar water heater). The application of wax (n-octacosane/OCT) as a medium for storing heat brings many positive influences for the system. However, the operational curve is undesirable for the OCT-based energy storage, which makes it necessary to use a binding material. The present work employed LD-class polymer (LDPE) and linear-LDPE as binding materials for OCT. The mixture is prepared through mechanical hot stirring, which comes into two categories: SOCT1 (OCT/LD) and SOCT2 (OCT/LLD). The assessment through the calorimetry method shows an increment in transition temperature for SOCT with a value of 2.1 °C and 5.5 °C. This contributes to the variation of fusion energy for solid-liquid change for both materials, which amounted to 132.05 J/g (SOCT1) and 113.4 J/g (SOCT2). Another assessment related to its chemical and structural phase demonstrates that SOCT has an identical structure to OCT, indicating that SOCT is mixed physically. At the operational level, SOCT is more optimal than OCT according to the indicator related to charge and discharge duration for energy exchange. SOCT1 demonstrates a short plateau line as the indication of a steady transition between 65.4–67.9 °C, while SOCT2 indicates the average heating rate, which is higher than for single OCT. The heat releasing curve for SOCT1 varies at a lower value between 1.92 °C/min and 0.77 °C/min, while SOCT2 has the lowest variation, which is only 0.17 °C/min. Moreover, the self-insulation for SOCT2 has the lowest rate, which is only 0.3 °C/min. The evaluation and analysis from this work show that SOCT is reliable to increase the operational curve of OCT and can be implemented for thermal systems

Advanced Fault Detection in Power Systems Using Wavelet Transform: SIMULINK-Based Implementation and Analysis

Traditional methods struggle to find faults in power transmission lines. This paper presents an approach for short transmission lines, leveraging the power of wavelet transforms. Traditional methods analyze time-domain signals, limiting their ability to differentiate fault transients. Wavelet transforms, offering a combined time-frequency analysis, provide a deeper understanding of these transients. A detailed short transmission line model is built in SIMULINK. Diverse fault scenarios are meticulously simulated, and current signals undergo wavelet transform analysis. Key features extracted from the wavelet coefficients act as fingerprints of potential faults. These features are then utilized to develop a robust fault detection algorithm specifically designed for short transmission lines. The proposed method promises enhanced fault detection capabilities compared to existing techniques in this domain. The results, presented in subsequent sections, will shed light on the effectiveness of wavelet transforms in empowering smarter and more reliable transmission line operations.

Knowledge management in the care for people with intellectual disabilities during the COVID‐19 pandemic

AbstractThe study aimed to gain insight into knowledge management in the intellectual disabilities (ID) care sector during the COVID‐19 pandemic. We explored and described how knowledge producers, intermediaries, and knowledge users experienced knowledge management during this crisis situation, the responses to the specific knowledge needs in the ID‐care sector, and changes in roles and collaboration during this period. Twenty‐five individual in‐depth semi‐structured interviews were conducted with knowledge producers, intermediaries, and knowledge users in the Dutch ID‐care sector. An inductive thematic analysis was conducted. Three key themes were identified: (1) knowledge needs during the COVID‐19 pandemic, (2) experiences with knowledge management, and (3) roles and collaboration in knowledge management. There was an urgent need for specific ID‐related knowledge and how to translate available evidence for the general population into ID‐care settings. In knowledge management, the focus was on knowledge production and exchange, with validation and application receiving less attention. Within stakeholder groups, collaboration and knowledge exchange were intensified by existing or new knowledge infrastructures. Between stakeholder groups, knowledge producers and users created short lines to exchange needs and produce knowledge. This paper provides unique insights into knowledge management in the Dutch ID‐care sector during the COVID‐19 pandemic. Implications are discussed to improve future knowledge management processes. Support with knowledge validation and local knowledge infrastructures (complementary to centralized national knowledge infrastructures) help to assess the reliability and usefulness of knowledge and improve its use in practice during future pandemic‐related crisis situations.

The influence of anterior cervical discectomy and fusion surgery on cervical muscles and the correlation between related muscle changes and surgical efficacy

BackgroundAnterior cervical discectomy and fusion surgery (ACDF) is a common technique in treating degenerative cervical spondylosis. This study is to evaluate the changes of cervical muscles after ACDF and analyze the correlation between related muscle changes and clinical efficacy.MethodsSixty-five postoperative patients (single-level ACDF) with cervical spondylotic myelopathy from January 2013 to December 2022 were analyzed. The measured parameters include: the axial section of longus colli cross-sectional area (AxCSA), the volume of cervical longus, the ratio of long and short diameter line (RLS), the cervical extensor cross-sectional area (CESA), the vertebral body area (VBA), and the CESA/VBA. The visual analog scale (VAS), modified Japanese Orthopedic Association score (mJOA), and neck disability index (NDI) were evaluated. The changes in muscle morphology were analyzed, and the correlation analysis was conducted between morphological changes and function scores.ResultsThe postoperative AxCSA of surgical segment (3rd month, 12th month, and the last follow-up) was decreased compared to preoperative (141.62 ± 19.78), and the differences were significant (P < 0.05). The corresponding data reduced to (119.42 ± 20.08) mm2, (117.59 ± 19.69) mm2, and (117.41 ± 19.19) mm2, respectively (P < 0.05). The RLS increased, and the volume of cervical longus decreased significantly after surgery (P < 0.05). Negative correlation was found between postoperative volume of cervical longus and VAS at the 3rd month (r = − 0.412), 12th month (r = − 0.272), and last follow-up (r = − 0.391) (P < 0.05). Negative correlation existed between postoperative volume of cervical longus and NDI at the 3rd month (r = − 0.552), 12th month (r = − 0.293), and last follow-up (r = − 0.459) (P < 0.05).ConclusionThe volume of cervical longus decreased and its morphology changed after ACDF surgery. The mainly affected muscle was the cervical longus closing to the surgical segment. Negative correlation was found between the postoperative volume of cervical longus and function scores (VAS and NDI).

The impacts of the transmission line length in an interconnected micro-grid on its performance and protection at different fault levels

Power systems, in recent years, have been experiencing a dynamic rise in the amount of power obtained from distributed renewable energy sources leading to the concept of microgrids to address the distributed power grid integration issues. Microgrids, a promising means of facilitating the green transformation of power systems, allow the union operation of distributed energy resources (DER) such as combined heat and power (CHP), renewables like photovoltaic (PV), wind and fuel cells (FC), energy storage systems, diesel generators, and controllable loads, either individually or in combination. The protection of DERs within microgrids can be considered as one of the main challenges associated with such phenomenon. Short and Long power transmission lines, in case of a fault, both have particular impacts on system parameters and may result into subsequent events threatening the microgrid and renewable generation units. On the other hand, The high penetration of microgrids not only can change the power flow within the power network, but it can also affect the fault current levels and may lead to their islanding in case of a fault. Before investing in microgrids, especially those in far places, this paper develops a tool to be used in investigating the influence of the interconnecting transmission line length as well as the type/severity of fault on the microgrid performance. The toolbox was developed using MATLAB/Simulink Toolbox. The developed tool was then validated on a case study microgrid and results show that the length of the interconnecting transmission line and the fault severity directly impact the microgrid performance (i.e. voltage and power deviations). In that case, interconnection or islanded mode is contingent upon the decision of the utility operator which also depends on the sensitivity of the equipment used in the microgrid.

A practical ball‐grid‐array transition modelling methodology for accurate and fast multi‐interposer package simulation

AbstractAn equivalent circuit modelling methodology for the ball‐grid‐array (BGA) transition is proposed and validated with full‐wave electromagnetic simulation and measurement results. The BGA transitions modelled with the proposed methodology are validated to have a good accuracy up to 40 GHz. Unlike the existing BGA modelling methodologies which cannot model the BGA transition with short transmission lines within the anti‐pad region, the proposed methodology is developed from the practical BGA modelling scenario and models the irregular‐shape solder pads with transmission lines within the anti‐pad region. The BGA transitions modelled with the proposed methodology can be used for accurate and fast signal integrity simulations, analyses, and optimizations on 2.5D and 3D packaging. Additionally, factors impacting the accuracy of the equivalent circuit model are revealed by the proposed methodology.

A bi-objective approach for the multi-skilled worker assignment of a hybrid assembly line-seru production system

The flexibility and responsiveness of seru production have caught the attention of manufacturing and electronics industries. However, multi-skilled worker assignment poses a crucial and challenging decision-making problem for seru production systems. The existing literature on this problem for pure seru production systems primarily focuses on improving efficiency indexes, which often leads to an unbalanced workload among workers. To address this issue, this article investigates multi-skilled worker assignment for a hybrid assembly line-seru production system that comprises divisional serus and a short assembly line. To balance workload and optimize production efficiency, a bi-objective integer nonlinear programming model is developed. This model jointly optimizes worker-to-seru, worker-to-line, batch-to-seru, task-to-worker, and the processing sequence of each batch. A meta-heuristic method, combining Non-Dominated Sorting Genetic Algorithm II (NSGA-II) with Multi-Objective Simulated Annealing (MOSA), NSGA-II-MOSA, is designed to solve the model. The results of numerical experiments demonstrate that the proposed model and solving method can greatly reduce workload imbalance while maintaining production efficiency. Moreover, NSGA-II-MOSA provides better Pareto solutions than three well-known multi-objective optimization approaches.

Analysis on the low-frequency electromagnetic pulse coupling to horizontal electrically short lines

In this study, we investigated the coupling features of the nuclear electromagnetic pulse (NEMP) on overhead cables in the middle-and-far regions, different from the transmission line model commonly used for field-line coupling in high-frequency cases, using a simpler lumped approximation to solve the electrically small size model in low-frequency cases. To verify its effectiveness, a simulation model with the same conditions was set up using the software of Computer Simulation Technology (CST), and cable coupling experiments were performed in a laboratory environment using a bounded-wave electromagnetic pulse simulator. The calculated results of the lumped approximation circuit were compared with the CST simulation and measured results, and the agreement was good. The results also shows that the load exhibits a differential response in the case of the low impedance and it is consistent with the excitation signal in the case of the high impedance. Finally, some more experiments were constructed to analyzed the effect of different cable parameters on the cable load response through experiments, and the experimental results are also in general agreement with the theoretical analysis, in which the induced signal of the low-impedance load is mainly determined by the magnetic field in the direction normal to the cable and the ground loop and the induced signal of the high-impedance load is mainly determined by the electric field in the direction of the height of the cable erection.

Controlling Randomization in Astronomy Simulations

As the primary requirement, correctly implementing and controlling random number generation is vital for a range of scientific analyses and simulations across astronomy and planetary science. Beyond advice on how to set the seed, there is little guidance in the literature for how best to handle pseudo-random number generation in the current era of open-source astronomical software development. We present our methodology for implementing a pseudo-random number generation in astronomy simulations and software and share the short lines of python code that create the generator. Without sacrificing randomization at run time, our strategy ensures reproducibility on a per function/module basis for unit testing and for run time debugging where there may be multiple functions requiring lists of randomly generated values that occur before a specific function is executed.

Research on Image Stitching Algorithm Based on Point-Line Consistency and Local Edge Feature Constraints.

Image stitching aims to synthesize a wider and more informative whole image, which has been widely used in various fields. This study focuses on improving the accuracy of image mosaic and proposes an image mosaic method based on local edge contour matching constraints. Because the accuracy and quantity of feature matching have a direct influence on the stitching result, it often leads to wrong image warpage model estimation when feature points are difficult to detect and match errors are easy to occur. To address this issue, the geometric invariance is used to expand the number of feature matching points, thus enriching the matching information. Based on Canny edge detection, significant local edge contour features are constructed through operations such as structure separation and edge contour merging to improve the image registration effect. The method also introduces the spatial variation warping method to ensure the local alignment of the overlapping area, maintains the line structure in the image without bending by the constraints of short and long lines, and eliminates the distortion of the non-overlapping area by the global line-guided warping method. The method proposed in this paper is compared with other research through experimental comparisons on multiple datasets, and excellent stitching results are obtained.