Output Factors Research Articles

A generalized model for monitor units determination in ocular proton therapy using machine learning: A proof-of-concept study

Objective. Determining and verifying the number of monitor units is crucial to achieving the desired dose distribution in radiotherapy and maintaining treatment efficacy. However, current commercial treatment planning system(s) dedicated to ocular passive eyelines in proton therapy do not provide the number of monitor units for patient-specific plan delivery. Performing specific pre-treatment field measurements, which is time and resource consuming, is usually gold-standard practice. This proof-of-concept study reports on the development of a multi-institutional-based generalized model for monitor units determination in proton therapy for eye melanoma treatments. Approach. To cope with the small number of patients being treated in proton centers, three European institutes participated in this study. Measurements data were collected to address output factor differences across the institutes, especially as function of field size, spread-out Bragg peak modulation width, residual range, and air gap. A generic model for monitor units prediction using a large number of 3748 patients and broad diversity in tumor patterns, was evaluated using six popular machine learning algorithms: (i) decision tree; (ii) random forest, (iii) extra trees, (iv) K-nearest neighbors, (v) gradient boosting, and (vi) the support vector regression. Features used as inputs into each machine learning pipeline were: Spread-out Bragg peak width, range, air gap, fraction and calibration doses. Performance measure was scored using the mean absolute error, which was the difference between predicted and real monitor units, as collected from institutional gold-standard methods. Main results. Predictions across algorithms were accurate within 3% uncertainty for up to 85.2% of the plans and within 10% uncertainty for up to 98.6% of the plans with the extra trees algorithm. Significance. A proof-of-concept of using machine learning-based generic monitor units determination in ocular proton therapy has been demonstrated. This could trigger the development of an independent monitor units calculation tool for clinical use.

Geriatric Population Triage: The Risk of Real-Life Over- and Under-Triage in an Overcrowded ED: 4- and 5-Level Triage Systems Compared: The CREONTE (Crowding and R E Organization National TriagE) Study.

Elderly patients, when they present to the emergency department (ED) or are admitted to the hospital, are at higher risk of adverse outcomes such as higher mortality and longer hospital stays. This is mainly due to their age and their increased fragility. In order to minimize this already increased risk, adequate triage is of foremost importance for fragile geriatric (>75 years old) patients who present to the ED. The admissions of elderly patients from 1 January 2014 to 31 December 2020 were examined, taking into consideration the presence of two different triage systems, a 4-level (4LT) and a 5-level (5LT) triage system. This study analyzes the difference in wait times and under- (UT) and over-triage (OT) in geriatric and general populations with two different triage models. Another outcome of this study was the analysis of the impact of crowding and its variables on the triage system during the COVID-19 pandemic. A total of 423,257 ED presentations were included. An increase in admissions of geriatric, more fragile, and seriously ill individuals was observed, and a progressive increase in crowding was simultaneously detected. Geriatric patients, when presenting to the emergency department, are subject to the problems of UT and OT in both a 4LT system and a 5LT system. Several indicators and variables of crowding increased, with a net increase in throughput and output factors, notably the length of stay (LOS), exit block, boarding, and processing times. This in turn led to an increase in wait times and an increase in UT in the geriatric population. It has indeed been shown that an increase in crowding results in an increased risk of UT, and this is especially true for 4LT compared to 5LT systems. When observing the pandemic period, an increase in admissions of older and more serious patients was observed. However, in the pandemic period, a general reduction in waiting times was observed, as well as an increase in crowding indices and intrahospital mortality. This study demonstrates how introducing a 5LT system enables better flow and patient care in an ED. Avoiding UT of geriatric patients, however, remains a challenge in EDs.

Deep Learning-Based Fishing Ground Prediction Using Asymmetric Spatiotemporal Scales: A Case Study of Ommastrephes bartramii

Selecting the optimal spatiotemporal scale in fishing ground prediction models can maximize prediction accuracy. Current research on spatiotemporal scales shows that they are symmetrically distributed, which may not capture specific oceanographic features conducive to fishing ground formation. Recent studies have shown that deep learning is a promising research direction for addressing spatiotemporal scale issues. In the era of big data, deep learning outperforms traditional methods by more accurately and efficiently mining high-value, nonlinear information. In this study, taking Ommastrephes bartramii in the Northwest Pacific as an example, we used the U-Net model with sea surface temperature (SST) as the input factor and center fishing ground as the output factor. We constructed 80 different combinations of temporal scales and asymmetric spatial scales using data in 1998–2020. By comparing the results, we found that the optimal temporal scale for the deep learning fishing ground prediction model is 15 days, and the spatial scale is 0.25° × 0.25°. Larger time scales lead to higher model accuracy, and latitude has a greater impact on the model than longitude. It further enriches and refines the criteria for selecting spatiotemporal scales. This result deepens our understanding of the oceanographic characteristics of the Northwest Pacific environmental field and lays the foundation for future artificial intelligence-based fishery research. This study provides a scientific basis for the sustainable development of efficient fishery production.

Returnable packaging systems and store operations: Processes, costs, and benefits

AbstractReturnable packaging systems (RPS) related to consumer products help to reduce problematic plastic and glass waste in supply chains. The purpose of this paper is to investigate distribution and return processes and the related cost drivers and benefits of returnable packaging with a deposit refund system in retail stores. Through the lens of the actor–network theory and based on 30 interviews with store managers, including on‐site observations, we develop a research model that structures key processes of RPS and their input and output factors. By subsequently applying system dynamics modeling, we find that: (1) customers’ process satisfaction, (2) price elasticity of demand, and (3) time between repeat purchases are key variables that impact RPS’ attractiveness and performance. This research contributes to an in‐depth understanding of processes within RPS as well as interdependencies between cost drivers and benefits for retailers. From a managerial perspective, these insights can enable retailers to take action based on the influencing factors for efficient operations related to RPS. Finally, this research has policy implications as it provides argumentation for the commercial benefits of RPS for retailers aside from the overemphasized cost perspectives.

Multi-point calorimeter using distributed fiber Bragg gratings for small field dosimetry in radiotherapy.

The interest of using fiber Bragg gratings (FBGs) dosimeters in radiotherapy (RT) lies in their (i) microliter detection volume, (ii) customizable spatial resolution, (iii) multi-point dose measurement, (iv) real-time data acquisition and (v) insensitivity to Cherenkov light. These characteristics could prove very useful for characterizing dose distributions of small and nonstandard fields with high spatialresolution. We developed a multi-point FBGs dosimeter customized for small field RT dosimetry with a spatial resolution of 1mm. The 3cm-long multi-point dosimeter is made by embedding a 80 silica fiber containing an array of thirty (30) co-located 1mm-long fs-written FBGs inside a plastic cylinder with an UV curing optical adhesive. With its higher thermal expansion coefficient, the plastic cylinder increases the sensitivity of the dosimeter by stretching the fiber containing the FBGs when the temperature rises slightly due to radiation energy deposition. Irradiations (2000MU at 600MU/min) were performed with a Varian TrueBeam linearaccelerator. The dose profile of a 2 2cm 6MV beam was measured with a mean relative difference of 1.8% (excluding the penumbra region). The measured output factors for a 6MV beam are in general agreement with the expected values within the experimental uncertainty (except for the 2 2cm field). The detector response to different energy of photon and electron beams is within 5% of the mean response ( pm/Gy). The calorimeter's post-irradiation thermal decay is in agreement with thetheory. An energy-independent small field calorimeter that allows dose profile and output factor measurements for RT using FBGs was developed, which, to our knowledge, has never been done before. This type of detector could prove really useful for small field dosimetry, but also potentially for MRI-LINAC since FBGs are insensitive to magnetic fields and for FLASH since FBGs have been used to measure doses up to100kGy.

Evaluating the input-process-output quality management model for chinese students studying in ASEAN educational institutions

Relevance. Educational institutions have increased their attention towards quality management to retain their competitiveness and remain relevant in the rapidly changing world. Several models have been proposed to guide quality management for educational institutions, but empirical evaluation of them has not been properly carried out. Purpose. The article main purpose is to assess the input-process-output (IPO) model as a one that is capable to enabling academic institutions in ASEAN countries to serve the demands of Chinese studying abroad. Methodology. A voluntary response sample of 61 Chinese students studying in ASEAN countries responded to an online closed-ended questionnaires. Results. Findings from the study revealed that input factors (p=0.14; p<0.05), process factors (p=0.00; p<0.05), and output factors (p=0.028; p<0.05) provide foundations for explaining quality management efforts by universities in the ASEAN region to satisfy the demands of students from China abroad. Conclusions. Built on the analyzed results, it was recommended that universities in the ASEAN region improve their quality management efforts by focusing on each element of the inputs, processes, and outputs to ensure they are consistent with the needs of Chinese students. Keywords: Input factors; process factors; output factors; ASEAN countries; Chinese students

A Study on the Operational Efficiency of National Supercomputer Resources Based on DEA Model

As a measure to improve the operational efficiency of the Korean supercomputer joint utilization resources, an efficiency analysis using DEA was conducted to derive the improvement level of the input and output factors of the operation plans of seven specialized centers. The factors that constitute the objective function of efficiency were identified through the operation plans submitted by the specialized centers, and DEA analyzed the improvement factors and levels of inefficient specialized centers through the CCR and BCC models, and then conducted an additional super-efficiency analysis to compare the relative efficiency levels among the efficiency groups. As a result of the analysis, the inefficiency of specialized centers in the meteorological/climate/environmental fields was identified from the reference group, and the need for improvement and the level of improvement of input and output variables were identified. In addition, the authors suggested ways to improve the establishment of resources and operational targets, such as a joint utilization ratio to secure financial efficiency at the government level in establishing a joint utilization resource.

Implementation of Data Envelopment Analysis (DEA) on Measuring the Efficiency of Gas Station Services

Along with the increasing number of transportation vehicles in Indonesia, the growth of the gas station business is also increasing from year to year. This requires companies in the oil and gas industry to improve their performance, and gas stations must have the right strategy to improve efficiency. Measurement of efficiency and productivity is one of the first steps that must be taken by a gas station operation to improve performance. This research analyzes the performance differences in each gas station with the Data Envelopment Analysis (DEA) approach, where DEA is a linear programming model based on measuring the relative efficiency of a unit using many inputs and many outputs. This study aims to identify input and output factors that affect the efficiency level of gas stations, determine the work efficiency of each gas station in carrying out the service process to consumers, and determine the improvement planning strategy for inefficient gas stations

Determination of output factor for CyberKnife using scintillation dosimetry and deep learning

Objective. Small-field dosimetry is an ongoing challenge in radiotherapy quality assurance (QA) especially for radiosurgery systems such as CyberKnifeTM. The objective of this work is to demonstrate the use of a plastic scintillator imaged with a commercial camera to measure the output factor of a CyberKnife system. The output factor describes the dose on the central axis as a function of collimator size, and is a fundamental part of CyberKnife QA and integral to the data used in the treatment planning system. Approach. A self-contained device consisting of a solid plastic scintillator and a camera was build in a portable Pelicase. Photographs were analysed using classical methods and with convolutional neural networks (CNN) to predict beam parameters which were then compared to measurements. Main results. Initial results using classical image processing to determine standard QA parameters such as percentage depth dose (PDD) were unsuccessful, with 34% of points failing to meet the Gamma criterion (which measures the distance between corresponding points and the relative difference in dose) of 2 mm/2%. However, when images were processed using a CNN trained on simulated data and a green scintillator sheet, 92% of PDD curves agreed with measurements with a microdiamond detector to within 2 mm/2% and 78% to 1%/1 mm. The mean difference between the output factors measured using this system and a microdiamond detector was 1.1%. Confidence in the results was enhanced by using the algorithm to predict the known collimator sizes from the photographs which it was able to do with an accuracy of less than 1 mm. Significance. With refinement, a full output factor curve could be measured in less than an hour, offering a new approach for rapid, convenient small-field dosimetry.

Comprehensive characterisation of the IBA myQA SRS for SRS and SBRT patient specific quality assurance.

The myQA SRS (IBA) is a new to market 2D complementary metal oxide semiconductor detector array with an active area 140 × 120mm2 and 0.4mm resolution, making it a potential real-time dosimetry alternative to radiochromic film for stereotactic plan verification. Characterisation of the device was completed to assess performance. The dosimetric properties of the device were assessed for 6FF and 6FFF beams from a Varian TrueBeam STx with high definition multileaf collimator. Clinical suitability of the device for Patient Specific Quality Assurance was verified using ten SRS/SBRT plans, compared against other detectors, as well as multi leaf collimator (MLC) tests including picket fence and chair. Gamma analysis was performed using myQA software with criteria of 4%/1mm. The device demonstrated compliance with recommended specifications for basic tests. After the required warm-up period, the maximum deviation in detector signal from initial readings was 0.2%. Short-term and long-term reproducibility was 0.1% (6FF) and 1.0% (6FFF), respectively. Dose linearity was within 0.3% (6FF) and 0.7% (6FFF) and dose-rate dependence within 1.7% (6FF) and 2.9% (6FFF) and were verified with a Farmer type ionization chamber (PTW 30013). Angular dependence was quantified for coplanar and non-coplanar situations. Output factors and beam profiles measured on the device showed agreement within 1% of baseline RAZOR diode (IBA) and CC04 ionisation chamber (IBA) measurements for field sizes 1 × 1 to 10 × 10cm2. The minimum gamma (4%/1mm) pass rates for MLC-pattern tests were 96.5% and 98.1% for the myQA SRS and film, respectively. The average gamma (4%/1mm) pass rates for SBRT and SRS plans were 98.8% and 99.8% respectively. This work represents one of the first studies performed on the commissioning and performance characterisation of this novel device, demonstrating its accuracy and reliability, making it highly useful as a film alternative in stereotactic treatment plan verification.

The effects of Foreign Investment shocks on the US economic growth and risk factors

ABSTRACT We examine the effects of shocks to Total Foreign Investment (TFI) and its components, Foreign Portfolio Investment (FPI), Foreign Direct Investment (FDI), and Bank Credit (BC) on the US economic growth and risk factors by estimating a series of Dynamic Factor Models. We extract comovements from 31 indicators to capture composite indices of output, monetary, and credit risk conditions that measure the US market conditions. We find that positive shocks to TFI, FPI, and FDI increase the real economic activity and lower the aggregate risks in the US. We also find that a shock to FPI results in the largest impacts on output and risk factors as well as their associated indicators, followed by shocks to TFI and FDI, respectively. Furthermore, we find that FPI shocks contribute the most to the historical fluctuations of output, monetary, and risk indicators.

Forefronts and hotspots evolution of the nanomaterial application in anti-tumor immunotherapy: a scientometric analysis

BackgroundTumor immunotherapy can not only eliminate the primary lesion, but also produce long-term immune memory, effectively inhibiting tumor metastasis and recurrence. However, immunotherapy also showed plenty of limitations in clinical practice. In recent years, the combination of nanomaterials and immunotherapy has brought new light for completely eliminating tumors with its fabulous anti-tumor effects and negligible side effects.MethodsThe Core Collection of Web of Science (WOSCC) was used to retrieve and obtain relevant literatures on antitumor nano-immunotherapy since the establishment of the WOSCC. Bibliometrix, VOSviewer, CiteSpace, GraphPad Prism, and Excel were adopted to perform statistical analysis and visualization. The annual output, active institutions, core journals, main authors, keywords, major countries, key documents, and impact factor of the included journals were evaluated.ResultsA total of 443 related studies were enrolled from 2004 to 2022, and the annual growth rate of articles reached an astonishing 16.85%. The leading countries in terms of number of publications were China and the United States. Journal of Controlled Release, Biomaterials, Acta Biomaterialia, Theranostics, Advanced Materials, and ACS Nano were core journals publishing high-quality literature on the latest advances in the field. Articles focused on dendritic cells and drug delivery accounted for a large percentage in this field. Key words such as regulatory T cells, tumor microenvironment, immune checkpoint blockade, drug delivery, photodynamic therapy, photothermal therapy, tumor-associated macrophages were among the hottest themes with high maturity. Dendritic cells, vaccine, and T cells tend to become the popular and emerging research topics in the future.ConclusionsThe combined treatment of nanomaterials and antitumor immunotherapy, namely antitumor nano-immunotherapy has been paid increasing attention. Antitumor nano-immunotherapy is undergoing a transition from simple to complex, from phenotype to mechanism.Graphical abstract

An Evidence-Based Blueprint for Architecting Social Capital in Organizations

The well-established concept of social capital in community studies is gaining prominence in management studies over the last decade due to evolving workplace and workforce. The paper presents a comprehensive and evidence-based model from past literature on how social capital is architected in organizations. We have adapted the seminal framework suggested by Murphy and DeNisi (2008) to capture distal, proximal, formation, and output factors. Also, our paper unveils areas of further investigation such as intervening, distortion, and psychological factors. We propose to move conversations among academicians and practitioners beyond just benefits of social capital to how one can intentionally facilitate social capital formation at the workplace for competitive advantage. Future researchers can continue to test and adjust the open model.

Efficiency of Low-Carbon Finance: Its Interrelationships with Industry and Macroeconomic Environment

AbstractThis study contributes to the literature by addressing the relevance of low-carbon finance efficiency and making significant contributions. We employ a simple weighted linear programming (LP) approach to estimate efficiency and compute entity scores with minimal optimization background, enhancing accessibility. Our study investigates interrelationships among the factors of production and outputs in estimating the efficiency of low-carbon finance, including financial index (renewable energy investment), renewable electricity output, renewable production, financial risk index, GDP, and research and development expenses, using the stochastic structural relationship programming (SSRP) model. Analyzing China, India, Brazil, and the USA, our findings show that China and the USA outperform other countries in low-carbon finance efficiency. This sheds light on comparative performance and variations across different contexts. A minimal initial overall renewable production plays an important role for the countries with lower financial indices to improve, while those with high indices should increase their focus on the energy sector. We identify a spillover effect of renewable production on financial index and financial risk index, emphasizing the positive relationship between renewable energy investments and overall financial outcomes. Integrating renewable energy initiatives into financial strategies brings potential benefits. This study significantly contributes to the literature on low-carbon finance efficiency, offering vital policy implications for sustainable finance and renewable energy sectors.

Structure optimisation of cathode parallel polar plate PEMFC based on topology optimisation

Polar plate design can directly affect the performance of the proton exchange membrane fuel cell(PEMFC). A novel topology parallel polar plate design is proposed to improve cell performance. We used the sparse nonlinear optimisation (SNOPT) algorithm to freely evolve the 2D model and obtain the output material factor distribution map. While keeping the height of the gas diffusion layer constant, the channel height is stretched proportionally to the output material factor to obtain 3D models. By analyzing the mass transfer, water management, and cell performance, the results indicate that increasing the selection range of material output factors is beneficial for the diffusion of reactive gases, reducing pressure loss, and improving cell performance. Reducing the selection range of material output factors helps increase the reaction gas flow rate and enhancing drainage performance. The optimisation model with lower limits benefits oxygen diffusion, increasing gas flow rate and pressure loss, and has little impact on drainage. Case 6 performs well in mass transfer and drainage performance, and the pressure loss is relatively small. The quantitative evaluation shows that Case 6 has an improvement of 22.2% compared to the parallel polar plate and 26.5% compared to the serpentine polar plate in cell efficiency.

Effect of Detector Orientation and Influence of Jaw Position in the Determination of Small-field Output Factor with Various Detectors for High-energy Photon Beams.

Accurate dose measurements are difficult in small fields due to charge particle disequilibrium, partial source occlusion, steep dose gradient, and the finite size of the detector. The study aims to determine the output factor using various detectors oriented in parallel and perpendicular orientations for three different tertiary collimating systems using 15 MV photon beams. In addition, this study analyzes how the output factor could be affected by different configurations of X and Y jaws above the tertiary collimators. Small field output factor measurements were carried out with three detectors for different tertiary collimating systems such as BrainLab stereotactic cones, BrainLab mMLC and Millennium MLC namely. To analyze the effect of jaw position on output factor, measurements have been carried out by positioning the jaws at the edge, 0.25, 0.5, and 1.0 cm away from the tertiary collimated field. The data acquired with 15 MV photon beams show significant differences in output factor obtained with different detectors for all collimating systems. For smaller fields when compared to microDiamond, the SRS diode underestimates the output by up to -1.7% ± 0.8% and -2.1% ± 0.3%, and the pinpoint ion chamber underestimates the output by up to -8.1% ± 1.4% and -11.9% ± 1.9% in their parallel and perpendicular orientation respectively. A large increase in output factor was observed in the small field when the jaw was moved 0.25 cm symmetrically away from the tertiary collimated field. The investigated data on the effect of jaw position inferred that the position of the X and Y jaw highly influences the output factors of the small field. It also confirms that the output factor highly depends on the configuration of X and Y jaw settings, the tertiary collimating system as well as the orientation of the detectors in small fields.

Modelling and commissioning validation of eclipse conical cone collimator for stereotactic radiosurgery using Monte Carlo simulation

Abstract Purpose: The miniaturized conical cones for stereotactic radiosurgery (SRS) make it challenging in measurement of dosimetric data needed for commissioning of treatment planning system. This study aims at validating dosimetric characteristics of conical cone collimator manufactured by Varian using Monte Carlo (MC) simulation technique. Methods & Material: Percentage depth dose (PDD), tissue maximum ratio (TMR), lateral dose profile (LDP) and output factor (OF) were measured for cones with diameters of 5mm, 7·5mm, 10mm, 12·5 mm, 15 mm and 17·5 mm using EDGE detector for 6MV flattening filter-free (FFF) beam from Truebeam linac. Similarly, MC modelling of linac for 6MVFFF beam and simulation of conical cones were performed in PRIMO. Subsequently, measured beam data were validated by comparing them with results obtained from MC simulation. Results: The measured and MC-simulated PDDs or TMRs showed close agreement within 3% except for cone of 5mm diameter. Deviations between measured and simulated PDDs or TMRs were substantially higher for 5mm cone. The maximum deviations at depth of 10cm, 20cm and at range of 50% dose were found 4·05%, 7·52%, 5·52% for PDD and 4·04%, 7·03%, 5·23% for TMR with 5mm cone, respectively. The measured LDPs acquired for all the cones showed close agreement with MC LDPs except in penumbra region around 80% and 20% dose profile. Measured and MC full-width half maxima of dose profiles agreed with nominal cone size within ± 0·2 mm. Measured and MC OFs showed excellent agreement for cone sizes ≥10 mm. However, deviation consistently increases as the size of the cone gets smaller. Findings: MC model of conical cones for SRS has been presented and validated. Very good agreement was found between experimentally measured and MC-simulated data. The dosimetry dataset obtained in this study validated using MC model may be used to benchmark beam data measured for commissioning of SRS for cone planning.

Dosimetric Evaluation of Semiflex Three-dimensional Chamber under Unflatten Beam in Comparison among Different Detectors.

The goal of this study is to investigate the dosimetric properties of a Semiflex three-dimensional (3D) chamber in an unflatten beam and compare its data from a small to a large field flattening filter-free (FFF) beam with different radiation detectors. The sensitivity, linearity, reproducibility, dose rate dependency, and energy dependence of a Semiflex 3D detector in flattening filter and filter-free beam were fully investigated. The minimum radiation observed field widths for all detectors were calculated using lateral electronic charged particle equilibrium to investigate dosimetric characteristics such as percentage depth doses (PDDs), profiles, and output factors (OPFs) for Semiflex 3D detector under 6FFF Beam. The Semiflex 3D measured data were compared to that of other detectors employed in this study. The ion chamber has a dosage linearity deviation of +1.2% for <10 MU, a dose-rate dependency deviation of +0.5%, and significantly poorer sensitivity due to its small volume. There is a difference in field sizes between manufacturer specs and derived field sizes. The measured PDD, profiles, and OPFs of the Semiflex 3D chamber were within 1% of each other for all square field sizes set under linac for the 6FFF beam. It was discovered to be an appropriate detector for relative dose measurements for 6 FFF beams with higher dose rates for field sizes more than or equal to 3 cm × 3 cm.

Investigation of emission plane control in GaInN/GaN multiple-quantum shells for efficient nanowire-based LEDs.

Significant attention has been directed toward core-shell GaInN/GaN multiple-quantum shell (MQS) nanowires (NWs) in the context of high-efficiency micro light-emitting diodes (micro-LEDs). These independent three-dimensional NWs offer the advantage of reducing the impact of sidewall etching regions. Furthermore, the emitting plane on the sidewalls demonstrates either nonpolar or semipolar orientation, while the dislocation density is exceptionally low. In this study, we assessed how changes in the NW morphology are affected by GaInN/GaN superlattice (SL) structures grown at varying growth temperatures, as well as control of the emission plane via the p-GaN shell and emission sizes. The SL growth rate was enhanced at elevated growth temperatures, accompanied by the shrinkage of the (0001)-plane and expansion of the (11̄01)-plane on the NWs. The samples exhibited a higher light output when the SLs were grown at elevated temperatures compared to those grown with lower temperatures. A similar trend was observed for the samples with a gradual temperature transition during the growth. These findings indicate that the dimensions of the (0001)-plane can be controlled through SL growth, which in turn influences the emission properties of NW-LEDs. In addition, the emission properties of NW-LEDs with different growth time p-GaN shells and different emission sizes were investigated. Based on the NW-LED characteristics, it was revealed that the weak emission of the (0001)-plane was the dominant factor for the limited light output, and the most effective way to realize high efficiency devices is to suppress current injection into the apex or minimize the grown (0001)-plane region. Overall, it is one promising way to control the emission planes of NWs, which holds significant relevance for the potential application of NW-LEDs in the realm of micro-LEDs.

Research on the Operation Optimization of Aggregate Resources under the Dual Factors of Power Grid and Economy

Under the influence of power grid and economy, the operation optimization of aggregate resources has high practical value and significance. For the problems of the existing aggregate resource operation optimization methods, this paper presents a completely new optimization method, considering the economic factors of power output, grid line transmission, grid stability, transformer capacity, energy storage charging and discharge loss, grid transmission loss, transformer loss and production arrangement of adjustable resource aggregate, and combined with the idea of electric power translation in the operation of the load device. By adopting a mixed-integer linear programming model (Mixed-Integer Linear Programming, MILP), the operation optimization problem of the aggregate resource is transformed into a mathematical planning problem to be solved, which effectively avoids the start-stop delay of the load device, and shortens the time taken to adjust power supply and demand, reduces the construction cost and operation and maintenance cost of the aggregate, and realizes the optimal allocation of electric power resources, improves the sustainable energy utilization rate and the stability of the power system, and provides a new direction for the continuous development and progress of the power system.