An improved spectral performance of SPWM inverter based on the time-sequence of chaos

A novel approach for improving the spectral performance of sinusoidal Pulse Width Modulation (SPWM) inverter is presented. By varying the carrier frequency according to chaotic time-sequence, the discrete spectrum of the output voltage is transformed into the continuous spectrum, which could reduce the acoustic noise concentrated at specific tones in an inverter-driven electric machine. Fourier analysis shows that the harmonic at the fixed frequency has been restrained effectively and the distribution of the spectrum is in a wider range. Besides, a novel variable is introduced for the evaluation of the output voltage spectrum in SPWM inverter. Simulations and experiments with DSP confirm the advantages of the novel approach. Experimental results show the annoying acoustic noise has been translated into some enjoyable sound like a fall or water flowing when this novel method is applied.

基于SPWM混合调制的光伏并网逆变实践教学装置研制

为更好达到光伏并网逆变原理教学目标,基于模拟和数字控制技术研制一台通用光伏并网逆变实践教学装置。装置集成了DC/DC、DC/AC、通信和上位机显示等单元。利用SG3525为核心的升压电路和DSP TMS320F28335为核心的逆变电路作为教学装置的通用主电路,采用正弦脉宽调制(SPWM)单、双极性混合控制策略,完成课程中直流升压、逆变等多种实验。通过教学装置的操作、训练,显著提升学生对升压开关变换电路的原理、特性以及单相SPWM逆变电路的工作原理、波形分析的理解。

CPS-SPWM级联H桥激励的变压器铁耗快速计算方法

针对载波移相(CPS)正弦脉宽调制(SPWM)级联H桥激励的变压器,提出一种基于经典损耗分离模型的铁耗快速计算方法.首先,结合SPWM电压波形特征定义集总占空比,并推导其关于调制比的解析模型;其次,基于经典损耗分离模型和集总占空比,构建CPS-SPWM级联H桥的铁耗计算模型,该方法可以直接使用调制比、直流母线电压等参数对铁耗进行计算,从而避免传统方法中的谐波分析或者数值积分过程;再次,基于本文铁耗计算模型,提出了一种针对SPWM电压激励的有限元(FEM)仿真等效方法,最后,通过实验验证了本文计算方法的有效性.研究结果表明:等效仿真铁耗误差小于3.6%、仿真用时减少74.5%;最大铁耗计算误差为7.6%.

基于SPWM的电磁流量计谐振式励磁系统研制

为了使电磁流量计长期可靠运行,需要降低励磁系统功耗并减少发热。因此,文中提出了一种基于SPWM控制的谐振式电磁流量计励磁控制方案,改变以往的恒流源驱动方式,采用高频开关电压源驱动,同时在励磁回路中串联电容来减少回路阻抗,并研制样机、开展实验验证。功耗测试结果表明:在相同励磁电流的条件下,所研制励磁系统功耗为原系统的58.3%,励磁电源功率为原系统的69.2%。水流量标定结果表明:当励磁频率为109.5 Hz时,所研制系统在水流速为0.5~5 m/s时标定精度满足0.5级要求。可见,所研制的励磁系统具有功耗低、测量精度高的特点。

Anti-aging performance improvement and enhanced combustion efficiency of boron via the coating of PDA

Boron is an ambitious fuel in energetic materials since its high heat release values,but its application is prohibited by low combustion efficiency and oxidization during storage.The polydopamine(PDA)was introduced into boron particles,investigating the impact of PDA content on the energetic behavior of boron.The results indicated that the PDA coating formed a fishing net structure on the surface of boron particles.The heat release results showed that the combustion calorific value of B@PDA was higher than that of the raw boron.Specifically,the actual combustion heat of boron powder in B@10%PDA increased by 38.08%.Meanwhile,the DSC peak temperature decreased by 100.65℃under similar oxidation rate compared to raw boron.Simultaneously,the B@PDA@AP and B@AP composites were prepared,and their combustion properties were evaluated.It was demonstrated that B@10%PDA@AP exhibited superior performance in terms of peak pressure and burning time,respectively.The peak pressure is 12.43 kPa more than B@AP and burning time is 2.22 times higher than B@AP.Therefore,the coating of PDA effectively inhibits the oxidization of boron during storage and enhances the energetic behavior of boron and corresponding composites.

Enhancing Private Healthcare Effectiveness in Lagos State, Nigeria: An Overview of the Effect of Quality Improvement Initiatives and Implications for Sustainable Healthcare Delivery

Background: Nigeria, a nation grappling with rapid population growth, economic intricacies, and complex healthcare challenges, particularly in Lagos State, the economic hub and most populous state, faces the challenge of ensuring quality healthcare access. The overview of the effect of quality improvement initiatives in this paper focuses on private healthcare providers in Lagos State, Nigeria. The study assesses the impact of donor-funded quality improvement projects on these private healthcare facilities. It explores the level of participation, perceived support, and tangible effects of the initiatives on healthcare delivery within private healthcare facilities. It also examines how these initiatives influence patient inflow and facility ratings, and bring about additional benefits and improvements, provides insights into the challenges faced by private healthcare providers in implementing quality improvement projects and elicits recommendations for improving the effectiveness of such initiatives. Methods: Qualitative research design was employed for in-depth exploration, utilizing semi-structured interviews. Private healthcare providers in Lagos involved in the SP4FP Quality Improvement Project were purposively sampled for diversity. Face-to-face interviews elicited insights into participation, perceived support, and project effects. Questions covered participation levels, support perception, changes observed, challenges faced, and recommendations. Thematic analysis identified recurring themes from interview transcripts. Adherence to ethical guidelines ensured participant confidentiality and informed consent. Results: Respondents affirmed active involvement in the SP4FP Quality Improvement Project, echoing literature emphasizing private-sector collaboration with the public sector. While acknowledging positive influences on facility ratings, respondents highlighted challenges within the broader Nigerian healthcare landscape affecting patient numbers. Respondents cited tangible improvements, particularly in staff management and patient care processes, validating the positive influence of quality improvement projects. Financial constraints emerged as a significant challenge, aligning with existing literature emphasizing the pragmatic difficulties faced by private healthcare providers. Conclusions: This study illuminates the complex landscape of private healthcare provision in Lagos State, emphasizing the positive impact of donor-funded quality improvement projects. The findings provide nuanced insights, guiding policymakers, healthcare managers, and practitioners toward collaborative, sustainable improvements. As Nigeria progresses, these lessons will be crucial in shaping healthcare policies prioritizing population well-being.

Selection criteria of MPOB-Angola germplasm collection for yield improvement of the oil palm

Oil palm germplasm collected from Angola,Africa in 1991 were subjected to genetic variability potential studies.The collection was planted in the form of open-pollinated families as trials at the Malaysian Palm Oil Board(MPOB)Kluang Research Station,Johor,Malaysia,in 1994.Dura palms from 52 families and tenera palms from 44 families of MPOB-Angola were evaluated for their bunch yield and bunch quality components.The objectives of this study were to determine the genetic variability among the families and performance of MPOB-Angola germplasm for yield improvement.The analysis of variance(ANOVA)revealed highly significant differences between the dura and tenera families for most of the traits,suggesting the presence of high genetic variability,which is essential for breeding programmes.Among the duras,family AGO 02.02 displayed the best yield performance,with a high fresh fruit bunch,oil yield and total economic product at 240.40,29.46 and 37.93 kg palm^(-1)year^(-1),respectively.As for the teneras,family AGO 03.04 recorded the highest FFB yield and oil yield at 249.25 and 45.22 kg palm^(-1)year^(-1),respectively.Besides that,several families with big fruit sizes or producing a mean fruit weight of 14-17 g were also identified.Both dura and tenera from AGO 01.01 recorded the highest oil to bunch(O/B)of 17.76%and 28.65%,respectively.These findings will facilitate the selection of palms from the MPOB-Angola germplasm for future breeding programmes.

Integrating artificial intelligence and high-throughput phenotyping for crop improvement

Crop improvement is crucial for addressing the global challenges of food security and sustainable agriculture.Recent advancements in high-throughput phenotyping(HTP)technologies and artificial intelligence(AI)have revolutionized the field,enabling rapid and accurate assessment of crop traits on a large scale.The integration of AI and machine learning algorithms with HTP data has unlocked new opportunities for crop improvement.AI algorithms can analyze and interpret large datasets,and extract meaningful patterns and correlations between phenotypic traits and genetic factors.These technologies have the potential to revolutionize plant breeding programs by providing breeders with efficient and accurate tools for trait selection,thereby reducing the time and cost required for variety development.However,further research and collaboration are needed to overcome the existing challenges and fully unlock the power of HTP and AI in crop improvement.By leveraging AI algorithms,researchers can efficiently analyze phenotypic data,uncover complex patterns,and establish predictive models that enable precise trait selection and crop breeding.The aim of this review is to explore the transformative potential of integrating HTP and AI in crop improvement.This review will encompass an in-depth analysis of recent advances and applications,highlighting the numerous benefits and challenges associated with HTP and AI.

Data-driven diagnosis of high temperature PEM fuel cells based on the electrochemical impedance spectroscopy: Robustness improvement and evaluation

Utilizing machine learning techniques for data-driven diagnosis of high temperature PEM fuel cells is beneficial and meaningful to the system durability. Nevertheless, ensuring the robustness of diagnosis remains a critical and challenging task in real application. To enhance the robustness of diagnosis and achieve a more thorough evaluation of diagnostic performance, a robust diagnostic procedure based on electrochemical impedance spectroscopy (EIS) and a new method for evaluation of the diagnosis robustness was proposed and investigated in this work. To improve the diagnosis robustness: (1) the degradation mechanism of different faults in the high temperature PEM fuel cell was first analyzed via the distribution of relaxation time of EIS to determine the equivalent circuit model (ECM) with better interpretability, simplicity and accuracy;(2) the feature extraction was implemented on the identified parameters of the ECM and extra attention was paid to distinguishing between the long-term normal degradation and other faults;(3) a Siamese Network was adopted to get features with higher robustness in a new embedding. The diagnosis was conducted using 6 classic classification algorithms—support vector machine (SVM), K-nearest neighbor (KNN), logistic regression (LR), decision tree (DT), random forest (RF), and Naive Bayes employing a dataset comprising a total of 1935 collected EIS. To evaluate the robustness of trained models: (1) different levels of errors were added to the features for performance evaluation;(2) a robustness coefficient (Roubust_C) was defined for a quantified and explicit evaluation of the diagnosis robustness. The diagnostic models employing the proposed feature extraction method can not only achieve the higher performance of around 100% but also higher robustness for diagnosis models. Despite the initial performance being similar, the KNN demonstrated a superior robustness after feature selection and re-embedding by triplet-loss method, which suggests the necessity of robustness evaluation for the machine learning models and the effectiveness of the defined robustness coefficient. This work hopes to give new insights to the robust diagnosis of high temperature PEM fuel cells and more comprehensive performance evaluation of the data-driven method for diagnostic application.

Research on Evacuation Path Planning Based on Improved Sparrow Search Algorithm

Reducing casualties and property losses through effective evacuation route planning has been a key focus for researchers in recent years.As part of this effort,an enhanced sparrow search algorithm(MSSA)was proposed.Firstly,the Golden Sine algorithm and a nonlinear weight factor optimization strategy were added in the discoverer position update stage of the SSA algorithm.Secondly,the Cauchy-Gaussian perturbation was applied to the optimal position of the SSA algorithm to improve its ability to jump out of local optima.Finally,the local search mechanism based on the mountain climbing method was incorporated into the local search stage of the SSA algorithm,improving its local search ability.To evaluate the effectiveness of the proposed algorithm,the Whale Algorithm,Gray Wolf Algorithm,Improved Gray Wolf Algorithm,Sparrow Search Algorithm,and MSSA Algorithm were employed to solve various test functions.The accuracy and convergence speed of each algorithm were then compared and analyzed.The results indicate that the MSSA algorithm has superior solving ability and stability compared to other algorithms.To further validate the enhanced algorithm’s capabilities for path planning,evacuation experiments were conducted using different maps featuring various obstacle types.Additionally,a multi-exit evacuation scenario was constructed according to the actual building environment of a teaching building.Both the sparrow search algorithm and MSSA algorithm were employed in the simulation experiment for multiexit evacuation path planning.The findings demonstrate that the MSSA algorithm outperforms the comparison algorithm,showcasing its greater advantages and higher application potential.

Effects of Microbial Fertilizers on Soil Improvement and Wheat Growth Characteristics in Saline-alkali Land

[Objectives]This study was conducted to further enrich the research on saline-alkali land improvement,and explore the effects of biological bacterial fertilizers containing Bacillus subtilis and Bacillus velezensis HM-3 in saline-alkali land improvement and crop growth promotion.[Methods]Wheat was planted in saline-alkali land in Huanghua City,Hebei Province,and a mixed application experiment was carried out using biological agents from Hemiao Biotechnology Co.,Ltd.[Results]Compared with the field of control check(CK),water-soluble salts and pH value in the experimental fields decreased,and living bacteria count in the soil increased.Meanwhile,the economic characters of wheat in the experimental fields showed excellent performance,with yields increasing by 39.09%and 27.49%compared with the CK.It could be seen that the application of biological bacterial fertilizers achieved obvious effects of improving saline-alkali soil and increasing wheat yield.[Conclusions]In this study,the effects of biological bacterial fertilizers on saline-alkali land and wheat growth characters were clarified,providing some technical support and theoretical guidance for wheat planting in Huanghua saline-alkali land.

In situ digital testing method for quality assessment of soft soil improvement with polyurethane

This study purposes an in situ testing method on quality assessment of soil improvement.Factual drilling data includes the spatial distribution and in situ strength of untreated and treated soil along three different drillholes measured by on-site drilling monitoring method.These factual drilling data can characterize the degree of soil improvement by penetration injection with permeable polyurethane.Result from on-site drilling monitoring shows that the linear zones represent constant drilling speeds shown in the plot of drill bit advancement vs.net drilling time,which indicates the spatial distributions of soil profile.The soil profile at the study site is composed of four layers,which includes fill,untreated silty clay,treated silty clay,and mucky soil.The results of soil profile are verified by the parallel site loggings.The constant drilling speeds profile the coring-resistant strength of drilled soils.By comparing with the untreated silty clay,the constant drilling speeds of the treated silty clay have been decreased by 13.0-62.8%.Two drilling-speed-based indices of 61.2%and 65.6%are proposed to assess the decreased average drilling speed and the increased in situ strength of treated silty clay.Laboratory tests,i.e.uniaxial compressive strength(UCS)test,have been performed with core sample to investigate and characterize in situ strength by comparing that with drilling speeds.Results show that the average predicted strengths of treated silty clay are 2.4-6.9 times higher than the average measured strength of untreated silty clay.The UCS-based indices of 374.5%and 344.2%verified the quality assessment(QA)results by this new in situ method.This method provides a cost-effective tool for quality assessment of soil improvement by utilizing the digital drilling data.

Post-operative morbidity after neoadjuvant chemotherapy and resection for gallbladder cancer: A national surgical quality improvement program analysis

BACKGROUND Gallbladder cancer is the most common malignancy of the biliary tract.Neo-adjuvant chemotherapy(NACT)has improved overall survival by enabling R0 resection.Currently,there is no consensus of guidelines for neoadjuvant therapy in gallbladder cancer.As investigations continue to analyze the regimen and benefit of NACT for ongoing care of gallbladder cancer patients,we examined American College of Surgeons National Surgical Quality Improvement Program(NSQIP)database to determine if there was higher morbidity among the neo-adjuvant group within the 30-day post-operative period.We hypothesized patients who underwent NACT were more likely to have higher post-operative morbidity.AIM To investigate the 30-day post-operative morbidity outcomes between patients who received NACT and underwent surgery and patients who only had surgery.METHODS A retrospective analysis of the targeted hepatectomy NSQIP data between 2015 and 2019 was performed to determine if NACT in gallbladder cancer increased the risk for post-operative morbidity(bile leak,infection rate,rate of converting to open surgery,etc.)compared to the group who only had surgery.To calculate the odds ratio for the primary and secondary outcomes,a crude logistic regression was performed.RESULTS Of the 452 patients,52 patients received NACT prior to surgery.There were no statistically significant differences in the odds of morbidity between the two groups,including bile leak[odds ratio(OR),0.69;95%confidence interval(95%CI):0.16-2.10;P=0.55],superficial wound infection(OR,0.58;95%CI:0.03-3.02;P=0.61),and organ space wound infection(OR,0.63;95%CI:0.18-1.63;P=0.61).CONCLUSION There was no significant difference in the risk of 30-day post-operative morbidity between the NACT and surgery group and the surgery only group.

基于SPWM的通信电源蓄电池组并联供电控制设计

为提升整个电源系统的稳定性,提出基于正弦脉冲宽度调制(Sinusoidal Pulse Width Modulation,SPWM)的通信电源蓄电池组并联供电控制设计研究。该设计先采用单极性倍频SPWM调制技术,有效调节电源系统的等效开关频率,并结合含有正弦量的整流器模块,设计并联蓄电池开环中的传递函数,确定整流侧的电流参数输入值,实现并联供电控制。测试结果表明,应用所提方法,即使在电源系统负荷发生显著变化的情况下,电池组间的供电差值始终被控制在40.0 W以内,应用效果较好。

Quieting the neonatal intensive care unit:A quality improvement initiative

BACKGROUND The neonatal intensive care unit(NICU)is vital for preterm infants but is often plagued by harmful noise levels.Excessive noise,ranging from medical equipment to conversations,poses significant health risks,including hearing impairment and neurodevelopmental issues.The American Academy of Pediatrics recommends strict sound limits to safeguard neonatal well-being.Strategies such as education,environmental modifications,and quiet hours have shown to reduce noise levels.However,up to 60%of the noises remain avoidable.High noise exposure exacerbates physiological disturbances,impacting vital functions and long-term neurological outcomes.Effective noise reduction in the NICU is crucial for promoting optimal neonatal development.AIM To measure the sound levels in a NICU and reduce ambient sound levels by at least 10%from baseline.METHODS A quasi-experimental quality improvement project was conducted over 4 mo in a 20-bed level 3 NICU in a tertiary care medical college.Baseline noise levels were recorded continuously using a sound level meter.The interventions included targeted education,environmental modifications,and organizational changes,and were implemented through three rapid Plan-Do-Study-Act(PDSA)cycles.Weekly feedback and monitoring were conducted,and statistical process control charts were used for analysis.The mean noise values were compared using the paired t-test.RESULTS The baseline mean ambient noise level in the NICU was 67.8 dB,which decreased to 50.5 dB after the first cycle,and further decreased to 47.4 dB and 51.2 dB after subsequent cycles.The reduction in noise levels was 21%during the day and 28%PDSA cycle(mean difference of−17.3 dB,P<0.01).Peak noise levels decreased from 110 dB to 88.24 dB after the intervention.CONCLUSION A multifaceted intervention strategy reduced noise in the NICU by 25%over 4 months.The success of this initiative emphasizes the significance of comprehensive interventions for noise reduction.

High rate of clinically relevant improvement following anatomical total shoulder arthroplasty for glenohumeral osteoarthritis

BACKGROUND The minimal clinically important difference(MCID)is defined as the smallest meaningful change in a health domain that a patient would identify as important.Thus,an improvement that exceeds the MCID can be used to define a successful treatment for the individual patient.AIM To quantify the rate of clinical improvement following anatomical total shoulder arthroplasty for glenohumeral osteoarthritis.METHODS Patients were treated with the Global Unite total shoulder platform arthroplasty between March 2017 and February 2019 at Herlev and Gentofte Hospital,Denmark.The patients were evaluated preoperatively and 3 months,6 months,12 months,and 24 months postoperatively using the Western Ontario Osteoarthritis of the Shoulder index(WOOS),Oxford Shoulder Score(OSS)and Constant-Murley Score(CMS).The rate of clinically relevant improvement was defined as the proportion of patients who had an improvement 24 months postoperatively that exceeded the MCID.Based on previous literature,MCID for WOOS,OSS,and CMS were defined as 12.3,4.3,and 12.8 respectively.RESULTS Forty-nine patients with a Global Unite total shoulder platform arthroplasty were included for the final analysis.Mean age at the time of surgery was 66 years(range 49.0-79.0,SD:8.3)and 65%were women.One patient was revised within the two years follow-up.The mean improvement from the preoperative assessment to the two-year follow-up was 46.1 points[95%confidence interval(95%CI):39.7-53.3,P<0.005]for WOOS,18.2 points(95%CI:15.5-21.0,P<0.005)for OSS and 37.8 points(95%CI:31.5-44.0,P<0.005)for CMS.Two years postoperatively,41 patients(87%)had an improvement in WOOS that exceeded the MCID,45 patients(94%)had an improvement in OSS that exceeded the MCID,and 42 patients(88%)had an improvement in CMS that exceeded the MCID.CONCLUSION Based on three shoulder-specific outcome measures we find that approximately 90%of patients has a clinically relevant improvement.This is a clear message when informing patients about their prognosis.

An Overview of Soil Improvement through Ground Grouting

Soil is an essential component of what surrounds us in nature, providing as the basis for our infrastructure and construction. However, soil is not always suitable for construction due to a variety of geotechnical issues such as inadequate bearing capacity, excessive settlement, and liquefaction susceptibility. Through improving the engineering qualities of soil, such as strength, permeability, and stability, ground grouting is a specific geotechnical method used. Using a fluid grout mixture injected into the subsurface, holes are filled and weak or loose strata are solidified as the material seeps into the soil matrix. The approach’s adaptability in addressing soil-related issues has made it more well-known in the fields of civil engineering and construction. In the end, this has improved groundwater management, foundation support, and overall geotechnical performance.

Artificial-intelligent-powered safety and efficiency improvement for controlling and scheduling in integrated railway systems

The multi-mode integrated railway system,anchored by the high-speed railway,caters to the diverse travel requirements both within and between cities,offering safe,comfortable,punctual,and eco-friendly transportation services.With the expansion of the railway networks,enhancing the efficiency and safety of the comprehensive system has become a crucial issue in the advanced development of railway transportation.In light of the prevailing application of artificial intelligence technologies within railway systems,this study leverages large model technology characterized by robust learning capabilities,efficient associative abilities,and linkage analysis to propose an Artificial-intelligent(AI)-powered railway control and dispatching system.This system is elaborately designed with four core functions,including global optimum unattended dispatching,synergetic transportation in multiple modes,high-speed automatic control,and precise maintenance decision and execution.The deployment pathway and essential tasks of the system are further delineated,alongside the challenges and obstacles encountered.The AI-powered system promises a significant enhancement in the operational efficiency and safety of the composite railway system,ensuring a more effective alignment between transportation services and passenger demands.

Discussion on the Status Quo of Vocational College Students’Self-Image and its Improvement Strategies

An individual’s self-image is a multi-dimensional and multi-structural concept.Its internal dimensions include ability,knowledge,values,personality,and temperament,and its external dimensions are physical appearance,behavior,and clothing.A good image will have a positive impact both in life and at work.We will choose appropriate clothing and makeup to modify the external image and cultivate positive qualities such as correct values and an optimistic attitude towards life to enhance internal dimensions.Among them,“personality”and“ability”mostly belong to the research category of mental health education,and“values”fit in the research field of ideological and political education.Ideological and political education and mental health education are both important components of higher education,which show similarities between them.Ideological and political education and mental health education can complement each other in many ways to enhance students’self-image.

Analysis of the Ideological and Political Concepts and Teaching Strategies for Quality Improvement in Physical Education Courses in Colleges and Universities

In today’s higher education system,the physical education program is not only for teaching sports skills and exercising physical fitness but also an important position for cultivating students’character,emotions,and values.With the in-depth development of the concept of ideological education,the ideology of college physical education courses has become an important direction of educational reform.In this paper,we will discuss the connotation of the concept of ideology and politics in college physical education courses,analyze the methods to effectively integrate the ideology and politics elements while guaranteeing the quality of teaching,and put forward the corresponding strategies to improve the quality,with a view to providing new ideas and methods for the construction of ideology and politics in college physical education courses.