BEACON SYNCHRONIZATION TECHNOLOGY FOR “BEIDOU” TERRESTRIAL IMPROVEMENT SYSTEM

Synchronization is an essential technology in the radio navigation system. The technique for improving the “Beidou” positioning ability is presented through constituting the terrestrial improvement system, and the beacon synchronization of the improvement system with the “Beidou” one-way time transfer model is realized.The direct digital synthesis (DDS) is adopted to generate the pseudo-random code clock having high precision and stability. Meanwhile, the CPLD device is used to design the synchronization pulse picking-up module, the spread spectrum PN code generator and the spread spectrum modulator. Measurement results indicate that the beacon synchronization has the high precision and the stability.

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.

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.

Deterioration Reason and Improvement Measure of the Retarding Effect of Protein Retarder on Phosphorus Building Gypsum

The retarding effect of protein retarder on phosphorus building gypsum(PBG)and desulfurization building gypsum(DBG)was investigated,and the results show that protein retarder for DBG can effectively prolong the setting time and displays a better retarding effect,but for PBG shows a poor retarding effect.Furthermore,the deterioration reason of the retarding effect of protein retarder on PBG was investigated by measuring the pH value and the retarder concentration of the liquid phase from vacuum filtration of PBG slurry at different hydration time,and the measure to improve the retarding effect of protein retarding on PBG was suggested.The pH value of PBG slurry(<5.0)is lower than that of DBG slurry(7.8-8.5).After hydration for 5 min,the concentration of retarder in liquid phase of DBG slurry gradually decreases,but in liquid phase of PBG slurry continually increases,which results in the worse retarding effect of protein retarder on PBG.The liquid phase pH value of PBG slurry can be adjusted higher by sodium silicate,which is beneficial to improvement in the retarding effect of the retarder.By adding 1.0%of sodium silicate,the initial setting time of PBG was efficiently prolonged from 17 to 210 min,but little effect on the absolute dry flexural strength was observed.

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.

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.

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.

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.

Introduction of Western Medicines into China and Improvement on Decoctions during Modern China

During the late Qing dynasty(1840 A.D.-1912 A.D.),a large quantity of Western medicines entered China,which continuously impacted the traditional Chinese medicine(TCM)market and revealed the shortcomings of Chinese medicines.Some personages in the TCM community followed the trend of learning from the West,and attempted to reform TCM,with the improvement on decoction becoming an important aspect of this effort.Through debates and trials,the improvement on decoction underwent three stages of conceptual evolution:“taking Chinese medicines as the foundation and referring to the dosage forms of Western medicines”,“introducing Western techniques to serve the preparation of decoctions”and“integrating the theories of TCM and Western medicine to improve decoctions”.The study highlights the effective complementarity between modern TCM and Western medicine in the field of pharmacy,and provides valuable experience and support for the reevaluation of the value of TCM in contemporary society.

Accountable capability improvement based on interpretable capability evaluation using belief rule base

A new approach is proposed in this study for accountable capability improvement based on interpretable capability evaluation using the belief rule base(BRB).Firstly,a capability evaluation model is constructed and optimized.Then,the key sub-capabilities are identified by quantitatively calculating the contributions made by each sub-capability to the overall capability.Finally,the overall capability is improved by optimizing the identified key sub-capabilities.The theoretical contributions of the proposed approach are as follows.(i)An interpretable capability evaluation model is constructed by employing BRB which can provide complete access to decision-makers.(ii)Key sub-capabilities are identified according to the quantitative contribution analysis results.(iii)Accountable capability improvement is carried out by only optimizing the identified key sub-capabilities.Case study results show that“Surveillance”,“Positioning”,and“Identification”are identified as key sub-capabilities with a summed contribution of 75.55%in an analytical and deducible fashion based on the interpretable capability evaluation model.As a result,the overall capability is improved by optimizing only the identified key sub-capabilities.The overall capability can be greatly improved from 59.20%to 81.80%with a minimum cost of 397.Furthermore,this paper also investigates how optimizing the BRB with more collected data would affect the evaluation results:only optimizing“Surveillance”and“Positioning”can also improve the overall capability to 81.34%with a cost of 370,which thus validates the efficiency of the proposed approach.

System error iterative identification for underwater positioning based on spectral clustering

The observation error model of the underwater acous-tic positioning system is an important factor to influence the positioning accuracy of the underwater target.For the position inconsistency error caused by considering the underwater tar-get as a mass point,as well as the observation system error,the traditional error model best estimation trajectory(EMBET)with little observed data and too many parameters can lead to the ill-condition of the parameter model.In this paper,a multi-station fusion system error model based on the optimal polynomial con-straint is constructed,and the corresponding observation sys-tem error identification based on improved spectral clustering is designed.Firstly,the reduced parameter unified modeling for the underwater target position parameters and the system error is achieved through the polynomial optimization.Then a multi-sta-tion non-oriented graph network is established,which can address the problem of the inaccurate identification for the sys-tem errors.Moreover,the similarity matrix of the spectral cluster-ing is improved,and the iterative identification for the system errors based on the improved spectral clustering is proposed.Finally,the comprehensive measured data of long baseline lake test and sea test show that the proposed method can accu-rately identify the system errors,and moreover can improve the positioning accuracy for the underwater target positioning.

Image encryption algorithm based on multiple chaotic systems and improved Joseph block scrambling

With the rapid development of digital information technology,images are increasingly used in various fields.To ensure the security of image data,prevent unauthorized tampering and leakage,maintain personal privacy,and protect intellectual property rights,this study proposes an innovative color image encryption algorithm.Initially,the Mersenne Twister algorithm is utilized to generate high-quality pseudo-random numbers,establishing a robust basis for subsequent operations.Subsequently,two distinct chaotic systems,the autonomous non-Hamiltonian chaotic system and the tentlogistic-cosine chaotic mapping,are employed to produce chaotic random sequences.These chaotic sequences are used to control the encoding and decoding process of the DNA,effectively scrambling the image pixels.Furthermore,the complexity of the encryption process is enhanced through improved Joseph block scrambling.Thorough experimental verification,research,and analysis,the average value of the information entropy test data reaches as high as 7.999.Additionally,the average value of the number of pixels change rate(NPCR)test data is 99.6101%,which closely approaches the ideal value of 99.6094%.This algorithm not only guarantees image quality but also substantially raises the difficulty of decryption.

Development of a Novel Noise Reduction Algorithm for Smart Checkout RFID System in Retail Stores

This paper presents a smart checkout system designed to mitigate the issues of noise and errors present in the existing barcode and RFID-based systems used at retail stores’checkout counters.This is achieved by integrating a novel AI algorithm,called Improved Laser Simulator Logic(ILSL)into the RFID system.The enhanced RFID system was able to improve the accuracy of item identification,reduce noise interference,and streamline the overall checkout process.The potential of the systemfor noise detection and elimination was initially investigated through a simulation study usingMATLAB and ILSL algorithm.Subsequently,it was deployed in a small-scale environment to validate its real-world performance.Results show that RFID with the proposed new algorithm ILSL and AI basket is capable of accurately detecting the related itemswhile eliminating noise originating fromunrelated objects,achieving an accuracy rate of 88%.

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.

Improvement of hepatic fibrosis after tenofovir disoproxil fumarate switching to tenofovir alafenamide for three years

BACKGROUND Both tenofovir alafenamide(TAF)and tenofovir disoproxil fumarate(TDF)are the first-line treatments for chronic hepatitis B(CHB).We have showed switching from TDF to TAF for 96 weeks resulted in further alanine aminotransferase(ALT)improvement,but data remain lacking on the long-term benefits of TDF switching to TAF on hepatic fibrosis.AIM To assess the benefits of TDF switching to TAF for 3 years on ALT,aspartate aminotransferase(AST),and hepatic fibrosis improvement in patients with CHB.METHODS A single center retrospective study on 53 patients with CHB who were initially treated with TDF,then switched to TAF to determine dynamic patterns of ALT,AST,AST to platelet ratio index(APRI),fibrosis-4(FIB-4)scores,and shear wave elastography(SWE)reading improvement at switching week 144,and the associated factors.RESULTS The mean age was 55(28-80);45.3%,males;15.1%,clinical cirrhosis;mean baseline ALT,24.8;AST,25.7 U/L;APRI,0.37;and FIB-4,1.66.After 144 weeks TDF switching to TAF,mean ALT and AST were reduced to 19.7 and 21,respectively.From baseline to switching week 144,the rates of ALT and AST<35(male)/25(female)and<30(male)/19(female)were persistently increased;hepatic fibrosis was also improved by APRI<0.5,from 79.2%to 96.2%;FIB-4<1.45,from 52.8%to 58.5%,respectively;mean APRI was reduced to 0.27;FIB-4,to 1.38;and mean SWE reading,from 7.05 to 6.30 kPa after a mean of 109 weeks switching.The renal function was stable and the frequency of patients with glomerular filtration rate>60 mL/min was increased from 86.5%at baseline to 88.2%at switching week 144.CONCLUSION Our data confirmed that switching from TDF to TAF for 3 years results in not only persistent ALT/AST improvement,but also hepatic fibrosis improvement by APRI,FIB-4 scores,as well as SWE reading,the important clinical benefits of long-term hepatitis B virus antiviral treatment with TAF.

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.

Research on Soil Conservation and Improvement Technology in Zhaoyang District

The environment of tobacco-growing soil directly affects the yield and quality of tobacco leaves.In order to solve problems of tobacco-growing soil degradation,low organic matter content and unbalanced soil nutrient supply and promote sustainable and healthy development of tobacco production,this paper comprehensively discussed conservation and improvement techniques of tobacco-growing soil based on existing problems in Zhaoyang District,aiming to provide reference for tobacco-growing soil conservation.

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.

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.

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.