Knowledge and practices of primary care physicians on the current referral system of diabetic retinopathy in Islamabad and Rawal-Pindi, Pakistan

AIM: To assess the current knowledge and practices in diabetic eye care and referral system regarding diabetic retinopathy(DR) in health centers of Islamabad and RawalPindi. METHODS: A cross-sectional study was carried out in 4 government and private health centers in RawalpindiIslamabad from May 2018 to Oct. 2018. A total of 38 Primary Care Physicians(general practitioners, family physicians, and internists) were recruited out of which data for 2 were either not returned, or were missing partially. Data were collected through a 27-item consented & validated, multiple-choice questionnaire based on physician characteristics, knowledge and practice of diabetic eye care and challenges faced due current DR referral system. Descriptive analyses for all variables were performed including, mean and standard deviation. Analytical analyses were also conducted to study association between different study variables. RESULTS: Mean scores of knowledge for general practitioners, family physicians, and internists were 41.7%, 42.0% and 46.6% respectively. A lack of knowledge, and suboptimal practices were observed regarding signs, symptoms, screening, testing, evaluation and referral of DR regardless of physicians’ specialty, or years in practice. Lack of expertise regarding direct ophthalmoscopy, interpretation of findings, and referral to an ophthalmologist were noted. Physicians who performed consultation and counselling according to patients’ needs referred more patients to an ophthalmologist than those who restricted their consultationto a fixed amount of time and had more patients per unit time(P=0.01). Physicians who had taken care of less than 5 number of patients with DR marked less incorrect answers with no significantly greater number or correct answers compared to physicians who had taken care of more than 5 number of patients with DR(P=0.044). An association of more than 5 patients with DR taken care of with more need based patient consultation and counselling was also noted(P=0.017). An evaluation of the current referral system for DR revealed major loopholes in the health care infrastructure, proper guidelines, properly functioning equipment, check and balances, and lack of guidance to physicians regarding acquiring and updating knowledge regarding DR. CONCLUSION: Lack of updated and adequate knowledge, practices among primary care physicians, and suboptimal diabetic eye care and referral system have contributed to late presentation of DR. Interventions are needed to improve current diabetic eye care, and knowledge and practices of primary care physicians.

Roadside dust contamination with toxic metals along industrial area in Islamabad, Pakistan

An investigation has been carried out to understand the contamination characteristics of roadside dust in the industrial area of Islamabad, Pakistan. The amounts of Si, S, Cl, K, Ca, Sc, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Pb,Zn, Ga, As, Se and Cd were determined from 95 roadside dust samples collected along the Islamabad industrial area using Proton Induced X-ray Emission(PIXE). The results indicated that concentrations of all elements,except Cd, in the roadside dust were significant. The results of the enrichment factor show that the elementary composition of the roadside dust could be categorized as soil elements from the crust of the earth and elements from anthropogenic pollution. The high enrichment factors imply that elements such Cr, Cu, Pb, Zn, As, Se,Cd, Ni, Co and S came from anthropogenic activities. The source of metal contamination was identified using multivariate statistical analysis. It has been concluded that Ca, Sc, Ti, V, Mn and Fe mainly originate from crustal sources; Cr, Cu, Ni, Pb, Zn and Ga are associated with point-sources from industrial pollution/traffic;and S, Cl, K, As and Se are mainly related to oil/coal combustion.

Assessment of perception of healthcare professionals regarding the use of herbal medicines in Islamabad, Pakistan: A cross-sectional study

Background The usage of herbal medicine for health care has gradually expanded because of its safety,effectiveness,cultural acceptance,and lack of negative effects in recent years all around the world.Plants and plant products have been used to heal and prevent illnesses with varying degrees of effectiveness throughout history.The main objective of the study is to evaluate the perception of healthcare professionals about the use of herbal medicines.Methods The study was conducted using a cross-sectional study design.The sample size was 382 participants;however,7 questionnaires were excluded because of invalid data.The 375 questionnaires were included by expert validation from which 77 were General Physicians,75 Pharmacists,74 Nutritionists,74 Nurses and 75 Herbalists.The study settings were hospitals,pharmacies&clinics of Islamabad.The data were analyzed using Chi-square test.Results Out of 375 respondents,54.7%(n=205)were males and 45.3%(n=170)were females.The majority of the respondents used internet 50.9%(n=191)as a source of information while 77.9%of participants consider that herbal medicines are safe because they are natural.Conclusion There was a significant difference seen in the perception of healthcare professionals regarding use of herbal medicines based on demographics.

巴基斯坦新特提斯构造–岩浆演化与重要金属成矿作用

巴基斯坦在大地构造位置上处于印度、欧亚和阿拉伯三大板块的汇聚带,正同时发生着大陆碰撞和大洋俯冲作用,是研究地球系统深部圈层相互作用与成矿效应的绝佳天然实验室。但是,目前对于巴基斯坦构造演化与成矿作用的研究还不系统,对于巴基斯坦的大型–超大型矿床形成的背景和机制仍不清楚。笔者针对巴基斯坦不同类型的优势矿种开展了深入解剖和对比研究,系统梳理最新研究进展,围绕巴基斯坦新特提斯构造–岩浆演化与成矿作用响应的关键科学问题,分析铜矿、铬铁矿、铅锌矿以及碳酸岩有关的稀土矿床等重要金属成矿类型形成的构造环境以及与区域重大地质事件的耦合关系,总结巴基斯坦区域成矿规律,为资源潜力分析和境内外找矿勘查提供依据。

基于时空融合算法的水体叶绿素a反演研究

为了准确反演水体中叶绿素a浓度,以黄柏河东支流域为例,采用STNLFFM时空融合算法,对2017年GF-4和Sentinel-2反射率数据进行融合,以重构Sentinel-2影像的时间序列数据,并对应用算法前后获取的水质参数-光谱特征响应关系建立多元线性回归模型,比较模型对叶绿素a的预测效果以验证时空融合算法的可行性,利用重构后影像光谱特征与水质参数的响应关系建立人工神经网络模型,反演2017年黄柏河东支流域各水库水体叶绿素a浓度。结果表明:利用时空融合算法生成的影像接近真实影像,提高了多元线性回归模型预测叶绿素a的效果,R2从融合前0.659提高至融合后0.844,且基于时空融合算法获取的水质参数-光谱关系建立的人工神经网络模型模拟精度较好,R2和MRE达到0.925和9.461%,反演的叶绿素a浓度空间差异性明显。证明了时空融合算法在水质参数反演过程中具有较好的应用前景。

Construction of a Computational Scheme for the Fuzzy HIV/AIDS Epidemic Model with a Nonlinear Saturated Incidence Rate

This work aimed to construct an epidemic model with fuzzy parameters.Since the classical epidemic model doesnot elaborate on the successful interaction of susceptible and infective people,the constructed fuzzy epidemicmodel discusses the more detailed versions of the interactions between infective and susceptible people.Thenext-generation matrix approach is employed to find the reproduction number of a deterministic model.Thesensitivity analysis and local stability analysis of the systemare also provided.For solving the fuzzy epidemic model,a numerical scheme is constructed which consists of three time levels.The numerical scheme has an advantage overthe existing forward Euler scheme for determining the conditions of getting the positive solution.The establishedscheme also has an advantage over existing non-standard finite difference methods in terms of order of accuracy.The stability of the scheme for the considered fuzzy model is also provided.From the plotted results,it can beobserved that susceptible people decay by rising interaction parameters.

基于纳米金修饰碳纤维微电极的电化学法测定黄芩素

利用柠檬酸三钠还原氯金酸的方法制得小粒径的纳米金颗粒(AuNPs),采用电化学沉积法将其修饰在碳纤维电极(CFME)表面,基于电化学法构建了一种灵敏度高、抗干扰性良好的测定黄芩素的微型电化学传感器.采用透射电镜、紫外分光光度法、扫描电镜等对电极及修饰材料进行表征,运用差分脉冲法、循环伏安法、电化学阻抗谱法考查了黄芩素在电极修饰前后的电化学性质,并优化了扫速、缓冲液pH、电沉积时间等实验条件.实验结果表明,AuNPs对黄芩素具有显著的电催化性能,AuNPs/CFME对黄芩素表现出良好的电化学响应,最佳修饰时间为10 min.黄芩素浓度在0.05~10μmol/L时,其氧化峰电流与浓度呈良好的线性关系,线性方程为I_(p)(nA)=0.4409C(μmol/L)+0.7066,R^(2)=0.998.该方法响应速度快、稳定性较好,可用于黄芩素的定量检测.

Mechanism of Thermally Radiative Prandtl Nanofluids and Double-Diffusive Convection in Tapered Channel on Peristaltic Flow with Viscous Dissipation and Induced Magnetic Field

The application of mathematical modeling to biological fluids is of utmost importance, as it has diverse applicationsin medicine. The peristaltic mechanism plays a crucial role in understanding numerous biological flows. In thispaper, we present a theoretical investigation of the double diffusion convection in the peristaltic transport of aPrandtl nanofluid through an asymmetric tapered channel under the combined action of thermal radiation andan induced magnetic field. The equations for the current flow scenario are developed, incorporating relevantassumptions, and considering the effect of viscous dissipation. The impact of thermal radiation and doublediffusion on public health is of particular interest. For instance, infrared radiation techniques have been used totreat various skin-related diseases and can also be employed as a measure of thermotherapy for some bones toenhance blood circulation, with radiation increasing blood flow by approximately 80%. To solve the governingequations, we employ a numerical method with the aid of symbolic software such as Mathematica and MATLAB.The velocity, magnetic force function, pressure rise, temperature, solute (species) concentration, and nanoparticlevolume fraction profiles are analytically derived and graphically displayed. The results outcomes are compared withthe findings of limiting situations for verification.

Influence of Brownian Motion, Thermophoresis and Magnetic Effects on a Fluid Containing Nanoparticles Flowing over a Stretchable Cylinder

The influence of Brownian motion and thermophoresis on a fluid containing nanoparticles flowing over a stretchable cylinder is examined.The classical Navier-Stokes equations are considered in a porous frame.In addition,the Lorentz force is taken into account.The controlling coupled nonlinear partial differential equations are transformed into a system of first order ordinary differential equations by means of a similarity transformation.The resulting system of equations is solved by employing a shooting approach properly implemented in MATLAB.The evolution of the boundary layer and the growing velocity is shown graphically together with the related profiles of concentration and temperature.The magnetic field has a different influence(in terms of trends)on velocity and concentration.

基于CE-318观测的甘肃省气溶胶光学特性分析

对于大气气溶胶地基观测资料的定量分析是了解气溶胶光学特性和大气污染特征的基本途径,可为探讨污染治理方向提供一定的依据。近年来,利用地基观测资料分析甘肃省不同区域气溶胶光学特性的研究较少。为了解甘肃省不同下垫面的大气气溶胶光学特性,本文基于2018年4月至2020年9月CE-318型太阳光度计观测资料,通过ASTPwin软件反演获得了甘肃省四个站点的气溶胶光学厚度AOD,计算了Angstrom波长指数α,分析了甘肃省不同区域不同季节AOD和α的分布和变化特征以及气溶胶光学厚度和波长指数的关系。结果表明:(1)观测时段内,所有站点各波段AOD的变化趋于一致,且AOD值随波长增大而减小。兰州和皋兰山AOD值冬季最高,春、秋季次之,夏季最低,兰州冬、春季AOD值分别比年均值超出14.98%和4.68%,皋兰山冬季AOD值比年均值超出3.88%。敦煌和民勤AOD值均为春季最高,比各自的年均值高出24.49%和26.30%。敦煌AOD季节分布为:春季>夏季>冬季>秋季,而民勤则表现为从春到冬季逐渐减小的趋势。(2)兰州和皋兰山春夏季主控粒子为粗模态,秋冬季则为细颗粒物主导。敦煌和民勤大气气溶胶常年由粗模态粒子主控。2019年冬季,兰州市区AOD值比其城郊的皋兰山高出68.0%;敦煌和民勤2019年春季沙尘气溶胶污染较为严重,敦煌AOD值比民勤超出42.42%。(3)四个站点AOD和α的频率分布均呈单峰曲线,不同季节AOD高频次分布范围存在差异性,但都处于1.0以下。α的高频次范围分布较为复杂,兰州春季、皋兰山春夏季、敦煌四季、民勤春夏秋季,α分布区间均小于1.0,而兰州夏秋冬季、皋兰山秋冬季、民勤冬季α主要分布于1.1以上。(4)不同季节AOD和α的关系存在差异,表现为不同季节,大气出现严重或者局部污染时,气溶胶的主控粒子粒径大小不同。春季大气出现局部或者严重污染、夏季大气局部污染时,四个站点气溶胶主要是大粒径粒子,其中沙尘气溶胶的贡献较大。夏季大气处于严重污染时,皋兰山气溶胶主要是细模态粒子,兰州、敦煌、民勤气溶胶依然由粗模态主控,但是兰州小粒径粒子导致的污染比重高于其余两站,其中85%以上属于城市工业-气溶胶污染。秋季大气处于严重污染状况时,兰州和皋兰山均由细模态粒子主导,其中城市工业-气溶胶占比明显增加,而敦煌和民勤依然由粗模态粒子主导,其中沙尘气溶胶占比偏重。冬季大气严重污染时,兰州依然由细模态粒子主导,而其他三站由粗模态粒子占据主导地位,冬季大气局部污染时,敦煌和民勤粗模态粒子与细模态粒子同时出现,皋兰山以细模态粒子为主。分析可知,总体上甘肃偏北地区气溶胶污染以沙尘气溶胶为主,而偏南地区气溶胶污染表现为粗模态与细模态粒子交替出现,这为下一步结合卫星遥感资料研究甘肃不同区域的气溶胶特性及大气污染特征提供了一些参考。

Algorithm for Visualization of Zero Divisor Graphs of the Ring ℤn Using MAPLE Coding

This research investigates the comparative efficacy of generating zero divisor graphs (ZDGs) of the ring of integers ℤn modulo n using MAPLE algorithm. Zero divisor graphs, pivotal in the study of ring theory, depict relationships between elements of a ring that multiply to zero. The paper explores the development and implementation of algorithms in MAPLE for constructing these ZDGs. The comparative study aims to discern the strengths, limitations, and computational efficiency of different MAPLE algorithms for creating zero divisor graphs offering insights for mathematicians, researchers, and computational enthusiasts involved in ring theory and mathematical computations.

A Hybrid SIR-Fuzzy Model for Epidemic Dynamics:A Numerical Study

This study focuses on the urgent requirement for improved accuracy in diseasemodeling by introducing a newcomputational framework called the Hybrid SIR-Fuzzy Model.By integrating the traditional Susceptible-Infectious-Recovered(SIR)modelwith fuzzy logic,ourmethod effectively addresses the complex nature of epidemic dynamics by accurately accounting for uncertainties and imprecisions in both data and model parameters.The main aim of this research is to provide a model for disease transmission using fuzzy theory,which can successfully address uncertainty in mathematical modeling.Our main emphasis is on the imprecise transmission rate parameter,utilizing a three-part description of its membership level.This enhances the representation of disease processes with greater complexity and tackles the difficulties related to quantifying uncertainty in mathematical models.We investigate equilibrium points for three separate scenarios and perform a comprehensive sensitivity analysis,providing insight into the complex correlation betweenmodel parameters and epidemic results.In order to facilitate a quantitative analysis of the fuzzy model,we propose the implementation of a resilient numerical scheme.The convergence study of the scheme demonstrates its trustworthiness,providing a conditionally positive solution,which represents a significant improvement compared to current forward Euler schemes.The numerical findings demonstrate themodel’s effectiveness in accurately representing the dynamics of disease transmission.Significantly,when the mortality coefficient rises,both the susceptible and infected populations decrease,highlighting the model’s sensitivity to important epidemiological factors.Moreover,there is a direct relationship between higher Holling type rate values and a decrease in the number of individuals who are infected,as well as an increase in the number of susceptible individuals.This correlation offers a significant understanding of how many elements affect the consequences of an epidemic.Our objective is to enhance decision-making in public health by providing a thorough quantitative analysis of the Hybrid SIR-Fuzzy Model.Our approach not only tackles the existing constraints in disease modeling,but also paves the way for additional investigation,providing a vital instrument for researchers and policymakers alike.

Deep Convolutional Neural Networks for Accurate Classification of Gastrointestinal Tract Syndromes

Accurate detection and classification of artifacts within the gastrointestinal(GI)tract frames remain a significant challenge in medical image processing.Medical science combined with artificial intelligence is advancing to automate the diagnosis and treatment of numerous diseases.Key to this is the development of robust algorithms for image classification and detection,crucial in designing sophisticated systems for diagnosis and treatment.This study makes a small contribution to endoscopic image classification.The proposed approach involves multiple operations,including extracting deep features from endoscopy images using pre-trained neural networks such as Darknet-53 and Xception.Additionally,feature optimization utilizes the binary dragonfly algorithm(BDA),with the fusion of the obtained feature vectors.The fused feature set is input into the ensemble subspace k nearest neighbors(ESKNN)classifier.The Kvasir-V2 benchmark dataset,and the COMSATS University Islamabad(CUI)Wah private dataset,featuring three classes of endoscopic stomach images were used.Performance assessments considered various feature selection techniques,including genetic algorithm(GA),particle swarm optimization(PSO),salp swarm algorithm(SSA),sine cosine algorithm(SCA),and grey wolf optimizer(GWO).The proposed model excels,achieving an overall classification accuracy of 98.25% on the Kvasir-V2 benchmark and 99.90% on the CUI Wah private dataset.This approach holds promise for developing an automated computer-aided system for classifying GI tract syndromes through endoscopy images.

Association of spiritual well-being with quality of life among undergraduate nursing students

Objective:The study was conducted with the aim of determining the spiritual well-being(SWB)of nursing students and its association with quality of life(QOL).Materials and Methods:A cross-sectional analytical study was conducted with a sample size of 504 nursing students collected from January 2023 to March 2023 in the nursing institutes of Khyber Pakhtunkhwa,Pakistan,using convenient sampling techniques.A Spiritual Health and Life-Orientation Measure(SHALOM)questionnaire for SWB and K-27 QOL(K-27 QOL)instrument were used for data collection that contains three parts.Results:The number of female participants was in the majority(50.4%)compared to male nurses(49.6%).The overall mean score of SWB of the students was 3.79±0.48,while the mean K-27 QOL score was 3.73±0.57.There were significant differences between the groups of gender(P=0.001),while no significant difference within the groups of semester(P=0.061)and college status(0.285).In QOL,there were significant differences within the groups of semester(P=0.000)and college status(P=0.036)while no significant difference in gender category(P=0.480).SHALOM score is positively and moderately correlated with QOL score(r=0.597,P<0.05).Conclusion:Spiritual practices are one of the important factors that are associated positively with QOL,therefore to enhance the QOL,it will require spiritual practices.

A Novel Fractional Dengue Transmission Model in the Presence of Wolbachia Using Stochastic Based Artificial Neural Network

The purpose of this research work is to investigate the numerical solutions of the fractional dengue transmission model(FDTM)in the presence of Wolbachia using the stochastic-based Levenberg-Marquardt neural network(LM-NN)technique.The fractional dengue transmission model(FDTM)consists of 12 compartments.The human population is divided into four compartments;susceptible humans(S_(h)),exposed humans(E_(h)),infectious humans(I_(h)),and recovered humans(R_(h)).Wolbachia-infected and Wolbachia-uninfected mosquito population is also divided into four compartments:aquatic(eggs,larvae,pupae),susceptible,exposed,and infectious.We investigated three different cases of vertical transmission probability(η),namely when Wolbachia-free mosquitoes persist only(η=0.6),when both types of mosquitoes persist(η=0.8),and when Wolbachia-carrying mosquitoes persist only(η=1).The objective of this study is to investigate the effectiveness of Wolbachia in reducing dengue and presenting the numerical results by using the stochastic structure LM-NN approach with 10 hidden layers of neurons for three different cases of the fractional order derivatives(α=0.4,0.6,0.8).LM-NN approach includes a training,validation,and testing procedure to minimize the mean square error(MSE)values using the reference dataset(obtained by solving the model using the Adams-Bashforth-Moulton method(ABM).The distribution of data is 80% data for training,10% for validation,and,10% for testing purpose)results.A comprehensive investigation is accessible to observe the competence,precision,capacity,and efficiency of the suggested LM-NN approach by executing the MSE,state transitions findings,and regression analysis.The effectiveness of the LM-NN approach for solving the FDTM is demonstrated by the overlap of the findings with trustworthy measures,which achieves a precision of up to 10^(-4).

An Innovative Approach Using TKN-Cryptology for Identifying the Replay Assault

Various organizations store data online rather than on physical servers.As the number of user’s data stored in cloud servers increases,the attack rate to access data from cloud servers also increases.Different researchers worked on different algorithms to protect cloud data from replay attacks.None of the papers used a technique that simultaneously detects a full-message and partial-message replay attack.This study presents the development of a TKN(Text,Key and Name)cryptographic algorithm aimed at protecting data from replay attacks.The program employs distinct ways to encrypt plain text[P],a user-defined Key[K],and a Secret Code[N].The novelty of the TKN cryptographic algorithm is that the bit value of each text is linked to another value with the help of the proposed algorithm,and the length of the cipher text obtained is twice the length of the original text.In the scenario that an attacker executes a replay attack on the cloud server,engages in cryptanalysis,or manipulates any data,it will result in automated modification of all associated values inside the backend.This mechanism has the benefit of enhancing the detectability of replay attacks.Nevertheless,the attacker cannot access data not included in any of the papers,regardless of how effective the attack strategy is.At the end of paper,the proposed algorithm’s novelty will be compared with different algorithms,and it will be discussed how far the proposed algorithm is better than all other algorithms.

GNSS-IR测量水位的精度评估和站点对比:以中国南海北部和日本南部站点为例

通过南海北部和日本多个实例,量化分析影响近岸全球卫星导航系统干涉反射计(GNSS-IR)反演潮位或风暴潮过程效果的主要影响因素。结果表明:接收机所能接收的卫星信号波段数量、反射信号功率对反演的时间分辨率和精度影响巨大。研究以中国香港HKQT站点为例量化多模多频GNSS-IR监测风暴潮的优势,同时展示日本J425站点在潮位站空缺地区记录完整风暴潮波形的能力。分别针对卫星信号接受波段、硬件配置、台站架设位置和架设高度等因素,对未来架设具有测量海平面能力的近岸GNSS站点提供具体的指导意见。

Diabetes and Hypertension Are Associated with Food Insecurity in a Cameroonian Population: A Case-Control Study

Diabetes and hypertension are the most prevalent cardiovascular risk factors. Recent studies showed an increase in the prevalence of food insecurity in our country. The aim of this study was to assess how food insecurity affects the dietary habits, socio-demographic characteristics and metabolic profile of individuals with diabetes or hypertension. This case-control study was conducted among diabetic and hypertensive participants (cases) and diabetic and hypertensive normal (controls) during the screening campaigns for nutrition-related chronic diseases. The sociodemographic, clinical and biochemical parameters of the participants were analyzed. Logistic regression analyses were performed to identify factors associated with diabetes and hypertension in the study population. Bivariate analyses showed that male gender (OR = 1.972;95% CI: 1.250 - 3.089), regular alcohol consumption (OR = 2.012;95% CI: 1.294 - 3.130), low fruit consumption (OR = 1.590;95% CI: 1.016 - 2.488), low dietary diversity (OR = 2.915;95% CI: 1.658 - 5.127) and abdominal obesity (OR = 1.893, CI 95% 1.203 - 2.978) were significantly associated with hypertension. In addition, low fruit consumption (OR = 1.829;95% CI 1.092 - 3.064), low legume consumption (OR = 3.515;95% CI 1.861 - 6.635), and hypertriglyceridaemia (OR = 2.241, 95% CI 1.139 - 4.408) were significantly associated with diabetes. The indirect association observed between food insecurity and diabetes and hypertension suggests the need for nutritional policies aimed at popularizing the production and consumption of fruits and legumes. Similarly, health services need to be aware and informed of the important role that food insecurity can play in the development of diabetes and hypertension.

Inter-Row Spacing of PV Power Plant

When designing a solar power plant, it is much more important to avoid the shadow on the PV Panels. As the shadow falls on the PV Panels;it significantly reduces the generation of required power as planned and designed. This research paper and case study will help a lot to avoid shadow, especially when selecting inter-row spacing between the strings of solar power plants.

Secure Transmission of Compressed Medical Image Sequences on Communication Networks Using Motion Vector Watermarking

Medical imaging plays a key role within modern hospital management systems for diagnostic purposes.Compression methodologies are extensively employed to mitigate storage demands and enhance transmission speed,all while upholding image quality.Moreover,an increasing number of hospitals are embracing cloud computing for patient data storage,necessitating meticulous scrutiny of server security and privacy protocols.Nevertheless,considering the widespread availability of multimedia tools,the preservation of digital data integrity surpasses the significance of compression alone.In response to this concern,we propose a secure storage and transmission solution for compressed medical image sequences,such as ultrasound images,utilizing a motion vector watermarking scheme.The watermark is generated employing an error-correcting code known as Bose-Chaudhuri-Hocquenghem(BCH)and is subsequently embedded into the compressed sequence via block-based motion vectors.In the process of watermark embedding,motion vectors are selected based on their magnitude and phase angle.When embedding watermarks,no specific spatial area,such as a region of interest(ROI),is used in the images.The embedding of watermark bits is dependent on motion vectors.Although reversible watermarking allows the restoration of the original image sequences,we use the irreversible watermarking method.The reason for this is that the use of reversible watermarks may impede the claims of ownership and legal rights.The restoration of original data or images may call into question ownership or other legal claims.The peak signal-to-noise ratio(PSNR)and structural similarity index(SSIM)serve as metrics for evaluating the watermarked image quality.Across all images,the PSNR value exceeds 46 dB,and the SSIM value exceeds 0.92.Experimental results substantiate the efficacy of the proposed technique in preserving data integrity.