An Artificial Heart System for Testing and Evaluation of Cardiac Pacemakers

The usability assessment of a pacemaker is a complex task where the dedicated programmer for testing programmed algorithms is necessary.This paper provides the outcomes of development and complex testing of the artificial cardiac system to evaluate the pacemaker’s functionality.In this work,we used the modular laboratory platform ELVIS II and created graphical user interface in LabVIEW programming environment.The electrical model of the heart allows signals generation(right atrium,right ventricle)and the monitoring of the stimulation pulses.The LabVIEW user interface allows to set the parameters of the generated signals and the simulation of the cardiac rhythm disorders as well as the monitoring and visualization of the pacemaker behavior in real-time.The results demonstrate the capability of proposed system to evaluate the paced and sensed pulses.The proposed solution allows the scientists to test the behavior of any cardiac pacemaker for its pre-programmed settings and pacing mode.In addition,the proposed system can simulate various disorders and test cardiac pacemakers in different working modes.

Single-cell pan-omics, environmental neurology, and artificial intelligence:the time for holistic brain health research

The brain,with its trillions of neural connections,different cellular types,and molecular complexities,presents a formidable challenge for researchers aiming to comprehend the multifaceted nature of neural health.As traditional methods have provided valuable insights,emerging technologies offer unprecedented opportunities to delve deeper into the underpinnings of brain function.In the everevolving landscape of neuroscience,the quest to unravel the mysteries of the human brain is bound to take a leap forward thanks to new technological improvements and bold interpretative frameworks.

Recognition and quality mapping of traditional herbal drugs:way forward towards artificial intelligence

The use of traditional herbal drugs derived from natural sources is on the rise due to their minimal side effects and numerous health benefits.However,a major limitation is the lack of standardized knowledge for identifying and mapping the quality of these herbal medicines.This article aims to provide practical insights into the application of artificial intelligence for quality-based commercialization of raw herbal drugs.It focuses on feature extraction methods,image processing techniques,and the preparation of herbal images for compatibility with machine learning models.The article discusses commonly used image processing tools such as normalization,slicing,cropping,and augmentation to prepare images for artificial intelligence-based models.It also provides an overview of global herbal image databases and the models employed for herbal plant/drug identification.Readers will gain a comprehensive understanding of the potential application of various machine learning models,including artificial neural networks and convolutional neural networks.The article delves into suitable validation parameters like true positive rates,accuracy,precision,and more for the development of artificial intelligence-based identification and authentication techniques for herbal drugs.This article offers valuable insights and a conclusive platform for the further exploration of artificial intelligence in the field of herbal drugs,paving the way for smarter identification and authentication methods.

Harnessing artificial intelligence for identifying conflicts of interest in research

This editorial explores the transformative potential of artificial intelligence(AI)in identifying conflicts of interest(COIs)within academic and scientific research.By harnessing advanced data analysis,pattern recognition,and natural language processing techniques,AI offers innovative solutions for enhancing transparency and integrity in research.This editorial discusses how AI can automatically detect COIs,integrate data from various sources,and streamline reporting processes,thereby maintaining the credibility of scientific findings.

Impact of single chamber and dual chamber permanent pacemaker implantation on left ventricular function:An observational study

BACKGROUND Permanent pacemaker implantation has the potential to impact left ventricular(LV)function and hence quality of life(QoL)in the long term.AIM To assess the effect of single-and dual-chamber pacing on LV function and QoL.METHODS This study included 56 patients who underwent permanent pacing:Dual pacing,dual sensing,dual responsive and rate responsive(DDDR)for the initial 3 months,ventricular sensing,inhibited response and rate responsive(VVIR)for the next 3 months,and DDDR mode for the last 3 months.Throughout the study period,various echocardiographic parameters,functional status,and QoL were measured to assess the impact of pacing on LV function compared with baseline and at every 3 months interval.RESULTS A significant change appeared in cardiac function after VVIR pacing which was in diastolic properties of LV as shown by increase in isovolumic relaxation time from(85.28±9.54 ms)to(89.53±9.65 ms).At the 3-,6-,and 9-month follow-up,reduction in LV ejection fraction was observed to be 62.71±4.66%,61.07±4.41%,and 58.48±3.89%,respectively.An increase in the QoL scores was noted at every follow-up visit.CONCLUSION An apparent depressant effect on LV function due to right ventricular pacing,with a higher incidence of adverse outcomes in the VVIR mode.In addition,an upsurge in QoL scores for the study population was noted,which indicates improvement in the QoL of patients post-pacing,irrespective of the mode.Generally,the DDDR mode is a highly preferable pacing mode.

Current knowledge for the risk factors of early permanent pacemaker implantation following transcatheter aortic valve replacement and what is next for the primary prevention?

In this editorial,we comprehensively summarized the preoperative risk factors of early permanent pacemaker implantation after transcatheter aortic valve replacement(TAVR)among patients with severe aortic stenosis from several renowned clinical studies and focused on the primary prevention of managing the modifiable factors,e.g.,paroxysmal atrial fibrillation before the TAVR.

The Application of Bilayer Artificial Dermis Combined with VSD Technology in Chronic Wounds

Background: Bilayer artificial dermis promotes wound healing and offers a treatment option for chronic wounds. Aim: Examine the clinical efficacy of bilayer artificial dermis combined with Vacuum Sealing Drainage (VSD) technology in the treatment of chronic wounds. Method: From June 2021 to December 2023, our hospital treated 24 patients with chronic skin tissue wounds on their limbs using a novel tissue engineering product, the bilayer artificial dermis, in combination with VSD technology to repair the wounds. The bilayer artificial dermis protects subcutaneous tissue, blood vessels, nerves, muscles, and tendons, and also promotes the growth of granulation tissue and blood vessels to aid in wound healing when used in conjunction with VSD technology for wound dressing changes in chronic wounds. Results: In this study, 24 cases of chronic wounds with exposed bone or tendon larger than 1.0 cm2 were treated with a bilayer artificial skin combined with VSD dressing after wound debridement. The wounds were not suitable for immediate skin grafting. At 2 - 3 weeks post-treatment, good granulation tissue growth was observed. Subsequent procedures included thick skin grafting or wound dressing changes until complete wound healing. Patients were followed up on average for 3 months (range: 1 - 12 months) post-surgery. Comparative analysis of the appearance, function, skin color, elasticity, and sensation of the healed chronic wounds revealed superior outcomes compared to traditional skin fl repairs, resulting in significantly higher satisfaction levels among patients and their families. Conclusion: The application of bilayer artificial dermis combined with VSD technology for the repair of chronic wounds proves to be a viable method, yielding satisfactory therapeutic effects compared to traditional skin flap procedures.

The Peripheral Hospital as Focal Point for Pacemaker Activity: Review of the Last 300 Implantations Carried out at the Haute Correze Hospital Center

Background: Pacemaker implantation is a very old activity which has revolutionized the cardiology practice throughout the world. This activity is effective at the Haute Correze Hospital Center since more than 20 years. Due to progress in this area, and the increasing request within this center located at the outskirts of town, we set out to evaluate our pacemaker activity in general and more specifically to assess the post-procedural complications in our series patients. Methodology: This was a retrospective longitudinal study. Data were recorded for period of 90 months from 27/05/2016 to 19/11/2023. This data collection was possible via a specific register completed by computerized patient data from the SillageTM software. All files of patients implanted with single or dual chamber pacemakers were included, generator replacements, upgrading procedures and addition of leads were excluded. The sampling was non-probabilistic, consecutive and non-exhaustive. Statistical analysis was carried out using the Excel 2019 spreadsheet and SPSS version 23 software. The quantitative variables were presented as mean ± standard deviation, the qualitative data as proportions. Results: A total of 303 first-time pacemaker’s implantations were carried out during the study period (rate of 40 per year). The average age in the population was 79.7 ± 9.4 years (44 - 99 years) with a male predominance of 63.7% (n = 193). Atrioventricular block (2nd and 3rd degree) was the main indication for pacemaker implantation in 42.9% of cases (n = 130). Patients were most often implanted with a dual-chamber pacemaker (57.7%, n = 175). The approach was most often cephalic in 72.6% of cases (n = 220), followed by the subclavian access in 27.4% of cases (n = 84). The average fluoroscopy time was 7.9 min ± 2.4 (1 - 43). The average irradiation dose in gray/cm2 was 12.4 ± 9.3 (0.22 - 117.5). The average length of hospitalization was 7 ± 4 (2 - 26) days. The overall complication rate at one year was 12.9% (n = 39). These complications are distributed as follows: Leads dislodgement in 8.2% (n = 25), hematoma 3.6% (n = 11) all without clinical consequences, pneumothorax 0.7% (n = 2), both cases of pneumothorax did not require specific care, infection (superficial) in 0.3% (n = 1). Leads dislodgement occurred after a median time of 18 days (IQR: 3 - 36). The earliest dislodgement was observed on D0 and the latest on D207. No serious complications were recorded. The average atrial threshold at implantation/first control/last follow-up was 0.7/1.3/0.8 V, respectively. The average ventricular threshold at implantation/first control/last follow-up was 0.5/1.08/0.87 V, respectively. The average atrial detection at implantation/first control/last follow-up was 3.2/2.3/ 2.05 mv, respectively. The average ventricular detection at implantation/first control/last follow-up was 10.3/11.03/10.8 mv. The average atrial impedance at implantation/first control/last follow-up was 610/457/457 ohms. The average ventricular impedance at implantation/first control/last follow-up was 754/547/563 ohms. Conclusion: Pacemaker implantation is safe at the Haute Correze Hospital Center with a relatively low rate of complications, in this case an almost zero major infection and no serious hematoma. The peripheral hospital should remain a focal point of this activity in order to respond more quickly to the needs of the populations.

Explainable Artificial Intelligence(XAI)Model for Cancer Image Classification

The use of Explainable Artificial Intelligence(XAI)models becomes increasingly important for making decisions in smart healthcare environments.It is to make sure that decisions are based on trustworthy algorithms and that healthcare workers understand the decisions made by these algorithms.These models can potentially enhance interpretability and explainability in decision-making processes that rely on artificial intelligence.Nevertheless,the intricate nature of the healthcare field necessitates the utilization of sophisticated models to classify cancer images.This research presents an advanced investigation of XAI models to classify cancer images.It describes the different levels of explainability and interpretability associated with XAI models and the challenges faced in deploying them in healthcare applications.In addition,this study proposes a novel framework for cancer image classification that incorporates XAI models with deep learning and advanced medical imaging techniques.The proposed model integrates several techniques,including end-to-end explainable evaluation,rule-based explanation,and useradaptive explanation.The proposed XAI reaches 97.72%accuracy,90.72%precision,93.72%recall,96.72%F1-score,9.55%FDR,9.66%FOR,and 91.18%DOR.It will discuss the potential applications of the proposed XAI models in the smart healthcare environment.It will help ensure trust and accountability in AI-based decisions,which is essential for achieving a safe and reliable smart healthcare environment.

Wireless Power Supply Based on MNG-MNZ Metamaterial for Cardiac Pacemakers

To solve the low power transfer efficiency and magnetic field leakage problems of cardiac pacemaker wireless powering, we proposed a wireless power supply system suitable for implanted cardiac pacemaker based on mu-negative(MNG) and mu-nearzero(MNZ) metamaterials. First, a hybrid metamaterial consisted of central MNG unit for magnetic field concentration and surrounding MNZ units for magnetic leakage shielding was established by theoretical calculation. Afterwards, the magnetic field distribution of wireless power supply system with MNG-MNZ metamaterial slab was acquired via finite element simulation and verified to be better than the distribution with conventional MNG slab deployed. Finally, an experimental platform of wireless power supply system was established with which power transfer experiment and system temperature rise experiment were conducted.Simulation and experimental results showed that the power transfer efficiency was improved from 44.44%,19.42%, 8.63% and 6.19% to 55.77%, 62.39%, 20.81%and 14.52% at 9.6 mm, 20 mm, 30 mm and 50 mm,respectively. The maximum SAR acquired by SAR simulation under human body environment was-7.14 dbm and maximum reduction of the magnetic field strength around the receiving coil was 2.82 A/m. The maximum temperature rise during 30min charging test was 3.85℃,and the safety requirements of human bodies were met.

Application Effect of External Diaphragm Pacemaker Combined with Active Respiratory Circulation Technology in Pulmonary Rehabilitation of Perioperative Lung Cancer Patients

Aim: To explore the application effect of external diaphragm pacemaker combined with active respiratory circulation technology in pulmonary rehabilitation of perioperative lung cancer patients. Methods: A total of 98 lung cancer patients admitted to our hospital from April 2020 to November 2021 were selected as the observation objects, and then divided into a control group and an observation group using the random number table method, with 49 cases in each group. The control group received routine admission guidance and active respiratory circulation training, while the observation group was supplemented with external diaphragm pacemaker on the basis of the control group. The intervention effect was evaluated by blood gas indicators, pulmonary function indicators, diaphragm function indicators, sputum comfort degree, and activity tolerance indicators before and after intervention. Results: Before intervention, there were no significant differences in blood gas analysis indicators, pulmonary function indicators, diaphragm function indicators, sputum comfort degree, and activity tolerance indicators between the two groups (P > 0.05). After intervention, the improvement degree of the above indicators in the observation group was higher than that in the control group (P < 0.05). Conclusions: The application of external diaphragm pacemaker combined with active respiratory circulation technology in pulmonary rehabilitation of perioperative lung cancer patients is significant, which can effectively improve the pulmonary function, blood gas function, and diaphragm function of lung cancer patients after surgery, and improve the activities of daily living and quality of life of patients.

Risk of permanent pacemaker implantation following transcatheter aortic valve replacement:Which factors are most relevant?

Transcatheter aortic valve replacement(TAVR)has emerged as a formidable treatment option for severe symptomatic aortic stenosis ahead of surgical aortic valve replacement.The encouraging results from large randomized controlled trials has resulted in an exponential rise in the use of TAVR even in the low-risk patients.However,this is not without challenges.Need for permanent pacemaker(PPM)post-TAVR remains the most frequent and clinically relevant challenge.Naturally,identifying risk factors which predispose an individual to develop high grade conduction block post-TAVR is important.Various demographic factors,electrocardiographic features,anatomic factors and procedural characteristics have all been linked to the development of advanced conduction block and need for PPM following TAVR.Amongst these electrophysiological variables,most notably a prolonged QRS>120 ms regardless of the type of conduction block seems to be one of the strongest predictors on logistic regression models.The index study by Nwaedozie et al highlights that patients requiring PPM post-TAVR had higher odds of having a baseline QRS>120 ms and were more likely to be having diabetes mellitus that those who did not require PPM.

Pacemaker post transcatheter aortic valve replacement:A multifactorial risk?

Pacemaker post-transcatheter aortic valve replacement is related to multifactorial risk.Nwaedozie et al brought to the body of evidence electrocardiogram and clinical findings.However,procedural characteristics have at least as much impact on the final need for a permanent pacemaker and potentially on the pacing rate.In this regard,long-term follow-up and understanding of the impact of long-term stimulation is of utmost importance.

Teaching Design of Course Building Decoration Materials Based on Generative Artificial Intelligence

With the digital transformation of global education and China's emphasis on education digital,generative AI technology has been widely used in the field of higher education.In this paper,the development of generative AI technology and its potential in personalized learning,interactive content creation and adaptive assessment in education were introduced firstly.Then,the application case of generative AI tools in teaching content creation,scenario-based teaching content development,visual teaching content development,complex concept deconstruction and analogy,student-led application practice and other aspects in the teaching of Building Decoration Materials was discussed.Through the teaching experiment and effect evaluation,the positive influence of generative AI technology on the improvement of students'learning effect and teaching efficiency was verified.Finally,some thoughts and inspirations on the combination of educational theory and generative AI technology,the integration of teaching design and generative AI technology,and the practice cases and effect evaluation were put forward,and the importance of teacher role transformation and personalized learning path design was emphasized to provide theoretical and practical support for the innovative development of higher education.

Hybrid Hierarchical Particle Swarm Optimization with Evolutionary Artificial Bee Colony Algorithm for Task Scheduling in Cloud Computing

Task scheduling plays a key role in effectively managing and allocating computing resources to meet various computing tasks in a cloud computing environment.Short execution time and low load imbalance may be the challenges for some algorithms in resource scheduling scenarios.In this work,the Hierarchical Particle Swarm Optimization-Evolutionary Artificial Bee Colony Algorithm(HPSO-EABC)has been proposed,which hybrids our presented Evolutionary Artificial Bee Colony(EABC),and Hierarchical Particle Swarm Optimization(HPSO)algorithm.The HPSO-EABC algorithm incorporates both the advantages of the HPSO and the EABC algorithm.Comprehensive testing including evaluations of algorithm convergence speed,resource execution time,load balancing,and operational costs has been done.The results indicate that the EABC algorithm exhibits greater parallelism compared to the Artificial Bee Colony algorithm.Compared with the Particle Swarm Optimization algorithm,the HPSO algorithmnot only improves the global search capability but also effectively mitigates getting stuck in local optima.As a result,the hybrid HPSO-EABC algorithm demonstrates significant improvements in terms of stability and convergence speed.Moreover,it exhibits enhanced resource scheduling performance in both homogeneous and heterogeneous environments,effectively reducing execution time and cost,which also is verified by the ablation experimental.

Optimal Location and Sizing ofMulti-Resource Distributed Generator Based onMulti-Objective Artificial Bee Colony Algorithm

Distribution generation(DG)technology based on a variety of renewable energy technologies has developed rapidly.A large number of multi-type DG are connected to the distribution network(DN),resulting in a decline in the stability of DN operation.It is urgent to find a method that can effectively connect multi-energy DG to DN.photovoltaic(PV),wind power generation(WPG),fuel cell(FC),and micro gas turbine(MGT)are considered in this paper.A multi-objective optimization model was established based on the life cycle cost(LCC)of DG,voltage quality,voltage fluctuation,system network loss,power deviation of the tie-line,DG pollution emission index,and meteorological index weight of DN.Multi-objective artificial bee colony algorithm(MOABC)was used to determine the optimal location and capacity of the four kinds of DG access DN,and compared with the other three heuristic algorithms.Simulation tests based on IEEE 33 test node and IEEE 69 test node show that in IEEE 33 test node,the total voltage deviation,voltage fluctuation,and system network loss of DN decreased by 49.67%,7.47%and 48.12%,respectively,compared with that without DG configuration.In the IEEE 69 test node,the total voltage deviation,voltage fluctuation and system network loss of DN in the MOABC configuration scheme decreased by 54.98%,35.93%and 75.17%,respectively,compared with that without DG configuration,indicating that MOABC can reasonably plan the capacity and location of DG.Achieve the maximum trade-off between DG economy and DN operation stability.

A Discussion of Artificial Intelligence in Visual Art Education

Since ChatGPT emerged on November 30, 2022, Artificial Intelligence (AI) has been increasingly discussed as a radical force that will change our world. People have become used to AI in which such ubiquitous technologies as Siri, Google, and Netflix deploy AI algorithms to answer questions, impart information, and provide recommendations. However, many individuals including originators and backers of AI have recently expressed grave concerns. In this paper, the authors will assess what is occurring with AI in Visual Arts Education, outline positives and negatives, and provide recommendations addressed specifically for teachers working in the field regarding emerging AI usage from kindergarten to grade twelve levels as well as in higher education.

Simultaneous Identification of Thermophysical Properties of Semitransparent Media Using a Hybrid Model Based on Artificial Neural Network and Evolutionary Algorithm

A hybrid identification model based on multilayer artificial neural networks(ANNs) and particle swarm optimization(PSO) algorithm is developed to improve the simultaneous identification efficiency of thermal conductivity and effective absorption coefficient of semitransparent materials.For the direct model,the spherical harmonic method and the finite volume method are used to solve the coupled conduction-radiation heat transfer problem in an absorbing,emitting,and non-scattering 2D axisymmetric gray medium in the background of laser flash method.For the identification part,firstly,the temperature field and the incident radiation field in different positions are chosen as observables.Then,a traditional identification model based on PSO algorithm is established.Finally,multilayer ANNs are built to fit and replace the direct model in the traditional identification model to speed up the identification process.The results show that compared with the traditional identification model,the time cost of the hybrid identification model is reduced by about 1 000 times.Besides,the hybrid identification model remains a high level of accuracy even with measurement errors.

Cultivation of Critical Thinking Skills: Exploring the Impact of Generative Artificial Intelligence- Enabled Instruction in English Essay Writing

This study explores the impact of generative artificial intelligence(AI)-enabled instruction on critical thinking in English essay writing among 1,050 first-year English majors across four colleges.Pedagogical strategies,including facilitating critical responses and emphasizing real-world application,are identified to enhance generative AI’s impact.Both qualitative and quantitative analyses reveal significant post-intervention improvements in critical thinking skills.This research contributes to understanding how generative AI can effectively foster critical thinking in educational settings.

A Review of Artificial Waterfalls in Gardens

When artificial waterfalls are built in gardens,leaves from trees or vegetation often fall into the water storage pool and block the pipelines,requiring regular cleaning of pipelines.This not only increases the manpower needed for maintenance but also disrupts the use of the waterfalls.Therefore,it is necessary to design a new type of artificial waterfall that is suitable for gardens.The waterfall should incorporate features that make cleaning easier,including filter plates and water funnels to prevent clogging caused by fallen leaves and debris.