Feasibility and Acceptability of Deploying a Collaborative Service Robot in Long-Term Care: Staff Experiences

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

This paper reported on the observation of the application of the Service Robot Aether in long-term care and provided some helpful information about the users' experiments. However, this paper focused on the robot's application and was unrelated to its software and hardware. That is, it did not relate to the scope of this Electronic journal.

1. This electronic journal's subject areas include Microelectronics, Optoelectronics, Industrial Electronics, Power Electronics, Bioelectronics, Microwave and Wireless Communications. The paper could not be recognized as a research paper at this stage.

2. Regarding the software, the authors mentioned, “Emerging research suggests integrating Artificial Intelligence (AI)-enabled service robots can enhance staff care delivery.” However, no report could be found on the AI information.

3. Regarding the hardware, Only Figure 1 shows the shape of this robot. No information about the specification could be found.

4. The style of the abstract and reference needs to be rewritten entirely.

5. The section “5. Strengths and Limitations” needs to be merged with the section “ 4. Discussion.”

 

6. The paper liked a report on using a commercial robot but did not provide technical information. The authors were suggested to resubmit it to other journals or rewrite it to emphasize the service robot's hardware and software.  

Comments on the Quality of English Language

The English language needs to be improved to express the research more clearly.

Author Response

Comment 1: 

This electronic journal's subject areas include Microelectronics, Optoelectronics, Industrial Electronics, Power Electronics, Bioelectronics, Microwave and Wireless Communications. The paper could not be recognized as a research paper at this stage. 

Response 1: 

Thank you for your feedback. 

The scope of Electronics is broad, which includes but not limited to Computer Science & Engineering, Systems & Control Engineering, Artificial Intelligence and so on. We think our paper fits your section of Artificial Intelligence. The topics of interest under the section include but are not limited to applications of AI and human-robot interaction, with which the focus of our paper is aligned. 

Comment 2:  

"Emerging research suggests integrating Artificial Intelligence (AI)-enabled service robots can enhance staff care delivery.” However, no report could be found on the AI information.

Response 2: 

Thank you. The sentence you pointed out is part of the abstract, which typically does not need references. In our full article, the paragraph starts with "Emerging studies investigated the use of various technologies and robots, including AI-enabled robots, for people with disabilities [10, 11, 13]." has given a number of examples of how AI-enabled robots could enhance staff's care delivery.

Comment 3: Regarding the hardware, Only Figure 1 shows the shape of this robot. No information about the specification could be found.

Response 3: 

We appreciate your feedback. Since we aim to submit our paper to the section of Artificial Intelligence and the foci of our paper are applications of AI and human-robot interaction in a long-term care home for residents from perspectives of staff, we think that showing the look of the robot is sufficient. 

Comment 4: The style of the abstract and reference needs to be rewritten entirely.

Response 4: Thank you. We modified our abstract and references to the style required by your journal.

Comment 5: The section “5. Strengths and Limitations” needs to be merged with the section “ 4. Discussion.”

Response 5: Thank you. We merged strengths and limitations with Discussion.

Comment 6. The paper liked a report on using a commercial robot but did not provide technical information. The authors were suggested to resubmit it to other journals or rewrite it to emphasize the service robot's hardware and software.  

Response 6: We appreciate your feedback. We aim to submit our paper to the section of Artificial Intelligence and the foci of our paper are applications of AI and human-robot interaction in a long-term care home for residents from perspectives of staff. We did not mean to provide information about the service robot's hardware and software as it is not the focus of our paper. Thank you.

Reviewer 2 Report

Comments and Suggestions for Authors

Dear Authors,

Congratulations on the choice of topic.
Here are my suggestions:

 The title of the article is clear and effectively reflects the study's objective, which is to investigate the implementation of an AI-enabled robot in a long-term care environment. However, the abstract, while providing an overall view of the context, objective, methodology, and results, could include more specific details, such as quantitative or qualitative data highlighting the impact of the Aether robot on interactions.

In the introduction, the context and relevance of using robots in long-term care are well presented, with a solid justification for the study. However, some information is repeated across different subsections, which could be reorganized for better clarity. It is recommended to combine subsections discussing challenges in long-term care to avoid redundancies and to expand the discussion on how the Aether robot differs from existing technologies, creating a clearer contrast.

The study’s methodology is well described, with the choice of Collaborative Action Research (CAR) and CFIR as the theoretical framework being justified and appropriate to the study's objective. Still, it would be important to detail how CFIR was adapted to the specific context and include information about triangulation strategies and data validation to enhance credibility.

The results are logically organized and divided into clear themes, such as facilitators and barriers. The inclusion of participant quotes enriches the qualitative analysis, but the excessive text may hinder the immediate comprehension of key points. It would be useful to quantitatively highlight interactions with the robot, such as the frequency or average duration of activities.

In the discussion, the text effectively connects the results to the study’s context and presents relevant practical implications. However, comparisons with other studies are limited, and the analysis of the study’s limitations could be more in-depth. It is suggested to compare the findings with similar research to better contextualize the contributions and discuss how the identified barriers could be overcome. Additionally, an expanded analysis of the impact of robot integration on workplace dynamics in care environments would be valuable.

The conclusion of the article effectively synthesizes the main findings and reinforces the study's relevance, but it could be more objective and less repetitive in relation to the discussion. It is recommended to include more detailed practical recommendations for using the Aether robot in similar settings and suggest specific directions for future research.

The study’s limitations are acknowledged but could be discussed in greater depth, considering how aspects such as participant selection (with higher interaction with the robot) may have influenced the results.

Author Response

Comment 1: 

The title of the article is clear and effectively reflects the study's objective, which is to investigate the implementation of an AI-enabled robot in a long-term care environment. However, the abstract, while providing an overall view of the context, objective, methodology, and results, could include more specific details, such as quantitative or qualitative data highlighting the impact of the Aether robot on interactions.

Response 1:

We really appreciate your feedback. We modified our abstract based on your journal's requirement. Since there is a 200-word limit for abstract and our study is qualitative, we presented three themes in the results in the abstract. We welcome your feedback on the updated version available to you.

Comment 2:

In the introduction, the context and relevance of using robots in long-term care are well presented, with a solid justification for the study. However, some information is repeated across different subsections, which could be reorganized for better clarity. It is recommended to combine subsections discussing challenges in long-term care to avoid redundancies and to expand the discussion on how the Aether robot differs from existing technologies, creating a clearer contrast.

Response 2:

We shortened and reorganized the introduction as you suggested, and we think it is clearer now. We also rewritten the paragraph that introduced features of Aether. We mentioned that Aether has features similar to many existing AI-enabled robots, including real-time safety hazards detection and conversation. We also mentioned that Aether has additional functions, including singing and playing karaoke, and so on.

Comment 3:

The study’s methodology is well described, with the choice of Collaborative Action Research (CAR) and CFIR as the theoretical framework being justified and appropriate to the study's objective. Still, it would be important to detail how CFIR was adapted to the specific context and include information about triangulation strategies and data validation to enhance credibility.

Response 3:

Thank you. We did collect data through different ways, including focus group, interview, site visits, observation and field notes. We did not adopt triangulation strategies and pursue "one fact". We allow "multiple facts" exist in this study and paper. This is because our paper focuses on staff's perspectives of having Aether at their work. Our qualitative study presented the rich and descriptive experiences of managers and staff members with different roles and backgrounds. Allowing multiple facts is advantageous in understanding different participants' perspectives on Aether, their needs and priorities, their position and the underlying factors shaping their positions, values and voices. Presenting such contextual information can be valuable for care leaders and policymakers in introducing initiatives to support LTC care team using AI-enabled robots in care delivery.

We explained how CFIR was adapted to our context by using its languages in constructs and domains in results and discussion. Also, I updated our last subheads of discussion as "Support and Resources from Inner and Outer Settings".

Comment 4:

The results are logically organized and divided into clear themes, such as facilitators and barriers. The inclusion of participant quotes enriches the qualitative analysis, but the excessive text may hinder the immediate comprehension of key points. It would be useful to quantitatively highlight interactions with the robot, such as the frequency or average duration of activities.

Response 4:

Thank you. We provided contextual information between quotes, as we aim to bridge quotes with similar information under each subtheme and theme, presenting a smooth flow in results. In the method section, we provided quantitative information as follows. "Between February and June 2024, we visited the care site twice a week for a total of 36 visits. In each site visit, we deployed Aether by having staff interact with Aether, or having staff facilitate residents’ interaction with Aether. Each visit lasted from 45 minutes to two hours."

Comment 5: 

In the discussion, the text effectively connects the results to the study’s context and presents relevant practical implications. However, comparisons with other studies are limited, and the analysis of the study’s limitations could be more in-depth. It is suggested to compare the findings with similar research to better contextualize the contributions and discuss how the identified barriers could be overcome. Additionally, an expanded analysis of the impact of robot integration on workplace dynamics in care environments would be valuable.

Response 5: 

In our discussion, we added more comparison with other literature as you suggested. For example, in our argument about the need for an increased accessibility and inclusivity of AI-enabled robot for residents with language impairment, we mentioned that this is consistent with another study on LOVOT robot, which is a non-verbal communication robot that also reported to support residents’ well-being. It has been highlighted in yellow in the updated manuscript.

We expanded the limitations, which are highlighted in yellow.

Practical recommendations: The paper focuses on feasibility and acceptability of deploying Aether instead of facilitators and barriers in implementing Aether. We reported what factors made it feasible or not feasible to deploy Aether from the care team’s perspective. Therefore

Nevertheless, our manuscript made the following recommendations to overcome identified barriers. 

"Future iterations could prioritize more inclusive language recognition, ensuring that staff and residents from various linguistic backgrounds can interact with AI systems more seamlessly. Also, it may be interesting to investigate the integration of deep learning technology for speech identification for service robots in group homes, as this may address the reported lack of adaptability and promote digital equity, allowing all users to fully benefit from the technology."

"LTC homes need to be prepared for changes in hierarchy, training and power dynamics brought by AI. Further, by recognizing the importance and benefits of service robot implementation in healthcare, necessary education initiation from school may help prepare future healthcare providers to become more familiar with and build competency in using service robots to facilitate patient-provider communications and expedite the work. Training from the institutions and facilities will also help increase the knowledge levels of service robots in the current workforce and will synergize with already educated incoming healthcare providers [48-49]. We call for more structural support to care homes in terms of human, technological and infrastructural resources to prepare for the adoption of AI from the macro level [50]."

In addition, we added the following sentence (highlighted in yellow) as new recommendations in promoting partnership: 

" In the future, researchers are recommended to investigate the impact of robot integration on workplace dynamics in different and care sites and care environments. Further, policymakers are recommended to work with care home leaders, staff, industrial partners and residents in developing strategies that nurtures collaboration and partnership in deploying different technology, including AI-enabled robots, in LTC homes.”

Comment 6: 

The conclusion of the article effectively synthesizes the main findings and reinforces the study's relevance, but it could be more objective and less repetitive in relation to the discussion. It is recommended to include more detailed practical recommendations for using the Aether robot in similar settings and suggest specific directions for future research.

Response 6: 

We agree with your suggestions. We updated our conclusion accordingly and appreciate your further feedback.

Comment 7: 

The study’s limitations are acknowledged but could be discussed in greater depth, considering how aspects such as participant selection (with higher interaction with the robot) may have influenced the results.

Response 7: 

Thank you. We added another sentence to address the bias you pointed out. It is available below, and also highlighted in yellow in the updated manuscript.

“Another limitation is selection biases. Staff interacting more with Aether were more likely to have good experiences with Aether and more likely to participate in interviews, which may influence results, especially the part about positive experiences with Aether.”

Reviewer 3 Report

Comments and Suggestions for Authors

The manuscript explores the feasibility and acceptability of deploying the collaborative service robot Aether in long-term care (LTC) homes, focusing on staff perspectives. Using Collaborative Action Research (CAR) and qualitative data collection methods, the study identifies key facilitators and barriers to integrating AI-enabled robots into care environments. While the research topic is relevant and timely, the paper could be strengthened by addressing some methodological, technical, and contextual gaps. Below are detailed recommendations for improvement.

 

The paper highlights that Aether's current functionality relies heavily on staff-initiated interactions, which limits its autonomy and adaptability in the LTC setting. This dependency on manual activation could reduce the robot's utility, particularly in resource-constrained environments where staff have limited capacity for such interventions. Drawing insights from “Data-Driven Learning for H∞ Control of Adaptive Cruise Control Systems”, the authors could explore the implementation of data-driven learning mechanisms to improve Aether’s autonomy. For instance, by leveraging historical interaction data, Aether could adapt to individual residents' preferences and behavioral patterns over time, enabling it to initiate interactions such as starting conversations or offering activities proactively. This enhancement would not only reduce staff workload but also improve the residents’ overall engagement and satisfaction.

 

The study also mentions challenges in handling multi-tasking scenarios, such as simultaneously addressing psychological support, activity facilitation, and safety monitoring. These demands highlight the limitations of Aether’s current system architecture. Drawing from “Distributed Real-Time Control Architecture for Electro-Hydraulic Humanoid Robots”, the authors could consider reconfiguring Aether’s control system into a modular and distributed framework. By segmenting functionalities such as emotional recognition, conversational logic, and mobility control into separate modules, the robot's response efficiency and stability could be significantly improved. A distributed architecture would also enable independent upgrades of each module, making Aether more adaptable to the evolving needs of LTC environments.

 

While the paper addresses resource constraints and high staff turnover as barriers to Aether's sustained deployment, it stops short of proposing concrete solutions to mitigate these issues. For instance, the limited training opportunities for staff and a lack of IT support during the deployment phase are significant challenges that could hinder the successful integration of Aether in other care settings. By introducing simplified operational procedures and automated troubleshooting systems, Aether could reduce its reliance on external technical expertise. Additionally, implementing AI-based training tools could help onboard new staff more efficiently, ensuring continuity in the robot’s usage despite staff turnover. These solutions could further enhance Aether’s scalability and long-term feasibility in similar care environments.

 

The study effectively employs CAR as its methodological framework, which is well-suited for addressing the complex dynamics of LTC settings. However, the potential limitations of CAR—such as the influence of researcher intervention on the deployment process—are not sufficiently discussed. The authors could enrich the methodological section by critically reflecting on how CAR may have shaped the findings and considering ways to mitigate these effects in future studies. Moreover, the relatively small sample size and the focus on staff perspectives limit the generalizability of the findings. Including perspectives from residents and their families could provide a more holistic understanding of Aether's impact and acceptance in LTC homes. Expanding the participant base in future research would strengthen the validity and applicability of the conclusions.

 

Overall, this manuscript addresses a significant and underexplored area of AI deployment in LTC homes. The research is methodologically rigorous and offers valuable insights into the challenges and opportunities of integrating service robots in care environments. 

Author Response

Comment 1: 

The paper highlights that Aether's current functionality relies heavily on staff-initiated interactions, which limits its autonomy and adaptability in the LTC setting. This dependency on manual activation could reduce the robot's utility, particularly in resource-constrained environments where staff have limited capacity for such interventions. Drawing insights from “Data-Driven Learning for H∞ Control of Adaptive Cruise Control Systems”, the authors could explore the implementation of data-driven learning mechanisms to improve Aether’s autonomy. For instance, by leveraging historical interaction data, Aether could adapt to individual residents' preferences and behavioral patterns over time, enabling it to initiate interactions such as starting conversations or offering activities proactively. This enhancement would not only reduce staff workload but also improve the residents’ overall engagement and satisfaction.

Response 1: 

Thank you for your great opinion! Aether could not initiate interactions during our five-month deployment period. The industrial partner did not programmed it into the way you mentioned “starting conversations or offering activities proactively”. Exploring the impact of an initiative Aether on staff’s workload and residents’ satisfaction is our future study.

Comment 2: 

The study also mentions challenges in handling multi-tasking scenarios, such as simultaneously addressing psychological support, activity facilitation, and safety monitoring. These demands highlight the limitations of Aether’s current system architecture. Drawing from “Distributed Real-Time Control Architecture for Electro-Hydraulic Humanoid Robots”, the authors could consider reconfiguring Aether’s control system into a modular and distributed framework. By segmenting functionalities such as emotional recognition, conversational logic, and mobility control into separate modules, the robot's response efficiency and stability could be significantly improved. A distributed architecture would also enable independent upgrades of each module, making Aether more adaptable to the evolving needs of LTC environments.

 Response 2: 

Thank you! In our future study, we will collaborate with industrial partners and investigate how by how to improve Aether’s adaptability in meeting the needs of residents and staff by implementing distributed architecture.

 Comment 3: 

While the paper addresses resource constraints and high staff turnover as barriers to Aether's sustained deployment, it stops short of proposing concrete solutions to mitigate these issues. For instance, the limited training opportunities for staff and a lack of IT support during the deployment phase are significant challenges that could hinder the successful integration of Aether in other care settings. By introducing simplified operational procedures and automated troubleshooting systems, Aether could reduce its reliance on external technical expertise. Additionally, implementing AI-based training tools could help onboard new staff more efficiently, ensuring continuity in the robot’s usage despite staff turnover. These solutions could further enhance Aether’s scalability and long-term feasibility in similar care environments.

Response 3: 

We agree. In our next stage of study, we aim to provide simplified operational procedures and automated troubleshooting systems for the staff members and manager to reduce their reliance on external technical experts. We also aim to developed AI-based training tools (hopefully within Aether itself) so that new staff can learn how to use Aether efficiently in care delivery.

Comment 4: 

The study effectively employs CAR as its methodological framework, which is well-suited for addressing the complex dynamics of LTC settings. However, the potential limitations of CAR—such as the influence of researcher intervention on the deployment process—are not sufficiently discussed. The authors could enrich the methodological section by critically reflecting on how CAR may have shaped the findings and considering ways to mitigate these effects in future studies. Moreover, the relatively small sample size and the focus on staff perspectives limit the generalizability of the findings. Including perspectives from residents and their families could provide a more holistic understanding of Aether's impact and acceptance in LTC homes. Expanding the participant base in future research would strengthen the validity and applicability of the conclusions.

Response 4:

Thank you for your suggestion. We added limitations of CAR in our paragraph of limitations as you suggested.

About the influence of researcher intervention on the deployment process:

We argue that researchers did infuence the deployment process informed by CAR, but the impact is positive. Hence there are more strengths than limitations. More details were as follows.

We conducted the study about feasibility and acceptability of Aether in a long-term care informed by CAR. The context was that the care home was short staffed and does not have enough human resource to test Aether and be responsible for handling any technical challenges. As a result, researchers were welcomed by the care home to deploy the robot and examine it each time in our site visit. During the stage, we also initiated in asking staff and residents what other things do you wich Aether could do. Care team’s voices were fully respected and addressed during the study process. We forwarded care team’s needs to the industrial partner, who modified Aether accordingly, and we tested Aether on the modified function in our next site visit. In this process, the care team worked collaborative with us and they shared equal power with researchers in accessing and upgrading Aether to be better tailored to local needs. In addition, our team consisted of multidisciplinary trainees, including existing and future caregivers, older adult partners, and senior researcher and health educator. It was the collaboration that made the deployment possible. The impact of our CAR process is consistent with the argument by Coghlan and Brydon-Miller that we have worked collaborative with each other to examine and develop the work. “This establishes an idea of collective activity, of which colalobration can be one form, at the core of the aspirations of action research.” (1)

1. Coghlan D, Brydon-Miller M. Sage Research Methods - The SAGE Encyclopedia of Action Research - Collaborative Action Research. In [cited 2025 Mar 5]. Available from: https://methods.sagepub.com/ency/edvol/encyclopedia-of-action-research/chpt/collaborative-action-research

Reviewer 4 Report

Comments and Suggestions for Authors

Dear authors, I read with interest your manuscript. Here my concerns:

-Introduction: if the study aim is about feasability (barriers and facilitators), then the reader may expect a dissertation about why a resident or staff member may want or may not want a robot in the facility. Even though in lines 45-46 a hint is provided about high workload in nursing homes, this is insufficent to understand the context. Moreover nothing is said about the resident perspective, but only general features of the robot. I suggest to develop more in depth this perspectives. Why would a resident like or need a Robot is the first question. Why one with Aether characteristics is another one (just non exhaustive examples).

-lines 150-155: why this home has been chosen? I suggest to highlight the criteria.

line 158: not clear if Aether was installed and left between one visit and the following or if Aether was present only when the study team was there. The latter situation makes the reader expect to consider the implication for the participants to be observed, but from the discussion it appears Aether was deployed for 5 months. I think it would be better to clearly state what the case is. 

-lines 74 and foll. : I think Aether description should be put in the materials/methods section of the manuscript, along with a clear statement abotu why this model has been chosen.

-line 224: Appendix 1 is nominated but could not find it.

-lines 194-224: Has a software of thematic analysis been used? if so, which one?

-Fig.3 I think that 2 pages of images to support the user friendliness of the materials are too many. I suggest move the figures into supplementary materials or resize (maybe just leave the second one).

-line 615: I cannot check what the E of HEART stands for. All the other letters are put in bold but not this one. Please fix it.

Kind Regards

Author Response

 Comment 1: 

-Introduction: if the study aim is about feasability (barriers and facilitators), then the reader may expect a dissertation about why a resident or staff member may want or may not want a robot in the facility.

Response 1: 

Thank you. I totally understand what do you mean. If a paper aims to report why a resident or staff member may want or may not want a robot in the care home, the study can usually be done before a robot is deployed, even designed. By understanding the preferences and expectation on an robot and the reasons behind from the perspectives of staff, researchers can write a paper to inform future design for such a robot.

In our case, Aether has been developed and evaluated, and was ready to be examined by us before the deployment period. That’s why our paper was focused on feasibility and acceptability of deploying Aether from staff and manager’s perspective in a LTC home. In other words, we explored how feasible is it to deploy Aether in the context, and factors facilitate or hinder deploying Aether.

That is why in our themes, we reported some features in the robot, some of environmental dynamics and some training and supports provided made Aether feasible to deploy. We also identified that in staff’s view, some other features in Aether, environmental factors and staffing crisis made it difficult to deploy Aether in the care home. We reported these findings based on the five-month deployment of Aether.

Even though in lines 45-46 a hint is provided about high workload in nursing homes, this is insufficent to understand the context. Moreover nothing is said about the resident perspective, but only general features of the robot. I suggest to develop more in depth this perspectives. Why would a resident like or need a Robot is the first question. Why one with Aether characteristics is another one (just non exhaustive examples).

More contextual information is provided in method. The focus of the paper is staff perspectives. We do plan to report residents’ perspectives about Aether in a separate paper, including their needs and preferences about an AI-enabled robot, and even over different types of AI-enabled robots.

Comment 2: 

-lines 150-155: why this home has been chosen? I suggest to highlight the criteria.

 Response 2: 

Thank you. We added reason that the care home was chosen in the updated manuscript.

“The home is operated by a non-profit association, subsidized by the government, was supportive to the deployment of Aether in their site.”

 Comment 3: 

line 158: not clear if Aether was installed and left between one visit and the following or if Aether was present only when the study team was there. The latter situation makes the reader expect to consider the implication for the participants to be observed, but from the discussion it appears Aether was deployed for 5 months. I think it would be better to clearly state what the case is. 

Response 3: 

Aether stayed in the care home between visits. I added this information in method section.

Comment 4: 

-lines 74 and foll. : I think Aether description should be put in the materials/methods section of the manuscript, along with a clear statement about why this model has been chosen.

Response 4: 

Thank you. In terms logic, we decided to introduce Aether at the introduction section because we would like to focus more on the underpinning framework, study design and research procedure in method, like what usually other papers do. Moving Aether into method may overwhelm some of the readers with too much information and less focus will be given to key elements in method (framework, design and procedure). In terms of structure, we think adding the information of Aether to introduction instead of method could make the overall structure of the paper more balanced.

We chose Aether because the industrial partner who agreed to collaborate with us has developed Aether.

Comment 5: 

-line 224: Appendix 1 is nominated but could not find it.

Response 5:

It has been uploaded as Appendix, which was not available to reviewers due to the setting of the journal. I will coordinate with the journal to make sure it is available to you.

Comment 5: 

-lines 194-224: Has a software of thematic analysis been used? if so, which one?

Response 5:

No software has been used, that is why in Step 3 of data analysis we reported that thematic analysis was conducted manually. Comment 6: 

-Fig.3 I think that 2 pages of images to support the user friendliness of the materials are too many. I suggest move the figures into supplementary materials or resize (maybe just leave the second one).

Response 6:

Thank you. We moved the first one to supplementary materials. Only the second one is left in the paper.

Comment 7: 

-line 615: I cannot check what the E of HEART stands for. All the other letters are put in bold but not this one. Please fix it.

Thank you. We decided to remove the acrynom.

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

All problems have been replied to adequately.

 

Author Response

Comments 1: All problems have been replied to adequately.

Response 1: Thank you very much! 

Reviewer 2 Report

Comments and Suggestions for Authors

Dear Authors,

This article can be accept in present form.

Best regards,

Author Response

Comment 1: This article can be accept in present form.

Response: 1: Thank you! We appreciate your warm words!

Reviewer 3 Report

Comments and Suggestions for Authors

Although the authors revised the manuscript, many parts still require improvement. Please try to improve the figures, tables, and scientific discussion. 

Author Response

Comment 1: Although the authors revised the manuscript, many parts still require improvement. Please try to improve the figures, tables, and scientific discussion. 

Response 1: Can you please provide more details so that we know what are your expectations exactly? For example, we appreciate you complete the sentence by "Please try to improve the figures, tables, and scientific discussion by doing xxx...". Thank you very much.

Reviewer 4 Report

Comments and Suggestions for Authors

Dear authors, 

my concerns have been addressed in a proper manner. I understand your arguments, which appear to be sound and clear. 

Kind Regards

Author Response

Comment 1: My concerns have been addressed in a proper manner. I understand your arguments, which appear to be sound and clear. 

Response 1: We appreciate your warm words! 

Round 3

Reviewer 3 Report

Comments and Suggestions for Authors

The current version can be accepted.