Emergency services are frequently called to attend mental health incidents and are looking for innovative ways to improve their responses and reduce the burden on services. Involuntary detention of people living with mental illness is considered more frequent than necessary, leading to increased pressure on emergency departments, and is often a traumatic experience for patients. The Police, Ambulance, Clinician Early Response (PACER) model was developed in 2019 in Canberra, Australia, and seeks to reduce involuntary detentions by embedding a mental health clinician into emergency services as a mobile mental health crisis response intervention. This protocol details a retrospective cohort study that will examine the association between PACER and involuntary detentions using medical and police records and compare the results to standard ambulance and police responses. We will use relative risk and odds ratio calculations to determine the probability of being involuntarily detained or diverted from hospital; and we will describe the patient characteristics and outcomes in the PACER cohort. Results will be reported using the STROBE checklist for reporting cohort studies. This study was not registered on a publicly accessible registry. There is some evidence of an increase in the prevalence of mental illness in Australia. The National Health Survey conducted by the Australian Bureau of Statistics reports that 20% of Australians experienced a mental illness between 2017 and 2018, representing an increase of 3% since 2007 ,5,6,7. MThe prevalence of mental illness is difficult to estimate globally. A systematic review of 174 surveys from 63 countries reported prevalence estimates from 1980 to 2013 .A Global Burden of Disease study estimated that the global prevalence of mental illness had risen from 665 million cases in 1990 to 970 million in 2019 21]. The 21]. The Patients attending the ED for mental health-related presentations tend to wait longer to be seen than patients who present for non-mental health concerns . In the ED activity data have demonstrated increased mental health-related presentations in the United Kingdom (UK) and United States (US), including significant increases in presentations by children and young people, particularly for self-harm-related symptoms ,24,25,26Each Australian state and territory has local mental health legislation which contains provisions for the involuntary detention of a person suspected to be living with mental illness, for the purpose of compelling them to an ED or hospital for compulsory mental health assessment. Those afforded these powers are typically doctors, mental health clinicians, police, and ambulance paramedics. In the Australian Capital Territory (ACT), the Mental Health Act 2015, Section 80 contains these involuntary detention provisions .Within the legislation, specific criteria must be met for the person to be involuntarily detained. Typically, the criteria for police and ambulance paramedics are lesser or more generalized than that of doctors and mental health clinicians, as they are not considered experts in identifying mental illness. Police and ambulance paramedics require only a reasonable belief that the person is living with mental illness, and that they pose a risk to themselves or others. However, a mental health clinician or doctor is required to distinguish mental illness with certainty, make a prediction that the person will deteriorate without immediate treatment, and, most notably, that the person is refusing treatment and care due to the symptoms of mental illness.Involuntary detention provisions provide invasive and restrictive powers that are allowed for the completion of that detention. This includes legal entry into the person’s home using force, such as breaching doors and windows, personal and property searching and removal of items, physical holds and restraint, and forcible giving of medication.In an Australian qualitative study, 122 patients who had direct contact with a police/clinician co-responder mental health crisis team were followed for 2 weeks after crisis contact . The autFurthermore, mental health legislation in Australia has a strong focus on least restrictive care, which is interpreted as the least intrusive course of action being considered before moving to more restrictive methods, whilst giving patients the right to refuse treatment or engagement with mental health services, where possible .A narrative synthesis review of qualitative studies explored patients’ experiences of involuntary detention during an acute period of mental illness . The revOther patients reported that the involuntary detention process triggered anger and rage, with corresponding dramatic escalation of agitation and behavioral disturbance, whereas others described withdrawal associated with feeling disempowered ,32,33,34Despite limited training opportunities to increase mental health literacy, the rate of mental health-related presentations being referred to ambulance services has increased ,15,35. AAn Australian cohort study examined the involuntary detentions by paramedics over a 3-month period, using medical records . The stun = 9014) [n = 4566, 51%) [n = 1003) were left in the community and the remaining were admitted to a hospital ward . The authors concluded that the rate of transport to an ED and subsequent discharge for people experiencing a mental health problem demonstrated a missed opportunity to improve patient outcomes and reduce the burden on services [These themes are consistent with international data which demonstrate a high prevalence of mental health-related presentations to ambulance services. A data linkage study examined the epidemiology of mental health-related ambulance calls in Scotland . The stuSeveral studies have demonstrated that mental health patients transported to an ED by police are more likely to be discharged home after assessment than those brought in by mental health professionals . One sucThere is evidence from observational research of increasing rates of involuntary detentions ,40,41,42An Australian study reported similar findings, demonstrating a 262% increase in the use of involuntary detentions by police and ambulance paramedics . The datWhilst involuntary detention will always be appropriate for certain patient presentations, there are several well-documented justifications for reducing the overall numbers including reducing trauma, reducing demand on health and emergency service resources, and consistency with overarching strategic mental health plans and standards. The increasing prevalence of mental illness, corresponding ED presentations, and increased rates of involuntary detentions add further resourcing and financial burdens on health and emergency services with negative impacts on hospital wait times and patient experience. With this in mind, alternative options to divert patients from hospital into community mental health services may be an appropriate and efficient intervention.The ACT has in place the Mental Health Act (2015) which gives involuntary detention powers to doctors, mental health clinicians, police officers, and ambulance paramedics .In the act, police and ambulance paramedics have very general criteria to meet, whereas doctors and MHOs have stricter, more extensive criteria, given that they are expected to make a more informed clinical assessment of the patient.This difference in criteria is associated with greater numbers of patients being involuntarily detained by police and ambulance paramedics than with doctors and clinicians. Furthermore, those detained by doctors and clinicians are significantly more likely to be admitted to a mental health inpatient unit. This can be interpreted as doctor and clinician application of involuntary detention provisions being more clinically informed than those invoked by police or ambulance.Due to the stark differences in criteria under the act, the ACT has observed a significant increase in patients being placed under involuntary detention by emergency services, with approximately 86% being assessed as not requiring hospitalization, and subsequently discharged. The rate of patients being brought into an ED under involuntary detention by the ambulance service is approximately four times higher than the number of patients brought into an ED by clinicians. Police also bring in a high number of patients subject to involuntary detention who go on to be released immediately after assessment. For the purpose of this research, these are considered “unnecessary” in that the person was involuntarily detained, assessed, and released as requiring immediate treatment and care for their mental illness, as defined in the act.The Police, Ambulance, Clinician Early Response (PACER) model differs from usual service provisions as a tri-response mobile emergency mental health service that provides a mental health clinician, police officer, and ambulance paramedic who attend mental health crises in the community together in a first responder vehicle. PACER can act as either a primary or secondary police/ambulance response and has access to mental health background information and the three agencies’ electronic records. From the perspective of the patient, PACER offers early intervention to a mental health crisis, potential diversion from hospital ED, avoidance of potential delays, and may reduce involuntary detentions, use of force, and associated trauma.The police officer has the primary role of maintaining the safety of the patient and the PACER team, the paramedic has the role of providing medical care including medical clearance, wound care, and emergency care; and the clinician has the responsibility for the patient’s mental health assessment and involuntary detention decision making.Few tri-response PACER models are in operation around the world. Co-response models are being utilized more frequently, which pairs a police officer or a paramedic with a mental health clinician to respond to mental health-related presentations. Of these models, many are a secondary response service, meaning that emergency services will already be on scene, and will refer to the co-response model following initial assessment.An evaluation of the co-response ‘Street Triage’ model in Birmingham and Solihull National Trust UK found a reduction in the number of involuntary detentions invoked, and the cost of the Street Triage model was offset by these reductions .A further evaluation of the West Midlands ‘Mental Health Triage’ model identified several benefits including improved patient outcomes, a positive cultural shift in the way emergency services view mental health crises, improved service collaboration, and more collaborative information sharing .In 2016, an evaluation of nine sites in England was undertaken and assessed the impact of street triage on involuntary detentions . The evaA descriptive study of the “Psychiatric Emergency Response Team” (PAM) paramedic and clinician co-response service in Stockholm County, Sweden, was undertaken over a 12-month period . Data weIn an Australian evaluation of the Northern Police and Clinician Emergency Response (NPACER) co-response police and clinician model, trend analysis and cross-comparison found that NPACER reduced involuntary detentions by 86% when compared with the single police-only response [Police and clinician co-responder models and their effectiveness were examined in a systematic review in 2018 . Twenty-Further qualitative research examining police officers’ attitudes to responding to mental health crises demonstrated that police often invoke involuntary detention in the absence of other mechanisms to support the person in the community, and they felt that mental health co-responder models provided a good alternative to detention and transport to an ED .A further literature review did not produce any research into the tri-response PACER model’s effectiveness or association with involuntary detentions. Whilst there are some studies examining the police/clinician or ambulance/clinician co-response models, tri-response models have not yet been evaluated and may yield different results. The PACER model in the ACT is adopted from the tri-response Birmingham UK model and has the capacity to operate as a first responder team.The aim of this study is to determine the association between three approaches to responding to an acute mental health crisis  and rates of involuntary detentions, and to estimate the strength of that association. Objective one is described in Rates of involuntary detention will be lower in the PACER cohort than the police and ambulance cohorts, and PACER rates of post-detention hospitalization will be higher.This is a cohort study using a retrospective design over a 12-month period using records from December 2019 to December 2020.Retrospective cohort studies allow researchers to formulate ideas about the associations and potential relationships between the independent variable  and dependent variables  without determining causal effect ,49,50,51There are several strengths to retrospective cohort studies. These include large sample sizes and statistical power based on the availability of large databases of data which have already been collected ,49,50,51This study will use PACER as the exposure, and police and ambulance cohorts as comparison.The study pertains to a single site in the Canberra Region, Australian Capital Territory (ACT).Canberra Health Services provides a comprehensive range of governmental primary, secondary, and tertiary public health services to the ACT region. Mental Health, Justice Health and Alcohol and Drug Services (MHJHADS) is a division within Canberra Health Services and includes inpatient mental health and assessment units, crisis assessment and management teams, community mental health and outpatient psychiatry teams, rehabilitation services, and step up/step down facilities across all age groups.Under the Mental Health Act 2015, all patients subject to involuntary detention must be brought to the Canberra Hospital Emergency Department as an approved facility for involuntary assessment . The CanThe participants included in this study are those who have received either a police, ambulance, or PACER response for a mental health crisis. For the purpose of this study, participants are those who are experiencing a mental health crisis where 000 police or ambulance emergency assistance has been requested. Generally, calls to emergency services demonstrate an immediate need for response and may include suicidal behavior, self-harm, or psychotic illness.The sample will include all PACER, police, and ambulance responses to mental health crises between December 2019 and December 2020.Occasionally, PACER will be diverted to prioritize time-critical jobs that are not related to mental health patients, such as cardiac arrest, if they are the closest emergency vehicle within range of the incident. These incidents will be excluded as they do not relate to the study.The ACT Policing Communications Sergeant is responsible for dispatching PACER through the 000-emergency system. This includes communicating with the ACT Ambulance Service and mental health services using a triaging system to determine which agency should respond in the first instance. The protocol is confidential, but is dependent on availability, location, and the likelihood of requiring a secondary team.Permission to conduct this retrospective cohort study was granted by the Canberra Hospital Service Clinical Ethics Committee and the La Trobe University Human Research Ethics Committee prior to conducting the evaluation.Section 2.3.10(a): This research carries no more than low risk as the project will be at a cohort level, and not an individual level.Section 2.3.10(c): It is impractical to obtain consent from patients, as they are subjected to mental health orders and/or guardianship orders. Seeking consent may cause more distress for the person/s responsible than not seeking consent.Section 2.3.10(e and f): There is sufficient protection of their privacy, as individual identifiers will not be collected as part of the project.Section 2.3.10(g): Currently, there is a high rate of unnecessary involuntary detention of people living with mental illness in the ACT. The outcomes of this evaluation will provide evidence for the improvement in service delivery for groups of very marginalized and vulnerable people, through providing least restrictive and patient-centered options for assessment, treatment, and care. The request for a waiver of consent is considered justified as the benefits of the evaluation greatly outweigh any potential risks.The ethical consideration for this study is that of patient consent to participate in the study. We sought and were approved for a waiver of consent for use of patient records as per Section 2.3.10 of the National Statement on Ethical Conduct in Human Research. The request for a waiver of consent was based on the following:The primary study outcome is the rate of involuntary detention in the three cohorts. Involuntary detentions will be compared with the total incident number to determine the rate of detention by cohort .Post-detention hospitalization will be explored using involuntary detention data. Post-detention hospitalization is the process whereby a patient who is subject to involuntary detention is then hospitalized in a psychiatric unit for that episode of care. It is considered that hospitalization justifies the use of involuntary detention, as the patient’s mental illness was acute and requiring emergency assessment at the time that the involuntary detention was invoked.Additionally, this study will review hospital diversion within the PACER model. Hospital diversion is defined as a process whereby a patient is assessed, and a treatment plan established in the community, negating the need for transfer to hospital. Hospital diversion data will be extracted from the PACER data collection form. For every PACER job, the police officer and paramedic will be asked if they would have invoked an involuntary detention if they were working outside of PACER in their general duties. This data will provide further evidence about the association between PACER and involuntary detention.Finally, the study will describe the characteristics of patients assessed by PACER including formulation, diagnosis, outcome, and general grouped demographics such as utilization by age.Copies of involuntary detention forms and secondary statistics kept by the Office of the Chief Psychiatrist will be used to extract data relating to the number of involuntary detentions invoked by PACER, police, and ambulance. The data will be used to measure the rate of involuntary detentions, post-detention hospitalization, and hospital diversions for each cohort. Post-detention hospitalization will be calculated using involuntary detention data from the Mental Health Tribunal Liaison and Mental Health, Alcohol and Drug Service, Justice Health, Integrated Care Record (MAJICeR) databases.The PACER data extraction form is completed collaboratively by the PACER team for each presentation and is stored in the CHS electronic record. These records will be used to extract PACER case mix and outcome data.Reducing the amount of missing data through mandatory documentation policies;Cross-referencing of PACER data forms by researchers, mental health clinicians, and police for finalization and closure;Calculating the sample size needed to measure effect;Recovering the missing data through contacting the author of the PACER forms to request completion;Further investigation of the clinical files by the researchers, depending on the missing variable;Calculating randomness using Little’s MCAR test.As this is a retrospective cohort study, participant drop out or “loss to follow up” is not a factor which would potentially cause bias. However, the retrospective approach can increase the risk of bias through the greater likelihood of missing data ,49,50,51We consider that there is a potential for missing data across different datasets, however, this is likely to be in small numbers based on the strict documentation protocols within the three agencies. However, this may be a single missing variable within the PACER data form, or a PACER data form completely missing.If the listed strategies do not resolve the missing data, we will undertake single or multiple imputation depending on what data are missing. Single imputation refers to the missing variable being replaced with a single value that would best represent the mechanism of the missing data ,53. MultMental health incident data from police and ambulance will be provided only as total number of jobs for the study period. Whilst there is a possibility that jobs may have been coded incorrectly, this is unlikely to be a significant source of bias, although it cannot be adjusted for, as missing data cannot be identified due to the reporting systems of each database.We consider that participants in the two police and ambulance cohorts are representative of the participants in the PACER cohort, as they meet the same inclusion criteria, minimizing the risk of selection bias.Confounding is common in observational studies and refers to an unknown variable which distorts the effect being measured, leading to an under- or over-representation of the association between the variables ,49,50,51A likely confounder is the risk of hospitalization by diagnosis. For example, a person experiencing a situational crisis or emotional dysregulation may be less likely to be involuntarily detained than someone who is acutely suicidal or psychotic. We will use multivariate regression analysis to build a regression model for the outcome and exposure, as well as the various diagnostic variables. The effect of the variable of interest  can be examined with confounding variables held constant. This will only be possible for the PACER data, as police and ambulance data provide only job numbers within the study period.Repeat participants can represent a challenge in observational research as repeated presentations can skew data in a particular direction. We will screen for this during the data extraction phase with consideration to omitting participants whose repeated presentations may cause bias in the data analysis.Sample size is an important factor in determining the validity of the study in terms of the statistical power necessary to reject or accept a hypothesis. Correlation observational studies such as cohort studies use a null hypothesis (PACER does not reduce involuntary detentions), which is set to be rejected with an alternative hypothesis (PACER does reduce involuntary detentions) ,49,50,51Effect size refers to the difference expected in the study outcome as a result of the intervention being measured and refers to the magnitude of the relationship between the two variables ,55,56. WDespite extensive review of the literature, we were unable to obtain any studies relating to the tri-service PACER model which explored rates of involuntary detentions. Instead, we referred to a trend analysis and cross-comparison study of the police and clinician co-response NPACER model in Victoria, Australia, to determine the association of NPACER and involuntary detentions . Within We will use the STATA statistical software, version 18.0  package for data management and analysis.We will use relative risk (RR) calculation to determine the risk of being involuntarily detained in the PACER, police, and ambulance cohorts. Relative risk refers to the probability of an event occurring in the exposed group versus the probability of the event occurring in the non-exposed group, and we will calculate this using standard calculations ,58.Following calculation of the RR, we will determine the confidence interval (CI) to measure the degree of certainty of the study sample using standard CI calculations. A 95% confidence interval will contain the true value of the risk ratio 95% of the time and represents a high degree of certainty . We willWe will use logistic regression using univariate and multiple analysis including gender, age, and diagnostic formulation as independent variables and involuntary detention as the dependent variable. We will use multiple analysis to control for potential confounding amongst the variables. Using this method, we will estimate the probability of being involuntarily detained or diverted from hospital by variable, expressed as the odds ratio (OR). Whilst there is no comparator for hospital diversions, these data will provide further understanding of the capacity of PACER in meeting its initial targets of linking patients with community support or de-escalating a social crisis, and accurately identifying those patients who do need to go to hospital for treatment.We selected RR in our analysis of rates of involuntary detention across the cohorts, as this represents the probability of occurrence of an event or outcome. Given that we are using PACER as the exposure group and police and ambulance as the non-exposed group to examine involuntary detentions as the outcome, we consider RR to be the most appropriate analysis to answer our research question.Alternatively, we selected OR for the logistic analysis, as this also indicates the nature of the association between the exposure and is a common calculation method for multivariate analysis technique.Finally, we will describe the patient characteristics and outcome of patients assessed by PACER, using total and percentage.The primary risk in this study relates to data security and integrity, as well as the deidentification of data. We have developed a strict management plan for the storage, deidentification, re-coding, disposal, and checking of data, which is consistent with national and local legislation and hospital policies and procedures.Privacy Act 1988 [Health Records (Privacy and Access) Act 1997 (ACT) [Extracted data will be stored in the CHS  information technology system. The system has high levels of protection as per the Commonwealth Act 1988  and the 97 (ACT)  includinDuring the extraction phase of the study, we will not extract identifying patient data such as name, date of birth, address, or any other identifying data. We will not record a patient’s age; rather, we will code into three age groups, adding an extra layer of security.At the end of the study, the research database will be archived within an allocated business folder of the CHS database. We will follow the CHS procedures and national and local legislation.At the end of the study period, archived data will be destroyed after seven years via the CHS Clinical Records Service, following standard data disposal processes defined in the policy.Error in data entry may occur when PACER clinicians complete the PACER data extraction form. Checks will be undertaken to identify unlikely values such as ages outside of 8–90 years.We will cross-reference the PACER data extraction form with the various electronic records to reduce systematic errors. The form will be cross-referenced by the police officer before sending it to the PACER project team.It is unlikely that duplication of data will occur, given the high level of documentation requirements for each patient’s job.Data extracted will be re-coded into new variables and applied to a code book.We will present our findings using the STROBE checklist for reporting cohort studies. We will provide total participant numbers for the PACER, police, and ambulance cohorts and RR calculations for both involuntary detention and diversion from hospital. We will provide standard logistic regression tables for involuntary detentions and diversion from hospital for the three cohorts. We will present characteristic data of PACER presentations, including age and gender demographics, reason for PACER presentation, formulation, and outcome, displayed in tables using total distribution and percentage.We will provide a comprehensive discussion of the study findings and their interpretation and describe the limitations of the study and opportunities for future research.Identifying patient data will not be included in the evaluation results.Whilst observational studies are an effective and robust method of establishing association, some limitations exist. The retrospective approach increases the likelihood of bias in the cohort or experimental group as the risk of missing data is higher ,51,52,53Presentation is a potential confounder for this study, as highly agitated or violent patients may be more likely to get a full police response than a PACER response, which has only a single police officer, and a person living with mental illness suffering severe injuries is more likely to receive an ambulance response.The study cannot adjust for individual decision making of PACER staff. Whilst all PACER staff were recruited against high standards of crisis experience, it is possible that some clinicians will be more risk averse than others.Imputation requires the researcher to carefully consider the plausibility of the causes of the missing data ,53. SingThe involuntary detention data from the police and ambulance data have not been tested for validity or reliability and may be subject to misclassification bias due to incorrect categorization within the relevant reporting systems. Because data systems within the police and ambulance service are different, we are unable to distinguish between non-differential and differential misclassification, should it occur.This study will provide evidence of the effectiveness of the PACER tri-response model through measuring the association between the model and the rate of involuntary detentions. To date, very limited data exist that explore the impact of the tri-response model of PACER, particularly its capacity to reduce involuntary detentions and emergency department presentations. This study provides evidence for the value of inserting mental health clinicians into the emergency services space and the capacity for upskilling and changing the culture of emergency service personnel when working with people living with mental illness. The results of this study will inform health services and policy makers in guiding decisions relating to mental health crisis interventions relating to emergency services.


This study offers an integrated service management system for rural tourist information based on a cloud platform to address the three main issues of high platform concurrency, difficulty storing and managing data, and trouble sharing data functions. Three levels—data, process, and architecture—are considered in the analysis and design of the platform. The Hadoop data storage system makes possible the collection, storage, administration, and exchange of data functions for large amounts of heterogeneous data from many different sources by utilising Netty data transmission technology, hybrid data storage technology, and the Web Foundation. The results demonstrate that the system’s response time is low, and the CPU consumption time and the average utilisation rate meet the actual needs. They resolve issues with the current rural tourism platforms application, such as the difficulty of data collection, the low rate of reuse, the low rate of sharing, the lack of timely updates, and severe island phenomena. The state has attached great importance to tourism development in various regions in recent years and constantly introduces new development measures. As a part of intelligent tourism, characteristic rural tourism has become essential to supporting the economy . ManagerSome experts put forward more suggestions for the research of tourism management systems. Through comprehensive analysis of relevant research results worldwide, they put forward that smart tourism should be guaranteed by appropriate technologies to provide practical help for relevant tourism information, tourism routes and various reservation services. It is considered that the government and relevant tourism management departments should provide appropriate assistance as the starting point, and do an excellent job in transportation service providers, tourism commodity providers and other service providers . The funWith the continuous gathering of tourism platform data, the rural tourism collection subsystem will collect more and more data, and the data transmission within the platform will be more and more frequent. Suppose the traditional data transmission mode is used for data transmission. In that case, the server will switch threads frequently due to too many opened lines, which will cause many server resources to be occupied . As a reTherefore, the platform has modified the data transmission mode, using the non-blocking I/O (NIO) method to complete the data transmission. NIO has three core components: buffer, selector and channel. The buffer is a memory buffer, the channel is an operation channel to access I/O, and the selector is a multiplexer to manage multiple channels by one thread . In NIO,The rural tourism data transmission technology based on Netty can avoid the system crash caused by the super high concurrency of the server, which is essential for the operation of the rural tourism cloud platform.The rural tourism cloud platform designed in this article adopts the storage mode of MongoDB NoSQL database and Hadoop distributed file system based on distributed data storage tools. Its system is composed of multiple computer nodes, which can communicate and coordinate with each other.Since MongoDB is document oriented and supports data storage with a disordered structure, it fits well with the data characteristics of rural tourism, which is very suitable for storing rural tourism data . At the In addition to MongoDB distributed storage tools, Hadoop distributed file system is also used to construct data storage subsystem . This isAs shown in HDFS is the underlying foundation of Hadoop to store massive rural tourism data. HDFS sliced the rural tourism historical data into chunks and kept them in different rural tourism servers .We require a tool that can rapidly and effectively interface with the front-end rural tourism service platform subsystem and the background rural tourism data storage subsystem to construct a cloud platform for rural tourism. At the same time, Django may be more effectively connected with the finished part because Django is primarily used for programming design in rural tourist platforms . The ModThere are three key technologies: rural tourism data transmission method based on Netty, mixed rural tourism data storage technology and rural tourism web framework. The application of these key technologies effectively solves the problems of difficult storage and scheduling of massive data encountered in the construction of rural tourism cloud platforms, realizes the rapid interaction and rendering of data between the subsystem of data storage and the subsystem of service platform, and lays a technical foundation for the development and use of data sharing mechanism.Because there are many modules on this platform, it is difficult to maintain the code to avoid the confusion of platform construction. Therefore, before the construction of the platform, the overall design of the platform architecture is made. The overall architecture of the platform is divided into four parts: the data acquisition layer, the big data storage and management layer, the service and application layer, and the security system. The overall architecture of the cloud platform is shown in etc.As a continuous provider of multi-source heterogeneous cloud platform data, the data acquisition layer mainly includes basic scenic spot information, video audio, panoramic photos, microblog comments, Ctrip comments, and rural tourism-related news and activities information in the official websites of prefecture-level cities and scenic spots. The data collection is mainly realized by Python-based web crawler technology. At the same time, some data need to be collected manually or generated automatically by the platform, such as basic information about scenic spots, system logs, The primary objective of big data storage and management is to achieve unified storage, mutual scheduling and effective management of rural tourism. It provides adequate data support for the cloud platform to build a harmonious and standardized sharing mechanism. At the same time, according to the different characteristics of multi-source heterogeneous rural tourism big data, appropriate storage methods should be used for storage, and a unified rural tourism visualization management and query demonstration application should be established.All platform services are supported by the service and application layers. Additionally, when utilizing the platform, users can directly access these tiers. The following services make up the platform’s main business units: By getting access to the service layer’s API service—the phrase used to describe how the platform developers package the data and resources in the platform into API services—the application layer can indirectly access the rural tourism data storage subsystem. Security assurance system mainly refers to avoiding the frequent access of external users to the open and shared API interface, resulting in excessive pressure on the system server and affecting the system’s regular operation .Data is the starting point and core of the platform construction. The data sources of the platform are summarized into five categories: basic information about scenic spots, data on scenic spot reviews, media information about scenic spots, virtual reality information about scenic spots and user behavior data. Due to the different characteristics of the five data types, storing the data without resolution will lead to data confusion, difficulty in management and data redundancy. To solve the above problems, the five data types are summarized and divided into scenic spot, behavior, and platform data. The rural tourism data storage subsystem is established to unify planning data collection and storage methods. According to the actual data characteristics, different data collection methods and storage methods are adopted, and unified standards are formulated, which realize the efficient storage and management of data. When the rural tourism data acquisition subsystem works, it also needs to conduct data docking with the data storage subsystem in addition to using its own multiple collectors. In this process, the collected data is uniformly connected to the database through communication services.Afterward, through the construction of the rural tourism service platform subsystem, it provides dynamic analysis, word cloud analysis and other functional interfaces and data resource sharing interfaces to realize the exchange and sharing of data and functions. It can enhance the sharing ability of data and operations of the cloud platform and facilitate the client to call data and function resources more conveniently.According to the overall architecture design, the rural tourism cloud platform consists of a data collection layer, big data storage and management layer, service and application layer and security system. However, to complete the actual landing development of the platform, it is necessary to build corresponding subsystems to realize the business functions. The application architecture of the platform is shown in The rural tourism service platform subsystem can be divided into server and client. The server is responsible for transforming the data of the data storage subsystem and the functions developed in the platform into accessible service API through the Django framework for internal application and sharing with external users. The client includes a government enterprise client and a scholar visitor client. According to the different functional requirements of the two kinds of clients, the corresponding API in the server is read respectively, and the client website of the service platform subsystem is finally formed by rendering the web page.The rural tourism data acquisition subsystem must be connected to the data storage subsystem to use its many collectors. The obtained data are combined into the database using the communication service in this step. Because these network data are generated at different rates daily, the data acquisition terminal must select different collection periods based on different speeds, such as the slower generation rate of Ctrip and news and the faster generation rate of microblog and environmental data. The actual data update for this article can be found in The rural tourism data storage subsystem is the transition between the data acquisition and service and application layers, which can be divided into the storage and quality control parts.The quality control part is an essential cornerstone of rural tourism data storage to ensure the correctness and reliability of the data. Due to the complexity of the data on the Internet, reliability is low without quality control. Therefore, a quality control module is developed for microblogs, Ctrip and news, which can automatically monitor and control the reliability of the access platform data from the server back-end to ensure the accuracy and reliability of the data in the platform.Both the server and client have a data storage subsystem to provide data support, and the Django framework is used to build the server within the platform. At the same time, the client also needs to use The Django web framework to interact with the back end. The server mainly provides data and available services for the platform client and establishes a unified and standardized data-sharing mechanism .The client provides corresponding functions for different user types. Users can provide services directly through the platform, dynamic analysis, and word cloud analysis. After the model training is implemented through the service API, the test set calculation results are input and uniformly calculated by the cloud platform. Users can directly obtain the result data after completion.The server includes two aspects: data service and function service. The function service mainly includes emotion analysis service and word cloud analysis service. Affective analysis service provides two sentiment analysis methods: text sentiment orientation discrimination based on syntactic rules and sentiment dictionary and text sentiment recognition based on deep learning . Users cetc., to help the relevant users of government enterprises fully manage the picturesque areas for rural tourism within their control. The scholar tourist terminal built the home page, personal center, tourism map, resource center, data crowdsourcing, and other helpful modules. Through the analysis and study conducted utilizing the platform’s data and function ports, which are available to the public, users can gain more knowledge about the general status of rural tourism.Government enterprises and student travelers are two different groups in the market. The government enterprise side has developed function modules. These include collection management, data management, emotional map, dynamic analysis, open approval, https://www.ctrip.com/) 156 addresses. Then, use selenium 3141 + webriver + chromedriver to simulate the scene of users using the Ctrip tourism platform. Through automatic access, click and slide, collect the website source code and analyze and sort out the required data. Because of the massive amount of code, only part of the background code of the Ctrip collector is shown for reference, as follows:First, the website of rural tourist attractions on Ctrip was collected manually, and a total of rural tourist attractions were collected on the official website of Ctrip The data storage module of the rural tourism data storage subsystem mainly uses MongoDB. It is suitable for storing user information, environmental parameters and other information in scenic spots, scenic spot basic information, microblog data, Ctrip data, news information, system logs and other data with time sequence and high frequency. Taking the environmental parameters as an example, it is appropriate to use the MongoDB database to store such long-time series data because of its fast updating, high frequency, and real-time data characteristics. The data file structure of regional weather and air quality information is as follows:https://zenodo.org/record/5643728#.ZEYYjXZBzGI; when the server receives the request, it maps the corresponding method show according to the path “index / GL / Weibo.” After confirming that the operation is correct, the query can be processed, and then the results are packaged into JSON format data and returned to the front end. Finally, the front end gets the data for rendering and presents it to the user.The specific workflow of the server interface is as follows: the system background service is developed by the DjangoMVT framework, the rural tourism data storage subsystem provides data support for service API, the front-end sends HTTP requests to the server through browser Ajax, which is the API interface to call back-end services (for example, Government agencies and student tourists make up the majority of the clientele. The front-end framework of the enterprise government client and the scholar tourist client is built using front-end languages such as HTML, CSS, and JavaScript with the assistance of the server side of the data storage subsystem and the service platform subsystem. The client functions are examined and created based on the functional requirements. The built-in front-end client is then integrated with the back-end server using Django, and clients for rural tourism government enterprises and rural tourism scholar tourists are achieved.In terms of server configuration hardware in the development process, the network bandwidth uses 100 m shared bandwidth, and the server CPU uses Zhiqiang v5608, 3.5 GHz, four core. The memory is DDR4 16g memory, hard disk 320G capacity. The number of servers is four, which are used to manage applications, files, databases and videos.4G memory is used in the computer configuration of the development side, Pentium G5680 3.5 GHz, hard disk 120 g solid state disk. After the development of the system, it is released to the server for testing.The system’s concurrent access does not imply that it will allow access from many users simultaneously, but that new users will continuously join. The interval duration is set to 10m for the particular test connection, which means that 20 concurrent users will be added automatically every 10 min to track changes in system performance characteristics. The maximum CPU usage is 13.189%, which is lower than the average of 80%. There is no hardware bottleneck in the system’s virtual environment, as indicated by the hard disk’s maximum and minimum values of 0.332 and 0.000, respectively, which fall within the usual range of 00 to 20.Every 10 s, five concurrent access users are added to the test script so all simultaneous users can simultaneously utilize a specific platform function. As more concurrent users are added, the performance metrics of the application server are tracked. To ensure that the system can scale, 500 simultaneous access users are tested without considering time while measuring the system’s performance. The actual number of concurrent users on the platform will be 300.The system’s minimum response time of 5S and average access time of less than 2.959s, respectively, fulfill the actual needs. While the average calculation is less than 12.626%, which follows the usual requirements, the CPU utilization rate of the system reaches 57.553% when concurrent users request many data. The findings indicate that the total contemporary access process’s average memory consumption rate is 680m, which is within the acceptable range and satisfies the actual needs.The system contains 130 test cases in total. In the end, 130 test cases are conducted after extensive testing, of which 102 are successful and 28 are not done correctly. After examination, it has been determined that several of the 28 test cases were unsuccessful because of flawed system function flow designs, others were due to incorrect system page links, and a few were due to data format inspection without judgment.The system performance test primarily examines throughput, CPU time used for database operations, CPU utilization, average transaction response time, and other metrics. The results show that the system’s response time is low, and the CPU consumption and average utilization can meet the actual needs.The system adopts the SSM framework, which is convenient for the classification and management of data information and reduces the amount of code to write programs to a large extent. Then the text emotion algorithm is combined with the scenic spot recommendation system, which can achieve the synergistic effect in scenic spot recommendation and applies to the travel recommendations. With the increase in historical behavior of user comments, the synergistic effect will be gradually obvious, to better meet the individual needs of users and, to a large extent, improve the efficiency of information retrieval.This study develops a comprehensive service management system for cloud-based information on rural tourism. The data storage subsystem solves the problems of rural tourism data in multi-source heterogeneous data storage, transmission, and management and realizes the unified storage and effective management of rural tourism data by using MongoDB and Hadoop hybrid data storage mode and using the Netty framework to build an efficient transmission server. The service platform subsystem can assist government enterprise users with the efficient management of scenic areas and platform data, as well as with the rapid acquisition of rural information for researchers and the provision of all-inclusive rural tourism services for visitors. The test results demonstrate that the system has a fast response time and that its average CPU utilization and time may match the actual demands. However, the method proposed in this article does not perform a horizontal comparison of various scenic locations in a given area, which is also the future research focus for system optimization. Due to anti-crawler means on some websites, some data types cannot be read directly by the interface and can only be collected by selenium + webdriver and other means. While the Internet update iteration speed is fast, the code needs periodic maintenance to avoid the failure of the crawler and the failure of normal data collection.10.7717/peerj-cs.1334/supp-1Supplemental Information 1Click here for additional data file.10.7717/peerj-cs.1334/supp-2Supplemental Information 2Click here for additional data file.


Emotion regulation difficulties have an important role in the presence of negative self-image. These problems in the self-regulation of emotion could lead to negative emotional processes (such as anger) that can lead to body dissatisfaction. Therefore, the aim of the present study was to examine emotion regulation difficulties than can negatively impact self-image and to understand if anger acts as mediator in the relationship between emotion regulation and body dissatisfaction.A cross-sectional study was carried out comprising 565 young adult women aged 18–30 years. The participants were administered the Difficulties in Emotion Regulation Scale (DERS), the State-Trait Anger Expression Inventory 2 (STAXI-2), and the Body Dissatisfaction dimension of the Eating Disorder Inventory-2 (EDI-2). The proposed hypotheses were tested by path analysis in MPlus 8.0.The results indicated that anger had a positive significant effect on body dissatisfaction as well as the non-acceptance of emotional responses, the lack of emotional awareness, and the lack of emotional clarity. Of all the dimensions of emotional regulation difficulties, impulse control difficulty was the dimension which had a positive significant indirect effect on body dissatisfaction explained by increased anger.The present study suggests the importance of emotion regulation in the prevention of body dissatisfaction. Impulse control difficulty may be the key emotion regulation emotion in explaining the increments of anger that lead to body dissatisfaction. Among young adults, the promotion of positive body image can be promoted by helping this population to self-regulate their anger impulses. Body dissatisfaction is defined as an individual’s negative evaluation of his or her own body due to the discrepancy between the perceived actual body shape and the desired ideal . In receBody dissatisfaction is prevalent in the general population, but it is also a potential risk factor for the development of eating disorders (EDs)  and reprIn recent years, self-discrepancy theory  has beenAdditionally, difficulties in emotional regulation, that is, difficulties by individuals in influencing the onset, intensity, and duration of their emotions  predict Regarding the influence of negative emotional states on the development of body dissatisfaction, this is consistent with Alireza and Padhy , who obsIn addition, individuals with EDs tend to repress and internalize their anger excessively , 25. ThiAs demonstrated, difficulties in emotional regulation and negative emotions play an important role in the development and maintenance of EDs. Although the predictive role of difficulties in emotional regulation among individuals with EDs is well established, the relationship between difficulties in emotional regulation and body dissatisfaction has been little studied, as well as the factors that may influence the association. Likewise, although the increase in body dissatisfaction in the face of negative emotions such as depression, anxiety, and stress has been investigated , few stuIn addition, it has recently been noted that current treatments for EDs have limited long-term success, in part because the psychological processes involved are not well understood . MoreoveM = 20.72 years, SD = 2.29) participated in the study. As shown in A total of 565 young women aged 18–30 years . Items are rated using a Likert-type format from 0 (Never) to 5 (Always) and summed to provide a total score on the subscale. In the present study, the Cronbach’s alpha coefficient for the body satisfaction subscale was 0.89.The “body dissatisfaction” subscale of the Eating Disorders Inventory-2  which indicated that the hypothesized model fitted the data adequately. This model explained 30% of the variance in anger and 19% of the variance in body dissatisfaction which indicated a large and medium effect size, respectively.The hypothesized model was tested with path analysis including the sociodemographic indicators with significant effects on the dependent variables as covariates see  (i.e., bThe direct effects shown in The indirect effects of the emotion regulation difficulties on body dissatisfaction were also tested see . Of the The first objective of the present study was to analyze the relationship between difficulties in emotional regulation, anger, and body dissatisfaction. The results showed that all the variables of the study were positively and significantly correlated with each other. Therefore, higher levels of difficulties in emotion regulation were related to greater body dissatisfaction. There is a consensus in previous literature that difficulties in emotion regulation play an important role in the etiology, maintenance, and severity of EDs. Accordingly, previous studies have shown that as difficulties in emotion processing and regulation increase, the symptomatology of EDs also increase in parallel , 47–49. Shriver et al. , recentlThe results of the present study also suggested that higher levels of emotion regulation difficulties were related to greater anger. These results are consistent with those reported in previous studies where feelings of anger have been found to increase as difficulties in emotion regulation increase , 20, espThe present study also found that greater anger was associated with greater body dissatisfaction. Although this relationship has been scarcely examined in previous studies, these results can be explained by studies associating negative emotions such as depression, anxiety, and stress with increased body dissatisfaction , 12. MorSimilarly, previous studies have associated anger with eating disorders. Greater symptoms of anorexia nervosa and bulimia nervosa have been reported among individuals with greater inappropriate anger , 22, 53.Secondly, the hypothesized model in which anger acted as a mediator in the relationship between difficulties in emotional regulation and body dissatisfaction was investigated. The results obtained showed that difficulties in impulse control and lack of emotional awareness had significant effects on anger. Likewise, anger had a significant positive effect on body dissatisfaction, where higher levels of anger were associated with greater body dissatisfaction. In turn, non-acceptance of emotional responses and lack of emotional clarity had a significant effect on body dissatisfaction, where higher levels of these emotional regulation difficulties were related to greater body dissatisfaction.Among the emotional regulation difficulties, impulse control difficulties had a positive and significant indirect effect on body dissatisfaction, explained by increases in anger. Therefore, greater impulse control difficulties were related to greater body dissatisfaction through the effect on anger. These results can be explained by the fact that females with an ED tend to present a high need for control, and many authors have conceptualized eating disorders as pathologies of control , 57. ThiOn the other hand, in relation to self-discrepancy theory , a recenMoreover, affective regulation theory proposes that loss of control in eating is preceded by an increase in negative emotional states . RelatedFor their part, therapists treating patients with eating disorders should be aware of these relationships and consider the possibility that anger and impulse control difficulties may underlie and be an important focus in reducing body dissatisfaction among young women. Moreover, it is known that eating disorders have a function. That is, if something exists and persists over time, it must necessarily play an important role and have a positive utility. Otherwise, it would be destined to disappear . TherefoConsequently, the development of an ED is a non-verbal way of expressing distress and asking for help. Young women may be overwhelmed by the intensity of the emotions of anger and difficulties in impulse control and this can lead to body dissatisfaction as a way of narrowing the focus on what they can really control and gives them security which is body modification and obsession. Family-based therapy is one of the therapies of choice in EDs that attempts to address the entire family in order to construct explanatory hypotheses for the family distress and triggered symptomatology.The present study is not without limitations. First, the cross-sectional nature of the study precludes the analysis of causal relationships between variables. Future studies should replicate the study using longitudinal designs in order to provide a more robust view of the causal relationships between variables. A second limitation is the use of self-reports to collect the study data, as well as the use of subscales of psychometric instruments rather than the full scales. This is because there is a greater likelihood of recall bias in the study using self-reported data. Because of this, the use of explicit self-report measures could be limiting. In future, it would be useful to couple these measures to implicit/objective tasks as suggested by Scarpina et al. . Third, When elaborating explanatory hypotheses, future studies could explore the possible presence of feelings of anger and their difficulty to externalize it, as well as to control impulses. This is due to the fact that it is common for females with an ED to have difficulties in differentiating themselves and achieving autonomy in their family environment, which can generate feelings of anger that cannot be expressed . In addiFuture studies should also aim to extend the present investigation and explore other variables involved in the relationship between difficulties in emotional regulation and body dissatisfaction. For example, future studies could investigate the mediating role of the use of social networking platforms in the relationship between difficulties in emotional regulation and the development of body dissatisfaction. Difficulty in impulse control plays an important role in the use of social networking platforms that may trigger greater body dissatisfaction. It would also be interesting to collect data on the BMI of the participants and analyze its influence on the study variables.The results of the present study suggest that difficulties in impulse control are a key factor in explaining the increased anger leading to body dissatisfaction among young adult women. The present study adds to studies that point to the relevance of increasing adaptive emotional regulation in EDs , the impThe original contributions presented in this study are included in the article/supplementary material, further inquiries can be directed to the corresponding authors.The studies involving human participants were reviewed and approved by the Deontological Commission of the Faculty of Psychology of the Complutense University of Madrid. The patients/participants provided their written informed consent to participate in this study.JM conceived of the presented idea and drafted the manuscript. MH contributed to the analysis and interpretation of data for the manuscript. MG and AE revised the manuscript critically and approved the version to be published. LO and II collected the sample and database. All authors contributed to the article and approved the submitted version.


The increasing network speeds of today’s Internet require high-performance, high-throughput network devices. However, the lack of affordable, flexible, and readily available devices poses a challenge for packet classification and filtering. This problem is exacerbated by the increase in volumetric Distributed Denial-of-Service (DDoS) attacks, which require efficient packet processing and filtering. To meet the demands of high-speed networks and configurable network processing devices, this paper investigates a hybrid hardware/software packet filter prototype that combines reconfigurable FPGA technology and high-speed software filtering on commodity hardware. It uses a novel approach that offloads filtering rules to the hardware and employs a Longest Prefix Matching (LPM) algorithm and allowlists/blocklists based on millions of IP prefixes. The hybrid filter demonstrates improvements over software-only filtering, achieving performance gains of nearly 30%, depending on the rulesets, offloading methods, and traffic types. The significance of this research lies in developing a cost-effective alternative to more-expensive or less-effective filters, providing high-speed DDoS packet filtering for IPv4 traffic, as it still dominates over IPv6. Deploying these filters on commodity hardware at the edge of the network can mitigate the impact of DDoS attacks on protected networks, enhancing the security of all devices on the network, including Internet of Things (IoT) devices. The rapid growth of the Internet, amplified by the proliferation of Internet of Things (IoT) devices and coupled with increasing network speeds, requires the deployment of high-performance, high-throughput network devices that prioritize energy-efficient solutions. In the context of IoT environments, the challenge lies in developing efficient mechanisms that can process packets rapidly while optimizing energy usage to meet their energy-constrained demands, even at the network edge.Packet processing in high-throughput networks is primarily the task of specialized hardware-based network devices that can quickly classify and filter packets, albeit with limitations. Performing this task programmatically on a 100 Gbps network requires packet filtering that can handle a throughput of over 148 million packets per second (Mpps). On a general-purpose computer with a processor speed of 4 GHz, this would mean that each packet should be processed in less than 27 clock cycles.Depending on the type of device, the classification of packets is based on certain criteria, such as searching by destination MAC address or the VLAN tag in switches, or the source/destination IP address in routers and firewalls. Performing such checks within the required 27 clock cycles is a major challenge, as multiple operations or memory fetches must be completed within this time frame. The 27 clock cycle example applies to the smallest frame size traffic, when the device is at its busiest due to the shortest packet arrival times. Regardless of this, devices in the network infrastructure must be able to handle packets of all sizes at all speeds. Otherwise, if one device fails, its availability can no longer be guaranteed.bots, often insecure computers or IoT devices) send traffic to the victim, consuming resources and disrupting normal users. Defending against such attacks is very difficult, as there may be millions of these infected devices. Distinguishing the ‘good’ traffic from the ‘bad’ and at the same time filtering it out is particularly problematic when dealing with very high network speeds.Malicious users on the Internet exploit this fact and attempt to disable access to certain services through Denial of Service (DoS) attacks and Distributed Denial of Service (DDoS) attacks. According to various sources ,2,3, DDoDespite current efforts to replace IPv4 with IPv6 in response to IPv4 address exhaustion, there is no clear indication that this transition will occur in the near future. Since the percentage of total IPv6 traffic remains lower c) need to send only the ordinal number of the first terminating rule that matches in hardware. For each combination of partially offloadable P0 rules, only the results of each fully offloadable pattern (pO) need to be sent to software as a true/false bitmap. For every combination of partially offloadable P1 rules, the hardware computes the data for partially offloadable patterns (pP) and sends it in full to the software. P2 rules have the same metadata requirements as P0 and P1 rules combined.The evaluation is solely conducted for all of the other groups of rules , as shown in All such rulesets include constant rules that always perform the same tasks, regardless of the security level of alert, as well as variable ones that change depending on the security status. The rules from The rest of the ruleset depends on the situation and may change depending on whether the network is under a DDoS attack and how severe it is. In the state of normal network activity , an external tool that monitors regular traffic accumulates secure hosts/networks in a secure table that is always forwarded . Using LPM also allows for the fast classification of source addresses according to their geo-location, and so it always forwards specific countries . All other traffic is forwarded, but also monitored by an external automatic DDoS attack detection system.During the DDoS attack, instead of allowing all unknown traffic from the variable part of the ruleset, the filter blocks everything except potentially secure tables (GOOD and GEOIP). Since all other traffic is monitored, this helps to isolate the bad IP addresses and adds them to the BAD table, which is updated accordingly. If necessary, the filter would additionally reject the GEOIP table, as shown in Since the packets in the implementation of this filter are prepared independently by hardware, with their metadata created before reaching the input interface of the software component, the software is unaffected by how they were created.pkt-gen tool (included in the Netmap framework) was used on a separate computer to generate packets, create the necessary metadata, attach it to the packets, and send them to the software filter, as shown in To test and validate the system without the need for multiple hardware implementations, the measurements were designed to ensure the independence of packet preparation and metadata creation. This was achieved by simulating the hardware part of the system by creating the metadata programmatically. The rdtsc [The test results are based on the 60 s average, and the CPU cycle counter in the software filter is implemented using the assembler instruction rdtsc , which aTo validate and verify the results of the simulated measurements, some of the measurements were performed on a real hybrid system that used FPGA hardware to generate metadata.random and specific traffic. Both types used randomly generated traffic with either completely random source IP addresses or specifically shaped traffic to seem like a DDoS attack. The specific traffic consisted of a combination of “normal” random traffic and randomly selected IP addresses from a large pool of malicious IP addresses. In this way, we could demonstrate how the filter performed under pressure, when the filtering load was high. All of the tests were set so that the bandwidth never reached the maximum possible value for the system. Additionally, to allow for better control and consistency of tests, all of the tests were performed on a system with a single CPU core at reduced frequency. For this reason, the efficiency of the two filtering methods could be compared based on the number of packets processed per second and the number of CPU cycles required to process one packet.We present a comparison of filtering results with and without offloading on hardware, using different hardware offloading configurations. The average total throughput and the average number of CPU cycles per packet were measured, and two types of measurements were performed: using The measurements were categorized by rulelists, which were tested with associated metadata specific to the rules within them. Multiple measurements were conducted for each rulelist to obtain average results for all of the hardware offloading configurations: without any hardware offloading (only the software filter without metadata) as a point of reference, and then with modified parameters for hardware offloading. Each individual rulelist consisted of multiple rules, created in such a way to test the offloading of a single metadata type and, in some cases, combinations of multiple types of metadata. The detailed explanations and extended results of these experiments can be found in .non-terminating rules, forcing the software filter to process each of them before forwarding the packet to the egress interface. This ensured that the same number of processing operations were performed for each packet, making the filtering comparable for all of the tests for the same group. The average software-only filtering throughput and cycle count for each type of ruleset in this group are shown in The rulesets used in tests were divided into two groups, depending on the type of rules used in them. One group used only non-terminating and terminating (Accept) rules. If the packet matched the terminating rule, it no longer needed to be processed, and so the subsequent rules were not checked. For this reason, the maximum throughput for these tests was slightly higher than the throughput for the tests from the first group of rulesets. The average software-only filtering throughput and cycle count for each type of ruleset in this group are shown in The second group used both random and specific traffic. The total throughput increase closely correlates with the CPU cycle decrease, and so it is not shown.terminating rules (OAc) show the greatest improvements for both types of traffic. For random traffic, the greatest improvement is seen using the ruleset with rules that partially offload the LPM algorithm, combined with rules that fully offload simple port checks to hardware with 20.2% fewer CPU cycles. For specific traffic, it is the variation in a ruleset that fully offloads simple port checks to hardware with 28.9% fewer cycles.The results in random and specific traffic cases uses the “realistic” version of the LPM ruleset with rules that can be assumed to be used in a realistic scenario, similar to the rules shown in P1** partial LPM offloading, it achieved a 17.8% reduction in CPU cycles for random and 23.6% for specific traffic. Other cases with the highest improvements for both types of traffic are those combining P1** or P2** partial LPM offloading with other metadata for an around 10% reduction in CPU cycles.The second highest test in both As previously mentioned, the results shown are all based on tests using metadata pre-generated by the packet generator. To test the hardware part of the hybrid system, i.e., how the system works when the NetFPGA generates the metadata and attaches it to the packets, another set of tests was performed.The test environment (testbed) for the hybrid tests, as shown in The tests for this hybrid system were performed in the same manner as the simulated tests, except that the packet generator did not have to create metadata and attach it to the packets. For this reason, it was expected that the results of all of the tests performed on the hybrid system would match the results of the simulated hardware. In all of the tests that were performed with the hybrid system, the average results of the hybrid system matched the average results of the simulation almost perfectly. From these results, it can be inferred that it is possible to achieve the same level of improvement over non-offloaded filtering with other types of metadata if specific offload capabilities are implemented in the hardware.metadata1 requires the fewest and least complex hardware updates to achieve a significant increase in DDoS protection. For example, to increase the total number of available LPM tables for hardware offloading, additional memory needs to be installed in the hardware. The use of this additional memory would not significantly impact the internal FPGA logic and overall system performance. On the other hand, other metadata types require more complicated changes, as parallelism cannot be leveraged as efficiently as in the case of metadata1. This could lead to delays and performance degradation, especially when offloading a large number of rules to hardware.The extent of improvement in each test may vary depending on the capabilities of the hardware, with performance being further enhanced as more metadata are offloaded to the hardware. Among the different metadata types, Improving the performance of the filter that uses hardware offloading means finding a balance between the size of the metadata and their usefulness. Responding to changes in the type and volume of traffic is also one of the most important matters to consider when offloading and even beforehand when creating the ruleset. Therefore, in cases where offloading has a negative impact on throughput, it can be bypassed and replaced with a better configuration.It is worth repeating that all of the tests  were performed on a system with a single CPU core at a reduced frequency. Moreover, they were performed on a system corresponding to the model shown in In this paper, we presented a datapath model of a high-speed network traffic classifier/filter based on a hybrid hardware/software combination of FPGA and off-the-shelf computer software. The hardware component model comprises a reconfigurable FPGA datapath capable of adapting to runtime packet classification changes in near real-time. On the other hand, the software component is a modified version of the filter used in our previous research, now equipped with additional functionality to receive metadata from the hardware. This integration allows for more efficient packet filtering, leading to improved performance over software-only packet filtering.We have shown that the hybrid system can achieve filtering in networks with speeds of 10 Gbps by heuristically distributing the workload between the hardware and software components. This is achieved by carefully selecting packet filtering methods and metadata that can be offloaded to the hardware, which optimizes the throughput of the system. To test the system, we developed a method to empirically evaluate the distribution of the workload between the hardware and software components. It bypasses the development of complex hardware implementations by simulating the necessary offloading of hardware to software.The implemented model shows performance improvements in tests that include both random traffic and traffic specifically designed to simulate DDoS attacks. It is shown that offloading different types of rules to hardware, fully or partially, results in varying performance improvements, with reductions of up to 30% in CPU cycles for certain offloads and rule types. In packet filtering, the use of rules based on LPM offers the advantages of higher throughput and simpler, more manageable rulesets. Therefore, these rulesets are well suited for DDoS protection, and their effectiveness can be further enhanced by hardware offloading.In addition, the scalability of such a system should be emphasized, because efficient use of the LPM algorithm for IP address lookup means that filtering does not depend on the number of rules, but on the method of offloading parts of the filtering to the hardware. With suitable hardware, it is expected that the improvement in such a system can be maintained at higher speeds.


There is an alarmingly high growth in breast and cervical cancers in low- and middle-income countries. Due to late presentation to doctors, there is a lower cure rate. The screening programmes in low- and middle-income countries are not comprehensive. In this paper, we systematically analyse the barriers to screening through an accessibility framework. We performed a systematic literature search in PubMed, Mendeley and Google Scholar to retrieve all English language studies  that contained information on breast and cervical cancer screening in low- and middle-income countries. We only considered publications published between 1 January 2016 and 31 May 2021. The review was guided by Preferred Reporting Items for Systematic Reviews and Meta-Analyses literature search extension (PRISMA-S), an extension to the PRISMA Statement for Reporting Literature Searches in Systematic Reviews. The search yielded a total of 67 articles from low- and middle-income countries in this review. We used a framework on accessibility known as the 5A framework, which distinguishes five aspects of access: approachability, acceptability, availability, affordability and appropriateness, to classify the screening barriers. We added two more aspects: awareness and angst, as they could explain other important barriers to screening. They confirmed how the lack of awareness, cost of the screening service and distance to the screening centre act as major impediments to screening. They also revealed how embarrassment and fear of screening and cultural factors such as lack of spousal or family support could be obstacles to screening. We conclude that more needs to be done by policymakers and governments to improve the confidence of the people in the health systems. Women should be made aware of the causes and risk factors of cancer through evidence-based strategies so that there is an increased adherence to screening. Key messagesFear of screening test results, lack of knowledge about the disease and screening, distance to the screening clinic, embarrassment to undergo screening, lack of support or permission from husbands to undergo screening and high cost of screening were the most common barriers. Barriers to treatment and socio-cultural factors have a major influence on screening uptake.Every year, there are >2.26 million new breast cancer cases and >600 000 new cervical cancer cases worldwide. Over 91% of deaths from cervical cancer and >79% of deaths from breast cancer occur in low- and middle-income countries . The incSo far, studies on barriers to breast and cervical cancer screening in low- and middle-income countries suggest that the level of knowledge on these health issues and factors that provide opportunities for knowledge acquisition, such as level of education and employment, determines the screening uptake in women . We included all types of studies . The relevant information from the publications was extracted and classified as themes based on our 7A framework presented earlier.Although this topic has been addressed in systematic literature reviews  population: women, their husbands, health workers, administrators, policymakers and religious leaders; (2) intervention: breast screening—self-breast examination and mammogram or mammography; cervical screening—Pap smear or Papanicolaou test and visual inspection with acetic acid; surgical procedures to remove cervical precancers such as Loop electrosurgical excision procedure and cryotherapy; (3) comparator: this was not a specific inclusion criterion since studies with and without a comparator group were included; (4) outcomes: barriers to access classified under the 7A framework of approachability, acceptability, availability and accommodation, affordability, appropriateness, awareness, as well as angst and fear; (5) study design: peer-reviewed publications to ensure the quality of research; only publications based on research on low- and middle-income countries; only articles published between January 2016 and May 2021 and only English language publications.The same PICOS method was used to exclude the publications with the following characteristics: (1) population: studies on population groups in high-income economies and studies on migrants from low-income and low-and-middle-income economies to high-income economies; (2) intervention: unproven methods of breast and cervical screenings such as thermal screening; (3) comparator: this aspect did not provide exclusion criteria; (4) outcomes: no barriers to access reported; (5) studies: editorials, letters and personal views and publications of languages other than English.The analysis applied the method of directed qualitative content analysis. From the selected publications, information related to the barriers to breast and cervical cancer screening was extracted under the different aspects of access in the 7A framework: approachability, acceptability, availability and accommodation, affordability, appropriateness, awareness and angst and fear. Each of the seven aspects had different dimensions, which were numerically coded, and all key findings were summarized in tables and explained narratively.The quality of the publications was assessed using the standard evaluation checklists such as Critical Appraisal Skills Programme (CASP)  and Effective Public Health Practice Project (EPHPP) (for quantitative publications). The qualitative study checklist had 10 questions with answer options of ‘Yes’, ‘Can’t tell’ and ‘No’. For each question that confirmed the fulfilment of a given quality criterion, the study got a score of 10 points. If the study was ambiguous regarding that criterion or did not meet that criterion, it received 5 or 0 points for that criterion, respectively. Overall, a study could get a maximum score of 100 points. The quantitative study checklist had eight components. Some components had subcomponents, while others did not. Each component had a grading of strong, moderate and weak. Each publication was graded for the eight components. Again, a study could receive a maximum overall score of 100 points, where each component had a grading of 12.5 points. A publication that received a strong grading scored 12.5 points, a publication that received a moderate grading scored 6.25 points and a publication that received a weak grading scored zero points. For mixed-methods studies, both the CASP and EPHPP checklists were applied, and therefore the maximum score of 200 points was used. For both checklists, there was an emphasis on the integrity of the sources, the validity of data collection and the relationship between the findings and the research question. Other criteria included the aim of the study, the clarity of the research question and whether the study design was suitable to answer the research question. We also checked the quality of our systematic review based on the PRISMA-S checklist see .The literature searches on 1 September 2020 yielded 453 articles in PubMed Central, 558 articles in Mendeley and 660 articles in Google Scholar: thus, 1671 articles in total. In addition, eight articles were identified from journals in India. After duplicate articles were removed, 677 articles remained. These were checked for relevance and whether they fit the inclusion criteria. Only 157 articles fit the timeline between 1 January 2016 and 31 August 2020. Given the inclusion criteria, 109 articles were off-topic and were excluded. The second level of screening was conducted, where 48 articles were assessed for eligibility. After scrutiny, 14 articles had to be eliminated because they did not meet the relevancy criteria, and 34 articles met the inclusion criteria and were selected for the literature review. Out of the 34 articles, 17 articles had adopted qualitative analysis, 14 articles had used quantitative analysis and three articles had used mixed-methods analysis. The 34 articles that were selected for the literature review were checked for reference articles, which might not have appeared in the first-level search in the three databases. This exercise yielded 29 articles that were added to the literature review. A second search was conducted on 1 June 2021 using PubMed, Google Scholar and Mendeley to see if any new articles were published after 1 September 2020 that met the inclusion criteria. The second search yielded four additional articles.A detailed description of the articles can be found in The overall characteristics of the articles included in the review are presented in In Among the seven barriers across 67 studies, awareness was the most significant barrier overall. However, there were differences in rankings between regions. In the 27 studies focused on East Africa, which were from Ethiopia, Tanzania, Somalia, Malawi and Uganda, Acceptability was frequently ranked as the most significant factor (in 55% of those that mentioned it) followed by awareness (in 40% of the studies that mentioned it). Whereas there were 16 studies from West African countries of Ghana, Nigeria, Cameroon and Burkina Faso, awareness was ranked as the predominant theme in 63% of the papers, followed by approachability  and acceptability (20%—restricted agency). Both were ranked as the main theme in three studies each. In India, there were 10 studies, where acceptability was ranked as the predominant theme in India (in 67% of the studies mentioning it), followed by awareness which was ranked first in 33% of the studies mentioning it. There were three studies each from the Middle East, Central America and Southern countries of Africa. Awareness was a common factor in all the above three locations. While restricted agency and hesitancy to be screened by male doctors were mentioned as an important factor in African countries of West and East Africa, it was not a factor in Asia or the Indian subcontinent. The barrier that was ranked as the second most important in East Africa was awareness cited in 40% of the studies followed by availability in 13% of the studies that mentioned it. In West Africa, 27% of the studies revealed that approachability was ranked as the second most important barrier, followed by acceptability with 20%. In India, awareness was ranked second, with 33% of the participants considering it to be significant, followed by affordability with 25%.In 21 studies that were based solely in rural communities, awareness was the most important barrier, followed by acceptability. In the 34 studies which were done in an urban setting, awareness and acceptability were ranked equally as most significant by 42% of the respondents, followed by approachability. In total, 50% of the studies which were based in combined urban and rural settings had affordability ranked as the main barrier, followed by awareness (43%) and acceptability (33%).There were only four studies that related exclusively to breast cancer, seven studies that dealt with both breast and cervical cancers and 56 studies that were concerned solely with cervical cancer. In the four studies which were entirely related to breast cancer, two studies ranked acceptability as the most important barrier. Approachability and awareness were ranked as the second and third most important barriers, respectively. The participants in the seven studies which dealt with both breast and cervical screening ranked acceptability first with 50% followed by angst (40%) and acceptability (33%). There were 56 studies that were concerned wholly with cervical cancer. In total, 45% of the studies in which awareness was mentioned ranked awareness as the most important barrier, acceptability was the second most important barrier (37%) followed by approachability (22%).In studies where women were the only participants (51 studies out of 67), awareness was ranked as the most important dimension by 46% of the studies that mentioned it, lack of recommendation was cited as the second most significant by 32% of the respondents and acceptability factors such as restricted agency, embarrassment or the need for a female doctor and arranging childcare were ranked third in 29% of the studies. In studies where other stakeholders such as spouses, health workers and community leaders were also part of the study (16 studies out of 67), acceptability was found to be the most important finding in 69% of the studies, followed by awareness with 57% of the studies that mentioned it ranked it second.The studies were appraised for internal/external validity and reliability based on the CASP appraisal checklist for qualitative studies and the EPHPP appraisal checklist for quantitative studies. Four qualitative studies were found to be of high quality, while the rest were of a medium level of quality. Two qualitative studies scored poorly on the checklist due to poor recruitment of candidates or insufficient information. All quantitative studies were found to be of a medium level of quality except one. In some of the studies, there was no information about research questions, the analysis process was not discussed and potential biases were not mentioned. Articles reporting on mixed-methods studies were appraised stepwise, and the qualitative and quantitative parts were assessed separately. Overall, validity and research design in these studies were poorly addressed, and thus, all of these studies were found to be of a medium level of quality.About 18% of the quantitative studies reviewed showed that a lack of promotion by the health-care provider was the most important barrier to breast and cervical cancer screening. This could be categorized into two types. First, there was no information provided by the health-care provider (physicians and nurses) about breast and/or cervical cancer. In one study from Tanzania . Second,The participants of the qualitative studies also said that the health workers did not explain why screening was needed, what benefits it had and when it had to be performed . No sustIn total, 12% of the studies reviewed revealed that long waiting times in the screening centre put them off from seeking screening services. Physicians were not on time and extended hospital waiting time resulted in time loss for the market and business . The lacThe qualitative studies revealed how discrimination by health-care providers led to distrust in the health system. Discrimination by health-care workers in health-care settings due to their health status or their religion was an uncommon but essential barrier. Discrimination against patients living with human immunodeficiency virus (HIV) hampered their access to cervical cancer screening , focus  and stakeholders . Acceptability factors were found to be the most important in countries of East Africa and India, whereas awareness was ranked as the most significant factor in West Africa. In countries of Asia, Southern Africa and the Middle East, approachability was the most important dimension. Availability was one of the important factors in East Africa but was not found to be important in the rest of the regions. Affordability was important in East Africa, India and Central America. East Africa and India were found to have similar rankings of barriers. While Overall across all regions and when classified according to study setting or the focus of the study , awareness was ranked as the most important barrier. Women had heard of cervical cancer but were not aware of the causes, risk factors and symptoms of cancer, and there was a reluctance to accept that one is susceptible to cervical cancer (Nevertheless, it needs to be considered that socio-cultural factors could prevent women from accessing screening services even if there is awareness and screening is closely available. In this regard, another finding from our review was that the lack of spousal support was a major barrier to the uptake of breast and cervical cancer screening. Ghanaian men in a study  expresseWe found in the review that women hesitated to undergo screening unless it was recommended by a physician. It is known that a recommendation by a doctor or a general practitioner can act as a motivator to undergo screening (Another important finding from the studies was that women did not attend screening because they feared screening test results. Due to the non-availability of suitable treatment in government hospitals or the inability to afford treatment in private hospitals , women bThe availability of screening clinics and the distance to reach the screening clinic were recognized as major impediments to breast and screening in the studies reviewed. To overcome these barriers, various strategies could be employed. For example, the health department of the Philippines has used vans or buses as mobile cancer detection clinics where screen-and-treatment methods could be performed in remote areas as part of its breast cancer control programme to supplement the gaps in the country’s breast cancer screening endeavours (The affordability of screening was established as an important inhibitor for cancer screening in our review study. As There is a correlation between educational attainment and knowledge of risk factors not only between low- and middle-income countries and high-income countries but also between the different ethnic, racial and immigrant groups within high-income countries (This study has some limitations that need to be acknowledged. Our review only included studies reported in English language publications. This indicates possible publication bias since relevant studies might have been reported in another language and/or not yet published. The extraction of data from the articles was done by one author only, which may have led to selection bias. The selection bias was, however, partly diminished by having another researcher screening the papers excluded based on title and abstract. In addition, the quality check of the studies was done by one author only, which may have resulted in evaluation bias. Moreover, quality checklists have been used to score quality and compare the studies, but we might have missed study-specific quality details. This bias was also partly reduced by discussing the unclear papers with all co-authors. Most of the studies originated from India and North, Central and East Africa. Only a few studies originated from West Asia, South-East Asia, Central and South America. In view of this, our findings cannot be extrapolated to all low- and middle-income countries. Whereas we have used the number of respondents indicating particular barriers to rank the significance of these barriers in each study, we also recognize that there needs to be a standardized methodology to rank the significance of variables in each study. The interpretation of the review results could only be context specific. Nevertheless, the review still indicates a set of potential barriers that could be considered when discussing breast and cervical cancer screening in any low- and-middle-income country.Further research is needed to assess women’s preferences for cancer prevention screening programmes and their value to the public. Also, more needs to be understood on how husbands and elderly family members can be influenced to support their women to undergo screening. As shown in our review, the opportunity cost of screening is as much a barrier as the cost of screening itself. New studies are needed to provide evidence on how the government should provide incentives to women to undergo screening and what kind of incentives should be provided. Should the screening be free? Should the incentives cover the cost of transportation to the screening centre? These investigations could provide insight into the women’s ability and willingness to pay for screening. To achieve the international goals of women’s cancer prevention, especially breast and cervical cancer prevention, more exploration is needed on whether governments and health systems should adopt population-based screening or targeted screening.Our systematic review found that while a lack of awareness, embarrassment, lack of family support and cost of screening were important barriers, the fear of diagnosis of cancer due to lack of finances for subsequent tests and treatment was the most significant barrier and had an overarching influence on the other barriers. Free cancer screening and nudges or incentives for cancer screening may increase uptake. However, much more needs to be done by governments in the area of financing cancer treatment, either fully or partially. Self-testing for cervical screening could be a panacea for several key barriers, such as embarrassment or shyness to undergo screening, affordability and lack of spousal support. Clinical breast examinations could be considered for population screening of breast cancer in low- and middle-income countries.czac104_SuppClick here for additional data file.