In the light of the current COVID-19 pandemic, being considered a present challenge for public health, the main purpose of this work is to analyze the vulnerability to stress of a sample of nursing students in Romania considering their status on labour market  before and during the COVID-19 pandemic. Employed students were more vulnerable to stress comparing to non-employed ones during the pandemic. In addition to this, the nursing students working in the medical system experienced medium vulnerability to stress during the pandemic comparing to those working before the pandemic who experienced a low vulnerability to stress. Excepting the non-employed students before the pandemic, the females were more vulnerable to stress comparing to the males in the sample and the students living in the country experienced a higher level of stress comparing to those living in the urban area. During the pandemic, most of the employed nursing students expressed their fear of getting infected with COVID-19, this representing the most stressful factor for them, while most of them mentioned the self-control as being the most proper strategy for them to cope with stress. These empirical findings have practical implications for stress control among present and future nurses, for management of medical units and for higher education nursing. The COVID-19 pandemic is considered a major challenge for public health. In this context, nursing students preparing themselves for this work should be key factors in the struggle against the virus infection, prevention and control. The experience of nursing students with medium studies in this field and who already work in the medical system is essential for their colleagues who are not employed as nurses yet. However, the studies related to stress among nurses and nursing students are limited during the COVID-19 pandemic, because a survey is considered to place undue stress on an individual. Good mental health for actual and future nurses is vital in order to control different infectious disease –4.The Romanian medical system has been severely affected by the COVID-19 pandemic and this new challenge requires nurses to become more than healthcare suppliers and to act like architects of the new health system. Work stress management should be the cornerstone of the new system and this should start earlier with better education for nursing students who prepare themselves to face work challenges. In Romania, nursing students with medium studies in this field (sanitary high school and sanitary post-secodary school) have the right to work as nurses in public and private medical units in any medical specialization. Superior studies in this field are not compulsory and do not depend on medium studies in specialized education centers. They provide additional advantages for nurses: higher salaries comparing to nurses with medium studies and the right to be promoted as head of department in a medical unit. The superior education for nursing students in Romania should be improved by supporting them in managing the stressful work situations. From this point of view, our study is a novelty for the specialized literature in Romania, because the vulnerability to stress of nursing students is analyzed before and during the COVID-19 pandemic and some strategies are suggested during the pandemic in order to cope with stress.Most of the studies from literature have analyzed the factors of stress for nurses utilizing a qualitative approach, but our research presents a quantitative approach. Comparing to previous studies, two perspectives on nursing students are considered: employed nursing students before and during the COVID-19 pandemic and nursing students who are not employed yet. The difficult context of the actual pandemic constraint students preparing themselves to become nurses and other recommendations should be made in order to surpass this constraint. Therefore, the subjects of this study are represented by nursing students: employed nursing students working in the medical system and non-employed nursing students. The employed nursing students working outside the health sector are not considered in this analysis.One of the challenges of human resources is work stress that diminishes work efficiency and causes negative effects for people’s souls and bodies . Work stNursing is considered a stressful work which impacts the physical and mental health of the nurses, but it also causes negative effects on the health system, especially for patients . The US Different categories of stressors have been identified in previous studies: a lot of pressure at work , violentThe effects of stress consist of: difficult decision to make, anxiety, less motivation for this work, apathy, decrease in the quality of life, risk of chronic diseases, less immunity .The negative effects of work stress for nurses impose recommendations for coping with stress. People who are successful in solving their problems, have coped with stress in a better manner comparing to those with a defensive strategy . In thisThere are more fields that have provided contributions to stress theory . Our approach is focused on psychiatric theory. Life events, the COVID-19 pandemic being an example, are considered as factors of stress that change the people’s behavior and the long-run pattern . In our Several directions of research have been recently identified in the context of work motivation during the COVID-19 pandemic. First of all, burnout has increased during the COVID-19 pandemic because of isolation , 16, undMore hypotheses have been formulated in order to validate them on empirical data. For example, employed students would not have had a higher stress vulnerability than non-employed ones before the pandemic because of their income and the respect earned owing to their chosen profession. Prior to the pandemic, non-employed students may have been exposed to stress related to not having employment in their field comparing to employed students.Many theories have explained the low rates of psychological comfort for non-employed people, the most known one being the Jahoda Deprivation Model. This model shows that being employed satisfies the basic needs of individuals: financial needs and psychological ones  . UnemploOn the other hand, the level of stress for employed students might be higher during the epidemic, comparing to non-employed ones because of the infection danger. According to the conversation of resource theory, work stress is caused by the threats of working environment . The COVThe theoretical description of the stress factors and strategies in order to overcome this, should be followed by an empirical analysis . In thisThis analysis is focused on graduate nursing students from the Faculty of Midwifery and Nursing from Bucharest, the single faculty of this kind in the city. Two different samples of students have been considered in this analysis: a sample of students who responded to the survey before the COVID-19 pandemic (June 2019) and a sample of students who responded to the survey during the pandemic (June 2020). The oral consent has been obtained from students and from the rector of the university. The approval of the ethics committee of the faculty was not necessary in this case since the study was based on students who had to complete an opinion survey without treating them as patients. The students expressed their volition to complete the survey without any constraint.Employed students are those who have a workplace. In this study, we have included only those employed nursing students working in the medical system as nurses in public and/or private hospitals, dispensaries or clinics and non-employed nursing students. Since the information is confidential, the employed individuals have not been asked to write the name of their employer. There are some students not working in the healthcare industry, but these ones have not been included in our sample. Since their number is low, a comparison with those working in the health sector would not be relevant.The total number of students was 270 in June 2019, but only 268 of them were employed as nurses or non-employed and they responded to the survey. For the period of the pandemic (June 2020), another 268 students were selected out of a total of 270 students (employed as nurses and non-employed). However, the samples are not representative at national level according to different characteristics, but they are relevant for nursing students in Bucharest, the capital of Romania. An online voluntary survey was utilized to collect data. The link of this survey was sent to nursing students by email.Miller and Smith scale has been used to assess the vulnerability to stress based on 20 questions in the survey concerning psychological features , social and behavioural factors , and biological factors  . Miller The stressors refer to: fear of getting sick with the new coronavirus, lack of experience in managing a pandemic, miscommunication and social distance, more patients comparing to the pre-pandemic period, mask wearing, the use of new equipment purchased during the pandemic, huge workload, more frequent use of disinfectants.Several coping strategies at work have been indicated since the beginning of the pandemic and the respondents have been asked to choose the most efficient one for them: self-control, colleagues’ support, implication of medical unit management, family’s support and spiritual dimension reflected from various perspectives like contact with nature, recognision of God’s power, use of prayers and holy books, spiritual improvement.The Alpha (Cronbach) coefficient has been computed for checking the internal consistency among the scale’s items. The calculated value of Cronbach’s Alpha coefficient is 0.76, suggesting good consistency.Apart from these questions, the students have been asked to provide answers in order to register some demographic characteristics:Gender ;Marital status (married/unmarried);Age group ;Environment ;Status on labour market (employed/non-employed);Living conditions .The statistical analysis is based on: a) treatment effects that estimate experimental-type causal effects using survey data and b) Pearson’s chi-square test to measure the association between vulnerability to stress and various characteristics: demographic variables  and copying strategies to stress for separate groups of nursing students: employed students before the pandemic, non-employed students before the pandemic, employed nursing students during the pandemic and non-employed ones during the actual medical crisis. In addition, some relative frequencies have been computed in order to identify the most severe stressor concerning the employed nursing students during the pandemic and the most efficient copying strategy to stress in the same period.In this case, the treatment is influenced by the emerging of the employed nursing students and non-employed ones on the labour market and by the existence of the pandemic period or not (during the pandemic and before the pandemic). In this case, the main advantage of this method is the ability to make comparisons between groups , while a disadvantage is related to extensive computations. Details on treatment effects method are provided in Appendix 2 in Pearson’s chi-square test has been selected as being the most suitable non-parametric test to apply in this study since the hypotheses of the test are fulfilled in this case: a) each two variables for which association is verified are measured at an ordinal or nominal level (category data for demographic variables and copying strategies to stress) and b) the two variables consist of two or more category, independent groups , environment , age category , copying strategies to stress .The Pearson’s chi-square test has the advantage of revealing whether there are significant differences between the groups with respect to a variable. For example, in this case, differences among stress scores are verified concerning males and females, also with regards to people living in villages and those living in urban environment. The main limit of this method is related to inaccurate results for some small samples when the expected frequencies are too low.i and a group of N units [Causal effects are defined as comparisons between possible outcomes in terms of expected values, median or odd-rations of an unit  N units . Appendi N units . On the  N units .H1a)Employed students do not experience a higher level of stress comparing to non-employed ones before the COVID-19 pandemic.H1b)Employed students experience a higher level of stress comparing to non-employed during the COVID-19 pandemic.H2During COVID-19 pandemic, employed students experience a higher level of stress comparing to employed ones before the pandemic.H3During COVID-19 pandemic, non-employed students experience a higher level of stress comparing to non-employed ones before the pandemic.In addition, some comparisons will be made between employed students before and during the pandemic in terms of coping strategies using Pearson’s chi-square test.The sample analyzed before the pandemic and the sample that made the subject of the research during the pandemic are separately described. The mean stress score for the sample before the pandemic is 25.55 (standard deviation = 9.96) which suggests low vulnerability to stress. However, during the pandemic, the average stress score reached 27.53 (standard deviation = 8.76) with values ranging from 8 to 60. In this period, 45.2% of the nursing students experienced average and high vulnerability to stress, which required suitable recommendations for stress control. The test used to compare two population proportions indicates no significant differences between the mean stress scores before and during the pandemic , but the number of students with high vulnerability to stress increased to 70% during the pandemic comparing to the pre-pandemic period. The stress control is necessary during the medical crisis in Romania in order to avoid the generalisation of cases with high stress.According to In When the entire sample was analyzed, the unemployed students had an average stress score of 16.57 corresponding to low vulnerability to stress, while the employed nursing students had an average score of around 22 which places them in the same category of stress. However, there is a significant difference between the two groups of students in terms of stress score, since the coefficients associated to all methods are statistically different from 0 to 10% significance level. Corroborating the results, the employed nursing students had a higher average stress score comparing to the students without a workplace throughout the period. This significant difference is explained by the higher scores of employed students during the pandemic comparing to non-employed ones.Before the COVID-19 pandemic, there were not significant differences in the stress scores of non-employed and employed nursing students. Before the pandemic, the average stress score of students without a workplace was 23.8 (low vulnerability to stress), while the average for employed ones was around 26 (low vulnerability to stress), but the difference is not important, because the coefficients associated to all treatment effects methods are not statistically significant, at 10% significance level.During the pandemic, the stress scores increased for both categories of students. During this period, the non-employed students have an average score of 26.61 (low vulnerability to stress), while the colleagues working in the medical system have an average score around 33 (medium vulnerability to stress). We can notice that the employed students belong to a superior category of vulnerability to stress during the pandemic, because of the new challenges during this period. According to these results, the hypotheses H1a) and H1b) are verified.In For the entire sample, the students analyzed during the pandemic had a higher average stress score (around 28) comparing to those who responded before the pandemic and who had an average stress score of 23.83. These average scores correspond to low vulnerability to stress. The difference in the average stress scores of students is significant before and during the pandemic, since the coefficients of all the methods in In the group of employed nursing students, the average stress score was around 30 (medium vulnerability to stress) during the pandemic, comparing to the average in the period before the pandemic, when the average score was 26.17 (low vulnerability to stress). The diference in average scores is significant due to statistical coefficients that are different from 0 to 10% significance level concerning all methods.In the group of non-employed nursing students, the average stress scores was around 26 (low vulnerability to stress) during the pandemic, comparing to an average of 22.63 (low vulnerability to stress) in the period before the COVID-19 pandemic, being lower than the score for employed students. The diference in average scores is significant from statistical point of view due to statistical coefficients that are not null for all methods, at 10% significance level. Therefore, the hypotheses H2 and H3 are verified during the COVID-19 pandemic, comparing to the period before this pandemic.In addition, we can state that employed nursing students were more vulnerable to stress comparing to their non-employed colleagues, even if both categories were more vulnerable to stress because of the pandemic. The coping strategies for nursing students during the pandemic should be adapted since these are different in some cases from those before the pandemic. Several coping strategies for stress were considered in case of the employed and non-employed students during the pandemic: self-control, spirituality, colleagues’ support, family’s support, manager’s support. In According to Pearson’s chi-square test, there are significant differences between males and females and between students from rural and urban environment regarding their vulnerability to stress in case of employed students before and during the COVID-19 pandemic and in case of non-employed students before the pandemic.Employed females in the medical system were more vulnerable to stress before the pandemic, comparing to males working in the same period and in the same field, at 10% significance level . The employed females were also more vulnerable to stress during the COVID-19 pandemic, comparing to employed males in the medical system . Non-employed female students from the Faculty of Midwifery and Nursing were more vulnerable comparing to male colleagues before the pandemic , but no significant statistical differences were identified between the two groups at 10% significance level during the medical crisis.Employed nursing students living in rural environment were more vulnerable to stress comparing to employed ones from urban environment before the pandemic  and during the medical crisis . Non-employed students from villages were more stressed out comparing to those from cities/towns before the pandemic , but no significant statistical differences are identified between the two groups at 10% significance level during the pandemic.There are no differences between employed and non-employed nursing students regarding stress vulnerability before and during the pandemic when characteristics like marital status and age categories are considered. For example, married nursing students working in the medical system did not experience more stress comparing to non-married ones and employed students before and during the pandemic. Married nursing students without employment were not more vulnerable to stress comparing to non-married colleagues without employment before and during the pandemic. Younger employed and non-employed students were not more vulnerable to stress comparing to older colleagues before and during the medical crisis.Some relative frequences were computed in order to identify the most powerful stressor indicated by employed students during the pandemic and the most efficient copying strategy in this period. Most of the employed nursing students in the sample considered that the fear of getting sick with the new coronavirus is the most important stressor for them (42.5% of the employed students during the pandemic). Lower percentages were registered by the rest of the factors of stress: huge workload (35.83%), lack of experience in managing a pandemic (1.67%), miscommunication and social distance (11.67%), more patients, comparing to the period before pandemic (4.17%), mask wearing (2.5%), the use of new equipment purchased during the pandemic (0.83%), more frequent use of disinfectants (0.83%).Some coping strategies at work are indicated during the pandemic and the respondents have been asked to choose the most efficient one for them: self-control, colleagues’ support, involving of hospital management, family’s support and spiritual dimension reflected from various perspectives as contact with nature, recognision of God’s power, use of prayers and holy books, spiritual improvement.During the pandemic, 34.17% of the employed nursing students considered that self-control helped them in coping with stress. 27.5% of them admitted that spiritual dimension was essential in overcoming the stressful situations in this period. 20% of employed nursing students asserted that family’s support was essential during the pandemic. During the pandemic, 14.16% of the employed nursing students appreciated the colleagues’ support as useful in surpassing stressful situations at work, while 4.17% of them considered that medical unit management had the most important contribution in surpassing the stressful situations. Therefore, we can state that self- control and spirituality are important factors in reducing stress among employed nursing students in the analyzed sample during the pandemic. In In the context of the current medical crisis, the aim of this work is to compare vulnerability to stress of nursing students from Bucharest considering their status on labour market and the changes regarding the levels of stress with respect to the pre-pandemic period.The objectives of the research are related to: hypotheses concerning comparisons between students’ levels of stress , the impact of demographic characteristics concerning vulnerability to stress, the identification of the most severe stressor and the most efficient strategy to cope with stress for employed nursing students during the pandemic.During the COVID-19 pandemic, the employed nursing students working in the medical system were more vulnerable to stress comparing to their colleagues without a workplace. Schwartzman has also revealed that there is a higher stress in case of employed students comparing to non-employed ones during the pandemic . In a prIf, before the epidemic, the employed students experienced a low vulnerability to stress, during this medical crisis, the average score indicates a medium vulnerability to stress. During the pandemic, a moderate level of stress among nursing students has also been registered on a sample of 662 students  in IndiaEmployed nursing students were more vulnerable to stress (medium vulnerability to stress) during the pandemic, comparing to employed students with low vulnerability to stress before the pandemic. Previously, Aguiar-Quintana et al. (2021) revealed that nurses were more vulnerable to stress during this medical crisis comparing to the pre-pandemic period . During During the pandemic, the higher level of stress for employed nursing students comparing to non-employed ones is in line with the conclusion of Sheroun et al. (2020) regarding the Indian nursing students .Gender is important in managing stressful situations. Employed females in our sample were more vulnerable to stress comparing to males in both periods. Non-employed females experienced stress more than males only before the pandemic, while during the medical crisis significant differences were noticed between the two groups. Our results are in line with other studies that confirm the higher vulnerability to stress of women comparing to men , 5 and tEnvironment had a significant impact on employed nursing students in both periods and non-employed ones before the pandemic. Employed students coming from villages were more vulberable to stress comparing to those coming from cities or towns, contrary to the study of Lambert and Lambert (2008) . Our resIn our study, a particular attention was paid to factors of stress and copying strategies to stress for employed and non-employed nursing students during the pandemic. Besides the stressful nature of the nursing duties, the COVID-19 pandemic increased specific stress factors that were also considered in this research and were confirmed by previous studies: the fear of getting sick with COVID-19, miscommunication and social distance at workplace, mask wearing, more frequent use of disinfectants, and increasing of patients’ number , 27. AlmThe lack of experience and professional knowledge in managing a pandemic situation of these proportions were considered the most stressful factors for nurses in this period by Mo et al. . HoweverIn many hospitals in Romania, new equipment has been received during the medical crisis, but that has required additional qualification. This aspect did not represent the most stressful challenge for most of the nurses in our sample.During the pandemic, most of the employed nursing students considered self-control as the most efficient copying strategy to stress (34.17% of the employed students). Self-control strategy is associated with good health of nurses, increases immunity and makes them less vulnerable to coronavirus .There are other studies confirming that self-control is an efficient method to cope with stress and it might refer to: positive thinking, physical exercise, recreation, tolerance, self-learning, self-reliance, compassion for the patients being in a more difficult situation, caution to avoid other stressful situations and prayer , 28. AllOnly 20% of the employed nursing students considered families as being essential in this pandemic in the study of Elloker (2003) . The supDuring the pandemic, 27.5% of the nursing students surpassed the stresfull situations with the aid of spiritual support. This copying strategy is the second as importance in our study. More levels were identified for the spirituality acts: individual stage consisting of personal opinions, primary and secondary levels (recognizing the power of God), coping resources (contact with nature), coping behavior (telling prayers and reading holy books) and spiritual improvement . The impDuring the pandemic, only 4.17% of the nursing students believed that medical unit management had the highest contribution in reducing the stress. This low percentage for this copying strategy with stress suggests that management of medical units should be improved.Our results have practical implications for strategies to cope with stress during the pandemic, for the management of medical units and for the higher education nursing. The pandemic context could not be stopped by nurses, but they should try to adapt themselves to new conditions and control their emotions and behaviors. Given this situation, besides self-control, spirituality could be also an important pillar for nursing students working in Bucharest.In addition to the previous recommendations that strictly refer to nurses’ acts, medical centers should implement strong policies in order to promote an adequate physical and structural environment. At institutional level, work security, flexible scheduling, interactive management and labor relations, good communication practices should be implemented by the managers of the medical units. Investment is necessary in order to promote those policies that help nurses in preventing diseases and maintaining good health. In addition, educational interventions are necessary in order to inform nurses about the strategies to cope with stress, maintain good health and good balance between work and profession.Specific strategies are necessary for students preparing themselves to work as nurses. Educational initiatives are the most important strategies for students to prepare themselves in order to face the pandemic challenges in their future work. They should also be motivated to practice this work since there is a shortage of personnel in this field in Romania. Faculties should adapt their educational programs in order to include web-based learning activities about coping with stress and ensuring personnel health and safety.Apart from these relevant results, our research presents few limits that allow us to indicate future directions of study. First, there are other factors that influence the vulnerability to stress which were not taken into account when computing the stress scores using Miller and Smith scale and the list of stressors proposed to students during the pandemic . Therefore, in a future study, nursing students should be asked to indicate other particular factors of stress with a significant impact on them.Second, this research only focused on a quantitative analysis of vulnerability to stress. Most of the studies from literature have focused on qualitative approaches in understanding the stressful circumstances for nurses, but this work limited itself to quantitative approach, because the number of nursing students is quite large and costs and time for individual interviews are higher. The results based on our quantitative approach are useful for the implementation of general policies in the Romanian medical system, but the consultation of a psychiatrist is necessary in case of people with a high level of stress who need specialized treatment.Third, our strategies to cope with stress were designed only for employed nursing students and may not be relevant for non-employed students. Different strategies in order to face stressful situations should be applied depending on the status of nursing students on labour market (employed or non-employed ones). The individuals who already work as nurses might need different strategies to cope with stress comparing to nursing students who are preparing themselves to start working in this field. However, the current recommendations for employed nursing students during the pandemic could be useful for non-employed colleagues when they are employed as nurses.Fourth, the sample of nursing students is representative for Bucharest, the capital of Romania, but not at national level. Therefore, the conclusions of this study could not be generalized to the entire population of nursing students in Romania. However, the research could be extended in order to include the other university centers with faculties of nursing. Comparisons between students coming from all these faculties are useful to verify whether the same stressors affect them the same manner and whether the same copying strategy was the most efficient.Workplace stress has become a more critical challenge in the labour market. Stress can affect hormonal balance and normal physiology of employed nursing students, thus, learning the stress coping strategies is essential in order to maintain good health, an acceptable life quality and well-being.The aim of this research is to assess the vulnerability to stress of nursing students depending on their status on labour market before and during the COVID-19 pandemic. The results indicated that employed nursing students were more vulnerable to stress comparing to non-employed students before and during the medical crisis. In addition, the nursing students working in the medical system experienced medium vulnerability to stress during the pandemic, comparing to those working before the pandemic who experienced low vulnerability to stress.Excepting the non-employed students before the pandemic, the females in the sample were more vulnerable to stress comparing to males because of their specific endocrine system, work involving emotions and other household duties, while the students in rural environment experienced stress more than those living in cities/towns because of commute and lower standard of living.During the pandemic, most of the employed nursing students indicated that the fear of getting sick with COVID-19 was the most stressful factor for them, while most of them claimed self-control as being the best strategy for them to copy with stress.In a future study, other factors impacting the vulnerability to stress will be considered: the increased use of Internet for communication, including online lectures and degree of confidence in COVID-19 vaccine. Apart from these factors of stress, other stressors should be considered in a future study. The department in which nursing students work might impact the vulnerability to stress. The nurses in emergency department might be more stressed out comparing to those in other departments. Aspects related to family should also be considered in another research: fear to get sick with the virus, unemployment, less time spent with family because of nursing duties etc.The quantitative approach will be completed with interviews with each nursing student based on their agreement and university ethical approval. In addition, the interviews will help us to identify different strategies to cope with stress for employed nursing students and non-employed students. A future research might include data from other universities in the country with this specialization, comparisons between faculties being necessary.S1 File(DOCX)Click here for additional data file.


Link adaptation (LA) is the ability to adapt the modulation scheme (MS) and the coding rate of the error correction in accordance with the quality of the radio link. The MS plays an important role in enhancing the performance of LTE/LTE-A, which is typically dependent on the received signal to noise ratio (SNR). However, using the SNR to select the proper MSs is not enough given that adaptive MSs are sensitive to error. Meanwhile, non-optimal MS selection may seriously impair the system performance and hence degrades LA. In LTE/ LTE-A, the LA system must be designed and optimized in accordance with the characteristics of the physical  and MAC layers  to enhance the channel efficiency and throughput. Accordingly, this study proposes using two LA models to overcome the problem. The first model, named the cross-layer link adaptation (CLLA) model, is based on the downward cross-layer approach. This model is designed to overcome the accuracy issue of adaptive modulation in existing systems and improve the channel efficiency and throughput. The second model, named the Markov decision process over the CLLA (MDP-CLLA) model, is designed to improve on the selection of modulation levels. Besides that, our previous contribution, namely the modified alpha-Shannon capacity formula, is adopted as part of the MDP-CLLA model to enhance the link adaptation of LTE/LTE-A. The effectiveness of the proposed models is evaluated in terms of throughput and packet loss for different packet sizes using the MATLAB and Simulink environments for the single input single output (SISO) mode for transmissions over Rayleigh fading channels. In addition, phase productivity, which is defined as the multiplication of the total throughput for a specific modulation with the difference between adjacent modulation SNR threshold values, is used to determine the best model for specific packet sizes in addition to determine the optimal packet size for specific packet sizes among models. Results generally showed that the throughput improved from 87.5 to 89.6% for (QPSK  In 2004, an initial study of long-term evolution (LTE) was introduced and viewed as a path for migration to 4G networks . The goaLTE and LTE-A are the primary communication technology and have a capability for the deployment in a place where it becomes complicated to get with other technologies such as digital subscriber line (DSL) or cable. This complicated process is because of the deployment’s cost; maintenance of such technologies; and the distinguished features of LTE, such as the high capacity of transmission bandwidth that reaches to 20 and 100 MHz in LTE and LTE-A, respectively . Such baRecently, the data transferred by wireless network devices and multimedia system are merged and developed as one of the main parts for this mode of network. In view of the outbreak of the highly contagious COVID-19 pandemic, millions of people are now working and studying from home using online services and software such as movie streaming applications, video conferencing tools, and online schooling applications. The high demand for network bandwidth due to these services led to a degradation of broadband network performance across the board. Spillover effects are expected on wireless cellular networks even after the end of mandatory lockdowns due to the increased use of such services in the typical work and study environment. Despite the promise of 5G technology to provide higher bandwidth capacities to meet the increases in bandwidth demand, the slow-paced 5G-network deployment in many countries means that existing LTE/LTE-A networks will experience degraded network performance for the foreseeable future. As videos are streamed, the broadband wireless networks are influenced by many factors that negatively affect the quality. For example, the dynamic nature of wireless networks with user mobility poses challenges in maintaining the quality and transmission of video. In addition, distance has drastically affects the received signal strength (RSS), which then directly affects the quality of video transmission. As the outcome of this effect takes action, the channel efficiency and video quality are considerably reduced, which result in degrading the network performance , 7.The LTE/LTE-A standards use frame aggregation in the MAC layer, that is, multiple numbers of MAC Service Data Unit (MSDUs) are transmitted via one frame transmission. Using a larger aggregated packet size in the MAC layer introduces a lower transmission reliability and higher channel efficiency and vice versa. This finding indicates that packet size could affect system performance. Thus, an improper packet size could negatively affect system performance.LA is a technique used to adapt modulation to the link budget for improved adjustments of the changing channel conditions . MeanwhiReduction in channel efficiency and challenges of path loss that occur because of varying in channel conditions such as fast dynamic nature of wireless networks with user mobility and stringent requirements of QoS (required packet loss) , 11The inaccuracy of dynamic modulation switching in the existing approach due to the misprediction of switching levels, and unspecified policy for selecting the best MS for various link conditions.Using improper packet size could introduces a lower transmission reliability and/or affects channel efficiency, and hence, it could negatively affect system performance as represented in .The current proposed work extends our previous paper [The proposed work aims to tackle the following challenges: us paper , which eus paper  is adoptus paper  by propous paper  owing toThe CLLA model is proposed, which adapts several parameters across physical and MAC layers including the analytical prediction of packet loss for the next modulation for improvement in throughput and adaptive modulation.Because of the limitation accuracy issue of adaptive modulation in CLLA model, the dynamic optimization MDP-CLLA model is proposed, which predicts the switching levels of adaptive modulation scheme more precisely and hence selects the optimal modulation level more accurately and offers more enhancement in throughput and LA of LTE/LTE-A.The performance  of proposed framework is evaluated against the existing approach with respect to the variation of different packet sizes and modulation schemes. The evaluation and comparison with the existing approach confirm the feasibility of the proposed models. Furthermore, the suggested models have been evaluated in terms of optimal packet size, which shows that the proposed work has a significant impact on the phase productivity when compared to the existing work.Many researchers [The contribution of this research can be summarized as follows: earchers , 15–17, The rest of the paper is organized as follows: Sect. This section provides an overview about LTE/LTE-A networks, the importance of LA, and the channel quality indicator measures required for this study.LTE and LTE-A play a significant role in offering connectivity to the Internet. However, with the widespread of multimedia applications, the demand for QoS support  in LTE and LTE-A has been increased dramatically. The bandwidth transmission for LTE and LTE-A can cover up to 5 km of urban and suburban areas and up to 100 km in rural areas. Because of these characteristics, LTE/LTE-A is a suitable option, offering cost-efficient and quick to be deployed. The LTE/LTE-A deployment architecture utilized in this research is point-to-point (PTP) since it aims to improve video transmission by taking the dynamic nature of broadband wireless networks and adjusting modulation based on the signals received and SNR measurements . LTE/LTEThe importance of LA is coming from that, in data and communication networks, the transmitted data are treated with unequal importance especially for video content and the loss of some video packets has a higher distortion impact on the received video quality compared to other less important packets, in addition to the difficulties of keeping growing the data rate as high as possible within bandwidth and power restrictions. To overcome this issue, spectral efficiency must be driven to the maximum . WirelesThe main parameter influencing QoS parameters, especially throughput and packet loss, is SNR, which is the ratio between the maximum signal strength that a wireless connection can achieve and the noise present in the connection . When thIn the literature, several researchers have proposed different methods for the improvement of LTE/LTE-A networks’ performance. For example, methods including link adaptation, power allocation, and QoS requirements were proposed. In , for exaBefore discussing the proposed models, the PER and SNR threshold values for several packet sizes are determined in this section.L, and the bit error probability for the channel is denoted by To avoid confusion of symbol or bit, the latter is used as the representative in packet size and error rate rather than symbol in this paper. Therefore, PER is determined using BER and the bits’ numbers in the packet. The packet’s length in bits is denoted by rding to , the PERmentclass2pt{minimB, the show and measure the SNR results mathematically and experimentally and the level of closeness from one another.use the simulation results of SNR threshold values to obtain the throughput and packet loss for various packet sizes with different modulation types.Table Based on equation mentclass2pt{minimThis paper extends the work presented in  by propoThe proposed work enhances the optimal decision of link adaptation for LTE/LTE-A and fits the quality requirements for the LTE/LTE-A. In fact, two link adaptation models are proposed. The first model is called cross-layer link adaptation (CLLA) and is based on the downward cross-layer design approach. The purpose is to consider the disparate of the system at MAC/physical layers. Consequently, at the physical layer, the received frame is measured on the basis of channel condition adaptation and path loss. It is measured by utilizing the mobility distance while adapting the PER at the MAC layer. However, the second model adopts the MDP over the cross-layer design approach (MDP-CLLA). In fact, the MDP-CLLA model uses the measured process of the CLLA model, where the selection of appropriate modulation is optimally chosen for the next frame and is sent as feedback to the sender. Additionally, the evaluation and comparison between the performance of proposed models and the existing LTE system are performed in terms of throughput, packet loss, overhead packet size , and phase productivity for different modulation schemes with different packet sizes.The framework of the CLLA model is illustrated in Fig. The algorithm of the CLLA model constitutes four parts: the main algorithm of the CLLA model; the packetization of data as indicator of MAC layer located at the transmitter side; the de-packetization of data at the receiver side; and the computing part of PER, number of error packets, and throughput. Algorithm 1 represents the algorithm of the CLLA model. As shown in Fig. The MDP-CLLA model consists of modified alpha-Shannon capacity formula and link adaptation and reception scheme.The modified alpha-Shannon capacity formula addressed in  is adoptFigure On the basis of MDP algorithm, Fig. In addition, the MDP algorithm is solved by the agent component see Fig.  through The algorithm of the MDP-CLLA model consists of the main algorithm of MDP-CLLA model; the packetization of data at the transmitter side; the de-packetization of data at the receiver side; and the computing part of PER, number of error packets, and throughput as shown in Algorithm 2.The reward function and the dynamic programming method used to obtain the optimal policy through the transition probability are presented below:Several studies on link adaptation have been discussed by using the reward function for throughput maximization. In , varyingNL bits at the receiver side. Here, N is the number of packets in a frame, and L is the number of bits per packet. The current throughput becomes dependent of SNR as long as throughput adaptation is implemented in the downlink channel. Throughput can be calculated using the formula below [The received frame comprises la below : 21\docucally in .R is the transmission rate. The frame throughput (Th) is given as follows: The frame is considered the data unit transmitted in point-to-point communication system. Therefore, the frame period time for each transmission is In addition, the number of bits for each modulation type must be added to the objective function, and it is done by Let PER imply packet error rate Since FER should be within an acceptable range, SNR FER, when using the The probability density function (PDF)xp(-γγ0)  for the In Eq. , no tranLet FER is considered a performance indicator of the link layer in the reward function. The utility function per frame is presented as follows:Now, to calculate the average frame error rate Thus, the reward function is expressed as:M) is the action that can be taken by the control agent.To increase the throughput, the range of FER must be adequate. Hence, increasing throughput per decreasing FER is considered the objective function. The proposed objective function is organized as follows: Maximizing the objective function through determining the decision policy bability  for all K intervals), Steady-state probabilities: r to Eq.  \documenLCF is the level crossing function that measures the rapidity of fading.State transition probabilities: The correlation fading process structure can be described through the effective FSMC approach. FSMC is used to model the dynamic of wireless channel in point-to-point communication . FSMC diThe state transition probability can be built as follows: First, determine the SNR state as In this respect, the channel is modeled as FSMC, and the Successful transmission: Failed transmission: Suppose the current state is The current research evaluated the performance of the existing LTE/LTE-A system, CLLA, and MDP-CLLA in terms of throughput and packet loss for orthogonal frequency-division multiple access (OFDMA) modulation scheme with different packet sizes. In addition, it calculated overhead packet size to determine optimal packet size and then the best phase productivity to determine the best model for each packet size.Regarding throughput and packet loss, the packet size comprises the MAC header apart from its payload. Therefore, the MAC header is excluded when calculating the throughput and packet loss.This subsection discusses the meaning behind the overhead packet size including the method of determining the number of packets and the meaning of phase productivity that helps in the process of determining overhead packet size and best phase productivity among models.The overhead discussed in this subsection has two types. The first is header size overhead (space overhead), and the second is modulation switching overhead (processing overhead).The space overhead is actually the bits that are used for MAC header protocol. In this research, these bits are excluded when the throughput is calculated. In the LTE/LTE-A system, the frame size is fixed on the basis of the modulation type. Its size is approximately 26,400 bits in the case of QPSK. For example, in the case of having 1000 bits of packet size, 27 packets are required to fill the frame bits, whereas only 4 packets are required for 8000 bits packet size. Hence, the overhead of 1000 bits packet becomes higher than that with 8000 bits.The processing overhead is the overhead that results from the processing time, which results from switching between modulations. Indirectly, SNR distance  and a UE, where data are transferred from eNode B to UE. The transmission mode 4 (closed loop) is implemented on the basis of 3GPP TS 36.211 V15.6.0 (2019-06) standard release. A channel knowledge at the transmitter is required at closed loop and occurs when dynamic adjustment is executed on the basis of the feedback of UEs. In addition, PTP is the type of connection between eNodeB and UE. Table The results of the existing LTE system, the CLLA model, and the MDP-CLLA model on the bases of throughput and packet loss are discussed here. Consequently, according to –36, the Existing LTE systemIn the existing LTE system, Fig. As shown in Fig. Furthermore, increasing packet size leads to a decrease in the number of packets for each frame, thereby decreasing the total MAC header data. At the end, the peak data rate is increased because of the less total MAC header data excluded from throughput computation.CLLA ModelIn the CLLA model, Fig. As shown in Fig. MDP-CLLA ModelIn the MDP-CLLA model, Fig. This subsection describes the throughput results in the case of SISO mode with various packet sizes. In this respect, the corresponding data rates of SNR threshold values for various packet size are presented. The purpose of these experiments is to show the effect of increasing packet size at different modulation levels to the throughput result on the proposed models compared with the existing system.Existing LTE systemFigure CLLA ModelFigure MDP-CLLA ModelAs shown in Fig. This part presents a scenario of the accepted packet loss for a given SNR threshold values in various packet sizes. This scenario includes three different experiments on the bases of the modulation type where the results are presented in terms of different packet sizes (see Table Discussion of Comparison among the Models based on throughput and packet lossSwitching from modulation to another is presented by determining the adaptive switching SNR range (ASR) which includes the range among the SNR switching points of the MDP-CLLA model, the CLLA model, and the existing LTE system. The purpose of this switching level is to compare the improvement of throughput among different models. Switching modulation can be (QPSK to 16-QAM) and (16-QAM to 64-QAM). As shown in Figs. To elaborate this finding, the comparison between the CLLA model and the existing system  software. The results were presented as mean ± standard deviation (SD). Statistical analysis of the data was carried out by using one-way analysis of variance (ANOVA) followed by post hoc test. The differences between the means were considered significant at For Rayleigh channel, Table Obviously, the MDP-CLLA model is proven to be the best efficient model compared with the CLLA and the existing system, as it has the highest significance. Table Overall, the outcomes of the MDP-CLLA model become the best in terms of accuracy of link adaptation compared with the CLLA model and the existing system since it is able to find all potential solutions and can identify the optimum utilizing the average reward function.This research is aimed to enhance the channel efficiency and throughput within an acceptable error rate by proposing a framework at physical and MAC layers containing two LA models: the CLLA and the MDP-CLLA models. The CLLA model is based on downward cross-layer utilizing analytical prediction of packet loss for the next modulation at the MAC layer beside deterministic SNR threshold values at physical layer. The MDP-CLLA model is proposed over the CLLA model that selects the optimal modulation level more accurately to be used for the next frame transmission. It offers more enhancement in throughput and channel efficiency compared with the CLLA model and the existing LTE system. Generally, the experimental results showed that the throughput in the CLLA model is improved by 87.5–89.6% and by 0–43.3% for (QPSK


Dental health care workers around the world are in a constant state of fear and anxiety because they work in a constrained space of the dental practice. During routine dental procedures, they are exposed to aerosol and splatter. These airborne particles pose a great risk of transmitting contagious infections to health care workers and patients, especially in an era of social distancing due to COVID-19. The current study was conducted to evaluate contamination amount, duration, the distance of aerosol, and splatter produced after cavity preparation using a two-hole and four-hole handpiece. The study was performed on a dental manikin in a dental simulation laboratory at the College of Dentistry, King Faisal University Al Ahsa. The dental manikin was set to a reclined position to simulate the clinical operatory position of the patient for dental restorative procedures. Aerosol and splatter were collected on Grade 1 qualitative cotton cellulose filter paper. These were placed on adhesive tape extending from the headrest of the dental manikin in six different directions  for up to 60 inches and on certain positions of the operator and assistant such as the chest, head, forearms, upper leg, and inside facemask. Class V cavity preparation was done by the principal investigator at a specific time of 3 min on tooth #11 using a two-hole high-speed handpiece, then on the next day, Class V cavity preparation was performed on tooth #21 by a four-hole handpiece. High volume suction was used throughout the cavity preparation. Immediately after cavity preparation, the first filter paper disc was replaced with new ones in all positions. The second set of filter papers was removed after 30 min. Transparent grids were used to count the contamination area on the filter paper disc. No statistically significant difference was found in the mean amount of aerosol and splatter produced by both handpieces, however, a statistically significant difference was found in an amount of aerosol and splatter produced at a 12, 24, and 36 inches distance immediately after cavity preparation and 30 min after cavity preparation, regardless of the type of handpiece used. It is advisable to refrain from removing the personal protective barriers immediately after the procedure within the vicinity of the dental practice. The use of other adjuncts such as high volume suction to reduce the spread of aerosol and splatter is also recommended. The majority of the dental health care workers are working in the constrained space of dental practice . During Dental procedures involving the use of a high- or low-speed handpiece, ultrasonic scaler, and air-water simultaneous spray from a triple syringe are liable to produce a huge amount of aerosols in the dental environment contaminated with saliva and/or blood ,8. A higDental rubber dam isolation reduces microbial contamination by controlling the dissemination of aerosol and splatter in clinical ambiance. Studies have also highlighted the significant role of high volume suction in mitigating the production of aerosol and splatter generated by the high-speed handpiece during dental procedures to more than 90% ,12.Recently, the airborne route of infection has received great attention due to the COVID-19 pandemic . The impConsidering the aforementioned rationale, the current study was conducted to evaluate contamination amount, duration, the distance of aerosol, and splatter produced after the cavity preparation using a two-hole and four-hole high-speed handpiece. In addition, it may help clinicians to propose guidelines to design adequate space for safe dental operations.The study was performed on a dental manikin in the dental simulation laboratory at the College of Dentistry, King Faisal University Al Ahsa. The manikin was set to a reclined position to simulate the clinical operatory position of the patient for dental restorative procedures. Rubber dam isolation was achieved for the upper anterior quadrant from tooth #13 to #23, as shown in One gram of ultra-filtrate containing fluorescent dye  was mixed with one liter of water and filtered . This mi2 box  then on the next day, Class V cavity preparation was performed on tooth #21 by a four-hole handpiece . High volume suction attached to the dental manikin  was used with a vented tip throughout the cavity preparation, which was standardized by testing the liquid uptake of 1 L per minute. Immediately after cavity preparation, the first filter paper discs were replaced with new ones in all positions. The second set of filter papers were removed after 30 min. The splatter and aerosol contaminated area on the filter papers were calculated by using transparent grids containing a 1 cm2 box . Each fit-test was used to compare differences in the aerosol and splatter produced using two holes and four holes handpiece. Differences in the amount of splatter produced immediately after cavity preparation and 30 min after cavity preparation were assessed using a paired t-test. A p-value ≤ 0.05 was considered statistically significant.Data were analyzed using SPSS version 23.0. Mean and standard deviation was calculated for aerosol and splatter produced during cavity preparation at different positions and distances. An independent 2 and 70 cm2 were recorded using the two- and four-hole handpiece, respectively, at the 10 o’clock position and a distance of 12 inches. The amount of splatter decreased with an increase in distance and was found to be the lowest at a maximum distance of 60 inches away from the patient  compared to the assistant area (197 cm2). The operator’s right hand and the assistant’s left hand were most prone to contamination by the splatter during cavity preparation, followed by the head, chest, and the least contamination was inside the mask for both the operator and assistant (The assessment of the contaminated surface area on the body revealed that the operator area was more contaminated (254 cmssistant .Comparing the two and four-hole handpieces, no significant difference was found in the mean amount of aerosol and splatter produced by both handpieces . The amoThis study was conducted to evaluate the amount and duration of aerosol and splatter produced during cavity preparation using a two-hole and four-hole high-speed handpiece, at various positions and distances. The result of the current study showed no statistically significant difference in the mean amount of aerosol and splatter produced by both handpieces, however, a statistically significant difference was found in the amount of aerosol and splatter produced at distances of 12, 24, and 36 inches immediately after cavity preparation and 30 min after cavity preparation, regardless of the type of handpiece used.In this study, maximum splatter and aerosol produced immediately after the procedure were found at the operator zone, followed by the assistant zone. This finding contradicts the previous study in which investigators found more splatter in the assistant zone compared to the operator zone . This diIndubitably, various contagious diseases such as HIV and HBV are transmitted through blood, saliva, and the gingival fluid of patients with known or unknown infection; therefore, it is wise to consider all patients potentially infective, irrespective of their medical history ,21. AddiRecently, COVID-19 infection has received great attention due to the easy transmission through the respiratory route. Ahmed et al.  reportedThe two-hole handpiece is also called Borden’s handpiece, after its successful development by Dr. John Borden’s in 1950. The turbine and body are the main components of the air-driven handpiece. Stainless steel and brass are the most common materials used to manufacture handpieces. Stainless steel handpieces are heavier and expensive than brass handpieces. However, titanium-based handpieces are preferable nowadays by clinicians and the manufacturer due to their lighter weight and greater resistance to repeated sterilization cycles compared to stainless steel . LikewisIt has been noticed that the whole circumference around the manikin showed splatter contamination for up to 36 inches immediately after the procedure except at the 4 o’clock position with both handpieces and 12 o’clock with the four-hole handpiece. This result is similar to Llandro et al.  in whichBennet et al.  reportedConsidering the findings of the current study, aerosol and splatter can spread up to 36 inches; therefore it is desirable to make an arbitrary “red zone” around the dental unit. This red zone will require thorough cleaning and disinfection by antiviral or antimicrobial disinfectant after every patient. No one should be allowed to enter the red zone during the procedure, except for the dentist and the assistant.Clinic ventilation plays a major role in mitigating the spread of airborne infections. Sarapultseva et al.  reportedThis study has some limitations that include the use of liquid volume uptake to measure suction flow due to the unavailability of a flowcheck device. Moreover, the concentration of splatter was not assessed and even a single drop was counted as positive in measuring grid squares. Since the tooth preparation was done only on anterior teeth by the high-speed handpiece, the results should be interpreted cautiously and cannot be generalized, as the results might be different for posterior teeth and with the use of some other devices such as a low-speed handpiece or ultrasonic scaler. Finally, a complete study was conducted on the dental manikin, which does not have saliva and blood, and hence may not produce a real-life work scenario.This study emphasizes that the dissemination of contaminated aerosol and splatter after cavity preparation remains a major threat to dental staff in the era of the COVID-19 pandemic. Therefore, it is advisable to use surgical disposable gowns, caps, face shields, or safety glasses, and refrain from removing the personal protective barriers immediately after the procedure within the vicinity of the dental practice. The use of other adjuncts such as high volume suction to reduce the spread of aerosol and splatter is also recommended.


Electrocardiograms (ECGs) provide important information for diagnosing cardiovascular diseases. In clinical practice, the conventional Ag/AgCl electrode is generally used; however, it is not suitable for long-term ECG measurement because of the risk of allergic reactions on the skin and the dying issue of electrolytic gels. In previous studies, several dry electrodes have been proposed to address these issues. However, most dry electrodes, which are the mode of conductive materials, have to contact the skin well and are easily affected by motion artifacts in daily life. In the smart clothes developed in this study, a noncontact electrode was used to assess the biopotential across the clothes to prevent skin irritation and discomfort. Moreover, a three-dimensional parametric model based on anthropometric data was built, and the technique of customized product design was introduced into the smart clothes development process to reduce the influence of motion artifacts. The experimental results show that the proposed smart clothes can maintain a good ECG signal quality stably under motion from different activities. An electrocardiogram (ECG) is an important biosignal that reveals the electrical activity of the heart and can be used for diagnosing cardiovascular diseases, such as myocardial hypoxia, myocardial infarction, and arrhythmia. To access ECG signals, a conventional Ag/AgCl electrode is most commonly used in clinical research. In general, it is applied with electrolytic gels to improve the conductivity between the skin and the electrode . HoweverRecently, many dry electrodes that measure biopotentials without electrolytic gels have been developed. However, many dry electrodes still encounter the issue of higher electrode–skin interface impedance because of the poorer contact between the skin and the electrode. Various types of conductive material and structure have been applied in the development of dry electrodes ,9,10,11,In 2016, Pani et al. proposed a fully textile electrode . The soalectrode . This elIn contrast to the above dry electrodes, which have to contact the skin directly or invasively, capacitive electrodes have also been developed to access biopotential without direct contact with the skin directly ,17,18. HIn this study, smart clothes using noncontact ECG electrodes and customized product designs were developed to access real-time ECG signals in daily life, even under motion. Moreover, in contrast to other smart clothes that usually do not contain both custom clothes and human-body-related numerical monitoring, a 3D parametric model based on anthropometric data was constructed. A customized product design technique was introduced into the smart clothes development process. To improve the fit of the smart clothes, a large amount of 3D mesh data of the human body were collected, a parametric torso model approximating the human body contour was established, and computer-aided design was integrated for smart clothing appearance design and tailoring. In the proposed smart clothes, noncontact electrodes can be easily placed on the chest and stably acquire the ECG signal by utilizing the mechanical design of the smart clothes. Finally, the performance of the ECG signal under different motion activities  was also investigated. The experimental results show that the ECG signal quality obtained by the proposed smart clothes is as good as that of the conventional electrode with conductive gels, and it can maintain a stable signal quality during different activities in daily life.The system architecture of the proposed smart clothes is illustrated in For the conventional Ag/AgCl electrode, conductive gels are usually applied in the gap between the epidermis and the electrode to reduce the equivalent impedance formed from the skin–electrode interface to acquire a higher-quality ECG signal. Therefore, in the equivalent electrical model for the electrode–skin interface of an Ag/AgCl electrode with conductive gels, the impedance of the conductive gel layer can be represented as a resistance. Because the epidermis also has the capacitance property , its mods. Cs denotes the capacitance formed from the electrode–skin interface. Rb denotes the equivalent impedance of the bias pathway. The input resistance and input capacitance of the operational amplifier are represented by Ri and Ci, respectively. The transfer function of the noncontact electrode can then be expressed asi, Rb, and Cs are increased or the value of Ci is decreased. The values of Ri, Rb, and Ci can be determined by selecting a suitable characteristic of the operational amplifier. An increase in Cs can be achieved by reducing the distance between the human body and the metal plate, or by expanding the area of the metal plate.According to Equation (1), a better signal quality of biopotential measurement is obtained when the values of RIn recent years, the technique of a 3D parametric model with a human body scanner has rapidly developed in clothing design to alleviate the issue of measurement error resulting from individual errors. In this study, a 3D parametric model based on anthropometric data collected by the 3D human body scanner  was built, and the customized product design was introduced into the smart clothes development process. In contrast to conventional 3D scanners, the structure sensor of the 3D human body scanner used is compatible with tablets allowing fast and convenient data collection of anthropometric body dimensions for clothing design.Although the scanner used has the advantages of a fast data capturing rate through noncontact measurement, the captured point groups occasionally exhibited poor quality, with several issues of overlapping, porosity, and noise. Therefore, data postprocessing is necessary to ensure consistency in the human body dimension database. Fourteen feature dimensions related to 3D human body dimensions  were selR-waves in this segment are extracted. After all R-waves have been detected, the R–R interval, related to the heart rhythm, can be estimated. After the ECG analysis procedure, the raw ECG data, heart rhythm, and activity time are recorded. The platform of the back-end system can provide not only the current ECG analysis but also weekly or monthly reports of activities and exercises summarized from the ECG database. A scenario diagram of the proposed smart clothing system is shown in A commercial laptop with the Windows 10 operating system was used as the platform of the back-end system. In the back-end system, the real-time ECG monitoring program is a Windows application developed using Microsoft Visual Studio. A flowchart of the proposed program is illustrated in In this section, the electrical characteristics of the proposed noncontact electrode are discussed. In this experiment, metal plates covered with insulation tapes, connected to a function generator, were placed close to the proposed noncontact electrode. The function generator produced a 3-V peak-to-peak sinusoidal waveform with varying frequency (0.01–1000 Hz) to estimate the magnitude and phase responses. The experimental results are shown in To investigate the ECG signal quality obtained by the proposed noncontact electrode, the conventional Ag/AgCl electrode with conductive gels and the proposed noncontact electrode are compared in this section. In the experiment, the subject was instructed to wear the smart clothes to acquire lead-I ECG signals across the cotton clothes, and three Ag/AgCl electrodes were placed close to these noncontact electrodes simultaneously. The ECG signals obtained by different types of electrodes and their ECG spectra are illustrated in Smart clothes have the highest consumption rates among these products. The quality of the clothing design lies in the production of clothes that are close to the body. In this study, young Taiwanese men were used as subjects to establish a 3D human body database. The characteristic parameters of the human body were defined, and a linear regression model was adopted to establish the relationship between the parameters and a grid. Using this technique and the body characteristic parameters, geometric shapes similar to the physical bodies could be generated swiftly. Using these shapes, the users could customize their clothes by drawing curves onto the body model, retrieving the area within the range of the curves, and using meshing techniques to minimize the length of the boundary curve and the sum of boundary vertex angles to smooth out the body model. The efficiency of 3D human body modeling for ECG measurement using noncontact electrodes was investigated. The smart clothes based on the parameterized 3D human body model, the average 3D human body model, and commercial gym clothes with a chest strap were used for testing. The average 3D human body model was generated from the proposed 3D parametric model by averaging the coordinates of each feature dimension in all 3D human body models. According to Next, the influence of the textile material and thickness of the smart clothes and sweating on the ECG measurement were investigated. The experimental results of the ECG measurement for different textile materials and thicknesses of the smart clothes are shown in Finally, the performances of the developed smart clothes and conventional Ag/AgCl electrodes under different daily activities and exercises, such as sitting, standing, walking, running, and jumping, were evaluated. The participants were instructed to perform different activities continuously every 5 s. The ECG signals acquired by the developed smart clothes and conventional Ag/AgCl electrodes are shown in The experimental results in The practicability and stability of the proposed smart clothes for ECG measurements under motion in daily life were also compared to those of conventional Ag/AgCl electrodes. The stability of the ECG signal quality obtained by the proposed smart clothes while walking was as good as that of sitting and standing. However, under some intense exercise (running and jumping), the motion artifact still caused a slight shift in the ECG baseline, but the ECG signal quality was still acceptable. The influence of intense exercise on the ECG measurement of the conventional Ag/AgCl electrodes was serious compared to the designed smart clothes because of the swinging of the ECG cable.In previous studies, smart clothes were developed to monitor biopotential, and a comparison between other smart clothes and the proposed ones is listed in In 2017, Liu et al. proposed smart clothes using a CNT-PDMS polymer electrode, consisting of a vest sewed with a polymer electrode (electrode diameter of 30 mm) and a commercial ECG recorder . The PDMIn this study, smart clothes were developed to monitor ECG signals using a noncontact sensing technique. In contrast to the above smart clothes, the proposed ones can effectively avoid skin irritation and reduce the influence of hair or sweat by accessing the ECG signal across the clothes. Moreover, the antimotion circuit of the ECG acquisition module and the mechanical design can effectively improve the measurement performance under motion in daily life. The proposed smart clothes design was developed using a noncontact sensing technique and the technique of a 3D parametric model with anthropometric data. Using the noncontact sensing technique, the proposed smart clothes can assess the long-term biopotential across the clothes to prevent skin irritation and discomfort. A 3D parametric model based on anthropometric data was built based on the body of the user to approximate the body geometry, and the technique of the customized product design was introduced into the smart clothes development process to reduce the influence of motion artifacts. Therefore, the designed smart clothes have great potential for monitoring ECG continuously in daily life. The wireless noncontact ECG acquisition module, wearable mechanical design of smart clothes, and back-end system platform in the proposed system were self-designed and self-assembled.Novel smart clothes with a noncontact biopotential sensing technique were proposed to monitor ECG signals across clothes. The mechanical design of smart clothes can effectively reduce the occurrence of motion artifacts. The electrode specifications demonstrate that it is adequate to acquire most biopotentials. Moreover, the signal quality of the proposed noncontact dry electrode was as good as that of the conventional electrode with conductive gels (correlation > 95%). The experimental results show that the proposed smart clothes can maintain a stable and good signal quality under different activities in daily life. Compared to most of the current smart clothes that must contact the skin directly, the proposed smart clothes can avoid the problem of skin irritation for long-term ECG measurement and provide a better ECG signal quality under motion. Therefore, the proposed smart clothes have great potential for monitoring ECG continuously in daily life.


Bladder cancer is a common cancer of the urinary tract, characterized by high metastatic potential and recurrence. The research applies a transfer learning approach on CT images  for the purpose of semantic segmentation of areas affected by bladder cancer. A system consisting of AlexNet network for plane recognition, using transfer learning-based U-net networks for the segmentation task. Achieved results show that the proposed system has a high performance, suggesting possible use in clinical practice.Urinary bladder cancer is one of the most common cancers of the urinary tract. This cancer is characterized by its high metastatic potential and recurrence rate. Due to the high metastatic potential and recurrence rate, correct and timely diagnosis is crucial for successful treatment and care. With the aim of increasing diagnosis accuracy, artificial intelligence algorithms are introduced to clinical decision making and diagnostics. One of the standard procedures for bladder cancer diagnosis is computer tomography (CT) scanning. In this research, a transfer learning approach to the semantic segmentation of urinary bladder cancer masses from CT images is presented. The initial data set is divided into three sub-sets according to image planes: frontal (4413 images), axial (4993 images), and sagittal (996 images). First, AlexNet is utilized for the design of a plane recognition system, and it achieved high classification and generalization performances with an  Urinary bladder cancer is one of the ten most common cancers worldwide. It is characterized by an cancerous alteration and uncontrollable growth of bladder tissue, typically urothelial cells, which develop into a tumor and can spread into other organs. Patients who suffer from bladder cancer may exhibit various symptoms, such as painful and frequent urination, blood in the urine, and lower back pain. Research indicates that tobacco smoking largely increases the risk of developing bladder cancer . Other eMultiple different pathohistological subtypes of bladder cancer exist, including urothelial carcinoma —the most common type of bladder cancer ; squamouDiagnosis of bladder cancer is commonly performed using cystoscopy, a procedure in which a fiber-optic instrument is passed through the urethra into the bladder and an optical evaluation is performed by a specialist in vivo . The proComputed tomography (CT) scans are a commonly used medical diagnostic imaging method in which multiple X-ray measurements are taken to produce tomographic images of a patient’s body, allowing the examination of patient’s organs without the need for a more invasive procedure . Today, Non-ionic monomer iodinated contrast agents are administered intravenously for arterial opacification and parenchymal enhancement, which helps with better delineation of soft tissue . AcquireVarghese et al. 2018) [18 [20] dRenard et al. (2020)  showed tZhang et al. (2020)  integratLiu et al. (2020)  demonstrHongtao et al. (2020)  demonstrQin et al. (2020)  proposedKaushal et al. (2020)  showed tLi et al. (2020)  demonstrMonteiro et al. (2020)  demonstrAnthimopoulos et al. (2018)  demonstrAnother study regarding segmentation on lung CTs was performed by Meraj et al. (2021)  with theKoitka et al. (2021) proposed an automatic manner of body composition analysis, with the goal of application during routine CT scanning. The authors utilized 3D semantic segmentation CNNs, applying them on a dataset consisting of 50 CTs annotated on every fifth axial slice split into an 80:20 ratio. The authors achieved high results with the average dice scores reaching 0.9553, indicating a successful application of CNNs for the purpose of body composition determination.Is it possible to design a semantic segmentation system separately for each plane?Is there a possibility to design an automated system for plane recognition?How does the transfer learning paradigm affect the semantic segmentation and generalization performance of designed U-nets?Which pre-trained architectures achieve the highest performances if used as a backbone for U-net?To increase the performances of algorithms for the semantic segmentation, we introduce a process of transfer learning. It is important to notice that alongside the performance from the semantic segmentation standpoint, the performance from the generalization standpoint must be evaluated as well. For these reasons, the following questions can be asked:To summarize the novelty of the article, the idea is to utilized multi-objective criteria to evaluate the performances of a transfer learning-based system for the semantic segmentation of urinary bladder cancer masses from CT images. The images are captured in three planes: frontal, axial, and sagittal, and the aim of the research is to maximize semantic segmentation performances by dividing data set according to planes and to introduce the system for automatic plane recognition.At the beginning of the paper, a brief description of the diagnostic procedure is provided together with the problem description. After the problem description, the used data set is presented, followed by a description of the used algorithms. After algorithm description, a mathematical approach to the transfer learning paradigm is presented together with used backbone architectures. In the end, the research methodology is presented followed by the results and discussion.With aim of developing an automated system that could be used in the diagnosis and decision making regarding urinary bladder cancer, a system for the semantic segmentation of urinary bladder cancer from CT images is proposed. The proposed approach is based on the utilization of CNN models that are executed on an HPC workstation. The idea behind the utilization of CNN-based semantic segmentation is to use a data set of images with known annotation to train CNN that will later be used to automatically annotate and evaluate new images. As input data to the semantic segmentation system, images of lower abdomen collected with CT are used.An input image, captured in three planes. First, the classification is performed, in order to determine the plane in which the image was captured. After the plane is determined, the image is used as an input to U-net architecture for that particular plane. Trained U-net architecture is used to create the output mask. The output mask represents the region of an image where urinary bladder cancer is present. Such an output enables automated evaluation of urinary bladder that results in an annotated image that is used to determine the urinary bladder cancer spread. A graphical overview of such a process is presented in Frontal plane.Sagittal plane.Axial plane.The dataset used in this research was created by using CT images collected in the Clinical Hospital Center of Rijeka, and it consists of CT images of the lower abdomen in three planes:All images contained in the data set are images where a form of bladder cancer is confirmed. The CT images with confirmed bladder cancer are presented in The distribution of the training, validation, and the testing data sets is presented for all three planes in When the numbers of images in each plane are compared, it can be seen that a significantly lower number of images were captured for the case of the sagittal plane, in comparison with the frontal and axial plane. Such an imbalance is a consequence of the fact that the CT urography procedures are, in the case of this research, dominantly performed in the frontal and axial planes only. Furthermore, images captured in the sagittal plane are captured with lower density, resulting in a lower number of images per patient.The use of this particular data set was approved by Clinical Hospital Center Rijeka, Ethics Board ; under the number 2170-29-01/1-19-2, on 14 March 2019. In order of creating output data for CNN training, image annotation was performed. Such an approach was utilized for creating output masks that represent the bladder region where a malignant mass is present. The annotation was performed by a specialist urologist according to the obtained medical findings.It is important to emphasize that all images and corresponding medical findings used during this research are validated with additional medical procedures, such as cystoscopy. Medical findings are evaluated by three independent raters—urologists with the experience in the field of radiography, including CT. As a observer agreement measure, Fless’ kappa DSC=When the overlap is low, From the presented extremes, it can be noticed that For purposes of selecting the best semantic segmentation model for each plane, a cross-validation procedure is introduced. The cross-validation procedure represents a standard procedure used in machine learning applications in order to define not only classification or semantic segmentation but also generalization performances. The aforementioned procedure is based on repeated re-training and testing of an ANN where data sets fractions (folds) that represent training and testing data sets are used interchangeably. The procedure is repeated until all folds are used for training and testing. The graphical representation of the described procedure is presented in i. On the other hand, generalization performances (With the obtained information about CNNs classification or semantic segmentation performances in all cases, information about generalization performances can be derived. The average classification or semantic segmentation performances (On the other hand, a CNN with high generalization performances will have:By using the presented criteria for performance evaluation, it can be noted that multi-objective criteria will be used for choosing the architecture that has the highest performances. All models are represented with tuples defined as:A set of tuples is sorted in such a manner that:In this case, In this section, an overview of the achieved results is presented. In the first subsection, the results achieved with AlexNet CNN architecture for plane recognition are presented. In the second, third, and fourth subsections, the results achieved with U-net architectures are presented for each plane. At the end of the section, a brief discussion about the collected results is provided.When the results of plane classification achieved by using AlexNet CNN architecture are observed, it can be noticed that the highest classification and generalization performances are achieved if the AlexNet architecture is trained by using RMS-prop optimizer for 10 consecutive epochs with data batches of 16. With the presented architecture If the change of classification and generalization performances through epochs are compared, it can be noticed that the highest results are achieved when AlexNet is trained for 10 consecutive epochs. Furthermore, it can be noticed that the performances are significantly lower when AlexNet is trained for higher number of epochs, pointing towards the over-fitting phenomena. If AlexNet is trained for just one epoch, the performances are also significantly lower as presented in From the presented result, it can be concluded that AlexNet can be used for CT image plane recognition due the high classification and generalization performances.If the results of semantic segmentation in the frontal plane are compared, it can be noticed that by applying the transfer learning paradigm, a significant improvement of semantic segmentation results is achieved. If a standard U-net architecture is utilized, The highest performances in both criteria are achieved if a pre-trained ResNet101 CNN architecture is used as a backbone for U-net. In this case, If the change of semantic segmentation and generalization performances through epochs are observed for ResNet101, it can be noticed that the highest semantic segmentation and generalization performances are achieved when the U-net is trained for 125 consecutive epochs. When the network is trained for a higher number of epochs, it can be noticed that significantly poorer performances are achieved. Such a property can be attributed to the occurrence of the over-fitting phenomena. When the network is trained for a lower number of epochs, the results are also poorer, as presented in When the performances of semantic segmentation algorithms trained with CT images captured in the axial plane are compared, it can be noticed that by applying the transfer learning approach, significant improvement in both semantic segmentation and generalization performances is achieved. When the isolated learning paradigm is utilized, When the change of The last data set used in this research is the data set of CT images captured in the sagittal plane. In this case, a significant improvement of semantic segmentation and generalization results can be observed if the transfer learning approach is utilized. In the case of standard U-net architectures, If the change of performances through epochs is observed, it can be noticed that the network with pre-trained VGG-16 architecture as a backbone achieved higher results if it is trained for a higher number of epochs. It is interesting to notice that the network has higher semantic segmentation performances if it is trained for 200 consecutive epochs. On the other hand, generalization performances are higher if the network is trained for 100 consecutive epochs, as presented in If From the presented results, it can be seen that U-net for the case of the sagittal plane, although having the highest performance from the point of view of semantic segmentation, has significantly lower results from the point of view of generalization. Such a characteristic can be attributed to the fact that this part of the data set has a significantly lower number of images, in comparison with the other two parts. Such a lower number of images results in a lower number of training images in all five cases of the five-fold cross-validation procedure.Such a lower number of training images results in lower semantic segmentation performances in some cross-validation cases and, thus, lower generalization performances. For these reasons, it can be concluded that, before the application of the proposed semantic segmentation system, more images captured in the sagittal plane need to be collected in order to increase the generalization performances of U-net for the semantic segmentation of images captured in the sagittal plane.A similar trend can be noticed when the results measured with The presented results are showing that there is a possibility for the application of the proposed system in clinical practice. It is shown that the high semantic segmentation performances enable the automatic evaluation of urinary bladder cancer spread. Furthermore, high generalization performances, especially in the case of the frontal and axial plane, indicate that the semantic segmentation system can be used for the evaluation of the new image data and new patients. The presented system can be used as an assistance system to medical professionals in order to improve clinical decision-making procedures.According to the presented results, we concluded that the utilization of the transfer learning paradigm, in the form of pre-trained CNN architectures used as backbones for U-nets, can significantly improve the performances of semantic segmentation of urinary bladder cancer masses from CT images. Such an improvement can be noticed in both semantic segmentation and generalization performances. If the semantic segmentation performances are compared, The design of a semantic segmentation system separately for each plane is possible.There is a possibility for the design of an automated system for plane recognition.By utilizing the transfer learning approach, significantly higher semantic segmentation and generalization performances are achieved.The highest performances are achieved if pre-trained ResNet101, ResNet50, and VGG-16 are used as U-net backbones for the semantic segmentation of images in the frontal, axial, and sagittal planes, respectively.On the other hand, for the case of generalization performances, From the presented results, by utilizing the proposed approach, results in range of the results presented from the state-of-the-art approach were achieved. Furthermore, the proposed redundant approach increased the diagnostic performances and minimized the chance for incorrect diagnoses.Future work will be based on improvements of the presented combination of classification and semantic segmentation algorithms by the inclusion of multiple classification algorithms before a parallel algorithm for the semantic segmentation. Furthermore, we plan to design a meta-heuristic algorithm for model selection with a fitness function that will be based on the presented multi-objective criteria.