*Article* **Online Learning, Mobile Learning, and Social Media Technologies: An Empirical Study on Constructivism Theory during the COVID-19 Pandemic**

**Omar A. Alismaiel 1,\*, Javier Cifuentes-Faura 2 and Waleed Mugahed Al-Rahmi 3**

**Abstract:** The study's main purpose was to discover the important factors that impact university students' online learning and academic performance during the COVID-19 epidemic, as well as their usage of social media throughout the pandemic. Constructivism theory was used and developed with constructs mostly linked to leveraging social media for collaborative learning and student interaction during the COVID-19 pandemic, given the context-dependent nature of online learning during the epidemic. During the COVID-19 epidemic, additional components such as collaborative learning, student participation, and online learning were implemented. The enlarged model, which assesses students' happiness and academic performance during the COVID-19 epidemic in connection to social media use, was validated using empirical data collected via an online survey questionnaire from 480 Saudi Arabian higher education students. AMOS-SEM was used to analyze the model's various assumptions (Analysis of Moment Structures-Structural Equation Modeling). The findings revealed that (1) using social media for collaborative learning and students' engagement has a direct positive impact on students' interactivity with peers and teachers; (2) students' interactivity with peers and teachers has a direct positive impact on online learning during the COVID-19 pandemic; (3) online learning during the COVID-19 pandemic mediates the relationship between students' interactivity and satisfaction; (4) online learning during the COVID-19 pandemic mediates the relationship between students' interactivity and satisfaction. Students, higher education institutions, and educational technology application suppliers would benefit greatly from the conclusions of this study, both theoretically and practically.

**Keywords:** social media technologies; online learning; COVID-19 pandemic; constructivism theory; academic performance

## **1. Introduction**

In the worldwide COVID-19 epidemic, traditional or face-to-face schooling has encountered unprecedented obstacles. Countries have made attempts to limit huge crowd meetings and maintain physical social distance in order to regulate the virus epidemic. Therefore, most countries implemented quarantine periods, thus ending traditional education [1,2]. Similarly, governments have switched from face-to-face to online education for all subjects. During the COVID-19 epidemic, many undeveloped nations, such as Saudi Arabia, lacked digital channels, social media, or online learning to engage students and instructors. Moreover, during the COVID-19 epidemic, they were unable to provide complete online learning [3]. COVID-19 has forced teachers and students in many developing countries to connect online for the first time for academic reasons. Because many schools lack an online learning management system (LMS) for the COVID-19 pandemic, leveraging social media to engage students and promote online learning throughout the pandemic

**Citation:** Alismaiel, O.A.;

Cifuentes-Faura, J.; Al-Rahmi, W.M. Online Learning, Mobile Learning, and Social Media Technologies: An Empirical Study on Constructivism Theory during the COVID-19 Pandemic. *Sustainability* **2022**, *14*, 11134. https://doi.org/10.3390/ su141811134

Academic Editors: Alfonso Chaves-Montero, Javier Augusto Nicoletti, Francisco José García-Moro and Walter Federico Gadea-Aiello

Received: 30 July 2022 Accepted: 31 August 2022 Published: 6 September 2022

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

might be advantageous [4,5]. During the COVID-19 epidemic, the study focuses on the participation of students and teachers on many social media platforms to drive online social interaction and generate successful online learning [6]. The interactive elements were interaction with group members or peers, interactivity with supervisors or lecturers, active collaborative learning, and engagement. Perception criteria included perceived ease of use, perceived utility, social media use, and research student delight. Therefore, both interpersonal and perceptual factors impact research students' academic achievement in higher education. Social media may boost collaborative learning and engagement by allowing individuals to work together to achieve a common goal [7]. Furthermore, study students' usage of social media suggests a positive relationship between academic success and satisfaction [8,9]; also discovered a relationship between academic success and student Facebook usage. It is uncommon for pupils to utilize social media for educational purposes [10]. Furthermore, students use social media to socialize rather than actively collaborate, participate, or achieve academic goals [8]. According to [11], a research model of social media antecedents and consequences was used; however, the results showed a higher perceived risk of using social media to waste time and a decreased willingness to learn. In addition, several research have found that the quantity of time spent on social media has a substantial influence [12]. It is likely that the majority of higher education students use social media and spend substantial time on it, and that the monitoring students' social media usage has a negative component. Excessive social media use is becoming more of a problem since it can lead to a lack of drive. According to experts, motivation might help a student's inner drive to succeed academically [10]. Students' strong desire to participate in active collaborative learning and study using technology may lead them to assume that social media may help them achieve this goal [13]. Thus, there is a negative impact on student interactions [14]. Social media has an influence on and can complicate a student's academic transfer from a college to a university level of education, jeopardizing research students' academic success [15]. The effects of social media in active collaborative learning environments were investigated, and it was revealed that using social media in these scenarios might help students learn more effectively. Thus, researchers should look at the interaction pattern that occurs during active collaborative learning [16]. Instructors do not use social media to educate or engage their students, despite their expertise with previous technology [17]. Professors are also lacking in social media abilities [18]. Students are not convinced by the existing platforms of teacher interaction, according to [19], so there is an excuse for effective active collaborative learning and understanding student– teacher communication regarding their training. However, students are receptive to new social media that will facilitate learning with teachers. According to educators, students seldom use social media networks for educational objectives [20]. Educators who utilize social media, however, have highlighted worries regarding the challenges it presents, as well as the insufficient evaluation and assessment [21]. According to an empirical study, students on campus demand more assistance in accessing additional social media active collaborative learning options than they do in face-to-face sessions. Lecturers can help students with quick inquiries, solutions, and coordination when it comes to using social media for active collaborative learning and involvement [22]. Teachers and students were given the opportunity to submit input during evaluative periods [23]. Experts claim that Facebook has a negative influence on school achievement in general, with male pupils being the most affected [24]. Therefore, the primary goal of this research is to identify and correct the flaws in a model that shows interactivity, social media use, active collaborative learning, engagement, and satisfaction of research students in higher education using the constructivism theor to evaluate academic performance during the COVID-19 pandemic [25]. As a consequence, this research is significant because it will disclose the characteristics and variables, the relationship between social media usage for active collaborative learning and engagement, and how these factors affect research students' academic advancement in higher education. "What are the interaction aspects that increase active collaborative learning and engagement, and hence academic success during the COVID-19

pandemic?" asks the researcher. This research will create a model of social media use for active collaborative learning and engagement by interactive factors, which will have an impact on academic performance in higher education institutions during the COVID-19 pandemic. It will also investigate the validity of constructivism for interactivity and social media use for active collaborative learning and engagement, which will have an impact on the academic performance of research students during the COVID-19 pandemic.

#### *Social Media Use in Higher Education*

Students in high school may utilize social media to evaluate and appreciate creative work, offer and receive educational assistance, and validate and enjoy creative work from classmates. Faculty usage [17,26], student engagement [27,28], and influence on, as well as related to, academic accomplishment are all researched in the context of higher education [29,30]. According to the researchers, university students who engaged in interactive blogs had a more favorable attitude toward peer interaction and academic achievement [31]. Students can use social media to communicate, cooperate, and interact in a social setting [32]. The use of social media curricula in higher education for teaching and learning has attracted the scholarly community's interest. Cognitive abilities and motivation for active collaborative learning in higher education, reflection, and metacognition are essential components of social media [33]. Several research have shown that using social media for student assignments results in higher levels of learning [34].

#### **2. Interactive Variables Used with Theories**

Students who were unable to achieve cognitive equilibrium and tried to become accustomed to achieving equilibrium cognition and supported learners in building knowledge can be found in social media networks to be interactive and with the perspective of the allotment of knowledge and information or discussion with others, according to the social constructivist theory [25]. As a consequence, constructivism [25] will be utilized to support the research's main thesis: learning is an active, creative process. The goal of this study was to fill in the gaps in the literature by examining how the use of social media for active collaborative learning and engagement affects the academic performance of research students during the COVID-19 pandemic. The constructivism theory was used to create the research model. As a consequence, constructivism was chosen in this research since it claims that engaging with classmates and lecturers leads to active collaborative learning [35]. Prior work has paved the way for the creation and refinement of a research model to investigate the influence of social media use in collaborative learning on academic achievement among research students. As a consequence of the investigation, seven operational themes of crucial factors on social media use for active collaborative learning and engagement that affect academic achievement were discovered and classified, see Figure 1. *Sustainability* **2022**, *14*, x FOR PEER REVIEW 4 of 16

In education, a social network is referred to as social media for allowing communi-

The engagement is centered on interactions between the person and the environment in order to ensure social and intellectual connections between study group members and the class in order to change student awareness and engagement [43]. Therefore, of the widespread usage of social media, individuals have incorporated online contact into their daily lives, demonstrating the various ways in which people interact with one another through information sharing [44]. Furthermore, a number of research that looked at the experience of utilizing social media networks revealed that it led to excellent learning outcomes and engagement [45]. One of the good aspects of social media platforms [46] is their influence on emotional components of the learning environment, as well as its impact on

Learner involvement in the course has increased as well, as seen by social media activity logs, particularly with an evaluation task. According to recent research [46], virtual interactions are one of the most effective strategies to improve communication, inspire students to study, encourage them to take their learning assignments more seriously, and

motivation and student engagement for active collaborative learning.

learners to grasp processes and participate in groups through the group process [36]. To support the learning processes required for the construction of a knowing society, new learning platforms that allow collaborative and constructive learning are required [37]. Students can utilize collaborative learning assignments on a wiki to discuss their work with others, receive feedback, and make changes before submitting the final version [38]. Students can utilize wikis to compile a collection of papers that represent the learning group's common knowledge. According to [39], active collaborative learning is more successful in diverse knowledge scenarios, and learners have strong cognitive abilities in this area. Several research looked at the possibilities of social media as a collaborative and cooperative learning tool [40]. To investigate students' perspectives of social media as an interactive learning tool, [41] created social media profiles for four university courses. Students who support using social media for academic purposes cited several benefits of using a social media course page as a useful learning resource, including increased interaction and engagement in discussions regarding course topics or research, as well as exposure to relevant media and learning materials. Several participants, however, were concerned regarding the necessity to stay on top of the social media course activities [42].

**Figure 1.** Research model. boost social network. While research on the use of social media for teaching and learning **Figure 1.** Research model.

*2.1. Using Social Media for Collaborative Learning*

*2.2. Using Social Media for Student Engagement*

*2.3. Interactivity with Peers*

#### *2.1. Using Social Media for Collaborative Learning*

In education, a social network is referred to as social media for allowing communication among research students, supervisors, professors, and experts, as well as enabling learners to grasp processes and participate in groups through the group process [36]. To support the learning processes required for the construction of a knowing society, new learning platforms that allow collaborative and constructive learning are required [37]. Students can utilize collaborative learning assignments on a wiki to discuss their work with others, receive feedback, and make changes before submitting the final version [38]. Students can utilize wikis to compile a collection of papers that represent the learning group's common knowledge. According to [39], active collaborative learning is more successful in diverse knowledge scenarios, and learners have strong cognitive abilities in this area. Several research looked at the possibilities of social media as a collaborative and cooperative learning tool [40]. To investigate students' perspectives of social media as an interactive learning tool, [41] created social media profiles for four university courses. Students who support using social media for academic purposes cited several benefits of using a social media course page as a useful learning resource, including increased interaction and engagement in discussions regarding course topics or research, as well as exposure to relevant media and learning materials. Several participants, however, were concerned regarding the necessity to stay on top of the social media course activities [42].

#### *2.2. Using Social Media for Student Engagement*

The engagement is centered on interactions between the person and the environment in order to ensure social and intellectual connections between study group members and the class in order to change student awareness and engagement [43]. Therefore, of the widespread usage of social media, individuals have incorporated online contact into their daily lives, demonstrating the various ways in which people interact with one another through information sharing [44]. Furthermore, a number of research that looked at the experience of utilizing social media networks revealed that it led to excellent learning outcomes and engagement [45]. One of the good aspects of social media platforms [46] is their influence on emotional components of the learning environment, as well as its impact on motivation and student engagement for active collaborative learning.

#### *2.3. Interactivity with Peers*

Learner involvement in the course has increased as well, as seen by social media activity logs, particularly with an evaluation task. According to recent research [46], virtual interactions are one of the most effective strategies to improve communication, inspire students to study, encourage them to take their learning assignments more seriously, and boost social network. While research on the use of social media for teaching and learning [17] is still in its early phases, these studies imply that it has the potential to be a transformative method for learning and teaching in higher education as a social networking tool. Before structuring their courses, selecting the pedagogical strategies they intend to employ and the sorts of evaluations they feel would increase their students' participation in the learning process, educators must first analyze their students' intellectual and social backgrounds. The usage of social media in higher education can help increase professor– student connection [47]. According to [48], social media use for learning is just as essential as learning objectives; thus, they must have a social presence, include interactive learning, and encourage active collaborative learning.

#### *2.4. Interactivity with Teachers*

Fluid interactions among research group members may be suffocated by traditional learning approaches [49]. Student participation has an impact on academic success [50]. Despite the relevance of the concept of integration, the integration of commuting students differs significantly from that of on-campus students, with socio-academic moments [51]. The traditional concept of engagement with peers and professors had more attraction

and importance for those students than the regularity with which these encounters took place or the depth of relationship between researchers and supervisors. By providing new opportunities to promote engagement, advanced technology has revolutionized the way students connect with one another, both inside and beyond the classroom. Facilitating relationships is crucial since it leads to more effective and better learning. Therefore, it is possible that it will become a need for academic achievement [52].

#### *2.5. Online Learning during the COVID-19 Pandemic*

This study backs up statements from [53], that using social media for online learning during the COVID-19 pandemic and academic communication, such as social media, can promote social learning and social presence. It also claims that by creating an interactive learning environment, encouraging social presence, and fostering social presence, using social media for formal academic communication might improve learning results. Various research have been produced that indicate the benefits of interpersonal connection because online engagement has been thoroughly examined in recent decades. Human involvement in online environments has been linked to student pleasure [54,55], faculty satisfaction [56], and student academic achievement [54,55,57].

#### *2.6. Students' Satisfaction*

Students from one cultural context may have various viewpoints on educational interventions based on their actions in another cultural environment [58]. This highlights the need of doing comparative research on online learner engagement as well as the impact of cultural variations on online student cooperation [59]. Furthermore, active collaborative learning environments, as well as students' happiness with them, is a hot topic that has spawned several research papers in the literature [60]. When it comes to user adoption and enjoyment with technology, perceived usefulness and ease of use are crucial elements to consider. They have been demonstrated to predict consumer happiness with websites and computers [61]. According to [62], while some studies have indicated that user entertainment has a significant impact on technology success, others have discovered that user perceptions of technology-provided entertainment are linked to IS systems and product adoption and satisfaction [63]. All forms of communication, according to [64], are important and should be incorporated in online courses since they promote students' learning and enjoyment. Furthermore, few studies have been performed on how students interact, communicate, negotiate, and cooperate in online classrooms [65]. This shows that students like connecting with peers who share similar interests, which boosts overall satisfaction with active collaborative learning in homogeneous groups [66].

#### *2.7. Students' Academic Performance during COVID-19 Pandemic*

Despite the fact that they mostly use it for social rather than academic purposes, the majority of respondents agreed that social media had a positive impact on their academic performance during the COVID-19 pandemic, according to a study on the impact of social media on students' academic performance during the COVID-19 pandemic in education [67]. It has been shown that there is a correlation between collaborative learning, engagement, and academic accomplishment [27]. The usage of social media in higher education has been recommended based on research [18]. Social media is viewed by learners and their communities as a means of disseminating fresh information. Facebook may be used to assist students or a specific group of people to communicate more successfully in a variety of ways [68]. The amount of time and effort students spend on educational activities is measured by student interaction and engagement [69]. The phrase "social media" encompasses a wide range of networked tools or technologies that highlight the Internet's social aspects as a conduit for communication, active collaborative learning to increase academic achievement, and creative expression in higher education [70]. They lead to the use of social media to increase educational access and engagement [71]. Social media platforms are widely used by students for both amusement and education. College

students utilize a variety of social media programs since it has become an important part of their daily lives for both personal and educational aims [8].

#### **3. Research Methodology**

We sent out 500 questionnaires for the study and 491 were returned by respondents; after human processing, 6 of the 491 questionnaires were incomplete ("students did not complete the survey") and had to be deleted, leaving 485. Outliers, defined as "data that differs abnormally from other values in a random sample," were found in 5 of the remaining 485 questionnaire copies put into SPSS, bringing the total number of acceptable surveys to 480 students. Hair et al. [72] argued for such exclusions, claiming that outliers might lead to erroneous statistical conclusions and should be removed. For the purpose of the study, we built a conceptual model based on constructivism theory to measure student satisfaction and academic achievement.

#### *3.1. Instrument Development*

Because Likert scales are widely used in information system (IS) research and have been thoroughly assessed in both marketing and social science, they were employed to examine the responses in this study [73]. This study's variables were all graded on a five-point Likert scale from 1 to 5: (1) Strongly disagree, (2) Disagree, (3) Undecided, (4) Agree, and (5) Strongly Agree were the five options. When choosing and creating a measuring scale, several aspects that affect the scale's reliability, validity, and utility must be taken into account. The study by Cooper and Schindlers [74] provided the foundation for these factors. The questionnaire looked at how students and researchers in higher education felt about using social media for active collaborative learning and engagement, as well as how it influenced their academic performance during the COVID-19 pandemic, was fine-tuned with the support of a pilot study with students, and tested beforehand. A questionnaire with 27 items was prepared after minor layout changes, and the online survey was administered toward the end of the semester in September 2021. Four items derived from [75] were used to examine the use of social media for collaborative learning in the questionnaire adapted from earlier studies. Students' engagement with social media was examined using three questions derived from [43]. A subset of six questions from [76] was used to assess interactivity with peers and teachers. Four questions derived from the questionnaire were used to assess online learning [77]. Students' academic performance during the COVID-19 pandemic was tested using four items from [78], and finally, student satisfaction was examined using four questions from [63].

#### *3.2. Sample Size and Data Collection*

Sampling is a statistical approach that includes picking a subset of individual observations from a population with the purpose of influencing student and researcher academic performance during the COVID-19 pandemic and satisfaction in higher education by employing social media for participation and active collaborative learning. The two types of sampling processes are random and non-random sampling. This study employed a random sampling technique because it assures that the research target group has an equal probability of being picked.

#### **4. Data Analysis and Results**

The current study's empirical analysis aims to explore how the interrelationships of many independent and dependent factors connected to using social media for active collaborative learning impact the academic performance during the COVID-19 pandemic of students and researchers. Structural Equation Modeling was the primary statistical tool employed in the data analysis for a variety of reasons (SEM). SEM is the most rigorous and powerful statistical research approach for dealing with complicated models, according to several specialists [72]. SEM is a set of statistical models aimed at explaining correlations between a large number of variables. After the measurement model has been confirmed, the researcher moves on to the second stage, which comprises estimating the structural model between the latent variables. The one-step technique, on the other hand, estimates the measurement model and structural models at the same time [72]. The data are shown in Table 1.

**Table 1.** Adjusted goodness-of-fit index (AGFI).

#### *4.1. Validity and Reliability*

In this study, AMOS 23 was used to calculate individual item dependability. The item is deemed dependable if the squared multiple correlations in (R2) of each item in the measurement model exceed 0.5. Individual item dependability is demonstrated if the standardized loading is equal to or greater than 0.70 [72]. The entire amount of true score volatility as a proportion of overall scale score variance is represented by composite reliability (CR) [72]. The consistency of a collection of variables in a measurement is determined using CR. The resulting coefficient is interpreted in the same way as Cronbach's alpha, with the difference that it accounts for true factor loadings rather than assuming that each item in the composite load assessment is equally weighted [72]. The average variance extracted (AVE) displays the total amount of variance in the indicators that the hidden construct accounts for [72]. Confirmatory factor analysis (CFA) can be used to explore this form of validity (see Tables 2 and 3).

**Table 3.** Sample covariances reliability.

#### *4.2. Measurement Model Fit*

The total model measure, according to [72], may be that the fit is evaluated using a variety of goodness-of-fit metrics divided into three categories: absolute fit measurements, incremental fit measures, and parsimonious fit measures. As a consequence of this advice, the following indices were used in this investigation: RMR, lFI, TLI, CFI, RMSEA, and 2/df. The Root-Mean-Square Error of Approximation (RMSEA) was chosen for this study because it is one of the most often used metrics for correcting the GOF test statistic's propensity to reject models with a high sample size or a large number of observable variables [72]. As illustrated in Figure 2, many fit indices should be employed to evaluate a model's goodness-of-fit, with a value of 0.90 or above [72]. *Sustainability* **2022**, *14*, x FOR PEER REVIEW 9 of 16 propensity to reject models with a high sample size or a large number of observable variables [72]. As illustrated in Figure 2, many fit indices should be employed to evaluate a model's goodness-of-fit, with a value of 0.90 or above [72].

**Figure 2.** Measurement model. **Figure 2.** Measurement model.

**Figure 3.** Structural model.

#### *4.3. Hypothesis Testing 4.3. Hypothesis Testing*

Hypothesis testing is the penultimate step in the data processing process. The goal of this investigation was to look at the nine options listed in Table 4. The statistical significance of the parameter estimated by SEM was determined using the Critical Ratio (C.R.), which is defined as the parameter estimate divided by the standard error (S.E.) [72]. Smaller *p*-values (*p* 0.01) are frequently regarded as very significant since they suggest that the observed difference would only occur once in a hundred times if no genuine difference existed. To summarize, when sample sizes or the number of observable variables get larger [72], the statistical test or the resultant *p*-value becomes less relevant [72], as seen in Figures 3 and 4. Hypothesis testing is the penultimate step in the data processing process. The goal of this investigation was to look at the nine options listed in Table 4. The statistical significance of the parameter estimated by SEM was determined using the Critical Ratio (C.R.), which is defined as the parameter estimate divided by the standard error (S.E.) [72]. Smaller *p*-values (*p* 0.01) are frequently regarded as very significant since they suggest that the observed difference would only occur once in a hundred times if no genuine difference existed. To summarize, when sample sizes or the number of observable variables get larger [72], the statistical test or the resultant *p*-value becomes less relevant [72], as seen in Figures 3 and 4.

*Sustainability* **2022**, *14*, x FOR PEER REVIEW 9 of 16

model's goodness-of-fit, with a value of 0.90 or above [72].

propensity to reject models with a high sample size or a large number of observable variables [72]. As illustrated in Figure 2, many fit indices should be employed to evaluate a

**Table 4.** Hypotheses relationships test.

*Sustainability* **2022**, *14*, x FOR PEER REVIEW 10 of 16

**Figure 3.** Structural model. **Figure 3.** Structural model.

seen in Figures 3 and 4.

**Figure 4.** *p*-value results. **Figure 4.** *p*-value results.

The hypotheses indicate the interrelationships between the components that may impact how higher education research students utilize social media for active collaborative learning and involvement, as well as their academic achievement. A two-step structural equation modeling technique was used to evaluate the assumptions. This technique was chosen for this study because it is more practical than other ways, such as the one-step method [72], as shown in Table 4. The hypotheses indicate the interrelationships between the components that may impact how higher education research students utilize social media for active collaborative learning and involvement, as well as their academic achievement. A two-step structural equation modeling technique was used to evaluate the assumptions. This technique was chosen for this study because it is more practical than other ways, such as the one-step method [72], as shown in Table 4.

#### **No Hypotheses Relationships Estimate S.E. C.R.** *p* **Results 5. Discussion and Implications**

**Table 4.** Hypotheses relationships test.

**5. Discussion and Implications**

H1 INP <--- SMCL 0.422 0.026 16.147 0.000 Accepted H2 INT <--- SMCL 0.297 0.028 10.638 0.000 Accepted H3 INP <--- SME 0.361 0.023 15.953 0.000 Accepted H4 INT <--- SME 0.273 0.024 11.295 0.000 Accepted H5 OL <--- INP 0.278 0.024 11.606 0.000 Accepted This research adds to the current literature by adding constructivism theory to better understand how students use social media for learning. Social media, along with the Internet, have revolutionized the way students interact, engage, and cooperate throughout the world. Collaboration and engagement on social media encourage a constructivist approach

H6 OL <--- INT 0.385 0.026 14.782 0.000 Accepted H7 SS <--- OL 0.530 0.022 24.179 0.000 Accepted

This research adds to the current literature by adding constructivism theory to better understand how students use social media for learning. Social media, along with the Internet, have revolutionized the way students interact, engage, and cooperate throughout the world. Collaboration and engagement on social media encourage a constructivist approach to learning, in which students and teachers collaborate for mutual benefit [79,80]. They can discuss and share useful knowledge in a group environment through social media sites. In addition, effective social media use boosts participant engagement, collaborative learning, and learner performance. Social media-based learning systems, rather than traditional learning approaches, put online learning during the COVID-19 pandemic in the hands of students [81]. Students may foster healthy classroom conversations, student engagement, peer integration, and teacher integration by using social media. These findings corroborate those of [82], which discovered that social networks are simple to use and explore, as well as being beneficial for interactive learning. Previous research on social networking networks and their practical utility yielded similar results [9,83–85] and claims that using social media in the classroom encourages greater contributions and participation in active student collaboration and engagement. Therefore, these virtual community interactions foster the desired learning outcomes and student success. Employing online social media for collaborative learning and interaction with instructors and peers

to learning, in which students and teachers collaborate for mutual benefit [79,80]. They can discuss and share useful knowledge in a group environment through social media sites. In addition, effective social media use boosts participant engagement, collaborative learning, and learner performance. Social media-based learning systems, rather than traditional learning approaches, put online learning during the COVID-19 pandemic in the hands of students [81]. Students may foster healthy classroom conversations, student engagement, peer integration, and teacher integration by using social media. These findings corroborate those of [82], which discovered that social networks are simple to use and explore, as well as being beneficial for interactive learning. Previous research on social networking networks and their practical utility yielded similar results [9,83–85] and claims that using social media in the classroom encourages greater contributions and participation in active student collaboration and engagement. Therefore, these virtual community interactions foster the desired learning outcomes and student success. Employing online social media for collaborative learning and interaction with instructors and peers boosts student engagement, which improves academic achievement. Students' intellectual capacities should be developed on a platform provided by the higher education administration. Based on the outcomes of the empirical study, it can be stated that social media communication devices assist students in regaining knowledge and engaging with others in real-time while transferring educational materials' contents. Furthermore, modern communication devices would aid students who are shy in front of their peers; instructors might open up on the web for collaborative learning and teaching in a global setting; physically challenged students would benefit from such technology. It also stands to reason that the widespread use of advanced tools in practical training in higher education makes it simpler for professors and students to engage digitally through web-based learning, discussion groups, and other techniques. This research discovered that using social media for collaborative learning and engagement, as well as interactions with peers and teachers, has a positive impact on students' online learning during the COVID-19 pandemic and academic performance during the COVID-19 pandemic, implying that implementing such sophisticated technological tools in higher education would result in innovative, drastic changes in international collaborative learning and engagement. Here is a summary of the key research findings. Peer and teacher contact, as well as students' use of social media for educational reasons, enhance with collaborative learning and engagement. Students' use of social media enhances online learning during the COVID-19 pandemic, interaction and engagement, as well as student–instructor communication. The contact and participation of students have a favorable influence on online learning during the COVID-19 pandemic. Furthermore, online learning during the COVID-19 pandemic has a strong favorable effect on student satisfaction and academic achievement. Therefore, this research provides a framework for examining the influence of students' educational use of social media on collaborative learning and engagement. This model was created based on observations from the literature and then tested using structural equation modeling. Students' usage of social media for educational purposes was examined using constructivism theory basics. After that, the effects of students' usage of social media for online learning during the COVID-19 pandemic on student engagement, faculty member involvement with students, and student course participation were examined. Finally, the overall effects of student interaction, instructor–student relationships, and student course participation in collaborative learning were discovered to have an impact on students' happiness and academic achievement in online learning during the COVID-19 pandemic. According to this study, the indicators are well-representative of the constructs. When all goodness-of-fit criteria were approved, the measurement model was likewise judged to be adequate. The concept reliabilities and average variance extracted values were determined in the current study, which looked at both convergent and discriminant validity. The research model was found to be sufficient as a consequence of the data, and the study's nine hypotheses were confirmed and approved. The model was updated with additional correlations, and the model's validity was validated using the indices and goodness-of-fit indices. All of these findings imply that social media offers a number of benefits, including

the ability to improve collaborative learning and engagement with peers and instructors; all of which have an impact on online learning during the COVID-19 pandemic, student satisfaction, and academic achievement. This project provided a paradigm for harnessing social media for collaborative learning and involvement in order to improve students' academic performance during the COVID-19 pandemic. Students were most satisfied with the assistance offered by teaching staff and their universities' public relations during the global lockdown and shift to online learning, all of which are results of our research [86–88]. Here are the scientific contributions:

#### **6. Conclusions and Future Work**

The study's main goal was to look at the effects of a variety of factors on online learning during the COVID-19 pandemic and student happiness in order to help students improve their academic performance during the COVID-19 pandemic. Using social media for collaborative learning, using social media for student engagement, interactivity with peers, interactivity with teachers, online learning during the COVID-19 pandemic, student satisfaction, and student academic performance during the COVID-19 pandemic were all included in the proposed model for this study, which was based on constructivism theory. These factors were assessed using a structural equation modeling (SEM) technique and an online questionnaire comprising 27 questions. Both collaborative learning and engagement had a favorable impact on peer and instructor interaction, according to the findings; both factors affected online learning during the COVID-19 pandemic, which improved students' happiness and academic success. The use of social media as a platform for educational learning, cooperation, and student participation, as well as the use of social media as a platform for interaction and online learning during the COVID-19 pandemic, were all highlighted. These recommendations, when combined with a set of standards for using social media in higher education, would benefit both students and institutions. According to the findings of this study, future research could incorporate more characteristics to analyze the impact of various aspects on online learning during the COVID-19 pandemic and students' academic performance during the COVID-19 pandemic through the use of social media for collaborative learning and student engagement. Future research should look at additional studies and variables that influence the usage of social media for online learning during the COVID-19 pandemic, collaborative learning, and engagement to improve students' academic achievement (e.g., environmental and cultural). Regardless of the insights it offers, this study has its own limitations. The findings should be interpreted cautiously because this study only examined one university, and behavior at other universities (both private and public) may vary. This study's emphasis on quantitative data is another drawback; as a result, researchers should use qualitative data instead (such as observations or interviews) to avoid discovering inconsistencies between research themes. Future studies should repeat this investigation in several nations, regions, and cultures to correct its flaws and broaden the range of its conclusions. Due to the small sample size, it was not able to conduct moderator research, hence the effects of age and gender were not examined.

**Author Contributions:** Conceptualization, O.A.A.; methodology, O.A.A., W.M.A.-R. and J.C.-F.; software, O.A.A. and W.M.A.-R.; validation, W.M.A.-R. and O.A.A.; formal analysis, J.C.-F., O.A.A. and W.M.A.-R.; investigation, O.A.A., W.M.A.-R. and J.C.-F.; resources, O.A.A.; data curation, O.A.A., W.M.A.-R. and J.C.-F.; writing—original draft preparation, O.A.A.; writing—review and editing, O.A.A., W.M.A.-R. and J.C.-F., visualization, O.A.A., W.M.A.-R. and J.C.-F.; supervision, O.A.A.; project administration, O.A.A.; funding acquisition, O.A.A. All authors have read and agreed to the published version of the manuscript.

**Funding:** This work was supported by the Deanship of Scientific Research, Vice Presidency for Graduate Studies and Scientific Research, King Faisal University, Saudi Arabia (Project No. GRANT139).

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Not applicable.

**Conflicts of Interest:** The authors declare no conflict of interest.

## **References**


**2. The expression of CD69 and CD3+ T-lymphocytes in the diagnosis or therapy of AF**

Recently, the link between inflammation and AF appeals increasing attention. Many studies have demonstrated serum or plasma inflammation biomarkers have a link with the development of AF, which supported chronic inflammatory responses might partici‐ pate in the development of AF (Chung MK et al.,2006;Hemandez Madrid A et al.,2007;Li J et al.,2010;Psychari SN et al.,2005). Moreover, some other studies reported that activat‐ ed T-lymphocytes and macrophages infiltrated the endomyocardial of patients with AF, which supported the activation of local T-lymphocytes played a role in the pathogenesis of AF (Chen MC et al., 2008;Nakamura Y et al.,2003;Yamashita T et al.,2010). However, up to now, there are no evidences supporting the link between the activation of periph‐ eral blood T-lymphocytes and AF. As is well-known, CD69 and HLA-DR are markers of activated T-lymphocytes. In other words, they are both specifically expressed on the sur‐ face of activated T-lymphocytes.[11, 12](Caruso A et al.,1997;Reddy M et al.,2004) CD69 is known as an early activation marker of T-lymphocytes [13](Sancho D et al.,2005) and HLA-DR is known as a late activation marker of T-lymphocytes.[14] (Geraldes L et al., 2010)They both play a role in the specific immune response to inflammation. [15, 16, 14, 17-19, 13, 20] (Sancho D et al.,2005;Geraldes L et al.,2010;Afeltra A et al.,1993;Ferenczi K et al.,2000;McDonald GB et al.,1987;Miki-Hosokawa T et al.,2009;Oczenski W et al., 2003;Vance BA et al.,2005) To our knowledge, there is little information available about the expression of CD69 and HLA-DR on peripheral blood CD3+ T-lymphocytes in pa‐ tients with AF.Thus we designed an experiment to investigate the relationship between the activation of peripheral blood CD3+ T-lymphocytes and AF by flow cytometric analy‐ sis that we aimed to provide more evidences to support this phenomenon (Liu L, et al., 2012;53(4):221-4.)

**Figure 4.** Percentage of CD3+CD69+ T-lymphocytes (A) and CD3+HLA-DR+ T-lymphocytes (B) were shown, respectively.

Effect of CD3+ T-Lymphocyte and n-3 Polyunsaturated Fatty Acids on the Diagnosis or Treatment of Atrial Fibrillation

http://dx.doi.org/10.5772/54167

51

During three-month follow-up, 37 patients had recurrence of AF (recurrence group) and 50 patients remained in sinus (sinus group). The results demonstrated that the mean values of CD69 and HLA-DR in sinus group at follow-up (1.17%±0.38, 28.71%±8.70) were all signifi‐ cantly down-regulated compared with before cardioversion (1.45%±0.44, 34.71%±9.75; all *p*<0.05). However, there were no statistically significant differences between recurrence group at follow-up (1.57%±0.39, 36.40%±9.32) and before cardioversion (1.60%±0.35, 37.72%

**Figure 5.** The mean values of CD3+CD69+ T-lymphocytes (A) and CD3+HLA-DR+ T-lymphocytes (B) in the sinus group

±11.11; *p*=0.721, *p*=0.544. Figure.5)

and recurrence group at follow-up and before cardioversion.

Fifty paroxysmal AF patients and fifty-six persistent AF patients, underwent successful elec‐ trical cardioversion, were enrolled in this study. Percentage of CD69 and Human leukocyte antigen DR (HLA-DR) positive peripheral blood CD3+ T-lymphocyte, which indicates Tlymphocyte activation, were examined by flow cytometric analysis in the patients and fiftyone healthy controls. Patients groups had higher levels of CD69 and HLA-DR than healthy controls. During three-month follow-up, 37 patients had recurrence of AF (recurrence group) and 50 patients remained in sinus (sinus group).

The results showed that Patients with AF groups had higher levels of CD69 and HLA-DR than healthy controls. The mean value of CD69 was significantly up-regulated in patients with paroxysmal (1.48%±0.42) and persistent AF (1.55%±0.38) compared with healthy indi‐ viduals (1.07%±0.37; all p<0.001). The mean value of HLA-DR was also significantly upregulated in patients with paroxysmal (35.16%±10.89) and persistent AF (37.73%±10.78) compared with healthy individuals (26.6%±8.41; all p<0.001. Figure 4)

Effect of CD3+ T-Lymphocyte and n-3 Polyunsaturated Fatty Acids on the Diagnosis or Treatment of Atrial Fibrillation http://dx.doi.org/10.5772/54167 51

**2. The expression of CD69 and CD3+ T-lymphocytes in the diagnosis or**

Recently, the link between inflammation and AF appeals increasing attention. Many studies have demonstrated serum or plasma inflammation biomarkers have a link with the development of AF, which supported chronic inflammatory responses might partici‐ pate in the development of AF (Chung MK et al.,2006;Hemandez Madrid A et al.,2007;Li J et al.,2010;Psychari SN et al.,2005). Moreover, some other studies reported that activat‐ ed T-lymphocytes and macrophages infiltrated the endomyocardial of patients with AF, which supported the activation of local T-lymphocytes played a role in the pathogenesis of AF (Chen MC et al., 2008;Nakamura Y et al.,2003;Yamashita T et al.,2010). However, up to now, there are no evidences supporting the link between the activation of periph‐ eral blood T-lymphocytes and AF. As is well-known, CD69 and HLA-DR are markers of activated T-lymphocytes. In other words, they are both specifically expressed on the sur‐ face of activated T-lymphocytes.[11, 12](Caruso A et al.,1997;Reddy M et al.,2004) CD69 is known as an early activation marker of T-lymphocytes [13](Sancho D et al.,2005) and HLA-DR is known as a late activation marker of T-lymphocytes.[14] (Geraldes L et al., 2010)They both play a role in the specific immune response to inflammation. [15, 16,

17-19, 13, 20] (Sancho D et al.,2005;Geraldes L et al.,2010;Afeltra A et al.,1993;Ferenczi K et al.,2000;McDonald GB et al.,1987;Miki-Hosokawa T et al.,2009;Oczenski W et al., 2003;Vance BA et al.,2005) To our knowledge, there is little information available about the expression of CD69 and HLA-DR on peripheral blood CD3+ T-lymphocytes in pa‐ tients with AF.Thus we designed an experiment to investigate the relationship between the activation of peripheral blood CD3+ T-lymphocytes and AF by flow cytometric analy‐ sis that we aimed to provide more evidences to support this phenomenon (Liu L, et al.,

Fifty paroxysmal AF patients and fifty-six persistent AF patients, underwent successful elec‐ trical cardioversion, were enrolled in this study. Percentage of CD69 and Human leukocyte

lymphocyte activation, were examined by flow cytometric analysis in the patients and fiftyone healthy controls. Patients groups had higher levels of CD69 and HLA-DR than healthy controls. During three-month follow-up, 37 patients had recurrence of AF (recurrence

The results showed that Patients with AF groups had higher levels of CD69 and HLA-DR than healthy controls. The mean value of CD69 was significantly up-regulated in patients with paroxysmal (1.48%±0.42) and persistent AF (1.55%±0.38) compared with healthy indi‐ viduals (1.07%±0.37; all p<0.001). The mean value of HLA-DR was also significantly upregulated in patients with paroxysmal (35.16%±10.89) and persistent AF (37.73%±10.78)

antigen DR (HLA-DR) positive peripheral blood CD3+

group) and 50 patients remained in sinus (sinus group).

compared with healthy individuals (26.6%±8.41; all p<0.001. Figure 4)

14,

T-lymphocyte, which indicates T-

**therapy of AF**

50 Atrial Fibrillation - Mechanisms and Treatment

2012;53(4):221-4.)

**Figure 4.** Percentage of CD3+CD69+ T-lymphocytes (A) and CD3+HLA-DR+ T-lymphocytes (B) were shown, respectively.

During three-month follow-up, 37 patients had recurrence of AF (recurrence group) and 50 patients remained in sinus (sinus group). The results demonstrated that the mean values of CD69 and HLA-DR in sinus group at follow-up (1.17%±0.38, 28.71%±8.70) were all signifi‐ cantly down-regulated compared with before cardioversion (1.45%±0.44, 34.71%±9.75; all *p*<0.05). However, there were no statistically significant differences between recurrence group at follow-up (1.57%±0.39, 36.40%±9.32) and before cardioversion (1.60%±0.35, 37.72% ±11.11; *p*=0.721, *p*=0.544. Figure.5)

**Figure 5.** The mean values of CD3+CD69+ T-lymphocytes (A) and CD3+HLA-DR+ T-lymphocytes (B) in the sinus group and recurrence group at follow-up and before cardioversion.

Before we received the result,we conduct the baseline clinical Caracteristics of the Studied Population to ensure facticity of the results (Table 2).

et al.,2002) HLA-DR belongs to the MHC class II system which is known as a late activation marker of lymphocytes. It is required for antigen presentation and activation of helper Tlymphocytes. (Geraldes L et al.,2010;Oczenski W et al.,2003;Bobryshev YV et al.,2011)They respectively expressed in some inflammatory infiltrates and played important roles in the pathogenesis of some inflammatory diseases such as allergic airway inflammation, (Miki-Hosokawa T et al.,2009;Wang HY et al.,2006) rheumatoid arthritis, (Afeltra A et al.,1993) psoriasis vulgaris lesional skin active inflammatory bowel disease (McDonald GB et al.,

Effect of CD3+ T-Lymphocyte and n-3 Polyunsaturated Fatty Acids on the Diagnosis or Treatment of Atrial Fibrillation

T-lymphocytes in AF patients.

role in the pathogenesis of AF. A few studies reported that some inflammatory lympho‐

cardial in patients with AF, which supported the local activation of T-lymphocytes played a role in the pathogenesis of AF.(Chen MC et al.,2008;Nakamura Y et al.,2003;Yamashita T et al.,2010) On the other hand, a lot of studies reported that serum or plasma inflammation bio‐ markers, such as C-reactive protein (CRP), interleukin (IL)-6, IL-8, IL-10, tumor necrosis fac‐ tor (TNF)-α, monocyte chemotactic protein (MCP)-1, vascular endothelial growth factor (VEGF), et al., increased in AF patients, which supported T-cell-associated chronic inflam‐ matory responses might involve in the pathogenesis of AF. (Chung MK et al.,2001;Heman‐ dez Madrid A et al.,2007;Li J et al.,2010;Psychari SN et al.,2005) In our study, we provided another evidence to support that there is an activation of peripheral blood CD3+ T-lympho‐ cytes in AF patients, demonstrated by the upregulation of CD69 and HLA-DR by flow cyto‐

Generally, our study here further emphasize that activation of T cells is involved in AF. As we all know, T-lymphocytes are the main cells participate in cell-mediated immunity, which is one of the primary ways of human immune. It can be suppressed by many immunosup‐ pressants such as Cyclosporine, Rapamycin, et al. If the activation of peripheral blood Tlymphocytes does participate in the pathogenesis of AF, maybe we can prevent recurrence

ipates in the progression of AF, we speculate the following three possibilities. Firstly, the ac‐

MCP-1, which could affect the contractility and electrical stability of myocytes inhomogene‐ ously and induce fibroblast activation leading to deposits of extracellular matrix fibrosis. (Ramos-Mondragon R et al.,2008) Secondly, activation of peripheral blood CD3+ T-lympho‐ cytes might promote the local immunologic inflammatory responses in the endomyocardial, and promote infiltrate of inflammatory lymphomononuclear in the endomyocardial in pa‐ tients with AF. Thirdly, the activation of peripheral blood CD3+ T-lymphocytes could acti‐ vate the calcineurin-nuclear factor, which involve in the T-lymphocytes signal transduction

It is important to note that there are several limitations that need to be addressed regarding this study. Firstly, The results cannot be taken as evidence to support that CD69 and HLA-

T-lymphocytes might cause the upregulation of IL-6 and

of AF through suppressing the activation of peripheral blood T-lymphocytes.

As for the underlying mechanisms of activated peripheral blood CD3+

T cells, and CD68+

T-lymphocytes implied there is an acti‐

http://dx.doi.org/10.5772/54167

53

T-lymphocytes maybe plays an important

macrophages, infiltrated in the endomyo‐

T-lymphocytes partic‐

1987). So the increase of CD69 and HLA-DR on CD3+

In fact, the activation of peripheral blood CD3+

cells, CD3+

vation of peripheral blood CD3+

cytes, such as CD45+

metric analysis.

tivation of peripheral blood CD3+

pathway. (Lin CC et al., 2004)

**Table 2.** Caracteristics of the Studied Population

ACEI indicates angiotensin-converting enzyme inhibitors; ARB, angiotensin receptor block‐ ing agents; CCBs, calcium channel blockers; WBC, white blood cells; CRP, C-reactive pro‐ tein; *p*, probability of significance (difference among three groups); and \*, *p*<0.05 persistent AF vs paroxysmal AF.

In this study, we found that the respective expression of CD69 and HLA-DR on peripheral blood CD3+ T-lymphocytes in AF patients was significantly higher than control group, which might suggest that high expression of CD69 and HLA-DR was associated with AF. In the subsequent follow-up, we further found that the expression of CD69 and HLA-DR in si‐ nus group at follow-up was significantly down-regulated compared with before cardiover‐ sion. However, the expression of CD69 and HLA-DR in recurrence group at follow-up was not significantly down-regulated. It might further support that the CD69 and HLA-DR lev‐ els were related with the state of AF.

As demonstrated by the present study, there was a link between high expression of CD69 and HLA-DR and AF. CD69, known as an early activation marker of lymphocytes, is a type II transmembrane glucoprotein and may enhance activation and proliferation/differentiation of T-lymphocytes. (Sancho D et al. 2005;Vance BA et al.,2005;Beeler A et al.,2008;Creeners P et al.,2002) HLA-DR belongs to the MHC class II system which is known as a late activation marker of lymphocytes. It is required for antigen presentation and activation of helper Tlymphocytes. (Geraldes L et al.,2010;Oczenski W et al.,2003;Bobryshev YV et al.,2011)They respectively expressed in some inflammatory infiltrates and played important roles in the pathogenesis of some inflammatory diseases such as allergic airway inflammation, (Miki-Hosokawa T et al.,2009;Wang HY et al.,2006) rheumatoid arthritis, (Afeltra A et al.,1993) psoriasis vulgaris lesional skin active inflammatory bowel disease (McDonald GB et al., 1987). So the increase of CD69 and HLA-DR on CD3+ T-lymphocytes implied there is an acti‐ vation of peripheral blood CD3+ T-lymphocytes in AF patients.

Before we received the result,we conduct the baseline clinical Caracteristics of the Studied

Age(yrs) 64.4±8.5 64.3±9.5 67.2±9.7 0.176 Men 31 (61%) 32 (64%) 34 (61%) 0.927 Hypertension 13 (25%) 20 (40%) 25 (45%) 0.106 Hyperlipidemia 11 (22%) 8 (16%) 7 (13%) 0.448 Diabetes 2 (4%) 3 (6%) 5 (9%) 0.566

ACE-I/ARB 10 (20%) 11 (22%) 21 (38%) 0.074 Statins 8 (16%) 7 (14%) 6 (11%) 0.743 β-blockers 8 (16%) 26 (52%) 30 (54%) <0.001 CCBs 5 (10%) 12 (24%) 7 (13%) 0.108

WBC count(per uL) 6349±1891 6768±1859 6375±1663 0.819 Lymphocytes(%) 30.9±3.8 32.5±4.3 31.5±4.1 0.147 Monocytes(%) 5.5±1.2 5.8±1.1 5.4±1.1 0.123 CRP(mg/dl) 0.24±0.12 0.48±0.25 0.60±0.22\* <0.001

ACEI indicates angiotensin-converting enzyme inhibitors; ARB, angiotensin receptor block‐ ing agents; CCBs, calcium channel blockers; WBC, white blood cells; CRP, C-reactive pro‐ tein; *p*, probability of significance (difference among three groups); and \*, *p*<0.05 persistent

In this study, we found that the respective expression of CD69 and HLA-DR on peripheral

which might suggest that high expression of CD69 and HLA-DR was associated with AF. In the subsequent follow-up, we further found that the expression of CD69 and HLA-DR in si‐ nus group at follow-up was significantly down-regulated compared with before cardiover‐ sion. However, the expression of CD69 and HLA-DR in recurrence group at follow-up was not significantly down-regulated. It might further support that the CD69 and HLA-DR lev‐

As demonstrated by the present study, there was a link between high expression of CD69 and HLA-DR and AF. CD69, known as an early activation marker of lymphocytes, is a type II transmembrane glucoprotein and may enhance activation and proliferation/differentiation of T-lymphocytes. (Sancho D et al. 2005;Vance BA et al.,2005;Beeler A et al.,2008;Creeners P

T-lymphocytes in AF patients was significantly higher than control group,

**Paroxysmal AF (n=50) Persistent AF (n=56)** *p*

Population to ensure facticity of the results (Table 2).

52 Atrial Fibrillation - Mechanisms and Treatment

Drugs:

**Table 2.** Caracteristics of the Studied Population

els were related with the state of AF.

AF vs paroxysmal AF.

blood CD3+

**Control (n=51)**

> In fact, the activation of peripheral blood CD3+ T-lymphocytes maybe plays an important role in the pathogenesis of AF. A few studies reported that some inflammatory lympho‐ cytes, such as CD45+ cells, CD3+ T cells, and CD68+ macrophages, infiltrated in the endomyo‐ cardial in patients with AF, which supported the local activation of T-lymphocytes played a role in the pathogenesis of AF.(Chen MC et al.,2008;Nakamura Y et al.,2003;Yamashita T et al.,2010) On the other hand, a lot of studies reported that serum or plasma inflammation bio‐ markers, such as C-reactive protein (CRP), interleukin (IL)-6, IL-8, IL-10, tumor necrosis fac‐ tor (TNF)-α, monocyte chemotactic protein (MCP)-1, vascular endothelial growth factor (VEGF), et al., increased in AF patients, which supported T-cell-associated chronic inflam‐ matory responses might involve in the pathogenesis of AF. (Chung MK et al.,2001;Heman‐ dez Madrid A et al.,2007;Li J et al.,2010;Psychari SN et al.,2005) In our study, we provided another evidence to support that there is an activation of peripheral blood CD3+ T-lympho‐ cytes in AF patients, demonstrated by the upregulation of CD69 and HLA-DR by flow cyto‐ metric analysis.

> Generally, our study here further emphasize that activation of T cells is involved in AF. As we all know, T-lymphocytes are the main cells participate in cell-mediated immunity, which is one of the primary ways of human immune. It can be suppressed by many immunosup‐ pressants such as Cyclosporine, Rapamycin, et al. If the activation of peripheral blood Tlymphocytes does participate in the pathogenesis of AF, maybe we can prevent recurrence of AF through suppressing the activation of peripheral blood T-lymphocytes.

> As for the underlying mechanisms of activated peripheral blood CD3+ T-lymphocytes partic‐ ipates in the progression of AF, we speculate the following three possibilities. Firstly, the ac‐ tivation of peripheral blood CD3+ T-lymphocytes might cause the upregulation of IL-6 and MCP-1, which could affect the contractility and electrical stability of myocytes inhomogene‐ ously and induce fibroblast activation leading to deposits of extracellular matrix fibrosis. (Ramos-Mondragon R et al.,2008) Secondly, activation of peripheral blood CD3+ T-lympho‐ cytes might promote the local immunologic inflammatory responses in the endomyocardial, and promote infiltrate of inflammatory lymphomononuclear in the endomyocardial in pa‐ tients with AF. Thirdly, the activation of peripheral blood CD3+ T-lymphocytes could acti‐ vate the calcineurin-nuclear factor, which involve in the T-lymphocytes signal transduction pathway. (Lin CC et al., 2004)

> It is important to note that there are several limitations that need to be addressed regarding this study. Firstly, The results cannot be taken as evidence to support that CD69 and HLA-

DR play a role in the pathogenesis of AF, it only indicate the possible association of CD69 and HLA-DR with AF. Secondly, how CD69 and HLA-DR contribute to the pathogenesis of AF and what is the underlying mechanism need to be further investigated. Thirdly, we did not study the influence of other immune activation-associated molecules (CD25, CD71, and CD122, et al) and co-stimulatory molecules (CD28, CTLA-4, CD80, CD86, et al) during the progression of AF.

plement system during and after cardiopulmonary bypass surgery: postsurgery activation involves C-reactive protein and is associated with postoperative arrhyth‐

http://dx.doi.org/10.5772/54167

55

Effect of CD3+ T-Lymphocyte and n-3 Polyunsaturated Fatty Acids on the Diagnosis or Treatment of Atrial Fibrillation

[5] Chung MK, Martin DO, Sprecher D, Wazni O, Kanderian A, Carnes CA, Bauer JA, Tchou PJ, Niebauer MJ, Natale A, Van Wagoner DR.C-reactive protein elevation in patients with atrial arrhythmias: Inflammatory mechanisms and persistence of atrial

[6] Hernandez Madrid A, Moro C. Atrial fibrillation and c-reactive protein: Searching

[7] Li J, Solus J, Chen Q, Rho YH, Milne G, Stein CM, Darbar D. Role of inflammation

[8] Psychari SN, Apostolou TS, Sinos L, Hamodraka E, Liakos G, Kremastinos DT. Rela‐ tion of elevated c-reactive protein and interleukin-6 levels to left atrial size and dura‐ tion of episodes in patients with atrial fibrillation. Am J Cardiol 2005;95:764-767.

[9] Chen MC, Chang JP, Liu WH, Yang CH, Chen YL, Tsai TH, Wang YH, Pan KL. In‐ creased inflammatory cell infiltration in the atrial myocardium of patients with atrial

[10] Nakamura Y, Nakamura K, Fukushima-Kusano K, Ohta K, Matsubara H, Hamuro T, Yutani C, Ohe T.Tissue factor expression in atrial endothelia associated with non‐ valvular atrial fibrillation: Possible involvement in intracardiac thrombogenesis.

[11] Yamashita T, Sekiguchi A, Iwasaki YK, Date T, Sagara K, Tanabe H, Suma H, Sawada H, Aizawa T.Recruitment of immune cells across atrial endocardium in human atrial

[12] Caruso A, Licenziati S, Corulli M, Canaris AD, De Francesco MA, Fiorentini S, Peroni L, Fallacara F, Dima F, Balsari A, Turano A.Flow cytometric analysis of activation markers on stimulated t cells and their correlation with cell proliferation. Cytometry

[13] Reddy M, Eirikis E, Davis C, Davis HM, Prabhakar U. Comparative analysis of lym‐ phocyte activation marker expression and cytokine secretion profile in stimulated human peripheral blood mononuclear cell cultures: An in vitro model to monitor cel‐

[14] Sancho D, Gomez M, Sanchez-Madrid F. Cd69 is an immunoregulatory molecule in‐

[15] Geraldes L, Morgado J, Almeida A, Todo-Bom A, Santos P, Paiva A, Cheira C, Pais ML.Expression patterns of hla-dr+ or hla-dr- on cd4+/cd25++/cd127low regulatory t cells in patients with allergy. J Investig Allergol Clin Immunol 2010;20:201-209.

lular immune function. J Immunol Methods 2004;293:127-142.

duced following activation. Trends Immunol 2005;26:136-140.

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for local inflammation. J Am Coll Cardiol 2007;49:1649-1650.


**3. Case study 2: Chaos synthesis**

This part introduces the notion of chaos synthesis by means of evolutionary algorithms and develops a new method for chaotic systems synthesis, [13]. This method is similar to genetic programming and grammatical evolution and is being applied along with evolutionary algorithms: differential evolution, self-organizing migrating, genetic algorithm, simulated annealing and evolutionary strategies. The aim of this investigation is to synthesize new

#### 12 Name of the Book 80 Simulated Annealing – Single and Multiple Objective Problems Simulated Annealing in Research and Applications 13

and simple chaotic systems based on some elements contained in a pre-selected existing chaotic system and a properly defined cost function. The investigation consists of two case studies based on the aforementioned evolutionary algorithms in various versions. For all algorithms, 100 simulations of chaos synthesis were repeated and then averaged to guarantee the reliability and robustness of the proposed method. The most significant results were carefully selected, visualized and commented on in this chapter.

More brief and simple description of above algorithmically defined cost function can be also

The input to this cost function is a synthesized function and the output is the fitness (quality) of the synthesized function (i.e., the individual in the population). In the cost function, it was tested twice to see if the behavior of the just-synthesized formula is really chaotic. The first test was done in step 2 (unique appearance in the data series) and the second one, in step 4,

The reason why in step 5) the sum of the non-unique data appearances was returned is based on the fact that the evolution is searching for minimal values. In this case, the value 2 means that some data element appears in the 500-data series twice, and 1 would means that there is

To make sure that the results so obtained are correct, all written synthesized functions were used for automatic generation of bifurcation diagrams and Lyapunov exponents, as further

SA algorithms have been applied 100 times in order to find artificially synthesized functions that can produce chaos. All of these experiments were done using the *Mathematica* software. The primary aim of this comparative study is not to show which algorithm is better or worse, but to show that symbolic regression is able to synthesize some new (at least in the sense of

Based on the results from experiments, two different sets of figures were created. The first set shows the performances of different algorithms from different points of view (see [13]), the second set (Figure 11 - Figure 14) shows behaviors of the selected synthesized programs, i.e., bifurcation diagrams. The synthesized programs are also appended to each figure in the form of the mathematical formula. Figure 15 shows an example of the so-called program length histogram, generated from 100 simulations. Program length (in *Mathematica* command: LeafCount, denoted as LC) means a number of elements that create a mathematical formula.

• **Result verification.** To be sure that the results as presented in the paper are correct, all written synthesized functions were used for automatic generation of bifurcation diagrams

• **Simulation results.** Based on the results (see selected Figures 11 - 14) and the selected bifurcation diagrams, it can be stated that all simulations give satisfactory results and that

• **Range of chaos and interval of observation.** During evolutions, chaos was searched by focusing on interval [0, 4], based on the a priori known behavior of the logistic equation

evolutionary synthesis of chaos is capable of solving this class of problems.

calculate *λ* for *Data*[ *fsynt*, 300, ... , *fsynt*, 500] , *i f λ* > 0 write all to file

(9)

Simulated Annealing in Research and Applications 81

*Data*[ *fsynt*, 1, ..., *fsynt*, 500] := *fsynt*, *k*+1 = *fsynt*, *k*(*xstart*), *k* ∈ [1, 500]

*if Data*[ *fsynt*, 1] �= *Data*[ *fsynt*, 2] �= .... �= *Data*[ *fsynt*, 500]

no periodicity and thus synthesized system is possible candidate for chaos.

done as in Equation 9.

*then* �

*else* penalize individual

where the Lyapunov exponent was tested numerically [5].

mathematical description and behavior) chaotic systems.

As a summary, the following statements are presented: As a summary, the following statements are presented:

⎧ ⎨ ⎩

discussed below.

**3.2. Simulations and results**

and Lyapunov exponents.

Deterministic chaos, discovered by [21] is a fairly active area of research in the last few decades. The Lorenz system produces a well-known chaotic attractor in a simple three-dimensional autonomous system of ordinary differential equations, [21], [22]. For discrete chaos, there is another famous chaotic system, called the logistic equation [23], which was found based on a predator-prey model showing complex dynamical behaviors. These simple models are widely used in the study of chaos today, while other similar models exist (e.g., canonical logistic equation [24] and 1D or 2D coupled map lattices, [25]). To date, a large set of nonlinear systems that can produce chaotic behaviors have been observed and analyzed. Chaotic systems thus have become a vitally important part of science and engineering at the theoretical as well as practical levels of research. The most interesting and applicable notions are, for example, chaos control and chaos synchronization related to secure communications, amongst others.

The aim of the present investigation is to show that EA-based symbolic regression (i.e., handling with symbolic objects to create more complex structures) is capable of synthesizing chaotic behavior in the sense that mathematical descriptions of chaotic systems are synthesized symbolically by means of evolutionary algorithms. The ability of EAs to successfully solve this kind of black-box problems has been proven many times before (see, for example, [26], [27]), and is proven once again here in this paper.


**3. Methods**

This systematic review was conducted with reference to the basics of Cochrane Handbook for Systematic Reviews of Interventions [19], described as stated by the Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) statement [20].

#### *3.1. Search Strategy and Selection Criteria*

A systematic review protocol was developed based on PRISMA-P and the PRISMA statement. Published articles from 1 December 2019, to 20 November 2020, were selected for review from 8 electronic databases (PubMed, CINAHL, Embase, medRxiv, Proquest, Wiley online library, Medline, and Nature).

The focus of the review was LPV/RTV treatment in COVID-19 patients. The primary outcome was the efficacy of LPV/RTV in COVID-19 patients. The secondary outcome was adverse events associated with its use.

### *3.2. Inclusion Criteria*

Readily accessible peer-reviewed full articles, observational cohort studies, and clinical trials were included.


**Matías Jeldres 1, Eder Piceros 2, Pedro A. Robles 3, Norman Toro 4,5,\* and Ricardo I. Jeldres 1**

Received: 14 September 2019; Accepted: 17 October 2019; Published: 19 October 2019

**Abstract:** In this study, the viscoelastic properties of quartz and kaolin suspensions in seawater were analysed considering two distinct conditions: pH 8 and 10.7. Creep and oscillatory sweep tests provided the rheological parameters. An Anton Paar MCR 102 rheometer (ANAMIN Group, Santiago, Chile) was used with a vane-in-cup configuration, and the data were processed with RheoCompassTM Light software (ANAMIN Group, Santiago, Chile). The outcomes were associated with the formation of solid species principally composed of magnesium precipitates. The magnesium in solution reduced in the presence of quartz (68 wt %), from 1380 to 1280 mg/L. Since the difference was not large regarding the solid-free seawater, the disposition of solid complexes at pH 10.7 was expected to be similar. The jump in pH caused both yield stress and viscoelastic moduli to drop, suggesting that the solid precipitates diminished the strength of the particle networks that made up the suspension. For the kaolin slurries (37 wt %), the yield stress raised when the pH increased, but unlike quartz, there was significant adsorption of magnesium cations. In fact, the concentration of magnesium in solution fell from 1380 to 658 mg/L. Dynamic oscillatory assays revealed structural changes in both pulps; in particular, the phase angle was greater at pH 8 than at pH 10.7, which indicates that at more alkaline conditions, the suspension exhibits a more solid-like character.

**Keywords:** viscoelasticity; quartz; kaolin; seawater; magnesium precipitates


2.2.2. Method 2—Heat Flow Meter Method (HFM)

By measuring heat flux density, one can obtain a more accurate result as large fluctuations in air temperature readings can be partially eliminated in this way. In this case, the thermal resistance can be determined from the formula:

$$R = \frac{(T\_{si} - T\_{sc})}{q} \tag{5}$$

and then, total thermal resistance can be calculated from the formula:

$$R\_{tot} = R\_{si} + R + R\_{sc} \tag{6}$$

where:

*Tsi*, *Tse*—the temperature of respectively the internal and external surface of the tested building enclosure (K),

*q*—the measured heat flux flowing through the building enclosure (W/m2),

*Rsi*, *Rse*—the calculated surface thermal resistances on respectively the internal and external side of the building partition ((m2K)/W).


*Edited by Natalia Szejko and Kamila Saramak*

Motor neuron diseases (MNDs) are a group of progressive neurodegenerative disorders associated with the degradation of the upper (UMN) or lower motor neurons (LMN) or both. They encompass amyotrophic lateral sclerosis (ALS), spinal muscular atrophy (SMA), spinobulbar muscular atrophy (SBMA), hereditary spastic paraparesis (HSP), and others. MND patients present with a wide variety of clinical symptoms, including muscular weakness, atrophy, and corticospinal tract signs in diverse combinations. Over recent years, considerable collaborative efforts have been made to unravel the underlying pathophysiology of MNDs and find novel therapeutic interventions. With this book, we aim to provide both professionals and the general public with an outline of the latest scientific advances regarding the genetics, pathophysiology, diagnostics, and treatment options for MNDs. Researchers from different parts of the world have contributed to this volume in order to create a comprehensive multidisciplinary overview of the topics.

Published in London, UK © 2024 IntechOpen © bestdesigns / iStock

Motor Neurons - New Insights

Motor Neurons

New Insights

*Edited by Natalia Szejko and Kamila Saramak*


**4. Instances of color objects with the process**

In this section, two kinds of instances of color objects created with the process are demon‐ strated, showing the color reproduction and further potential applications.

#### **4.1. UV-ink-based 3D Printing**

UV-ink-based 3D Printing follows the similar principle as the DOD (drop on drop) 3D Printing technology. A UV-LED flatbed printer is used as a 3D printer and the UV ink as the modeling material. The UV ink jetting from the printer nozzle solidifies after being irradiated by a UV lamp. Finally, the model is shaped through layer-by-layer printing. However, the difference between UV-ink-based 3D Printing and DOD printing is that the modeling process of each layer of the former is an integrated section and of the latter is a series of lines. So, because of this characteristic of UV-ink-based 3D Printing, it is more suitable for 2.5D modeling. Below are two examples of UV-ink-based 3D Printing.

#### *4.1.1. Application for oil painting reproduction*

After completion of one layer of material, the printing nozzles moves back to the origin, and platform falls to a certain height in the Z axle, such as 0.5 mm. The printing nozzles restart to form the next layer. This is called one layer forming cycle, and after certain cycles, the color

Three-dimensional color printer with solid forming has one key technology, that is, the development of coloring software modules. The software can process STL file data, form a solid layer contour, and add an internal solid modeling tool to add gradient color information. According to the requirements of colored objects, a coloring module should have two func‐

**1.** *STL file data processing function*: (a) read and parse STL files; (b) establish triangular facet

**2.** *Gradient interpolation coloring on each layer*: (a) linear interpolation coloring; (b) cosine interpolation coloring; (c) cosine G color tone interpolation coloring; (d) power interpo‐

Using UGNX software or CAD drawing software to make three-dimensional solid modeling, mapping is performed through the menu options after forming "\* .stl" file. With common 3D modeling software, in the "File" menu there are "Export" command, and it can export a "\* .stl" file, and then manually change it into ".txt" type files. To understand the file format, use

Quick slicing algorithms create a data structure of triangular with vertices and edges. After the data structure is created, software will reorder all distinct vertexes, and then topology data are completely setup. Finally, the above-mentioned interpolation functions can be used to

In this section, two kinds of instances of color objects created with the process are demon‐

UV-ink-based 3D Printing follows the similar principle as the DOD (drop on drop) 3D Printing technology. A UV-LED flatbed printer is used as a 3D printer and the UV ink as the modeling material. The UV ink jetting from the printer nozzle solidifies after being irradiated by a UV lamp. Finally, the model is shaped through layer-by-layer printing. However, the difference between UV-ink-based 3D Printing and DOD printing is that the modeling process of each layer of the former is an integrated section and of the latter is a series of lines. So, because of

topology; (c) design solid slicing algorithm and contour generation.

notepad to open "\* .txt", and then we can see data of small triangular.

strated, showing the color reproduction and further potential applications.

**4. Instances of color objects with the process**

solid is finally completed.

42 New Trends in 3D Printing

lation coloring.

show the results.

**4.1. UV-ink-based 3D Printing**

tions:

*3.8.3. Coloring module software development*

3D Printing is a novel method to reproduce oil paintings so that it can restore the stereo brushwork of the original. In this work, we use a laser scanner to detect the surface morphology of an oil painting and first build the 3D model. Second, we extract the cross section from the 3D model with a certain contour interval according to the thickness of UV-LED ink. Finally, we print white ink layer by layer for 3D shaping and print a color image onto the neutral 3D model.

We selected an oil painting (**Figure 9**) of 7.5 cm (L) × 6 cm (W) for scanning and printing. A laser 3D scanner is used to obtain point cloud data of the original oil painting (**Figure 10**). Next, we measured the thickness of the UV ink to determine the number of the printing layers.

**Figure 9.** The original oil painting.

**Figure 10.** Point cloud model of the oil painting.

This work first conducted the UV-LED printing for 1–10 layers of C, M, Y, K, and W ink separately. Then, we measured the average thickness of the paper and every color lump by a CHY-C2 thickness gauge (see **Table 1**).

**Table 1.** Average thickness of every color lump.

Obviously, the thickness of these four ink films is different. The average thicknesses of C, M, Y, K, and W ink films are 11, 13.2, 7.9, 9, and 13.7 μm. According to the subtractive color-mixing principle, most radiation light will be absorbed after color mixing. White ink possesses both highest lightness and thickest ink film, so it is considered the best modeling materials for layered printing.

After 3D model slicing, 2D cross-sectional data can be obtained by intersecting the 3D model horizontally with a series of planes. The number of slices that we can obtain in this case is equal to the ratio of model height to white ink-film thickness. As a result, 91 layers are determined to be printed. **Figure 11** shows the result of cross sections extraction. Through contour vectorization and RIP, the neutral 3D model (**Figure 12**) and the reproduction (**Figure 13**) were printed by a UV LED printer.

**Figure 11.** Cross sections.

**Figure 12.** Neutral 3D model.

**Figure 13.** Reproduction.

**Layers Color lump 0 1 2 3 4 5 6 7 8 9 10** Average thickness (μm) C 243.9 251.7 261.6 272.6 283.2 294.4 307.1 318.2 328.5 339.2 351.8

Obviously, the thickness of these four ink films is different. The average thicknesses of C, M, Y, K, and W ink films are 11, 13.2, 7.9, 9, and 13.7 μm. According to the subtractive color-mixing principle, most radiation light will be absorbed after color mixing. White ink possesses both highest lightness and thickest ink film, so it is considered the best modeling materials for

After 3D model slicing, 2D cross-sectional data can be obtained by intersecting the 3D model horizontally with a series of planes. The number of slices that we can obtain in this case is equal to the ratio of model height to white ink-film thickness. As a result, 91 layers are determined to be printed. **Figure 11** shows the result of cross sections extraction. Through contour vectorization and RIP, the neutral 3D model (**Figure 12**) and the reproduction (**Figure 13**) were

**Table 1.** Average thickness of every color lump.

layered printing.

44 New Trends in 3D Printing

printed by a UV LED printer.

**Figure 11.** Cross sections.

**Figure 12.** Neutral 3D model.

M 243.9 255.7 268.9 282.6 296.2 309.5 322.5 335.4 348.3 361.5 374.6 Y 243.9 247.7 255.8 264.6 272.1 279.8 287.4 295.9 303.7 310.9 318.6 K 243.9 248.9 258.0 266.8 276.3 285.1 294.0 303.4 312.1 321.3 330.5 W 243.9 254.8 268.6 282.9 296.9 310.1 323.8 337.3 350.2 364.1 378.9

#### *4.1.2. Application for a topographical map of Taiwan*

3D Printing of a colored topographical map follows the same principle as printing a stereo oil painting. First, we extracted and vectorized the contours of the topographical map of Taiwan. Then, we provided different colors to various heights of contour sections according to the standard of altitude tinting. Based on the actual situation, in order to obtain the best printing effects and quality, 14 layers were tinted as shown in **Table 2**.

**Table 2.** Altitude tinting of the topographical map.

Finally, we use UV-LED printer to print the topographic relief and altitude-tint legend. The horizontal scale is 1:3,000,000, the vertical scale is 1:1,500,000, and the printing height is 2.59 mm.

#### **4.2. Paper-based 3D Printing**

Matrix 300A, a kind of paper-based 3D printer, is provided by MCOR technologies. It contains a standard Epson 310N printer supplied with the color system and a matrix printer responsible for elevation building. An A4 paper is used and the aqueous adhesives used to adhere two layers volatilize no harmful gas.

**Figure 14** shows the flowchart of printing steps. The process begins with a 3D digital model in "\*.stl", "\*.obj" or "\*.wrl" format. Each edge of the layer is printed with bar codes, which are used to read the sequence. Before the 3D building, a piece of a blank paper is affixed to the build plate, and the glue spreader will uniformly coat aqueous adhesive on the paper. Then, the colorful layers are laid on the paper tray of the matrix printer, and the top layer will be pulled by paper-feed roller and gripper onto the built plate. As shown in **Figure 14**, Step 3, the build plate will rise to the top of the build space to press the heat plate, thereby smoothing the top layer and ensuring that it will adhere firmly to the blank paper at a high temperature. The blade will cut the top layer into the contour of the corresponding 2D cross section once the build plate lowers, and the glue spreader will coat aqueous adhesive on the top layer. Similarly, the next layer is processed; the process is repeated until all the necessary layers are processed. When matrix printer stops working, a large paper cube as shown in **Figure 14**, Step 4, is obtained. After the basal and excess portion is removed, the 3D object is obtained.

**Figure 14.** The printing process of the Matrix 300A.

Using paper as a printing material, paper-based 3D Printing shows an excellent performance on full-color reproduction. In fact, the printer only colors the surface of object, the excess and interior portions are all blank, which contribute to low-cost and high efficiency.

#### *4.2.1. Application for historic preservation*

Cultural relic is a very important part in the development of human culture. When visitors enter the scenic spots and historical sites, it is often difficult to see the full view of the cultural relics. Because of long time, corrosion, or man-made damage, cultural relics are difficult to save. 3D scanning technology provides a good permanent preservation of cultural relics, and 3D Printing technology provides a good method to produce a copy.

Take a Buddha sculpture for instance, it describes how paper-based 3D Printing technology can do the trick in historic preservation through 3D data acquisition, processing, and printing. The first step is to use the Mephisto EX PRO 3D scanner to obtain the 3D data of a Buddha, as shown in **Figure 15**. The second step is to use the Mephisto software to process the data. It mainly includes removing outliers, smoothing, and data compression, as shown in **Figure 16**. The final step is fabrication. The paper-based 3D printer of Matrix 300A is actuated to finish the reproduction of the sculpture. Basic workflow includes coloring-carving-sizing-pressingbonding, and the physical 3D model is shown in **Figure 17**.

**Figure 15.** Scanning process.

**4.2. Paper-based 3D Printing**

46 New Trends in 3D Printing

layers volatilize no harmful gas.

**Figure 14.** The printing process of the Matrix 300A.

*4.2.1. Application for historic preservation*

Matrix 300A, a kind of paper-based 3D printer, is provided by MCOR technologies. It contains a standard Epson 310N printer supplied with the color system and a matrix printer responsible for elevation building. An A4 paper is used and the aqueous adhesives used to adhere two

**Figure 14** shows the flowchart of printing steps. The process begins with a 3D digital model in "\*.stl", "\*.obj" or "\*.wrl" format. Each edge of the layer is printed with bar codes, which are used to read the sequence. Before the 3D building, a piece of a blank paper is affixed to the build plate, and the glue spreader will uniformly coat aqueous adhesive on the paper. Then, the colorful layers are laid on the paper tray of the matrix printer, and the top layer will be pulled by paper-feed roller and gripper onto the built plate. As shown in **Figure 14**, Step 3, the build plate will rise to the top of the build space to press the heat plate, thereby smoothing the top layer and ensuring that it will adhere firmly to the blank paper at a high temperature. The blade will cut the top layer into the contour of the corresponding 2D cross section once the build plate lowers, and the glue spreader will coat aqueous adhesive on the top layer. Similarly, the next layer is processed; the process is repeated until all the necessary layers are processed. When matrix printer stops working, a large paper cube as shown in **Figure 14**, Step 4, is

obtained. After the basal and excess portion is removed, the 3D object is obtained.

Using paper as a printing material, paper-based 3D Printing shows an excellent performance on full-color reproduction. In fact, the printer only colors the surface of object, the excess and

Cultural relic is a very important part in the development of human culture. When visitors enter the scenic spots and historical sites, it is often difficult to see the full view of the cultural relics. Because of long time, corrosion, or man-made damage, cultural relics are difficult to save. 3D scanning technology provides a good permanent preservation of cultural relics, and

Take a Buddha sculpture for instance, it describes how paper-based 3D Printing technology can do the trick in historic preservation through 3D data acquisition, processing, and printing. The first step is to use the Mephisto EX PRO 3D scanner to obtain the 3D data of a Buddha, as

interior portions are all blank, which contribute to low-cost and high efficiency.

3D Printing technology provides a good method to produce a copy.

**Figure 16.** Processing photograph.

**Figure 17.** Physical 3D model.

#### *4.2.2. Application for topographic maps*

Digital elevation model (DEM) plays a vital role in engineering construction, hydrology, geological prospecting, etc. Although considering preservation and update of map data, it could not convey actual and accurate 3D feelings to people. In addition, the traditional mold is time-consuming and costly. Thereby, an ability to easily build physical topographic map is necessary. 3D Printing provides the support.

**Figure 18.** Monochrome physical 3D model.

**Figure 19.** Colorful physical 3D model.

Slice IT that supports Matrix 300A is used to slice 3D digital model into many 2D layers with equal thickness, the thickness of the A4 paper is a fixed number, 103.2 μm. The 3D solid model of DEM is sliced into 293 layers. After the printing process of Matrix, the physical 3D model is obtained, as shown in **Figures 18** and **19**.