In the scope of evaluation methodologies for Internet of Things (IoT) systems, some approaches concern security, while others latency. However, some methodologies evaluate systems that contain active entities, so-called actuators. In this paper, we propose a novel methodology for evaluating such systems with actuator components using Graph Representation of the Angle of the Force and Time (GRAFT). GRAFT facilitates easy computation of the net force produced by physical or mechanical acts occurring on a daily basis on Earth. We use laws and definitions of physics describing the relations between Speed, Distance, and Time (SDT), apply them in a heliocentric system, and model the considered systems with a graph. The continuous movement of the Earth was shown to be weakening the total produced net force in some systems. We considered this weakening issue a problem, and we propose two possible solutions to overcome it by using restoration values, or reordering actuator sessions, in GRAFT to arrive to a more force-efficient system. We compared our default GRAFT algorithm to a special implementation using the Clock-Angle-Problem (CAP) for sessions. We also study and discuss an IoT-focused case for validating our approach, and we present a detailed explanation of the proposed GRAFT algorithm. The experimental results show the ability of GRAFT to provide highly accurate results, which also exemplifies that our GRAFT approach is programmable, hence deployable in real life scenarios. With 184 countries pledging to limit the increase in average global temperature to 1.5 °C above pre-industrial levels , more amsense, actuate with, and communicate over the Internet. Consequently, things may be sensors [The Internet of Things (IoT) is a relatively new paradigm suggesting that things can be connected to the Internet and provide usable data about their environments. IoT as defined in  has emer sensors , actuato sensors , small p sensors , etc. th sensors , smart c sensors , smart v sensors , and sma sensors .As clarified in , an actuIn some systems, geographically distributed sensors coupled with actuators are interconnected by wired/wireless networks to perform the entitled tasks, namely Wireless Sensor/Actuator Networks (WSANs) . To gainMany challenges are faced by IoT applications, such as security and energy efficiency , while eIt is well established that Earth is a heliocentric globe, which rotates around its own axis (by spinning) as it revolves around the Sun. The average rotational speed of a point at the equator on the surface of Earth due to its rotation about its own axis is about 465 m/s , which rRelative to the Sun, the Earth’s rotation period (true noon to true noon) is its true solar day , which iAccording to the Heliocentric theory, there are different measurements—since it is not a perfect sphere—for the radius of Earth from its center to the surface . There aAs shown in G’ is an ordered pair  is called energy. It was shown by Jansen and Stevels  how eachEnergy was also proven to be convertible from one form to another, but can be neither destroyed nor created, which is called The Universal Law of Energy Conservation . This laIn light of the definitions discussed above, we aim to propose our novel idea for evaluating the efficiency of actuators that are deployed within certain given conditions in some IoT environment. The purpose and main concern of our proposal is to compute the total net force, which can give an indication of how efficient the evaluated system is. In this paper, we propose the GRAFT (Graph Representation using the Angle of the Force and Time) model, which can be used even on different planets of our solar system, as well as for other solar systems that have planets moving around a star. Our work also includes a proposed algorithm with variables that can be modified for different actions, locations, planets, or solar systems.When applying our proposed evaluation model to a given actuator system, the result presents how weakened the produced force can be, due to the continuous movement of the Earth. The proposed evaluation methodology can also help deploy a more efficient system using the available resources, in terms of net force produced. That is, a system ‘A’ that consumes less energy than system ‘B’ to exert the same value of total produced force, or ‘A’ that consumes the same amount of energy consumed by ‘B’ to exert more force, is the efficiency we are seeking.The following sections of this paper are as follows. In the field of IoT systems with actuators deployability, previous and current research articles have evaluated their proposed systems using methodologies that mainly targeted performance issues such as latency, power consumption, and resource allocation. The authors of  analyzedThere are hundreds, perhaps thousands, of papers, surveys, and proposed ideas discussing a very wide range of issues relating to Earth, astronomy, and IoT knowledge ,40,41,42sessions), through the day.Several tasks need to be performed by an actuator each day, in different times , has to be performed.Each task performed by an actuator has several working cycles. The number of working cycles in a task might be similar to, or different from, the number of cycles performed in other tasks. However, a cycle in a task is similar to all other cycles in the same or other tasks. A working cycle has a predefined known amount of produced force.The cycles of a task may be performed in any time within the session.The number of tasks, the order of the tasks, and the number of cycles performed in each task, is a daily routine that will consume/produce the same amount of energy, hence the same amount of daily force.The GRAFT model computes the total net produced force, in a day, by this actuator, performing the predefined tasks in the predefined sessions.First, the actuator scenario that can be applied into the GRAFT model goes as the following:G’ is built where:The nodes of the graph represent the sessions where tasks are performed by an actuator, producing similar type of force.One extra central node is added to the graph and an edge is defined between this extra node and all other nodes. This should always produce a graph with the following properties:simple;two-leveled acyclic tree;complete bipartite;planar; andhas one face.The weight of each edge equals the ratio value of cycles performed in the adjacent node, to the total number of cycles performed in a day.The positioning of each node is then determined according to the starting time of the session and the session duration. The position of each session is stable relative to Sun position in the sky and not affected by Earth rotation about its axis, because the position of the sun for an observer standing on Earth defines the time for that person. For example, if an actuator is supposed to perform a task during the time 12:00–13:00, it means that this actuator will enter the session/node at 12:00, and will have 60 min to perform the task. That is, the movement of Earth for this static actuator is causing it to enter/exit the session.Accordingly, a graph ‘The model is studied on the planet Earth, but can be—by changing some values in its algorithm—generalized to other similar-to-Earth planets.A node represents a session. A session is a vertical sector that lies between two lines drawn on the surface of Earth. A sector has two endings at north and south, where the two lines meet. The first line represents the starting time of a session, while the second line represents the ending time of the session.A task is all the predefined number of working cycles that should be performed in a named session.A cycle is a predefined unit of tasks. A task is at least one cycle.Session time is the number of minutes during which the actuator has to perform the task.Travelled distance is the distance the actuator travels from the entering point in a session, until the exiting point out of a session.Angle of the session is the angle between two lines: the first is the line connecting the central node to the entering point of a session, and the second line is the one connecting the central node to the exiting point of a session.x-axis.Direction of the session is the estimate bearing of the line connecting the central node to a point between the entering point and exit point, relative to the The central node represents the point in the center of Earth where the speed of rotation equals to zero.W’ of an edge evaluates the ratio of the number of cycles ‘c’ performed in the adjacent session to the total number of cycles ‘T’ that should be performed by all tasks in a day. However, R equals ‘1’ cycle, hence As previously mentioned, the weight ‘A’ produced by a task that performs ‘c’ cycles equals W too.The force ‘Equation , the ratany other similar case, the graph will have different numbers of nodes, edges, weights, and angles for each case. Hence, an algorithm is needed to compute the daily produced force in any similar system. The direction of each edge is considered the vector of the force, which is produced by the task and performed in the adjacent session. The weight of that edge is considered the magnitude of that force.All nodes in the GRAFT are stable angle wise. This means that, since calculating the net produced daily force depends on the direction (its sine and cosine), as will be shown, it matters if the angle between any two edges differs. In addition, despite maintaining the graph properties of being complete bipartite, acyclic tree, and planar with only one face, for The proposed model is based on the true solar day concept.The average rotation speed of the surface of Earth and the average radius of Earth are used in the proposed algorithm.As there are various different parameters used in the GRAFT model and algorithm, it is more suitable to present them in a tabular form. If all tasks were performed with all their cycles at the same session, then this would produce 100% force, because the direction of force produced by all performed cycles is the same, and the weight of the edge representing the session equals exactly 1 .M’ that performs ‘c’ working cycles a day is better than actuator ‘N’ that performs the same number of cycles if M’s total net daily produced force is higher than N’s , and extends for 191 min, hence ends at 15:11. In the fifth and final session of the working day, another four cycles should be done within the following 120 min of the fourth session. Hence, the fifth session starts at 15:11 and ends at 17:11. If this routine is daily committed to, the net force calculated next would be the daily produced net force by that machine.Since the rotation axis of Earth is not perpendicular to its orbit about the sun, as shown in In this subsection, we provide a step-by-step explanation of the proposed GRAFT algorithm. For this reason, we give each major step in Algorithm 1 a number that indicates that step. Furthermore, We apply the calculations of the algorithm to the previously proposed case, leading to computing the net force. Our methodology of computing the net force will be conducted as in the following description:Algorithm 1: The GRAFT algorithm.The user inputs the number of sessions, which must be bigger than zero. The user then inputs the number of cycles that should be performed in each session. After that, the algorithm draws the graph and defines each edge’s weight. The user then inputs the starting and ending times of each session. The algorithm then calculates the session time by subtracting the start time from the ending time of the session.x-axis. This latter value is used then as the direction of the force vector, which is used in computing the vertical and horizontal components of it. At the end of the algorithm, the net force produced by the system is computed. Each step of the algorithm is numbered and explained in detail as the following:(1)–(3): Initialize the variables of the algorithm.(4): User inputs the number of sessions in a day ‘S’.(5): The algorithm checks if the number of sessions ‘S’ equals one or more, otherwise the calculations will be meaningless.(6): Declare an array that will hold the values of cycles per session.(7)–(10): Start a for loop in which the user inputs the number of cycles per session, and consequently the algorithm computes the total number of cycles per day.(11): Draw the graph according to the number of sessions.(12)–(21): Start a for loop in which each session’s weight, vertical component, and horizontal component are calculated.–13): Compute the weight of the session using Equation (3: Comput–(14) and (15): User inputs the start and end times of the session.–(16): The algorithm computes the total time of the session accordingly.–(17): The algorithm computes the session’s distance. If both the rotational speed at a given point on the surface of Earth and the movement time between two points are known (computed in Step (16)), then the distance ‘the time , as giveThe algorithm calculates each session’s distance ‘–(18): Use the result of Step (17) to calculate the angle ‘Equation , which ix-axis. The results of this are provided in Column 7 of The results of this step are provided in Column 6 of –x-axis. To do so, perform the following:(19): In this step, compute the direction ‘*x-axis is 270°. Consequently, the direction of the session equals 270 plus  and (21): The algorithm in this step computes the vertical and the horizontal components of the edge, respectively, as a vector, and uses the weight of the edge as its magnitude. Equations  and 6)  6) are u(22)–(24): The algorithm in this step updates the values of the public variables “VerticalComponents” and “HorizontalComponents”, respectively, and moves to the next session.(25)–(27): Once the FOR sentence terminates, all needed values to find the total net produced force for all sessions become available. Using those values, the Pythagorean theorem, and classical trigonometric calculations, the algorithm computes the net force and its direction. Finally, the algorithm returns the public values NetForce and NetAngle in Step (27).After that, it calculates the distance that the actuator travels while it is in the session time (using the average speed of Earth). Then, it calculates the angle of the session drawn on the central node (using the average diameter of the planet). Consequently, the algorithm finds the direction of the session relatively to the x-axis is approximated by 238.45°. For the proposed case, the computed net force equals approximately 57.4% out of the optimal 100%. This means that GRAFT model could represent how the movement of Earth weakened the produced force with a percentage of 42.6%. Moreover, the computed direction of the net force vector relatively to the restoration value is needed to gain back the weakening of force caused by the rotation of Earth. A restoration value might be one or several cycles done within pre-defined time sessions. For the correctness of a proposed restoration value to be tested, the GRAFT model must be applied one more time for combining the original net force vector with the proposed restoration value vector. Consequently, if a final vector whose magnitude equals to precise ‘1’ is gained, the proposed restoration value is successful.According to the assumptions of the GRAFT model, a system, in which a machine works 17 cycles, that produces daily net force more than 57.4%, is better than the one studied in our proposed case. The GRAFT model, along with its algorithm, was applied to calculate the total net force produced by a machine performing seventeen cycles of work within pre-defined time sessions. The application of GRAFT on the mentioned case showed that the ratio of the net force to the optimal 100% ratio maps to a number between 0 and 1. If the 100% ratio is required in some situation, a https://github.com/HamzaBaniata/GRAFT) and compared the results of GRAFT with the results of the CAP formula.In this subsection, we compare the sessions’ directions we obtained when applying the GRAFT model—which were computed on Line 19 of the GRAFT algorithm, and provided previously in Algorithm 2: Clock-Angle-Problem.The CAP formula calculates the angle between the beginning of the session and the end of the session Equation . The CAPEquation . HoweverEquation . AlgoritEquation  presentsH is the hour; and M is the minutes past the hour.In contrast, our results were more accurate since GRAFT considered the fact that Earth is not a perfect sphere. The GRAFT results were quite close to the theoretical results obtained from CAP with an average absolute difference of 0.155° in the direction computing. This indicates the correctness of our proposed methodology in computing the angles and the direction of sessions.We suggested a case in The CAP formula and the GRAFT algorithm provide exactly the same results if and only if the system is deployed on a perfectly spherical planet.If the planet deviates from spherical symmetry, GRAFT gives more accurate and slightly different results compared with the results of CAP formula. Accordingly, we can draw conclusions regarding how spherical the planet is by comparing the results of GRAFT and CAP models.In the case of a planet that has a random shape, and not close enough to spherical symmetry, the CAP formula is not applicable. In such case, only GRAFT algorithm can provide the desired results. This is because we can simply use different radius measurement for each session.Although our approach appears to be replaceable by a simple vector addition, in reality, it is not as simple as it seems. The simple vector addition is applicable in the case where the planet is a perfect sphere. However, the results will be different when the planet is not a perfect sphere. This is demonstrated by the comparison presented in Additionally, actuators might be deployed underground, or above the surface of the planet, as in the case of satellites. In these cases, the effective radius used in GRAFT model changes, and the resultant net force will be different. GRAFT in such cases is applicable in a reliable manner. We believe that, for massive projects, such as deploying millions of actuators, our approach for evaluating the efficiency of the whole system may be highly needed.In the scope of evaluating Internet of Things (IoT) systems, the evaluation of entities such as processors, sensors, and control devices may consider criteria such as security, latency, network load, etc. However, some IoT systems include actuator entities that are entitled to perform physical actions periodically, or upon specified data sensed by the sensors in the system. This paper proposes the GRAFT (Graph Representation using the Angle of the Force and Time) approach with the main objective to evaluate such systems in terms of force production. To show the applicability of the proposed GRAFT model, a case study was suggested, and then the model was applied on it. After that, the calculations were performed using our proposed algorithm, followed by a step-by-step explanation of this algorithm. When compared to the 100% optimal net force that can be obtained, if the Earth were not moving, our work showed that the ratio of net produced force maps to a number between 0 and 1. This was considered a problem that can be overcome by the “Restoration Value”, the concept of which is also proposed, resulting a more force-efficient system in terms of GRAFT. Although the GRAFT model was studied on the planet Earth, we believe that it can be modified to be generalized on other similar-to-Earth planets. To validate our proposed methodology, we implemented the GRAFT algorithm using the Clock-Angle-Problem formula, and compared the results of our proposed algorithm to the results obtained using our specially designed implementation. The measurements of sessions’ directions were very close, with average absolute difference of 0.155°, which indicates the validity of the GRAFT algorithm. The difference between the compared results appeared due to the fact that the Earth is not a prefect sphere, a factor that was considered in the GRAFT algorithm.


Blockchain-based loan system can be summed up as: information exchange between various government departments; information exchange between enterprises and various financial institutions; detection of the actual use of loans in the form of encrypted currency. This technology is supposed to reduce a lot of financing costs for SMEs on average. Therefore, this research extends complexity theory to discover the factors that affect the use of Blockchain loan systems by SMEs. Complexity, perceived risk, perceived fairness and reward sensitivity prove to have significant effects on usage intention. Complexity proves to have moderating effects on other relationships. This research may contribute to the system performance improvement and provide opportunities for SMEs to share information with financial institutions or individuals around the world, thereby providing investors with equal opportunities for competition. Small and medium-sized enterprises (SMEs) employ various forms of employment, and their mechanisms are relatively flexible, which can meet the needs of diverse forms of employment. Since the operating information of SMEs is not as transparent as that of listed companies, it brings great difficulties to financial institutions in pre-lending investigations, loan approvals, and post-lending management. The vast majority of loan work relies on manual investigation, judgment, review, and accumulation of years of work experience. Therefore, the labor cost in the entire loan process is too high. For some SMEs, in order to obtain loans faster, they may deliberately hide debts or business risks, which will lead to the failure of financial institutions’ investments. For financial institutions, since it takes a lot of time and manpower to do due diligence, they will increase loan interest rates as compensation. The above reasons create an illusion that SMEs are unwilling to borrow from financial institutions, and financial institutions are unwilling to lend to SMEs.Blockchain-based loan system is designed to solve the problem of difficult, expensive and slow financing for SMEs. This system integrates various data and information related to SMEs such as supervision, taxation, transaction, customs, legal affairs, social security fee, and water and electricity charges. In the Blockchain-based loan system, financial institutions can query various business data of SMEs after legal authorization, and form a corporate profile, so as to judge the business status of the business before and after the loan. This system is provided and supervised by the government. SMEs who want to obtain loans quickly at low cost can voluntarily join the Blockchain-based loan system. After obtaining the consent of SMEs, relevant financial institutions can obtain their business data from the system. Moreover, since loans are issued in digital currency, the flow of funds is supervised by the financial institutions that issue loans to ensure that loans are used in actual business activities or designated purpose. The functions of this system can be summed up as: information exchange between various government departments; information exchange between enterprises and various financial institutions; detection of the actual use of loans in the form of encrypted currency. This technology is supposed to reduce a lot of financing costs for enterprises on average.Although financial institutions vigorously promote the Blockchain-based loan system to support SMEs in financing, some SMEs hide the truly important data in the depths of the company and are unwilling to share it with financial institutions because it involves shareholder interests, trade secrets, patent privacy, transaction information, peer competition, and other specific requirements, etc. Since SMEs have different acceptance levels or some concerns about using Blockchain-based loan system, it is necessary to study the key factors that affect SMEs to carry out the system. Therefore, the focus of this research is to discover the factors that affect the use of Blockchain-based loan systems by SMEs, with the aim of enhancing usage intention and acceptance of Blockchain-based loan systems by SMEs.In recent years, Blockchain technology has been integrated with governments and enterprises to become a key innovation and has been widely recognized , 2. ApplWalton 2014)  reviews   reviewsComplexity may occur in the use of Blockchain-based loan system by financial institutions and SMEs. For financial institutions, although this system provides sufficient information to analyze the operating status of SMEs, the massive amount of information has brought excess workload to the managers. They need to classify the industry first, and then decide which information is important for loan review, which information is important for post-loan monitoring, and which information is only an auxiliary reference. These tasks have undoubtedly increased the complexity of the work. For SMEs, originally, many of them did not follow the standards of large enterprises to formulate work processes. Their financial process, employment system, sales channels, capital flow, cost control, etc. may not meet the requirements of financial institutions. Therefore, in order to obtain loans, small and medium-sized enterprises must adjust and upgrade their original work processes to make everything formal. And this will definitely increase the complexity of the work of SMEs. In summary, complexity is an important factor in financial institutions and SMEs in accepting Blockchain-based loan system activities.From the perspective of motivation and behavior, SMEs choose a Blockchain-based loan system because of their inherent needs and an interest-driven performance. The decision-making behavior of SMEs is goal-oriented, and their goal is to obtain loans quickly and at low cost. When the Blockchain-based loan system cannot satisfy SMEs in some respects, SMEs will abandon it and look for alternatives instead. Therefore, this research brings together the complexity theory and pull-push-mooring effects to better study the Blockchain-based lending system.Push factors refer to the factors that lead to dissatisfaction with existing products or services . In thisIn order to be eligible to use the Blockchain-based loan system, SMEs must improve their own information records, including but not limited to taxes, bank transfers, utility bills, wages, inventory, operating costs, etc. For SMEs, it is necessary to upgrade the current management system, train or hire specialized employees, especially to complete data that has not been recorded for many years, which brings certain risks to SMEs. Can the cost of improving this information bring the expected satisfactory low-interest loans? Will so much information uploaded to financial institutions be used for tax investigation or employment arbitration? Will senior employees who manage this information sell this information privately to peers for compensation? The most important thing is that if loans are issued in the form of digital currency, the core competitiveness of small and medium enterprises, such as suppliers, accessories and retail information, will be controlled by the government and financial institutions. In this case, the intellectual property rights of SMEs are likely to be copied at low cost. In order to apply the Blockchain-based loan system, the management system of small and medium-sized enterprises also needs to undergo many changes. Whether these changes can actually improve the company’s operating efficiency is still unknown. Perceived risk is a popular factor that has been applied to variety of research fields, such as customer loyalty , disasteH1: Perceived risk negatively affects usage intention of Blockchain-based loan system.Blockchain-based loan system can bring fast and low-cost loans to SMEs, which is the biggest motivation for them to make changes. All small and medium-sized enterprises will conduct serious cost accounting for their investment and the returns they obtain, and strive to obtain the best returns with the lowest cost area. They will be very sensitive to returns, and if they find that companies of similar size and business have obtained loans by upgrading themselves, they will follow suit. The pursuit of rewards will prompt the central enterprise to adopt more sensitive and proactive behaviors to use Blockchain-based loan system, because reward sensitivity is closely related to the high efficiency and better completion of the work to obtain returns , 31 TherH2: Reward sensitivity positively affects usage intention of Blockchain-based loan system.Perceived fairness is the most basic requirement of every industry. However, due to the complexity of financial institutions’ loan data and the difficulty of monitoring the flow of funds, it is difficult to make fair loan decisions based on business information. When various information of SME is uploaded to Blockchain-based system, financial institutions will compare the real capital needs and repayment capabilities of different companies. Commercial bribery, sales volume and cost fraud, which affect fair competition, are eliminated. In fact, because the information of many SMEs is not open and transparent, part of the loans enters the accounts of the company’s shareholders’ affiliated companies and is privately possessed by some major shareholders. In fact, sometimes the senior management of financial institutions is aware of this illegal act, but due to the exchange of benefits, it is rarely known to the outside world. This may lead to regulated business SMEs unable to obtain loans, and a large number of loan resources occupied by enterprises through commercial bribery or drawer agreements. When all relevant corporate information is displayed in the Blockchain-based loan system, managers of financial institutions who are qualified to query information will quickly discover which qualified SMEs have been treated unfairly. They can be rewarded or promoted by reporting suspicious loan behavior. Perceived fairness is so important that it exists in research in all walks of life, such as management decision ; Tax comH3: Perceived fairness positively affects usage intention of Blockchain-based loan system.In plenty of research fields, complexity is always a key factor that affecting the adopting progress, including self-evaluation  and purcH4: Complexity negatively affects usage intention of Blockchain-based loan system.When the complexity increases, SMEs may worry about whether their high-paid staff can transmit operating and financial information to the system on time in accordance with the requirements of financial institutions, thereby increasing their perception of risks. The higher the complexity of routine maintenance and use of the system, the more users feel the increased risk of use, and the less willing to use the system. Therefore:H5: Complexity will negatively moderate the relationship between perceived risk and usage intention.Although the increase in complexity will bring some difficulties, when SMEs work hard to adapt to this complex system, they will look forward to the rewards they will obtain by using the system in the future. This is because the more they pay, the more they expect in return. When some small and medium-sized enterprises overcome the complexity, they may find themselves ahead of their peers in terms of loan efficiency, and obtain more favorable loan interest rates than their peers. Thereby, when users reduce the complexity, they may increase the intention to use the Blockchain-based loan system for more reward. Therefore:H6: Complexity will negatively moderate the relationship between reward sensitivity and usage intention.Accurate and complex operations make information fraud impossible. This is because dynamically updated information will make it easier for falsify data to be tracked and discovered. This is because dynamically updated information will make it easier for some people to falsify data to be tracked and discovered. Overly complex operations will put companies without professional and technical personnel at a disadvantage in the competition, thus feeling that Blockchain technology does not bring fair competition. This prompts those companies that like to pursue fairness to use the system more passively. Therefore:H7: Complexity will negatively moderate the relationship between perceived fairness and usage intention.The proposed model is showed in Questionnaire was designed to take a survey among Blockchain-based loan system users. Most of them are senior executives in finance, management, and operations industries or young heirs to family businesses in SMEs. The participants in the questionnaire are voluntary. They are fully allowed to disclose the contents of the file investigation. Most of them are under 40, have a bachelor degree or above, are willing to accept new things, and have begun to use the system to apply for loans for companies. In order to increase the reliability and validity of the document survey, we first conducted a questionnaire survey with 54 managers. Based on their feedback, we upgraded the old questionnaire and then launched a formal online questionnaire survey in April 2020. A total of 323 questionnaires were received, which is 75.5% response rate. Incomplete and invalid questionnaires were removed, leaving 296 valid questionnaires.Perceived risk has a three items for measurement based on Wu et al. (2011)  study. 1Reward sensitivity has a three items for measurement based on Paola et al., (2015)  study. 1Perceived fairness has a three items for measurement based on Maqsoom et al., (2019)  study. 1Complexity has a three items for measurement based on Lopes et al., (2020)  study. 1Usage intention has a three items for measurement based on Xu et al., (2020)  study. 1All the items are measured by seven-likert scale from 1 strongly disagree to 7 strongly agree. Smart-PLS was applied to this test because Blockchain-based loan system is new and PLS technics has advantages in testing new model , 47. In Tables 2 value reflects the proportion of the total variation of the dependent variable that can be explained by the independent variable through the regression relationship. Overall, usage intention is explained by the four independent variables in a large proportion of variance of 27.8%.To better explain complexity’s moderating effect between perceived fairness and usage intention, plot of two levels of complexity is showed in SMEs have shown great enthusiasm for participating in the questionnaire survey, although different companies face different difficulties, they all gave full support in this questionnaire survey. As a disadvantaged group, SMEs have shown through their enthusiastic participation that they are willing to embrace Blockchain-based loan system. All the items were given relatively high scores; even those that were originally thought to have a negative effect especially reward sensitivity and perceived fairness. To a certain extent, this shows that SMEs are looking forward to new financing channels to obtain operating funds, because the difficulty of SMEs loans has now become a widespread phenomenon restricting their development. Due to the global economic recession brought about by the epidemic and the political and economic closure of many countries around the world, the survival and development of SMEs is not optimistic. As a new financial mechanism, Blockchain-based loans may provide SMEs with opportunities for wealth fairness and they look forward to a fair competition environment based on block-chain technology.Complex theory is a theory widely used in various disciplines, plenty of previous researches have proved the users’ responses based on complexity related indicators contribute to adoption in different research fields –57. ThisComplexity is proved to have a significant negative effect on usage intention, which indicates that although SEMs use the system proficiently and have great stickiness to the system , 65, theThese discoveries represent major advancements in technology and finance. On the one hand, this research has contributed to financial innovation by providing proof of the most influential psychological factors related to small and medium-sized enterprises lending directly through the Blockchain network system. In the past, this was a research field that academic researchers rarely paid attention to. On the other hand, this research represents an important step in the research on how SMEs’ beliefs and attitudes towards Blockchain financial technology affect the decision-making process of their use. With the support of the current comprehensive framework (PPM), our research works by incorporating complexity theory into the model and proving that this Social psychology structure plays an important role as a direct antecedent and moderating variable in the formation of system usage intentions.The results of this study show that the promotion of Blockchain-based loan system has a lot to do with the management strategies of financial institutions. It is very important to understand the psychological factors that can explain the intention of using the system, especially the role of complexity of use in this process. Encouraging SMEs to directly use Blockchain-based loan system instead of providing massive amounts of materials and multiple trips between financial institutions are very helpful to improve work efficiency. In this way, financial institutions will not only be able to fully utilize the commercial potential of Blockchain technology, but also reduce the personnel and management costs associated with the loan process.It is important to emphasize the need to reduce the difficulty of system operation and simplify the types and quantities of materials that need to be provided. In this sense, governments and financial institutions must establish effective and friendly system operation procedures to make SMEs perceive that using this loan system is not risky and as simple, safe, fast and convenient as traditional manual channels. The interactive application of the loan system needs to optimize every detail of the loan and constrain the financial institution . The government and financial institutions should set up special teams and programs to train SMEs who are passionate about this system to encourage fair competition for loans.In line with PPM theory, in order to better pull users back instead of pushing them out, financial institutions should also: 1) Improve free education on the use of information systems; 2) Reward those who are proficient and correctly using the system Enterprises, thus making this system the main way for SME loans. 3) In the first few years, if the company caused application errors due to unskilled operations, financial institutions should give understanding and try not to hold the company accountable.The loan system based on Blockchain technology is a breakthrough achievement because it greatly shortens the negotiation time from a few weeks to a few days or hours. The government provides supporting services such as credit enhancement, interest discount, and risk compensation for small and medium enterprises using this system. By Blockchain technology, the government, enterprises and financial institutions have established mechanisms for information sharing, privacy protection and mutual trust, which not only makes corporate information true and unchangeable, but also enables financial institutions to query corporate information in accordance with laws and regulations. This can play a role in solving the financing pain points of three types of SMEs: manufacturing, foreign trade and science and technology innovation. Traditional financial institutions will carry out investment work according to their own less transparent standards, but in the future, Blockchain technology can make everyone a lender. Anyone can use their own standards to carry out small loans and track the flow of funds they have borrowed in real time. One of the main advantages of a Blockchain-based loan system is that it provides the possibility of obtaining funds from various investors and reduces the reliance on traditional financial institution processes. The system also provides opportunities for SMEs not limited to local financial institutions. They can share information with financial institutions or individuals around the world, thereby providing investors with equal opportunities for competition.Despite the contributions of this study, this research has some limitations. First, since the investigation is conducted in China, the administrator of the system, it could be interesting to apply this model in different countries especially in those developed countries to test the model’s consistency. Second, when the borrowers are SMEs, this model is proved to be applicable. Future research should also examine the consistency of the model when the individual acts as a borrower. Finally, most of the participants in this study are traditional companies, and their financial and business information is relatively complete. Future research should join those startups that have just been established with professional technology and patents as their main assets.S1 Appendix(DOCX)Click here for additional data file.S1 Data(CSV)Click here for additional data file.


In individuals having low back pain, the application of spinal manipulative therapy (SMT) has been shown to reduce spinal stiffness in those who report improvements in post-SMT disability. The underlying mechanism for this rapid change in stiffness is not understood presently. As clinicians and patients may benefit from a better understanding of this mechanism in terms of optimizing care delivery, the objective of this scoping review of current literature was to identify if potential mechanisms that explain this clinical response have been previously described or could be elucidated from existing data.Three literature databases were systematically searched . Our search terms included subject headings and keywords relevant to SMT, spinal stiffness, lumbar spine, and mechanism. Inclusion criteria for candidate studies were publication in English, quantification of lumbar spinal stiffness before and after SMT, and publication between January 2000 and June 2019.The search identified 1931 articles. Of these studies, 10 were included following the application of the inclusion criteria. From these articles, 7 themes were identified with respect to potential mechanisms described or derived from data: 1) change in muscle activity; 2) increase in mobility; 3) decrease in pain; 4) increase in pressure pain threshold; 5) change in spinal tissue behavior; 6) change in the central nervous system or reflex pathways; and 7) correction of a vertebral dysfunction.This scoping review identified 7 themes put forward by authors to explain changes in spinal stiffness following SMT. Unfortunately, none of the studies provided data which would support the promotion of one theme over another. As a result, this review suggests a need to develop a theoretical framework to explain rapid biomechanical changes following SMT to guide and prioritize future investigations in this important clinical area. Low back pain (LBP) is the leading musculoskeletal cause of disability globally, while its financial burden continues to grow with an aging population , 2 . OneSpinal manipulative therapy (SMT) is a common mechanical conservative intervention for LBP that is recommended by several clinical practice guidelines and review papers –8. RecenTaken together, these studies provide a unique investigative opportunity. Given that most interventions for LBP require weeks or months to exert their effect   and few,While the above development is unique in LBP research, it exists independently from an existing theoretical framework that would explain how the effects of SMT influence spinal stiffness and, ultimately, LBP in some, but not in other affected individuals. A theoretical framework is helpful for providing directions and priorities for future studies that would delineate the working mechanics of this phenomenon , 14. ThiWith this in mind, we conducted a scoping review with the objective of identifying existing literature that would offer mechanistic explanations for a change in spinal stiffness of individuals with LBP who report improvements in disability following spinal manipulation. The results from this review could then be used to develop a theoretical framework to guide future investigations in this area.A scoping review is a form of review scholarship based on a framework for synthesizing available published literature on a given topic , 16. A sAn established scoping review methodology was used to collect and organize relevant information to examine the existing body of literature . The revThe review process followed the recent guideline of PRISMA  and, particularly, the extension for Scoping Reviews (PRISMA-ScR) . The peeEligibility criteria included: 1) publication in English; 2) quantification of lumbar spinal stiffness before and after an SMT; and 3) publication between January 1st, 2000 and June 10th, 2019 . Exclusion criteria included: 1) not using SMT as an intervention; and 2) only measuring cervical spinal stiffness. A pair of independent reviewers (PJ and IP) screened the search results in two rounds. All studies were first screened using titles and abstracts to identify relevant, possibly relevant, and irrelevant citations. Secondly, relevant and possibly relevant studies were screened in full text to determine eligibility against the above inclusion criteria. A third reviewer (GK) was involved to resolve disagreements.From the selected studies, data were extracted by 2 reviewers (PJ and IP), and any discrepancies were resolved after discussion. Extracted data from each included study contained: 1) first author and year of publication; 2) study design; 3) sample size and characteristics; 4) interventions; 5) spinal stiffness measurement and other variables/outcomes; and 6) main results.Sentences that explained or speculated about the mechanism of SMT were manually extracted from the selected studies. Candidate sentences included wording such as “may be due / related / associated / explained / modified”, “is believed”, “was hypothesized”, “may permit / allow / result / modify / increase / decrease/ facilitate / inhibit / explained” or “have been reported / shown to”. If a sentence did not contain one of these phrases, but implied a potential mechanism underlying the effect of SMT, the sentence was also extracted. The extracted sentences were classified as either 1) a hypothesis or a re-statement from another study; or 2) a suggestion based on data from the study.The extracted sentences were then pooled and categorized into mechanistic themes based on the context of the sentence. The sentences were analyzed within another full-text review in order to convey the original authors’ intentions; then they were grouped together with respect to anatomical references  or measurements . From these groupings, themes were created by 2 reviewers (PJ and IP) after discussion.Our literature search identified 1929 studies. Two studies were manually added based on additional data sources (reviewer’s knowledge of the literature and reference list of an included study). After removing the duplicates and two rounds of screening, 10 studies met the inclusion criteria and were then processed for sentence extraction  themes that may explain this response directly; and 2) themes that are best described as secondary in that they most likely arise from direct mechanisms. To make this distinction, we assume that the force imparted by SMT is experienced by a number of spinal tissues directly. These would include bone, muscle, ligament, nerve, and others. As such, the themes that describe the immediate involvement of these tissues would be considered to be primary themes.For the primary themes, we will limit our discussion to the possibility that the force imparted by SMT has a direct effect on the tissue of interest, resulting in a change in stiffness with no other systems involved.For this theme, we assume that the application of a direct force to the muscle will cause a change in the muscle that may impact post-SMT stiffness. Certainly, the application of direct force to a muscle can directly cause viscoelastic changes in the muscle that may result in stiffness alteration. The rapid application of force in SMT, however, would suggest a smaller viscoelastic effect than if the force were applied slowly . When a Similar to muscle, applying a force on bones, ligaments, tendons, and joint capsules, etc. may directly result in a change in segmental stiffness due to the viscoelastic phenomenon. However, the contribution of each of these spinal tissues to the change in spinal stiffness will differ as the load experienced by each tissue is different during SMT . While aIt is unlikely that applying a force directly on the nerve would cause a direct change in spinal stiffness, although nerves can certainly experience such force directly. Nerve compression, direct pressure on a nerve, may cause pain, numbness, or muscle weakness, which may affect spinal stiffness; however, it would be unlikely that forces during SMT would achieve a magnitude that would cause this to happen and would most likely affect other tissues directly before the nerve would be impacted in this way.While it may be possible that the SMT force applied to the muscle can impact spinal stiffness directly, it is also possible that the nerve structures within the muscle are triggered by the deformation experienced by the muscle itself, which then initiate other downstream mechanisms. Deformation of muscle could activate paraspinal sensory neurons via stimulating muscle spindles , 33, whiAn increase in mobility can only happen as a result of some change within the system occurring first. As such, this will be discounted as a primary theme. Put another way, whatever tissues are being affected, they subsequently allow a change in mobility or at least a theoretical change in mobility. Moreover, a change in spinal stiffness does not necessarily imply an increase in spinal mobility. Indeed, spinal stiffness represents the stiffness of underlying tissues throughout the application of load or, in other words, the tissue dynamics in response to the application of load , 35. It A decrease in pain intensity and an increase in pressure pain threshold have been reported separately in two themes, but one could consider these potential mechanisms together. Although the work by Wong et al. 2016) shows how experimental pain (increased pain intensity) changes stiffness , it is u16 shows None of the selected studies specifically mentioned the potential secondary effect of change in spinal tissues for stiffness change. However, evidence exists that the mechanical stress, such as caused by SMT, could stimulate or hinder non-nociceptive, mechanosensitive receptive nerves in spinal tissues, including skin, tendons, ligaments, facet joints, and intervertebral disc –44, whicNerves can be stimulated by the deformation of the tissue in which they reside, which then begins a cascade of other events . AlthougFinally, one study stated that “back stiffness is one of the primary clinical indicators of vertebral dysfunction” implying that SMT “corrects” the vertebral dysfunction in the presence of spinal stiffness change . Since tA limited number of included studies indicate the lack of evidence on this topic. Moreover, none of the studies used a method justifying a cause-and-effect relation between SMT and lumbar spinal stiffness change that would promote one theme over another. These results suggest the need to create a working model for these changes, which can guide and prioritize future investigations. Future studies should focus on verifying the identified potential mechanisms; the priority may be on the mechanisms associated with changes in muscle activity and spinal tissue behavior, as they were the primary mechanistic themes that could affect spinal stiffness directly. There also needs to be more effort taken to understand how other measures of spinal function (e.g. EMG) could be helpful in understanding post-SMT changes. Understanding the mechanism(s) for lumbar spinal stiffness changes following SMT could provide valuable knowledge on understanding the LBP source and how it may be targeted with specific therapeutic interventions in the future.The main limitations of this scoping review are the small number of included studies and their heterogeneity. First, the interventions varied between studies, which might have influenced the effect on spinal stiffness and the other outcomes. For instance, spinal manipulation and mobilization have been shown to generate different physiological responses , and migThis scoping review identified 7 themes of potential mechanisms for the change in lumbar spinal stiffness following SMT: change in muscle activity, increase in mobility, decrease in pain, change in pressure pain threshold, change in spinal tissue behavior, change in the central nervous system or reflex pathways, and correction of vertebral dysfunction. Our review suggests the need to systematically investigate these proposed mechanisms as the selected studies did not provide supporting data to verify the cause-and-effect relations, and to develop a theoretical framework for future research. Our review also provides insights on which suggested mechanisms may have research priorities in order to understand the change in spinal stiffness following SMT.Additional file 1. List of the search terms and its subject headings.


Shear wave elastography with ultrasound is a noninvasive method used for measuring stiffness in the human body. Shear wave elastography can be used for accurately and quantitatively measuring stiffness. However, its disadvantage is that the stiffness value can vary significantly because the region of interest (ROI) setting depends on the diagnostic operator. In this study, a stiffness measurement program using color mapping in shear wave elastography was developed to address the above-mentioned disadvantage. Color map and color ratios were obtained and evaluated for major lower limb muscles  at active voluntary contraction. According to the result, when the developed program was used, a small standard deviation compared to the conventional stiffness measurement method, such as kilopascal or meter per second unit using ROIs, was measured in all cases. In conclusion, our results demonstrate that the stiffness measurement method using our program is expected to improve reliability in shear wave elastography ultrasound imaging. Computed tomography (CT) based on an X-ray source and magnetic resonance imaging (MRI) using radiofrequency pulses are widely used in the field of diagnostic imaging ,2. HowevPalpation is one of the most widely used methods for evaluating diagnostic research. It involves a physical examination of the body to assess tissue stiffness, such as for muscles, tendons, lymph nodes, breast mass, and liver fibrosis ,14. HoweTo perform quantitative evaluation from shear wave elastography images including muscle or tendon images, region of interest (ROI) setting is essential. However, the quantitative evaluation value with respect to the ROI settings vary significantly depending on the ultrasound operator. Thus, to develop a software program that can extract the overall color ratio of an image, a relatively high objectivity result can be obtained for shear wave elastography. In this study, we developed a program to measure stiffness using color mapping in shear wave elastography as well as to evaluate the color ratio based on the stiffness of major lower limb muscles.Ultrasound images and shear wave elastography images were captured using an Acuson S-3000 ultrasound device  with a linear probe at a high frequency (9.4 MHz). The linear probe consisted of a high-density element array with a fine pitch using 576 number of elements and was positioned in the middle region of each muscle, parallel to the fascia plane. The stiffness measurements were performed by a clinical sonographer with more than 8 years of experience in diagnostic radiology.The study procedure was approved by the Gachon University Institutional Review Board. All participants signed an informed consent prior to participating in this study. The researcher marked measuring points on each muscle with measuring tape from the anatomical landmarks. Muscle stiffness was measured in at active voluntary contraction. All participants were instructed on how to contract their muscles before measurement. Four muscles of lower limbs were used for the stiffness measurements using shear wave elastography: biceps femoris (BF), medial gastrocnemius (MG), rectus femoris (RF), and tibialis anterior (TA). The positions of muscles contraction were explained in a previous study . Ultrasound images and shear wave elastography images were captured using an Acuson S-3000 ultrasound device with a linear probe at a high frequency (9.4 MHz). The linear probe consisted of a high-density element array with a fine pitch using 576 number of elements and was positioned in the middle region of each muscle, parallel to the fascia plane. The stiffness measurements were performed by a clinical sonographer with more than 8 years of experience in diagnostic radiology.The manufacturers of the ultrasound device provided a quality factor (Q-factor) for the stiffness measurements . This fax,y, which is composed of T ; We proposed an area distribution that represents the relative superiority of red, green, and blue images, and then calculated each color ratio, which can be expressed as:T (②). Finally, the color ratio value is obtained and an accurate stiffness measurement (③) is performed.Based on the above descriptions, we implemented the proposed algorithm using the MATLAB™ v8.3 programming language. To process this software in the proposed program language, we performed the following the data process: First, we acquired the elastography data in DICOM format and then it is interlocked with MATLAB software to acquire 3-dimensional data ) without DICOM header information. Finally, each color result was derived by applying the proposed algorithm in the image domain.Shear wave elastography allows the quantitative evaluation of tissue stiffness in units of kPa or m/s using the ROI and perform a musculoskeletal pain examination. In general, the ROI setting in the shear wave elastography image sets the number of target muscle or tendon areas, and then derives an average quantitative value. However, this elastography has not been used practically because the measured stiffness is different for each operator. Thus, the purpose of this study was to develop a more quantitative and objective stiffness measurement program using color mapping in shear wave elastography.Based on the color extracted images, we evaluated the quantitative data for each color ratio with the major lower limb muscles .According to the quantitative results, the red color ratio was a mean of 0.028 (approximately 2.8%) ± 0.0023 (standard deviation), 0.139 ± 0.0128, 0.018 ± 0.0015, and 0.347 ± 0.0161 for the contracted BF, MG, RF, and TA, respectively. The evaluated red color ratio increased in ascending order of RF, BF, MG, and TA. In addition, the blue color ratio had a mean of 0.423 ± 0.0265 (standard deviation), 0.552 ± 0.0368, 0.583 ± 0.0105, and 0.002 ± 0.0001 for the contracted BF, MG, RF, and TA, respectively. The evaluated blue color ratio increased in ascending order of TA, BF, MG, and RF. A comparison of the quantitative evaluation and visual assessment confirmed that the same tendency was observed. However, the green extraction results showed no tendency for tissue stiffness. The evaluated green color ratio increased in the order of MG, RF, BF, and TA.The purpose of developing the stiffness measurement program using color mapping was to overcome the disadvantages of the conventional evaluating method using ROIs. As previously mentioned, the conventional method is not used practically and has a major drawback in that the deviation of the result becomes large because the ROI setting depends on the operator. The ratios of the differences between the mean and the standard deviations were 15.65% and 15.63% for kPa and m/s, respectively, with the conventional evaluation method. In addition, the ratios of the differences between the mean and the standard deviations were 6.97%, 5.18%, and 5.20% in the red, green, and blue maps, respectively, with our developed program. Based on the results, we confirmed that the reliability of our developed program is better than that of the conventional method for evaluating stiffness using shear wave elastography.In this study, we developed a color mapping program to obtain a more accurate stiffness value than the conventional method in shear wave elastography. However, the limitation of this study was the stiffness range setting for shear wave elastography in major muscle scans. Kunwar et al. suggested an elastography scoring system for cervical lymph nodes and breast lesions . In thatWe objectively evaluated the stiffness of major lower limb muscles using a color mapping software program with shear wave elastography imaging. Our results demonstrated that our developed program can improve the reliability and accuracy of quantitative evaluation of stiffness in shear wave elastography. Based on the results of this study, it is expected to be applicable to accurate measurement of stiffness of various muscles and tendons as well as major lower limb muscles.


Indirect reciprocity is one of the major mechanisms in the evolution of human cooperation. In indirect reciprocity, social norms with which individuals distinguish good people from bad people play essential roles. Despite extensive studies on the evolution of cooperation in indirect reciprocity, little is known about which social norms people actually adopt. Here we reveal what kind of norms are adopted by people in indirect reciprocal situations in daily life by using scenario-based experiments. The results showed that people evaluated “justified defection” as neither good nor bad and withheld their evaluation. Theoretically, social norms that evaluate justified defection as good are required for cooperation to be stable. However, the norm that people actually adopted deviates from the theoretical predictions. Our results indicate the necessity to reconsider the justification of “justified defection” in the evolution of cooperation. Mutual cooperation in a competitive situation has been an essential driver in the development of human society, but its mechanism is a difficult puzzle to solve. Especially, indirect reciprocity –8 is a sThe simplest norm of indirect reciprocity is image-scoring ,4, whichIn particular, defection against a bad recipient  is a key factor in establishing cooperation ,12,14–16Despite numerous experiments on indirect reciprocity –24 havinAs mentioned above, there is a deviation between predictions from theories and experimental results about the assessment rule for the actions against bad recipients. In particular, the distributions of assessment rules toward bad recipients in humans are unknown. By analyzing how second-order information, which is theoretically required to sustain cooperation, is used by humans in evaluating others, the function of the omission of punishment and the justified defection in human society will be revealed.Here, we design experiments to clarify the distribution of people’s assessment rules in indirect reciprocity. In the scenario-based experiments, two people appeared in the scenario. One was a donor who does or does not cooperate with his/her recipient. The other was the recipient who asks the donor for help. Participants were asked to rate the donor as good or bad by observing when the donor chose to cooperate or not with the recipient. The recipient is labeled either good or bad. Participants evaluate four scenes in the combination of donor behaviors and recipient labels. Since the purpose of this study is to investigate which norms people adopt in real society, we adopted scenario-based experiments rather than an economic experiment.Most theoretical studies have adopted an assumption in which a single norm pervades throughout a population resulting in all individuals using the same norm. However this assumption clearly oversimplifies the reality. In recent years, researchers have tackled this assumption by developing a model in which various norms coexist in the population ,31. HoweWe designed three scenario-based experiments to explore how humans evaluate the donor’s action using the first and second-order information in indirect reciprocity. Participants were recruited through a Japanese crowdsourcing service (Yahoo! Crowdsourcing). To broaden the generalizability of findings, each experiment had completely different participants. All experiments were approved by the ethics committee of Rissho University, application number 29–3 and 30–15. Informed consent was obtained from all subjects.We recruited 200 participants ). Participants evaluated a donor’s behavior using first- and second-order information. First-order information is the donor’s behavior (cooperation/defection), and second-order information is recipient reputation (good/bad). Combining both types of information, participants rated four scenes: cooperation with the good recipient (CtoG), defection against the good recipient (DtoG), cooperation with the bad recipient (CtoB), and defection against the bad recipient (DtoB) .Participants first evaluated the scenes in order of CtoG and DtoG. To eliminate order effects on the cases of a bad recipient, the order of CtoB and DtoB was randomized among participants. The specific scenarios are as follows. In the first scenario, the participants were assumed to be workers in a restaurant. Assume that a colleague, Alice (recipient), asks another colleague, Bob (Donor), to take over the night shift, and Bob agrees (cooperation) or refuses (defection). We also controlled Alice’s reputation. The cases in which Alice has a good reputation are as follows.Alice works hard and is always willing to take over when others cannot come to do the night shift. That is why Alice is liked very much by colleagues in the restaurant including you.The cases in which Alice has a bad reputation are as follows.Alice is not serious about her work and often takes time off from the night shift for various reasons. She often takes time off for selfish reasons and is not liked by her colleagues including you.In the actual experiment, Alice and Bob’s names were converted into common Japanese names. After reading the scenario, participants rated how they assessed Bob’s behavior from three viewpoints using a 5-point scale: “Bob is a reliable person”, “Do you like Bob?”, and “Do you feel sympathetic to Bob?” The evaluation scores for the donor’s action were obtained by simply adding together the scores of these three statements See  Tables.Experiment 2 was conducted using different scenarios in order to generalize the results by eliminating the dependence on a specific scenario. We recruited 200 participants ). The basic settings are the same as for Experiment 1. The differences from Experiment 1 are as follows. The donor and recipient were changed from restaurant workers to neighborhood residents, and the recipient (Alice) asks the donor (Bob) for personal advice about distress. The cases in which Alice's has a good reputation are as follows.Alice is always willing to respond to other people's requests and give them advice in a friendly manner. For this reason, Alice is well-liked by her acquaintances, including you.The cases in which Alice has a bad reputation are as follows.Alice has a habit of talking negatively about other people behind their backs. Also, she always thinks that she is right and sometimes forces her opinions on others, so her acquaintances, including you, feel that Alice is somewhat unpleasant.We set up the scene of a giving game to examine not only the evaluation of behaviors in daily life but also behavior in an economic experiment. We recruited 200 participants ). Participants were given an explanation of the rules of a giving game, in which a donor and a recipient were randomly matched in an iterated game, and then asked to rate the behavior of the donor. Participants rated donor behavior (donate / not donate) in the giving game the same as in Experiments 1 and 2. Recipient reputation was controlled by how many times he/she chose to donate during his/her past five rounds as a donor (5 (good), 0 (bad)). To show the participants that it was an economic game in an anonymous situation, we described the donor and the recipient as Player A and Player B. The cases in which the recipient (Player B) has a good reputation are as follows.Player A is now the "donor" and Player B is now the "recipient". Player B selected "donate" all five times when he/she was previously the donor.The cases in which Player B has a bad reputation are as follows.Player A is now the "donor" and Player B is now the "recipient". Player B selected "not donate" all five times when he/she was previously the donor.We first analyze distributions of donor ratings in each scenario. The curves in all diagrams in To analyze these differences in distributions statistically, we employed quantile regression . The ordIn this study, each quantile of evaluation scores was estimated for three experiments separately. To compare CtoB and other conditions, we used the CtoG dummy, DtoG dummy, and DtoB dummy as independent variables.For indirect reciprocity to work, people need to have norms that distinguish the good and bad of others’ behavior and cooperate only with good people. Extensive theoretical and empirical studies have looked for suitable norms for the evolution of cooperation, but there is no clear answer for the norms people adopt in our society. From a theoretical prediction, to stabilize cooperation through indirect reciprocity, a norm is needed that prescribes regarding as good those who do not cooperate with a bad person (justified defection) ,12,14–16Our results reveal that people do not evaluate the defection with a bad recipient as either good or bad and withheld their evaluation. This means that justified defection is neither justified nor unjustified. We also found, as expected, that cooperation was mostly considered good and defection with good recipients was considered bad.As a result, the norms adopted by people can be summarized as shown in In a theoretical model of indirect reciprocity, a player’s reputation depends on his/her behavior, the reputation of his/her recipients, and the norms of observers. Therefore, the good and bad evaluations of the recipients may not be directly associated with cooperation and defection. To unify the reputations of the recipients among all participants in our experiments, they were designated as perfect cooperators or perfect defectors. In the future study, it will be necessary to consider the higher-order information, i.e. reputation of the donor or reputation of the previous recipient of the present recipient . This maThis paper is a first step to reveal a neutral reputation as an evaluation of justified defection. Many extensions are needed to understand the mechanism of this phenomenon. To explore the reason for the neutral evaluation of the defection against bad recipients, it is necessary to analyze whether the neutrality in evaluation is “don’t know” or “withhold evaluation.” People acquire an understanding of indirect reciprocity in childhood , so anotS1 FigRestaurant worker scenario.(DOCX)Click here for additional data file.S2 FigPersonal advice scenario.(DOCX)Click here for additional data file.S3 FigEconomic game scenario.(DOCX)Click here for additional data file.S1 TableRestaurant worker scenario.(DOCX)Click here for additional data file.S2 TablePersonal advice scenario.(DOCX)Click here for additional data file.S3 TableEconomic game scenario.(DOCX)Click here for additional data file.S1 Text(DOCX)Click here for additional data file.


Background.Zirconia restorations with high mechanical properties are the current treatment options for fixed restorationswith advantages of high biocompatibility and low pulp irritation. Although the effect of sintering time and temperature on theoptical and mechanical properties of zirconia core material were investigated, the effect of these parameters on the translucentmonolithic zirconia is still uncertain. This study aimed to evaluate the effect of the changes in sintering temperature andholding time on the mechanical and structural properties of monolithic zirconia.Methods. Totally, 340 self-colored (A2) zirconia specimens from two different monolithic zirconia groups (n=170) wereprepared, measuring 15.5×12.5×1.2 mm. Then, 17 subgroups (n=10), including the control groups, were sintered accordingto sintering parameters. XRD analysis was used to determine phase transformations. The surface roughness of the specimenswas evaluated using profilometry, and the flexural strength of the specimens was evaluated by the three-point bending test.The data were analyzed using three-way ANOVA and post hoc multiple comparison test with Bonferroni correction (a=0.05)at a significance level of 0.05. Independent-samples t-test was used to compare the subgroups between the control groups(P˂0.05).Results. No tetragonal-to-monoclinic phase transformation was observed in the groups. Changes in the sintering parametersdid not significantly affect the surface roughness and flexural strength of monolithic zirconia. Surface roughness values forall the subgroups were above the clinically critical limit.Conclusion. According to the results of this study, changes in the sintering parameters did not affect the surface phasetransformation, surface roughness, and flexural strength of monolithic zirconia. Pure zirconia occurs in monoclinic phase at room temperature, becomes tetragonal between 1170ºC and 2370ºC, and the cubic phase is stable up to the melting point of 2680ºC.2 The yttrium-stabilized tetragonal zirconia polycrystalline (Y-TZP), the most commonly used zirconia in dentistry and stable with yttrium in nanometers at room temperature, could be obtained by alloying zirconia with 2‒3% of yttrium oxide.4Concurrent with the development of CAD/CAM technology, zirconia has been widely used in the dental field due to its excellent mechanical properties, high biocompatibility, and low allergic potential.7 Stawarzcyk et al7 reported that an increase in the sintering temperature resulted in a decrease in the flexural strength of zirconia. In contrast, some studies reported that sintering parameters did not affect the flexural strength of zirconia ceramics.9In previous studies, the flexural strength of zirconia ceramics varied between 608 and 1540 MPa, and these differences occur depending on sintering parameters, surface treatments, and microstructure.11 Heintze et al12 reported that rough surfaces reduce the fracture resistance of the material, and changes in surface roughness affect the wear properties of zirconia. In clinical applications, the grinding procedures made by the dentist also directly affect the wear properties of zirconia. Additionally, it has been reported that changes in surface roughness also stimulate phase transformation.13 Preis et al14 reported that the polishing process reduces surface roughness and phase transformations on the zirconia surface. Currently available zirconia materials are generally sintered between 1350ºC and 1600ºC, and yttrium is incorporated into the structure at high sintering temperatures.15 However, sintering temperatures higher than 1600ºC cause excessive grain growth and increase porosity. Besides, it was observed that the mechanical and optical properties of the zirconia were not sufficient at sintering temperatures of <1400ºC.7 The degradation of zirconia at low temperatures and the strength of the material depend on many factors, including the amount of the stabilizing oxide, the distribution of the stabilizer, the phase composition, the particle size and distribution, etching and surface treatments, and the presence of the secondary phases. Although these factors are independent, they are mainly affected by sintering parameters, which have been considered as predominant factors to obtain stable zirconia.16According to the literature, the critical smoothness for plaque accumulation is 0.2 μm.16 Additionally, as a result of high flexibility and fracture strength, monolithic zirconia can be used even in cases where the interocclusal distance is insufficient in the posterior region.7Zirconia is used as an infrastructure due to its high opacity, and the main disadvantage of zirconia restorations is chipping in veneering ceramics. To overcome the chipping problem, the use of monolithic zirconia restorations, which can be used without veneering ceramics, has gained popularity. In addition, with monolithic zirconia blocks, it is possible to obtain more translucent and aesthetic restorations without veneering ceramics.17 However, the effect of sintering parameters on monolithic zirconia, directly related to oral conditions, is still uncertain.18 Therefore, this study investigated the effect of sintering parameters on the microstructure, surface roughness, and flexural strength of monolithic zirconia materials. The null hypothesis of the study was that sintering parameters do not affect the microstructure, surface roughness, and flexural strength of the translucent monolithic zirconia.Changes in sintering parameters affect the properties and microstructure of zirconia.In this in vitro study, two different commercially available pre-sintered, self-colored (A2) translucent monolithic zirconia materials   were used. Totally, 340 samples (n=170) with a dimension of 19×15.5×1.6±0.05 mm were prepared from pre-sintered blocks using a precision cutting machine . All the samples in each group were randomly divided into 16 subgroups according to sintering temperature  and holding time  for each group (n=10). Additionally, one subgroup, sintered according to the manufacturer’s instructions, was defined as the control group (n=10) . The heaThe effect of sintering temperature and holding time on the phase composition and t-m transformation were crystallographically examined using a diffractometer  on three randomly selected samples from each group. All the samples were subjected to Cu K radiation. The voltage and current were set to 40 kVp and 40 mA, respectively. Diffraction profiles were recorded within a range of -10 to 90º, a continuous θ/2θ scan with a step size of 0.05º, and a scan speed of 4.0 deg/min.The surface roughness (Ra) of the groups was evaluated by using a contact profilometer . Ra values of each specimen were obtained by three measurements on the three different axes passing through the center of the specimens, and mean Ra values were calculated. Measurement parameters were set to nOc: × 5; Oc/L: 0.8; range: 20×5. The profilometer was calibrated before each measurement.A three-point bending test was performed to determine the flexural strength of the groups using a universal testing machine  at a crosshead speed of 1 mm/min. The support distance was set to 8.5 mm, and the loading rod was 2 mm in diameter. The flexural strength was calculated according to the following formula:2σ = 3Nl/2bd2], l = the distance between the supports [8.5 mm], b = width of the specimen [12.5 mm], d = thickness of the specimen [1.2 mm]).. Shapiro-Wilks test was used to determine whether the surface roughness and flexural strength data showed normal distribution. Homogeneity of the data was analyzed with Levene's test at the 0.05 significance level. The data were evaluated using three-way ANOVA and post hoc multiple comparison test with Bonferroni correction (a=0.05) at a significance level of 0.05. Independent-samples t-test was used to compare the subgroups between the control groups (P˂0.05).XRD analysis revealed no monoclinic (m) phase on the surface of the analyzed specimens within groups. Only tetragonal (t) characteristic peaks were determined on the surface of the specimens.According to the statistical analysis conducted, material, holding time, sintering temperature, and interaction between these factors were not significant for the surface roughness and flexural strength values  and 3. SAccording to the results of the study, the sintering temperature and holding time did not affect the microstructure, surface roughness, and flexural strength of the groups. Therefore, the null hypothesis of the study that sintering parameters do not affect the microstructure, surface roughness, and flexural strength of the translucent monolithic zirconia was accepted.21 These devices that provide surface-independent, high-resolution surface profile information, are scientifically accepted.20 Besides, contact profilometers have advantages of repeatability, applicability, and reliability. Therefore, the surface roughness of the specimens was measured using a contact profilometer. Changes in the surface roughness of materials affect the wear properties of zirconia restorations. This study showed that sintering conditions have no significant effect on the surface roughness of zirconia specimens. Consistent with the present study, Ebeid et al9 reported that the mean surface roughness value of zirconia decreased with an increase in sintering temperature and holding time, but these changes were not significant. Preis et al14 reported no significant difference in surface roughness between the zirconia specimens sintered with different sintering parameters, but the surface roughness of the specimens significantly decreased after glazing and polishing processes; therefore, phase transformation decreased on the surface of zirconia specimens. Surface roughness is associated with bacterial accumulation, and more bacterial involvement occurs on rough surfaces.22 Bollen et al22 reported that the roughness of tooth surface or any restoration should be <0.2 μm, and this value could be considered as a threshold value for bacterial involvement. The results of this study revealed that the surface roughness values for all the groups were >0.3 μm. These results show that polishing and glazing processes should be performed carefully for zirconia restorations after the sintering process or intraoral adjustment. Phase transformations on the zirconia surface negatively affect the mechanical properties of the material. Mechanical properties of zirconia and stability of the tetragonal phase depend on particle size and the metastable microstructure. In this study, sintering temperature and holding time did not affect the phase transformation on the surface of zirconia specimens. Consistent with the present study, Ebeid et al9 reported that changing the holding time and sintering temperature did not induce phase transformation on the monolithic zirconia surface. Hjerppe et al8 reported no phase transformation in the structure of the partially stabilized zirconia material with a decrease in sintering time. Contrary to the present study, Inokoshi et al23 investigated the effect of changes in sintering parameters on phase transformation in three different commercial zirconia materials and reported that the cubic phase increased in surface structure due to an increase in sintering temperature and holding time. The authors also reported that as a result of unstable zirconia microstructure, the monoclinic phase was determined at the highest sintering temperature, and changes in sintering parameters caused phase transformation. Differences between the present study and the study conducted by Inokoshi et al23 could be attributed to higher sintering temperatures used in the previous study.Contact profilometers are widely used in the dental field.4 According to the results of this study, sintering temperature and holding time did not significantly affect the flexural strength of zirconia specimens. Consistent with the present study, Hjerppe et al8 reported that changes in sintering parameters and the thermal aging process did not affect the flexural strength of zirconia. Ebeid et al9 concluded that sintering parameters did not significantly affect the flexural strength of the translucent monolithic zirconia material. Contrary to the results of this study, Inokoshi et al23 reported that changing the sintering parameters affected the mechanical properties of the zirconia material. Trunec24 reported that the fracture strength of zirconia depends on the particle size that varies due to changes in sintering parameters. Stawarczyk et al7 concluded that the flexural strength of zirconia decreased with an increase in sintering temperature, and the highest strength could be obtained between 1400ºC and 1550ºC, and the lowest strength at low temperatures. These differences from other studies could be related to the structure of the material used, sintering parameters, and phase transformation of the material’s structure. In this study, the sintering parameters were determined at a certain sintering temperature and holding time intervals in accordance with the literature25 and manufacturer recommendations. Thus, further studies are needed to examine the effect of the sintering process at higher or lower temperatures and in shorter or longer holding times on the properties of zirconia. In addition, the effect of other sintering parameters such as heating rate and sintering atmosphere on the properties of the zirconia should be investigated.Zirconia is the most durable ceramic material used in dentistry due to its high flexural strength.Within the limitations of our study, it was concluded that sintering parameters did not significantly affect the microstructure of translucent monolithic zirconia. Changes in the sintering parameters did not significantly affect the surface roughness of the translucent monolithic zirconia. For all the groups, the surface roughness was above the clinically acceptable values. Changes in sintering parameters did not significantly affect the flexural strength of the translucent monolithic zirconia.CÖ and GC were responsible for the concept and the design of the study. CÖ performed the experimental design of study, data collection and statistical analysis. CÖ and GC were responsible for drafting the manuscript, critical revision of the article and final approval of the version to be published. All the authors participated in the literature review.None.This study was not supported financially by any individual or organization.The authors declare no competing interests with regards to the authorship and/or publication of this article.Not applicable.


Heteractis crispa, Hcr 1b-3 and Hcr 1b-4, demonstrate different effects on rASIC1a and rASIC3 currents. While Hcr 1b-3 inhibits both investigated ASIC subtypes with IC50 4.95 ± 0.19 μM for rASIC1a and 17 ± 5.8 μM for rASIC3, Hcr 1b-4 has been found to be the first potentiator of ASIC3, simultaneously inhibiting rASIC1a at similar concentrations: EC50 1.53 ± 0.07 μM and IC50 1.25 ± 0.04 μM. The closest homologs, APETx2, Hcr 1b-1, and Hcr 1b-2, previously demonstrated the ability to inhibit hASIC3 with IC50 63 nM, 5.5, and 15.9 μM, respectively, while Hcr 1b-2 also inhibited rASIC1a with IC50 4.8 ± 0.3 μM. Computer modeling allowed us to describe the peculiarities of Hcr 1b-2 and Hcr 1b-4 interfaces with the rASIC1a channel and the stabilization of the expanded acidic pocket resulting from peptides binding which traps the rASIC1a channel in the closed state.Currently, five peptide modulators of acid-sensing ion channels (ASICs) attributed to structural class 1b of sea anemone toxins have been described. The APETx2 toxin is the first and most potent ASIC3 inhibitor, so its homologs from sea anemones are known as the APETx-like peptides. We have discovered that two APETx-like peptides from the sea anemone  In the aromatic region (240–320 nm) of CD spectrum results were expressed as molar ellipticity . The secondary structure contents were determined according to the method of Provencher and Glöckner, using their CONTIN program  program .Xenopus laevis oocytes after injection of 2.5–10 ng of cRNA, as previously described /IC50) nH)) + A; where y is the relative value of current inhibition; C is the peptide concentration; IC50 is the half maximal inhibitory concentration; nH is the Hill coefficient; A is the response value at maximal inhibition (% of control). Calculations were carried out using software Origin 7.0. The data are presented as mean ± SD.Animal care and animal experiments were performed following the protocol approved by the Animal Care and Use Committee of the Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Approval Code: 267/2018; Approval Date: 2 October 2018. RAS. Rat ASIC1a and ASIC3 channels were expressed in escribed . After i® software  [Theoretical models of peptide Hcr 1b-2 (UniProt accessions C0HL52) were built with homology modeling method based on 3D structures of APETx2 (PDB ID 1WXN and 2MUB) ,38, APET Canada) .® software [2+  was used as a template [® software and the PROCHECK server [The homology model of homotrimeric rASIC1a (construct Ser40-Leu463 aa) was generated with Modeller 9.19 interface in UCSF Chimera 1.11.2 , and loosoftware . The strtemplate . AccordiK server . The mod9 computed docking poses) were reclustered and analyzed using Chimera 1.11.2rc [® [Modeling of macromolecular complexes rASIC1a–Hcr 1b-2 and rASIC1a–Hcr 1b-4 was done with the molecular docking technique. Only extracellular regions of rASIC1a trimer Tyr71-Tyr424 aa) was used for the docking procedure. Initially blind rigid body docking was performed with the ClusPro 2.0 server . The top1.11.2rc , Discove1.11.2rc , and MOE4 aa was 1.2rc [® . The mosMD simulations of the rASIC1a–Hcr 1b-2 and rASIC1a–Hcr 1b-4 complexes in a hydrated nonfixed 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC) lipid bilayer performed in an Amber12:EHT force field  were car