Velocity profiles and equations relating flow rates and pressure losses [31].
\r\n\tDiagnostic tools are advancing: micro-and nano-diagnostics, advanced molecular genetics, and diagnosis of the aberrant clotting factor synthesis development and the options for the staging of the genetic abnormality - severe, moderate, and mild expression.
\r\n\tTreatment developments and advances start with prevention, intra-uterine approaches, genetic manipulation, genetic engineering, the high specificity of replacement factors, and recombinant technology.
\r\n\tIn addition to the above, the book will provide an update on the prevention of transmission of pathogens and potentially toxic substances used to stabilize and preserve treatment commodities. The role of big data and artificial intelligence through both machine learning and the application of deep learning and digital footprinting will also be addressed.
\r\n\tIn the developing world, there is an urgent need to collect, preserve and process plasma for the manufacturing of high yield, safe, and stabilized cryoprecipitate, or pharmaceutical fractionation of purified and specific clotting factors, as well as improvement on diagnostic and sociomedical approaches with an emphasis on patient and family care, and management of bleeding episodes.
The reserve of nonconventional heavy oils is one of the most important petroleum resources in the current world [1, 2]. These oils are highly asphaltic, dense, and viscous compared to conventional oils, such as Brent and West Texas Intermediate [3, 4]. The density is comparable to that of water, and the viscosity can be greater than that of water by more than five orders of magnitude at room temperature [5, 6]. This type of highly viscous oils is produced using a variety of mining and
The focus of the current chapter is the lubricated pipe flow (LPF) of heavy oils, where a water annulus separates the viscous oil-core from the pipe wall. It is an alternative flow technology, which is more economic and environmentally friendly than conventional heavy oil transportation technologies [9, 10]. The benefit of LPF is that it is a specific flow regime in which a continuous layer of water can be found near the pipe wall. As wall shear stresses are balanced by pressure losses in any kind of pipeline transportation, this flow system requires significantly less pumping energy than would be required to transport the viscous oil alone at comparable process conditions [10, 11, 12, 13, 14, 15, 16, 17].
\nA number of industrial scale applications of LPF are reported in the literature. For example, a 38.9-km long lubricated pipeline having 6 inch diameter was successfully operated by Shell for more than 12 years in California [18]. The frictional pressure loss for this pipeline was not only orders of magnitude less than that for transporting heavy oil but also quite comparable to the loss for transporting water [6]. The pipeline was operated by adding up to 30 vol% water. A number of water lubricated pipelines were used to transport heavy oil at Lake Maracaibo in Venezuela [1]. One of the challenges the operators faced to run these pipelines was cumulative wall fouling. Different operational measures, such as increasing water fraction or water flow rate and changing the water composition were taken to control the fouling. However, these measures were never sufficient to stop wall fouling. Water lubricated pipe flow technology was also used in Spain for the purpose of transporting heavy fuel oil [6]. Syncrude Canada Ltd. transported bitumen froth (a mixture of 60% bitumen, 30% water, and 10% solids) from a remote extraction plant to upgrading facility; they used a 35-km long and 36-inch diameter lubricated pipeline [12, 19, 20]. The lubrication process in the Syncrude pipeline produced a fouling layer of oil on the pipe wall. The thickness of the fouling layer was approximately 5% of the pipe’s internal diameter [12, 19]. At present, Brazilian oil producers are in the process of producing viscous oils from off-shore reservoirs with the application of water lubricated flow in vertical pipelines [21, 22].
\nA concerning phenomenon during the lubricated pipe flow of viscous heavy oil or bitumen is wall fouling [1, 3]. The probable LPF regime is presented in Figure 1. A wall fouling layer of oil is shown to surround a water annulus lubricating the viscous oil core. Although a number of experimental studies demonstrated the fouling layer to be a natural and inevitable consequence of the lubrication process, the mechanism of wall fouling in LPF has not been studied in detail [7, 12, 17, 19]. The application of LPF where the phenomenon of wall fouling must be accepted under regular operating conditions is sometimes referred to as “continuous water assisted flow (CWAF)” [13].
\nHypothetical presentation of the flow regime in a water lubricated pipeline [
Successful operation of a water lubricated pipeline is dependent on a few critical flow conditions. The preliminary requirement for establishing LPF is the simultaneous pumping of heavy oil and water in the pipeline. This kind of pumping into a horizontal pipeline can result in different flow regimes, depending upon the superficial velocities and the properties of oil [18, 24, 25]. The prominent flow regimes are dispersed, stratified flow, bubbles, slugs, and lubricated flows. The boundaries between the flow regimes are not well defined [7, 18]. It is possible to describe qualitatively the transition from a flow regime to the other one on the basis of similar regime transitions in gas-liquid flow systems [13]. At lower flow rates of the fluids, stratified flow can be expected [26, 27]. The relative positions of the oil and water in this kind of flow regime are controlled by the effect of gravity, that is, the difference between the liquid densities. If the density of water is higher than that of oil, oil is to float on water and vice versa. By increasing the water flow rate, the stratified flow regime may be transformed into bubble or slug flow. The increased flow rate is likely to increase the kinetic energy and turbulence of the water, which results in waves at the oil-water interface and, ultimately, transforms the stratified oil into bubbles or slugs. Further increase in the water flow rate may split bubbles or slugs into smaller droplets of oil. Contrariwise, increasing the oil flow rate at a constant water flow can promote coalescence of bubbles or slugs, which may produce the water lubricated flow regime [24, 25].
\nThe minimum velocity for the mixture of heavy oil and water required to obtain the water lubricated flow regime in a horizontal pipeline has been reported as 0.1–0.5 m/s for different applications [10, 12, 13, 15, 28]. In addition to the minimum velocity criterion, sustainable lubricated pipe flow also requires a minimum water fraction, typically between 10 and 30% [1]. A greater percentage of lubricating water does not cause a significant reduction in the pressure loss; even if it reduces the pressure loss to some extent, it also reduces the amount of oil transported per unit of energy consumed [10, 13, 20]. Water lubrication is usually identified from pressure loss measurements [13]. The establishment of lubricated pipe flow is typically associated with a significant and nearly instantaneous reduction in frictional pressure losses [20].
\nAs mentioned earlier, a significant concern during the application of lubricated pipe flow is that a minor fraction of the transported oil tends to adhere to the pipe wall, which eventually leads to the formation of an oil layer on the pipe wall [1, 3, 12, 13, 15, 18, 19, 29]. Frictional pressure losses in a “fouled” pipe, that is, with an oil coating on the wall, are higher compared to those for transportation of the same mixture in an unfouled pipe [15, 30]. Nevertheless, the frictional losses with wall fouling are substantially lower than that would be expected for transporting only heavy oil [10, 20, 29].
\nWall fouling is practically unavoidable in the water lubricated pipeline transportation of viscous oils [10, 12, 13, 15, 20]. Varying degrees of wall fouling are experienced in the applications of this pipe-flow technology. Different descriptions have been used in the literature to classify these applications, for example:
\nLubricated pipe flow has been used in this chapter to refer to any of these flow types, despite the fact that they exhibit quite different characteristics.
\nCore annular flow (CAF) primarily denotes an idealized version of lubricated pipe flow. It involves a core of viscous oil lubricated by a water annulus through a pipe with a clean (unfouled) wall [11, 29, 31]. Many research studies published in the 1980s and 1990s focused exclusively on CAF, for example, [11, 31, 32]. In most of these studies, wall fouling was either minimized or avoided through prudent selection of operating conditions, such as water cut and construction material of pipe. In pilot-scale and industrial operations, attempts to operate CAF pipeline usually required expensive mitigation strategies to handle wall fouling. In most published cases, it was impossible to avoid wall fouling (see, for example [15, 33]).
\nThe self-lubricated flow (SLF) and continuous water assisted flow (CWAF) are the commonly applied forms of LPF in the industry. As mentioned earlier, the SLF refers to the water lubricated pipeline transportation of a viscous mixture known as bitumen froth containing approximately 60% bitumen, 30% water, and 10% solids by volume [12, 19, 20]. The water fraction in the froth lubricates the flow; additional water is usually not added. In a SLF pipeline, water assist appears to be intermittent, and the oil core may touch the pipe wall at times [10, 12, 29]. Continuous water assisted flow denotes the pipeline transportation of heavy oil or bitumen when the water lubrication is more stable and the oil core touches the pipe wall infrequently [10, 13, 34]. Approximately 20–30 vol% water required to produce lubricated flow is supplier from an external source to a CWAF pipeline. Both SLF and CWAF involve wall fouling. For example, the thickness of fouling layer was measured from 5.5 to 8.5 mm in a 150-mm SLF pipeline transporting bitumen froth at 25°C [19]. Similar thicknesses in a 100-mm CWAF pipeline were found to vary from 1 to 5 mm depending on the operating temperature and mixture velocity [10, 23].
\nLubricated pipe flow has been applied in a specific industrial context for transporting viscous oils like heavy oil and bitumen with limited success in many cases [1, 3, 9, 18, 20, 21]. A challenge to the broader application of LPF technology is the lack of a reliable model to predict frictional pressure losses, even though numerous empirical (e.g., [12, 13]), semi-mechanistic or phenomenological (e.g., [10, 11, 15]) and idealized models (e.g., [14, 32, 33, 35, 36, 37]) have been proposed to date. The existing models were developed based on either single-fluid or two-fluid approach. A critical analysis of these models is important to underscore their limitations and to realize the scope of developing new approach to model LPF frictional losses.
\nSingle-fluid models are also known as equivalent fluid models. This kind of models generally takes an engineering approach to predict the pressure gradients. The flow system is modeled by considering the flow of a hypothetical fluid under comparable LPF process conditions. In some cases, this hypothetical fluid is water [10, 12, 13, 15]. In other cases, the properties of this fluid are determined using the mixture properties [11]. The flow regime in a single-fluid model is assumed to be in turbulent state, and the friction factor is recognized as inversely proportional to the nth power of a representative Reynolds number (Re), that is,
There are a few two-fluid models available in the literature [23, 32, 33, 38]. However, most of these were proposed for smooth pipe CAF, that is, this kind of models does not take into account the hydrodynamic roughness. As a result, these models are not suitable for SLF or CWAF. However, these models do have an advantage over single-fluid models. The actual mechanism of frictional pressure loss is addressed to some extent while developing a two-fluid model. The modeling approach is described in details with two examples as follows.
\nOliemans et al. [32] described the mechanism of frictional losses in their pioneering model developed for a CAF system. They identified the shear in the turbulent water annulus as the major contributing factor to pressure losses. However, they had to empirically address two important aspects of core annular flow: physical roughness on the oil core and water holdup. They also used a couple of idealized concepts like Reynold’s lubrication theory and Prandtl’s mixing length. This two-fluid model systematically underpredicted the CAF pressure losses. Also, the implementation of the model is not straightforward.
\nHo and Li [31] adapted the key features of Shi et al. [33] to develop another two-fluid model. They recognized the major source of frictional pressure loss in CAF to be the shear in the turbulent water annulus and modeled the turbulence based on the concept of Prandtl’s mixing length. They also considered the oil core to be a plug having a rough surface. However, instead of empirically quantifying this roughness like [33], the complexity of physical roughness was simplified in [32] based on the concept of hydrodynamic roughness. An idealized core annular flow regime was subdivided into four hypothetical zones as presented in Figure 2, which also depicts the dimensionless distances of these zones from the stationary pipe wall. The velocity profiles in the sublayers are usually presented using these nondimensional terms. The relationships of flow rate and pressure drops were obtained by integrating these velocity profiles with respect to the dimensionless distance. The equations are presented in Table 1.
\nHypothetical subdivision of perfect or ideal core annular flow into four zones showing dimensionless distances from the pipe wall [
Zone | \nEquations | \nRange | \n
---|---|---|
Laminar sublayer (1) | \nu1+ = y+ | \n0 ≤ y+ ≤ 11.6 | \n
Turbulent layer (2) | \nu2+ = 2.5ln(y+) + 5.5 | \n11.6 ≤ y+ ≤ yc+ − 5 | \n
Laminar sublayer (3) | \nu3+ = 2.5ln(yc+ − 5) − yc+ + 10.5 + y+ | \nyc+ − 5 ≤ y+ ≤ yc+ | \n
Plug core (4) | \nu4+ = 2.5ln(yc+ − 5) + 10.5 | \nyc+ ≤ y+ ≤ R+ | \n
(1) + (2) + (3) | \nQw = 2π(νw2/v*)[(2.5R+yc+ − 1.25yc+2)ln(yc+ − 5) + 3R+yc+ − 2.125yc+2 – 13.6R+] | \n0 ≤ y+ ≤ yc+ | \n
(4) | \nQo = π(νw2/v*)(R+ − yc+)2[2.5(lnyc+ − 5) + 10.5] | \nyc+ ≤ y+ ≤ R+ | \n
Velocity profiles and equations relating flow rates and pressure losses [31].
The principal focus of Ho and Li [31] was the water annulus in a CAF pipeline. The annular thickness was the most important parameter in the two-fluid model. However, they had to determine this thickness empirically. Moreover, they used the idealized concept of perfect CAF, that is, the perfectly concentric orientation of the oil core in the pipe, even though the orientation is more likely to be eccentric [29, 33]. The eccentricity of the oil core has a consequential effect on the CAF pressure losses [39].
\nEven after involving a number of simplifications, the Ho and Li model very closely addresses the physical mechanism of CAF pressure losses. This model allows predicting the pressure gradients using the values of oil and water flow rates. As expected, this two-fluid model underpredicts the CWAF friction losses consistently. This is because a CWAF system involves considerable wall fouling and oil core eccentricity, while the two-fluid model was developed for the perfect CAF in a hydrodynamically smooth pipe.
\nAdapting the modeling methodology described in [32], a physics-based approach to model CWAF pressure losses was proposed in [38]. Please refer to Ref. [23] for the details of the development. It is a semi-mechanistic two-fluid model, which requires simulating the turbulent flow of annular water on the fouling oil layer in a lubricated pipeline. The turbulence in the water annulus is modeled with the anisotropic ω-RSM model instead of the standard isotropic models. It can capture the effects of the thickness of the wall fouling layer, the equivalent hydrodynamic roughness produced by the viscous oil layer on the pipe wall, and the water holdup. The model was validated using actual CWAF data collected by varying pipe diameter, oil viscosity, water fractions, and flow rates. Compared to existing CFD models, this model is more robust as it not only produces better predictions but also requires significantly fewer computing resources. Although a promising development, the current version of the model involves some simplifications and is difficult to implement.
\nArney et al. [11] performed a comprehensive study on the core annular flow in a horizontal pipeline involving both experiments and theoretical analysis. Their primary objective was to enrich the CAF database and introduce a simple approach to calculate the frictional pressure losses.
\nFor the experiments, Arney et al. [11] used two oils: waxy crude oil (
Two important parameters used for this study were the water holdup (
They also measured the pressure losses for a variety of flow conditions. Based on the data, they proposed a single-fluid model. The friction factor (
where
Using this model, it was possible to predict a large number of CAF pressure drop data sets with a reasonable accuracy. The model showed good conformance with friction factor values at high Reynolds number. However, there was significant under prediction when Reynolds number was low. This was due to the fact that at low Reynolds number, the core annular flow was slightly unstable.
\nJoseph et al. [12] investigated the “Self-Lubrication” phenomenon of Bitumen froth (approximately 60% bitumen, 30% water, and 10% solids by volume), which was extracted using Clark’s hot water extraction process from the oil sands of Athabasca. The water in the froth, while transporting through the pipelines, was released due to high shear resulting in a lubricating layer near the wall. This is just another form of CAF where the annular water comes from the mixture itself.
\nTwo different setups were used to experimentally study the phenomenon of self-lubrication. First, a setup of 6 m long 25 mm ID pipe loop was used at the University of Minnesota. The froth was continuously recirculated. The duration of the experiments varied from 3 to 96 hours. The velocities for which pressure gradients were measured ranged from 0.25 to 2.5 m/s. Water volume fractions were kept within 20–40%, and the froth temperature ranged between 35 and 55°C. From the collected pressure gradient data at different flow rates, it was observed that there was a critical velocity range (from 0.5 to 0.7 m/s) below which the self-lubrication was being lost. The longest experimental time in this setup was 96 hours. This test was conducted in an already fouled pipeline. Despite the residual fouling, no further fouling was observed during the experiment. The authors suggested that this may be due to the clay particles (Kaolinite) from the released water protecting the oil core from accumulating to the pipe wall. The researchers also observed that heating the froth to a higher temperature would not necessarily improve the lubrication. This was due to the opposing effects of lowered bitumen viscosity at high temperature and reabsorption of the released water into the core. The other test setup (0.6 m ID and 1000 m long pipeloop) was at Syncrude (Canada), where pilot-scale tests were performed.
\nBased on the experimental data, a single-fluid model for the SLF of bitumen froth was proposed. In this model, a “Blasius-type” equation was used to correlate the
In Eq. (6), the complex flow behavior of self-lubricated flow is addressed with an empirically determined value of
McKibben et al. [13] carried out the investigation to examine free water-crude oil flows and, specifically, to establish a correlation for predicting the pressure gradients in continuous water assisted flow.
\nThe experiments were conducted using the followings:
A 53-mm ID pipeline consisting of approximately 60 m long horizontal insulated section;
The water fractions between 0.10 and 0.36;
The temperatures ranging from 18 to 39°C
The average velocities of the mixtures between 0.5 and 1.2 m/s;
Four different oils with the viscosities of 91.6, 24.9, 7.1, and 5.8 Pa s.
On the basis of the CWAF data sets at different water equivalent Reynolds number, the correlation of Fanning friction factor was found as:
\nThe inverse relationship between friction factor and water Reynolds number suggested that friction was controlled by a very thin water layer. A water layer of this type formed the lubrication region surrounding the oil core and provided the lubricating force required to overcome the effect of natural buoyancy.
\nRodriguez et al. [15] mainly focused on lab- and pilot-scale experimental measurements. They also took a semi-mechanistic approach to model frictional pressure losses of horizontal core annular flows in pipes having both fouled and clean walls. That is, the model was actually developed for the CWAF systems.
\nLab-scale tests were conducted with a 27-mm ID PVC pipe and a crude oil having a viscosity of 0.5 Pa s at 20°C. For the pilot-scale experiments, a steel pipeline (77 mm ID and 274 m length) was used to pump a highly viscous crude oil (36.95 Pa s and 972.1 kg/m3 at 20°C). A freshwater network was used to control the water injection. A piston pump pumped the water, and its flow rate was adjusted via a calibrated frequency inverter. The water superficial velocity was kept constant at 0.24 m/s, and three oil superficial velocities, 0.80, 1.00, and 1.10 m/s, were tested.
\nIn the experiments, a wavy core of viscous oil was observed, and the annular flow of water was mostly turbulent (Reynolds number for the water flow:\n
where \n
where \n
where \n
From Eqs. (13) and (14), the mixture viscosity can be expressed as:
\nEq. (15) shows that the mixture viscosity is affected by the slip ratio: the faster the core moves relative to the annulus, the lower the mixture viscosity and pressure drop. For the simple case of perfect core annular flow (PCAF), putting n = 1 and s = 2, Eq. (15) can be transformed into:
\nThe final form of the pressure drop model was obtained by introducing a two-phase multiplier defined as
\nUsing Eq. (10), (13), and (14), the above equation becomes
\nwhich becomes using Eq. (12) and \n
The hydrodynamic component of frictional pressure gradient can be expressed as
\nor
\nwhere \n
The proposed model can be used to analyze, correlate, and generalize pressure drop data. Along with that, the model allows for the satisfactory representation of different annulus flow regimes, kinematic effects, and wall conditions, including fouling. The model accounts for effects of buoyancy on the core. However, it cannot provide reliable predictions without regressing the values of
In continuation of the previous research [13], McKibben et al. [10] carried out an extensive experimental investigation of CWAF. The tests were conducted at the Saskatchewan Research Council (SRC), Saskatoon, Canada using 25, 100, and 260 mm steel pipe flow loops. The average thickness of wall fouling (
Based on the experimental study, a new empirical correlation for the Fanning friction factor was proposed as follows:
\nwhere
A scientific methodology of modeling single phase turbulent flow is to use computational fluid dynamics (CFD) [40]. In general, this modeling approach decomposes the turbulent flow into two parts: (i) time-averaged mean motion; (ii) time-independent fluctuations. The product of such decomposition is the transformation of Navier-Stokes (NS) equations into Reynolds Averaged Navier Stokes (RANS) equations [41]. In course of the mathematical transformation, additional terms of turbulent stresses are produced to make the matrix of equations “unclosed”; that is, the number of unknowns is higher than the number of equations. Various turbulent stresses in RANS equations are necessarily modeled empirically for the “closure” of the matrix [42]. The continuity and RANS equations can be presented with the following simplified differential equations:
\nwhere
Eddy-viscosity models were developed based on the concept of a hypothetical term known as eddy-viscosity (
Anisotropic turbulence can be addressed using Reynolds Stress Models (RSM), in which the hypothetical concept of eddy-viscosity is discarded [46]. An example of anisotropic model is
To acknowledge the superiority of a Reynolds stress model, a study of the equivalent hydrodynamic roughness (
Comparison of experimental pressure gradients with simulation results: 25.4 × 15.9 × 2000 mm rectangular flow cell; average coating thickness,
It should be mentioned that turbulence is a complex subject. Even though RANS methodology is feasible to computationally resolute the phenomenon of turbulence, it averages the process variables with a steady-state assumption in course of solving NS equations. The minor scale unsteady features of turbulence are usually neglected in this kind of averaging [44]. Most important of these features is the turbulent eddies. The scale of these eddies can vary over orders of magnitude [46]. The CFD solution of taking the effect of these eddies into account is computing differential NS equations without any kind of modeling. The available methods for the purpose are Large Eddy Simulation (LES) and Direct Numeric Simulation (DNS). However, these two simulation techniques demand extremely high computational resources [44]. At a computing rate of 1 gigaflop, the requirement of computational time for DNS is of the order of the Reynolds number to the third power (
Two-fluid CFD modeling approach to predict frictional pressure losses of core annular flow was used in different studies [14, 35, 36]. They considered the water annulus to be turbulent and the viscous core to be a laminar plug. Usually, the annular turbulence was modeled with standard
The performance of existing models in predicting friction losses is analyzed by comparing the experimental results collected for a lab-scale LPF system with the corresponding results obtained using five different models in Figure 4. The water equivalent friction factor (
where
Comparison of experimental and predicted values of water equivalent friction factor with respect to an equivalent Reynolds number.
The CAF model proposed by Arney et al. [11] significantly under predicts the experimental results for CWAF tests. The model was developed based on the experiments conducted in a 15.9-mm glass pipeline, which was selected for the purpose of controlling wall fouling and visualizing the flow regime. Compared to the CAF model, higher predictions of
Among the models presented in Figure 4, the CWAF model 3 demonstrates superiority in predicting both the magnitude and the trend of CWAF friction factors. The performance of the model tends to be better at higher flow rates. The reason is, most likely, the difficulty in establishing the lubricated flow regime at lower flow rates. The improved predictions of this model can be attributed to the following facts:
Instead of a purely empirical reasoning, the model was developed based on phenomenological observations. The physics of frictional pressure losses in a CWAF pipeline dominated the modeling approach. It can be considered as an empirical two-fluid model.
Special attention was paid to the contribution of wall fouling in increasing CWAF pressure drops.
A large data set covering a wide variety of process conditions was used to regress out the model constants.
However, it should be emphasized that the CWAF model 3 needs further validation with multiple independent data sets. Producing more quality data of CWAF pressure losses would be essential for the purpose.
\nAs demonstrated here, the existing models generally adopt an empirical approach to predict LPF friction losses. The effects of operating conditions in these models are usually accounted for with empirical constants. The actual physical mechanisms that govern the pressure losses in an LPF pipeline are almost entirely disregarded. As a result, the models developed for a CAF system cannot be applied to a CWAF system and vice versa. More rigorous studies are essential to develop a fully mechanistic approach to model the LPF friction losses. The CFD can be expected to play a significant role in the process.
\nThe lab-scale applications reported in the literature and a few commercial successes prove that continuous water assisted flow is a reliable method for the long-distance transportation of heavy oil. One of the major barriers to spread commercial applications of this flow technology is the lack of a viable model to predict frictional losses on the basis of operating parameters, such as pipe diameter, flow rates, fluid properties, and water fraction. A new model capable of dealing with the hydrodynamic effects produced by the “wall fouling” layer in a CWAF pipeline is required to facilitate wider industrial implementation of this pipeline transportation technology. The phenomenon of wall fouling has not been thoroughly probed till now, although it is an important characteristic of CWAF technology. Therefore, the future researches should be focused on the investigation of the hydrodynamic effects produced by the wall fouling layer.
\nThe oil core touching the pipe wall in a large water-assisted pipeline is another unaddressed phenomenon. Experiments conducted at Saskatchewan Research Council suggest that this phenomenon is significant for intermittent water assist when the bulk velocity is less than 1 m/s and the water fraction is less than 30% [10]. More devoted research works are necessary to determine the contribution of intermittent core/wall contact to the LPF pressure loss.
\nThe presence of solids like sands or clays in a CWAF pipeline is another important issue. The solids embedded on the wall fouling layer and the oil core may increase the equivalent roughness. In some cases, the fine particles in the lubricating water can change its apparent viscosity and the nature of contact between the oil-covered wall and the oil core (see [12] for additional details). Future work in this field would help to characterize the effects of solid fraction on the pressure losses in CWAF pipelines.
\nThe objective of the current chapter is to provide a brief introduction to the water lubricated transportation of heavy oil. The contents are summarized as follows:
Lubricated pipe flow is an alternative technology for long distance transportation of heavy oil. This kind of water assisted pipeline transportation is more economic and environmentally friendly than the conventional viscous oil transportation technologies. Its applications can be categorized as core annular flow, self-lubricated flow, and continuous water assisted flow. From an engineering perspective, CWAF is more significant than CAF or SLF.
A technical challenge to the field-scale application of CWAF is the absence of a reliable model to predict friction losses.
The models proposed to date for CWAF friction losses can be categorized as single-fluid and two-fluid models. In general, the methodology followed to develop a two-fluid model is more mechanistic, while a single-fluid model is an empirical development.
Applicability of an existing model for a specific set of flow conditions cannot be justified at present without a comparative analysis based on a reliable data set.
The most important research opportunities to develop a more reliable model for CWAF friction losses are related to the following subjects:
Wall fouling
Intermittent water lubrication
Solid laden CWAF
CFD modeling
Enrichment of the CWAF database
A part of the manuscript was the outcome of a research project that was funded by the
The authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest (such as honoraria, educational grants, participation in speakers’ bureaus, membership, employment, consultancies, stock ownership, or other equity interest, and expert testimony or patent-licensing arrangements), or nonfinancial interest (such as personal or professional relationships, affiliations, knowledge or beliefs) in the subject matter or materials discussed in this manuscript.
A part of the manuscript is adapted from the corresponding author’s PhD dissertation.
\nPhysical activity (PA) is one of the most accessible interventions for anxiety disorders for the public, whereas few systematic research has been done to examine its efficacy. PA is defined as a movement that causes an increase in energy expenditure in the movement of people [1], including walking, running, doing housework, jogging, or other sports that are defined as PA behaviour [2, 3]. Dollman et al. (2015) have classified PA intensity with metabolic equivalent (MET) as light PA (MET: 0–2.99), moderate-to-vigorous PA (MET:3–5.99), and vigorous PA (MET: ≥6) through a scale of energy expenditure [4, 5, 6]. PA intervention aims to promote the health of people through exercise training, sports and habit of PA [7, 8]. A PA intervention study should specify the processing target (e.g., children, adolescents, or some clinic population), PA type (e.g., aerobic exercise, resistance exercise, or yoga), PA intensity (e.g., light, moderator, moderator-to-vigorous), PA frequency (e.g., three sessions per week, 60 minutes per session), PA duration (e.g., three months, 1 years), and outcome measurement [9]. The PA intervention research is easier to quantify and more accessible to the generalised population. It is also found to benefit mental health. Therefore, research is also focused on the effect of PA intervention on panic disorder.
For example, Ensari, Petruzzello [10] conducted an RCT experiment to deliver a 40-minute yoga programme for eighteen participants with high-anxious. The result suggested a significant main effect of the task on panic and respiratory measures (p < .05). When collapsed over inhibition task and condition, there was a small reduction in cognitive anxiety from baseline to immediately post and 1-h post-condition (p < .05) [10]. Similarly, Naderi, Naderi [11] investigated the effect of physical exercise on anxiety among victims of child abuse and reported a significant reduction in anxiety (p < .001). Accordingly, the author argued that such improvement is comparable to empirically supported treatments for panic and GAD. However, such effects of PA intervention on panic disorder used a variety of PA types, intensity levels, or frequency and, therefore, produced isolated effects. The effect of PA could vary regarding individual differences, such as age and gender [12]. A most recent systematic review in 2022 tended to examine the effect of regular exercise interventions on the panic disorder in adults. They only retrieved eight studies in this field and demonstrated no clear evidence suggesting whether regular exercise programs (at least two 20-minute sessions per week for at least six weeks) reduce panic-related symptoms. The study argued for more RCT studies to support more robust and clear evidence for better understanding [11].
Moreover, there were even fewer studies focused on the effect of PA intervention on the panic disorder or general anxiety disorder (GAD) in children and adolescents, respectively. This may be because it is difficult to categorise different anxiety disorders among children. Furthermore, there is a lack of tools to measure child panic in laboratory settings. For example, there is the anxiety scale for children with autism spectrum disorder, revised children’s manifest anxiety scale and social anxiety scale for children to measure anxiety disorder in children and adolescents [9, 13, 14], whereas the panic disorder is measured based on the sensitivity of anxiety scales in children and adolescents [15]. These unclear concepts may increase the research difficulty, which supports the evidence for PA intervention on panic disorder in children and adolescents. Therefore, this chapter aims to carry out a quantitative review to clarify and explore the evidence in this area. Moreover, the secondary objective is to investigate the effect of PA intervention on anxiety disorder in children and adolescents.
The previous Machado, Telles [11] review obtained a similar outcome measurement to examine the effect of PA on anxiety disorder. Their target sample did not limit the population age, which means there is no evidence that physical activities affect panic and anxiety disorder in children and adolescents. Consequently, the current analysis aims 1) to summarise and explain the potential impact of PA interventions on panic symptoms and critically comment on the research that exists and 2) to analyse the effect of PA intervention on panic and anxiety symptoms in children, adolescents and early adulthood, through meta-analysis, which provides reference evidence for further research.
The study is based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines. A protocol for this review was registered with PROSPERO (CRD42022334054).
The forest plot of the effect size of physical activity on panic in children, adolescents and early adulthood.
Search is conducted on 22nd April 2022, which follow databases: MEDLINE (Ovid), EMBASE, Web of Science, Cochrane Central Register of Controlled Trials, and SPORTDiscus. Search terms based on the PICO format (participants/population, intervention/exposure, comparison, outcome) were divided, and adjusted according to the respective databases’ Thesaurus and Medical Subject Headings (MeSH) terms (Bramer et al., 2018) through Ovid. Articles must be available in English, there will be no restriction on the publication period. The full list of search terms is provided in Supplementary Material 1.
The inclusion criteria of the current analysis were: 1) Population: studies included participants who primarily exhibited panic or anxiety symptoms or were diagnosed with panic or anxiety disorders in children, adolescents (5–19 years) and early adulthoods (19–22 years). Participants may present secondary comorbid other illnesses, such as diabetes; 2) Intervention: studies applied regular PA intervention (i.e. walk, jog, aerobic, strength, or multimodal training), which is prescribed to reduce panic disorder or GAD, social anxiety disorder, obsessive–compulsive disorder, post-traumatic stress disorder, and agoraphobia. PA interventions can be combined with other treatment procedures were also included; 3) Comparators: studies included a control group as a comparator, which is not received the PA intervention delivery; 4) Outcomes: studies that took panic symptoms or panic disorder as the primary outcome. And the second outcome was anxiety symptoms, GAD, social anxiety disorder, obsessive–compulsive disorder, post-traumatic stress disorder, or agoraphobia; 5) Study Design: studies carried out in randomised trials (RCT) comparing an intervention(s) encompassing PA with a group(s) without PA intervention or encompassing PA at the baseline with post PA intervention.
The exclusion criteria were: 1) studies reported in non-English language; 2) studies reported insufficient information to estimate effect size or other essential data.
Study selection: Data will be formatted in RIS format and will be managed using the endnote software. PRISMA 2020 guidelines will be applied for reporting the screening process [16]. Two researchers will undertake the removal process through an independent screen. Firstly, all duplicate articles will be removed before reviewing titles and abstracts. Those not fitting the inclusion criteria will be removed. Then, full-text versions will be collected when the articles meet the screening criteria. Discussions with a third reviewer will resolve discrepancies between the two independent reviewers.
Data extraction: Two independent reviewers will extract the following four data dimensions. Including fundamental characteristics (e.g., author, public year, country, population, sample, age, sex, weight status), intervention characteristics (e.g., PA intensity/frequency/duration, intervention program), methodology (e.g., data analysis method), and effect size.
Two reviewers will independently score the studies according to the National Institutes of Health study quality assessment tool for Quality Assessment of Controlled Intervention Studies from the National Heart, Lung, and Blood Institute (https://www.nhlbi.nih.gov/health-topics/study-quality-assessment-tools). The quality assessment focused on the specification of eligibility criteria, generalisability, intervention description, outcome assessment and incomplete data [17]. There were 14 items assessed in the quality assessment, as shown in Appendix S1. The tool does not assign numeric values or definite judgements of the quality of the studies, although it has good, fair, and poor results. Good quality studies have less bias risk and are more valid. A fair study is prone to some bias but insufficient to invalidate its findings. A poor study has a high-risk of bias and is considered invalid [18]. The results of quality assessment are presented in Table 1.
Study | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | overall |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Kenis-Coskun et al., 2022 | Y | Y | Y | NR | NR | Y | Y | Y | Y | Y | Y | Y | Y | Y | Good |
Tanksale et al., 2021 | Y | Y | N | N | N | Y | Y | Y | N | Y | Y | NR | NA | Y | Fair |
Nazari et al., 2020 | Y | Y | N | N | N | Y | Y | Y | NR | Y | Y | Y | Y | Y | Fair |
Romero-Pérez et al., 2020 | Y | Y | N | N | N | Y | Y | Y | Y | Y | Y | NR | Y | Y | Fair |
Yu et al., 2020 | Y | Y | N | N | N | N | Y | Y | Y | Y | Y | Y | Y | Y | Fair |
Mucke et al., 2020 | Y | Y | N | N | N | Y | Y | Y | Y | Y | Y | Y | NA | Y | Good |
Akko et al., 2020 | Y | Y | N | N | N | Y | Y | Y | Y | Y | Y | Y | Y | Y | Good |
Luna et al., 2019 | Y | Y | N | N | N | Y | Y | Y | Y | Y | Y | NR | Y | Y | Fair |
Naderi et al., 2019 | Y | Y | N | N | N | Y | Y | Y | Y | Y | Y | NR | Y | Y | Fair |
Ensari et al., 2019 | Y | N | N | NR | NR | Y | Y | Y | Y | Y | Y | NR | Y | Y | Fair |
Polis et al., 2017 | Y | Y | N | N | N | Y | Y | Y | NR | Y | Y | NR | NA | Y | Fair |
Smits et al., 2009 | Y | N | NR | NR | NR | Y | Y | Y | Y | Y | Y | NR | Y | Y | Fair |
Broman-Fulks & Storey, 2008 | Y | N | NR | NR | NR | Y | Y | Y | Y | Y | Y | NR | Y | Y | Fair |
Lindwall et al., 2005 | Y | Y | N | N | N | Y | N | N | N | NA | Y | NR | Y | Y | Poor |
Crew et al., 2004 | Y | Y | N | N | N | Y | Y | Y | Y | N | Y | NR | NA | Y | Fair |
Summary of quality of included studies.
The studies we aimed to include in the current analysis were RCTs with both between-subject, within-subject and mixed designs. Consequently, a combined effect size of standard mean difference (Cohen’s d) was calculated for each study to produce a pooled effect size based on the improved method provided in Morris [19]. Firstly, the effect size of studies reported only median and interquartile range was estimated based on the improved formula [20, 21], where d refers to Cohen’s d; q1 refers to the first quartile; q3 refers to the third quartile:
Moreover, studies reported pre-calculated Cohen’s d without providing the mean or standard deviation was estimated standard error using the 95% confidence interval for meta-analysis weighting [22], where SE refers to standard error, CLup and CLlow refer to the upper and the lower bound of the confidence interval, respectively:
The effect sizes were from between-subject design, within-subject design and mixed design studies were extracted, converted and matched to Cohen’s d with an online converter tool ‘Psychometrica’ (https://www.psychometrica.de/effect_size.html), which follows the method proposed in Morris [19] and Lakens [23].
The statistical analysis was carried out in STATA v.17. The estimated effect sizes of adolescent panic and anxiety were pooled in a quantitative meta-analysis in a random effect model and Cohen’s d to determine the overall effect among the studies. A significant result of this analysis indicates that there was a significant effect of physical activities/exercise on adolescent panic or anxiety across the studies. The effect size is considered small when SMD is between 0.2 and 0.5, medium when it is between 0.5 and 0.8, and large when it is above 0.8 [24].
Then, a heterogeneity test of the available data was carried out with the random effect model. A non-significant result in the heterogeneity test would mean that the effect sizes were homogenous and measured a consistent effect on the same side. The heterogeneity I2 is considered moderate when I2 > 50%, and it is considered high when I2 > 75% [21]. Egger’s regression-based tests were then used to assess the publication bias. A significant result in this test would suggest potential publication bias in the current analysis.
Finally, exploratory meta-regression analyses were performed on the available characteristic data, including age, gender and intervention duration, to determine potential predictors of the current effect. The research method would be entered into subgroup analysis to determine whether the study design made a difference in the overall effect.
As shown in Appendix 2, keywords searching in MEDLINE (Ovid), EMBASE, Web of Science, Cochrane Central Register of Controlled Trials, and SportDiscus resulted in 1691 articles. After reviewing, based on inclusion criteria, twelve studies were identified, and four studies were excluded based on exclusion criteria, leaving eight studies for the meta-analysis. The included 11 studies were all RCTs in different designs (within-subject, between-subject and mixed design).
As shown in Table 2, 15 RCT studies with sufficient data were included. Among these studies, 14 obtained anxiety measurements, including social anxiety disorder [14, 25, 26] and GAD [10, 13, 27, 28, 29, 30, 31, 32], and 4 studies obtained panic measurements [10, 31, 32, 33]. There were 994 participants included in total, and 478 and 354 participants were allocated in the intervention and control groups, respectively. The mean age of the participants was 13.21 ± 4.16 years old, ranging from 8 to 24 years old. Physical activity intervention duration was from a minimum of 2 weeks to 8 months, and frequency was 2 or 3 sessions per week, with two studies performing a one-session intervention [10, 34]. Two studies also provided discussion and reflection sessions after the physical activity sessions [34, 35] and two studies were conducted on the school campus [14, 28].
Study | Overall sample | IG sample Pre-I (Post-I) | CG sample Pre-I (Post-I) | Overall age (SD) | Female sample | IG content | CG content | Frequency (Duration) | Panic and anxiety measurement | Study Design | Intensity measurement |
---|---|---|---|---|---|---|---|---|---|---|---|
Kenis-Coskun et al., 2022 | 28 | 14 (14) | 14 (14) | 9.90 (1.91) | 20 | Multiple rehabilitation exercises repeated 10 times each: Corner Pectoral Stretch; Scapular Retraction with External Rotation; Triceps Brachii Strengthening; Biceps Strengthening Exercise; Biceps Strengthening Exercise; Lateral Abdominal Muscle Strengthening Exercise; Push Up; Back Extensors Strengthening. | NR | 3 s/w (12 weeks) | RCADS | Mixed | NA |
Tanksale et al., 2021 | 61 | 31 (31) | 30 (30) | 9.44 (1.35) | 22 | The lead researcher delivered the Yoga program face-to-face to all participants on the university campus within a group of less than 5 parent–child dyads. | Participants were randomly allocated to a waiting list without receiving intervention | 1 s/w (6 weeks) | ASC-ASD | Between-subject | NA |
Nazari et al., 2020 | 40 | 20 (20) | 20 (20) | 11.11 (2.29) | NR | 20 mins of Pilates exercises & 20 mins of body weight-bearing exercise & 20 mins aerobic exercises (V-forward, V-back & march) | NR | 3 s/w (16 weeks) | RCMAS | Mixed | Heart rate |
Romero-Pérez et al., 2020 | 105 | 54 (54) | 51 (51) | 9.88 (0.83) | 60 | 5-min warm-up, a 40-min aerobic exercise | The CG participants continued with their usual activities at the end of the classes | 2 s/w (20 weeks) | RCMAS | Mixed | NA |
Yu et al., 2020 | 188 | 106 (99) | 82 (72) | 9.8 (0.7) | 35 | 20-min class recess in the morning and one extra gym class (40 min) after school in the afternoon, including Jogging 20 min in the morning break every weekday; Rope skipping 40 min on Monday and Thursday; Playing badminton 40 min on Wednesday and Friday; 200-m relay race 40 min on Tuesday. | Children in the control school followed their usual practice with no extra intervention | (weekday daily) 5 s/w (8 months) | SAQ-C24 | Mixed | NA |
Mucke et al., 2020 | 60 | 30 (NA) | 30 (NA) | 17.9 (1.24) | 0 | The exercise group performed an exercise session at moderate intensity on a bicycle ergometer (30 mins) | During the next 30 mins, the control group read an article from a magazine of their choice | One session | STAI | Between-subject | Heart Rate |
Akko et al., 2020 | 44 | 23 (23) | 21 (21) | 9.35 (0.6) | 39 | 45 min after school running and running-based games of moderate-intensity | preadolescent children participated in assisted homework sessions to prevent attention bias and to control for retest effects | 3 s/w (10 weeks) | STAI | Mixed | NA |
Luna et al., 2019 | 113 | 69 (69) | 44 (44) | 13.82 (0.79) | 49 | 55-minute sessions volleyball sessions, including warming-up, training and friendly matches and regular stage competition; Meetings for comprehension and reflection with the intervention of the responsibility roles | Traditional collective sport (basketball) with a conventional teaching style in which the teachers directed all tasks without students’ participation | 2–3 s/w (6 weeks) | SAS-A | Mixed | NA |
Naderi et al., 2019 | 22 | 11 (11) | 11 (11) | 8 to 11 | 22 | Aerobic dancing: Warming up (10–15 min); Basic movements (35–40 min); Cooling down (10 min) | Not receiving any intervention | 3 s/w(8 weeks) | STAI | Mixed | NA |
Ensari et al., 2019 | 18 | 9 (9) | 9 (9) | 22.1 (5.0) | 18 | 40 min Yoga session, which was designed based on published recommendations under the guidance of an instructor with the specific order of poses | Stretching exercises | One session | API & SAI | Mixed | Heart Rate |
Polis et al., 2017 | 23 | 12 (5) | 11 (8) | 11 to 18 | NR | Evening yoga session led by yoga instructor | NR | 2 s/w (6 weeks) | STAI | Mixed | NA |
Smits et al., 2009 | 92 | 48 (48) | 44 (44) | 19.43 (1.31) | 51 | 20 min treadmill exercise on a computer-controlled treadmill, maintaining 70% of max heart rate | 20-min resting period | One session | API | Mixed | Heart Rate |
Broman-Fulks & Storey, 2008 | 24 | 12 (12) | 12 (12) | 19.04 (1.90) | 19 | 20 min aerobic exercise: treadmill running | Report to the lab at the same time but no exercise | 3 s/w (2 weeks) | ASI-R | Mixed | Heart Rate |
Lindwall et al., 2005 | 110 | 56 (27) | 54 (35) | 16.35 (1.56) | 110 | Preferred multiple aerobics exercises (45 min) and discussion (15 min), including water aerobics, step-up, badminton, kickboxing, spinning dancing, climbing, bowling, karate, jujitsu, yoga and different ballgames | Control group were put on a waiting list with no forms of alternative activities organised | 2 s/w (24 weeks) | SPAS | Mixed | NA |
Crew et al., 2004 | 66 | 66 (66) | NA | NR (Grade 4) | 33 | The aerobic group exercised by means of stationary cycling, track running, and jumping on a minitrampoline. The physical activity group engaged in a variety of physical activities such as shooting baskets for skill improvement, playing a common children’s game called foursquare, and walking | NA | 3 s/w (6 weeks) | STAI | Within-subject | Heart Rate |
Overall | 994 | 561 (488) | 433 (371) | 13.21 (4.16) | 478 (51.3%) |
Characteristics of included studies.
IG = intervention group; CG = control group; Pre-I: pre-intervention; Post-I: post-intervention; s/w = sessions per week; NR = not reported; NA = not applicable; ASC-ASD: Anxiety Scale for Children–Autism Spectrum Disorder RCMAS = Revised Children’s Manifest Anxiety Scale; SAQ-C24 = Social Anxiety Scale for Children; SAS-A = Social Anxiety Scale for Adolescents; STAI = State–Trait Anxiety Inventory; SAI = State Anxiety Inventory; SPAS = Social Physique Anxiety Scale; RCADS = Anxiety and Depression Scale in Children-Revised; API = Acute Panic Inventory; ASI-R = Anxiety Sensitivity Index-Revised. The sports type are labelled in bold.
NA: not applicable, NR: not reported, CD: cannot determine, overall of Good: more than 10Y (NA = Y), Fair 8 to 10Y, Poor: Below 8.
Overall, three reports showed good quality, whereas most studies were fair. We can find that in terms of random methods, most of the studies do not report the process of random sampling and there are basically no studies that apply computer random sampling methods. In addition, the information reported on the sample power is relatively lacking.
Funnel plot of the effect size estimates of physical activity on the panic symptoms in children and adolescents.
Predictor | Coefficient B | SE | 95% CI | z | |
---|---|---|---|---|---|
Age | −.03 | .03 | [−.11 .04] | −.99 | .325 |
Gender Ratio (Female) | −.06 | .66 | [−1.35 1.23] | 0.09 | .927 |
Meta-regression analysis on age and gender predicting pooled effect sizes of PA intervention reducing panic disorder.
The forest plot of the effect size of physical activity on anxiety disorder in children and adolescents.
Funnel plot of the effect size estimates of physical activity on anxiety disorder in children and adolescents.
The research method (mixed-design vs. between-subject & within-subject design) was entered into subgroup analysis to determine whether the main effect changed between the two interactive groups. No significant group difference in homogeneity was identified in either research method, Qb(1) = 1.26,
The current chapter carried out a meta-analysis on 15 reports to investigate the pooled effect sizes of PA intervention on panic and anxiety symptoms among children, adolescents and early adulthood. Compared to the controls, we reported a small effect of PA on reducing panic symptoms and a middle effect on reducing anxiety symptoms. To our knowledge, this is the first study to summarise the effect of PA on panic and anxiety symptoms in children, adolescents and early adulthood with meta-analysis.
The primary finding of the current meta-analysis is that the pooled effect sizes from 4 reports yielded a significant small effect (
However, it is very important to bear in mind that this result is very primal and exploratory because it was summarised from four reports with limited sample sizes, of which one study targeted children (N = 28) [33], two studies targeted adolescents (N = 92; N = 24, respectively) [31, 32] and one study targeted early adulthoods (N = 18; age mean = 22.1) [10]. There is, to date, indeed a shortage of evidence in this field. A most recent 2022 systematic review only identified eight studies testing PA intervention’s effect on panic disorder among adults [11] and argued for more evidence. On the one hand, it is difficult to recruit children with panic symptoms or diagnosed with panic disorder and deliver interventions for them. Unlike general anxiety symptoms, panic disorder is often clinically diagnosed and needs to be treated with extra caution. On the other hand, the tool to measure panic symptoms are limited among children. The experiments included in the current analysis used measurements, including API, RCAD and ASI-R [10, 31, 32, 33]. Among these scales, RCAD and ASI-R are developed for anxiety and only address panic symptoms in their subscales, which were not specifically developed for panic disorder. API was developed for panic symptoms but not aimed at children. It is important to evaluate the assessment tool because the panic among children and adolescents could differ between ages [42]. In comparison, another scale developed after 2014 to measure panic symptoms, namely the Panic Disorder Severity Scale for Children, adapted for adolescents from 11 to 17 years old [43], and used in some studies testing the effect of CBT on panic disorder. Future studies could consider testing the effect of PA on children’s panic with suitable assessments.
The secondary finding of the current analysis is that PA intervention had a middle effect (
Knowing that PA intervention reduces panic and anxiety symptoms across the empirical evidence, the next question is what type of exercise produces an optimal effect. The current meta-analysis could not perform the proper subgroup analysis to determine the best PA type due to insufficient data inclusion. Among the 15 studies, three studies applied resistance training, including push up [33], weight-lifting [13] and treadmill exercises [31], whereas others applied aerobic exercise in groups or individually. Among which, the push up and weight-lifting seems to produced the large and significant effect sizes reducing anxiety symptoms (d = −1.72, p < .001; d = −1.07, p = .002, respectively) [13, 33]. The effect of resistance training seemed somewhat contradictive to the mechanism in which the high lactate level could induce panic and anxiety symptoms when such anaerobic exercise produces lactate. There are two possible reasons to explain this. One possible reason is that only lactate in the brain induces the change in brain acidosis that leads to panic and anxiety symptoms [44], whereas muscle lactate produced by anaerobic exercise is independent of that in the brain [45]. It is the blood lactate which influences brain acidosis. The second reason is that the participants were measured almost immediately after the PA intervention cooled down, where the blood lactate level remained still. Hiscock, Dawson [46] tested 4 different types of weight-lifting technic to investigate the difference in muscle activation and blood lactate. The blood lactate was measured immediately after the exercise and no change in blood lactate was detected with a significant difference in muscle activation. Consequently, blood lactate was not influenced by different exercise intensities if measured immdiately after the intervention. Hypothetically, it is the regulation of CO2 during PA that potentially attenuates panic and anxiety symptoms. Future studies could compare, first, the effect of breathing practice from CBT and PA intervention with controlled blood lactate levels. Second, future studies could investigate the long-term effect of resistance training on blood lactate and panic & anxiety symptoms.
The last point to make is that the current meta-regression analysis did not suggest evidence of whether individual differences predicted the pooled effect sizes. Although it was argued in other literature that gender or age could moderate the effect of PA [12]. Previous literature reported gender differences in PA index as age grows [47], and more mature adolescents have more autonomy in PA than children [48], such that they can initiate behaviours that enhance the positive effects of PA on anxiety. As a result, the benefits of PA on depression and anxiety may increase with age. However, the current meta-regression analysis failed to demonstrate such effects on gender or age. One possible reason is that there were only 15 experiments identified in this study, which obtained limited power to detect any individual difference. Thirteen studies reported their gender ratio, and 12 reported the distribution of age. More studies are required to investigate individual differences’ role in the effect of PA intervention on anxiety and panic symptoms.
This meta-analysis has several limitations. Firstly, we used Cohen’s d rather than Hedges’ g to estimate the SMD, which the results might be biased in small sample studies. The reason to pick Cohen’s d was that some studies already reported pre-calculated Cohen’s d and did not provide sufficient information (N, mean, SD) to carry out transformation or bias correction. With limited numbers of the study identified, it would be impossible to exclude them from the analysis, and this could only be solved by including more studies with sufficient data. Secondly, the current study did not control the comorbidity among children and adolescents, which could affect the outcome of physical activities on panic and anxiety symptoms. As a result, the current results were very primal and exploratory, which should be considered cautiously.
Conclusion(s).
The current meta-analysis reported a small effect of PA intervention on reducing panic symptoms and a middle effect on reducing anxiety symptoms in children, adolescents and early adulthood. Meta-regression analysis did not support age or gender predictors of the pooled effect size. More studies in this field are required to produce a more solid conclusion.
We thank all of the staff who contributed their time to our research.
China Scholarship Council and University of Exeter PhD Scholarship.
Appendix 1 Search strategy of systematic review.
Appendix 2 Flow chart of studies retrieved and screened according to the PRISMA.
Appendix 3 Characteristics of included studies.docx.
Appendix 4 Summary of quality of included studies.
Appendix 5 Meta-analysis of raw data.
Intro
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Aalborg University has Two Satellite Campuses, one in Copenhagen (Aalborg University Copenhagen) and the other in Esbjerg (Aalborg University Esbjerg).\n· He is a member of prestigious IEEE (Institute of Electrical and Electronics Engineers), and IAENG (International Association of Engineers) organizations. \n· He is the chief Editor of the Journal of Software Engineering.\n· He is the member of the Editorial Board of International Journal of Computer Science and Software Technology (IJCSST) and International Journal of Computer Engineering and Information Technology. \n· He is also the Editor of Communication in Computer and Information Science CCIS-20 by Springer.\n· Reviewer For Many Conferences\nHe is the lead person in making collaboration agreements between Aalborg University and many universities of Pakistan, for which the MOU’s (Memorandum of Understanding) have been signed.\nProfessor Akbar is working in Academia since 1990, he started his career as a Lab demonstrator/TA at the University of Sussex. After finishing his P. hD degree in 1992, he served in the Industry as a Scientific Officer and continued his academic career as a visiting scholar for a number of educational institutions. In 1996 he joined National University of Science & Technology Pakistan (NUST) as an Associate Professor; NUST is one of the top few universities in Pakistan. In 1999 he joined an International Company Lineo Inc, Canada as Manager Compiler Group, where he headed the group for developing Compiler Tool Chain and Porting of Operating Systems for the BLACKfin processor. The processor development was a joint venture by Intel and Analog Devices. In 2002 Lineo Inc., was taken over by another company, so he joined Aalborg University Denmark as an Assistant Professor.\nProfessor Akbar has truly a multi-disciplined career and he continued his legacy and making progress in many areas of his interests both in teaching and research. 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Polymorphism at the DNA level includes a wide range of variations from single base pair change, many base pairs, and repeated sequences. Genomic variability can be present in many forms, including single nucleotide polymorphisms (SNPs), variable number of tandem repeats (VNTRs, e.g., mini- and microsatellites), transposable elements (e.g., Alu repeats), structural alterations, and copy number variations. Different forms of DNA polymorphisms can be tracked using a variety of techniques; some of these techniques include restriction fragment length polymorphisms (RFLPs) with Southern blots, polymerase chain reactions (PCRs), hybridization techniques using DNA microarray chips, and genome sequencing. During the last years, the recent advance of molecular technologies revealed new discoveries of DNA polymorphisms. DNA polymorphisms are endless, and more discoveries continue at a rapid rate. Mapping the human genome requires a set of genetic markers. DNA polymorphism serves as a genetic marker for its own location in the chromosome; thus, they are convenient for analysis and are often used as in molecular genetic studies.",book:{id:"6719",slug:"genetic-diversity-and-disease-susceptibility",title:"Genetic Diversity and Disease Susceptibility",fullTitle:"Genetic Diversity and Disease Susceptibility"},signatures:"Salwa Teama",authors:[{id:"249329",title:"Dr.",name:"Salwa",middleName:null,surname:"Teama",slug:"salwa-teama",fullName:"Salwa Teama"}]},{id:"58467",title:"Generation of Antibody Diversity",slug:"generation-of-antibody-diversity",totalDownloads:3211,totalCrossrefCites:2,totalDimensionsCites:2,abstract:"Because of the huge diversity, the immunoglobulin repertoire cannot be encoded by static genes, which would explode the genomic capacity comprising about 20,000–25,000 human genes. The immunoglobulin repertoire is provided by the process of somatic germ line recombination, which is the only controlled alteration of the genomic DNA after meiosis. It takes place in mammalian B lymphocyte (B cells) precursors in the bone marrow. The genome germ line sequence of undeveloped B cells is organized in gene segments and compromise V (variable), D (diversity), and J (joining) gene segments constituting the variable domain of the heavy chain and only V and J genes for building up the variable domain of the light chain. The rearrangement of the variable region follows a strict order. The following processes that participate in the generation of antibody diversity were summarized—allelic, combinational, and junctional diversity, pairing of IgH and IgL, and receptor editing—which all together produce the primary antigen repertoire (pre-antigen stimulation). When a B cell encounters a foreign antigen, affinity maturation and class switch are induced. Thereby the antibody repertoire increases. The resulting secondary immunoglobulin repertoire reveals in humans at least 1011 specificities for different antigens.",book:{id:"5784",slug:"antibody-engineering",title:"Antibody Engineering",fullTitle:"Antibody Engineering"},signatures:"Oliver Backhaus",authors:[{id:"177685",title:"M.Sc.",name:"Oliver",middleName:null,surname:"Backhaus",slug:"oliver-backhaus",fullName:"Oliver Backhaus"}]},{id:"61204",title:"Polymorphisms",slug:"polymorphisms",totalDownloads:2075,totalCrossrefCites:3,totalDimensionsCites:11,abstract:"Polymorphism or variation in DNA sequence can affect individual phenotypes such as color of skin or eyes, susceptible to diseases, and respond to drug, vaccine, chemical, and pathogen. It occurs more often than mutations (frequency ≥ 1%). The common polymorphism is single nucleotide polymorphism (SNP) which is a single base change in a DNA sequence that occurs most commonly in the human genome. SNPs have been used as molecular markers in a wide range of studies. Genome-wide association studies (GWAS) searches for SNPs that occur more frequently in person with a particular disease than in person without the disease and pinpoint genes or regions that may contribute to a risk of disease. 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Modern embryology owes its initial development to the key embryo collections that began in the 19th century. The first large collection was that of Carnegie, and this was followed later by the major 7 collections. The second role of the Carnegie collection was for researchers to establish a defined set of Carnegie stages based on embryo morphological features. Today, embryos are imaged three-dimensionally (3D) by a range of imaging modalities including, magnetic resonance microscopy (MRM), episcopic fluorescence image capture (EFIC), phase-contrast X-ray computed tomography (pCT), and optical projection tomography (OPT). Historically, embryo serial images were reconstructed using wax-plate and model techniques. The above new 3D imaging techniques now allow 3D computer reconstructions, analysis, and even 3D printing. 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She is now a lecturer at the University of Witwatersrand, South Africa, and a principal researcher at the Health Economics and Epidemiology Research Office (HE2RO), South Africa. Dr. Moolla holds a Ph.D. in Psychology with her research being focused on mental health and resilience. In her professional work capacity, her research has further expanded into the fields of early childhood development, mental health, the HIV and TB care cascades, as well as COVID. 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He is currently the Director of the Postgraduate Program in Implantology of the Bioface/UCAM/PgO (Montevideo, Uruguay), Director of the Cathedra of Biotechnology of the Catholic University of Murcia (Murcia, Spain), an Extraordinary Full Professor of the Catholic University of Murcia (Murcia, Spain) as well as the Director of the private center of research Biotecnos – Technology and Science (Montevideo, Uruguay). Applied biomaterials, cellular and molecular biology, and dental implants are among his research interests. He has published several original papers in renowned journals. In addition, he is also a Collaborating Professor in several Postgraduate programs at different universities all over the world.",institutionString:null,institution:{name:"Universidad Católica San Antonio de Murcia",country:{name:"Spain"}}},{id:"342152",title:"Dr.",name:"Santo",middleName:null,surname:"Grace Umesh",slug:"santo-grace-umesh",fullName:"Santo Grace Umesh",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/342152/images/16311_n.jpg",biography:null,institutionString:null,institution:{name:"SRM Dental College",country:{name:"India"}}},{id:"333647",title:"Dr.",name:"Shreya",middleName:null,surname:"Kishore",slug:"shreya-kishore",fullName:"Shreya Kishore",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/333647/images/14701_n.jpg",biography:"Dr. Shreya Kishore completed her Bachelor in Dental Surgery in Chettinad Dental College and Research Institute, Chennai, and her Master of Dental Surgery (Orthodontics) in Saveetha Dental College, Chennai. She is also Invisalign certified. She’s working as a Senior Lecturer in the Department of Orthodontics, SRM Dental College since November 2019. She is actively involved in teaching orthodontics to the undergraduates and the postgraduates. Her clinical research topics include new orthodontic brackets, fixed appliances and TADs. She’s published 4 articles in well renowned indexed journals and has a published patency of her own. Her private practice is currently limited to orthodontics and works as a consultant in various clinics.",institutionString:null,institution:{name:"SRM Dental College",country:{name:"India"}}},{id:"323731",title:"Prof.",name:"Deepak M.",middleName:"Macchindra",surname:"Vikhe",slug:"deepak-m.-vikhe",fullName:"Deepak M. Vikhe",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/323731/images/13613_n.jpg",biography:"Dr Deepak M.Vikhe .\n\n\t\n\tDr Deepak M.Vikhe , completed his Masters & PhD in Prosthodontics from Rural Dental College, Loni securing third rank in the Pravara Institute of Medical Sciences Deemed University. He was awarded Dr.G.C.DAS Memorial Award for Research on Implants at 39th IPS conference Dubai (U A E).He has two patents under his name. He has received Dr.Saraswati medal award for best research for implant study in 2017.He has received Fully funded scholarship to Spain ,university of Santiago de Compostela. He has completed fellowship in Implantlogy from Noble Biocare. \nHe has attended various conferences and CDE programmes and has national publications to his credit. His field of interest is in Implant supported prosthesis. Presently he is working as a associate professor in the Dept of Prosthodontics, Rural Dental College, Loni and maintains a successful private practice specialising in Implantology at Rahata.\n\nEmail: drdeepak_mvikhe@yahoo.com..................",institutionString:null,institution:{name:"Pravara Institute of Medical Sciences",country:{name:"India"}}},{id:"204110",title:"Dr.",name:"Ahmed A.",middleName:null,surname:"Madfa",slug:"ahmed-a.-madfa",fullName:"Ahmed A. Madfa",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/204110/images/system/204110.jpg",biography:"Dr. Madfa is currently Associate Professor of Endodontics at Thamar University and a visiting lecturer at Sana'a University and University of Sciences and Technology. He has more than 6 years of experience in teaching. His research interests include root canal morphology, functionally graded concept, dental biomaterials, epidemiology and dental education, biomimetic restoration, finite element analysis and endodontic regeneration. Dr. Madfa has numerous international publications, full articles, two patents, a book and a book chapter. Furthermore, he won 14 international scientific awards. Furthermore, he is involved in many academic activities ranging from editorial board member, reviewer for many international journals and postgraduate students' supervisor. Besides, I deliver many courses and training workshops at various scientific events. Dr. Madfa also regularly attends international conferences and holds administrative positions (Deputy Dean of the Faculty for Students’ & Academic Affairs and Deputy Head of Research Unit).",institutionString:"Thamar University",institution:null},{id:"210472",title:"Dr.",name:"Nermin",middleName:"Mohammed Ahmed",surname:"Yussif",slug:"nermin-yussif",fullName:"Nermin Yussif",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/210472/images/system/210472.jpg",biography:"Dr. Nermin Mohammed Ahmed Yussif is working at the Faculty of dentistry, University for October university for modern sciences and arts (MSA). Her areas of expertise include: periodontology, dental laserology, oral implantology, periodontal plastic surgeries, oral mesotherapy, nutrition, dental pharmacology. She is an editor and reviewer in numerous international journals.",institutionString:"MSA University",institution:null},{id:"204606",title:"Dr.",name:"Serdar",middleName:null,surname:"Gözler",slug:"serdar-gozler",fullName:"Serdar Gözler",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/204606/images/system/204606.jpeg",biography:"Dr. Serdar Gözler has completed his undergraduate studies at the Marmara University Faculty of Dentistry in 1978, followed by an assistantship in the Prosthesis Department of Dicle University Faculty of Dentistry. Starting his PhD work on non-resilient overdentures with Assoc. Prof. Hüsnü Yavuzyılmaz, he continued his studies with Prof. Dr. Gürbüz Öztürk of Istanbul University Faculty of Dentistry Department of Prosthodontics, this time on Gnatology. He attended training programs on occlusion, neurology, neurophysiology, EMG, radiology and biostatistics. In 1982, he presented his PhD thesis \\Gerber and Lauritzen Occlusion Analysis Techniques: Diagnosis Values,\\ at Istanbul University School of Dentistry, Department of Prosthodontics. As he was also working with Prof. Senih Çalıkkocaoğlu on The Physiology of Chewing at the same time, Gözler has written a chapter in Çalıkkocaoğlu\\'s book \\Complete Prostheses\\ entitled \\The Place of Neuromuscular Mechanism in Prosthetic Dentistry.\\ The book was published five times since by the Istanbul University Publications. Having presented in various conferences about occlusion analysis until 1998, Dr. Gözler has also decided to use the T-Scan II occlusion analysis method. Having been personally trained by Dr. Robert Kerstein on this method, Dr. Gözler has been lecturing on the T-Scan Occlusion Analysis Method in conferences both in Turkey and abroad. Dr. Gözler has various articles and presentations on Digital Occlusion Analysis methods. He is now Head of the TMD Clinic at Prosthodontic Department of Faculty of Dentistry , Istanbul Aydın University , Turkey.",institutionString:"Istanbul Aydin University",institution:{name:"Istanbul Aydın University",country:{name:"Turkey"}}},{id:"256417",title:"Associate Prof.",name:"Sanaz",middleName:null,surname:"Sadry",slug:"sanaz-sadry",fullName:"Sanaz Sadry",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/256417/images/8106_n.jpg",biography:null,institutionString:null,institution:{name:"Istanbul Aydın University",country:{name:"Turkey"}}},{id:"240870",title:"Ph.D.",name:"Alaa Eddin Omar",middleName:null,surname:"Al Ostwani",slug:"alaa-eddin-omar-al-ostwani",fullName:"Alaa Eddin Omar Al Ostwani",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/240870/images/system/240870.jpeg",biography:"Dr. Al Ostwani Alaa Eddin Omar received his Master in dentistry from Damascus University in 2010, and his Ph.D. in Pediatric Dentistry from Damascus University in 2014. Dr. Al Ostwani is an assistant professor and faculty member at IUST University since 2014. \nDuring his academic experience, he has received several awards including the scientific research award from the Union of Arab Universities, the Syrian gold medal and the international gold medal for invention and creativity. Dr. Al Ostwani is a Member of the International Association of Dental Traumatology and the Syrian Society for Research and Preventive Dentistry since 2017. He is also a Member of the Reviewer Board of International Journal of Dental Medicine (IJDM), and the Indian Journal of Conservative and Endodontics since 2016.",institutionString:"International University for Science and Technology.",institution:{name:"Islamic University of Science and Technology",country:{name:"India"}}},{id:"42847",title:"Dr.",name:"Belma",middleName:null,surname:"Işik Aslan",slug:"belma-isik-aslan",fullName:"Belma Işik Aslan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/42847/images/system/42847.jpg",biography:"Dr. Belma IşIk Aslan was born in 1976 in Ankara-TURKEY. After graduating from TED Ankara College in 1994, she attended to Gazi University, Faculty of Dentistry in Ankara. She completed her PhD in orthodontic education at Gazi University between 1999-2005. Dr. Işık Aslan stayed at the Providence Hospital Craniofacial Institude and Reconstructive Surgery in Michigan, USA for three months as an observer. She worked as a specialist doctor at Gazi University, Dentistry Faculty, Department of Orthodontics between 2005-2014. She was appointed as associate professor in January, 2014 and as professor in 2021. Dr. Işık Aslan still works as an instructor at the same faculty. She has published a total of 35 articles, 10 book chapters, 39 conference proceedings both internationally and nationally. Also she was the academic editor of the international book 'Current Advances in Orthodontics'. She is a member of the Turkish Orthodontic Society and Turkish Cleft Lip and Palate Society. She is married and has 2 children. Her knowledge of English is at an advanced level.",institutionString:"Gazi University Dentistry Faculty Department of Orthodontics",institution:null},{id:"202198",title:"Dr.",name:"Buket",middleName:null,surname:"Aybar",slug:"buket-aybar",fullName:"Buket Aybar",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/202198/images/6955_n.jpg",biography:"Buket Aybar, DDS, PhD, was born in 1971. She graduated from Istanbul University, Faculty of Dentistry, in 1992 and completed her PhD degree on Oral and Maxillofacial Surgery in Istanbul University in 1997.\r\nDr. Aybar is currently a full-time professor in Istanbul University, Faculty of Dentistry Department of Oral and Maxillofacial Surgery. She has teaching responsibilities in graduate and postgraduate programs. Her clinical practice includes mainly dentoalveolar surgery.\r\nHer topics of interest are biomaterials science and cell culture studies. She has many articles in international and national scientific journals and chapters in books; she also has participated in several scientific projects supported by Istanbul University Research fund.",institutionString:null,institution:{name:"Marmara University",country:{name:"Turkey"}}},{id:"178412",title:"Associate Prof.",name:"Guhan",middleName:null,surname:"Dergin",slug:"guhan-dergin",fullName:"Guhan Dergin",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/178412/images/6954_n.jpg",biography:"Assoc. Prof. Dr. Gühan Dergin was born in 1973 in Izmit. He graduated from Marmara University Faculty of Dentistry in 1999. He completed his specialty of OMFS surgery in Marmara University Faculty of Dentistry and obtained his PhD degree in 2006. In 2005, he was invited as a visiting doctor in the Oral and Maxillofacial Surgery Department of the University of North Carolina, USA, where he went on a scholarship. Dr. Dergin still continues his academic career as an associate professor in Marmara University Faculty of Dentistry. He has many articles in international and national scientific journals and chapters in books.",institutionString:null,institution:{name:"Marmara University",country:{name:"Turkey"}}},{id:"178414",title:"Prof.",name:"Yusuf",middleName:null,surname:"Emes",slug:"yusuf-emes",fullName:"Yusuf Emes",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/178414/images/6953_n.jpg",biography:"Born in Istanbul in 1974, Dr. Emes graduated from Istanbul University Faculty of Dentistry in 1997 and completed his PhD degree in Istanbul University faculty of Dentistry Department of Oral and Maxillofacial Surgery in 2005. He has papers published in international and national scientific journals, including research articles on implantology, oroantral fistulas, odontogenic cysts, and temporomandibular disorders. Dr. Emes is currently working as a full-time academic staff in Istanbul University faculty of Dentistry Department of Oral and Maxillofacial Surgery.",institutionString:null,institution:{name:"Istanbul University",country:{name:"Turkey"}}},{id:"192229",title:"Ph.D.",name:"Ana Luiza",middleName:null,surname:"De Carvalho Felippini",slug:"ana-luiza-de-carvalho-felippini",fullName:"Ana Luiza De Carvalho Felippini",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/192229/images/system/192229.jpg",biography:null,institutionString:"University of São Paulo",institution:{name:"University of Sao Paulo",country:{name:"Brazil"}}},{id:"256851",title:"Prof.",name:"Ayşe",middleName:null,surname:"Gülşen",slug:"ayse-gulsen",fullName:"Ayşe Gülşen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/256851/images/9696_n.jpg",biography:"Dr. Ayşe Gülşen graduated in 1990 from Faculty of Dentistry, University of Ankara and did a postgraduate program at University of Gazi. \nShe worked as an observer and research assistant in Craniofacial Surgery Departments in New York, Providence Hospital in Michigan and Chang Gung Memorial Hospital in Taiwan. \nShe works as Craniofacial Orthodontist in Department of Aesthetic, Plastic and Reconstructive Surgery, Faculty of Medicine, University of Gazi, Ankara Turkey since 2004.",institutionString:"Orthodontist, Assoc Prof in the Department of Aesthetic, Plastic and Reconstructive Surgery, Faculty of Medicine, University of Gazi",institution:null},{id:"255366",title:"Prof.",name:"Tosun",middleName:null,surname:"Tosun",slug:"tosun-tosun",fullName:"Tosun Tosun",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/255366/images/7347_n.jpg",biography:"Graduated at the Faculty of Dentistry, University of Istanbul, Turkey in 1989;\nVisitor Assistant at the University of Padua, Italy and Branemark Osseointegration Center of Treviso, Italy between 1993-94;\nPhD thesis on oral implantology in University of Istanbul and was awarded the academic title “Dr.med.dent.”, 1997;\nHe was awarded the academic title “Doç.Dr.” (Associated Professor) in 2003;\nProficiency in Botulinum Toxin Applications, Reading-UK in 2009;\nMastership, RWTH Certificate in Laser Therapy in Dentistry, AALZ-Aachen University, Germany 2009-11;\nMaster of Science (MSc) in Laser Dentistry, University of Genoa, Italy 2013-14.\n\nDr.Tosun worked as Research Assistant in the Department of Oral Implantology, Faculty of Dentistry, University of Istanbul between 1990-2002. \nHe worked part-time as Consultant surgeon in Harvard Medical International Hospitals and John Hopkins Medicine, Istanbul between years 2007-09.\u2028He was contract Professor in the Department of Surgical and Diagnostic Sciences (DI.S.C.), Medical School, University of Genova, Italy between years 2011-16. \nSince 2015 he is visiting Professor at Medical School, University of Plovdiv, Bulgaria. \nCurrently he is Associated Prof.Dr. at the Dental School, Oral Surgery Dept., Istanbul Aydin University and since 2003 he works in his own private clinic in Istanbul, Turkey.\u2028\nDr.Tosun is reviewer in journal ‘Laser in Medical Sciences’, reviewer in journal ‘Folia Medica\\', a Fellow of the International Team for Implantology, Clinical Lecturer of DGZI German Association of Oral Implantology, Expert Lecturer of Laser&Health Academy, Country Representative of World Federation for Laser Dentistry, member of European Federation of Periodontology, member of Academy of Laser Dentistry. Dr.Tosun presents papers in international and national congresses and has scientific publications in international and national journals. He speaks english, spanish, italian and french.",institutionString:null,institution:{name:"Istanbul Aydın University",country:{name:"Turkey"}}},{id:"260116",title:"Dr.",name:"Mehmet",middleName:null,surname:"Yaltirik",slug:"mehmet-yaltirik",fullName:"Mehmet Yaltirik",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/260116/images/7413_n.jpg",biography:"Birth Date 25.09.1965\r\nBirth Place Adana- Turkey\r\nSex Male\r\nMarrial Status Bachelor\r\nDriving License Acquired\r\nMother Tongue Turkish\r\n\r\nAddress:\r\nWork:University of Istanbul,Faculty of Dentistry, Department of Oral Surgery and Oral Medicine 34093 Capa,Istanbul- TURKIYE",institutionString:null,institution:{name:"Istanbul University",country:{name:"Turkey"}}},{id:"171887",title:"Prof.",name:"Zühre",middleName:null,surname:"Akarslan",slug:"zuhre-akarslan",fullName:"Zühre Akarslan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/171887/images/system/171887.jpg",biography:"Zühre Akarslan was born in 1977 in Cyprus. She graduated from Gazi University Faculty of Dentistry, Ankara, Turkey in 2000. \r\nLater she received her Ph.D. degree from the Oral Diagnosis and Radiology Department; which was recently renamed as Oral and Dentomaxillofacial Radiology, from the same university. \r\nShe is working as a full-time Associate Professor and is a lecturer and an academic researcher. \r\nHer expertise areas are dental caries, cancer, dental fear and anxiety, gag reflex in dentistry, oral medicine, and dentomaxillofacial radiology.",institutionString:"Gazi University",institution:{name:"Gazi University",country:{name:"Turkey"}}},{id:"272237",title:"Dr.",name:"Pinar",middleName:"Kiymet",surname:"Karataban",slug:"pinar-karataban",fullName:"Pinar Karataban",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/272237/images/8911_n.png",biography:"Assist.Prof.Dr.Pınar Kıymet Karataban, DDS PhD \n\nDr.Pınar Kıymet Karataban was born in Istanbul in 1975. After her graduation from Marmara University Faculty of Dentistry in 1998 she started her PhD in Paediatric Dentistry focused on children with special needs; mainly children with Cerebral Palsy. She finished her pHD thesis entitled \\'Investigation of occlusion via cast analysis and evaluation of dental caries prevalance, periodontal status and muscle dysfunctions in children with cerebral palsy” in 2008. She got her Assist. Proffessor degree in Istanbul Aydın University Paediatric Dentistry Department in 2015-2018. ın 2019 she started her new career in Bahcesehir University, Istanbul as Head of Department of Pediatric Dentistry. In 2020 she was accepted to BAU International University, Batumi as Professor of Pediatric Dentistry. She’s a lecturer in the same university meanwhile working part-time in private practice in Ege Dental Studio (https://www.egedisklinigi.com/) a multidisciplinary dental clinic in Istanbul. Her main interests are paleodontology, ancient and contemporary dentistry, oral microbiology, cerebral palsy and special care dentistry. She has national and international publications, scientific reports and is a member of IAPO (International Association for Paleodontology), IADH (International Association of Disability and Oral Health) and EAPD (European Association of Pediatric Dentistry).",institutionString:null,institution:null},{id:"172009",title:"Dr.",name:"Fatma Deniz",middleName:null,surname:"Uzuner",slug:"fatma-deniz-uzuner",fullName:"Fatma Deniz Uzuner",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/172009/images/7122_n.jpg",biography:"Dr. Deniz Uzuner was born in 1969 in Kocaeli-TURKEY. After graduating from TED Ankara College in 1986, she attended the Hacettepe University, Faculty of Dentistry in Ankara. \nIn 1993 she attended the Gazi University, Faculty of Dentistry, Department of Orthodontics for her PhD education. After finishing the PhD education, she worked as orthodontist in Ankara Dental Hospital under the Turkish Government, Ministry of Health and in a special Orthodontic Clinic till 2011. Between 2011 and 2016, Dr. Deniz Uzuner worked as a specialist in the Department of Orthodontics, Faculty of Dentistry, Gazi University in Ankara/Turkey. In 2016, she was appointed associate professor. Dr. Deniz Uzuner has authored 23 Journal Papers, 3 Book Chapters and has had 39 oral/poster presentations. She is a member of the Turkish Orthodontic Society. Her knowledge of English is at an advanced level.",institutionString:null,institution:null},{id:"332914",title:"Dr.",name:"Muhammad Saad",middleName:null,surname:"Shaikh",slug:"muhammad-saad-shaikh",fullName:"Muhammad Saad Shaikh",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Jinnah Sindh Medical University",country:{name:"Pakistan"}}},{id:"315775",title:"Dr.",name:"Feng",middleName:null,surname:"Luo",slug:"feng-luo",fullName:"Feng Luo",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Sichuan University",country:{name:"China"}}},{id:"344229",title:"Dr.",name:"Sankeshan",middleName:null,surname:"Padayachee",slug:"sankeshan-padayachee",fullName:"Sankeshan Padayachee",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of the Witwatersrand",country:{name:"South Africa"}}},{id:"315727",title:"Ms.",name:"Kelebogile A.",middleName:null,surname:"Mothupi",slug:"kelebogile-a.-mothupi",fullName:"Kelebogile A. 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In recent years, emerging technologies such as multi-omics, high-throughput technologies, and genome editing tools could assist plant physiologists in unraveling molecular mechanisms in specific critical pathways. The global picture of physiological processes in plants needs to be investigated continually to increase our knowledge, and the resulting technologies will benefit sustainable agriculture.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/13.jpg",hasOnlineFirst:!0,hasPublishedBooks:!0,annualVolume:11409,editor:{id:"332229",title:"Prof.",name:"Jen-Tsung",middleName:null,surname:"Chen",slug:"jen-tsung-chen",fullName:"Jen-Tsung Chen",profilePictureURL:"https://mts.intechopen.com/storage/users/332229/images/system/332229.png",biography:"Dr. Jen-Tsung Chen is currently a professor at the National University of Kaohsiung, Taiwan. He teaches cell biology, genomics, proteomics, medicinal plant biotechnology, and plant tissue culture. Dr. Chen\\'s research interests include bioactive compounds, chromatography techniques, in vitro culture, medicinal plants, phytochemicals, and plant biotechnology. He has published more than ninety scientific papers and serves as an editorial board member for Plant Methods, Biomolecules, and International Journal of Molecular Sciences.",institutionString:"National University of Kaohsiung",institution:{name:"National University of Kaohsiung",institutionURL:null,country:{name:"Taiwan"}}},editorTwo:null,editorThree:null,series:{id:"10",title:"Physiology",doi:"10.5772/intechopen.72796",issn:"2631-8261"},editorialBoard:[{id:"313856",title:"Dr.",name:"Christophe",middleName:"F.E.",surname:"Hano",slug:"christophe-hano",fullName:"Christophe Hano",profilePictureURL:"https://mts.intechopen.com/storage/users/313856/images/system/313856.png",institutionString:"University of Orléans",institution:{name:"University of Orléans",institutionURL:null,country:{name:"France"}}},{id:"33993",title:"Dr.",name:"Jose Carlos",middleName:null,surname:"Jimenez-Lopez",slug:"jose-carlos-jimenez-lopez",fullName:"Jose Carlos Jimenez-Lopez",profilePictureURL:"https://mts.intechopen.com/storage/users/33993/images/system/33993.jpg",institutionString:"Spanish National Research Council",institution:{name:"Spanish National Research Council",institutionURL:null,country:{name:"Spain"}}},{id:"191770",title:"Dr.",name:"Mohamed A.",middleName:null,surname:"El-Esawi",slug:"mohamed-a.-el-esawi",fullName:"Mohamed A. 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