**1. Introduction**

Significant research is being conducted on the development of autonomy for underwater robotic vehicles, which are widely employed in many fields of application such as oceanographic, marine archeology [1], military organizations, and cable tracking and inspection [2].

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and eproduction in any medium, provided the original work is properly cited. © 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

The advent of underwater robotic vehicles has significantly reduced the dangers in deep sea exploration. Two kinds of robotic vehicles used in marine research are remotely operated vehicles (ROVs) and autonomous underwater vehicles (AUVs). The main difference between the two is that ROVs are connected to the ship by communication cables whereas AUVs operate independently from the ship. AUVs operate without an umbilical; therefore, AUVs are able to conduct a larger range of work area. In this research, AUV intelligent rescue system (AIRS) can minimize the loss of losing or unpredictable catastrophic failure of AUVs caused by emergency conditions.

In recent years, the micro-electro-mechanical system (MEMS) has almost become a vital technology for modern society because of its small volume, low power consumption, low cost, and ease of integration into systems or modification [3]. The MEMS technology creates entirely innovative kinds of products, such as gyroscope sensor in camera-shake detection systems [4], multi-axis inertial motion sensors for smartphone-based navigation [5], and rehabilitation systems based on inertial measurement units (IMUs) [6]. Additionally, the integration of global positioning system and inertial navigation system (GPS/INS) is usually employed to measure the position of AUVs [7, 8]. Unfortunately, small errors in the measurement of initial data are double integrated into larger errors progressively in attitude data, and such errors increase without bound. Error reduction calibration for initialization of INS is paramount for the systematic parameter, like scale factor, bias, and misalignment of the axes. As the situation depicted above, a calibration method is investigated and adopted in this research. There are many researches utilizing Kalman filter (KF) [9], complementary filter (CF) [10], adaptive Kalman filter (AKF) [11], or extended Kalman filter (EKF) [12] to fuse the gyroscope and accelerometer together, taking advantages of their individual strength. In this research, we use EKF to filter IMU outputs with a balance of noise canceling and adaptability simultaneously used in sensing attitude algorithm for AIRS.

The sensing algorithm with EKF for sensing the attitude of AUV, while employing the backpropagation network (BPN) to classify motion data that are formed in the AUV. Before classify the data, there is a problem. The problem is compounded by the fact that our system is computationally complex due to values estimation of AUV and causes the high dimension that is called "curse of dimensionality," which donates the drastic rise of computational complexity and the classification error. Therefore, the step of feature extraction (FE) is an important procedure in data classification [26]. Further, we feed the data into eural network to distinguish every AUV motion in each operating period. The neural network consists of multiple artificial neurons to receive inputs, and process them to obtain an output [13]. By repeating amendments to the model weights, the neural network makes central processing unit (CPU) more logical to calculate the nonlinear systems of AUV motion [14]. The neural network has been widely used because of a number of advantages, including estimating which variables are important in classification, detecting possible interactions between predictor variables, and constructing the prediction model with a high accuracy rate. Furthermore, the neural network has emerged as an important tool in classification which has been investigated in many different important applications [15]. In this study, neural network classifier (NNC) is used in the calculation of nonlinear systems AUV attitude data to detect a catastrophic failure of an AUV. Based on the multilayer feed-forward backpropagation algorithm as NNC, we proposed an effective activity recognition method using 10-DOF sensor module.

The concept of AIRS is inspired from the vehicle safety device: airbags have a flexible fabric bag that can protect and restrict the occupant from being thrown away during a crash accident [16, 17]. Wang and Dragcevic designed the airbags, which fire via a small pyrotechnic charge to increase motorcyclists' safety protections when riding a motorcycle [18, 19]. The airbags are applied to not only fall-protection devices but also automatic inflatable life buoy by the inflatable method of a gas cylinder [20–23]. We extended the airbag systems to load on the AUV with CO2 cylinder to implement the AIRS. In this research, we developed a malformed detection algorithm for AUV with both EKF and BPN, and the implementation of the airbag system loaded on AUV is underway.


2.6.4. Viscosity

Viscosity of nanoemulsions was measured at di fferent angular velocities at a temperature of 25 ◦C using the Brookfield synchro-Lectric viscometer (LVDVI prime, Middleborough, MA, USA).

### *2.7. Transmission Electron Microscopy (TEM)*

Structural morphology of nanoemulsion droplets was investigated with TEM (Tecnai 20, Philips, Holland, OR, USA) operated at 200 kV and of a 0.15 nm e fficient in comprehensive resolution. The bright field imaging technique with high magnification and di ffraction modes was used to examine the morphology and structure of the nanoemulsion globules [15]. TEM imaging was carried out by staining a drop of the nanoemulsion with phosphotungstic acid solution (2% *w*/*v*) and directly placing on the copper grids, subsequently dried at room temperature (25 ± 2 ◦C).

### *2.8. In Vitro Release*

The drug release studies were performed employing a vertical Franz di ffusion cell having an effective surface area of 1.13 cm2 and simulated tear fluid (pH 7.4) as the dissolution medium [16]. Briefly, 1 mL of nanoemulsion (equivalent to 5 mg of moxifloxacin per ml) or drug solution (control) in the stimulated tear fluid was taken on a previously soaked cellophane dialyzing membrane (MWCO 12–14 kDa, Spectra/por ® Spectrum Laboratories Inc., Rancho Dominguez, Berkeley, CA, USA) that separates the donor and receptor cell. The entire assembly was kept on a thermostatically controlled water bath set at 37 ± 0.5 ◦C and receptor medium was stirred at 50 rpm. Aliquots of sample (1 mL) were drawn at regular time intervals (0.5, 1, 2, 3, 4, 5 and 6 h) and replaced with the same volume of fresh media. The samples were subsequently diluted and analyzed for moxifloxacin content by HPLC. The data were analyzed to determine correlation coe fficient (*r*2) and release kinetics using various mathematical models [17];

where *Q* represents quantity of drug released in time *t*, *Q*0 represents value of *Q* at zero time, *k* represents the rate constant, *n* represents the diffusional exponent, *a* represents the time constant and *b* represents the shape parameter. The correlation coefficient (*r*2) and the order of release pattern was calculated in each case.

### *2.9. Ex Vivo Permeation*

The permeation studies were carried out using the Franz diffusion cell with a standard setup previously used in our earlier study [18]. Briefly, optimized formulation (MM3) or control (commercial eye drops; Vigamox™) (equivalent to 5 mg of moxifloxacin per mL) was placed in donor compartment and simulated tear fluid (pH 7.4) in the receptor compartment. Between donor and receptor compartment, the isolated rabbit cornea membrane was placed. The temperature of the medium was maintained at 37 ± 0.5 ◦C by the circulation of warm water through the outer jacket. Samples were withdrawn at predetermined time intervals (up to 6 h) and the same volume of fresh medium was replaced. The withdrawn samples were diluted and analyzed by HPLC.


**1. Introduction**

Liver transplantation (LT) is the only effective treatment for patients with endstage liver disease (ESLD). The first successful pediatric LT was performed by Thomas Starzl in 1967 on a child with biliary atresia (BA). This marked the beginning of the use of LT in pediatric practice [1, 2]. By 2020, the total number of LTs performed was about 32,000 per year, 7–8% of which were pediatric transplant surgeries [3].

In the Russian Federation, the first pediatric LT was performed in 1997. Today, the total number of transplantations performed has exceeded 1000. The need for this type of medical care is fully satisfied in Russia. The LT program is being implemented at Shumakov National Medical Research Center of Transplantology and Artificial Organs (Shumakov Center), Russia's leading transplant center; over 100 LTs are

performed annually. Surgeries are performed in children with extremely low body mass, starting from the first months of life.

Invasive diagnostic procedures, such as needle biopsy, carry high risks for young children with low body mass. Therefore, it is an urgent task to search for markers for the development of noninvasive methods of assessing liver graft function. Given physical developmental delays in children, which are associated with hepatobiliary diseases and subsequent hormonal dysregulation, GH and IGF-1, the key elements in neurohumoral control of liver function can serve as important indicators reflecting the outcome of LT. The significance of GH and IGF-1 in pediatric LT is related to the role of hormones in the regulation of growth and body mass, their influence on hepatocyte function and immune system activity. A number of studies have shown the relationship between the GH/IGF-1 axis and recipient/graft survival [4–6].

Despite the large number of studies on the role of the GH/IGF-1 axis in children and adults, none of them are devoted to their relationship with physical development in children after LT [7–9]. The study of the role of the GH/IGF-1 axis in the neurohumoral regulation of liver graft function in young children is an important task. It may allow to assess the functional ability of the graft by noninvasive methods and will also create a vector for coming up with personalized therapy. This chapter describes the impact of the GH/IGF-1 axis on the outcome of pediatric LT (namely the clinical significance of the GH/IGF-1 axis in pediatric liver recipients) and characterizes its relationship with patients' anthropometric parameters.


*2.1. Data Collection*

The system uses several mechanisms to collect information from and about the users. Below, we describe how questionnaires as well as sensor measurements are used to understand the user behavior.


*4.9.1 Musa paradisiaca L.*

*M. paradisiaca* is an herbaceous plant that grows up to about 9 m with a robust treelike false-stem. The unripe fruits and juice of *M. paradisiaca* is used in folk medicine to treat and manage diarrhea, dysentery, cholera, intestinal lesions, ulcerative colitis, diabetes, sprue, uremia, nephritis, gout, hypertension, cardiac disease, otalgia and hemoptysis [94, 95]. The flowers are also employed in treating dysentery, diabetes and menorrhagia [94]. The root is also used traditionally as an anthelmintic [95], for treating blood disorders and venereal diseases [94]. It is also used as an anti-inflammatory, analgesic and anti-dote for snakebites [96].

The green fruits of *M. paradisiaca* has been reported to possess anti-hypertensive [97] as well as hypoglycemic effect due to effects on insulin production and glucose utilization [98]. *M. paradisiaca* inhibits cholesterol crystallization in vitro [99]. *M. paradisiaca* has also been shown to induce atherosclerosis [100]. There have been reports of the potential of *M. paradisiaca* flower to enhance milk production of nursing rats [101, 102]. Serotonin, nor-epinephrine, tryptophan, indole compounds, tannin, starch, iron, crystallisable and non-crystallisable sugars, vitamins, albuminoids, fats, mineral salts have been found in the fruit pulp of *M. paradisiaca*  [94] with several other compounds that have been isolated and identified from various parts of the plant [103].


*2.12. Eicosanoid Profiling*

The concentrations of eicosanoids were assessed in pooled liver lysates (fibrocyte-ablated-, control-, and supercontrol-group, *n* ≥ 8 per group) via LC-MS/MS as described before [47].