**Abstract**

Ethnobotany is a life science which studies the interaction between human beings and flora in particular and broadly deals with the investigations, observations, and identifications of botanical diversity used for the prevention and treatment of human and livestock ailments. The current chapter reviews the history and development of ethnobotany and the involvement of this branch of science in the innovation and derivation of drug products which is originated from plants and claimed by the traditional healers and indigenous people used for the prevention and treatment of disease. This chapter also combines interdisciplinary and multidisciplinary methods that can lead to further productive, comprehensive, and systemic guesstimates in the investigation of the relationship between the plants and humans. Regardless of its various bottlenecks, ethnobotany becomes an attractive and hopeful area of research. It also covers ethnobotanical knowledge and modern science, ethnobotany research and their applications, plant conservation and sustainable management practices, taxonomy, and economic botany. The chapter also deals with the ways in which different societies and cultures have come to perceive, know, use, classify, and symbolically represent plants and animals.

**Keywords:** ethnobotany, ethnobiology, ethnoecology, ethnomedicine, herbal medicine, ethnopharmacology, natural products, medicinal plants


*3.3. Data Description*

Two hundred and eighty prefecture-level cities in China are the subject of the data in this paper, which involve a total of 21 variables in the fields of energy, tourism, environment, and economy; the data collection was challenging; most city statistics were not updated in a timely manner, leading to a significant amount of missing data in 2020; and artificially completing the data would interfere with the validity of the research findings. Likewise, the pace of China's tourism development has slowed down dramatically as a result of the new crown pandemic, taking into account that force majeure circumstances will compromise the validity of the findings and have a negative influence on tourism's contribution to the green economy. Given the aforementioned justifications, based on the availability and consistency of data, this paper selects the relevant data of 280 cities in 30 provinces from 2007 to 2019, excluding the data of Tibet, Hong Kong, Macao and Taiwan. Due to the long period and the change in some city data, this paper takes 2019 prefecture-level cities as the benchmark, excludes the data of merged cities, and retains the data related to the removal of counties and promotion of cities. The relevant data are obtained from *The China City Statistical Yearbook, China City Construction Statistical Yearbook, China Energy Statistical Yearbook* and *Tourism Statistical Yearbook* of each city. Carbon emission data were calculated based on county-level data from the literature. The list of pilot low-carbon cities is based on the list announced by the National Development and Reform Commission. To avoid the interference of multicollinearity and pseudo-regression, the VIF test and unit variance test were conducted on the panel data, and the results showed that the variance inflation factor of the panel data was less than three, and they all passed the LLC test and Fisher-ADF test at the 1% significance level, so there was no multicollinearity problem, and the data were smooth. In addition, the effect of heteroskedasticity was eliminated by taking the logarithms of all variables.


*4.1. The Typology of Values*

Values, apart from being a set of belief systems or culture, are the core instruments in expressing, interpreting, and understanding viewpoints in the planning process. They also represent a core embedment of the planning experience from conceptualisation to the outcome and its monitoring and further alterations in plans.

Further, each of these four main elements or dimensions (in Figure 2) produces particular *core values* that enable the operation of spatial planning (as a comprehensive process) and the creation of preconditions for further changes in land use and space through spatial development. The interrelation between these four dimensions manifests in six types of core values that influence spatial planning. Based on developed useful classifications and assessments' approaches, the typology of *spatial (territorial) values* is proposed (in Table 1).

**Table 1.** Values and their characteristics.

"Spatially allocated values are the ones that may be recognised spatially as both provided by ecosystems and human-made formations. Ecosystems, e.g., agricultural and forest land and ecological landscapes, are an essential part of natural capital. Their quality is the basis for environmental viability. However, the impact of human beings on ecosystems is considerable. Ecosystems provide humans with services that are relevant for survival, health, and welfare/culture. Human-made formations, e.g., developments, improvements, and utility supply, are an essential part of human-made capital. Its quality is the basis for socio-economic equity. Human-made formations provide humans with services that are relevant for dwelling, workplace, and recreation.


*Article* **Homoepitaxy Growth of Single Crystal Diamond under 300 torr Pressure in the MPCVD System**

#### **Xiwei Wang 1, Peng Duan 1, Zhenzhong Cao 2, Changjiang Liu 2, Dufu Wang 1,2, Yan Peng 1,\* and Xiaobo Hu 1,\***

Received: 30 October 2019; Accepted: 26 November 2019; Published: 28 November 2019

**Abstract:** The high-quality single crystal diamond (SCD) grown in the Microwave Plasma Chemical Vapor Deposition (MPCVD) system was studied. The CVD deposition reaction occurred in a 300 torr high pressure environment on a (100) plane High Pressure High Temperature (HPHT) diamond type II *a* substrate. The relationships among the chamber pressure, substrate surface temperature, and system microwave power were investigated. The surface morphology evolution with a series of different concentrations of the gas mixture was observed. It was found that a single lateral crystal growth occurred on the substrate edge and a systemic step flow rotation from the [100] to the [110] orientation was exhibited on the surface. The Raman spectroscopy and High Resolution X-Ray Diffractometry (HRXRD) prove that the homoepitaxy part from the original HPHT substrate shows a higher quality than the lateral growth region. A crystal lattice visual structural analysis was applied to describe the step flow rotation that originated from the temperature driven concentration difference of the C2H2 ion charged particles on the SCD center and edge.

**Keywords:** single crystal diamond; Homoepitaxy growth; 300 torr

#### **1. Introduction**

Diamond is gaining more attention for its outstanding optical, electrical, mechanical, and thermal properties. Since the first successful synthesis of diamond by General Electric more than half a century ago, diamond has attracted researchers to develop new growth technologies and extend multiple applications. Currently, High Pressure High Temperature (HPHT) and Microwave Plasma Chemical Vapor Deposition (MPCVD) technologies are widely used to manufacture large, single crystal diamonds with good quality and clarity. High-quality single crystal diamond (SCD) is available in superhard cutting tools, optical components, semiconductor and high-power electronics, and even in quantum applications [1–4].

Although the HPHT method still produces the overwhelming majority of a single crystal diamond, the metallic impurity incorporation and high dislocation density in crystal edges limits its further application in the semiconductor and quantum field. MPCVD technology has become a mature and reliable method for high quality SCD growth since it has the advantages of the control of the nitrogen concentration and dislocation density [5]. Many studies have indicated that the surface morphology, growth rate, and crystal quality depend on the internal reaction chamber structural parameters such as the substrate holder, input gas mixture, and chamber pressure. Accordingly, the growth mechanism of high quality SCD was proposed. Qi Lang et al. reported a growth rate of 165 μm/h by doped nitrogen into the reaction chamber [6]. Nad et al. compared different sizes of pocket holders to control the substrate surface morphology under a chamber pressure of 240 torr. Silva et al. showed

that increasing the process pressure can increase the diamond growth rate and improve the crystal quality [7,8]. F. Lloret studied the stratigraphy of SCD lateral growth on a three-dimensional structure and designed a geometric model for the growth sector configuration [9–11]. Among these, the reaction pressure plays an important role in the overall carbon deposition and homoepitaxy growth because it determines the shape, distribution, and available area of the activated plasma. Due to the limitation of the CVD system parameter, achieving high chamber pressure during the growth meets a particular set of problems and uncertainties [12]. Most research studies have reported that pressure was controlled in a range of 100–250 torr [13–15] during diamond crystal growth. Growth pressures higher than 250 torr are still rarely seen.

In this study, we focused on SCD growth under a reaction pressure of 300 torr. The surface morphology and growth rate were studied in order to optimize the growth rate to ensure the crystal quality.

#### **2. Materials and Methods**

#### *2.1. Preparation of the CVD Diamond Substrate*

High quality HPHT diamond crystal, which is 7 × 7 mm in size, was grown in a cubic press system by Jinan Diamond Technology Co., Ltd. The origin diamond was type I *b* with a nitrogen concentration of about 1019/cm3, as measured by Secondary Ion Mass Spectroscopy (SIMS) from EAG laboratories (Shanghai China) [16]. After the HPHT growth, the diamond crystal was boiled in the mixed solution of perchloric acid, sulfuric acid, and hydrochloric acid for 3 h to remove the dirt covered on the crystal surface (All the above acids are from Aladdin, Shanghai, China). The HPHT diamond substrate plate was cut parallel to the (100) surface by the laser sawing system. The substrate was 5.97 mm × 5.57 mm in size, and the thickness was 0.61 mm. Mechanical polishing was applied to remove the surface cracks generated during the sawing process. Ultrasonic cleaning of the methanol and acetone separately for half an hour was used to remove the organic substances on the surface of the substrate.

#### *2.2. The Etching of the CVD Single Crystal Substrate*

To achieve a nitrogen-free growth environment during the entire process, the chamber was evacuated to 0.1 torr by dry pump before the supply of the hydrogen. Etching was followed for half an hour under 300 torr pressure and 900 ◦C in a pure hydrogen environment to remove the impurities and defects caused by the mechanical polishing.

#### *2.3. Growth Parameter Investigation*

After the etching, the CVD diamonds were grown on the substrates with different parameters including the temperature, pressure, and methane concentration. The relationship between the temperature, pressure, and microwave power was studied systematically to understand the system's plasma energy distribution and absorbance. All diamond substrates were laser cut to 0.5 mm thickness and grown in the reaction chamber with a methane concentration of 3%.

The surface morphology and growth rate were investigated at different methane concentrations under a pressure of 300 torr and 1150 ◦C with hydrogen flow at 600 sccm for 4 h of growth. The methane concentration was varied from 2% to 5% in order to get an acceptable surface morphology and growth rate to optimize the SCD growth.

#### *2.4. The Growth of the CVD Diamond Layer*

After that, the SCD layer was grown for 4 h after hydrogen etching of the substrate at 900 ◦C for half an hour. The chamber pressure was 300 torr, while the substrate temperature was kept at 1150 ◦C with a gas mixture of CH4:H2 to 18:600 sccm. During the CVD reaction, the thickness of the sample increased and approached the lower edge of the plasma. The substrate surface temperature increased, which changed the thermodynamics balance for the carbon deposition and hydrogen etching. A thermo

pyrometer was used to measure the in situ substrate temperature. Since the sample thickness increases during the CVD reaction, the self-control recipe mode was activated during the growth period in order to self-adjust the input microwave power to maintain the substrate surface temperature through the feedback of the thermo pyrometer. The temperature variation range was less than 10 ◦C throughout the whole period of growth.

#### *2.5. The Surface Morphology and Crystal Quality Analysis*

A confocal laser scanning microscope OLS-4000 from Olympus (Tokyo, Japan) was employed to examine the top surface morphology of the diamond. Single crystal quality was assessed via HRXRD by D8 Discover operating with CuKα1 radiation with an anode on a fixed power supply at 40 kV/40 mA from Bruker. The room temperature Raman spectra were obtained by the LabRAM HR800 system of Horiba Jobin Yvon (Paris, France) with a 514 nm solid laser as the excitation source to determine the phase structure.

#### **3. Results and Discussion**

#### *3.1. CVD System for SCD Growth*

The System type Ardis 300 is equipped with a 2.45 GHz/6 kW microwave reactor by Optosystems Ltd. The microwaves enter the reaction chamber through the quartz window from the corn shape guide beneath the sample stage. Figure 1 shows a schematic diagram of the structure of the Ardis 300 reaction chamber. The sample stage is made of copper with water channels inside to allow cooling during the reaction. A molybdenum plate is placed on the top of the stage and a specially designed closed type sample holder is located in the center for the substrates [8,17]. Quartz windows are implanted into the stainless steel chamber shell on the top and side wall for inspection. A double interference infrared radiation thermo pyrometer is installed to measure the temperature of the substrate with an emissivity of 0.1 through a slit of 2 mm. In order to get a real-time substrate temperature measurement during the deposition reaction, the system was managed to carve a guide channel hole throughout the encircled ring, which is parallel to the ring surface. The pressure of the reactor was able to reach a maximum of 300.0 torr with an accuracy of 0.1 torr.

**Figure 1.** Schematic diagram of the Ardis 300 reaction chamber. The red rectangle on the Mo holder represents the High pressure High Temperature (HPHT) diamond substrate, and the green arrow stands for the direction and for the microwave transmission path.

#### *3.2. The Influence of the Chamber Pressure on the Microwave Power and Substrate Temperature*

The chamber pressure plays a significant role in determining the growth rate, morphology, and crystal quality prominently in terms of the homoepitaxy and lateral growth during the CVD reaction. In order to obtain optimized parameters for homoepitaxy growth, a stable thermal and electromagnetic field should be guaranteed by considering a series of deposition parameters such as microwave power, chamber pressure, and methane concentration. Figure 2a shows the relationship between microwave power and substrate temperature under different chamber pressures from 200 to 300 torr for Ardis 300. The results indicate that, under the same pressure of the reaction chamber, the substrate temperature increases linearly with the microwave power. The slopes under the different chamber pressures are calculated and fitted in Figure 2b. The slope of the curve increases from 0.134 (200 torr) to 0.234 (300 torr). The fitting curves follow the exponential function calculated as:

$$\mathbf{y} = 0.13 + 6.2 \times 10^3 \mathbf{e}^{\left[\frac{(\mathbf{x} - \mathbf{1} \partial \mathcal{J} \mathcal{S} \mathcal{J})}{36.64}\right]}.\tag{1}$$

**Figure 2.** (**a**) Relationship of the microwave power to the substrate temperature during the CVD growth under different high chamber pressures. The chamber pressure varied from 200 to 300 torr. (**b**) Calculated slopes of the curve from Figure 2a at different chamber pressures with fitting. Two photos of the plasma were captured throughout the inspection window under 3800 kW, 1150 ◦C, 220 Torr, and 300 Torr, separately.

The entire CVD deposition reaction system is a strong self-adaption multi-field environment with different plasma particles generated by the microwave discharge in the chamber. The movement of all deposition-related ionized particles is violently affected by the constantly changing compound electromagnetic field provided by the reactor, which leads to different transmissions of the particles throughout the plasma generation to the deposition position on the diamond substrate. As the chamber pressure increases, the effective availability of the microwave increases to promote the methane and hydrogen to discharge, which causes a dynamic acceleration for both the carbon deposition and etching because of the different partial pressures [18]. The surface temperature difference of the substrate acts as the driving force for the material transformation in the thermodynamic routine. The present experimental result indicates a significant increase in the magnitude of the slope of microwave power over the substrate temperature since the reaction pressure increases. It reveals that there is enormous potential for plasma discharge absorption for the supplied power in an even higher pressure environment (over 200 torr).

The plasma photos in Figure 2b were captured under the same microwave power of 3800 W and temperature of 1150 ◦C. It shows that the plasma diminished in size and brightened in color from 220 to 300 torr separately. In this procedure, the plasma energy density increases. As a consequence, the charged concentration of the carbon-atom-related growth species such as CH3 and C2H2 increases. No clear point microwave discharge around the substrate and Molybdenum ring edge was found during the pressure change in the deposition reaction. The temperature gradient will be changed accordingly and will bring a different thermodynamic approach to the substrate homoepitaxy and the edge lateral overgrowth [19].

#### *3.3. The Influence of the Methane Concentration on the Morphology and Growth Rate*

As the only carbon atom provider, the methane concentration is particularly emphasized for the SCD growth with the CVD method. The optimal methane concentration leads to a polycrystalline-free layer surface with high quality and an acceptable growth rate. Besides the growth rate, another significant parameter, known as the edge boundary of the substrates, should be fully considered, which requires a controllable, sequential, and well organized epitaxial lateral overgrowth to exclude the growth of the polycrystalline. Several typical surface morphologies are exhibited in Figure 3 for methane concentrations from 2.0% to 5.0%. Harris and Goodwin [17,20] described the CVD diamond growth reaction using a simple model in which the growth rate depended on a metastable competition between the hydrogen etching and the methyl radical deposition. Figure 4 shows the relationship between the methane concentration and the growth rate, which were obtained at a pressure of 300 torr and 1150 ◦C and a hydrogen flow of 600 sccm throughout the entire experiment. An almost linear relationship for the methane concentration with the growth rate was present. When the methane concentration was 2%, which shows a recessive role in the competition, the substrate exhibited a multi-hole structure with plenty of etch pits on the diamond surface. The violent etching reaction restrained the appearance of the homoepitaxy step growth, which corresponded to a low growth rate of about 15.6 μm/h. When the methane concentration increased to 3%, the surface showed parallel and regular growth steps flow along the [100] direction, which indicates a well-controlled equilibrium of the carbon transportation to the substrate from the charge plasma and, meanwhile, indicates an organized arrangement of carbon atoms. As the methane concentration increased gradually, polycrystalline appeared and the different domains were present on the surface.

The surface was severely covered with the disordered polycrystalline scale clusters when the methane concentration increased to 5%, which proves that over-dosed methane led no approach to a compromised diamond quality, even though this sample achieved a high growth rate of 51 μm/h.

In order to obtain a higher quality homoepitaxy of a single crystal diamond layer with a reasonable growth rate, we decided to limit the methane concentration to 3% during the deposition growth.

**Figure 3.** Surface morphology evolution of the substrates grown under the environment of CH4:H2 at 2.0%, 3.0%, 4.0%, and 5.0%. The substrates were grown at 1150 ◦C and 300 torr. The images were captured by the confocal laser scanning mode of the confocal laser scanning microscope.

**Figure 4.** Relationship between the methane concentrations versus the deposition growth rate. The growth rate was calculated by the average measurement of the four corners and center after the growth and divided by the time. The red line is the fitting curve of the dot distribution.

#### *3.4. The Homoepitaxy Growth of the Single Crystal Diamond*

After determining the temperature, pressure, and the methane concentration, we tried to optimize the reaction parameter to achieve a high-quality CVD single crystal homoepitaxy diamond layer. The average growth rate was 27.12 μm/h, which almost matches the result we obtained from Figure 4.

Figure 5a is an image of the diamond surface taken by the confocal laser scanning microscope. Most of the surface area is covered with a regular step flow. Several large dark inclusions can be observed in the center of the sample, which represents the metal compound catalysts left in the crystal during the HPHT growth. The light yellow boundary shows the original HPHT diamond substrate edge beneath the as-grown sample. Lateral growth can be clearly observed by comparing the edge of the sample with the HPHT substrate boundary. Figure 5b–d show the photos captured in the laser scan mode. Two domains can be observed from Figure 5b,c in different positions of the sample. The center domain steps are along the [100] orientation, which can be easily observed on the surface of SCD homoepitaxy layers. The step width is about 10–16 μm. However, the steps on the edge domains go along the [110] orientation with a width of around 18–26 μm. Clear step merging along the [110] orientation can be observed on the edge lateral growth. After comparing the diameter of the as-grown sample with the original substrate before and after the growth, we confirmed that the [100] orientation domain on the edge is generated by the lateral growth. The right edges in Figure 5b show the generation of the polycrystalline. The polycrystalline can become an induction of the un-epitaxial features on the edges and corners and leads to the formation of asymmetric nuclei, which exhibit the pyramid structure revealed in the red block [21,22]. Shreya Nad et al. reported that the non-uniform surface temperature shall be generated at the sharp edges of the substrate during the CVD growth. This phenomenon may be caused by the difference in the plasma density in the corresponding ambient region between the substrate, holder surface, and the local heat transmission to the cooling water, which leads to the generation of higher index symmetric planes such as (110) and (111) in pyramid structures or polycrystalline [7].

Figure 5d shows the crack along the [100] direction, which may be caused by the metal inclusion. A. Ababou et al. reported that metal inclusions play a role in the CVD homoepitaxy growth by accelerating the formation of the sp2 phases because of non-epitaxial growth. The dislocations brought by the metal inclusions will be propagated from the center of the substrate to the epitaxy layer throughout the entire growth process even if they are concealed inside. The stress will be relieved as the defects accumulate to generate enough lattice mismatch before breaking and cracking [23].

**Figure 5.** (**a**) Image of the entire diamond substrate surface after 4 h of growth at 300 torr/1150 ◦C, CH4:H2 = 16:600 sccm. Three detailed images are labeled as positions 1, 2, and 3. (**b**) The image of the sample of 50× amplification at position 1. The red box reveals the pyramid structure in the edge neighboring the polycrystalline. (**c**) The image of the 50× amplification at position 2. (**d**) The image of the 50× amplification at position 3 with a deep crack in the center. The red arrows show the direction of the step flow.

#### *3.5. CVD Homoepitaxy Growth Diamond Quality*

In order to understand the quality of the homoepitaxy layer and the lateral edge, we measured the rocking curves of the High Resolution X-Ray Diffractometry (HRXRD) and Raman spectra of the samples. Figure 6a shows the X-Ray Diffractometry (XRD) rocking curves of (400) reflection on different sections of the CVD substrate. The section positions are labeled from 1 to 7 corresponding to those points on the substrate. The distance between two measured points is 1 mm. Since the distance of the SCD layer in the labeled direction was about 6.13 mm, points 1 and 7 were on the lateral edges, and points 2 to 6 were on the homoepitaxy layer from the original substrate, as designed. The FWHM values of the rocking curve of points from 1 to 7 are shown in Figure 6b. The layer structural quality is similar to that of points 2 to 6. The FWHM values of the rocking curve for homoepitaxy layer were about 57–59" while those of the edge section were 86.98" and 70.98" at points 1 and 7, respectively. The measurement was accomplished in a high-intensity configuration of the variable slit mode and indicates a high uniformity on the homoepitaxy growth and an imperfect crystalline quality on the lateral edges. Figure 7 shows the Raman spectra of the CVD layer at positions 1 and 4, which represents the structural quality of the homoepitaxy and lateral sections. Two spectra are dominated by a single sharp peak at 1332.43 cm−1, which reveals that the internal stress did not increase by an order of magnitude. No peak related to the sp2 carbon phase can be observed. The full width at the half maximum (FWHM)

value of point 1 is somewhat larger than that of position 4, which indicates higher residual stress on the lateral edges than in the center. This matches the XRD rocking curve result. This means that the stress around position 4 is smaller than that of point 1. Both of the XRD rocking curves and Raman spectra prove that the sample layer shows a high crystal quality in both the center and edge parts of the sample, while the homoepitaxy region inherited from the HPHT substrate presents a high crystal quality with fewer defects and low internal stress compared with the edge overgrowth.

**Figure 6.** (**a**) HRXRD rocking curve of the (400) direction symmetric reflections of the location points from 1 to 7. The distance of each neighbor point was designed to be 1 mm. As a result, points 1 and 7 were located on the lateral growth area of the CVD layer. (**b**) The XRD FWHM of the location positions from points 1 to 7.

**Figure 7.** Raman spectrum of the CVD homoepitaxy layer at room temperature, the black and red lines correspond to location points 1 and 4, respectively.

#### *3.6. Crystal Lattice Visual Structure Analysis of the Step Flow Rotation*

In order to understand the growth mechanism of the homoepitaxy and lateral growth as well as the step flow rotation on the edges, diamond lattice structure analysis was used to describe what happened on the edges. Figure 8a shows the basic double unit cells of the carbon atom's cubic region at the center of the face during diamond phase formation. The blue atoms form the (100) unit face while the red ones are in (110) faces. After the deposition of the (100) surface, following the original step flow, the step flow rotates 45◦ in the [110] direction on the edge of the sample. Figure 8b simulates the step flow of the CVD sample edge to describe the appearance of the step rotation. The black atoms are on the sample surface linked by the blue lines, forming the [100] orientation step surface. The green surface represents the (110) surface. Alexandre Tallaire et al. reported this phenomenon generated from the (100) face to the (110) face on the lateral side, which is almost the same as our result of the transformation of the step flow. Their team explained that the face rotation should evolve due to the temperature difference between the center and the edge [13,24]. E.V. Bushuev et al. also considered the dependence of the diamond epitaxial growth rate on the substrate temperature. They predicted that the microwave power would play a minor role in the growth kinetics via the plasma distribution [25]. C.C. Battaile et al. reported the CH3 and C2H2 groups are the main source for the growth of the (100) and (110) surfaces, respectively, during the CVD diamond deposition. Furthermore, acetylene is particularly important for aiding in the formation of multi-carbon clusters on the nuclei on the different orientation surfaces [26,27]. In sum, we predict that the step flow rotation of our sample was caused by the anomalous distribution of the C2H2 on the substrate surface. Different from the CH3 guided nuclei, which dominated the primary surface for the crystal growth, for the C2H2 guiding mode, two carbon atoms were first combined to form a double bond bridge onto the ravine of the (110) surface before further deposition, which resulted in a 45◦ guide to the lattice formation. As a result, the generation of the C2H2 cluster needed extra time and energy to generate equivalent growth on the (110) surface. The thermodynamic of the growth of the center and edge of the sample were driven by the temperature gradient provided by the optimized microwave plasma. The higher temperature of the edge provided the required surface energy for the growth of the (110) surface. According to the Gibbs–Wulff principle, the (110) plane has a lower surface free energy than that of the (100) surface. Meanwhile, it has a lower growth rate as well [24]. As the time elapsed during the reaction, the (110) surface was found to have a lower surface energy level than that of the (100) surface on the edge and lateral growth regions. Additionally, the lower growth rate of the (110) surface led to the step merging at the rotation site from the [100] to [111] steps. Similar morphology can be observed in Figure 5d because of the poor thermo conductivity of the surface crack. The temperature on the crack edge was higher than that of the other regions. It may have also been caused by the plasma point charge.

**Figure 8.** (**a**) Atom lattice visual structure of the diamond double unit molecule cell. The green lines are links of the carbon molecules on the (100) surface. The red lines are the (110) surface. (**b**) The lattice visual structure indicates the edge rotation transformation from the direction [100] to [110]. The black atoms are the carbon atoms on the surface of the substrate. The blue lines contact the atoms on the (100), (010), and (001) surfaces. The green lines link the carbon atoms and form the faces vertical to the [110] direction.

#### **4. Conclusions**

In this paper, we introduced an HPHT diamond substrate as the seed of the homoepitaxy growth in a CVD system under a high chamber pressure of 300 torr. The relationships among the input power, substrate temperature, and chamber pressure were first studied in order to understand the plasma behavior during the deposition reaction. A series of methane concentrations, growth rates, and surface morphologies were investigated to optimize the growth parameter. After that, a high quality SCD layer was achieved with a 27.12 μm/h growth rate under a 300 torr high pressure environment. The sample surface presented a regular uniform [100] orientation surface step flow in the original substrate area and a [110] orientation step in the lateral growth edges. Raman spectroscopy and the HRXRD rocking curve were used to investigate the internal stresses and crystal quality of both the homoepitaxy and lateral layers. The lattice visual structure model was employed to explain the step flow rotation in the lateral growth edge. Different from the CH3 guided [100] orientation deposition model, C2H2 acted as the preponderant growth source of the [100] orientation step flow, which relies on higher energy provided by the higher temperature on the substrate edges.

**Author Contributions:** Conceptualization, X.W. and Y.P.; methodology, X.W. and P.D.; software, X.W. and Y.P.; validation, D.W., Y.P., X.H.; formal analysis, X.W. and P.D.; investigation, X.W. and Z.C.; resources, X.W., Y.P. and C.L.; data curation, X.W. and Y.P.; writing—original draft preparation, X.W.; writing—review and editing, Y.P. and X.H.; visualization, X.W.; supervision, X.H.; project administration, D.W. and C.L.; funding acquisition, D.W., C.L. and X.H.

**Funding:** This research was funded by The National Key R&D Program of China, grant number 2018YFB0406501, and the Key Basic Research Projects of Shandong Province Natural Science Foundation, grant number ZR2017ZA010.

**Acknowledgments:** We would like to thank Jinan Diamond Technology Co. Ltd for providing the HPHT diamond substrate that was used in the experiments.

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

#### **References**

© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).


*Article* **Multiple Object Tracking in Robotic Applications: Trends and Challenges**

**Abdalla Gad 1,†, Tasnim Basmaji 1,†, Maha Yaghi 1, Huda Alheeh 1,2, Mohammad Alkhedher 3 and Mohammed Ghazal 1,\***

**Abstract:** The recent advancement in autonomous robotics is directed toward designing a reliable system that can detect and track multiple objects in the surrounding environment for navigation and guidance purposes. This paper aims to survey the recent development in this area and present the latest trends that tackle the challenges of multiple object tracking, such as heavy occlusion, dynamic background, and illumination changes. Our research includes Multiple Object Tracking (MOT) methods incorporating the multiple inputs that can be perceived from sensors such as cameras and Light Detection and Ranging (LIDAR). In addition, a summary of the tracking techniques, such as data association and occlusion handling, is detailed to define the general framework that the literature employs. We also provide an overview of the metrics and the most common benchmark datasets, including Karlsruhe Institute of Technology and Toyota Technological Institute (KITTI), MOTChallenges, and University at Albany DEtection and TRACking (UA-DETRAC), that are used to train and evaluate the performance of MOT. At the end of this paper, we discuss the results gathered from the articles that introduced the methods. Based on our analysis, deep learning has introduced significant value to the MOT techniques in recent research, resulting in high accuracy while maintaining real-time processing.

**Keywords:** multiple object tracking; MOT; self-driving; autonomous vehicle; autonomous navigation; SLAM; KITTI; MOTChallenges; MOT15; MOT16; MOT17; UA\_DETRAC


**3.2 Input voltage reference (IVR) technique**

The voltage across small input filter capacitor is measured and compared to the MC supply voltage to generate gate drive signal for RCC of IPC method as shown in **Figure 8**.

The IVR technique can be used to detect the regeneration in the matrix converter for electrical braking methods. The duty cycle variation is directly proportional to the increase in the line to line voltage across the input filter capacitor of the matrix converter under regeneration with respect to the output power (Po), as shown in Eq. (5).

$$\mathbf{V\_{AB}} \propto P\_o \propto D \tag{5}$$

**61**

**Figure 9.**

*Bidirectional switch (BDS) method.*

*Matrix Converter for More Electric Aircraft DOI: http://dx.doi.org/10.5772/intechopen.81056*

1.Bidirectional switch (BDS) method

2.Input power clamp (IPC) method

**4.1 Bidirectional switch (BDS) method**

3.Standard clamp circuit (SCC) method

regeneration takes place in the MC motor drive.

**4.2 Input power clamp (IPC) method**

investigated:

**4. Methods for avoiding regeneration in matrix converter**

To avoid regeneration in matrix converters, three novel circuit topologies are

The power circuit for the BDS method [18], regeneration control circuit (RCC) or electrical braking circuit, is shown in **Figure 9**. The regeneration control circuit (RCC) is introduced across the input filter capacitors (CAB, CBC, and CAC). The regeneration control circuit (RCC) is responsible for power dissipation when

The RCC consists of three bidirectional switches (BDSAB, BDSBC, and BDSAC) in series with three resistors (RAB, RBC, and RAC) connected across the input lines, in parallel with the input filter capacitor. The schematic of the regeneration control

The input power clamp (IPC) method [19] is used for braking the electrical energy in a matrix converter motor drive. The IPC method requires only one braking resistor and a UDS, as shown in **Figure 10**, when compared to the BDS method, which requires three switches in series with three resistors. Electrical braking circuit or regeneration control circuit (RCC) for the input power clamp (IPC) method

circuit (RCC) or electrical braking circuit (EPC) is depicted in **Figure 9**.

Here, *VAB* is line voltage across small input filter capacitor.

The RCC is turned on only if any voltage difference is detected between MC supply voltage and voltage across the small input filter capacitor for each sampling period. In addition, if the small input filter capacitor voltage is equal to the MC supply voltage, then the duty cycle is set to zero. Gate drive signal is generated using FPGA and DSP control platform similar to PC technique. The power dissipation through RCC happens only if the MC drive is operating under regenerative mode.

*Aerospace Engineering*

**Figure 8**.

shown in Eq. (5).

regenerative mode.

power. The MC drive is not capable to output whole of regenerated power because of it losses such as friction, windage, iron, switching and conduction losses. Because of above reason, the braking resistor dissipates less than the actually regenerated power. As written in Eqs. (3) and (4), the design of braking resistor

Ib = Vin/Rb (4)

where the braking current (Ib) and input power (Pin,max) are directly proportional to the input voltage. The braking resistor design also depends on the braking time, thermal capacity of the resistor, and heat sink. And the current rating of UDS/

The voltage across small input filter capacitor is measured and compared to the MC supply voltage to generate gate drive signal for RCC of IPC method as shown in

The IVR technique can be used to detect the regeneration in the matrix converter for electrical braking methods. The duty cycle variation is directly proportional to the increase in the line to line voltage across the input filter capacitor of the matrix converter under regeneration with respect to the output power (Po), as

VAB ∝ Po ∝ D (5)

The RCC is turned on only if any voltage difference is detected between MC supply voltage and voltage across the small input filter capacitor for each sampling period. In addition, if the small input filter capacitor voltage is equal to the MC supply voltage, then the duty cycle is set to zero. Gate drive signal is generated using FPGA and DSP control platform similar to PC technique. The power dissipation through RCC happens only if the MC drive is operating under

Here, *VAB* is line voltage across small input filter capacitor.

*Block diagram of the input voltage reference (IVR) technique for IPC method.*

2

/Rb (3)

(Rb) relies on maximum regenerative power during regeneration.

Pin,max = Vin

BDS in RCC must be higher than the braking current.

**3.2 Input voltage reference (IVR) technique**

**60**

**Figure 8.**


**4. Increasing rate of lower genital tract infections**

Cervicitis as well as vaginitis has been one of the common diseases influencing the health of female genital system. The happening rate of female vaginal and cervical inflammation is increasing rapidly in modern world which may be organism mutations, immunological changes, and poor hygiene in underdeveloped world or liberal sexual behaviors particularly in western countries. Fortunately enough, with the increased medical knowledge, health education, improved diagnosis and aggressive lines of therapy, prompt eradication of these infections is possible.


**3. Classification**

186 Congenital Heart Disease – Selected Aspects

In the normal heart, the coronary arteries arise from the upper half of sinuses, close to the sinotubular junction in most of cases (Muriago et al., 1997). A connection above the level of the sinotubular junction is possible. The coronary orifices are not always located in the centre of aortic sinuses. The left coronary ostium may lie near the junction between the left and right aortic sinuses, whereas the right ostium may lie near the junction between the right and the non-coronary aortic sinuses (Muriago et al., 1997). The discrimination between a common variant and an anomalous origin from an unusual site within the appropriate sinus is often difficult. It is inappropriate to use the notation of left and right aortic sinuses when there is an anomalous aortic origin of one of the coronary arteries. The categorisation proposed by the working group of Leiden (Gittenberger-de Groot et al., 1983) is based on the view by an observer positioned in the sinus farthest from the pulmonary trunk. The sinus at the right hand of the observer is named sinus 1 and gives rise to the right coronary artery in the normal heart, whereas the sinus at the left hand is named sinus 2 and normally gives rise to the left coronary artery. Another classification is used in this review with the two sinuses adjacent to the pulmonary trunk called respectively appropriate sinus and opposite sinus. The origin of mistakes that occur in the literature is often due to the confused interpretation describing the relationships of the ectopic coronary arteries with the adjacent structures, mainly the great vessels. The schematic representation, often cited, with a cross-section view of the aortic and pulmonary valves is erroneous. Indeed, the aortic and pulmonary annuluses are not in the same plane and the latter is more superior. Therefore, it is easy to understand that the initial path of the RCA is facing the subpulmonary infundibulum and not the pulmonary trunk (figure 2). According to the position and the

Fig. 2. Volume-rendered computed tomography image of the heart with the normal origin of the right coronary artery (white circle) marked. AO: aorta, LV: left ventricle, PT: pulmonary

**RV**

**SPI**

**PT**

**LV**

trunk, RA: right atrium, RV: right ventricle, SPI: subpulmonary infundibulum.

**RA**

**AO**

So far, no consensus exists to define and classify easily the wide spectrum of the congenital coronary artery abnormalities (Angelini, 2002). Numerous, sometimes long or complex, descriptions have been presented in the literature (Angelini 2007, Dodge-Khatami et al., 2000, Jacobs & Mavroudis, 2010, Rigatelli et al., 2009, Roberts, 1986). We propose, in this review focused on the proximal anomalous connections of the coronary arteries, a simplified classification with 8 types (table 2). This classification is based on an anatomical view with the contribution of postmortem data (Frescura et al., 1998) and recent imaging modalities. By definition, the abnormalities involve the orifices of the LCA and RCA, and their branches. Different types of ANOCOR may be observed in the same patient. Diagnosis of ANOCOR is sometimes uncertain, especially in cases of an incomplete or poor-quality imaging. We consider that an accurate anatomical diagnosis should be the first step when an ANOCOR is suspected.

Table 2. Simplified classification of proximal anomalous connections of the coronary arteries.

Proximal Anomalous Connections of Coronary Arteries in Adults 189

Fig. 4. Angiographic view showing an anomalous connection of the left main coronary

An anomalous orifice of a coronary artery is usually linked with an ectopic ostium. Nevertheless, in rare postmortem observations (Frescura et al., 1998), a valve-like stenosis has been described with a ridge, consequence of an aortic wall fold that is in contact with an ostium in right position. Recently, a LMCA originated from the left sinus in the usual site, but with a slit-like orifice due to a tangential initial course associated with a short intramural segment, has been described (Angelini et al., 2010). An ectopic origin of a coronary artery in the appropriate sinus remains possible, but the limit between a true abnormality and a common variant may be tenuous, such as a connection in the lower half of the sinus, or near

ANOCOR from the non-coronary sinus proved by surgical or postmortem examination were previously described as exceptional. Nevertheless, a higher frequency of the latter is

A high take-off from the aorta at least 10 mm above the sinotubular junction is generally considered as an anomalous connection (Hlavacek et al., 2010). However, the height of takeoff judged to represent the abnormality is based on few solid data. Indeed, a level of 4 mm has been reported in a postmortem study (Frescura et al., 1998). Therefore, the criteria to determine an anomalous aortic origin above the sinotubular junction should be redefined with the contribution of non-invasive imaging. Usually, the ectopic vessel continues to arise

artery (arrow head) with the proximal right coronary artery (arrow).

**3.3 Anomalous connection with the appropriate sinus (type III)**

the commissural junction between the left and right cusps.

noticed in recent studies using tomographic imaging.

above the appropriate sinus (figure 5).

**3.4 Anomalous connection with the non-coronary sinus (type IV)**

**3.5 Anomalous connection above the sinotubular junction (type V)**


*2.1. Sites along with the Collection of Field Data*

We prepared ground observation datasets obtained at six sites (A–E) located in six different districts: Site A, in Thot Not, Can Tho (10◦10 N, 105◦33 E); Site B, in Chau Thanh (10◦16 N, 105◦08 E); Site C, in Cho Moi (10◦25 N, 105◦27 E); Site D, in Thoai Son (10◦16 N, 105◦08 E); and Site E, in Tri Ton, An Giang (10◦23 N, 105◦06 E) [7,8,10,21–27] Figure S1. The soils at sites A–C are classified as silty clay fluvisol (a type of alluvial soil; [17]), while the soils at sites D and E are classified as sulfuric humaquepts (a type of alluvial soil [17]).

In Can Tho and An Giang, 50 farmers' rice paddies (30 in site A, five each in sites B–E) were chosen as regions of interest (ROIs). At the center of each ROI, field water level data were collected for the supervised classification of the satellite remote sensing data with a water level gauge (daily, 10:00 AM–12:00 PM at site A) or with a HOBO CO-U20L-04 water level data logger (Onset Computer Corporation, United States; collected every 4 h at sites B–E). At the same time, we collected information about the history of field operations (e.g., fertilization and land preparation/sowing/harvesting dates) at each ROI throughout the

observation period. The numbers of ROIs in the inundated/non-inundated rice paddies are described in the cited literature [10].

**Figure 1.** Flowchart of the methodology of this study outlining the data, processing and analysis steps.

*2.2. CyGNSS GNSS-R Datasets and Their Preprocessing Methods*

All CyGNSS [10] Lv.1 Version 3.0 data observed from the first observation (August 2018) until December 2021 were downloaded from https://podaac.jpl.nasa.gov/ dataset/CYGNSS\_L1\_V3.0 (accessed on 15 January 2022). The reflectivity (Γ) data were calibrated [28] using Equation (1):

$$\Gamma(\theta) = \frac{(4\pi)^2 (P\_{DDM} - N) \left(R\_r + R\_t\right)^2}{\lambda^2 G\_r G\_t P\_t} \tag{1}$$

where *PDDM* is the maximum value of the analog power in the delay/Doppler maps (DDM), *N* is the noise floor related to the *DDM*, *Rr* is the receiver–specular point (SP) distance, *Rt* is the transmitter–SP distance, *λ* is the wavelength, *θ* is the incidence angle, *Gr* is the receiver antenna gain in the direction of the SP and *GtPt* is the transmitter equivalent isotropically radiated power (EIRP). The noise floor is computed as the mean value of the DDM subset, where the signal is absent (located above the characteristic horseshoe shape of the DDMs). The effect of the scattering area with the highest analog power in the DDM maps was used as the size of the specular point. Since the CyGNSS GPS signal integration time is fixed at 1 s, the footprint shape was inversely computed using the integration time, the velocity of the SP and the effective scattering area.

Our precision index model's design was inspired by the spatial localization technique of common data assimilation methods such as the local ensemble transform Kalman filter or local particle filters [10]. The precision index (PI) was calibrated using the following equation in the grid covered by the SP footprint, as shown in Equation (2):

$$PI = \frac{\cos(\theta) \times GS}{sqrt(ESA) \times \exp(3.0 \times \left(DistSP/SemiDSP\right)^2)} \approx \text{ObsEr} \tag{2}$$

where *θ* is the incidence angle, *GS* is the grid spacing, *ESA* is the effective scattering area, *DistSP* is the distance from the center of the specular point, *SemiDSP* is the semidiameter of the ellipsoidal-shaped specular point, and *ObsEr* is the observation error (Figure 2).

**Figure 2.** Illustration of the precision index. The light blue tiles are rasterization grid cells. The yellow circular area is the effective scattering area. The red tile in the yellow/green circle effective scattering area is the corresponding grid. The green, blue and red arrows are equivalent to the *GS*, *DistSP* and *SemiDSP* terms in Equation (2).

Each specular point in the CyGNSS data format contains analog power in a 17 × 11 array of DDM bins [17 rows for Delay with a 0.25-chip resolution, 11 columns for Doppler with a 500-Hz resolution]. We also analyzed the analog power in the DDM by regarding the power as a probability density of a 3-dimensional histogram (representing skewness and kurtosis) as described in Equation (3) and Figure 3 by targeting 5 × 5 arrays surrounding the element containing the maximum analog power over the DDM at each specular point. If the kurtosis value was greater than 0.01, the precision index (*P*) zeroed out before its use to omit the noise derived from the specular effects over highly rough land surfaces.

$$\begin{aligned} SKW\\_a &= \sum\_{i=-2}^{2} \sum\_{i=-2}^{2} \left( \frac{(p\_{ij} - p\_{00}) / (TP \times 25)}{1/3 + \sqrt{2} [(DPL\\_P\_{ij} - DPL\\_P\_{00})]} \right)^3 \\ SKW\\_b &= \sum\_{i=-2}^{2} \sum\_{i=-2}^{2} \left( \frac{(p\_{ij} - p\_{00}) / (TP \times 25)}{1/3 + \sqrt{2} [- (DPL\\_P\_{ij} - DPL\\_P\_{00}) + (DLY\\_P\_{ij} - DLY\\_P\_{00})]} \right)^3 \\ SKW\\_c &= \sum\_{i=-2}^{2} \sum\_{i=-2}^{2} \left( \frac{(p\_{ij} - p\_{00}) / (TP \times 25)}{1/3 + \sqrt{2} [(DPL\\_P\_{ij} - DPL\\_P\_{00}) + (DLY\\_P\_{ij} - DLY\\_P\_{00})]} \right)^3 \\ DDM\\_SkSW &= MAX \{ abs(SKW\\_a), abs(SKW\\_b), abs(SKW\\_c) \} \\ DDM\\_KTS &= \sum\_{i=-2}^{2} \sum\_{i=-2}^{2} \left( \frac{(p\_{ij} - p\_{00}) / (TP \times 25)}{1/3 + \sqrt{2} \left[ (DPL\\_P\_{ij} - DPL\\_P\_{00})^2 + \left( Dly\\_P - DPL\\_P\\_P \right)^2 \right]} \right)^4 \end{aligned} \tag{3}$$

where *SKW* is skewness, KTS is kurtosis, *P*00 is the maximum analog power value (W) on the DDM arrays of each specular point ["00" indicates the index of the element containing the maximum analog power among all arrays in the *DDM*; i.e., *P*00 in Equation (3) is equivalent to *PDDM* in Equation (1)], *i* and *j* are array indexes over the *DDM* surrounding the maximum analog power element (*i* is the Delay row index and *j* is the Doppler column index), *TP* indicates the sum of the power analog values of all arrays in the *DDM*, and *DPL* and *DLY* indicate the doppler–delay index of the target element (i.e., *Pij* or *P*00) over the *DDM* array.

**Figure 3.** Illustration of DDM 3D statistics (skewness and kurtosis). The calibration is conducted by assuming that the analog power is equivalent to the probability density of the DDM 3D histogram (Delay, Doppler and Analogue power).

After calibrating the reflectivity (Γ) and PI on a latitude/longitude map (with a 500 m resolution and a daily temporal resolution) (Lv. 2, Figure 4), the data were applied to a temporal Kalman smoother on each 15-day cycle (temporal localization scale: 14 days. 1σ = 5 days) to obtain the Lv. 3 product (Figure 5) for the subsequent spatiotemporal analysis. The Lv. 2 data were also applied for the temporal analysis (with a slight modification to the change detection algorithm described in [29]) just after being applied in the Γ(*θ*)-normalization task with Equation (4) and in a 30-day moving average filter; then, the results were compared with the ALOS-2/PALSAR-2 products reported in [10]. To generate the Lv. 3 products, this study simply used a linear Kalman filter (i.e., the time-evolution of the model was assumed to be negligible). Γ-reflectivity was treated as both the states and measurements.

Γ*normalized* = Γ−Γmin Γmax−Γmin referring to a paper [29]

$$\left(\Gamma(\theta)\_{normalized} = \frac{\Gamma(\theta) - \Gamma(\theta)\_{\min}}{\Gamma(\theta)\_{\max} - \Gamma(\theta)\_{\min}}\right) \tag{4}$$

where Γ(*θ*)max/min is the temporal maximum/minimum value of the corresponding incidence angle bin. Due to the data quantity limitations of specular points obtained during the 2018–2022 period, we calibrated the incidence angle bins prepared for every 5◦ interval (i.e., 0–5◦, 5–10◦, 10–15◦, 15–20◦, 20–25◦, 25–30◦, 30–35◦, 35–40◦, 40–45◦, 45–50◦, 50–55◦, 55–60◦, 60–65◦ and 65–70◦ bins) in each grid.

**Figure 4.** A sample of the Lv. 2 daily product (**a**) Γ(*θ*)normalized; (**b**) incidence angle; (**c**) precision index clipped at the Mekong Delta ((**d**) Optical image) on 4 January 2021.

**Figure 5.** A sample of the Lv. 3 15−day−cycle Kalman smoother product based on the precision index [Γ(dB) without or with applying the precision index (**a**,**b**), zeroed out based on the kurtosis threshold and DDM 3D statistics such as skewness (**c**) and kurtosis (**d**)] clipped at Mekong Delta on 1 August 2018.

After calibrating the reflectivity (Γ) and PI on a latitude/longitude map (with a 500 m resolution and a daily temporal resolution) (Lv. 2, Figure 4), the data were applied to a temporal Kalman smoother on each 15-day cycle (temporal localization scale: 14 days. 1σ = 5 days) to obtain the Lv. 3 product (Figure 5) for the subsequent spatiotemporal analysis. The Lv. 2 data were also applied for the temporal analysis (with a slight modification to the change detection algorithm described in [29]) just after being applied in the Γ(*θ*)-normalization task with Equation (4) and in a 30-day moving average filter; then, the results were compared with the ALOS-2/PALSAR-2 products reported in [10].