*2.1. Ameliorative Effect of SR, CR, and Combined Extracts on Hyperglycemia, Dyslipidemia, and Insulin Resistance in T2DM Rats*

To evaluate the compatibility effects of SR and CR, a favorable T2DM rat model with a notable glycolipid metabolism disorder was established by HFD along with low dose of STZ. The significant increase of FBG, FINS, TG, TC, LDL-C, and FFA levels in T2DM rats was observed. By contrast, compared with T2DM rats, the levels of the above biochemical factors were decreased to a range from 51.1% to 85.4% after oral administration of individual and combined extracts. Furthermore, LSC or HSC extracts exerted better effects than the single drug, and the levels of these biochemical indexes declined remarkably after treatment. Metformin demonstrated a similar regulation as HSC in T2DM rats (Figure 1). These results indicated the better effects of combined extracts on the regulation of glucose and lipid homeostasis.

**Figure 1.** The levels of fasting blood glucose (FBG), fasting insulin (FINS), total cholesterol (TC), triglyceride (TG), free fatty acid (FFA), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C) in serum of the normal group (N), model group (M), and groups gavaged with metformin (P), scutellaria Radix (SR), coptidis Rhizome (CR), low dose of combined extracts group (LSC) and high dose of combined extracts (HSC). The values were shown as mean ± SD. # *p* < 0.05, ## *p* < 0.01, ### *p* < 0.001 vs. normal group; \* *p* < 0.05, \*\* *p* < 0.01, \*\*\* *p* < 0.001 vs. model group. Data were analyzed by One-way-ANOVA.

#### *2.2. Pathological Assessment of Some Tissues Related to Insulin Resistance*

The liver tissues of normal rats exhibited normal cellular structure with neat liver lobule, liver cords, liver sinusoid, and a clear three pipeline structure of the portal area. While notable changes with severe fatty degeneration were observed in the liver tissues of T2DM rats, this indicated that the model had been successfully established. Compared to model rats, SR and CR group rats showed moderate fatty degeneration, while LSC, HSC, and P group rats showed mild fatty degeneration by HE staining observation. The islet cells of T2DM rats showed severe atrophy. After treatment, SR and CR group rats showed moderate atrophy, however, LSC, HSC, and P group rats showed mild atrophy. The mean adipocyte diameter of T2DM rats compared with normal rats was seriously increased. After treatment, the mean adipocyte diameter was decreased and HSC showed a normalized effect. The skeletal muscle of T2DM rats was notably infiltrated with inflammatory cells, but P, SR, CR, LSC, and HSC group rats were normalized (Figure 2). The histological examination results were consistent with biochemical data, which further confirmed the synergistic effect of SR and CR.

**Figure 2.** Histopathological observation of liver, pancreas, skeletal muscle and adipose tissue in the normal group (N), model group (M), and groups gavaged with metformin (P), scutellaria Radix (SR), coptidis Rhizome (CR), low dose of combined extracts group (LSC) and high dose of combined extracts

(HSC). Liver tissues of M: notable changes with severe fatty degeneration can been seen as shown by the black arrow; Pancreas of M: severe atrophy of pancreatic islet cells is shown by the black arrow; Skeletal muscle of M: notably inflammatory cells infiltration is indicated by the black arrow; Adipose tissues of M: mean adipocyte diameter was seriously increased, as indicated by the black arrow. Samples were stained with H&E and photographed at 400× magnification.


*3.7. Electrostrictive Properties*

The longitudinal strain (*S*3) behavior of the P(VDF-HFP) film, fibers, and fiber mats compressed at 30◦, 60◦, and 80◦C and induced by an external electric field (*E*3) at a frequency of 1 Hz, is presented in Figure 9a. At a low electric field, the electrostriction behavior demonstrated that the total thickness strain had an approximately quadratic relation to the applied electric field. This can be illustrated by the electrostriction which is shown in Equation (7) and Maxwell stress. The Maxwell stress effect involves electrostatic attractions and interactions with the charges on the electrodes showing SM = ε0εrE23/Y. This equation can be used to estimate the value of the Maxwell stress which can be neglected due to its small and negligible value in the case of a low dielectric constant at an applied low electric field. The induced strain of all samples based on the electrostrictive behavior can be observed. The linear relationships between the induced strain and the electric field, shown in Figure 9b, display that their slope can be assigned as the electrostrictive coefficient (*M*33). As a result, the electrostrictive behavior of the samples can be expressed according to Equation (7). The M33 increased with the fraction of temperatures compressed and the increased number of polymer–polymer interfaces may play a key role, affecting both the electrical and mechanical properties as shown in Figure 9c. This was reflected by the abruptly increased space charge distribution, and the increasing dielectric constant increased with the compressed fibers. Clearly, this study indicates that fibers compressed by temperature are promising electrostrictive materials for actuation and can be fabricated with a simple preparation.

**Figure 9.** *Cont*.

**Figure 9.** Strain behaviors of film, fibers, and compressed fibers as a function of the (**a**) electric field and (**b**) square of the electric field at 1 Hz. (**c**) The effect of the compression fibers on the electrostrictive coefficients and absolute β fraction.


**1. Introduction**

Waterlogging and salinization issues (typically referred to as twin problems) elevate due to seepage from unlined canals, flooding of inferior quality groundwater, and practicing poor techniques for irrigating the land [1,2]. Because of the aforementioned twin problem, a significant proportion of the crop yield decreases in waterlogged areas worldwide due to the uplifting of anaerobic conditions and the growth of hydrophilic weeds, which develop nutrient deficiency in the root zone [3–5].

Unfortunately, in Pakistan along the Indus Basin Flood Plains (IBFP), approximately 7 million hectares (ha) of the land are affected by waterlogging and salinization. Nearly

**Citation:** Imran, M.A.; Xu, J.; Sultan, M.; Shamshiri, R.R.; Ahmed, N.; Javed, Q.; Asfahan, H.M.; Latif, Y.; Usman, M.; Ahmad, R. Free Discharge of Subsurface Drainage Effluent: An Alternate Design of the Surface Drain System in Pakistan. *Sustainability* **2021**, *13*, 4080. https://doi.org/10.3390/su13074080

Academic Editor: Mohammad Valipour

Received: 13 March 2021 Accepted: 1 April 2021 Published: 6 April 2021

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

**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

half of the waterlogged area (~3 million ha) is located in Punjab, mainly responsible for regulating ~90% of the country's food chain [1,2,6]. This might be due to this area comprising the largest irrigation structure run by gravity, which is regrettably unlined. However, the unlined system contributes a significant portion of groundwater replenishment by seepage, which is the second most crucial freshwater source. However, in some areas of Pakistan, the groundwater level is already close to the soil bed, especially the areas close to the IBFP. This leads to the conversion of precious fertile land into toxic saline unculturable land. Some of the problems associated with waterlogging and salinity in the farms and lands of Pakistan are demonstrated in Figure 1. However, keeping in mind that various efforts and approaches have been actively employed to eliminate the twin evils. For instance, management practices related to soil and crop [7] drainage networks in either the surface or subsurface [8–11] and raising the soil bed [12–14]. A significant improvement has been documented in the literature due to the consideration of management practices, as mentioned earlier [8–11].

**Figure 1.** Example of farm and land problems associated with waterlogging and salinity in Pakistan showing: (**a**) improper control of waterlogging and salinity in low-lying areas of Sindh, (**b**) the reduction of essential nutrients including N, P, and K, and an increase of minerals such as Fe and Mn in the soil, and (**c**,**d**) the mismanagement of surface water resources and salinity causing water with the total dissolved solids (TDS) over 1500 in the Thatta and Sindh districts. (Source: Adaptive AgroTech Consultancy).

> Similarly, the government of Pakistan (GOP) initiated mega-projects, such as the Salinity Control and Reclamation Project (SCARP) wells between the 1960s and 2000s, whereby the vast number of tubewells (vertical drainage system) were installed to maintain the sustainable groundwater table for crops [15]. The purpose of SCARP tubewells was to lower the water table, leaching the salts by intensified irrigation, and to ensure the comfort zone for crop production [16,17] by simply pumping the water from the ground and disposing of it into a well-lined drainage channel. From here, the gravity force was employed for conveying the water into nearby streams. It was reported that about 8 million ha of land were reclaimed at a cost of USD 2 billion [18]. However, later, it was recognized that SCARP tubewells were not a promising option due to the massive operational costs, maintenance costs, and the country's socioeconomic instability. An alternative option preferred by farmers is the privatization of tubewells to obtain good-quality shallow groundwater [1,18].

> Another sustainable solution for reclaiming the wetlands is developing surface or subsurface drainage structures for carrying away the water from the waterlogged areas. In this regard, the World Bank releases the funds to line the water conveying channels, particularly watercourses and farmers' field channels, for enhancement of the culturable land [2,19]. Surface or subsurface drains merely collect the water below the root zone through collectors/laterals and drain it to nearby sumps or reservoirs. The sumps or reservoirs are constructed deep below the surface or subsurface channels in order to carry a significant amount of water. When the sumps get filled, they are emptied by employing a pumping unit to pump the water from the sumps or reservoirs and outfalls into the surface drains, usually constructed bottom-up from the subsurface drains. In this regard, subsurface drains and laterals work as water collecting entities from waterlogged areas, whereas pumping units and surface drains operate as water conveying entities from one locality to another locality [3,20–22]. Fourth Drainage Project (FDP) is one of the leading

projects of the World Bank's twin evil removal initiative, which was installed in Faisalabad. In this regard, the literature documented a significant improvement of groundwater quality and reclamation of salinity from the agriculturable land [23,24]. However, electricity shortfalls and extensive pumping make it dysfunctional overall. Therefore, researchers need to further explore alternative options that could be energy-efficient and economical. In order to do so, there would be technical modifications required on the FDP site. It could be done by redesigning the surface drains and employing gravity for conveying the water from the sumps to the surface drains. Alternatively, the latest techniques of GIS and geophysics have been considered for selecting suitable basins with freshwater aquifers for the formation of an efficient exploration strategy [2]. However, redesigning the surface drainage network still seems necessary.As such, various design parameters need to be taken into account, including permissible velocity, side slope, and bedslope. Permissible velocity for clear and muddy water was calculated by Fortier et al. [25] at 0.45 and 0.75 m/s, respectively. Ritzema et al. [26] stated that for fine sand and loam, the velocity ranges from 0.1 to 0.3 m/s and from 0.3 to 0.6 m/s, respectively. The government of Pakistan (GOP, 1993) [27,28] concluded that for fine sand, the maximum velocity is 0.45 m/s, and for sand and sandy loam the maximum velocity is 0.75 m/s. Deshmukh et al. [29] concluded that the time required for water to flow from a section of channel (time of flow) and the flow velocity can be affected by a resectioning of the drain, and overland flow time can be increased by raising the cross-section of the drain. The side slope should be checked for stability against erosiveness, under wet conditions, and against the sudden lowering of water levels on the cessation of flows. Steep side slopes are desirable to save excavation as well as the land area occupied. However, the steeper side slope can only be used in cohesive and well-aggregated soils or where bank protection is provided. The GOP (1993) [27] have recommended following side slope ratios also called horizontal to vertical distance (H:V) for sand, loam, and clay, which are 3:1, 2:1, and 1:1, respectively. According to the 1984 United States Bureau of Reclamation (USBR) [30] guide, the value of Manning's roughness coefficient 'n' lies between 0.025 and0.030. The value of Manning's roughness coefficient 'n' reflects the net effect of all factors causing the reduction of flow. As a general guide, berm width is taken as twice the channel depth with a minimum of 5 to 10 feet. Tipton and Kalmbach et al. [31–33] recommended a berm width of 4, 6, and 10 feet for channels having a design depth (D) of <4, 4–6, and >6 feet, respectively. The minimum berm width is taken equal to the drain design depth (D) or the depth of cut (H). The berm may be increased when higher velocities tend to enlarge the section, or the drain passes through marshy or unstable soils.

At present, the subsurface drains outfall their effluent into the sump via drainage collector pipes, from which water is pumped and carried through shallow surface disposal channels, and ultimately outfalls into surface drains. Lackey K. A. [34] reported that pumping stations involve a complex balancing of several critical priorities, including reliable long-term service, operations and maintenance considerations, capital cost, and constructability. An investigation of the current situation reveals that pumping units, electricity transmission lines, transformer devices, and other instrumentation have been pilfered, and that there is a shortage of budget and electricity for operating such systems. Okarwy et al. [35] also investigated the impact of shallow surface drainage, rather than a conventional design. The design is more economical and adoptable for economically unstable countries such as Pakistan because it excludes the requirement of sump and pump accessories.

In the present study, we proposed a redesigned consideration for the Paharang drainage network that could receive drainage effluents under the gravity flow from sumps to surface drains. The idea is to lower down the beds of surface drains from the corresponding sump beds to develop the hydraulic gradient. In this regard, active surface drain beds are excavated further to achieve the prerequisite depth, so that drainage collectors directly dispose the collected water (via perforated pores) from waterlogged areas into the surface drains under the action of gravity. In addition, the study also determines

the additional design requirements for the surface drains' cross-section and subsurface drainage units. In order to achieve the subsurface gravity flow, the modified bed level of surface drains was set below the drainage collector. The required surface drain bed level is achieved by deepening the existing bed level and/or decreasing the bed slope. The proposed design was completed after many successive trials. Interconnected MS-Excel worksheets were developed to optimize and redesign the L-section and the X-section of the proposed approach.

### **2. Data and Methods**

### *2.1. Study Area*

The Paharang drainage network (PDN) lies in the southwestern part of Faisalabad city (longitude 73◦0501.6800 to 73◦11027.2700 N Latitude 31◦34038.5000 to 31◦4200000 E). It has a drainage area of 560 km2 . The project area contains a wide range of coarse to medium soil textures. It has an overall length of 63 km (39.15 miles). The uniform slope of 1:5000, which is generally prevalent in the area, was adopted from the source to the receiving body, the Chakbandi main drain. Moreover, eight branch/tributary drains contribute to the main drain. Figure 2 demonstrates the map and schematic of the FDP and the PDN, respectively. Existing blueprints of the PDN, which include maps, L-sections, X-sections, sump pumps along the collector's outfall, discharge in drains, hydraulic structures, water table depth, and soil type along the drain, were collected from the Punjab Irrigation Department (PID) in Faisalabad.

### *2.2. Computation of Required Bed Level*

To discharge SS outflow into the surface drain network by the action of gravity, it is mandatory to maintain a downward slope between the SS and the surface drainage channels. It is merely done by lowering the bed of the surface drain from the level of the SS drainage collector pipe. Elevation of the SS drainage collector pipe at the surface drain (*ELC*) is calculated as:

$$EL\_c = CL - (D \times S) \tag{1}$$

where *D* is the distance from the sump to the surface drain; *S* is the slope of the collector drain, and *CL* is the existing SS drainage collector level at sump. *ELC* is calculated to determine the required bed level of the surface drain. The minimum water level in the surface drain is calculated as:

$$\text{WL}\_{LF} = \text{EL}\_{\mathbb{C}} - \text{SF} \tag{2}$$

$$BL\_{RV} = WL\_{LF} - d\_{LF} \tag{3}$$

where *WLLF* is low-flow water level (minimum level) in the surface drain; *SF* is the safe margin (0.3 to 0.5 m); *BLRV* is the revised drain bed level, and *dLF* is the flow depth at low flow. The existing and proposed design of the drain section, along with the water level for both the high/maximum (*WLHF*) and low/minimum (*WLLF*) flow conditions, are described in Figure 3. An extended SS drainage collector pipe receives water from the existing SS drainage network and directly disposes of into the surface drain.

All the sumps have the potential to operate with the proposed extended drainage collector pipe facility to outflow the SS water into the surface drainage channel because of gravity. Drainage collector pipes discharge SS water freely when the surface drain is operating at a low/minimum flow. However, this free outfall is hampered temporarily when the water level in the surface drain reaches the level of the drainage collector pipe, particularly during a storm or a high-level surface runoff. In turn, the drainage collector pipe ceases to dispose of the SS outflow into the surface drainage for a few hours/days. A self-closing valve/lid is thus mounted at the outlet of the drainage collector pipe to block/stop the backward flow of the surface drain water into the conventional sump via the drainage collector pipe.

**Figure 2.** (**a**) Layout map of the Fourth Drainage Project (FDP), and (**b**) non-scaled layout of drainage and location of sump pumps in the Paharang drainage network (PDN).

**Figure 3.** Schematic arrangement of extended pipe collector from sump to surface drain.

### *2.3. Redesign of Surface Drain L-Section*

To ensure the gravity flow of SS effluent; surface drainage channels needed to be redesigned; lowering the surface drain bed and water level by 1 to 2 m. This was achieved by changing the existing bed slope of drains S1:1 (H:V) to a smaller value S2:1 (S2 > S1) by such an extent that the requisite bed level was achieved over the selected distance *D,* as shown in Figure 4.

$$
\Delta BL\_B = EB\_{LB} - \frac{D}{(S\_2 - S\_1)}\tag{4}
$$

$$BL\_B = BL\_A + \frac{D}{S\_2} \tag{5}$$

where *BLA* and *BLB* are bed levels at *A* and *B*, respectively, *D* is the distance from point *A* to point *B*, *EBLB* is the existing bed level at *B*, and ∆*BLB* is the change in the bed level at *B*. The slope beyond point *B* may be either kept the same as the existing slope or changed to accomplish further lowering. This was repeated until the bed level of all main/branch/tributary drains was achieved as required at all the collector outfall locations.

**Figure 4.** Typical schematic diagram of longitudinal section.

### *2.4. Flow Section Design*

Manning's formula was used to redesign the cross-section of the proposed drains using the existing drains roughness coefficient (n) and side slope values. The drain crosssection at low flow and high flow was achieved by changing the values of bed width (B), and revised bed slope (S2). The point where the bed slope of the surface drainage channel changes is represented as point A in Figure 4. A compromise design was achieved for all main, branch, and tributary drains and all their reaches by endorsing the prime efforts on the redesigning of the bed level of the Paharang main drain (surface drain). The simultaneous design was carried out using the Excel workbook. Interconnected worksheets were designed for each main, branch, or tributary drain. During the redesign, the drain top width was taken as a design constraint, such that the row for the revised cross-section is not varied too much from the existing row of the drain.

### *2.5. Flow Section Design*

Design continuity of the outfalling drain (i.e., branch drain) and receiving drain (i.e., main drain) was ensured by employing the following conditions:

$$\text{BL}\_{\text{O}} \ge \text{BL}\_{\text{R}} \text{ and } \text{WL}\_{\text{L}\text{FO}} \ge \text{WL}\_{\text{L}\text{FR}} \text{ and } \text{WL}\_{\text{H}\text{FO}} \ge \text{WL}\_{\text{H}\text{FR}}.$$

where BL is the bed level and WL is the water level. The subscripts O and R stand for the outfalling and receiving drains, respectively, whilst LFO and HFR stand for the low flow in the outfalling drains and the high flow in the receiving drains, respectively.

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

### *3.1. Required Bed Lowering and Design Continuity*

Extended SS drainage collector pipe levels were calculated with slope ranges between 0.0007 and 0.0013. Low-flow depth was measured anddepends upon the corresponding channel section. Figure 4 shows that the outfall levels of the proposed extended drainage collector pipes are well below the existing bed level. Hence, it was required to lower the bed level of the surface drainage channel from 2.29 to 4.1 m, which includes the level of the extended drainage collector pipe, depth of discharge, and safe margin for the free disposal of the sumps effluent. Overall, 11 out of 24 reaches of the surface drainage channels were required to lower the bed level by about 3 m or more from the outfall of extended drainage collector pipe.

The required bed level of the surface drain (main drain) depends upon outfall levels of the SS drainage pipe collectors as well as the outfall levels of branch drains. Contrastingly, the bed levels of the branch and tributary drains depend upon the SS drainage pipe collector levels and their outfall, the bed level of the surface drain (main drain), and the receiving body. Thus, the selection of any parameter for the upstream drain affects the design parameters of all other higher-/lower-order surface, branch, and tributary drains accordingly. This requirement was resolved by many successive trials. The results of the final selected trial are presented in Table 1.

**Table 1.** Design continuity of the Paharang main drain.

### *3.2. Redesigned Longitudinal Sections*

The whole length of the Paharang main drain was divided into 17 reaches, in which 7 branches/tributary drains and 4 SS drainage pipe collectors were directly outfalling into the main drain. Based on the proposed configuration of the longitudinal section, this needed to be redesigned. In the first trial, it was ensured that the bed level of the main drain remained lower than the outfall levels of the extended drainage collector pipes. From this trial, it was observed that the bed level of Paharang main drain at the outfalling point was lower than the receiving Chakbandi main drain, which resulted in non-uniformity and free flow of the hydraulic structure. Alternatively, it seemed that the design did not need any alteration up to the reduced distance (RD) of 7.16 km because there was no interconnected branch/tributary drain and no drainage pipe collector outfall. Another significant purpose to keep the section as per the existing design was the large aqueduct of Waghwal (Jhang BC and Mudhuana) laid in this section at the RD of 7.097 km. Undoubtedly, lowering the bed level of the aqueduct could be too expensive and problematic. In the second trial, the bed level of the main drain was started lower from the RD of 7.160 km. However, at the bed slope of 1:5000, the required level could not be achieved; also, it was not possible to increase the depth more than the downstream portion, as the bed level was lowered more than the first reach. In the third trial, from the reach at the RD of 7.160 to the RD of 53.950 km, the channel bed slope was decreased up to 1:8000. The required bed level was achieved, but the capacity to carry the discharge of the channel reduced as the bed slope decreased. Therefore, the channel bed width was increased to pass the design discharge. The complete proposed design of Paharang main drain along with existing design are described in Figure 5. All sumps can outfall at gravity flow during the low-flow conditions and the reach-wise design of the parameters with low-flow water levels are given in Table 2.

**Figure 5.** Proposed L-section of the Paharang main drain.

**Table 2.** Reach-wise design for Paharang main drain.

### *3.3. Redesigned Cross-Section*

There were six sites selected randomly to represent the different reach of length for showing the existing and proposed design of the cross-section of the Paharang main drain, presented in Figure 6. In the proposed design, the right bank of the channel was kept as the same design in most of the reaches, because it would be difficult and expensive to shift the service road and dowel. Therefore, the left side of the channel was used to increase the bed width, because extra berm width was available on the left side for future extension. However, for some reaches after the RD of 34.140 km, it became necessary to shift the dowel and service road to maintain the berm width required for the proposed design. However, there was no paved service road in these reaches. In the typical cross-section design of both the main and sub drains, the side slope of the channel was used at 1:1.5, and for the spoil bank, 1:2 inner and outer bank slope was used. In the plots of the cross-section channel (Figure 6), the side slope may not look perfect because of the unequal horizontal and vertical scaling, but in the whole design, its value was taken as 1:1.5.

In the remodeled section from the RD of 7.160 km to the RD of 53.950 km, a mild channel slope of 1:8000 was used, which reduced the discharge capacity of the drain. Therefore, passing the design discharge at the mild bed slope required a larger channel section. Channel capacity can be increased by increasing depth and bed width. Depth was increased to attain the required bed level. Thus, keeping in mind the relation of B/d = 2, the bed width was increased to increase the discharge capacity of the drain. As the bed width increased, the top width also increased. At the start of the tail side, increase in the top width was managed with extra width available for future extension. However, in the next section towards the head side, the extra berm was not enough. Therefore, an additional row was required for the proposed design. Similarly, the bed level difference was also increasing from tail to head, which caused an increase in the row. Important features for the proposed design cross-sections presented in the Table 3.

**Figure 6.** Cross-section design of (**a**) relative distance (RD) of 9.750 km, (**b**) RD of 17.350 km, (**c**) RD of 32.000 km, (**d**) RD of 37.390 km, (**e**) RD of 42.060 km, and (**f**) RD of 51.510 km on the Paharang main drain.

**Table 3.** Features of design cross-section of the Paharang main drain.

To lower the bed level and redesign the cross-section of the PDN, it was necessary to calculate the earthwork in terms of excavation, and to dump the excavated materials in a specific manner. For the proposed design, 1435 m3 and 1030 m3 of earthwork were required for the Paharang main drain and its branch/tributary drain, respectively.

### *3.4. Modification in Hydraulic Structures*

Mainly, there are three types of hydraulic structures along the main drain that are bridges, aqueducts, and water coarse crossings. Because of the excavation, in terms of lowering the bed level of the drain, the stability of the structure reduces as the foundations of the supporting piers are exposed. To protect the structure and foundation's stability, one must either increase the depth of the foundation by providing a pad (expensive solution) or line the section around the structure to increase the stability and remove the risk of erosion. Both solutions can be adopted, as the proposed L-section design of the main drain shows that the change in bed level is increasing towards the source point. Thus, the proposed design can be divided in two sections at the RD of 25.910 km; at this point, the difference between the existing and proposed bed levels was 1.57 m. In this section, the exposure of the foundation was less, so the section was lined around the structure. In the second section after the RD of 25.910 km, the bed level difference was more. Therefore, the foundation depth can be increased by providing a pad below the foundation, as shown schematically in Figure 7 (left). There were three aqueducts lying in the redesigned section of the Paharang main drain. Table 4 describes the details of the changes made with respect to the bed level. In the cross-section design at the proposed bed level, the top width increases because of an increase in the bed width. Therefore, it causes an increase in aqueduct length and change in bed level and water level that are explained by the schematic, proposed design of the aqueduct in Figure 7 (right).

**Figure 7.** Schematic diagram of the pad design (**left**) and the aqueduct with the proposed design (**right**).

**Table 4.** Difference in design bed level (DBL) of the aqueduct.

### **4. Conclusions**

An alternate design of the Paharang drainage system was evaluated that can receive gravitation discharge of subsurface drainage effluent. A model based on Microsoft Excel was developed to complete the design. The proposed design was achieved by lowering the bed level and decreasing the drain bed slope. As the bed level and low-flow water level of the surface drain become lower than the subsurface drainage collector pipes, the water can discharge freely into the surface drain under gravity at all times. The present constraints related to budget, electricity, law and order, theft of sump pump parts, etc. would thus become irrelevant. Therefore, the subsurface drainage system can operate uninterrupted throughout the year. The cost related to operating the pumping unit in terms of electricity/fuel, required labor, and maintenance can also be reduced. The redesign of the Paharang main drain to admit free flow may be adopted after further economic and structural analysis. In the future, subsurface drainage projects should be designed to ensure gravity outflow into surface drains by deepening the flow section of surface drains.

**Author Contributions:** Conceptualization, M.A.I.; Data curation, M.A.I., and J.X.; Formal analysis, M.A.I. and J.X.; Funding acquisition, M.S. and R.R.S.; Investigation, M.S., R.R.S., Q.J., H.M.A., and M.U.; Methodology, M.A.I., N.A., and M.U.; Project administration, J.X., R.A., and M.S.; Resources, N.A. and R.A.; Software, M.A.I., Q.J., and Y.L.; Supervision, J.X., M.S., and R.R.S.; Validation, J.X.; Visualization, H.M.A., Y.L., and M.S.; Writing—original draft, M.A.I.; Writing—review and editing, J.X., M.S., R.R.S., and H.M.A. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

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

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Data is contained within the article.

**Acknowledgments:** The present research was conducted at the School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, 710055 Shaanxi, Xi'an, China. The first author acknowledges the financial support for postdoctoral studies from University of Architecture and Technology, 710055 Shaanxi, Xi'an, China. The authors acknowledge the editorial and financial supports by the Open Access Publication Fund of Adaptive AgroTech Consultancy International.

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

### **References**


*3.1. Brevilin A Shows a Broad-Spectrum Antiviral Activity against IAV*

In our previous work, brevilin A showed potent antiviral activity against PR8 virus assessed by cytopathogenic effect (CPE) reduction assay and the cell viability assay [20]. To further verify its anti-IAV activity, brevilin A was tested in a plaque reduction assay using several IAV strains including A/PR/8/34 H1N1, A/FM/1/47 H1N1, A/Hong Kong/498/97 H3N2, and A/chicken/Guangdong/1996 H9N2 viruses. Ribavirin served as a positive control. The concentration for 50% of maximal effect (EC50) of brevilin A obtained with PR8 for viral plaque formation was calculated to be 2.96 ± 1.10 μM. This result concurs with the EC50 of 1.75 ± 0.59 μM that we evaluated in previous work. Comparable to PR8, the EC50 values of brevilin A obtained with H1N1 (FM1), H3N2, and H9N2 were 1.60 ± 1.14, 3.28 ± 1.09, and 2.07 ± 1.12 μM, respectively (Table 1). While the EC50 of ribavirin obtained with these four IAV strains were between 7.05 to 10.76 μM. These results indicate that brevilin A exhibits better anti-IAV activity than ribavirin, and the effects of both are not IAV type/subtype specific. In order to test whether brevilin A possesses antiviral activity against other RNA viruses, the effect of brevilin A on respiratory syncytial virus (RSV) was evaluated by a CPE reduction assay. However, brevilin A did not show inhibitory effect on RSV at a noncytotoxic concentration.

*a* Effective concentration required for reducing virus-induced plaque number by 50%. *b* Selectivity index, CC50/EC50.

#### *3.2. Brevilin A Inhibits Progeny Virus Production in Various Virus-To-Cell Ratios*

To examine to what extent the anti-IAV activities of brevilin A is affected by virus-to-cell ratio, the cells were infected with PR8 at a MOI (MOI, defined as the ratio of input infectious viral particles per target cell) of 0.001 or 1 in the presence of either brevilin A (8 μM) or vehicle control (DMSO). Virus titers in the supernatants at the indicated time points were quantified by plaque assays. As shown in Figure 2A, after infection with virus at a MOI of 0.001, the amount of progeny virus in the supernatants increased over the incubation time and peaked at 48 hpi in vehicle control, while treatment with brevilin A could significantly reduce the production of infectious virus from cells at 24 or 48 hpi. Even when cells were infected with virus at a higher MOI (MOI = 1), treatment of brevilin A also significantly decreased virus production by about 10-fold at 8 and 12 hpi (Figure 2B). These findings imply that the treatment of brevilin A strongly suppresses the replication of IAV, of note, the inhibitory activity of brevilin A is still rather effective against a relatively higher dose of input virus.

Additionally, we also analyzed the impact of brevilin A on replication of H1N1 (FM1), H3N2, or H9N2 in MDCK cells over multiple replication cycles. As shown in Figure 2C–E, compared to the vehicle, virus titers at each time point were markedly reduced by treatment with brevilin A.

**Figure 2.** The inhibitory effect of brevilin A on the growth curves of various influenza A viruses (IAV) strains. Madin–Darby canine kidney (MDCK cells) were infected with influenza A/PR/8/34 H1N1 virus at a MOI of 0.001 (**A**) or 1 (**B**), or A/FM/1/47 H1N1 virus (**C**), A/Hong Kong/498/97 H3N2 virus (**D**), or A/chicken/Guangdong/1996 H9N2 virus (**E**) at a MOI of 0.001. Cells were then treated with 8 μM of brevilin A or vehicle. At the indicated time points after infection, virus titers in the supernatants were determined by a plaque assay. The data represent means ± SD. \*, *p* < 0.05; \*\*, *p* < 0.01; \*\*\*, *p* < 0.001 are considered statistically significant, compared to vehicle.

#### *3.3. Brevilin A Is E*ff*ective at the Viral Genome Replication and Translation Stage*

The life cycle of influenza virus is around 8–10 h and is divided into three steps: virus entry (0–2 h), viral genome replication and translation (2–8 h), and progeny virion release (8–10 h) [23]. To investigate the stage of viral cycle where brevilin A exhibits its activity against PR8 virus, we next performed time of addition experiments. MDCK cells were infected with PR8 virus, and brevilin A was added or removed at the indicated time points. The expression levels of influenza M2 protein in infected cells were measured at four time-intervals, 0–2, 2–4, 4–8 and 8–10 hpi. We found that the M2 level at the interval 4–8 hpi was reduced around 70%, compared to the vehicle. In contrast, no antiviral activity was detected for the remaining three intervals (0–2, 2–4, 8–10 hpi) (Figure 3A). These data indicate that brevilin A is effective at the viral genome replication and translation stage. No inhibitory effect was observed at virus entry stage or progeny virion assembly/release stage.

We then performed two other experiments to examine the mode of action of brevilin A. First, brevilin A was added to the IAV infected cells at 0, 4, 6, or 8 hpi, the supernatant was collected at 24 hpi, and the virus titers were determined by plaque assay. The virus titers were decreased when brevilin A was added at 0–4 hpi, compared to vehicle. However, similar titers were observed in the treatment and vehicle control when the compound was added 6 h after infection (Figure 3B). Moreover, the results obtained with an immunofluorescent assay showed that compared to the vehicle control, the expression of viral protein M2 was markedly reduced when brevilin A was added at 0 to 4 hpi, and addition of brevilin A at 6 hpi still had a minor impact on M2 expression (Figure 3C). These data suggest that brevilin A blocks the intermediate stage (s) of the influenza virus life cycle between approximately 4 to 6 hpi.

**Figure 3.** Influence of different treatment conditions of brevilin A on IAV replication. (**A**) MDCK cells were infected with PR8 at a MOI of 1, brevilin A or vehicle was present at four time-intervals, 0–2, 2–4, 4–8, and 8–10 hpi. At 12 hpi, cell lysates were analyzed by Western blot assay; (**B**) MDCK cells were infected with PR8 at a MOI of 0.1, then treated with brevilin A (8 μM) at 0, 2, 4, or 6 hpi. The virus titers in the supernatant were determined by plaque assay at 24 hpi; (**C**) MDCK cells infected with PR8 (MOI = 1) were treated with brevilin A at the indicated times. The M2 protein expression was determined by immunofluorescence assay at 12 hpi. The scale bar in the images is 100 μm. The data represent means ± SD. \*, *p* < 0.05 is considered statistically significant compared to vehicle.


*Article* **Abnormal Dorsal Caudate Activation Mediated Impaired Cognitive Flexibility in Mild Traumatic Brain Injury**

**Hui Xu 1,2,\*, Xiuping Zhang 3 and Guanghui Bai 1,4,\***

**Abstract:** Background: Mild traumatic brain injury (mTBI) is an important but less recognized public health concern. Previous studies have demonstrated that patients with mTBI have impaired executive function, which disrupts the performance of daily activities. Few studies have investigated neural mechanisms of cognitive flexibility in mTBI patients using objective tools such as the psychological experiment paradigm. Here, we aimed to examine neural correlates of cognitive flexibility in mTBI. Methods: Sixteen mTBI patients and seventeen matched healthy controls (HCs) underwent functional MRI during a rule-based task-switching experimental paradigm. Linear models were used to obtain within-group activation maps and areas of differential activation between the groups. In addition, we conducted mediation analyses to evaluate the indirect effect of abnormal dorsal caudate activation on the association between information processing speed and cognitive flexibility in mTBI. Results: mTBI patients exhibited significantly longer reaction time in the task switching (TS) condition compared to HCs, reflecting impaired cognitive flexibility. In addition, the patients showed reduced activation in the dorsal caudate (dCau), anterior cingulate cortex, and other frontal regions during the TS condition. Mediation analysis revealed that the reduced dCau activation had a significant effect on the relationship between information processing speed and cognitive flexibility in mTBI. Conclusions: Abnormal dorsal caudate activation in mTBI mediates impaired cognitive flexibility, which indicated dorsal caudate might be playing a vital role in the cognitive flexibility of mTBI patients. These findings highlight an alternative target for clinical interventions for the improvement of cognitive functions in mTBI.

**Keywords:** mild traumatic brain injury; functional MRI; cognitive flexibility; task switching; dorsal caudate


**3. Proposed Method**

Computer vision tasks, such as self-driving vehicles, under-water robots and remote sensing, employ real-time haze removal to realise fast and robust image recognition. In this section, a real-time and highly accurate haze-removal algorithm is proposed.


**1. Introduction**

Opportunistic managers, rather than maximizing the shareholder's wealth, tend to misuse the organizational resources for their own benefit. A good set of governance practices and ownership structures can mitigate the conflict of interest between the principles and the agents, hence enhancing the firm value. The purpose of this paper is to investigate the effect of corporate governance quality and ownership structure on the relationship between agency cost and firm performance. This is one of the few studies to explore the relationship between agency costs and firm performance in a dynamic modeling approach. Specifically, this study aims to address the following research questions: (1) Does corporate governance quality mitigates the relationship between agency cost and firm performance? (2) How do ownership concentrations affect the relationship between agency cost and firm performance? (3) How do state and non-state companies moderate the relationship between agency cost and firm performance?

Data is extracted of 2248 Chinese A-listed companies for the period 2008–2016. Using both fixed effects and dynamic panel generalized methods of moment estimation, the results show that agency cost is negatively related to firm performance. At the same time, corporate governance and ownership concentration enhances firm performance. When corporate governance and ownership concentration are taken as a moderating variable, we find a positive impact on the agency–performance relationship. We also studied the effect of ownership type on the association between agency cost and firm performance. Non-state ownership positively moderates the relationship between agency cost and firm performance. In contrast, the agency cost keeps its negative sign when the state ownership is taken as a moderating variable. Our conclusions are supported by taking alternative measures of independent variables for robustness.


**4. Conclusion**

The management of early glottic cancer is controversial, with no head to head randomized controlled trials comparing oncologic/survival or functional/QOL outcomes between modalities. The majority of studies in the literature consist of single arm retrospective series, with few head to head retrospective series. A meta-analysis by our group (Higgins et al., 2009) showed a significant increase in overall survival with TOL surgery, and similar local control and laryngectomy-free survival between modalities. Voice outcomes were similar between modalities, but with an overall tendency for improved voice outcomes with radiotherapy. Three recent head-to-head studies have been published since our analysis, with two of these studies (Mahler et al., 2010; Schrijvers et al., 2009) showing a significant increase in LFS with TOL surgery. A recent systematic review (Spielmann et al., 2010) was unable to find clear differences in voice outcomes and QOL measures between modalities. The review demonstrated improved electroacoustic scores in some patients treated with radiotherapy, but did not demonstrate improvement in voice QOL. The most striking difference between treatment modalities is financial, with four of five recent studies (Higgins, 2011; Philips et al., 2009; Goor et al., 2007;, Brandenburg et al., 2001) showing TOL surgery to be more cost-effective. It is also worthwhile to note that TOL surgery is less time consuming for patients. Patients undergoing TOL surgery convalesce over a matter of days while patients undergoing radiotherapy are treated over four or more weeks. In summary, it is our view that although TOL surgery and radiotherapy may share similar oncologic, voice, and QOL outcomes, TOL surgery offers the distinct advantages of reduced health care costs and shorter duration of treatment.

#### **5. References**

174 Otolaryngology

(Performance Status Scale for Head and Neck Cancer Patients), and were more likely to have a Voice Handicap Index (VHI-10) score of 10 or more. However, another Canadian study by Osborn et al demonstrated a non-significant trend for increased voice-related quality of life (V-

Our meta-analysis (Higgins et al., 2009) demonstrated a trend for improved voice quality with radiotherapy, yet this was a non-significant finding. Currently, the major argument in favour of radiotherapy is improved voice quality, but this has yet to be born out in largescale systematic studies. It is also difficult to link electroacoustic analytic outcomes with

Our group (Higgins, 2011) recently published a cost-utility analysis comparing TOL surgery to radiotherapy and demonstrated an almost two-fold increase in cost with radiotherapy. The TOL surgery cost \$2475.65 CAD/case, generating 1.663 QALYs, whereas radiation cost \$4965.85 CAD/case, generating 1.506 QALYs. Another Canadian cost analysis was reported by Philips et al (Philips et al., 2009) and concluded that radiotherapy was four times as costly as TOL surgery. A recent Dutch study (Goor et al., 2007) also demonstrated the increased cost of radiotherapy. The total cost of radiotherapy and TOL surgery was 8322 euros and 4434 euros, respectively. In addition, an American study by Brandenburg et al (Brandenburg et al., 2001) demonstrated increased costs associated with radiotherapy compared to TOL surgery. In contrast, a single Belgian study (Gregoire et al., 1999) documented an increased cost of TOL surgery compared to radiotherapy. However, this study reported a 30% positive margin rate in the TOL surgery group, and positive margins

Overall, the majority of studies point to an increased cost with radiotherapy compared to TOL surgery. However, it is worthwhile to note that each of these five studies did not include patients undergoing robotic TOL surgery, which may impact significantly on cost

The management of early glottic cancer is controversial, with no head to head randomized controlled trials comparing oncologic/survival or functional/QOL outcomes between modalities. The majority of studies in the literature consist of single arm retrospective series, with few head to head retrospective series. A meta-analysis by our group (Higgins et al., 2009) showed a significant increase in overall survival with TOL surgery, and similar local control and laryngectomy-free survival between modalities. Voice outcomes were similar between modalities, but with an overall tendency for improved voice outcomes with radiotherapy. Three recent head-to-head studies have been published since our analysis, with two of these studies (Mahler et al., 2010; Schrijvers et al., 2009) showing a significant increase in LFS with TOL surgery. A recent systematic review (Spielmann et al., 2010) was unable to find clear differences in voice outcomes and QOL measures between modalities. The review demonstrated improved electroacoustic scores in some patients treated with radiotherapy, but did not demonstrate improvement in voice QOL. The most striking difference between treatment modalities is financial, with four of five recent studies

RQOL) among patients who underwent radiotherapy as opposed to TOL surgery.

subjective vocal function and QOL outcomes.

were managed with adjuvant radiotherapy instead of re-excision.

**3.3 Cost effectiveness**

effectiveness.

**4. Conclusion**

**12**

*Romania*

**Epigenetics in Head and**

Magdalena Chirilă

**Neck Squamous Cell Carcinoma**

*"Iuliu Haţieganu" University of Medicine and Pharmacy Cluj-Napoca,*

In addition to the genetic information required to establish an organism, recent decades have unveiled a previously unknown type of chromatin modification, known as epigenetic, which is defined as heritable DNA changes that are not encoded in the sequence itself. Unlike genetic modifications, the epigenetic ones are reversible, and increasingly appear to

It is increasingly evident that genetics alone cannot explain the complexity of phenotypes in the living world. Heritable phenotypic characteristics that are not caused by DNA sequence alterations represent the object of epigenetics and include potentially reversible changes such as histone modifications, DNA methylation, and imprinting. At the interface between epigenetics and genomics, a new discipline that is emerging, epigenomics, promises to profoundly change the way we envision phenomena in the biological and medical sciences. Epigenetic modifications can provide an astronomic number of distinct signatures, with huge diagnostic and prognostic value, but it is essential to consider all the different sources

Epigenomics-based diagnostic tools for early cancer detection represent an exciting development. Tumors shed their DNA into the blood, and epigenetic changes that occur early during tumorigenesis, sometimes even in premalignant lesions, can provide valuable biomarkers. Previous research at Epigenomics identified Septin 9 as a single gene in which DNA methylation changes occur very early in colorectal cancer development and are present in the vast majority of tumors of all stages. In most tissues, CpG (cytosine 5 phosphorylated guanine) islands around transcription start sites are largely unmethylated, but their methylation has been described in many tumors and can serve as potential biomarkers. One of the advantages of using epigenomic biomarkers is that, in most cases,

Stephen B. Baylin, M.D., professor of cancer research and deputy director of The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins University and colleagues recently presented a molecular model to explain how DNA methylation causes gene silencing in mammalian cells. They used the GATA-4 gene as a model to investigate how polycomb protein complexes and DNA methylation maintain the chromatin in its silent state. They found that polycomb protein occupancy at genomic regions enriched in trimethylated

serve fundamental roles in cell differentiation and development.

DNA methylation changes precede clinical symptoms.

**1. Introduction**

of information.


**1. Introduction**

The Asian temperate mixed forest in northeastern China is one of the three major temperate mixed forests in the world (i.e., northeastern North America, Europe, and East Asia) [1], which is of great strategic importance to the carbon trading of China. The forests of Northeast China have experienced three periods of excessive timber harvesting in the last century, including the period of Russian and Japanese aggression (1896–1945), the period of encouraging excessive harvesting for timber production (1950–1977), and the period of national economic reforms and the broadening of international relations (1978–1998) [2]. The excessive logging and neglected cultivation of forests nearly exhausted exploitable forest reserves in the region [3]. Since the Natural Forest Conservation Program (NFCP) was put into practice in 1998, there was a profound shift in focus from timber production to environmental protection by rehabilitating damaged forest ecosystems, afforesting desertified and degraded areas, and banning logging in natural forests [2]. In this context, natural secondary forests (NSFs) are gradually expanding and gaining importance. NSFs, which account for as much as 70% of the forests of northeastern China, refer to as the natural-regeneration forests after stand-replacing disturbances of primary forests by anthropogenic activities or by extreme natural events [4,5]. Nowadays, the NSFs

**Citation:** Du, C.; Fan, W.; Ma, Y.; Jin, H.-I.; Zhen, Z. The Effect of Synergistic Approaches of Features and Ensemble Learning Algorithms on Aboveground Biomass Estimation of Natural Secondary Forests Based on ALS and Landsat 8. *Sensors* **2021**, *21*, 5974. https://doi.org/ 10.3390/s21175974

Academic Editors: Moulay A. Akhloufi and Mozhdeh Shahbazi

Received: 8 August 2021 Accepted: 2 September 2021 Published: 6 September 2021

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

**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

of northeastern China are gradually recovering from the excessive logging of the 20th century, which led to an extraordinary reduction in the quality of the forest ecosystem. NSFs are of significance to China not only for timber supply, but also for a vital reservoir of biodiversity, potential carbon sequestration, a destination of ecological tourism, and a broad ecological shelter for northeastern China [2].

The accurate estimation of forest aboveground biomass (AGB) has a critical effect on the understanding of forest quality and recovery in the NSFs of northeastern China. AGB is defined as the dry mass of live or dead matter from tree or shrub life forms, typically expressed as a mass per area density (e.g., Mg/ha) [6]. In general, AGB could be obtained by (1) direct harvest method; (2) allometric equation-based method; (3) biomass expansion factor (BEF)-based method; (4) process-based biogeochemical modeling; (5) remote sensingbased estimation method. Although the direct harvest method is the most exact among these methods, it is time-consuming, destructive, and labor-intensive. It is only suitable for AGB estimation of a small area or of individual trees with a small sample size [7] and is usually applied as reference data to establish allometric equations of AGB (e.g., [8,9]). An allometric equation-based method is more flexible and feasible than the direct harvest method to estimate AGB on both individual tree and plot levels. A variety of allometric equations are developed for diverse tree species by modeling the relationship between AGB and various physical parameters of trees, such as diameter at breast height (DBH), tree height, crown diameter, etc. (e.g., [8,10–13]). Similar to an allometric equation-based method, the BEF-based method applied BEF defining as the ratio of all stand biomass to growing stock volume to convert timber volume to biomass [14]. However, the allometric equation-based and BEF-based methods are still time-consuming and expensive because both of them are based on the acquisition of field measurements (such as DBH, tree height), and still limited to plot-level or individual tree-level AGB estimations. Process-based biogeochemical models consider the processes including photosynthesis, absorption, and carbon allocation, and generally couple biology, soil, climate, hydrology, and anthropogenic effects [15]. To some degree, these models could improve the conventional, point-based estimation of biomass over large areas [16]. However, the high uncertainties in biomass estimation due to constraints in data source, spatial resolution, homogeneous assumption, and inaccuracy of models greatly limit the usage of process-based biogeochemical models [15]. The remote sensing-based method is exceedingly appealing for estimating forest biomass on a large scale (e.g., local, regional or global) because of its unique characteristics such as repetitive data acquisition, large coverage, digital format, and so on [15], and of the capability of providing spatially explicit AGB estimates for every pixel location, instead of only the mean or total biomass within a given inventory unit [17,18]. Nowadays, it becomes the most commonly used method for large-scale AGB estimation [19–21].

In the last three decades, researchers have attempted a variety of remotely sensed data sources to estimate AGB. With a relatively long history of data availability, optical satellite imagery (such as Landsat, MODIS, etc.) has become a primary data source for biomass estimation (e.g., [22–25]). In particular, Landsat series satellite imagery is the most commonly used data source for AGB estimation (e.g., [26–30]), mainly because of the continuous, long-term, medium spatial resolution, and cross-calibrated data for global surface observations, and free access policy [31]. However, it is of significance to notice the data saturation in Landsat imagery, which refers to the phenomenon that spectral reflectance values are not sensitive to the change in biomass of mature forest or advanced successional forests even if AGB varies significantly [32,33]. For example, Steininger [34] found that the canopy reflectance in Landsat imagery saturates when the AGB approaches 15 kg/m2 or over 15 years of age in Brazilian tropical secondary forests. Zhao et al. [33] examined the saturation values in Landsat imagery for different vegetation types in a subtropical region, and found the AGB saturation values for pine forest, mixed forest, Chinese fir forest, broadleaf forest, bamboo forest, and shrub were 159, 152, 143, 123, 75, and 55 Mg/ha, respectively. Data saturation in optical imagery like Landsat significantly lowers the accuracy and increases the uncertainties of AGB estimation [15]. Data saturation

still exists in RADAR (Radio Detection and Ranging) data like SAR (Synthetic Aperture Radar) [35]. Generally speaking, saturation values could be higher obtained by longer wavelengths (such as L and P bands) and lower by shorter wavelengths (such as C bands), and also vary for different forest structures [36]. Until now, the data saturation problem caused by remote sensing signals is still one of the biggest obstacles to applying optical imagery and RADAR data for AGB estimation [15,37,38].

Since the 1990s, it has been found that LiDAR (Light Detection and Ranging) is more advantageous than optical imagery for AGB estimation because it is more relative to tree height and produces less estimation error [39]. Meanwhile, LiDAR is unaffected by the data saturation problem, even for high AGB values (>1000 Mg/ha) [40]. Thus, LiDAR data is widely used in AGB estimation in the last two decades. According to the format of return signals, LiDAR can be classified into discrete and continuous LiDAR; according to platforms, LiDAR can be classified into spaceborne, airborne, UAV(Unmanned Aerial Vehicle), terrestrial, backpack/handheld LiDAR; according to the size of the footprint, LiDAR can be classified into small footprint (footprint size <1 m), mid footprint (footprint size: 10–30 m), and large footprint LiDAR (footprint >50 m) [41]. In recent years, Airborne Laser Scanning (ALS) data, a kind of discrete, multiple returns, and small footprint LiDAR data captured from an aerial platform, has received much scientific and operational attention for AGB estimation than any of the other remote sensing data [42]. ALS emits laser pulses towards the ground and receives the pulses reflected from the tree canopy, branches, leaves, trunk, shrub, and then ground to form a three-dimensional profile of forest structure. ALS is far more capable than optical and RADAR sensors in estimating forest parameters and is considered the premier tool for large-scale AGB estimation (e.g., [43–47]). It is beneficial to estimate AGB by capturing both two-dimensional spectral information of the upper canopy and three-dimensional structural information of the canopy. However, the spectral characteristics of vegetation provided by ALS are very limited since most LiDAR systems only work at a single wavelength [48]. Thus, the integration of optical imagery and ALS data has become the most promising approach for large-scale AGB estimation (e.g., [48–53]).

Features are the most direct representation or manifestation of data sources. Feature extraction and selection could greatly influence the accuracy of AGB estimation [54]. A variety of spectral-related features including band combinations, textures, diverse vegetation indices, leaf area index, fraction of vegetation cover, and so on were derived from optical imagery for AGB estimation (e.g., [29,55–58]). Similar, diverse point-based features including height statistics (e.g., mean, maximum, variance, skewness, etc.), canopy-based quantile estimators, canopy relief ratio, laser penetration rates, canopy closure, and so on were extracted from LiDAR data for AGB estimation (e.g., [25,46,52,59,60]). Some researchers directly combined optical imagery and LiDAR features (e.g., [21,61,62]) while a few of them designed novel features derived from optical imagery and LiDAR data to improve AGB estimation. For example, Zhang et al. [48] developed two novel groups of features (i.e., *COLI*1 and *COLI*2) using seven vegetation indices derived from Landsat 8 and the best-performing LiDAR variable (i.e., mean of height). The *COLI*1 and *COLI*2 were generated by the multiplication and ratio combinations of the best-performing LiDAR variable and each vegetation index, respectively. They found that the stacked sparse autoencoder network model with the combination of all *COLI*1, optical, and LiDAR features yielded the highest accuracy of AGB estimation for the coniferous and broadleaf mixed forest of southeast China. However, whether it is more efficient to use novel features extracted from both data than directly combine all features is still needed to be further investigated.

In addition to data sources and features, it is vital to establish a reliable and suitable model to estimate AGB. Currently, most remote sensing-based AGB estimation methods use data-driven empirical models, which can be divided into parametric and nonparametric models [63]. Parametric models explicitly determine parameterized expressions of independent variables (e.g., spectral bands) and the dependent variable of interest (e.g., AGB) assuming the probability distributions of the variables being assessed [63]. Multiple linear regression, a classic parametric model with normality assumption, was

the most widely used method in previous AGB studies due to their simplicity and interpretability (e.g., [53,64,65]). Other parametric models, like non-linear regression (e.g., an exponential, power, or polynomial fitting function), were also applied for AGB estimations (e.g., [59,66,67]). Unlike parametric models, nonparametric models are distribution-free methods in which the predictor does not take a predetermined form but is constructed according to information derived from the data. Most machine learning models belongs to non-parametric, such as artificial neural network (ANN), random forest (RF), k-nearest neighbor (KNN), support vector machine (SVM), cubist (CB), classification and regression tree (CART), convolutional neural networks (CNN) and so on. Without the assumption of distribution, the non-parametric machine learning models are extremely flexible and capable of capturing the complex relationships between remote sensing variables and AGB, and widely applied in AGB estimation (e.g., [43,68–73]).

Ensemble learning, a branch of machine learning, is designed to learn tasks by constructing and then integrating multiple learners to produce a strong learner for improving accuracy [74,75]. There are three basic categories of ensemble learning: bagging, boosting, and stacking. RF and adaptive boosting (AdaBoost) algorithms are classic representatives of bagging and boosting algorithms, respectively. RF builds trees using subsamples and a random subset of predictors and can be very effective for estimating AGB due to its robustness to overfitting and noise in the training dataset [43,76,77]. Adaptive boosting is an iterative boosting algorithm that adaptively changes the distribution of the training set based on the performance of previous learners. Another boosting algorithm, called extreme gradient boosting (XGBoost), has been demonstrated to show great advantages in decreasing overestimation of low AGB values and underestimation of high AGB values for a forest type-based biomass estimation using continuous forest inventory data and Landsat 8 imagery [54]. Stacking, first proposed by Wolpert [78], is another method for combining multiple models but is less used than bagging and boosting. Unlike the RF algorithm that the base learner is homogeneous (e.g., regression tree), stacking are heterogeneous ensemble algorithms that could integrate diverse base learners to generate a stronger learner. The stacking algorithm was used to estimate canopy height in forestry (e.g., [79]), however, its potential has not been fully explored in AGB estimation.

Although the synergistic utilization of ALS and optical passive imagery was proved to improve AGB estimation [48], the synergistic approach (i.e., features) has not been fully investigated, especially for NSFs with complex structures. For example, is it more efficient to apply a novel feature extracted from passive imagery and LiDAR data (e.g., *COLI*1 and *COLI*2 in [48]) or directly combine all the features from the two data sources (like [61])? In addition, will ensemble learning algorithms improve the accuracy of AGB estimation for NSFs? Inspired by these questions, this study aimed at exploring the effects of different synergistic approaches of features and ensemble learning algorithms on AGB estimation of NSFs of northeastern China based on ALS and Landsat 8 OLI (Operational Land Imager) imagery. Specifically, the objectives of this study were (1) to investigate the effects of different data sources and classic machine learning algorithms on AGB estimation of a natural secondary forest; (2) to grope for a highly effective approach to combine ALS and Landsat 8 OLI imagery on AGB estimation of a natural secondary forest; (3) to explore the performances of ensemble learning algorithms in estimating AGB of a natural secondary forest; (4) to generate an accurate wall-to-wall AGB map of a natural secondary forest for future forest resources management.

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

#### *2.1. Study Area*

The study area is located in Maoershan Experimental Forest Farm of Northeast Forestry University (NEFU), Shangzhi, Heilongjiang Province, China, ranging from 127◦29 to 127◦44 E and 45◦14 to 45◦29 (Figure 1). The landform of the forest farm belongs to a low mountain and hilly area. The terrain gradually rises from south to north, with an

average elevation of 300 m. The highest mountain is Maoer Mountain, with an elevation of 805 m.

**Figure 1.** The location of study area: (**a**) The location of Maoershan Experimental Forest Farm within Heilongjiang Province; (**b**) the locations of 195 plots (20 m × 30 m) within Maoershan (Background: Landsat 8 OLI image).

The total area of the forest farm is 26,496 ha, which belongs to a typical natural secondary forest in northeastern China. The vegetation in the Maoershan area is a part of Changbai plant flora, with the original zonal top-level community of Korean pine broad-leaved forest. Due to the destruction in the last century, the original vegetation has undergone reverse succession. It has formed a forest landscape in which natural secondary forests are dominated by precious broad-leaved forests, poplar and birch forests, oak forests, and so on, and plantations such as red pine and larch are inlaid. The main species include *Betula platyphylla*, *Quercus mongolica*, *Populus davidiana*, *Larix olgensis*, *Pinus sylvestris*, and *Pinus koraiensis*, etc. The average forest coverage rate is 95%, and the total stock is approximately 3.5 million m3.

#### *2.2. Data Collection*

#### 2.2.1. Remotely Sensed Data

The remotely sensed data utilized in this study include ALS data and Landsat 8 OLI imagery. ALS data were obtained in September 2015. It is a secondary product scanned by the LiDAR sensor (Riegl LMS-Q680i) carried by the LiCHY system of the Chinese Academy of Forestry. The maximum frequency of the laser pulse of the LiDAR sensor is 400 kHz, with a wavelength of 1550 nm, a scanning angle of ±30◦, a sampling interval of 1 ns, and vertical accuracy of 0.15 m. The sidelap of this flight strip was designed to be greater than 60%, with an average point cloud density of 3.6 points·m−2.

To be consistent with ALS data in time, the Landsat 8 OLI imagery acquired on 13 September 2015 was applied in this study (downloaded from https://earthexplorer.usgs. gov/ (accessed on 1 September 2021)). The scene ID is LC81170282015256LGN01 (L1T-level product), with cloudiness of 1.35%, sun elevation angle of 45.28◦, and sun azimuth angle of 154.91◦. Seven multispectral bands (band1–band7) of 30 m nominal spatial resolution were utilized in this study. The radiometric resolution of the imagery is 12 bits and the swath width is 185 km × 185 km.

#### 2.2.2. Reference Data

The 195 fixed plots data of continuous forest resources inventory obtained in 2016 was applied as reference data in this study (see Figure 1b). The plot size was 20 m × 30 m and the center of each plot was correctly determined using a GPS (accuracy ±5 m). The diameter at breast height (DBH) of the trees larger than 5 cm and the tree species of each plot were recorded.

The AGB of individual trees was calculated using the species-specific allometric growth equations with DBH. In this study, the allometric growth models developed by [80,81] for the major species of trees and understory in northeastern China were employed to calculate the AGB of individual trees. The allometric growth equation was showed as Equation (1) and the parameters of major species of trees and understory were listed in Table 1.

$$\mathcal{W} = \begin{array}{c} a \cdot D^b \end{array} \tag{1}$$

where *W* represents aboveground biomass (kg), *D* represents DBH (cm), *a* and *b* are estimated parameters of different species in [80,81]. The AGB of the plot was the cumulative summation of the AGB of individual trees of each plot.

**Table 1.** Estimated parameters (*a* and *b*) of the allometric growth models of different species applied in this study.

1 Represents plantations; otherwise are natural forests. 2 represent arbor-like mixed species of understory that do not have a specific Latin name.

#### *2.3. Methods*

To investigate the effects of different synergistic approaches of features and ensemble learning algorithms on AGB estimation of NSFs, a five-step methodology with three experiments of features (Feature experiments I-III) was implemented in this study, including (1) data preprocessing, (2) feature extraction and selection, (3) establishment and evaluation

of classic machine learning models, (4) establishment and evaluation of ensemble learning models, (5) wall-to-wall AGB prediction using the most effective algorithm and features. Feature experiment I was designed to explore the effects of features from different data sources (ALS, optical imagery, and combined data) on AGB estimation based on a variety of machine learning algorithms; Feature experiment II was designed to investigate how to efficiently combine the best-performing ALS feature (a unique feature) with several spectral features for AGB estimation, is it better to use novel extracted features or directly combine all the features?; Feature experiment III aims to compare the performance of combining all features for AGB estimation. The feature experiment design and logic of this study were shown in Table 2 and Figure 2, respectively.

**Table 2.** Feature experiments designed in this study.

1 Number of features was determined by the procedure described in Section 2.3.2. 2 *COLI*1 and *COLI*2 were calculated using Equations (3) and (4) described in Section 2.3.2. 3 Feature 3 is the best performing ALS feature.

**Figure 2.** The flowchart of this study. Note: the number in parentheses represents feature number. Feature 1: optimal ALS features; Feature 2: optimal Landsat 8 features; Feature 3: the best performing ALS feature; Feature 4: all *COLI*1s; Feature 5: all *COLI*2s.

#### 2.3.1. Preprocessing of Remotely Sensed Data

The preprocessing of the ALS data includes (1) noise elimination (such as air points, low points, and isolated points). The radius of a fitting plane and the multiples of standard deviation were set to 0.5 m and 1, respectively. The algorithm will automatically calculate the standard deviation of the surrounding fitting plane of a point. If the distance from this point to that plane is less than multiples of standard deviation, this point will be kept. (2) classification of ground and non-ground points. The ground points were classified by improved progressive triangulated irregular network densification (IPTD) filtering algorithm developed in [82]. The maximum building size and maximum terrain angle were set to 20 m and 88◦, respectively. (3) normalization of point clouds. A digital terrain model (DTM) with a resolution of 0.5m was generated based on ground points using the inverse distance weighted (IDW) interpolation method. The power of the distance between sampling points and an unknown point was set to 2, and the smallest number of points

used for interpolation was 12. Then, the point clouds were normalized by subtracting the DTM value from the elevation of all points. The preprocessing of the ALS data was implemented using LiDAR 360 V3.2 of GreenValley International.

Preprocessing of the Landsat 8 OLI imagery including radiometric calibration, atmospheric correction, and topographic correction was implemented using ENVI 5.3 software. The Fast Line-of-sight Atmospheric Analysis of Spectral Hypercube (FLAASH) radiative transfer model was implemented for atmospheric correction and conversion to surface reflectance in the EVNI environment. The topographic correction was conducted with the well-known Sun Canopy Sensor + C correction (SCS + C) approach using the extension tool of "Topographic Correction\_V5.3\_4\_S1". The SCS + C correction approach reduces overcorrection and is an effective topographic correction method in forested and mountainous terrain [83,84]. The SCS + C topographic correction model can be expressed by Equation (2).

$$L\_t = L \cdot \left(\frac{\cos \theta \cdot \cos \alpha + \mathcal{C}}{\cos i + \mathcal{C}}\right) \tag{2}$$

where *Lt* is the corrected pixel radiance value of the image; *L* is the uncorrected pixel radiance value of the image; *i* is the incidence angles on a horizontal surface; *θ* is the solar zenith angle; α is the slope angle; C is the semi-empirical parameter. DTM generated from ALS data was applied for topographic correction in this study.

2.3.2. Feature Extraction and Selection


**Author details**

Samuel Veras1 \* † , Verônica Kozmhinsky1†, Paulo Goes2† and Mônica Heimer 3†

1 Institute of Integral Medicine Professor Fernando Figueira, Recife, Brazil

2 Federal University of Pernambuco, Recife, Brazil

3 Pernambuco University, Recife, Brazil

\*Address all correspondence to<EMAIL_ADDRESS>
†These authors contributed equally.

© 2020 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.

**157**

1059-1063

*Behavioral and Psychosocial Factors as Mediators of the Oral Health Impact on Adolescents…*

[9] Crocombe LA, Broadbent JMW, Thomson M, Brennan DS, Poulton R. Impact of dental visiting trajectory patterns on clinical oral health and oral health-related quality of life. Journal of Public Health Dentistry.

[10] Nanayakkara V, Renzaho A, Oldenburg B, Ekanayake L. Ethnic and socio-economic disparities in oral health outcomes and quality of life among Sri Lankan preschoolers: A cross-sectional study. International Journal for Equity

[11] Nélio V, Pereira C, Amaral O. Prevalence and determinants of dental caries in a sample of schoolchildren of Sátão, Portugal. Revista Portuguesa de Estomatologia, Medicina Dentária e Cirurgia Maxilofacial. 2014;**55**:214-219

[12] Petersen PE. The World Oral Health Report 2003: Continuous improvement

approach of the WHO global oral health programme. Community Dentistry and Oral Epidemiology. 2003;**31**:3-23

[13] Mcgrath C, Bedi R. A national study of the importance of oral health to life quality to inform scales of oral health related quality of life. Quality of Life

of oral in the 21st century—The

Research. 2004;**13**:813-818

[14] Bernabé E, Tsakos G, De Oliveira CM, Sheiham A. Impacts ondaily performances attributed to malocclusion using the conditionspecific feature of the OIDP index. The Angle Orthodontist. 2008;**78**:241-247

[15] Bernabé E, Krisdapong S,

Sheiham A, Tsakos G. Comparison of the discriminative ability of the generic and condition-specific forms of the child-OIDP index: A study on children with different types of normative dental treatment needs. Community Dentistry and Oral Epidemiology. 2009;**37**:155-162

2012;**72**:36-44

in Health. 2013;**12**:89

*DOI: http://dx.doi.org/10.5772/intechopen.89567*

[2] Barbieri CH, Rapoport A. Evaluation

[1] Goes PSA, Watt RG, Hardy R, Sheiham A. Impacts of dental pain on daily activities of adolescents aged 14-15 years and their families. Acta Odontologica Scandinavica. 2008;**66**:7-12

of the quality of life of patients rehabilitated with implant-mucoussupported prostheses versus conventional total dentures. Brazilian Journal of Head and Neck Surgery. 2009;**38**:84-87

[3] Caglayan F, Altun O, Miloglu O, Kaya MD, Yilmaz AB. Correlation between oral health-related quality of life (OHQoL) and oral disorders in a Turkish patient population. Medicina Oral, Patología Oral y Cirugía Bucal.

[4] Bianco A, Fortunato L, Nobile CGA, Paiva M. Prevalence and determinants of oral impacts on daily performance: Results from a survey among school children in Italy. European Journal of Public Health. 2009;**20**:595-600

2009;**14**:573-578

[5] Bastos RS, Carvalho E,

Journal. 2012;**62**:137-143

Health. 2001;**18**:219-227

Health. 2007;**24**:217-224

Xavier A, Caldana ML, Bastos JRM, Lauris JRP. Dental caries related to quality of life in two Brazilian adolescent groups: A cross-sectional randomised study. International Dental

[6] Slade GD. Epidemiology of dental pain and dental caries among children and adolescents. Community Dental

[7] Goes PSA, Watt RG, Hardy R, Sheiham A. The prevalence and severity of dental pain in 14-15 year old Brazilian schoolchildren. Community Dental

[8] Lewis C, Stout J. Toothache in US children. Archives of Pediatrics and Adolescent Medicine. 2010;**164**:

**References**

*Behavioral and Psychosocial Factors as Mediators of the Oral Health Impact on Adolescents… DOI: http://dx.doi.org/10.5772/intechopen.89567*


**1. Introduction**

Native American architecture offers a unique opportunity to reconstruct the dwellings used and designed by the prehistoric communities. When the European explorers arrived in America at the end of the 15th century, they found a world that was already impossible to reconstruct in Europe [1]. By means of the information contained in their chronicles, the dwellings built by the communities that inhabited those lands can be reconstructed. They also show that their lifestyles ranged between nomadism and sedentarism, comprising a great variety of systems as a result of the combination of both of them. However, sedentarism is considered the final step of this process which continues until today and which was consolidated with the construction of the first settlements.

Studying the evolution of culture during Prehistory, the anthropologist and historian Leroi-Gourhan [2,3] published research in 1964 which contained a graph about the evolution of flint tools. That graph showed that, as millennia went by, the amount of flint used to obtain each point decreased as the resulting sharp increased. This way, he demonstrated that the evolution of human beings was determined by the efficiency improvement at work. In parallel to this transformation, the sedentary process had gone forward and each community had chosen a different system to live in, as the North America of the 15th century shows [4].

This way, it is viable to understand that the sedentary process went forward according to the pattern found by Leroi-Gourhan. Proceeding on this basis, the aim of the present research consists in determining if that pattern can also be found in the evolution of the dwellings which were designed during the sedentary process that took place throughout Prehistory in North America. In other words, if the evolution from the nomad dwellings to the sedentary models pursued an improvement on energy efficiency.

In order to achieve it, eight of the most relevant dwellings built by the North American natives were analyzed. The dwellings which were chosen are the tipis, used by tribes such as the Crow or the Sioux [4–18]; the wigwams built by the Ojibwa or the Chippewa [4,19–25]; the Navaho hogans [4,22,26–31]; the Caddoan grass houses [1,4,32–35]; the earthlodges built by the Mandan, the Hidatsa and the Arikara [4,22,36–38]; the plank houses used by the Haida [4,39–46]; the Iroquois longhouses [4,20,21,47–54]; and the pueblos, specifically one of the adobe houses built in Acoma [55–60]. Each one corresponds to a different step of the sedentary process (Figure 1).

**Figure 1.** The dwellings that were analyzed. First row, from left to right: tipi [61], wigwam [62], hogan [31] and grass house [61]. Second row, from left to right: earthlodge [63], plank house [45], longhouse [47] and pueblos [63].

The most affordable way to determine the efficiency level of the chosen dwellings would were by means of the shape factor. Defined as the ratio between the envelope surface area and the volume of air contained under it [64], it is one of the most popular parameters used to estimate the relation between the design of a building and its energy losses due to outward exposure. Despite its undeniable utility, it simplifies the morphology of the building and does not take into account some of its characteristics, such as its orientation, the existence of any excavated surface area or its indoor compartmentalization.

In order to solve these lacks, the present research proposes to determine the capacity of an envelope to transform the outdoor conditions into the indoor ones, proposing to interpret these buildings as if they were machines. This way, it consists in analyzing the capacity of an envelope to transform the outdoor temperature and the outdoor humidity into the indoor temperature and the indoor humidity, just by means of its presence. This means that an envelope works as an air-conditioning machine and contributes an amount of energy.

Besides, a statistical method was used in order to understand the relation of this parameter with the morphological and the technical aspects of the dwellings, as well as with their corresponding weather data.