2.3.3. The Objective Function of Coordinated Development

In order to demonstrate the principle of water–ecology–energy–food coordinated development in the process of water rights allocation, the existing coordinated development status can be quantified into a specific value, which is called the coordinated development index. The greater the coordinated development index is, the better the coordinated development status of the four resources is. The maximum index of coordinated development is taken as the objective function. The comprehensive evaluation method is used to calculate the coordinated development index. The comprehensive evaluation method [27,28] can select objective indicators from the regional economic, social, and ecological environment. Multiple indicators can be evaluated systematically and normatively at the same time, and the evaluation results can be quantified. Finally, a general numerical value is formed, and the evaluation purpose is achieved through numerical comparison.

(1) The selection of comprehensive evaluation indicators for coordinated development is shown in Table 1.

**Table 1.** The comprehensive evaluation indicators of water–ecology–energy–food coordinated development.

#### **Table 1.** *Cont.*

$$y\_{ij} = \frac{\mathbf{x}\_{ij} - \min(\mathbf{x}\_j)}{\max(\mathbf{x}\_j) - \min(\mathbf{x}\_j)},\tag{5}$$

when the indicator is negative

$$y\_{ij} = \frac{\max(\mathbf{x}\_j) - \mathbf{x}\_{ij}}{\max(\mathbf{x}\_j) - \min(\mathbf{x}\_j)},\tag{6}$$

where *yij* is normalized data; max(*xj* ) is the maximum indicator *j* in *n* years; and min(*xj* ) is the minimum indicator *j* in *n* years.

(B) The calculation of the index Calculate the weight of the indicator in the year *i* under the index *j*:

$$P\_{ij} = \left(\frac{y\_{ij}}{\sum\_{i=1}^{n} y\_{ij}}\right), i = 1, 2, \dots, n. \tag{7}$$

Calculate the information entropy of indicator *j*:

$$E\_{\vec{l}} = -\frac{1}{\ln n} \times \sum\_{i=1}^{n} \left( P\_{\vec{l}\vec{j}} \times \ln \left( P\_{\vec{l}\vec{j}} \right) \right). \tag{8}$$

Determine the weight of indicator *j*:

$$M\_{\vec{j}} = \left(\frac{1 - E\_{\vec{j}}}{k - \sum\_{j=1}^{k} E\_{\vec{j}}}\right), \vec{j} = 1, 2, \dots, l. \tag{9}$$

Calculate the coordinated development indicator *Gi* in the year *i*:

$$G\_{l} = \sum\_{j=1}^{k} \left( M\_{j} \times y\_{lj} \right). \tag{10}$$

(C) The objective function of coordinated development

$$\text{maxRG} = \text{maxG}\_{\prime} \tag{11}$$

where *RG* is the objective function of the coordinated development on water–ecology– energy–food.

#### 2.3.4. The Constraints of Industry Water Rights

The current water rights security for industrial and agricultural production and the water rights security for future life are taken, as constraints in this model. Domestic water is the sum of water for the daily life of residents and urban public water. Ecological water includes artificial lake replenishment, urban road sprinkler, and green space irrigation. The energy industry includes coal mining, coal washing, coking, crude oil refining (including gasoline, diesel, kerosene and other crude oil processing industries), and thermal power generation. Food planting includes the cultivation of rice, corn, wheat, and beans (potatoes do not grow in Yinchuan). Other agriculture includes planting industries other than food crops, as well as timber, livestock products, and fishery products. Other agriculture includes farming other than food crops, as well as timber, animal, and fish products.

(1) The constraints of water rights of life:

$$\mathcal{W}\_{\rm L} \ge \left(1 + \mathcal{N}\_{\rm II}\right)^{a} \mathcal{P}\_{\rm U} \times Q\_{\rm II} + \left(1 + \mathcal{N}\_{\rm R}\right)^{a} \mathcal{P}\_{\rm R} \times Q\_{\rm R} + \mathcal{G} \mathcal{D} \mathcal{P}\_{\rm UP} \left(1 + \mathcal{N}\_{\rm UP}\right)^{a} \times M\_{\rm GDP\prime} \tag{12}$$

where *WL* is the water rights of life (m3 ); *PU*, *PR* are the number of urban people and rural people; *NU*, *NR* are the population growth rate of urban and rural; *QU, QR* are the per capita domestic water quota for urban and rural; *GDPUP* is the *GDP* of urban public industry; *NUP* is *GDP* growth rate of urban public industry; and *MGDP* is the water consumption per CNY 10,000 *GDP*; *a* is the year for future domestic water security.

(2) The constraints of water rights of ecology:

$$\mathcal{W}\_{\rm E} \ge \mathcal{S}\_{\rm G} \times \mathcal{M}\_{\rm G} + \mathcal{S}\_{L} \times (\mathcal{E}\_{L} + \mathcal{K}\_{L}) + \mathcal{S}\_{R} \times \mathcal{M}\_{R\prime} \tag{13}$$

where *WE* is the water rights of ecology (m3 ); *SG* is the greening coverage area; *MG* is the quota for greening irrigation; *SL* is the area of artificial lake; *EL* is the evaporation supply quota of local lakes; *KL* is the infiltration supply quota of local lakes; *SR* is the area of urban roads; and *MR* is quota of urban road sprinkling.

(3) The constraints of water rights of energy industry:

$$\mathcal{W}\_{\rm N} \ge \sum (\mathcal{R}\_{\rm Nk} \times \mathcal{M}\_{\rm Nk})\_{\prime} \tag{14}$$

where *WN* is the water rights of energy industry (m3 ); *RNk* is the production of energy *k*; *MNk* is the water quota for the exploitation or processing of energy *k*.

(4) The constraints of water rights of food planting:

$$\mathcal{W}\_{\mathcal{F}} \ge \sum (\mathcal{R}\_{Fk} \times \mathcal{M}\_{Fk}).\tag{15}$$

(5) The constraints of water rights of other agriculture:

$$\mathcal{W}\_{\mathcal{O}} \ge \sum (\mathcal{R}\_{\mathcal{O}k} \times \mathcal{M}\_{\mathcal{O}k})\_{\prime} \tag{16}$$

where *WO* is the water rights of other agriculture (m3 ); *ROk* is the production of other agriculture *k*; *MOk* is the water quota of other agriculture.

(6) The constraints of water rights of general industry:

$$\mathcal{W}\_{\rm I} \ge \sum (\mathcal{R}\_{\rm Ik} \times \mathcal{M}\_{\rm Ik})\_{\prime} \tag{17}$$

where *WI* is the water rights of general industry (m3 ); *RIk* is the production of general industry *k*; *MIk* is the water quota of general industry.

(7) The constraints of total water rights:

$$\mathcal{W}\_L + \mathcal{W}\_\mathcal{E} + \mathcal{W}\_\mathcal{N} + \mathcal{W}\_\mathcal{F} + \mathcal{W}\_\mathcal{O} + \mathcal{W}\_\mathcal{I} \le \mathcal{W}\mathcal{R}\_\mathcal{\epsilon} \tag{18}$$

where *WR* is the total water rights in this city.

(8) The method to solve model

The MATLAB software and particle swarm optimization algorithm are used to solve the water rights allocation model in this study.

#### **3. Results**

According to the water rights allocation model proposed above, Yinchuan in 2019 is taken as an example to calculate the water rights allocation of coordinated development on water–ecology–energy–food. Among the data required for calculation, the water resources data are from Ningxia Water Resources Bulletin (2013–2019) [29–35], and social and economic data are from Yinchuan Statistical Yearbook (2014–2020) [36–42]. The total amount data of water rights allocation in Yinchuan comes from the Yellow River Institute of Hydraulic Research. We put the data into Equations (1) to (18), using MATLAB software to compile the particle swarm optimization algorithm for iterative solution. The result of water rights allocation for the coordinated development on water–ecology–energy–food in Yinchuan is obtained, as shown in Table 2:

**Table 2.** Water rights allocation scheme of the coordinated development of water–ecology–energy– food in Yinchuan.

#### **4. Discussion**

*4.1. Results Analysis of Water Resources Value in Various Industries*

It can be seen from Figure 2, after the allocation of water rights for the coordinated development on water- ecology-energy-food, the value of water resources in various industries in Yinchuan has changed. The water resources value in the living system it increased by 2.10 × 108 CNY, in the ecosystem it increased by 0.22 × 108 CNY, in the energy industry system it decreased by 0.70 × 108 CNY, in the food planting system it decreased by 0.32 × 108 CNY, it increased by 0.14 × 108 CNY in other agricultural systems, and it increased by 0.86 × 108 CNY in general industrial systems. The total water resources value increased by 2.31 × 108 CNY compared with before allocation. It can be seen that after the allocation of water rights, the overall value of water resources in Yinchuan city has increased, and the efficiency of water resources utilization has improved. When Li et al. [43] optimized the regional water use structure based on water resource vulnerability, they also took the industrial water resource value as an important influencing factor to allocate water resources. In this paper, emergy method is used to quantify the water resources value in various industries, which is conducive to obtain the objective and reliable allocated results. (1) Comparison of the water resources value in various industries under current water rights and allocated water rights. In the efficiency objective of city-industry water rights allocation model, the emergy method is used to calculate the value of water resources in various industries in this paper. The comparison of water resources value in various industries before and after water rights allocation is shown in Figure 2: rights and allocated water rights. In the efficiency objective of city-industry water rights allocation model, the emergy method is used to calculate the value of water resources in various industries in this paper. The comparison of water resources value in various industries before and after water rights allocation is shown in Figure 2:

(1) Comparison of the water resources value in various industries under current water

*Water* **2022**, *14*, x FOR PEER REVIEW 10 of 15

*4.1. Results Analysis of Water Resources Value in Various Industries*

**4. Discussion**

**Figure 2.** Comparison chart of water resources value in various industries under different water rights. **Figure 2.** Comparison chart of water resources value in various industries under different water rights.

It can be seen from Figure 2, after the allocation of water rights for the coordinated development on water- ecology-energy-food, the value of water resources in various industries in Yinchuan has changed. The water resources value in the living system it increased by 2.10 × 108 CNY, in the ecosystem it increased by 0.22 × 108 CNY, in the energy industry system it decreased by 0.70 × 108 CNY, in the food planting system it decreased by 0.32 × 108 CNY, it increased by 0.14 × 108 CNY in other agricultural systems, and it increased by 0.86 × 108 CNY in general industrial systems. The total water resources value increased by 2.31 × 108 CNY compared with before allocation. It can be seen that after the allocation of water rights, the overall value of water resources in Yinchuan city has increased, and the efficiency of water resources utilization has improved. When Li et al. [43] optimized the regional water use structure based on water resource vulnerability, they also took the industrial water resource value as an important influencing factor to allocate water resources. In this paper, emergy method is used to quantify the water resources value in various industries, which is conducive to obtain the objective and reliable allocated results. (2) Comparison of the value of water resources per cubic meter in various industries. (2) Comparison of the value of water resources per cubic meter in various industries. According to the calculation of the value of water resources and the allocation results of water rights in various industries, the value of water resources per cubic meter in Yinchuan city can be obtained. The value of water resources per cubic meter of the living system is the highest, reaching 15.54 CNY/m3 , followed by that of the energy industry system, reaching 10.28 CNY/m3 , and that of the food production system is the lowest, only 0.67 CNY/m3 . The value of water resources per cubic meter in the ecosystem is 2.05 CNY/m3 , that of other agricultural systems is 4.94 CNY/m3 , and that of general industrial systems is 5.37 CNY/m3 . Wang Yu et al. [44] used the emergy method to calculate the value of water resources per cubic meter of the four sectors (life, industry, extra-river ecology, and agriculture) in nine provinces and autonomous regions in the Yellow River Basin. They also obtained the result that the value of water resources per cubic meter of life sector is the largest and that of the agriculture sector is the smallest. Li et al. [43] also suggested that the value of water resources per cubic meter of agriculture is minimal. The food planting industry is faced with the problem of low water efficiency, and it is a trend that accelerates the development of regional water-saving agricultural engineering renovation.

#### According to the calculation of the value of water resources and the allocation results of water rights in various industries, the value of water resources per cubic meter in *4.2. Results Analysis of Coordinated Development Index G*

Yinchuan city can be obtained. The value of water resources per cubic meter of the Through the optimal allocation of the right to use water resources of various industries in Yinchuan in 2019, the change of water rights of various industries will directly affect the values of some comprehensive evaluation indicators. It will thus change the size of the coordinated development index on water–ecology–energy–food. The trend and

*Water* **2022**, *14*, x FOR PEER REVIEW 11 of 15

*4.2. Results Analysis of Coordinated Development Index G*

comparative analysis of that in Yinchuan from 2013 to 2019 under the condition of current water rights and allocated water rights are shown in Figure 3: comparative analysis of that in Yinchuan from 2013 to 2019 under the condition of current water rights and allocated water rights are shown in Figure 3:

Through the optimal allocation of the right to use water resources of various industries in Yinchuan in 2019, the change of water rights of various industries will directly affect the values of some comprehensive evaluation indicators. It will thus change the size of the coordinated development index on water–ecology–energy–food. The trend and

opment of regional water-saving agricultural engineering renovation.

living system is the highest, reaching 15.54 CNY/m3, followed by that of the energy industry system, reaching 10.28 CNY/m3, and that of the food production system is the lowest, only 0.67 CNY/m3. The value of water resources per cubic meter in the ecosystem is 2.05 CNY/m3, that of other agricultural systems is 4.94 CNY/m3, and that of general industrial systems is 5.37 CNY/m3. Wang Yu et al. [44] used the emergy method to calculate the value of water resources per cubic meter of the four sectors (life, industry, extra-river ecology, and agriculture) in nine provinces and autonomous regions in the Yellow River Basin. They also obtained the result that the value of water resources per cubic meter of life sector is the largest and that of the agriculture sector is the smallest. Li et al. [43] also suggested that the value of water resources per cubic meter of agriculture is minimal. The food planting industry is faced with the problem of low water efficiency, and it is a trend that accelerates the devel-

**Figure 3.** Trend and comparison of the water–ecology–energy–food coordinated development index **Figure 3.** Trend and comparison of the water–ecology–energy–food coordinated development index in Yinchuan city from 2013 to 2019 under different water rights conditions.

in Yinchuan city from 2013 to 2019 under different water rights conditions.

As can be seen from Figure 3, in terms of the extended development trend of the water–ecology–energy–food coordinated development index, except that the current As can be seen from Figure 3, in terms of the extended development trend of the water–ecology–energy–food coordinated development index, except that the current water rights declined in 2017, the current indexes and the allocated indexes basically showed an upward trend from 2013 to 2018. Both dropped significantly in 2019 compared to the previous year. Through the analysis of comprehensive evaluation indicators data, it is found that natural annual precipitation (*B1*) decreased significantly in Yinchuan in 2019, and the energy exploitation and food crop yield was decreased. As the result, the per capita water resources (*A1*), energy self-sufficiency rate (*C3*) and food self-sufficiency rate (*D4*) and other positive indicators decreased significantly, which has an impact on the coordinated development index in this year. The coordinated development index under the current water rights condition has a slight decline in 2017, which is due to the obvious decline of annual precipitation (*B1*) in this year compared with 2016.

It can also be seen from Figure 3 that in 2014 and 2016, the coordinated development index under current water rights is slightly larger than that under allocated water rights, which is mainly caused by the changing trend of the proportion of water rights in food planting (*AD1*). The proportion of water rights of food planting (*AD1*) peaked in 2014 and 2016, at 52.36% and 51.54%. Compared with the situation of current water rights in 2019, it is 30.90%, and the proportion of water rights of food planting (*AD1*) under allocated water rights is even smaller, only 27.62%. Under the condition of allocated water rights, the proportion of water rights of food planting (*AD1*) is more discrete than the current water rights, which leads to the decrease of the coordinated development index of water–ecology–energy–food.

From 2013 to 2016, the coordinated development index under the condition of allocated water rights was basically equal to that under the condition of current water rights. From 2017 to 2019, the coordinated development index under the condition of allocated water rights was significantly higher than that under the condition of current water rights. It can be shown that the regional water–ecology–energy–food coordinated development state obtained by water rights allocation in this paper is superior to the current situation. The water rights allocation model established in this paper can provide reference and help to promote the coordinated development of regional water–ecology–energy–food. From 2013 to 2016, the coordinated development index under the condition of allocated water rights was basically equal to that under the condition of current water rights. From 2017 to 2019, the coordinated development index under the condition of allocated water rights was significantly higher than that under the condition of current water rights. It can be shown that the regional water–ecology–energy–food coordinated development state obtained by water rights allocation in this paper is superior to the current situation. The water rights allocation model established in this paper can provide reference and help to promote the coordinated development of regional water–ecology–energy–food.

water rights declined in 2017, the current indexes and the allocated indexes basically showed an upward trend from 2013 to 2018. Both dropped significantly in 2019 compared to the previous year. Through the analysis of comprehensive evaluation indicators data, it is found that natural annual precipitation (*B1*) decreased significantly in Yinchuan in 2019, and the energy exploitation and food crop yield was decreased. As the result, the per capita water resources (*A1*), energy self-sufficiency rate (*C3*) and food self-sufficiency rate (*D4*) and other positive indicators decreased significantly, which has an impact on the coordinated development index in this year. The coordinated development index under the current water rights condition has a slight decline in 2017, which is due to the obvious

It can also be seen from Figure 3 that in 2014 and 2016, the coordinated development index under current water rights is slightly larger than that under allocated water rights, which is mainly caused by the changing trend of the proportion of water rights in food planting (*AD1*). The proportion of water rights of food planting (*AD1*) peaked in 2014 and 2016, at 52.36% and 51.54%. Compared with the situation of current water rights in 2019, it is 30.90%, and the proportion of water rights of food planting (*AD1*) under allocated water rights is even smaller, only 27.62%. Under the condition of allocated water rights, the proportion of water rights of food planting (*AD1*) is more discrete than the current water rights, which leads to the decrease of the coordinated development index of water–

#### *4.3. Results Analysis of Water Rights Allocation 4.3. Results Analysis of Water Rights Allocation*

ecology–energy–food.

A comparative analysis is made between the current water rights of various industries in Yinchuan in 2019 and the allocated water rights in various industries based on the coordinated development of water–ecology–energy–food in this paper, as shown in Figure 4. A comparative analysis is made between the current water rights of various industries in Yinchuan in 2019 and the allocated water rights in various industries based on the coordinated development of water–ecology–energy–food in this paper, as shown in Figure 4.

*Water* **2022**, *14*, x FOR PEER REVIEW 12 of 15

decline of annual precipitation (*B1*) in this year compared with 2016.

**Figure 4.** Comparison of the percentage of current water rights and allocated water rights in various industries. **Figure 4.** Comparison of the percentage of current water rights and allocated water rights in various industries.

As can be seen from Figure 4, the allocated water rights of life in Yinchuan increased by 1.07%, the allocated water rights of ecology increased by 1.85%, the allocated water rights of energy industry decreased by 1.09%, that of food planting decreased by 3.27%, that of other agriculture increased by 0.83%, and general industry increased by 0.65% compared with the current water rights. Water rights of life and ecology have increased, while agricultural water rights have decreased and industrial water rights have little change, which is consistent with the optimization trend of water resources in the Yellow River Basin proposed by Xia et al. [45]. In addition, according to Yinchuan's future economic and social development focus, urban planning and industrial and agricultural construction characteristics, the water rights allocation scheme based on coordinated development of water–ecology–energy–food in this paper is reasonable and sustainable, which can provide some reference for the reasonable allocation of regional water rights.

#### **5. Conclusions**

In this paper, the water resource is taken as the object of control, and a municipalindustry water rights allocation model for the coordinated development of water–ecology– energy–food is established. The fairness objective of the model is established by satisfaction function, the efficiency objective is established by the emergy method, and the coordinated development objective is calculated by comprehensive evaluation method. We calculate the water security for each industry as constraints of the water right allocation model. The conclusions are as follows:

There are still some shortcomings in this paper: It is difficult to completely distinguish the cross industries when dividing the industries, and it is also difficult to make comprehensive statistics of all water use units in the industry. Further research is needed in the future.

**Author Contributions:** All authors contributed to the study conception and design. Data curation, H.Y.; formal analysis, W.Z.; methodology, Y.H.; writing—original draft, Y.H.; writing—review and editing, W.Z. All authors commented on previous versions of the manuscript. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by Basic R&D Special Fund of Central Government for Nonprofit Research Institutes (HKY-JBYW-2020-17) and National Natural Science Foundation of China (No. 51979119).

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

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** The original data used during the study were provided by a third party. The data that support the findings of this study are available in "Ningxia Water Resources Bulletin" and "Yinchuan Statistical Yearbook". These data were derived from the following resources available in the public domain: Ningxia Water Resources Bulletin: http://slt.nx.gov.cn/xxgk\_281/fdzdgknr/ gbxx/szygb/ accessed on 20 June 2022. Yinchuan Statistical Yearbook: http://www.yinchuan.gov. cn/xxgk/zfxxgkml/tjxx/tjnj/ accessed on 20 June 2022. The authors have made sure that all data and materials as well as software application or custom code comply with field standards.

**Conflicts of Interest:** The authors have no conflict of interest to declare that are relevant to the content of this article.

## **References**


2. Etiology and embryology

Though unexplained, a young maternal age and low socioeconomic status are the commonest risk factors for GS [10, 11]. Smoking, drugs, environmental toxins and poor nutrition have also been implicated [12]. A genetic link in the form of homozygous gene polymorphisms has been reported [13] and is substantiated by an increased prevalence among familial cases of birth defects and twins [14].

The embryological origin of GS is still a matter of conjecture. Several theories have been put forward attempting to expound the abdominal wall defect: failed body-wall folding [15]; a vascular insult to the omphalo-mesenteric artery [16] or to the right umbilical vein [17]; a localized disruption of the amniotic membrane [18]

midline and may involve solid organ prolapse. Ultrasound is instrumental in picking up closing GS which is defined as a worsening ratio of intra vs. extra peritoneal bowel dilatation [27]. Further aids to diagnosis of GS are high levels of maternal serum alpha-fetoprotein (MSAFP) [28], intrauterine growth retardation with or without oligo-/an-hydramnios [7, 29, 30]. As GS is usually an isolated anomaly with very few risks to the mother or child, termination of pregnancy is not habitually

A spontaneous onset of labor will typically occur around 36 weeks gestation and the route of delivery is dependent on obstetric indications [33, 34]. There is a lack of high-level evidence to support early induction of labor in uncomplicated GS cases [35, 36] and a similar lack of evidence to support cesarean section [37]. Early

LMICs have an overall high mortality rate in neonates with correctable congenital anomalies [38, 39] and suffer from a lack of medical facilities and personnel [40]. Non-governmental and governmental organizations have been criticized for not doing enough [41, 42] though new partnerships are attempting to redress this

Mortality from GS in low-to-middle-income countries (LMICs) can reach up to 80–100% [45–48] which is in sharp contrast to the <10% in HICs [49]. Sepsis is a major culprit in most cases of neonatal mortality in LMICs [48]. The Gastroschisis International (GiT) network has suggested that poor resuscitation combined with sepsis and abdominal compartment syndrome is directly linked to the poor outcome [50].

Antenatal care may not be well developed [51] or mothers may engage poorly with it [52] which risks births in areas far from the reach of the pediatric surgeon. A delay in transfer of the neonate with GS remains a main concern [47, 53] however a recent study from South Africa has suggested that resuscitation at the initial point of care and throughout transfer may be the key to improving the end result [51].

A GS infant is ideally delivered at or near a facility with pediatric surgical support [25]. Conversely, outborn cases have been shown to have worse outcomes such as longer days on parenteral nutrition and longer duration to achieving full

The accepted approach to managing GS is to cover the gut with a sterile bag (Figure 3), nasogastric decompression and fluid resuscitation. Hypothermia is a major risk due to the exposed gut and significant fluid losses [55]. Premature babies are particularly prone to hypothermia because of their high ratio of skin surface to weight and a lower amount of subcutaneous and brown fat. They may also have respiratory

The authors follow the protocol outlined in Figure 4. At the outset doctors and nurses are reminded that the triad of hypovolemia, hypothermia and sepsis are the major threats to this neonate and that resuscitation is directed to mitigating their

issues which impact on their oxygen consumption and heat production [55].

offered [2, 31, 32].

Management of Gastroschisis

[43, 44].

feeds [54].

119

4. Timing and mode of delivery

DOI: http://dx.doi.org/10.5772/intechopen.85510

(emergency) delivery is beneficial in closing GS [26].

5. GS in low to middle income countries (LMICs)

6. Initial management (pre-operative management)

Figure 1. Gastroschisis with prolapsed bowel to the right of the umbilicus.

or teratogen-induced mesenchymal failure [19]. None of the theories are fully satisfactory [20]. The right-sided occurrence of the defect has been linked to the position of the yolk sac [15, 21] without clear reasoning as to why. Left-sided defects have also been described [22].


*<IP_ADDRESS> Plenity™*

*Weight Management*

(non-exhaustive list).

*<IP_ADDRESS> SmartByte Device*

related SAEs were observed.

**7.2 Weight-management devices**

*7.2.1 Oral removable palatal space-occupying devices*

control arms, respectively. Device- or procedure-related AEs were observed in 93 subjects (83.8%, mainly peristomal granulation tissue, abdominal pain, and nausea/ vomiting, mild in the majority of cases). Device- or procedure-related SAEs were

Overall, AspireAssist® is relatively safe and has a strong effectiveness. The device was approved by the FDA in June 2016. It is indicated for weight loss in

ommendations, in subjects who failed to respond to non-surgical weight-loss therapy. It is contraindicated in several conditions including pregnancy, non-adult subjects, upper gastrointestinal bleeding conditions, chronic abdominal pain, severe cardiopulmonary diseases, and eating disorders (non-exhaustive list). Complications include skin irritation, infection, and electrolyte abnormalities

SmartByte Device (Scientific Intake) is an oral device occupying space on the upper palate. It includes a temperature-recording sensor to monitor usage (**Figure 6**). It is worn in mouth during meal consumption. The device is renewed every 12 months. By creating limited bite size and slower eating, SmartByte Device

ized into SmartByte Device (n = 102) or control (no oral intervention, n = 71) arms for 4 months. All subjects were given lifestyle recommendations. The primary effectiveness endpoint, assessed in the ITT population at Month 4, was a greater responder rate at 5% weight loss in SmartByte Device arm compared to control arm. At Month 4, the responder rates at 5% weight loss were 20.6 and 5.6% in SmartByte Device and control arms, respectively. The study did not meet the primary effectiveness endpoint. At Month 4, the weight losses were 1.7 and 0.4% in SmartByte Device and control arms, respectively. Device-related AEs were observed in five subjects (4.9%, including two episodes of transient choking on food). No device-

causes a decrease in food intake with subsequent weight loss [16]. In the pivotal study, 173 subjects (BMI between 26 and 36 kg/m2

*SmartByte Device (Scientific Intake—Picture downloaded from the internet).*

, in conjunction with lifestyle rec-

) were random-

observed in four subjects (3.6%), including peritonitis but no death.

obesity with BMI between 35 and 55 kg/m2

**248**

**Figure 6.**

Plenity™ (Gelesis, Inc.) is a superabsorbent hydrogel (cellulose and citric acid, forming a three-dimensional matrix) administered orally in capsules with 500 mL of water (three capsules, 20–30 minutes before lunch and dinner). The hydrogel particles hydrate up to 100 times their initial weight in the stomach and intestine (**Figure 7**). The particles mix with ingested food and create a larger volume with higher elasticity and viscosity. The particles degrade in the colon and are eliminated in the feces. By creating a larger volume with higher elasticity in the stomach and intestine, Plenity™ causes early satiety and a decrease in food intake with subsequent weight loss [17].

In the pivotal study, 436 subjects (245 females, 191 males, mean BMI = 33.8 kg/m2 ) were randomized into Plenity™ (n = 223) or control (sham capsule, n = 213) arms for 6 months. All subjects were given lifestyle recommendations. The co-primary effectiveness endpoints, assessed in the ITT population (multiple imputation) at Month 6, were a significantly greater weight loss in Plenity™ arm compared to control arm (supersuperiority) and the responder rate at 5% weight loss in Plenity™ arm. At Month 6, the weight losses were 6.4 and 4.4% in Plenity™ and control arms, respectively, and the responder rate at 5% weight loss in Plenity™ arm was 58.6%. The study did not meet the first co-primary effectiveness endpoint but met the second co-primary effectiveness endpoint. Most device-related AEs were of gastrointestinal origin (mainly abdominal distension, diarrhea, infrequent bowel movements, and flatulence, mild in the majority of cases), observed in 84 subjects (37.7%). No device-related SAEs were observed.

Overall, Plenity™ is safe and has a modest effectiveness. The device was cleared by the FDA in April 2019. It is indicated to aid in weight management in overweight and obesity with BMI between 25 and 40 kg/m2 , in conjunction with lifestyle recommendations. It is contraindicated in pregnancy, non-adult subjects, and history of allergic reaction to the components of Plenity™ capsule. No relevant complications have been reported.

**Figure 7.** *Plenity™ (Gelesis, Inc.—Picture downloaded from the internet).*

Comparative effectiveness of the above anti-obesity medical devices is reported in **Table 2**.

#### **Table 2.**

*Approved/cleared anti-obesity medical devices in the USA ranked by extent of total body weight loss in pivotal studies.*

Relevant complications (non-exhaustive list), some being very rare, of the above anti-obesity medical devices are reported in **Table 3**.

#### **Table 3.**

*Relevant complications of the approved/cleared anti-obesity medical devices in the USA in pivotal studies.*

#### Cost of the above anti-obesity medical devices is reported in **Table 4**.

**251**

**Author details**

Hassan M. Heshmati

**Conflict of interest**

Endocrinology Metabolism Consulting, LLC, Anthem, AZ, USA

surgery). Their use should always be combined with lifestyle changes.

The author received honorarium for consultancy from Gelesis, Inc.

© 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,

\*Address all correspondence to<EMAIL_ADDRESS>
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*Anti-Obesity Medical Devices*

Garren Gastric Bubble).

**approval**

**11. Conclusions**

*DOI: http://dx.doi.org/10.5772/intechopen.91697*

countries (e.g., Epitomee Device [18]).

been challenged for safety reasons [8, 11–14].

play a major role in the management of obesity.

**10. Over-the-counter anti-obesity medical devices**

products (e.g., NozNoz, slow control fork, slipper genie).

**8. Anti-obesity medical devices withdrawn from the market in the USA**

**9. Anti-obesity medical devices under investigation or pending**

Several anti-obesity medical devices have been withdrawn by the manufacturers from the market in the USA after approval by the FDA (e.g., Maestro Rechargeable System, Realize Adjustable Gastric Band, ReShape Integrated Dual Balloon System,

Several anti-obesity medical devices are currently in development in different

EndoBarrier® has obtained a CE mark in the EU but its approval in the USA has

A variety of anti-obesity medical devices are available as over-the-counter

Anti-obesity medical devices represent a heterogenous family of devices in terms of presentation, usage/administration, mechanism of action, effectiveness, safety, regulation, availability, and cost. They offer an attractive approach in managing obesity. Anti-obesity medical devices are positioned to bridge the gap between more conservative treatments (e.g., lifestyle) and more aggressive interventions (e.g., bariatric

Considering the large market size of obesity treatment and the small percentage of subjects treated with drugs or bariatric surgery, anti-obesity medical devices can

#### **Table 4.**

*Cost of the approved/cleared anti-obesity medical devices in the USA.*

*Weight Management*

in **Table 2**.

**Table 2.**

*studies.*

Comparative effectiveness of the above anti-obesity medical devices is reported

**Medical device Treatment duration Total body weight loss** Lap-Band® 36 months 18.0% AspireAssist® 12 months 12.1% Orbera™ Intragastric Balloon System 6 months 10.2% TransPyloric Shuttle 12 months 9.5% Obalon Balloon System 6 months 6.6% Plenity™ 6 months 6.4% SmartByte Device 4 months 1.7%

Relevant complications (non-exhaustive list), some being very rare, of the above

*Approved/cleared anti-obesity medical devices in the USA ranked by extent of total body weight loss in pivotal*

Lap-Band® 36 months Proximal gastric enlargement, band erosion or

AspireAssist® 12 months Skin irritation, infection, electrolyte abnormalities

Obalon Balloon System 6 months Balloon migration, intestinal obstruction, gastric

**Relevant complication**

migration, system leaks

6 months Balloon migration, intestinal obstruction, gastric ulcer, gastric perforation

ulcer, gastric perforation

Cost of the above anti-obesity medical devices is reported in **Table 4**.

**Medical device Average cost (Range)** Lap-Band® \$15,000 (\$10,000–\$30,000) AspireAssist® \$10,000 (\$7,000–\$13,000) Orbera™ Intragastric Balloon System \$6,000 (\$3,000–\$9,000) TransPyloric Shuttle To be determined Obalon Balloon System \$8,000 (\$6,000–\$9,000) Plenity™ \$100/month SmartByte Device \$500

*Relevant complications of the approved/cleared anti-obesity medical devices in the USA in pivotal studies.*

anti-obesity medical devices are reported in **Table 3**.

Plenity™ 6 months None

*Cost of the approved/cleared anti-obesity medical devices in the USA.*

**duration**

TransPyloric Shuttle 12 months Device impaction, gastric ulcer

SmartByte Device 4 months Choking on food, mouth soreness

**Medical device Treatment**

Orbera™ Intragastric Balloon

System

**Table 3.**

**250**

**Table 4.**


**Author details**

*Assorted Dimensional Reconfigurable Materials*

solution-processed planar PSCs (**Table 2**).

**3. Conclusions**

transferred to the conduction band of SnO2, thus enhancing the conductivity of SnO2 and reducing the charge recombination at the interface. SnO2/GQDs fabri-

Xiaojuan et al. [55] tried to incorporate chemical modified (2D naphthalene diimide) graphene into SnO2 nanocrystal as ETL for highly efficient PSCs. They modified SnO2 with 2D naphthalene diimide-graphene, which can increase the surface hydrophobicity and is responsible for the van der Waals interactions

between surfactant and perovskite. Thus, highly efficient PSCs were fabricated with maximum PCE of 20.2% and enhanced fill factor of 82%, which could be attributed to the improved electron extraction ability, electron mobility and the reduced carrier recombination, resulting in the increased FF. This work provides an important direction for further search in utilizing carbonaceous materials for low-temperature

Graphene, due to its unique properties, has been explored widely in solar cells, and graphene metal oxide nanocomposites have been widely used in emerging third-generation solar cells. In view of reported literature, it is obvious that these materials played a significant role in enhancing the efficiency of 3G solar cells. In this chapter, the use of graphene nanocomposites has been explored in DSSCs and PSCs. Graphene nanocomposites as photoanode material in DSSCs seemed to be a promising approach to increase the charge transport, charge separation and thus the performance of solar cell. The low cost of graphene brings new prospects for commercialization, particularly to replace the use of Pt as counter electrode in DSSCs. In PSCs, the use of graphene and its derivatives with metal oxide (G/ metal oxide nanocomposites) as electron transport layer has shown to be valuable. Incorporating of graphene into metal oxide reduces the series resistance and the charge recombination between perovskite and metal oxide as well as improves the electron and hole transport from the perovskite layer to the corresponding electrodes. Moreover, graphene nanocomposites have proved to be an efficient electron-transporting layer fabricated at lower temperature, thus suitable for flexible substrates in PSCs. Furthermore, these materials are interesting to replace Pt-FTO or ITO and noble metals (silver or gold) in 3G solar cells. Thus, the efficient replacement of the existing expensive materials reduces the cost of third-generation

**4. Futuristic aspects/prospective of graphene metal oxide**

nanocomposites in different layers of solar cells is necessary.

Graphene-based materials are interesting from the perspective of both fundamental science and technology due to their nontoxicity, chemical and thermal stability and mechanical strength. Although graphene metal oxide nanocomposites can be used to enhance the PCE of 3G solar cells by various optimization methods, manufacturing of highly efficient and stable solar cell is challenging. Moreover, much practical work needs to be done to obtain the optimal performance. From the future perspective, a mechanism for physical-chemical interactions of these

From energy point of view, graphene metal oxide nanocomposites can be used for energy storage and conversion devices such as solar cells, fuel cells, batteries, capacitors, etc. The unique graphene properties, such as high conductivity and

cated solar cell showed low hysteresis and average PCE of 19.2%.

**34**

solar cells.

**nanocomposites**

Tahira Mahmood\*, Madeeha Aslam and Abdul Naeem National Centre of Excellence in Physical Chemistry, University of Peshawar, Peshawar, Pakistan

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**5.2 PiL testing of SM1**

In **Figure 8**, results for the starting of the SM1 have been given. Tracking of the reference speed is precise.

In **Figure 9**, results for the reversing of the speed of the SM1 have been given. Tracking of the reference speed is again obtained precisely.

**Figure 11.** *Starting of SM2-PiL.*

**Figure 12.**

**Figure 13.**

**165**

*Load step changes of SM2-PiL.*

*Reversing of the speed of SM2-PiL.*

*Synchronous Machine Nonlinear Control System Based on Feedback Linearization…*

*DOI: http://dx.doi.org/10.5772/intechopen.89420*

**Figure 9.** *Reversing of the speed of SM1-PiL.*

**Figure 10.** *Load step changes of SM1-PiL.*

*Synchronous Machine Nonlinear Control System Based on Feedback Linearization… DOI: http://dx.doi.org/10.5772/intechopen.89420*

**Figure 11.** *Starting of SM2-PiL.*

To check the novel control algorithm PiL, testing of both (SM1 and SM2) machines have been done. Testing included starting process, reversing of the speed

In **Figure 8**, results for the starting of the SM1 have been given. Tracking of the

In **Figure 9**, results for the reversing of the speed of the SM1 have been given.

Tracking of the reference speed is again obtained precisely.

and load step changes.

*Control Theory in Engineering*

**5.2 PiL testing of SM1**

reference speed is precise.

*Reversing of the speed of SM1-PiL.*

**Figure 9.**

**Figure 10.**

**164**

*Load step changes of SM1-PiL.*

**Figure 12.** *Reversing of the speed of SM2-PiL.*

**Figure 13.** *Load step changes of SM2-PiL.*

In **Figure 10**, results for the load step changes of the SM1 have been given. The step change is from no load to 100% of the nominal load. Except from rotor speed and electromagnetic torque, results of damper flux observer and load torque estimation are also given.

**Appendix**

**Author details**

Marijo Šundrica

**167**

Synchronous machine SM 1 parameters:

*DOI: http://dx.doi.org/10.5772/intechopen.89420*

0.162 (p.u.), Inertia constant *H*: 0.14 (s). Synchronous machine SM 2 parameters:

q-axes *L*σQ: 0.0509 (p.u.), Inertia constant *H*: 2.2 (s).

Power *Sn*: 1560 (kVA), Voltage *Un*: 6300 (V), pole pairs *p*: 5, frequency *f*n: 50 (Hz),

stator winding resistance *R*s: 0.011 (p.u.), stator winding leakage inductance *L*σs: 0.148 (p.u.), mutual inductance d-axes *L*md: 1.177 (p.u.), mutual inductance q-axes *L*mq: 0.622 (p.u.), rotor winding resistance *R*f: 0.0017 (p.u.), rotor winding leakage inductance *L*σf (p.u.): 0,186, damper winding resistance d-axes *R*D: 0.0481 (p.u.), damper winding leakage inductance d-axes *L*σD: 0.096 (p.u.), damper winding resistance q-axes *R*Q: 0.0256 (p.u.), damper winding leakage inductance

Končar—Power Plant and Electric Traction Engineering, Zagreb, Croatia

© 2019 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,

\*Address all correspondence to<EMAIL_ADDRESS>
provided the original work is properly cited.

There is an error of about 10% in observer operation, and an error in load torque estimator of about 5%. This is due to reduction in data precision during PiL testing. In spite of that, an error in speed tracking exists only during the step change and it is about 3%.

#### **5.3 PiL testing of SM2**

In **Figure 11**, results for the starting of the SM2 have been given. Tracking of the reference speed is precise.

In **Figure 12**, results for the reversing of the speed of the SM2 have been given. Tracking of the reference speed is again obtained precisely.

In **Figure 13**, results for the load step changes of the SM2 have been given. The step change is from no load to 100% of the nominal load. Except from rotor speed and electromagnetic torque, results of damper flux observer and load torque estimation has been also given.

There is an error of about 15% in observer operation, and an error in load torque estimator of about 3%. This is due to reduction in data precision during PiL testing. In spite of that, an error in speed tracking exist only during the step change and it is about 2%.


**1. Introduction**

Given the broad economic, environmental, and social challenges in the modern competitive environment, it is not surprising that effective sustainability management has emerged as an important variable in the strategic management process [1, 2]. Increasingly, firms are finding it necessary and beneficial to build sustainability principles into their strategic planning, and the extant research has shown that effective strategic management of sustainability can have a variety of positive outcomes for the firm such as improved economic [3, 4], improved human resource factors [5, 6], and reputational benefits [7, 8]. Historically, strategic sustainability management has had an 'outputs' focus [9, 10], such as, the focus on reporting sustainability outcomes fundamental to the triple-bottom line (TBL) framework. However, scholars have recently noted the shortcomings of the TBL (and similar) frameworks that emphasise the outputs of sustainability management rather than the antecedent resources and capabilities [11]. Recently, there has been a push to reassess the research approach to researching effective sustainability management processes by refocusing on the application and nature of strategic inputs [12]. Over the past 30 years, the focus on strategic antecedents has been evident in other disciplines (e.g., human resource management, accounting and finance, and marketing) that have been elevated to operate as integral aspects of the strategic management process.

The most popular theoretical strategic management lens for the exploration of strategic inputs is the resource-based view of the firm (RBV) [13, 14]. As RBV literature developed, scholars increasingly focussed on the nature of intangible assets, as research showed that it was these assets that were the most integral to establishing a sustainable competitive advantage [15]. One such asset that has received increasing attention is the knowledge capabilities that exist within a firm, and how that knowledge can be accessed and applied to strategic decision making [16]. This has led to the establishment of the knowledge management (KM) field of strategic management research, an extension of the RBV focussing exclusively on the application and nature of knowledge in a competitive context [17, 18]. The concept of knowledge management (KM) has become the key theoretical framework through which knowledge is examined and researched [19, 20].

Insofar as there has been research seeking to align principles of KM and sustainability, these have been retrospective in nature rather than deliberate and systematic [21]. Frameworks such as those by [22] have sought to improve the sustainability of the KMs themselves. Whilst this is a valuable pursuit that has the potential to benefit firm processes, it does not offer solutions to the effective management of sustainability. Other frameworks, such as, the one devised by [23] sought to reconfigure sustainability at the conceptual level so as to fit it into extant finance/ HRM/marketing KM structures. These have ultimately been proven to be insufficient for the challenges facing modern firms operating in today's competitive landscape [21, 24]. There is a notable absence in the literature of a KM that actually provides insight into the effective strategic management of sustainability [24]. Given its demonstrable importance to the strategic management process, and the noted absence of a knowledge management process dedicated to the sustainability concept, this chapter seeks to address the broad research opportunity to explore what elements comprise a sustainability knowledge management system.


**5. Conclusions**

From our investigations, we conclude that the potassium channel Kv1.3, but not KCa3.1, contributes to SMC proliferation in arteriogenesis by controlling the expression of growth factor receptors, as well as their downstream genes relevant for phenotype switch and cell cycle progression.

**Author Contributions:** M.L. wrote and prepared the manuscript; A.C.M., K.K., H.I.-A., and S.M. the experiments; E.D. conducted the scientific direction and wrote the manuscript. All authors have read and agreed to the published version of the manuscript.

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

**Acknowledgments:** We thank Anna Kluever for proofreading the manuscript.

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