**5. Action of** *BRCA1* **and** *BRCA2* **proteins in DNA double strand damage repair**

Although the action of the *BRCA1* and *BRCA2* gene products in cancer causation is not fully discovered [9], their function in maintaining the genomic stability is well understood. This involves the DNA double strand break repair [DSB] which is the most deleterious type of DNA damage as no healthy DNA strand left for the repair mechanism [10]. The DSB will be repaired by 2 mechanisms in the healthy eukaryotic cells -The Homologous directed repair [HDR] pathway, which is a highly accurate system and Non-Homologous end joining [NHEJ] pathway which is prone to errors. BRCA1 and BRCA2 proteins involve in the HDR mechanism following stimulated by the cellular DNA damage response. This function is facilitated by other cellular proteins including RAD51 [11, 12], Ataxia-Telangiectasia kinase [ATM-kinase].

The following flow chart shows the mechanism of DNA DSB repair and the steps involving the BRCA1/2 proteins (**Figure 2**).

Mutation of the *BRCA1/2* genes causing loss of the encoded protein functions causes abnormal checkpoint stimulation and genomic errors in DNA repair

**Figure 2.**

*Action of BRCA1/2 protein in DNA double strand break repair. Source - functions of* BRCA1 *and* BRCA2 *in the biological response to DNA damage [13].*

causing cancer development through uncontrolled cellular proliferation, impaired cell apoptosis in abnormal cells.


**Abstract**

Chronic lymphocytic leukemia (CLL) is the most common type of leukemia in developed countries. CLL is diagnosed with absolute B lymphocyte count (B-ALC) >5000/micrL sustained for at least 3 months, morphologically mature-appearing small lymphocytes, and flow cytometry showing the typical immunophenotype of CLL cells. Different prognostic parameters are used to differentiate between low-and high-risk patients, which would affect treatment decisions. Rai and Binet staging systems are the two most commonly used in practice. There has been a significant change in how we manage patients in CLL over the last 5 years. We have shifted away from chemoimmunotherapy toward novel agents such as BTK, PIK3, and BCL-2 inhibitors, which are not only more efficacious but are also safer and better tolerated. New prognostic models are being developed, and it appears that minima residual disease (MRD) directed therapy will become the norm in the future. Many clinical trials are looking at various combinations of novel therapies, with a defined period of treatment based on MRD analysis, to enable patients to have a period of treatmentfree remission instead of continuous therapy. In this chapter, we summarize the latest updates in CLL management.

**Keywords:** CLL, leukemia, treatment, chemoimmunotherapy, MRD, novel agents


**1. Introduction and statement of the problem**

Forest living communities (FLCs) essentially depend on forests for meeting their basic needs of food, cloth, shelter and other essentials. FLCs get direct income through Non-Wood Forest Products (NWFPs) harvest and trade sale. Commonly the FLCs sell their NWFPs harvest without value addition, which results in less income, if FLCs make value addition to the harvested NWFPs their income can be increased by 400%. To undertake NWFPs value addition the FLCs require microfinance assistance and eco-friendly technologies. If they are provided with microfinance to meet their basic needs and procuring eco-friendly technologies, the FLCs can undertake NWFPs value addition for increasing their income level. Therefore the main purpose of this study is appreciates prevalent microfinance practices, NWFPS value additions and EFTs that are available to the FLCs to enhance their income level and reduce drudgery of FLCs that gradually lead to arrest environmental degradation [1–3] and up keep of natural resources.

## **2. Mainstream microfinance institutions**

In India major sources of microfinance are (a) organized sector (banks, government agencies [4] etc.) and (b) un-organized sector (money lender, traders relatives, friends etc.) The former is regulated by government bodies like Reserve Bank of India (RBI), banking regulation act etc., and the later has no formal regulatory bodies. Microfinance falls under the primary sector and they are supposed to meet specific pre-decided targets.

## **3. The SHG-bank linkage phenomenon**

#### **3.1 Model-I: bank – SHG - members**

In this SHGs are formed by group members themselves, after surviving for six months the SHG can link itself with a bank close to the group members and deposit their entire saved amount into the bank account. The bank sanctions credit/loan to the SHG four times to the groups saved and deposited amount e.g. the SHG saved INR 1000 and deposited into bank savings account, the bank sanctions an amount INR 4000 as credit, thus total amount INR 5000 is available to the SHG for onward lending to the group members.

#### **3.2 Model-II: bank - facilitator agency - SHG - members**

The second groups are formed by NGOs (in most of the cases) or by government agencies. The groups are nurtured and trained by these agencies. Government or other community-based organizations to take the lead in forming the SHGs, and then provide savings and credit facilities by the banks. Even after the linkage with banks, these facilitating agencies continue interacting with the groups. Most linkage experiences begin with this model with Non-Government Organizations (NGOs) playing a major role. This model has also been popular and more acceptable to banks, as some of the difficult functions of social dynamics are externalized.

#### **3.3 Model - III: bank – NGO - MFI (micro-finance institute) - SHG - members**

Due to various reasons, banks in some areas are not in a position to even finance SHGs promoted and nurtured by other agencies. In such cases, the NGOs promoted and nurtured the groups and also act as financial intermediaries. First, they promote the groups, nurture and train them and then approach banks for bulk loans for onlending to the SHGs. The banks lend to these intermediaries for onward financing to the groups or their members.

Study area selection:

**Rationale of selecting,** Atmakuru (Atmakur) /Kurnool, Pembi (Nirmal) /Adilabad, Polavaram (Eluru) /West Godavari in Andra Pradesh these forest divisions are bestowed with NWFPs abundantly.

#### **4. Methods of NWFPS value additions**

When the researcher undertook research study survey in the select geographical area, the investigator observed and noted the below outlined NWFPs value addition systems. These value addition systems can be categorized into two [5] different value additions system: i) Manual system, adding value to NWFPs conventionally

**23**

distant market.

dweller/harvester.

*Microfinance Practices and NWFPs Value Additions for Sustainable Environment…*

by FLCs e.g. stitching leaf plates with bamboo nails and ii) technology supported system, doing value NWFPs with the help of EFTs e.g. stitching leaf plate with the

**Grading:** dividing all harvest (collected NWFPs) into various type considering the harvest color, weight, size, appearance, etc. This grading will help the harvester

**Washing:** collected NWFPs can be washed with water or can wiped with cloth in case of NWFPs, such as, gums, up rooted herbs, bulbs etc., can benefit NWFPs

**Sizing:** Harvested medicinal herbs necessitate cutting herbs into different sizes of the harvested herb. This sizing value can be undertaken harvester that benefits

**Aeration**: after harvesting NWFPs its life (longevity) period can be enhanced especially in case of Mahua (*Madhuca latifolia*) Kullu (*Sterculia urens*), Gooseberry/ Aonla (*Emblica officinalis)* this value addition enhances the [6] bargaining power of the harvester and enable him/her to earn more price, which eventually lead to increase income level and better quality of life to the forest dwellers who harvests NWFPs. **Steaming**: NWFP like Gooseberry/Aonla **(***Emblica officinalis)* needs to be deseeded, to deseed the harvested Gooseberry fruits can be steamed, after steaming the fruits will become soft to deseed safely and pulp of Gooseberry can be dried in the sun light seeds can be traded separately. This will have dual benefit of increased

**Warehouse:** NWFPs are natural resources, [7] they will come in appropriate season, yet consumption of NWFPs will be done every day. NWFP like Mahua flowers will come in summer season for a couple of months, if the harvester sells it as soon as it is harvested, he or she gets below normal price as everybody may sell the harvested stocks which results increased supply that results in weak bargain power of seller. Alternately the harvest can be stored in warehouse for a couple of months or more which will enable the seller to get better and increased price. **Breaking:** NWFPs like Mahua seeds, Sal seeds, and sal seeds, Achar (Buchanania lanzan) seeds are having upper hard husks that can be broken with

sticks to get inner required grains that give the harvester a better price.

**Fastening**: *Bauhinia vahlii* (leaf/*eistar aaku*) are harvested [8]) from large barker which are used as material for making for meals plates, cups etc. which are bio-degradable and eco-friendly. The forest [8] dweller harvest these green leave and sell in loose without value addition. But these loose leaves drying for a couple of days three to four leaves can be fastened with the help of bamboo stick small nails or can be stitched with the help of sewing machine and further with the help of the compressor an edge can be made to make like dining steel plate which give five to six

**Crushing**: NWFPs like soap nuts [9], Emblica officinalis, *Terminalia chebula*. and *Terminalia chebula* Retz are hard nuts. These nuts can be crushed with grinding machine or manual crushing implements that will give enhanced prices to the harvester, further the crushed powder can be packed and sold in the local market or

**Baking**: NWFPs like sal seeds have wings like parts, to make it tradable the wings like part is to be dissected from the seed this can be done by way of baking the seeds in the fire with the fuel wood, which can fetch better price to the forest

**Microfinance**: while conducting the research study survey it was learned that, forest dwelling communities sell their NWFPs as soon as they harvested for want of money at low price to fulfill daily needs. If these forest dwellers are provided [1–3] with access to small amount of money (microfinance) to obtain their daily needs, they

*DOI: http://dx.doi.org/10.5772/intechopen.95419*

to seek enhanced price for different grades.

price separate trade for pulp and seeds.

time more price than if sold in as raw leaves.

them in sourcing better price and increased market.

help of sewing machine.

harvester.

*Microfinance Practices and NWFPs Value Additions for Sustainable Environment… DOI: http://dx.doi.org/10.5772/intechopen.95419*

by FLCs e.g. stitching leaf plates with bamboo nails and ii) technology supported system, doing value NWFPs with the help of EFTs e.g. stitching leaf plate with the help of sewing machine.

**Grading:** dividing all harvest (collected NWFPs) into various type considering the harvest color, weight, size, appearance, etc. This grading will help the harvester to seek enhanced price for different grades.

**Washing:** collected NWFPs can be washed with water or can wiped with cloth in case of NWFPs, such as, gums, up rooted herbs, bulbs etc., can benefit NWFPs harvester.

**Sizing:** Harvested medicinal herbs necessitate cutting herbs into different sizes of the harvested herb. This sizing value can be undertaken harvester that benefits them in sourcing better price and increased market.

**Aeration**: after harvesting NWFPs its life (longevity) period can be enhanced especially in case of Mahua (*Madhuca latifolia*) Kullu (*Sterculia urens*), Gooseberry/ Aonla (*Emblica officinalis)* this value addition enhances the [6] bargaining power of the harvester and enable him/her to earn more price, which eventually lead to increase income level and better quality of life to the forest dwellers who harvests NWFPs.

**Steaming**: NWFP like Gooseberry/Aonla **(***Emblica officinalis)* needs to be deseeded, to deseed the harvested Gooseberry fruits can be steamed, after steaming the fruits will become soft to deseed safely and pulp of Gooseberry can be dried in the sun light seeds can be traded separately. This will have dual benefit of increased price separate trade for pulp and seeds.

**Warehouse:** NWFPs are natural resources, [7] they will come in appropriate season, yet consumption of NWFPs will be done every day. NWFP like Mahua flowers will come in summer season for a couple of months, if the harvester sells it as soon as it is harvested, he or she gets below normal price as everybody may sell the harvested stocks which results increased supply that results in weak bargain power of seller. Alternately the harvest can be stored in warehouse for a couple of months or more which will enable the seller to get better and increased price.

**Breaking:** NWFPs like Mahua seeds, Sal seeds, and sal seeds, Achar (Buchanania lanzan) seeds are having upper hard husks that can be broken with sticks to get inner required grains that give the harvester a better price.

**Fastening**: *Bauhinia vahlii* (leaf/*eistar aaku*) are harvested [8]) from large barker which are used as material for making for meals plates, cups etc. which are bio-degradable and eco-friendly. The forest [8] dweller harvest these green leave and sell in loose without value addition. But these loose leaves drying for a couple of days three to four leaves can be fastened with the help of bamboo stick small nails or can be stitched with the help of sewing machine and further with the help of the compressor an edge can be made to make like dining steel plate which give five to six time more price than if sold in as raw leaves.

**Crushing**: NWFPs like soap nuts [9], Emblica officinalis, *Terminalia chebula*. and *Terminalia chebula* Retz are hard nuts. These nuts can be crushed with grinding machine or manual crushing implements that will give enhanced prices to the harvester, further the crushed powder can be packed and sold in the local market or distant market.

**Baking**: NWFPs like sal seeds have wings like parts, to make it tradable the wings like part is to be dissected from the seed this can be done by way of baking the seeds in the fire with the fuel wood, which can fetch better price to the forest dweller/harvester.

**Microfinance**: while conducting the research study survey it was learned that, forest dwelling communities sell their NWFPs as soon as they harvested for want of money at low price to fulfill daily needs. If these forest dwellers are provided [1–3] with access to small amount of money (microfinance) to obtain their daily needs, they

*Environmental Issues and Sustainable Development*

specific pre-decided targets.

**2. Mainstream microfinance institutions**

**3. The SHG-bank linkage phenomenon**

**3.2 Model-II: bank - facilitator agency - SHG - members**

**3.1 Model-I: bank – SHG - members**

lending to the group members.

the groups or their members. Study area selection:

with NWFPs abundantly.

**4. Methods of NWFPS value additions**

In India major sources of microfinance are (a) organized sector (banks, government agencies [4] etc.) and (b) un-organized sector (money lender, traders relatives, friends etc.) The former is regulated by government bodies like Reserve Bank of India (RBI), banking regulation act etc., and the later has no formal regulatory bodies. Microfinance falls under the primary sector and they are supposed to meet

In this SHGs are formed by group members themselves, after surviving for six months the SHG can link itself with a bank close to the group members and deposit their entire saved amount into the bank account. The bank sanctions credit/loan to the SHG four times to the groups saved and deposited amount e.g. the SHG saved INR 1000 and deposited into bank savings account, the bank sanctions an amount INR 4000 as credit, thus total amount INR 5000 is available to the SHG for onward

The second groups are formed by NGOs (in most of the cases) or by government agencies. The groups are nurtured and trained by these agencies. Government or other community-based organizations to take the lead in forming the SHGs, and then provide savings and credit facilities by the banks. Even after the linkage with banks, these facilitating agencies continue interacting with the groups. Most linkage experiences begin with this model with Non-Government Organizations (NGOs) playing a major role. This model has also been popular and more acceptable to banks, as some of the difficult functions of social dynamics are externalized.

**3.3 Model - III: bank – NGO - MFI (micro-finance institute) - SHG - members**

Due to various reasons, banks in some areas are not in a position to even finance SHGs promoted and nurtured by other agencies. In such cases, the NGOs promoted and nurtured the groups and also act as financial intermediaries. First, they promote the groups, nurture and train them and then approach banks for bulk loans for onlending to the SHGs. The banks lend to these intermediaries for onward financing to

**Rationale of selecting,** Atmakuru (Atmakur) /Kurnool, Pembi (Nirmal) /Adilabad, Polavaram (Eluru) /West Godavari in Andra Pradesh these forest divisions are bestowed

When the researcher undertook research study survey in the select geographical area, the investigator observed and noted the below outlined NWFPs value addition systems. These value addition systems can be categorized into two [5] different value additions system: i) Manual system, adding value to NWFPs conventionally

**22**

can store and add value to the harvested NWFPs that will give them more price and arrests distress sale of NWFP.

## **5. Microfinance practices and NWFPS value additions**

This part of the paper outlines microfinance requirements, sources and prevailing other microfinance practices and also FLCs livelihood sources and their augmentation.

As exhibited in **Table 1** Mean household size in the selected forest range places is 4.4 (three to six members) which is in sync with emerging nucleus family system and it is partly to secure Government welfare scheme benefits including ration card, MGNREGA work card etc. To secure survival and daily needs of forest dwellers, they do various income generating activities such as NWFP harvest and trade, artisan labour, public project wages, and sundry other items As exhibited **Table 1**, the forest dwellers are taking up, non-destructive eco-friendly based techniques that facilitate NWFPs value additions, enhanced earnings and better quality of life. In the long run all these contributes for reducing poverty amongst forest dwellers and decreased environmental degradation and increased green forest cover.

From above **Table 2** this can be inferred that mean amount of money needed for forest dwellers in all places of the study for procuring food for all times a day meals and for other daily needs, shopping goods is INR 37533. Out of this INR 13665 is provided by agriculture and allied sources, next INR 8677 is materializing from trading of NWFPs. The remaining amount has been sourced from other activities as shown in the **Table 2**.

**Microfinance activities profile of researched places:** the researcher has made an attempt to profile microfinance activities that were prevalent in the research study places.

**Table 3** exhibits access of microfinance to forest dwellers, it could be observed that Atmakur range, SHG is having access to 51% of microfinance requirements, next comes indigenous banker who extends financial assistance up to 25%,, remaining is purveyed other sources as shown in the **Table 3**. Similarly other ranges accessibility to various microfinance requirements are shown in the above **Table 3**.

As shown in the **Table 4**, it is observed that the primarily forest dwellers require for family members healthcare that has share of 26%, next is for food that has share of 21.8%, and remaining is for other activities as shown in the **Table 4**.

The investigator had group meetings with the forest dwellers and collected the views that revealed that the forest dwellers are yet to aware fully the benefits of NWFPs value addition, emerging innovative and eco-friendly technologies. Hence,

*Sources: Estimated based on field survey 2014.*

*\* Threshold financial sources need to facilitate subsistence and other survival for forest dwellers in terms of money and money equivalents.*

**25**

*Microfinance Practices and NWFPs Value Additions for Sustainable Environment…*

**Income from agricultural sources (including subsistence)**

**Income from MGNREGA**

7154 19.6 13797 37.8 7811 21.4 7738 21.2 36500

7801 19.7 13587 35.2 6832 17.7 10380 27.4 38600

7800 20.8 13612 36.3 8175 21.8 7913 21.1 37500

**Polavaram (Eluru) / West Godavari**

**Score\* % of**

**score**

**INR % INR % INR % INR %**

Mean 7585 20.0 13665 36.4 7606 20.3 8677 23.6 37533

**Pembi (Nirmal) / Adilabad**

**Score\* % of**

Moneylender 17 25.0 21 30.9 16 23.9 54 27.8

SHG 35 51.0 27 42.6 29 43.3 91 46.9

Total 68 100 68 100 67 100 194 100

**score**

06 9.0 08 10.3 07 10.4 12 6.2

10 15.0 12 16.2 15 22.4 37 19.1

**Agriculture labour and other source** **Total INR**

**Total**

**Score\* %**

the concerned Government and NGOs should be initiate necessary interventions to create awareness and facilitate NWFPs value additions and also provide market

*Source: field survey 2013–2014. Score\*- Individual responses for a particular source for meeting microfinance*

**Figure 1** an integrated network that is envisaged and as shown in the **Figure 1**, all stakeholders should collaborate, cooperate and coordinate to achieve the integrated objective. Providing livelihoods to forest dwellers is a comprehensive issue and strong integration and involvement of all systems (lateral integration, forward/ market linkages) and stakeholders including forest dwellers Public Policy makers, Government, NGOs/Civil societies. Enhancing livelihoods and ensuring welfare to the poor forest dwellers is a Global concern in general and India in particular. This is a challenge and to be addressed together, fastening all stakeholders' involvement in the evolution and execution of the envisaged policy. As shown in **Figure 1**, integrated linkages to all these entities must be promoted as strategic measure to secure

linkages to the value added NWFPs.

*Forest dweller access to microfinance in the researched places.*

*requirement including multi responses.*

*DOI: http://dx.doi.org/10.5772/intechopen.95419*

**Income from NWFP**

**Name of the range and (division) / District**

Atmakuru (Atmakur) / Kurnool

Pembi (Nirmal) / Adilabad

Polavaram (Eluru) West Godavari

**Table 2.**

*Source: field survey 2014.*

**Name of the range**

**Source of Micro Credit**

Banks/ Government

**Table 3.**

Relatives and friends/others

*Different sources of survival to the forest dwellers.*

**Atmakuru (Atmakur) / Kurnool**

**Score\* % of**

**score**

#### **Table 1.**

*Amount of money required for survival of the forest dwellers.*

*Microfinance Practices and NWFPs Value Additions for Sustainable Environment… DOI: http://dx.doi.org/10.5772/intechopen.95419*

#### **Table 2.**

*Environmental Issues and Sustainable Development*

arrests distress sale of NWFP.

and increased green forest cover.

*Sources: Estimated based on field survey 2014.*

*Amount of money required for survival of the forest dwellers.*

shown in the **Table 2**.

study places.

can store and add value to the harvested NWFPs that will give them more price and

This part of the paper outlines microfinance requirements, sources and prevailing other microfinance practices and also FLCs livelihood sources and their augmentation. As exhibited in **Table 1** Mean household size in the selected forest range places is 4.4 (three to six members) which is in sync with emerging nucleus family system and it is partly to secure Government welfare scheme benefits including ration card, MGNREGA work card etc. To secure survival and daily needs of forest dwellers, they do various income generating activities such as NWFP harvest and trade, artisan labour, public project wages, and sundry other items As exhibited **Table 1**, the forest dwellers are taking up, non-destructive eco-friendly based techniques that facilitate NWFPs value additions, enhanced earnings and better quality of life. In the long run all these contributes for reducing poverty amongst forest dwellers and decreased environmental degradation

From above **Table 2** this can be inferred that mean amount of money needed for forest dwellers in all places of the study for procuring food for all times a day meals and for other daily needs, shopping goods is INR 37533. Out of this INR 13665 is provided by agriculture and allied sources, next INR 8677 is materializing from trading of NWFPs. The remaining amount has been sourced from other activities as

**Microfinance activities profile of researched places:** the researcher has made an attempt to profile microfinance activities that were prevalent in the research

**Table 3** exhibits access of microfinance to forest dwellers, it could be observed that Atmakur range, SHG is having access to 51% of microfinance requirements, next comes indigenous banker who extends financial assistance up to 25%,, remaining is purveyed other sources as shown in the **Table 3**. Similarly other ranges accessibility

As shown in the **Table 4**, it is observed that the primarily forest dwellers require for family members healthcare that has share of 26%, next is for food that has share

The investigator had group meetings with the forest dwellers and collected the views that revealed that the forest dwellers are yet to aware fully the benefits of NWFPs value addition, emerging innovative and eco-friendly technologies. Hence,

Atmakuru (Atmakur) / Kurnool 36500 4.33 Pembi (Nirmal) / Adilabad 38600 4.54 Polavaram (Eluru) / West Godavari 37500 4.25 Mean 37533 4.37

*Threshold financial sources need to facilitate subsistence and other survival for forest dwellers in terms of money and*

**required for household survival \***

**Household size (No. of persons)**

to various microfinance requirements are shown in the above **Table 3**.

of 21.8%, and remaining is for other activities as shown in the **Table 4**.

**Forest range & (Division) / District Amount of financial resources**

**5. Microfinance practices and NWFPS value additions**

**24**

*\**

**Table 1.**

*money equivalents.*

*Different sources of survival to the forest dwellers.*

*Source: field survey 2013–2014. Score\*- Individual responses for a particular source for meeting microfinance requirement including multi responses.*

#### **Table 3.**

*Forest dweller access to microfinance in the researched places.*

the concerned Government and NGOs should be initiate necessary interventions to create awareness and facilitate NWFPs value additions and also provide market linkages to the value added NWFPs.

**Figure 1** an integrated network that is envisaged and as shown in the **Figure 1**, all stakeholders should collaborate, cooperate and coordinate to achieve the integrated objective. Providing livelihoods to forest dwellers is a comprehensive issue and strong integration and involvement of all systems (lateral integration, forward/ market linkages) and stakeholders including forest dwellers Public Policy makers, Government, NGOs/Civil societies. Enhancing livelihoods and ensuring welfare to the poor forest dwellers is a Global concern in general and India in particular. This is a challenge and to be addressed together, fastening all stakeholders' involvement in the evolution and execution of the envisaged policy. As shown in **Figure 1**, integrated linkages to all these entities must be promoted as strategic measure to secure

#### **Table 4.**

*Forest dwellers microfinance required for various activities.*

#### **Figure 1.**

*Networking of NWFP processing, microfinance, EFT, logistics and infrastructure [10].*

the intended goal of providing subsistence requirements. Eco-friendly NWFPs value additions [11] necessitates eco-friendly technologies which will rendered numerous benefits including reducing environmental degradation, deforestation yet, enhanced income to the forest dwellers. Technological and Scientific research institutions may shoulder the responsibility for promoting conventional [12] NWFPs value addition techniques.

#### **6. Conclusions and suggestions**

Average amount of money required for FLCs in the study area for procuring food items to 3 square meals a day and for other daily needs, cloths etc., is INR 37533. Out of this INR 13665 is provided by agriculture and allied activities, next

**27**

**Author details**

Rajahmundry, Andhra Pradesh, India

provided the original work is properly cited.

\*Address all correspondence to<EMAIL_ADDRESS>
forest dwellers to market their value added NWFPs.

Teki Surayya

*Microfinance Practices and NWFPs Value Additions for Sustainable Environment…*

INR 8677 is materializing from trading of NWFPs. The quantum of money that can be earned by way of trading NWFPs may be enhanced through appropriate value additions with the help of eco-friendly technologies, which will have multiple benefits including enhanced self-employment, raised income yet reducing environmental degradation and increased forest cover, better flora and fauna health.

It was observed about 47% of microfinance assistance is provided by Self-Help Groups, yet indigenous banker is providing about 28% of total requirements of the forest dwellers. It is deduced that self-help groups will act as purveyors of microfi-

It is observed that the primarily forest dwellers require for family members healthcare that has share of 26%, next is for food that has share of about 22%. Group meetings with the forest dwellers revealed that the forest dwellers are yet to aware fully the benefits of NWFPs value addition, emerging innovative and eco-friendly technologies. For example if AONLA **(***Emblica officinalis)* sold in raw form as tender fruit they may get say INR 50 Kilogram (Kg.) if they make value addition in form boling the AONLA fruits remove the seed and dry the pulp in the sunlight now the price of the dried AONLA pulp can be sold @ INR 200 after making provision for process loss and overhead. Hence, the concerned Government and NGOs should - initiate necessary interventions to create awareness and facilitate NWFPs value additions and

Dedicated linkages tagging all concern parties to be evolved to facilitate increased income level of forest dwellers. These integrated linkages with all concern entities must be promoted as strategic measure to secure the intended goal of providing subsistence requirements. Eco-friendly NWFPs value additions necessitates eco-friendly technologies which will rendered numerous benefits including reducing environmental degradation, deforestation yet, enhanced income to the forest dwellers. Technological and Scientific research institutions may shoulder the responsibility for promoting conventional NWFPs value addition techniques.

Effective development plans to facilitate increased earnings and better quality life to the forest dwellers must incorporate measures for better threshold logistics which can link forest dwellers value added NWFPs reach the distant market to get remunerative earnings. Yet there should provision for microfinance that encourages the forest dwellers to become micro-entrepreneurs. Involvement of voluntary organization to support NWFPs value addition, imparting training, and helping

Department of Commerce and Management Studies, Adikavi Nannaya University,

© 2021 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,

*DOI: http://dx.doi.org/10.5772/intechopen.95419*

nance requirements of the forest dwellers.

also provide market linkages to the value added NWFPs.

#### *Microfinance Practices and NWFPs Value Additions for Sustainable Environment… DOI: http://dx.doi.org/10.5772/intechopen.95419*

INR 8677 is materializing from trading of NWFPs. The quantum of money that can be earned by way of trading NWFPs may be enhanced through appropriate value additions with the help of eco-friendly technologies, which will have multiple benefits including enhanced self-employment, raised income yet reducing environmental degradation and increased forest cover, better flora and fauna health.

It was observed about 47% of microfinance assistance is provided by Self-Help Groups, yet indigenous banker is providing about 28% of total requirements of the forest dwellers. It is deduced that self-help groups will act as purveyors of microfinance requirements of the forest dwellers.

It is observed that the primarily forest dwellers require for family members healthcare that has share of 26%, next is for food that has share of about 22%. Group meetings with the forest dwellers revealed that the forest dwellers are yet to aware fully the benefits of NWFPs value addition, emerging innovative and eco-friendly technologies. For example if AONLA **(***Emblica officinalis)* sold in raw form as tender fruit they may get say INR 50 Kilogram (Kg.) if they make value addition in form boling the AONLA fruits remove the seed and dry the pulp in the sunlight now the price of the dried AONLA pulp can be sold @ INR 200 after making provision for process loss and overhead. Hence, the concerned Government and NGOs should - initiate necessary interventions to create awareness and facilitate NWFPs value additions and also provide market linkages to the value added NWFPs.

Dedicated linkages tagging all concern parties to be evolved to facilitate increased income level of forest dwellers. These integrated linkages with all concern entities must be promoted as strategic measure to secure the intended goal of providing subsistence requirements. Eco-friendly NWFPs value additions necessitates eco-friendly technologies which will rendered numerous benefits including reducing environmental degradation, deforestation yet, enhanced income to the forest dwellers. Technological and Scientific research institutions may shoulder the responsibility for promoting conventional NWFPs value addition techniques.

Effective development plans to facilitate increased earnings and better quality life to the forest dwellers must incorporate measures for better threshold logistics which can link forest dwellers value added NWFPs reach the distant market to get remunerative earnings. Yet there should provision for microfinance that encourages the forest dwellers to become micro-entrepreneurs. Involvement of voluntary organization to support NWFPs value addition, imparting training, and helping forest dwellers to market their value added NWFPs.


1.Letter of Intent

This is a letter prepared by the successor to formally expresses their interest in making an offer for the business. It often requires specific information, including how the transition will be done to fit the structure of the business. This letter of intent becomes particularly important if the next generation owner intends to purchase the business from an exiting business owner. This is to allow for fair negotiation and can ensure there is a focus on the expectations of the business owner to reach an agreement.

2.Purchase and Sale Agreement

This document is also referred to as the Definitive Purchase Agreement. It includes the final agreement between the parties and acts as a legally binding document for the ownership exchange. Within it, the shares and how they will be divided is outlined. Also, there will be details on how stocks and assets are to be purchased. This agreement should be drafted by an attorney who is well-versed in all the requirements and payments necessary. Furthermore, the attorney can support the exit strategy advisory team with their expertise. With the Definitive purchase agreement, the tax implications for each transaction are captured.

#### 3.Earn-Out Agreement

One aspect of an exit strategy is offering the successor a guarantee that the business will continue to grow and thrive even after the business owner has made their exit. For most business owners, getting a one-time cash payment to close the deal is the best strategy. This may not be ideal for the buyer. With the earn-out agreement, the buyer offers to make payments to the exiting owner after the exit for some time. This is highly risky for the business owner, as once they exit the business, they have little control over the operations and real success of the entity. If this agreement is used, it needs to have precise and careful wording that offers the exiting business owner some protection.

4.Non-Compete Agreement

When a business owner chooses an exit strategy, there is one highly valuable asset that they take away with them. That is their expertise and knowledge on how to run the business. This can be of concern to the business successor who will want to take all the necessary steps to protect their new investment in the business. This is where the non-compete agreement is essential. This is a formal agreement that outlines that the exiting business owner will not create a competing business or be employed within the same industry in a competing organization for some time. Typically, the non-compete agreement will cover three years.

To ensure that the full legal process is followed, some documents need to be updated continuously for ease of transition. These include all intellectual property licenses, patents, trademarks, and copyrights. The same applies to any software that may hold sensitive or confidential information. These types of documents have an impact on royalties and the way they are collected.

Also, contracts with vendors and clients need filing and updating as they tie into the value of the business. They also provide information on the length of time these stakeholder relationships are valid.


**1. Introduction**

Housing is a basic need of human beings and a significant part of the infrastructural requirements of any society. The housing sector constitutes about 38% of the construction industry globally [1]. Over the years, concerns about housing have been directed at availability, adequacy, affordability, and sustainability. Housing availability is a major challenge as housing deficit has been ascribed to some major global challenges, especially population growth and urbanization [1, 2]. Already, more than 50% of the world's population currently lives in urban areas with a future projection of approximately 70% by the year 2050 [3]. This growing population will require functional facilities to sustain livelihood of which housing is one of the most prominent.

Responding to the housing deficit effectively will result in high resource extraction and utilization, which are often associated with negative environmental impacts. Hence, mitigating the impact of housing delivery is important in the efforts to provide adequate housing. Hence, emphasis is shifting toward sustainable options in housing delivery. In this respect, life cycle assessment (LCA) has become a widely accepted methodology for estimating the environmental impact of housing provision toward ensuring sustainability [4]. However, the LCA approach has some limitations, especially with respect to its close affinity with the linear materials and energy flow model as against the circular economy model, which has become a preferred option.

In order to promote sustainability through efficient resource utilization, the circular economy (CE) approach has gained ascendancy. CE refers to an economic growth model that prevents environmental degradation by promoting resource efficiency through waste minimization and adoption of regenerative and restorative practices as against end-of-life approach [5]. The concept is, therefore, closely linked to the sustainable development goals SDGs through Target 12.5, which seeks to substantially reduce waste generation through prevention, reduction, recycling, and reuse (3Rs). The circular economy approach when extended to the housing sector seeks to improve sustainability of housing through the use of circular materials, adoption of circular design strategies, reduction of waste in the housing delivery value chain, and adoption of regenerative strategies in housing design and delivery using innovative processes [2].

In the building and construction industry, the design stage has been recognized as the most efficient and effective stage for adopting sustainable practices in which CE strategies can be explored [6, 7]. According to Fatourou-Sipsi and Symeonidou [8], sustainable building design has become necessary with the enormous environmental impact of the building construction and demolition. It has been estimated that CE will result in 4% of economic growth by 2030 in the EU countries [9]. Hence, the EU through the European Green Deal is active in pushing for a more sustainable Europe [10, 11]. However, developing economies in Sub-Saharan Africa, especially Nigeria, are still grappling with the uptake of sustainable buildings. It is, therefore, necessary to fasttrack the uptake, especially in the housing sector through the route of CE adoption.

In Nigeria, housing deficit has been estimated to be up to 20 million [12]. In addition, awareness of circular economy is growing in Nigeria [13]. However, solid waste management practices appear to dominate discourse on circular economy in the Nigerian context [14–16]. Meanwhile, the construction industry is growing with technology adoption remaining rather rudimentary in the housing sector. The construction waste implications associated with low technology adoption in the housing construction sector can be very profound. This presents an opportunity to evaluate the prospects of circular design strategies in the Nigerian housing sector. Hence, relevant literature were deployed to underscore circular strategies applied to the design of housing. Built examples of public housing in Lagos, Nigeria were also evaluated to determine the extent of alignment with circular design and construction principles. Given the push towards sustainable buildings in Nigeria and the gradual ascendance of life cycle assessment studies in the Nigerian built environment, the current paper also makes good effort to align circular design strategies with the LCA framework.


*Article* **Uncertain Analysis of Fuzzy Evaluation Model for Water Resources Carrying Capacity: A Case Study in Zanhuang County, North China Plain**

**Yinxin Ge 1, Jin Wu 1,\*, Dasheng Zhang 2, Ruitao Jia 1 and Haotian Yang 1**

**Abstract:** The scientific and accurate evaluation of water resources carrying capacity has good social, environmental and resource benefits. Reasonable selection of evaluation parameters is the key step to realize efficient and sustainable development of water resources. Taking Zanhuang County in the North China Plain as the research area, this study selected fuzzy comprehensive evaluation models with different weights in the established evaluation index framework to explore the sources of uncertainty affecting the evaluation results of water resources carrying capacity. By using the sensitivity analysis method of index weight, the index with the biggest influence factor on the evaluation result is selected to reduce the uncertainty problems such as index redundancy and small correlation degree. The results show that the correlation and reliable of comprehensive evaluation value obtained by different weight methods is different. The evaluation result obtained by using the analytic hierarchy process is more relevant than the entropy weight method, and it is more consistent with the actual load-bearing situation. The study of sensitivity index shows that water area index is the biggest factor affecting the change of evaluation results, and water resources subsystem and socio-economic subsystem play a dominant role in the whole evaluation framework. The results show that strengthening the data quality control of index assignment and weight method is helpful to reduce the error of water resources carrying capacity evaluation. It can also provide scientific basis for the improvement of fuzzy evaluation model.

**Keywords:** water resources carrying capacity; uncertainty analysis; fuzzy comprehensive evaluation model; weight sensitivity analysis

#### **1. Introduction**

Water resources are irreplaceable natural resources that not only restrict the sustainable development of society but also play a vital role in social development [1,2]. At present, studying the carrying capacity of water resources is a prerequisite for determining the important development relations between water resources and population, ecology and social economy in the region [3]. It is the necessity to manage the sustainable use of water resources and other related water issues [4]. Water resources and other related water issues must be managed sustainably [5]. Of great significance for promoting the development of the Chinese economy and improving the quality of life is how to effectively realize the balance and sustainable development of water resources, the water environment and the economy [6].

In recent years, the water resources carrying capacity has been discussed more than sustainable development, where the former generally refers to the development and utilization degree of natural water resources [7]. Some studies [8–10] have concluded that they often express similar meanings as indicators such as the sustainable utilization of

**Citation:** Ge, Y.; Wu, J.; Zhang, D.; Jia, R.; Yang, H. Uncertain Analysis of Fuzzy Evaluation Model for Water Resources Carrying Capacity: A Case Study in Zanhuang County, North China Plain. *Water* **2021**, *13*, 2804. https://doi.org/10.3390/w13202804

Academic Editor: Carmen Teodosiu

Received: 31 August 2021 Accepted: 7 October 2021 Published: 9 October 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/).

water volume, ecological limit of water environment, limit of water resources and shortage degree [11]. Chinese research on the water resources carrying capacity was first proposed by the Xinjiang Water Resources Soft Science Research Group [12] and constituted a breakthrough in the field of water resources. In the larger theoretical context of sustainable development and water management, the most representative definition is to coordinate the reasonable scale of ecological health and sustainable development resources under certain social conditions of economic, environmental and technological development [13]. Water resource carrying capacity is defined as "the size of population and economy scale that a region's water resources can carry, which had necessary requirements for ecological environmental protection and had certain technical level and social and economic development level in a certain historical stage". Since the water resources carrying capacity involves water resources system, ecological environment system and social economic system under different regional and natural conditions, the interaction among multiple systems will further amplify the complexity and uncertainty [14]. Therefore, strengthening the study of uncertainty of water resources carrying capacity is conducive to improving the reliability of evaluation results. Among the comprehensive dynamic evaluation models, the fuzzy comprehensive evaluation model [15] is widely used. In addition, fuzzy comprehensive evaluation manages fuzzy evaluation variables through accurate mathematical methods, which can provide a more scientific and practical quantitative evaluation of hidden and fuzzy concepts. At the same time, the model can be used to verify whether the evaluation index weight and other related uncertainty issues have a great impact on the evaluation results [16]. Therefore, the fuzzy evaluation model is selected as an example to study the uncertainty of the evaluation results of the water resources carrying capacity [17,18]. From the perspective of weight data and indicator assignment, the uncertainty of water resources carrying capacity is seldom considered in the application of the fuzzy evaluation model, which makes the results of water resources carrying capacity limited in practical applications [11,15,19]. Therefore, the uncertainty study of water resources carrying capacity model will improve the accuracy of evaluation. At the same time, the research on the uncertainty of water resources carrying capacity also provides a direction for the improvement of the model [20–22].

Based on the consideration of these uncertain factors, this paper studies the fuzzy comprehensive evaluation model by comparing the weight method determined by the analytic hierarchy process and the entropy weight method [23,24] under certain technical outline standards. Correlation analysis was used to solve the uncertainty among weights, the indexes with high sensitivity coefficient and great influence on evaluation results were screened out by calculating the influence of indexes through sensitivity analysis [25]. This study provides reliable scientific basis for reducing the uncertainty of the results of the fuzzy evaluation model and improving the efficiency of water resources utilization [26,27]. Taking Zanhuang County in the North China Plain as an example, the evaluation of water resources carrying capacity is carried out with certain characteristic parameters [28,29], which can provide reference for water resources managers in the North China Plain.

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

#### *2.1. Study Area*

The study area (37◦26 to 37◦46 N, 114◦20 to 114◦31 E) is located in Shijiazhuang city in southwestern Hebei Province (Figure 1b). The district's east–west length is 44.8 km, and its north–south width is 37 km, resulting in a total area of 1210 km2 (Figure 1c). It borders the surrounding counties of Shijiazhuang City and Xingtai City inside, and Shanxi Province outside. The county is located in a warm, semi-humid monsoon continental climate. The temperature difference between seasons is large, with an annual average temperature of 13.6 °C. The average annual precipitation and evaporation are 508.9 mm and 1885 mm, respectively, and precipitation mainly occurs from July to September. Regarding its topography, the region is located at the eastern foot of the Tai-hang Mountains. The landform features of the region are mainly composed of mountains and hills. On the

whole, the mountain trend is higher in the west and lower in the east. The abundant basin-scale crossing of water resources from the Ziya River System and the artificial canal South-to-North Water Diversion Project in the study area can meet 68% of the county's annual water consumption. The county has 11 towns under its jurisdiction.

**Figure 1.** Maps showing (**a**) the location of Hebei in China; (**b**) the location and elevation of study area in Hebei; (**c**) the administrative boundaries in the study area combined with its land use.

#### *2.2. Methods*

2.2.1. Fuzzy Comprehensive Evaluation Model

As water resources carrying capacity evaluation index standards and evaluation system boundaries are usually uncertain and fuzzy, fuzzy comprehensive evaluation models can improve the objectivity and accuracy of evaluation results and more comprehensively reflect the situation of regional water resources more comprehensively [30]. This paper adopts this model and its basic principle is as follows: to establish evaluation index set U = (u1, u2,...,um) and the comment set V = (v1, v2,...,vn), the results of fuzzy comprehensive evaluation are as follows:

$$\mathbf{C} = (\mathbf{c}\_1, \mathbf{c}\_2, \dots, \mathbf{c}\_m) = \mathbf{W} \cdot \mathbf{R} \tag{1}$$

where W is a fuzzy subset on U, W = (w1, w2,...,wn), 0 ≤ wi ≤ 1 (∑n i=1 wi = 1); wi is the membership degree of U to W (the weight value of this indicator), which represents the extent to which a single element ui plays a role in the evaluation factor; "·" is a fuzzy operator which ordinary matrix algorithm is adopted; C is a fuzzy subset of V, C = (c1, c2,...,cm), 0 ≤ cj ≤ 1 (∑m j=1 cj = 1); cj is the membership degree of V to C, which represents the result of comprehensive evaluation. The membership (evaluation) matrix is as follows:

$$\mathbf{R} = \begin{bmatrix} \mathbf{r}\_{11} & \cdots & \mathbf{r}\_{1n} \\ \dots & \ddots & \dots \\ \mathbf{r}\_{m1} & \cdots & \mathbf{r}\_{mn} \end{bmatrix} \tag{2}$$

In the formula, rij is the membership degree of evaluation ui to vj, and Ri = (ri1, ri2,...,rim) is the result of single factor for evaluation of ui.

The actual value of the evaluation index ui is compared with the classification interval, the membership degree of the corresponding level vj, which is named the value of rij, can be calculated. In order to eliminate the level skip phenomenon in which the value of the evaluation grade changes in a small range at the end of the section, the membership function can be smoothly transitioned between each level, and the fuzzy processing is performed. When calculating the membership degree matrix R, r (t) i (t = 1, 2, 3, 4, 5,), which means the membership of the t-th level, ri is the actual value of the index, and x (t) max and x (t) min refer to the upper limit and lower limit of the t-th evaluation level, respectively. The algorithm of the membership matrix R is not elaborated in detail [31].

After obtaining fuzzy comprehensive evaluation matrix C of each town, each grade of the evaluation index reflects different situations of water resources carrying capacity [32]. A value between 0 and 1 is assigned to each grade for quantification, and the larger the value is, the stronger the water resources carrying capacity is. Generally speaking, the evaluation indexes were divided into five levels, and the comment set V = (v1, v2,...,v5). The v1 level indicates that the carrying capacity of water resources is in a best state, and the coordinated development of water resources with economy, society and ecology is in a state of sustainable utilization. The v2 level indicates that the carrying capacity of water resources is in a good state, and the water resource is sufficient to support the local economic and social development level. The v3 level indicates that the carrying capacity of water resources is in the general state and there is no obvious regional water shortage problem. The v4 level indicates that the carrying capacity of water resources is in a poor state, but it can basically meet the water demand of various industries. The v5 level indicates that the carrying capacity of water resources is in a very poor state and the contradiction of water resources is prominent. Take α1 = 0.1, α2 = 0.3, α3 = 0.5, α4 = 0.7 and α5 = 0.9 for levels v1, v2, v3, v4 and v5, respectively. The scoring value of each grade and the final comprehensive evaluation value of water resources carrying capacity are calculated according to the formula below.

$$\theta = \frac{\sum\_{\mathbf{t}=1}^{5} \mathbf{b}\_{\mathbf{t}}^{\mathbf{k}} \alpha\_{\mathbf{t}}}{\sum\_{\mathbf{t}=1}^{5} \mathbf{b}\_{\mathbf{t}}^{\mathbf{k}}} \tag{3}$$

where θ is the comprehensive evaluation value of water resources carrying capacity based on the comprehensive evaluation result matrix C; bk t is the value of the membership degree of each evaluation index; k is the coefficient set when the dominant role needs to be highlighted, usually k = 1.

#### 2.2.2. Index Weight Calculation Methods

The weight calculation methods can be divided into subjective methods and objective methods [33,34], including the binomial coefficient method and the analytic hierarchy process. The subjective method research is relatively mature, with strong subjective arbitrariness, and more dependence on the thinking of the decision analyst. However, the principal component analysis, entropy and other objective methods use decision matrices, which have a strong mathematical theoretical basis to determine weights based on relationships between the original data. Since many factors are involved in the water resources carrying capacity, and different factors have different effects on it, the actual situation of the study area should be considered when assigning weights [35]. First, the relationship between the indicators was clarified, and the corresponding index system was established. The index system was divided into three levels: target level, criterion level and index level [36]. In this paper, the analytic hierarchy process and the entropy weight method were used to discuss and study this respectively, and an appropriate weight method was found.

Analytic Hierarchy Process

The analytic hierarchy process (AHP) is a systematic method of making decisions by means of qualitative indicators and fuzzy quantification [30]. According to the nature of the problem and the overall goal to be achieved, it deconstructs the problem into different constituent factors. The AHP combines the factors at different levels according to their interrelationship and the affiliation relationship, forming a multilevel analysis structure model. Thus, ultimately, the problem is attributed to the determination of the importance of the lowest level (plans, measures, etc. for decision making) relative to the highest level (the overall goal) or the arrangement of the relative order of superiority and inferiority. The main steps of the analytic hierarchy process are as follows:

#### Entropy Weight Method

The entropy weight method is used to determine the weight of each evaluation index. Generally, when the information entropy of an index is smaller, the information provided and the index weight is greater, and vice versa [37]. The main calculation steps are as follows:

The original evaluation index matrix B was obtained according to the membership:

$$\mathbf{B} = \begin{bmatrix} \mathbf{b}\_{11} & \cdots & \mathbf{b}\_{1n} \\ \dots & \ddots & \dots \\ \mathbf{b}\_{m1} & \cdots & \mathbf{b}\_{mn} \end{bmatrix} \tag{4}$$

where bij is the original value of the i-th index in the j-th year. The normalized matrix A is obtained by eliminating the dimensional effect. The positive and negative indicators are treated as follows:

Positive indicators:

$$\mathbf{a}\_{\mathbf{i}\rangle} = \frac{\mathbf{b}\_{\mathbf{i}\rangle} - \min\left(\mathbf{b}\_{\mathbf{i}\bar{\mathbf{j}}}\right)}{\max\left(\mathbf{b}\_{\bar{\mathbf{i}}\bar{\mathbf{j}}}\right) - \min\left(\mathbf{b}\_{\bar{\mathbf{i}}\bar{\mathbf{j}}}\right)}\tag{5}$$

Negative indicators:

$$\mathbf{a}\_{\mathrm{i}\mathbf{j}} = \frac{\max\left(\mathbf{b}\_{\mathrm{i}\mathbf{j}}\right) - \mathbf{b}\_{\mathrm{i}\mathbf{j}}}{\max\left(\mathbf{b}\_{\mathrm{i}\mathbf{j}}\right) - \min\left(\mathbf{b}\_{\mathrm{i}\mathbf{j}}\right)}\tag{6}$$

Normalization matrix:

$$\mathbf{A} = \begin{bmatrix} \mathbf{a}\_{11} & \cdots & \mathbf{a}\_{1n} \\ \dots & \ddots & \dots \\ \mathbf{a}\_{m1} & \cdots & \mathbf{a}\_{mn} \end{bmatrix} \tag{7}$$

Calculation of objective weight through the entropy weight method:

$$\mathbf{w}\_{\mathbf{i}} = \frac{1 - \mathbf{e}\_{\mathbf{i}}}{\mathbf{m} - \sum\_{i=1}^{m} \mathbf{e}\_{\mathbf{i}}} \tag{8}$$

Information entropy:

$$\mathbf{e}\_{\mathbf{i}} = -\frac{1}{\ln \mathbf{n}} \sum\_{\mathbf{j}=1}^{n} \mathbf{p}\_{\mathbf{i}\mathbf{j}} \ln \mathbf{p}\_{\mathbf{i}\mathbf{j}\prime} \mathbf{p}\_{\mathbf{i}\mathbf{j}} = \frac{\mathbf{a}\_{\mathbf{i}\mathbf{j}}}{\sum\_{i=1}^{n} \mathbf{a}\_{\mathbf{i}\mathbf{j}}} \tag{9}$$

#### 2.2.3. Calculation Method of Weight Sensitivity

In the evaluation of water resources carrying capacity, the weight of each index in the evaluation index system can be obtained with the help of fuzzy comprehensive evaluation model, but it cannot judge which index has a high impact on the evaluation. Sensitivity analysis can explain the influence of which index weight by changing the value of relevant variables. It is an essential basic step in the process of multi-criteria decision making, because it is directly related to the accuracy and reliability of decision-making results [38].

This paper adopted the single-factor division method [39] to test the sensitivity of the index weight, which can be shown by removing a certain variable weight. The weights of the other variables were equally distributed to remove the variable weight value and to maintain the total weight value and the value of 1. The changing situation reflects the trend and regularity of the influence of single-factor weight changes on the water resources carrying capacity and then removes the weights of other indicators individually, calculates their respective sensitivities and evaluates the impact of the uncertainty of the weight of each indicator on the research results variation. If removing this index weight does not have a great impact on the score result, then the comprehensive evaluation of the water resources carrying capacity is insensitive to this index weight, and vice versa. The calculation of this method is shown in Formulas (10) and (11).

$$\text{RMSE} = \sqrt{\frac{\sum\_{i=1}^{n} \left(\frac{\chi - \chi\_i}{\mathbf{Y}}\right)^2}{\mathbf{n}}} \tag{10}$$

$$\text{TF}^{\cdot} = \sum\_{i=1}^{k} \text{F}\_{\text{RMSEC}} \tag{11}$$

where RMSEC is the rate of change of root mean square error (the sensitivity index); n is the number of index weight variables; Y is the comprehensive evaluation value in the original fuzzy comprehensive evaluation results; Yi is the comprehensive evaluation value after changing the weight index variable; TF is the total sensitivity; K is the number of comprehensive evaluation results; FRMSEC is the change rate of the root mean square error of the comprehensive evaluation results, that is, the sensitivity of each weight variable in each comprehensive evaluation after changing.

Firstly, the evaluation of water resources carrying capacity is calculated under the basic framework of the fuzzy comprehensive evaluation model, and the framework of the evaluation system of water resources carrying capacity is established. Then, according to the original data, it is processed and indexed according to the grading standards. Secondly, the reliability analysis of the comprehensive evaluation value obtained by different weights was compared by using correlation analysis method. The error contrast of mathematical objectivity was analyzed under a certain research report standard. The evaluation index value of water resources carrying capacity under the selected weight results was calculated. Thirdly, the sensitivity analysis method of single variable removal is used to calculate the sensitivity index of these evaluation values to screen out the index that has the greatest influence on the evaluation results. For this research, the uncertainty methods provide ideas for the systematic model study of water resource carrying capacity evaluation, Besides this, it also provides direction for the improvement of the model.

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

#### *3.1. Construction of the Evaluation Index System and Classification Standard*

The selection of indicators is directly related to the accuracy and authenticity of the evaluation results of water resources carrying capacity, so the selection of evaluation indicators should follow the principles of science, integrity, hierarchy, dynamic and operability [40,41]. To accurately reflect the status of the water resources carrying capacity in this region, indices were selected from two aspects. On the one hand, when selecting indicators, we mainly considered our available data (The Shijiazhuang Water Resources Bulletin, Statistical Yearbook of Zanhuang) [42,43] and referred to indicators in other literature [39–41,44]; on the other hand, according to the actual situation and characteristics of water resources in Hebei Province, combined with experts' opinions, the indexes of the

study area were selected comprehensively [45]. Finally, the total system was divided into four subsystems: water resources, water environment, water ecology and social economy. A total of 13 evaluation indexes were selected to construct the evaluation index system of water resources carrying capacity in Zanhuang County (Table 1). If the index value increases indefinitely and approaches the V1 standard with better carrying capacity, it is a positive index. On the contrary, as the index value increases infinitely and approaches the V5 standard with poor carrying capacity, it is a negative index. The definition and criterion of each indicator in the index layer are shown in Table 2.

#### *3.2. Comparison of Weight Results between the Analytic Hierarchy Process and the Entropy Weight Method*

Different weights should be assigned to various evaluation indices because of their different effects on water resources carrying capacity. Weight is a very important factor in fuzzy comprehensive evaluation, and its accuracy directly affects the rationality of the evaluation results. The data sources used in this paper are mainly from the Shijiazhuang Water Resources Bulletin (2017) and Statistical Yearbook of Zanhuang in 2017. The above two calculation methods can be used to obtain the weights of the four subsystems of the analytic hierarchy process (detailed calculation process can be found in the supplementary materials section in Tables S1 and S2), which are respectively WA = 0.46, WB = 0.14, WC = 0.13, WD = 0.27; the weight of the four subsystems of the entropy weight method is WA' = 0.20, WB' = 0.38, WC' = 0.16, WD' = 0.26. The final weights calculated by each index layer are shown in Figure 2.

**Figure 2.** Comparison of weight results calculated by AHP and EWM.

From Figure 2, the five indexes ranked from high to low of the analytic hierarchy process are water resources development and utilization rate, water consumption per unit of GDP, water area index, per capita GDP and domestic water quota, with weights of 0.18, 0.15, 0.13, 0.10 and 0.09, respectively, accounting for 65% of the total contribution rate, including the water resources subsystem and the socio-economic subsystem, which should be the focus of improving the water resources carrying capacity of study area. The other indexes have relatively little influence on the evaluation results. This result verifies that the analytic hierarchy process comprehensively considers the coupling effect between multiple criteria and multiple indicators, and focuses on the importance of identifying effective indicators.

**Table 2.** Definition and criterion of each indicator in the index layer.

The weights of the first five indicators of the entropy method are urban sewage discharge index (0.25), domestic water quota (0.19), water consumption per unit of GDP (0.12), ecological base flow guarantee rate (0.09) and industrial wastewater discharge index (0.06). The first five indicators calculated by this method cover the four sub-systems of the entire criterion, namely, water resources, water environment, water ecology and social economy. First, according to the formula there is no horizontal comparison between the indicators in the calculation process, in that there is no distinction between primary and common indicators. Second, the weight value is too mathematically objective, which covers all the subsystems in the five indicators ranked from high to low. Therefore, the coupling and correlation of the main influencing indicators are often ignored, and it is limited in practical applications. The mutual influence between indicators cannot be ignored for accurate evaluation.

#### *3.3. Comparative Study of Fuzzy Comprehensive Evaluation*

It can be seen from Figure 2 that there is a big difference between the weight results of the analytic hierarchy process and the entropy weight method. Tables 3 and 4 are the comprehensive evaluation results of the analytic hierarchy method and the entropy weight method, respectively. Table 5 presents the correlation analysis, in which IBM SPSS Statistics 25 software was used to illustrate this more clearly.

**Table 3.** Comprehensive evaluation results of water resources carrying capacity by the analytic hierarchy process in Zanhuang County.

**Table 4.** Comprehensive evaluation results of water resources carrying capacity by the entropy weight method in Zanhuang County.

**Table 5.** Correlation analysis of the membership values of two weighting methods and evaluation values.

Note: \*: *p* < 0.05, significant correlation; \*\*: *p* < 0.01, extremely significant correlation.

The reason for this result is that the entropy weight method has some shortcomings. First, the number of indicators selected in this evaluation is larger than the number of objects to be evaluated, resulting in deviations. Second, the entropy weight method ignores the importance of the index and excessively relies on an objective weight assignment, which causes the dimension of the evaluation index to not be reduced and the subjective intention

of the decision-maker to be ignored [32,46]. At the same time, because each township is independent and different, the weight of each index layer should be different. This factor was not well represented in this method, and many similar weight results were obtained during calculation. The analytic hierarchy process comprehensively considers the coupling effect between multiple criteria and multiple indicators according to the intention of the decision-makers and the actual local situation. Moreover, the method more effectively identifies the importance of the main influencing indicators [47].

In Table 5, we have found that among the five membership values obtained by the analytic hierarchy process, four membership values (v1, v2, v3, v5) are significantly correlated with the evaluation value theta, the contribution rate of correlation accounted for 80%. Among the five membership values obtained by the entropy weight method, only two membership values (v1, v5) are significantly correlated with theta and the contribution rate of correlation accounted for 40%. It indicates that the correlation contribution rate of evaluation results obtained by using the analytic hierarchy process is higher than the entropy weight method. The reliability of the analytic hierarchy process is higher. In addition, the average evaluation value theta of the analytic hierarchy process (0.5672) obtained is higher than the entropy weight method (0.4791), and the standard deviation of the former (0.0791) is lower than the latter (0.1019). It also indicates that the error result is smaller. Besides this, the evaluation value obtained by the analytic hierarchy process is also more satisfied with the degree of non-overloading of the evaluation results in the evaluation report of Carrying capacity in Hebei Province. In summary, it shows that the analytic hierarchy process in this study is more suitable for the actual situation.

According to the existing research results, combined with the water resources conditions, ecological environment characteristics and social development of Hebei Province, the comprehensive grading standards are obtained (Table 6).

**Table 6.** Classification criteria of comprehensive score values of water resources carrying capacity.

#### *3.4. Analysis of Evaluation Results*

In general, the scores of the 11 towns and villages in the comprehensive evaluation value determined by the analytic hierarchy process were between 0.4 and 0.7. This result indicates that the water resources carrying capacity of the region is in a general and a good bearing capacity. Water resources remain to be exploited, so the local economy can maintain its development. Domestic and ecological water use is in a relatively balanced state, and there will not be a serious water shortage in the near term.

According to the comprehensive score, Tumen, Zhangshiyan, Zanhuang, Huangbeiping, Yuantou, Xilongmen, Xuting, Xiyangze, Nanqinghe, Nanxingguo and Zhangleng townships are ranked from high to low. In calculating the comprehensive evaluation value, the weight value of each subsystem is different. When the scores are the same, the score value of the subsystem with a larger weight value has a greater impact than does the evaluation result of the subsystem with a smaller weight value [48]. In order to better show the contribution of each subsystem's score to the comprehensive evaluation value, this paper calculates the accumulation of each subsystem in the comprehensive evaluation value of each township to explore the impact of each subsystem. The results are shown in Figure 3. The depth of the color orange on the map is used to reflect the final evaluation value of each region. The darker the color, the higher the evaluation value, and the lighter the color, the smaller the evaluation value.

Because natural water resources and the distribution of local industry are limited, various regions have different water resource conditions, ecological environments, and social and economic development patterns [49]. Therefore, the water resources carrying capacity of 11 towns shows a certain degree of spatial differentiation. To reflect the spatial

divergence of various regions at the subsystem level more clearly, this paper conducted independent fuzzy comprehensive calculations on the water resources, water environment, water ecological and socioeconomic subsystems. After obtaining the comprehensive score value of each system, the results obtained were based on the Kriging interpolation method to carry out optimal unbiased interpolation research on the data results to reduce the uncertainty of the evaluation results. This process was mainly due to the consideration of spatial correlation and independence, which makes the results more reliable. The results are shown in Figure 4.

**Figure 3.** Comprehensive scoring values and accumulation of water resources carrying capacity in Zanhuang County.

Figure 4 shows that the spatial distribution of the four subsystems to the water resources carrying capacity was different because of the different index weights. For (a), the high scoring value was concentrated in the eastern part of the study area, which is far from the mountainous area. However, the other parts of the study area, especially Tumen, mainly consumed a large amount of water for irrigation, leading to a high utilization rate of water resources. Meanwhile, a small number of river systems pass through this area, so the water area index was low. In contrast, the score was higher in the central and western regions due to the distant distribution of industrial and urban centers for (b). The eastern part of the county had a lower score due to the discharge of domestic sewage and industrial wastewater. The difference was significant between agricultural areas and wetland rivers in the (c) regional distribution. The high and low values were more obvious when reflecting the high vegetation coverage and the construction of new river channels. The low value of the (d) region was mostly distributed in the middle and northeastern parts of the study area, which have a high per capita GDP, but the domestic water quota and population

density were much higher than they were in other districts. The contribution of high scores in other regions may be influenced by the urban–rural integration.

**Figure 4.** Maps with the spatial distribution of four subsystems' classification: (**a**) Water resources subsystem quality classification from scoring values; (**b**) Water environment subsystem quality classification from scoring values; (**c**) Water ecological subsystem quality classification from scoring values; (**d**) Socioeconomic subsystem quality classification from scoring values.

#### *3.5. Sensitivity Analysis Results of Weight*

This paper used a fuzzy comprehensive evaluation model of weight determined by the analytic hierarchy process. It determined the sensitivity distribution of the weight change of the index variable. Figure 5 compares the comprehensive evaluation value of each township with and without one indicator weight removed. "BASE" represents the result of the comprehensive evaluation value calculated under the condition of all indices, while "-xx" represents it after removing the weight of this evaluation index. Figure 5 indicates that when certain indicators were removed separately, there were many differences in the results of some comprehensive evaluation values. Therefore, the weights of these indicators are highly sensitive. To further study the sensitivity of the specific index weight to the comprehensive evaluation value of the water resources carrying capacity, the RMSEC of each township after the weight change of each index was quantitatively calculated and added to obtain the total sensitivity, TF. The calculation results are shown in Figure 6.

**Figure 5.** Comparison of the comprehensive score values of each township between original and single index weight removed. (The meaning of the abscissa in the figure is to use the first letters of the names of the locations to represent the towns. The indexes like "A1, A2. . . D3" express the meanings of index layer in Table 1 in turn.)

**Figure 6.** Distribution of total sensitivity of evaluation indexes of water resource carrying capacity. (The indexes like "A1, A2. . . D3" express the meanings of index layer in Table 1 in turn.)

The overall sensitivity results indicated that the index variables with high sensitivities were the water area index, water resource development and utilization rate, and per capita GDP, which reached 73.13%, 38.88% and 27.10%, respectively. All of them belong to the water resources subsystem and were significantly larger than the index variables of other systems. Therefore, special attention should be given to the water resources subsystem with a high sensitivity index in the evaluation of the water resources carrying capacity.

#### **4. Conclusions**

This paper used the fuzzy comprehensive evaluation model to evaluate the carrying capacity of water resources under the weight comparison method. The evaluation results indicated that the 11 townships in Zanhuang County had good bearings. At the same time, the sensitivity analysis method based on the index weight was used to identify the index results with the greatest influence. The evaluation results showed that the sensitivities of the water area index, water resource development and utilization ratio, per capita GDP, water consumption per unit regional GDP and domestic water quota were 73.13%, 38.88%, 27.72%, 27.10% and 15.03%, respectively. The analysis of the attribution results of the water resources carrying capacity subsystem indicated that the water resources carrying capacity of the study area was greatly affected by the regional water resources endowment and socioeconomic statuses.

The case study proved that there is a certain degree of uncertainty in the evaluation of water resources carrying capacity. The main sources of uncertainty are the uncertainty of index assignment and the uncertainty of weight. Among them, the uncertainty caused by water area index is the largest, and the uncertainty caused by fertilizer intensity index is the smallest. The uncertainty of the weight can be studied by the degree of correlation contribution. The degree of correlation contribution of the evaluation value obtained by the analytic hierarchy process is 80%, which is much higher than the 40% obtained by the entropy method. The final evaluation result obtained from the analytic hierarchy process is more in line with the actual state of good carrying capacity in Zanhuang County. Therefore, strengthening the control of the data quality of high-uncertainty indicators can help reduce errors in the evaluation of water resources carrying capacity.

Compared with previous research, the present study provides a good example of the uncertainty of water resources carrying capacity evaluation from the perspective of index sensitivity analysis and weight screening. The result is of great significance to the selection of water resources carrying capacity evaluation indicators and the practical application of evaluation results, which has great value in expanding the application of evaluation models and the development and utilization of local water resources in the future.

**Supplementary Materials:** The following are available online at https://www.mdpi.com/article/ 10.3390/w13202804/s1, Table S1: Evaluation criteria of 1–9 scale method, Table S2: The judgment matrix of four subsystems.

**Author Contributions:** Y.G., methodology, data analysis, software; J.W., conceptualization, formal analysis, supervision; D.Z., methodology, data provision; R.J., software, data curation; H.Y., data curation. All authors have read and agreed to the published version of the manuscript.

**Funding:** This study was funded by the National Natural Science Foundation of China (Grant No.: 41807344).

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

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Data available upon request due to privacy and ethical restrictions.

**Acknowledgments:** The authors would like to express their gratitude to the editors and anonymous experts for their constructive comments.

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

#### **References**


**4.4. Fractional 2 levels factorial design**

Here, the DOE is applied to analyze the objective functions. The proposed approach uses tools of the experimental design method: fractional designs, notably of Box generators to estimate the performance of the induction motor. The interest is to save calculation time and to find a near global optimum. The saving of time can be substantial because the number of simulations needed is significantly reduced.

Since six parameters define the shape of the motor, it is advisable to determine the effect of each parameter on the objective functions. Thus, it is very important to provide proper parameter ranges. The considered parameters are listed in Table 5. There are two types of parameters; continuous parameters and discrete parameters.

Optimization of Induction Motors Using Design of Experiments and Particle Swarm Optimization 199

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**Resolution Design name Number of Runs Generators**

**Table 7.** Box generator of the fractional factorial design 26-2.

**Table 8.** Contrasts and contribution obtained.

**Figure 7.** Plot of effects for the efficiency.

87

87.2

87.4 87.6

87.8

Response

88 88.2

88.4 88.6

**4** 26-2 16 �� � �� � �� � ��

**Contrasts EFF kg/kW Tr I0/I Tst P** 13 2 9 45 7 **CDSW** 1 18 8 0 3 **Cdb** 3 1 0 0 5 **Spp** 4 10 2 25 41 **Tstrip** 34 24 36 0 14 **Zsw** 38 29 39 0 19 **P CDSW + Cdb Tstrip** 1 0 1 0 0 **P cdb + CDSW Tstrip** 2 2 1 0 0 **P Spp + Tstrip Zsw** 2 5 3 18 1 **P Tstrip + CDSW Cdb + Spp Zsw** 1 3 0 4 5 **P Zsw + Spp Tstrip** 1 3 0 4 5 **CDSW Spp + Cdb Zsw** 0 1 0 0 1 **Cdb Spp + CDSW Zsw** 1 2 1 0 0

The application of DOE identifies the effect of each parameter on each objective function. We can notice that for the efficiency Zsw, Tsrip, and P are the most significant factors with respectively 38% 34% and 13% of contribution on the objective function. Moreover, Fig. 7 gives more details. When P is low the efficiency is high and vice versa when P is high.

P CDSW cdb Spp Tstrip Zsw

Factors


**4.4 Quality control and quality assurance**

Amongst the many government or professional organizations that require periodic inspection of frozen samples, the standards put forward by Health Canada are the strictest (Health Canada, 2000). Rigorous standards of operation are essential for sperm banks. Sperm banks must have specific requirements for screening, processing and quarantine of samples. Licensing is required in some countries and sperm banks are inspected in accordance with existing standards or regulations. While auditing is absolutely necessary, it might pose the risk of exposure of frozen specimens to room temperature while such inventory is performed. Straws thaw more rapidly than vials and can warm up to -80°C within 8 to 15 seconds at room temperature, dramatically increasing the possibility of damaging samples during inventory or verification of samples' identity (Tyler et al., 1996). Clear labelling systems to easily identify and link samples to a specific donor or patient must be in place to enable sample location and for performing inventory. The samples should remain in LN2 during the duration of inventory performance and the audit must be performed by qualified and skilled staff.

Several facility and equipment-related quality control and risks factors must be considered for cryopreservation and storage of semen. Physical security of bank facilities and proper identification of sample location within freezers is crucial. Equipment must be appropriate and functional, with defined periodic service and maintenance schedules. Staff must be supplied with all necessary personal protective equipment. Adequate supplies of LN2 gas must be guaranteed and spare LN2 prefilled tank must be available in case of emergency. All staff involved in handling LN2 must be properly trained by a certified organization. Standard operating procedures must be developed to clearly describe each step of the process of sample collection, processing, banking and handling. Annual reviews of both proper documentation and LN2 training must be performed. Temperature of freezers chambers and LN2 levels in tanks must be monitored on a continuous basis and all data logged in secure databases. Alarm systems and appropriate call procedures must be in place to attend to any emergencies. 24 hour monitoring and response is absolutely essential to safely maintain the integrity of the clinical samples in storage. Storage rooms must be monitored continuously for O2 levels and staff activity in enclosed spaces must be monitored to avoid hypoxic injury. Backup power generation must be available in the event of a power failure. Each sample designated for storage has to be properly verified, assessed, processed, labelled, frozen and stored. Double-checking the identity of samples at each step is highly recommended. Some banks choose to divide samples from individual patients or couples and store them in different tanks or locations to minimize the risk of total loss of their biologic material (WHO, 2010).


*Edited by Frank Czerwinski*

Heat treatment and surface engineering are seen as crucial elements in the design and manufacture of strategic components in a wide range of market sectors and industries including air, sea and land transportation, energy production, mining, defense or agriculture. This book offers a broad review of recent global developments in an application of thermal and thermochemical processing to modify the microstructure and properties of a wide range of engineering materials. Although there is no formal partition of the book, chapters represent two different application areas of heat treatment. The first group covers the conventional heat treatment with processing of bearing rings, wrought and cast steels, aluminum alloys, fundamentals of thermochemical treatment, details of carbonitriding and a design of cooling units. The second group describes a use of non-conventional thermal routes during manufacturing cycles of such materials as vanadium carbides, titanium dioxide, metallic glasses, superconducting ceramics, nanoparticles, metal oxides, battery materials and slag mortars. A mixture of conventional and novel applications, exploring a variety of processes employing heating, quenching and thermal diffusion, makes the book very useful for a broad audience of scientists and engineers from academia and industry.

ISBN 978-953-51-0768-2

Heat Treatment - Conventional and Novel Applications

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