*Measuring Infrastructure Skills Productivity DOI: http://dx.doi.org/10.5772/intechopen.85953*

*Infrastructure Management and Construction*

**60**

**Work measurement data collection form**

Firm: Gang no.: No. of skilled: No. of operators in gang:

Contract duration:

Type of building:

Storey building:

No. of floors: Weather condition:

**Element description**

Discharge/loading of material

Mixing of mortar

Laying of blocks

Pointing

Others (specify)

**Table 1.**

*Typical work measurement form [2].*

*R, rating; WR, watch reading/cumulative; OT, observed time; AL, allowance; ST, standard time; BT, basic time.*

Bungalow

Other

No. of unskilled:

Study no.: Start time:

Finish time:

Total observed time:

Wall thickness:

225 mm Wall height:

1.5–2.1 m Above 3.0 m

Observer:

**R**

**WR**

**OT**

**BT**

**AL**

**ST**

**Remark**

100 mm

Other

0–1.5 m

2.1–3.0 m

150 mm

Date:

**Table 2.** *Regression model for skills productivity.*

**63**

**S/N**

**LN man- hours**

**Y**

1 2 3 4 5 6 7 8 9 10 11

6.0400

2.3978

14.4827

5.7494

6.0200

2.3025

13.8611

5.3015

6.0500

2.1972

13.2931

4.8277

6.0400

2.0794

12.5596

4.3239

6.1200

1.9459

11.9089

3.7865

6.0300

1.7917

10.8040

3.2102

6.0100

1.6094

9.6725

2.5902

6.0100

1.3862

8.3311

1.9216

6.0300

1.1098

6.6921

1.2317

6.0400

0.6931

4.1863

0.4804

6.1000

—

—

—

9579.2959

9591.6441

4209.9665

3754.3560

−12.3482

455.6105

**−0.0271**

6.0208

2.3566

−0.0639

**6.0846**

**98.1389**

**X**

**XY**

**X2**

**n∑XY**

**∑**

**X**

**∑**

**Y**

**n∑X2**

**(∑x)2**

**E-F**

**G-H**

**β = I/J**

**Ẏ**

**Ẋ**

**Βẋ**

**α =**

**Ẏ-Βẋ**

**S = 2b\*100**

**LN cycle no.**

**C**

**D**

**E**

**F**

**G**

**H**

**I**

**J**

**K**

**L**

**M**

**O**

**P**

**Q**

*Measuring Infrastructure Skills Productivity DOI: http://dx.doi.org/10.5772/intechopen.85953*

### *Measuring Infrastructure Skills Productivity DOI: http://dx.doi.org/10.5772/intechopen.85953*

*Infrastructure Management and Construction*

**62**

**S/N**

**LN man-hours**

**Y**

**∑** **Table 2.**

*Regression model for skills productivity.*

**156.54**

**61.2728**

**368.4345**

**161.9218**

**942.5226**

**X**

**XY**

**X2**

**Y2**

**n∑XY**

**∑**

**X**

**∑**

**Y**

**n∑**

**X2**

**(∑x)2**

**H-I**

**F-G**

**β = K/J**

**Βẋ**

**α =**

**Ῡ-βẊ**

**LN cycle no.**

**C**

**D**

**E**

**F**

**G**

**H**

**I**

**J**

**K**

**M**

**N**

**O**

#### *Infrastructure Management and Construction*

**Table 3.**

*Learning rate of skills productivity.*

**65**

*Measuring Infrastructure Skills Productivity DOI: http://dx.doi.org/10.5772/intechopen.85953*

completed. Eq. 8 can be rewritten as

**2.2 Questionnaires and interviews**

2.The foreman delay survey

and point-by-point ongoing data.

• The foreman delay survey

• The craftsmen's questionnaire

1.The craftsmen's questionnaire survey

where S is the learning rate, which is defined as the percentage reduction in the unit input, i.e. cost, man-hours or time, as a result of doubling the number of units

Questionnaire and interview techniques involve collection of information through interviews from workers and supervisors in the construction industry [36].

The craftsmen's questionnaire survey is an intermittent perception strategy that is utilised for assessing the management productivity and to recognise difficulties impacting skilled workers' output and motivation. This procedure includes a normal premise; the labourers are asked to give a guess of the loss of time on site, rank the seriousness of the difficulties and prescribe system to these difficulties, and therefore, managers would have the capacity to distinguish difficulties activated by deferrals and their plausible administrative suggestions to these difficulties. This strategy produces work joy and inspiration between the specialists as it communicates the feeling of association in the enhancement of the job instead of being only a device for its achievement [37]. The inconvenience of this system is because information gathered together are normally founded on the labourer's memories and estimates as opposed to correct

Shortcoming originates from the measurement that workforces are not in a site to quantitatively perceive the reasons of general delays as they are not regarding the organisation, which lessens the individual technique and inclined to incorrectness, and work may likewise be irritated when workforces are named upon to fill the forms in classification for namelessness purposes; also, the methodology ends up being troublesome and dreary when every representative needs to fill a form.

The investigation conducted by Chang and Borcherding [37] recommended a new method which is related to the activity sampling method. In this method workers are selected randomly and are requested to fill the questionnaire form based on their utmost current events; this technique leads to better-quality accurateness and abridged work interruption as workforces are near to the observer at their various

The basic principle of the foreman delay survey method is to assist foremen, being closer to their work in order to determine and calculate the losses due to time at the close of each day at work with acceptable correctness [38]. This technique involves the foremen being requested to fill a list for day-to-day delay account in the project site, and the obtained information is measured, and a summary of time lost is shown stipulating all the stages of site supervision, together with the foremen who contributed to the data. This method generates job happiness and motivation for foremen and their teams as they increase in value the fact that their decisions are respected by site

areas of work to complete the surveys form on the spot.

The two types of surveys that are mainly used by observers are:

S = (2^b) ∗ 100 (9)

*Measuring Infrastructure Skills Productivity DOI: http://dx.doi.org/10.5772/intechopen.85953*

*Infrastructure Management and Construction*

**64**

**S/N**

**LN manhours**

**Y**

12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 **∑** **Table 3.**

*Learning rate of skills productivity.*

156.5400

61.2728 *Source: Bureau of Labor Statistics [3], Ugulu and Allen [12].*

368.4345

161.9218

5.9800

3.2581

19.4834

10.6152

6.0100

3.2189

19.3456

10.3613

5.9800

3.1781

19.0050

10.1003

5.9800

3.1355

18.7503

9.8314

5.9900

3.0918

18.5199

9.5592

5.9800

3.0445

18.2061

9.2690

5.9800

2.9957

17.9143

8.9742

6.0100

2.9444

17.6958

8.6695

5.9800

2.8903

17.2840

8.3538

6.0400

2.8332

17.1125

8.0270

6.0100

2.7725

16.6627

7.6868

6.0000

2.7080

16.2480

7.3333

6.0400

2.6390

15.9396

6.9643

6.0400

2.5649

15.4920

6.5787

6.0300

2.4849

14.9839

6.1747

**X**

**XY**

**X2**

**n∑XY**

**∑**

**X**

**∑**

**Y**

**n∑X2**

**(∑x)2**

**E-F**

**G-H**

**β = I/J**

**Ẏ**

**Ẋ**

**Βẋ**

**α =**

**Ẏ-Βẋ**

**S = 2b\*100**

**LN cycle no.**

**C**

**D**

**E**

**F**

**G**

**H**

**I**

**J**

**K**

**L**

**M**

**O**

**P**

**Q**

where S is the learning rate, which is defined as the percentage reduction in the unit input, i.e. cost, man-hours or time, as a result of doubling the number of units completed. Eq. 8 can be rewritten as

$$\mathbf{S} = \{\mathbf{2} \land \mathbf{b}\} \ast \mathbf{100} \tag{9}$$

#### **2.2 Questionnaires and interviews**

Questionnaire and interview techniques involve collection of information through interviews from workers and supervisors in the construction industry [36]. The two types of surveys that are mainly used by observers are:

The craftsmen's questionnaire survey is an intermittent perception strategy that is utilised for assessing the management productivity and to recognise difficulties impacting skilled workers' output and motivation. This procedure includes a normal premise; the labourers are asked to give a guess of the loss of time on site, rank the seriousness of the difficulties and prescribe system to these difficulties, and therefore, managers would have the capacity to distinguish difficulties activated by deferrals and their plausible administrative suggestions to these difficulties. This strategy produces work joy and inspiration between the specialists as it communicates the feeling of association in the enhancement of the job instead of being only a device for its achievement [37].

The inconvenience of this system is because information gathered together are normally founded on the labourer's memories and estimates as opposed to correct and point-by-point ongoing data.

Shortcoming originates from the measurement that workforces are not in a site to quantitatively perceive the reasons of general delays as they are not regarding the organisation, which lessens the individual technique and inclined to incorrectness, and work may likewise be irritated when workforces are named upon to fill the forms in classification for namelessness purposes; also, the methodology ends up being troublesome and dreary when every representative needs to fill a form.

The investigation conducted by Chang and Borcherding [37] recommended a new method which is related to the activity sampling method. In this method workers are selected randomly and are requested to fill the questionnaire form based on their utmost current events; this technique leads to better-quality accurateness and abridged work interruption as workforces are near to the observer at their various areas of work to complete the surveys form on the spot.

• The foreman delay survey

The basic principle of the foreman delay survey method is to assist foremen, being closer to their work in order to determine and calculate the losses due to time at the close of each day at work with acceptable correctness [38]. This technique involves the foremen being requested to fill a list for day-to-day delay account in the project site, and the obtained information is measured, and a summary of time lost is shown stipulating all the stages of site supervision, together with the foremen who contributed to the data.

This method generates job happiness and motivation for foremen and their teams as they increase in value the fact that their decisions are respected by site management. Furthermore, the foreman delay surveys do not consider the availability of data on the efficiency of work approaches in a job and the capability of the labour force or the level of productivity attained; also, it offers a reasonably priced technique of finding input times activities.


**9. Infection control**

Standard prophylaxis is due to cefuroxime 2 g iv every 6 hours in the first 24 hours from heart transplantation (the first two boluses are given in the operating room, at the induction of general anesthesia and once CPB is started). The amount of antibiotic given in the ICU should be tailored for the patient's creatinine clearance, especially if the patient is not under renal filter. Further extension and change of antibiotic therapy should depend on microbiological results of the donor and on microbiological samples of the recipient once admitted in the ICU. Furthermore, in case of redo-operation with existing wound infection, the patient will receive vancomycin and meropenem as standard medication and vancomycin plasma levels should be tested daily. Obviously, due to the immunosuppressive therapy, transplanted patients are very prone to infections. Delivery of care should be done in sterile conditions and, besides standard iv antibiotic therapy, topical antifungal medications should be given in the early postoperative period.

Recipient-related risk factors may be:

• Uncontrolled diabetes (doubled risk)

amount of blood products given.

only emergency treatment.

*11.1.2. Preoperative evaluation*

Technical risk factors are:

predictor of PGD.

• High vasoactive or inotropic support (doubled risk)

intra-aortic balloon pump (IABP) placement may help.

**11.1. Anesthesia and intensive care management**

more complex and creates a unique scenario [24].

pathology and the possible related comorbidities.

*11.1.1. For cardiac transplantation in pediatrics*

• Warm ischemic time (= explant time + implant time); implant time was found to be a strong

Anesthesia and Intensive Care Management for Cardiac Transplantation

http://dx.doi.org/10.5772/intechopen.79837

147

• Resternotomy (it has been identified as a risk factor for severe PGD due to adherences and tissue fibrosis that can extend the explant time and increase the risk of infections).

• Prolonged CPB time, with subsequent systemic inflammatory response, vasoplegia, clotting and platelet dysfunction, leukocyte activation, free oxygen radical release, and larger

All these factors can increase the ischemic-reperfusion injury and the overall mortality [23].

The first step to treat a PDG is vasoactive and inotropic support. If it were not sufficient, an

In case of very severe PGD, an extracorporeal membrane oxygenation (ECMO) becomes the

Pediatric heart transplant represents a small subgroup (14%) of total cardiac transplant where the differences in anatomy and physiology make the surgical procedure and the management

The management of pediatric patients undergoing cardiac transplantation differs from the adult patients because it requires a specific knowledge of physiology and physiopathology at

This heterogeneous population with a wide range of age, genetic disorders, anatomical anomalies, and symptoms can be classified in four different groups based on the different etiology: 1—CHD (congenital heart disease); 2—DCM (dilated cardiomyopathy); 3—RETX

The preoperative evaluation is an essential step in order to better analyze both the cardiac

different stages of growth, from the newborns through childhood up to adulthood.

(retransplant); 4—OTHER (**Table 7**) [25]; each of these has specific features.


*2.5. Sensor Test*

Solutions of a certain pH were prepared from 0.1 M citric acid (aq.) and 0.1 M trisodium citrate dihydrate (aq.), 0.05 M NaH2PO4 (aq.), 0.1 M Na2HPO4 (aq.), 0.05 M NaHCO3 (aq.), and 0.1 M NaOH (aq.). The pH of the buffer solution was measured by a pH meter (INESA PHSJ-3F). Each UPPGF sample was dipped into the buffer solution for 2 min and then blown using a N2 flow to eliminate the excess solution on its surface. The reflectance spectra of the UPPGF samples were recorded before and after the dipping process. The samples were recovered by soaking in pH 10 buffer solution for 2 s, washing with deionized water, and then blowing with N2.

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

#### *3.1. Preparation and Characterization of UPPGF*

The synthesis of ultrathin photonic polymer gel films (UPPGF) is shown in Scheme 1. We obtained close-packed (cp) monolayer colloidal crystals (MCCs) by gas–liquid interface self-assembly. As shown in Scheme 1a, the polystyrene (PS) microspheres were stacked in a dense hexagonal manner on the silicon substrate to form cp MCCs. The non-close-packed monolayer colloidal crystals (ncp MCCs-x) (x = etching time in minutes) was obtained by O2 plasma etching of cp MCCs. P2VP swells by protonation in acid solution.; thus, we selected P2VP as the responsive polymer in this study. The P2VP precursor solution (3.25 wt %, in NM) was immersed into the ncp MCCs by spin-coating (Scheme 1b). Finally, the P2VP was completely cross-linked with DIB in the vacuum drying oven at 120 ◦C to obtain UPPGF-x (x = etching time in minutes) (Scheme 1c).

**Scheme 1.** Steps to fabricate UPPGF. (**a**) Monolayer colloidal crystals of PS nanoparticles were etched through oxygen plasma etching for different times. (**b**) The ncp MCCs was infiltrated with a polymer precursor (qP2VP) solution by spin coating. (**c**) P2VP was crosslinked by annealing.

The packing density of the ncp MCCs can be controlled by adjusting the O2 plasma etching time. The cp MCCs were treated at 80 ◦C for 12 h before etching to enhance the contact between PS and the silicon wafer and ensure that the film did not fall off or fold during etching and response detection. O2 plasma etching was then performed on the cp MCCs. Figure 1 reveals that the particle size of the PS microspheres gradually decreased with increasing etching time (from 438 nm for the sample without etching to 430 nm for ncp MCCs-2, 417 nm for ncp MCCs-4, 404 nm for ncp MCCs-6, and 395 nm for ncp MCCs-8). However, due to the good contact between PS and the silicon wafer, the position of the PS microspheres did not change during the etching process, and the gap between the microspheres increased gradually. Thus, ncp MCCs with different packing density were formed. Low-magnification SEM images reveal that the order of the array was not destroyed by plasma etching, and ordering of PS microspheres was maintained even after etching for 8 min. Such a characteristic is an important condition enabling films to display color and achieve a visual response to pH.

**Figure 1.** SEM images of the ncp MCCs after etching: (**a**,**f**) top views of ncp MCCs-0; (**b**,**g**) top views of ncp MCCs-2; (**c**,**h**) top views of ncp MCCs-4; (**d**,**i**) top views of ncp MCCs-6; and (**e**,**j**) top views of ncp MCCs-8.

UPPGF was prepared by spin-coating a polymer precursor solution onto ncp MCCs and thermal crosslinking. The qP2VP was spin-coated onto the surface of ncp MCCs. As shown in Figure 2, the P2VP was coated uniformly on the surface of the PS microspheres but it did not completely fill the voids between spheres. The viscosity of P2VP is such that rapid spin-coating does not allow it to fully infiltrate the substrate structure. The thickness of the films decreased with increasing etching time (478 nm for qP2VP-infiltrated ncp MCCs-0 to 462 nm for qP2VP-infiltrated ncp MCCs-2, 440 nm for qP2VP-infiltrated ncp MCCs-4, 430 nm for qP2VP-infiltrated ncp MCCs-6, and 414 nm for qP2VP-infiltrated ncp MCCs-8) because the thickness of P2VP on the surface of the PS array was determined by the speed of spin-coating and the concentration of the precursor solution. The thickness of the films depended on the particle size of PS after etching when the speed of the spin-coating and concentration of qP2VP were held constant. Figure 2 shows that the array maintained its good order after thermal cross-linking. Although the temperature of thermal cross-linking was higher than the glass transition temperature of PS, the protective effect of P2VP prevented serious deformation of the microspheres. During thermal crosslinking, P2VP gradually infiltrated the gap between PS microspheres, which grew larger with increasing etching time and allowed more P2VP to infiltrate into the pores. Thus, waves were produced on the surface of the films. Compared with that before thermal cross-linking, the thickness of the films decreased (from 478 to 440 nm for UPPGF-0, from 462 to 419 nm for UPPGF-2, from 440 to 397 nm for UPPGF-4, from 430 to 390 nm for UPPGF-6, and from 414 to 387 nm for UPPGF-8). This finding is related to the slight deformation of PS microspheres and the infiltration of P2VP.

**Figure 2.** SEM images of the fabricated structures: (**a**–**e**) cross-sectional views of the qP2VP-infiltrated ncp MCCs-x (x = (**a**) 0 min; (**b**) 2 min; (**c**) 4 min; (**d**) 6 min; and (**e**) 8 min); and (**f**–**j**) cross-sectional views of UPPGF-x (x = (**f**) 0 min; (**g**) 2 min; (**h**) 4 min; (**i**) 6 min; and (**j**) 8 min) obtained after thermal annealing.

#### *3.2. Optical Properties of UPPGF*

To better understand the effect of O2 plasma etching on the structure of the film, we studied its optical properties. A high-refractive index silicon wafer (*n* ~ 3.5) was chosen as the substrate on which to construct UPPGF. Fabry–Pérot fringes are formed by reflecting the interference between the beams of the thin-film air and thin-film substrate interfaces [37]. Under normal conditions, the position of the interference peak wavelength conforms to Equation (1) [38]:

$$m\lambda = 2nd,\tag{1}$$

where *n* is the refractive index of the film, *m* is an integer, and *d* is the thickness of the film. Calculations indicated that the peak of the cp MCCs was located in the visible region (585 nm; *d* = 438 nm, *m* = 2, and *n* = 1.335) [39]. In the experiments (Figure 3a), the center of the reflection peak was found at 588 nm. The valley observed was the result of multiple scattering from a single sphere, and the characteristic mode of 2D photonic crystals with hexagonal symmetry was found. The position of the valley gradually shifted toward shorter wavelengths with increasing etching time (625 nm for ncp MCCs-2, 617 nm for ncp MCCs-4, 611 nm for ncp MCCs-6, and 596 nm for ncp MCCs-8). This finding could be attributed to the refractive index of the film gradually decreasing with increasing etching time, because the distance between colloidal crystal microspheres did not change with the increase of etching time, but the ratio of air in the array increased, resulting in the decrease of effective refractive index of the film, consistent with the phenomena observed in the SEM images (Figure 1).

**Figure 3.** Optical properties of the fabricated structures:(**a**) reflectance spectra of the ncp MCCs-x obtained at different etching times (x = 0, 2, 4, 6, 8 min); (**b**) reflectance spectra of the qP2VP-infiltrated ncp MCCs-x; and (**c**) reflectance spectra of UPPGF-x obtained after thermal annealing.

We constructed UPPGF by spin-coating and thermal crosslinking. We found only one reflection peak in the visible region after spin-coating of the qP2VP, and no valleys associated with the photonic characteristic mode were observed. This is because of the refractive indices contrast was eliminated when the P2VP was infiltrated into the films. In this case, the position of the reflection peak also moved toward shorter wavelengths with increasing etching time (688 nm for qP2VP-infiltrated ncp MCCs-0, 653 nm for qP2VP-infiltrated ncp MCCs-2, 619 nm for qP2VP-infiltrated ncp MCCs-4, 584 nm for qP2VP-infiltrated ncp MCCs-6, and 549 nm for qP2VP-infiltrated ncp MCCs-8; Figure 3b). Because the thickness of the film decreased gradually, the UPPGF obtained by thermal cross-linking showed the same trend (656 nm for UPPGF-0, 621 nm for UPPGF-2, 589 nm for UPPGF-4, 547 nm for UPPGF-6, and 533 nm for UPPGF-8; Figure 3c). The reflection peaks of all films demonstrated a certain blue-shift after thermal cross-linking, which was due to the decrease in film thickness. The above data are consistent with the change in film thickness observed in the SEM images (Figure 2).

#### *3.3. Responsiveness of the UPPGF to pH and Mechanism Research*

We tested the responsiveness of the UPPGF sensors to pH by immersing them in buffers of different pH. P2VP swells in acidic solution, and its degree of swelling is related to its degree of protonation. Figure 4 illustrates that the reflection peaks of the films did not change significantly when the films were immersed in alkaline solution (pH ≥ 7). In acidic solution (pH < 7), however, the reflection peaks of all films gradually shifted toward longer wavelengths with decreasing pH. Even under strongly acidic (pH = 2.57) conditions, this response was maintained because the PS array prevented the collapse of the film structure caused by the high degree of swelling. This phenomenon is shown more intuitively in Figure S5. As shown in Figure 4f and Figure S5, in comparison with that of UPPGF-0, the pH responsiveness of the UPPGF templated by non-close-packed monolayer colloidal crystals was improved, and UPPGF-4 and UPPGF-6 showed the best responsiveness to pH. The displacement of reflection peak of UPPGF-4 was 80 nm, about 30 nm longer than the wavelength shift of UPPGF-0. However, compared with that of UPPGF-6, the responsiveness of UPPGF-8 was reduced to a certain extent. It is well known that the sensing ability of polymer gel sensor is closely related to the volume of polymer gel. Thus, we think that the responsiveness of the UPPGF was determined by the volume of P2VP, and the volume change of P2VP in the UPPGF may be influenced by etching.

**Figure 4.** (**a**–**e**) pH dependence of the reflectance spectra of the UPPGF-x (x = (**a**) 0 min; (**b**) 2 min; (**c**) 4 min; (**d**) 6 min; (**e**) 8 min) sensors after equilibration in pH buffer solution; and (**f**) the corresponding shifts of the reflectance peak of UPPGF-x.

We further explained the variation of the pH responsiveness of the UPPGF with increasing etching time through simple calculation based on geometric model. In Scheme 2, we set the diameter of the PS microspheres as *D* and the total thickness of the film as *H*. The *D* of the PS microspheres decreased to *d* after etching, assuming that the thickness of P2VP on the PS microspheres *h* is unchanged. We then calculated the volume (*VP2VP*) of P2VP with decreasing *d*:

$$V\_{P2VP} = V\_{total} - V\_{PS} = \frac{3\sqrt{3}D^2H - \pi d^3}{12} = \frac{3\sqrt{3}D^2(h+d) - \pi d^3}{12} \tag{2}$$

$$V\_{P2VP}' = \frac{\sqrt{3}D^2 - \pi d^2}{4} \tag{3}$$

$$
\Delta\lambda = \frac{2n \cdot \Delta H}{m} = \frac{2n \cdot V\_{\text{P2VP}} \cdot f\_{\text{P2VP}}}{m} \tag{4}
$$

**Scheme 2.** (**a**–**e**) Side views of UPPGF-0, UPPGF-4, and UPPGF-8; and (**d**–**f**) top views of UPPGF-0, UPPGF-4, and UPPGF-8.

We found that the *VP2VP* did not always increase with decreasing *d*. Using Equations (2) and (3), we calculated that *VP2VP* increased gradually as *D* decreased from *D* to 0.74*D* but decreased gradually with further decreases in particle size beyond 0.74*D*, i.e., *VP2VP* reached its maximum value at 0.74*D*. According to Equation (4) (where Δ*λ* is the displacement of the reflection peak, Δ*H* is the change in thickness of the film, *n* is the refractive index of the film, *m* is an integer, and *fP2VP* is the swelling rate of P2VP), the displacement of the reflection peak is proportional to the variation in *VP2VP*. Therefore, the law of responsiveness of UPPGF to pH is well explained. In the actual tests, however, maximum volume was achieved even if the particle size was not reduced to 0.74*D*, likely because P2VP did not completely cover the film, as assumed, to form a smooth surface (Figure 2). Thus, *VP2VP* in the actual experiments decreased at a faster rate than predicted by the calculations.

We monitored the change in film thickness with decreasing pH through SEM to confirm our hypothesis. In Figure 5, the thickness of UPPGF-4 increased from 397 to 408, 419, 440, and 449 nm in response to immersion in pH 5.08, 4.20, 3.39, and 2.57 buffer solutions, respectively; the thickness of the UPPGF would still increase when pH is 2.57 with no structural collapse. Other films showed the same trend with decreasing pH (Figures S1–S4). UPPGF-4 also showed the maximum thickness variation, which explains why UPPGF-4 had the best pH responsiveness.

**Figure 5.** SEM images of UPPGF-4 after equilibration in buffer solution at: pH 5.08 (**a**); pH 4.20 (**b**); pH 3.39 (**c**); and pH 2.57 (**d**).

#### *3.4. Linearity of the UPPGF to pH and Mechanism Research*

Sensors with good linearity can detect analytes more accurately in the whole range of measurement. As shown in Figure 6a, we found that the linearity towards pH was gradually enhanced with increasing etching time. The coefficient of determination (R2) of the sensor gradually increased from 0.95684 (UPPGF-0) to 0.9816 (UPPGF-8). This phenomenon can also be explained by Scheme 2. The relationship between the filling fraction of P2VP (*NP2VP*) and PS particle size (*d*) is in accordance with Equation (5):

$$N\_{P2VP} = 1 - \frac{\pi d^3}{3\sqrt{3}D^2(h+d)}\tag{5}$$

**Figure 6.** (**a**) Linear relation between UPPGF-x (x = 0, 2, 4, 6, 8 min) and pH; (**b**) response kinetics of UPPGF-x to a pH 3.39 buffer solution; (**c**) reversibility of UPPGF-x over 10 cycles of exposure to pH 9.17–3.39; and (**d**) hysteresis loops of the UPPGF-x sensors between pH 9.17 and 2.57.

Equation (5) reveals that *NP2VP* always increase with decreasing *d*. We thus considered that *NP2VP* is an important factor affecting the linearity of response. Although the PS array provided the necessary optical signals for the film, it could restrain the regular swelling of the polymer gel. Therefore, the linearity of UPPGF increased with increasing etching time. Considering response degrees and linearity of response, UPPGF-6 exhibited the best properties among the synthesized films.

#### *3.5. Response Speed of the UPPGF to pH*

Fast response speeds are widely favored in practical applications. We measured the response speed of the UPPGF by immersing them in buffer solution of pH = 3.39 and recording the change in reflection peak over time. Approximately 90% of the total response could be achieved within 10 s by the films, and stable responses could be achieved within 2 min (Figure 6b). The response speed of UPPGF was faster than that of the inverse opal hydrogel pH sensor (20 min) reported by Braun et al. [23] and the 2D-PCCA pH sensor (30 min) reported by Asher et al. [15], and comparable with our previously reported inverse opal monolayers of P2VP gels [31] and ultrathin P2VP gel-infiltrated MCCs films [32]. This fast response speed was due to the structural characteristics of the UPPGF, which included submicron thickness. The response speeds of UPPGF did not decrease with increasing volume of P2VP. Although the volume of P2VP increased after etching, the thickness of the whole film decreased.

#### *3.6. Stability of the UPPGF to pH*

We tested the stability of the UPPGF samples. Folding or shedding was not found in the SEM images when the UPPGF responds to the pH buffer solution (Figure 5 and Figures S1–S4). Then, the films were immersed in buffer solution of pH = 3.39 and then recovered in a solution of pH = 9.17. Figure 6c reveals that the position of the reflection peak remains basically unchanged after 10 cycles, thereby indicating good cyclic stability. Although more P2VP was in contact with the substrate with increasing etching time, the contact force between PS and the silicon substrate was

improved through heat treatment of the cp MCCs at 80 ◦C prior to etching. Thus, the UPPGF sensors showed good stability.

#### *3.7. Hysteresis Loops of the UPPGF to pH*

Sensors with low hysteresis loops can accurately detect the environment regardless of their input history. The peak shifts of the UPPGF samples observed under two approaches of pH input, i.e., from pH 9 to 2 and from pH 2 to 9, were recorded, and film recovery was found to be unnecessary for detecting different pH solution. As shown in Figure 6d, all UPPGF exhibited small hysteresis loops with short test times (2 min), likely because of the submicron thickness of the film. Ions could diffuse rapidly through the film, and the polymer gel could swell and shrink quickly. Thus, UPPGF can be used to test the environment continuously.

#### *3.8. Visual Response of the UPPGF to pH*

Importantly, the UPPGF achieved visual response to pH. In Figure 7, we can see that the color of the film changed with the change of pH. Compared with UPPGF-0, the color change of the UPPGF templated by ncp MCCs was more obvious. This phenomenon is consistent with the change of the redshift of the reflection peak with the etching time (Figure 4). Moreover, other responsive materials (for example, other responsive polymer gels, MOF, etc.) can be combined with ncp MCCs to improve their sensing capabilities. A sensor array could be obtained by the combination of the films etched at different times to achieve more accurate analysis.

**Figure 7.** Optical micrographs showing the pH dependence of the different response colors of UPPGF-x (x = 0, 2, 4, 6, 8 min) (the size of each optical micrograph: 1.2 mm × 0.9 mm).


4.4.2. Photocatalytic Hydrogen Formation

The photocatalytic H2 generation experiments were conducted in quartz vials (capacity of 10 mL) under illumination with a 1000 W Xenon lamp (Hönle UV Technology, Gräfelfing, Germany; Sol 1200 solar). An amount of 6 mg of the photocatalyst was suspended in 6 mL aqueous methanol (10 vol% methanol). The suspension was purged with argon for 20 min to remove the air, and the quartz vial was sealed with a specially made rubber septum degassed for sampling. The amount of H2 gas evolved during the photocatalytic reaction was quantified every two hours using a gas chromatograph (Shimadzu GC-8A, Shimadzu Deutschland GmbH, Duisburg, Germany) equipped with thermal conductivity detector (TCD) and 60/80 molecular sieve 5 Å column.


The metering of water use and the collection of fees either for amounts overstepping quota or for every cubic meter of water pumped certainly serves the purpose of ensuring general discipline in water use. It is however only justified if the fees lead to a reduction of pumping. This can happen either directly or indirectly by using the collected fees to subsidize water saving measures.

Metering by electricity consumption is practicable and makes economic sense. It should be developed further with the electricity company using their daily available "big data". It would be ideal if the water fee could be collected automatically together with the electricity fee saving the effort for a second fee collection system.

Much has been achieved in the last years and a combination of crop system change and South-North Water Transfer (SNWT) clearly has sufficient potential to stop aquifer depletion, not only in Guantao but in the whole of the NCP. But stopping the depletion is not enough. Even if a cone of depression is stabilized by surface water imports and a hydraulic quasi-steady state can be reached, such a closed system will salinize with time. Only if drainage outflows to the sea via canals, streams, rivers and the aquifer are restored one can truly speak of a sustainable solution. In future, the focus should turn to groundwater quality. The salinity of pumped water should be monitored at least once per year. The increased agricultural pumping in the deep aquifer of the last few years is probably already related to an increase in salinity in the shallow aquifer's cones of depression. While the end of over-pumping is within reach, the salinity problem will not go away and requires further careful management.

### **5.2 Agriculture and Future Groundwater Management in the NCP**

Groundwater depletion in the NCP was a consequence of the governments' will to battle famine in the early 1980s. Hebei Province played an important role in feeding the country since then. It increased its yield by 2–3 times over the past 3 decades. The intensification of food production coincided with a time of decreasing rainfall, which magnified the consequences regarding groundwater levels.

The centralized governmental structure in China usually allows the Chinese leaders to mobilize a vast amount of resources to pursue a goal or solve any problem in a determined manner once an issue is confirmed as extremely important. If a problem is perceived as in conflict with other objectives of interest, any decision is essentially a trade-off. This is the case for groundwater management in the NCP because mitigating groundwater over-pumping may hurt national food security and farmers' income, which are both considered at least as important as environmental protection, if not more important. In 2021, the agricultural department again received the task of increasing crop production (http://www.xinhuanet.com/2021-01/03/c\_1 126940702.htm).

Population will peak between 2025 and 2030 at about 1.5 billion (Chen et al. 2020), who want to have an ever-richer diet with more meat, vegetables, and fruit. Climate change will decrease the yield of some of today's cultivars due to higher temperature and increase the water demand of crops due to higher ET (see Sect. 5.5). Water scarcity is exacerbated by deteriorating soil and water quality. Climate change may also put a question mark to the water transfers from the South, which must maintain a reserve for its own growth. So, will the solutions envisaged today still hold in 2050 or does it take more? To approach this question, a look at some trends of today is helpful.

### *5.2.1 Transition from Smallholder Agriculture to Larger Farms*

The first trend is the transition from the present smallholder agriculture to modernized larger-scale farming in the NCP. The smallholder family farms with a cropping area of a third of a hectare, are economically unattractive and have no future. The annual income from a winter wheat and a summer maize crop on that area is less than 3000 CNY per person , which compares unfavorably with the average annual income in China of about 30- 000 CNY per person. Young people leave the countryside and look for jobs in the cities. Their support of their parents is usually more significant than the parents' own income from farming. Most people working in the fields are above 45 and the question must be asked, who will produce China's food in 2050 (see Box 5.2). The situation is expected to change dramatically in the next decade(s) due to the fast change in rural population structure. With it, agricultural production activities and organization forms will change substantially too, from smallholder farming to larger farms through land aggregation.

Take Switzerland for example: For an economically viable farm of 4 persons in Switzerland a farm area of about 100 ha (300 times the area of a Chinese family farm or almost the size of the whole cropland of a village in the NCP) is necessary. It is typically managed by the family plus one additional farm hand, which is feasible due to a high degree of mechanization, applying modern technology both for remotely controllable hardware, including machinery and irrigation equipment, and for information technology harnessing information on plant health, weather and markets for example.

Chinese farming is developing in the same direction. Farm sizes in the NCP are already increasing. Big entrepreneurs lease land from individual farmers, sometimes of whole villages, to practice a larger scale and more efficient style of farming. This opens up new opportunities also for increased efficiency in water use. However, it is unclear how grain production can eventually become profitable for big farms relying on land leased from small farm households. With the current leasing cost (800–1000 CNY/mu/year), planting grain crops (wheat and maize) is not sufficiently profitable to attract farming enterprises to take over. Agricultural land ownership and the right to trade ownership in a more permanent way will become more and more a critical issue in this transition process.

Using engineering and agronomic approaches, larger farm units can fully exploit the potential for improving water use efficiency beyond today's level. While highly efficient center-pivot sprinklers are neither applicable nor affordable for today's small family farms, they can unfold their full water saving potential on farms of at least 100 ha in size. A large farm can also afford to fallow a certain percentage of its area in order to let the soil rest or to plant green manure without having to be pushed by government. Today's pioneers of big farming go into niche products such as plant seeds, health foods, medicinal plants, or farm tourism to optimize income. At the next stage, grain production should be considered for scale-up to a more efficient and profitable operation.

Greenhouses are the most profitable production units, even at the scale of a family farm. When equipped with soil moisture sensors and automatic drip- or microsprinkling equipment they can save significant amounts of water compared to the traditional green houses. At the same time, they can save labor, which meanwhile has become expensive in China. In the US, vertical farms are quickly expanding. They produce vegetables in hydroponic cultures close to the consumer. Their water use is minimal as most of the transpired water can be recycled. And they do not need any agrochemicals except nutrients. Economic viability relies on the consumers' demand for healthy food. China's urban elite is also conscious of food quality, which shows in collective ordering or "crowd farming" of farm products from trusted producers in the periphery.

Bigger farms allow a more scientific approach to crop production, often termed "precision agriculture", which benefits the quality of the produce as well as the environment. Drones already today apply crop protection products. In future they will be able to deposit those products on plants in need only. Similar technology can improve fertilizer application to conserve nutrients and reach more uniform production over the area.

The smart water meters, which have been successfully applied in China's West will also be sustainable in the NCP if pumping in big farms is concentrated on fewer wells. Management of water quota by a county's water resources administration will become feasible when it needs to address only a small number of large farms instead of thousands of small farms. Already during the project, the biggest farm of Guantao enthusiastically volunteered to cooperate with our metering experiment. They want to save water—and thus energy—as they are much more conscious of cost-efficiency than the smallholder farmers. Smart devices such as smart water meters with data transmission to a central server and eventually a feedback from that server to the device, mark the beginning of the Internet of Things (IoT) in agriculture.

Information technology and the full use of available information have to play a bigger role in farming. Alibaba launched the "ET Agricultural Brain". This digital tool enables farmers to raise their crop yields and income by leveraging big data. The app allows farmers to digitally record information about their yields in order to optimize their entire production cycle, raising efficiency and capacity. It was preceded by similar efforts in North America where for example Climate Corporation analyses 50 terabytes of weather data every day and sends the information to users via its Software-as-a-Service platform Climate.com. The corporation's goal is to leverage data to help farmers deal with the increasingly volatile weather caused by climate change.

Agricultural research in China is quite advanced, but it is slow in trickling down into practice. A recent example shows how it can be made available to farmers faster: Through a national campaign, about 20.9 million farmers adopted the recommendations of a study, which increased productivity and reduced environmental impacts. As a result of the intervention, farmers were together US\$12.2 billion better off through savings in fertilizer and increase in yield (Cui et al. 2018). The new type of agriculture requires human resources with the relevant education. To feed China's population in 2050, a scientifically educated workforce with an agricultural background will be vital (Tso 2004).

Increase of production per ha does not automatically mean increase of production per cubic meter of water, i.e. more "crop per drop". Therefore, optimization of production must go in parallel with other options of reducing water use. Agrotechnology has still some other methods in store, which under the name of "new green revolution" will help to optimize the combined efficiency of water and nitrogen use (see Sect. 5.3).

### *5.2.2 Consumer Behavior and Food Demand*

Water saving must include the **reduction of food waste** post-harvest, in retail and on the level of the consumer. In recent years Chinese propaganda campaigns focused on the reduction of food waste in restaurants. In Europe initiatives push smart logistics for internet-based distribution of food close to expiration date. Food saved is water saved.

Future water demand is closely related to the diet people desire (McLaughlin and Kinzelbach 2015). Even a stagnating population will further increase water demand if the present trend towards increasing consumption of meat and milk products continues. In the past 30 years China's meat consumption has grown 2.5 fold with a population increase of about 15%, and the trend towards more meat continues, with values admittedly still low in comparison to many western countries (see Box 5.3)

Box 5.2: Development of China's population and possible consequences for agriculture.

.

However, the trend in meat consumption could change over health concerns. Young people in the west turn to vegetarianism. While the number of vegetarians in Germany was estimated to be 0.6% in 1983, it increased to about 10% of the population in 2016, with typical vegetarians being between 19 and 29 years old (Mensink et al. 2016). The market adapted to this dietary shift and the associated new demand. Sales of meat substitutes are increasing rapidly, creating a new billion-Dollar market.

The **diet** plays an important part in determining the water demand in agriculture. Of course, its meat component impacts in the first place the production of feed grain, which grows in summer and presents a smaller potential for water saving than wheat. But **substitutes**for wheat could also be considered. Potatoes yield the largest number of calories with the least input of water per unit area. Of course, dietary changes need time for people to get accustomed to. But did China not get accustomed to wheat after centuries of millet? Potatoes, which were unknown before Columbus, are the 4th staple food crop (after rice, wheat and maize) in China since 2015 (Xinhua 2015). Possibly China may also get used to Quinoa, which is advocated by the UN in its efforts to enhance the globe's food security while saving water (FAO 2011).

Box 5.3: Development of China's meat consumption

### **5.3 Drought Resistant and High Yield Wheat Varieties**

Managing groundwater sustainably depends to a high degree on agricultural strategies adopted in the NCP. Pursuing high yield to feed people was the major agricultural target pursued during the past 4 to 5 decades. The NCP played an important role in improving grain production during this period, when numerous high yield varieties were bred and widely cultivated. The yields of wheat and maize increased considerably from 1980 to 2010 (Fig. 5.1). They can reach 9 t/ha for wheat and 10.5 t/ha for maize today. This is much higher than the respective national average yields of 6.2 t/ha and 5.4 t/ha (2019 data) and opens up a yield gap. While the development of crop varieties has helped to achieve the goal of self-sufficiency in agricultural goods, the yield gap still presents a reserve to be activated.

The achievements in grain production were accompanied by a tremendous increase in fertilizer and irrigation water inputs, with the well-known consequences for groundwater depletion.While over the last 40 years yield increase was the primary objective, now the reduction of agricultural intensity has become an essential option to mitigate groundwater level decline.

Increasing attention has been given to the applications of biologic approaches, such as breeding of drought resistant varieties, or genetic modification and gene editing to largely improve photosynthetic efficiency. According to 30-year field experiments at the Center for Agricultural Resources Research, Institute of Genetics

**Fig. 5.1** Changes of grain yield and WUE for wheat and maize in NCP from 1980 to 2010 (Zhang et al. 2011)

and Developmental Biology, CAS, a wheat variety with high water use efficiency could save 30–50 mm of irrigation water compared to the normal varieties planted in NCP (Fang et al. 2017) with almost the same level of yield. The WUE could be improved by 21.6% maximally by adoption of highly water productive varieties for wheat. On average, adopting high WUE varieties could achieve an increase of grain yield by about 1% and an increase in WUE by 0.5% annually (Zhang et al. 2010).

A recent study revealed that nitrogen status affects rice chromatin function through the modification of histones, and some specific genes regulating tillering. The transcription factor NGR5 mediates hormone signaling and increased NGR5 levels can drive increases in rice tillering and yield without increasing nitrogen fertilization requirements (Wu et al. 2020). This kind of breakthrough in genetic or biological sciences can be expected to greatly improve water and nitrogen use efficiencies of grain crops. Therefore, another "green revolution" through genetic editing technologies may happen in the near future. It should result in new drought resistant crop varieties and varieties with higher photosynthetic ability, using less water and nitrogen fertilizer.

### **5.4 Importing Surface Water: Benefit and Risk**

For regions lacking large rivers while suffering from severe water shortage, groundwater overdraft seems to be inevitable and importing surface water from outside of the region is the most direct and effective way to alleviate the decline of groundwater levels. Based on the experience from groundwater overdraft control in the NCP so far, importing surface water should not only increase the availability of water but also the efficiency of its use. Present use of surface water imports is extremely inefficient as the timing of water transfers depends on flows in the upstream, which are not synchronous with the irrigation calendar. Storage capacity available in the plain area is by far not sufficient to allow more efficient use of the imports. Improvement requires further updating of water infrastructure including the water system's connectivity and maintenance, e.g. by dredging river channels, renovating pools and ponds, as well as using imported water for MAR.

Import of surface water has been planned, designed, and implemented rather well compared to other methods of groundwater over-pumping control so far. Although it seems irreplaceable in the struggle to end groundwater depletion in the NCP, it is still facing considerable risks and uncertainties.

The surface water quota from the Yellow River will still be strictly limited in the near future. Due to constraints on water quota, after three years of groundwater overpumping governance, almost all cities and counties have used up their quota of Yellow River water. However, some counties' task of cutting down on groundwater extraction has not been achieved. In Hebei Province Yellow River water has mainly been used for agricultural irrigation. If no further imports are possible, groundwater over-pumping governance can only rely on optimization of the cropping structure, which depends heavily on government subsidies. With the decline of these, the further promotion of over-pumping control action in these mainly rural areas remains challenging.

The high cost of water supply from the SNWT project brings risk and uncertainty to the groundwater over-pumping control system. One important reason is that Hebei provincial government can only spend a small portion of its whole budget for projects supporting the SNWT. 78% of the investment relies on bank loans. The construction of water treatment plants and connecting water supply pipelines is mainly supported by financing through non-governmental investors. These investors expect high returns on their investments. The above two factors result in high water supply and transfer costs for the SNWT. The water price at the entrance of the main canal of the SNWT Project into Hebei Province is 0.97 CNY/m3, the price of water entering the surface water treatment plant is 2.76 CNY/m3, and the water price for the consumers is 7.43 CNY/m3, which is 24% higher than in Beijing, and 34% higher than in Tianjin. It amounts to 155% of the current average water price in urban areas, and to 210% of the current county average water price of Hebei Province.

Due to its high price, water of the SNWT Project is not affordable for agricultural and ecological purposes. Even redundant SNWT water is too expensive to replace groundwater in agricultural irrigation and preserve the groundwater system.

If the present water price of the SNWT's Central Route of 2.5 CNY/m3 is assumed, the water needed for irrigation of winter wheat would cost about 6- 000 CNY/ha. This amount is close to the present input cost for planting one ha of winter wheat and would make wheat planting with SNWT water economically infeasible. Today, the irrigation cost of wheat with groundwater (including maintenance and labor) is about 1000 CNY/ha or 1/6th of the total input cost. The cost of water of the Eastern Route will be less than that of the Central Route, but it cannot be cheaper than groundwater as it has to be pumped up by about 100 m from the Yangtze River, about twice the lift presently necessary for deep aquifer groundwater in the NCP. If the management of all irrigation water would be put into the responsibility of one big company, they could make an average price, which would dilute the high marginal cost of the transfer water to an acceptable prize for food production.

### **5.5 Climate Change in the NCP**

Climate change influences the fate of groundwater resources in the NCP in many ways. Precipitation determines not only groundwater recharge. It also determines the need of supplementary irrigation and therefore groundwater abstraction. Its distribution in time, extreme rain events or drought events can be as important for agricultural production as the annual total precipitation. Temperature, wind speed and radiation influence the potential evaporation, which finally determines the evapotranspiration potential of the crops and thus the water requirements. Finally, climate change may affect the flow of rivers, which are now the source of water transfers to the NCP.

The NCP has seen climate change in the past. Observations since the mid-twentieth century show that it has become warmer and drier. Most observed downward trends in annual precipitation amount were statistically significant (Chen et al. 2010; Fu et al. 2009; Liu et al. 2005; Sun et al. 2017; Wang et al. 2012). Summer precipitation, which accounts for 50–75% of the total annual rainfall in NCP, also has decreased significantly (Fan et al. 2012; Sun et al. 2020; Wang et al. 2012; Ye 2014), while precipitation in other seasons has shown contrasting trends (Fan et al. 2012; Sun et al. 2020). The decrease in rainfall led to a decrease in groundwater recharge. Significant increase was not only observed in the mean annual temperature but also in temperature during both wheat and maize seasons (Chen et al. 2010; Liu et al. 2014; Zhang et al. 2015). Surprisingly, a long-term decreasing trend has been observed in actual evapotranspiration, which can be explained by decreasing trends in precipitation, sunshine duration and wind speed which overcompensated the increase in ET due to temperature rise alone (Cao et al. 2014; Chen et al. 2010; Fan et al. 2012; Liu et al. 2014; Song et al. 2010). A recent study based on remote sensing and physical modeling found that actual evapotranspiration increased slightly since 2000, but concluded that the contribution of climate change was less than that of human activities (Chen et al. 2017). The result agrees with the measurement data of Luancheng Agro-Eco-Experimental Station of the Chinese Academy of Sciences showing that the actual seasonal ET of winter wheat and summer maize under wellwatered conditions gradually increased from the 1980s to the 2000s possibly caused by the increase in leaf stomatal conductance associated with the introduction of new cultivars (Zhang et al. 2011). With global warming, more crops can be grown in Northeast China, which has better rainfall, and the recent decades already have shown some shift in production from the NCP towards the Northeast, reducing the pressure on the NCP.

The Fifth Assessment Report by the Intergovernmental Panel on Climate Change (Pachauri et al. 2014) provides the analysis of model outputs from the fifth phase of the Coupled Model Intercomparison Project (CMIP5). CMIP5 produced a state-of-theart multi-model dataset designed to advance our knowledge of climate variability and climate change including "long term" simulations of twentieth-century climate and projections for the twenty-first century and beyond for a number of Representative Concentration Pathways (RCPs) for atmospheric greenhouse gas (GHG) concentrations (Van Vuuren et al. 2011). Annual averages of temperature and precipitation for two RCPS and a time interval at the end of the century are shown in Fig. 5.2. Looking at Eastern China for the more pessimistic RCP8.5, one can find a strong increase in yearly average temperature (5–7 °C) and an increase in annual rainfall (10–20%) compared to the baseline of 1986–2005. For a lower emission scenario, annual rainfall hardly changes, while average temperature increase is about 1 °C.

To adapt these global projections to regions, a process called downscaling is required to obtain a higher spatial resolution suited for the scale of the region. The problem with the projections is their uncertainty. While different models usually agree well as far as the projected temperature rise is concerned, predictions of rainfall are extremely uncertain reaching from increase to decrease of rainfall. This is also true for the NCP, where the ensemble of climate models shows discrepancies among GCMs and downscaling methods, concerning the projected mean and extremes of precipitation. Some studies show a likely increase in annual precipitation but at varying rates (Fu et al. 2009; Tao and Zhang 2013), while others project a decline in annual precipitation (Liu et al. 2013). Being influenced by several climate variables, evapotranspiration estimates turn out to be very uncertain, making it difficult to draw conclusions about future trends. The projected changes of evapotranspiration during the wheat or wheat–maize growth period in the NCP could either increase or decrease within a range of around ± 10% depending on the GCM and greenhouse gas emission scenario employed (Guo et al., 2010; Lv et al. 2013; Mo et al. 2013; Tao and Zhang 2013).

We can distinguish direct and indirect impacts of climate change on groundwater resources. Changes in the amount, intensity and frequency of precipitation directly determine groundwater recharge and indirectly influence the demand of groundwater pumping for irrigation. The direct impacts of changes in precipitation on groundwater recharge have been found to contribute less to groundwater resources than the changes in pumping, not only in the NCP but also in other regions (Larocque et al. 2019; Li et al. 2014). However, it should be noted that studies on climate change assessments usually ignore the indirect impacts of precipitation on groundwater pumping, and

**Fig. 5.2** Change in average surface temperature (a) and change in average precipitation (b) based on multi-model mean projections for 2081–2100 relative to 1986–2005 under the RCP2.6 (left) and RCP8.5 (right) scenarios (Pachauri et al. 2014). The number of models used to calculate the multi-model mean is indicated in the upper right corner of each panel. Stippling (i.e., dots) shows regions where the projected change is large compared to natural internal variability and where at least 90% of models agree on the sign of change. Hatching (i.e., diagonal lines) shows regions where the projected change is less than one standard deviation of the natural internal variability

these indirect impacts are usually connected to human activities. Similarly, evapotranspiration also directly influences groundwater recharge and indirectly determines groundwater pumping by crop water demand. Previous studies in the NCP focused on the influence of projected evapotranspiration on future crop water demand and crop yield (Tao and Zhang 2013; Xiao et al. 2020; Xiao and Tao 2016). Hardly any model takes into account the decrease of plant transpiration due to the impact of CO2 on stomatal conduction, which also modifies estimates of irrigation water demand (Guo et al. 2010).

While an increase in transpiration will decrease recharge and instigate more pumping due to higher plant water demand, there are three mechanisms, which in other regions of the world have shown to increase groundwater recharge: The first is the increase in extremes such as strong rainfall events (Fischer and Knutti 2019). Recharge is not a linear function of rainfall. While small rain events may give zero recharge, large events lead to over-proportional recharge. The second is the decrease of average wind with global warming. As reported above, this trend has been observed in China over the last decades. If it continues, it will reduce the expected increase in evapotranspiration due to temperature increase. The third mechanism is due to the increase of winter precipitation also quoted from literature above. At warmer winter temperatures, the soil freezing depth will be reduced and more recharge will occur in the cold season when evaporation is low, especially when there is thawing snow.

To get a coherent picture for the trends in evapotranspiration and the resulting crop water demand, we did our own assessment. The results presented in Box 5.4 show that overall, the crop water deficit will increase by mid-century and increase even further by late century. The compensation by decreasing wind speed as in the past decades is not seen anymore. That means the second mechanism mentioned above will most probably not be available.

Given all the interactions and assuming that total annual precipitation will not decrease, recharge will most probably not change much compared to today. But, due to more extremes both wet and dry, the use of the aquifer as a buffering device is of growing importance in the future.

The water resources availability in the NCP is not only determined by the development in the NCP itself. As the North in recent years relies increasingly on water imports from the South, the influence of climate change on the water availability in the catchment of the Han River and the Yangtze River in general is also a relevant influence factor.

### **References**

Cao L, Zhang Y, Shi Y (2011) Climate change effect on hydrological processes over the Yangtze River basin. Quat. Int. 244:202–210. https://doi.org/10.1016/j.quaint.2011.01.004

Box 5.4: Influence of climate change on crop water deficit

Chapter 5 in: Mukherjee A, Scanlon BR, Aureli A, Langan S, Guo H, McKenzie AA (eds), Global Groundwater. Elsevier, pp 65–71

**Open Access** This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

## **Final Remarks**

The solution of the NCP's water problems is determined by the balance of three big forces: the national requirement of grain security, the water resources system, and the agricultural system. Water authorities are in favor of water transfers while agricultural authorities are in favor of subsidized adaptation of the cropping system. However, there is no silver bullet. The solution of the NCP's water problems until 2050 and beyond consists of a mosaic of measures, which needs all available pieces to complete the puzzle. Some pieces are not easily recognized as contributors. China rightfully relaxed its requirements of grain self-sufficiency in recent years. Imported grain is imported virtual water. Grain imports of 99 Mio. tons in 2020 were at a record high compared to the local production of 670 Mio. tons. They make a non-negligible contribution to the alleviation of water scarcity as do the imports of meat of all kinds. Other pieces of the puzzle are for example irrigation with wastewater—after proper treatment—and seawater desalinization.

Actors should be encouraged to contribute their inventive share, hopefully avoiding the pitfalls existing in every method. They can all be guided by the value of irrigation water expressed in terms of a stiff water price. The government need not make people pay that price in every case. A tax and fee system makes only sense if it leads to a reduction of pumping, if not directly via farmers' profit optimization then by turning the revenue into subsidies to incentivize proven water saving methods in agriculture.

When discussing climate change, we looked at scenarios for 2035–2064 and for 2070–2099 (Sect. 5.5). If we look that far ahead, we also must look at other societal developments. Towards the end of the century, China's population will be half of that of today (see Box 5.2). Then water resources will easily get into equilibrium with demand, and management can concentrate on issues of water quality, for example salinity and pollution, which are probably the more serious long-term problems. For the coming 30 years, however, China still has to sustain or even increase the food production of today to satisfy the demands of her people. That implies that groundwater management in the NCP as outlined in this book will still be needed

W. Kinzelbach et al., *Groundwater Overexploitation in the North China Plain: A path to Sustainability*, Springer Water, https://doi.org/10.1007/978-981-16-5843-3

for a while to see China over the population peak before stress on water resources ceases towards the end of the century.

To conclude, we see the continued need of managing groundwater sustainably, avoiding not only over-pumping but increasingly deterioration of groundwater quality. If suitably managed, groundwater resources are cheap, readily accessible, and more importantly, provide a safeguard to buffer extremes under climate change.

## **Appendices: Technical Guides and Manuals of Tools**

Nine appendices are provided, containing more technical details on methods used, documentation of software and instructions for use and further development. They are listed below, together with the book chapters they refer to. The appendices can be downloaded from Springer's website.


Normative Mineralogy Especially for Shales, Slates, and Phyllites

*Hans Wolfgang Wagner*

## **Abstract**

First, an insight into normative mineralogy and the most important methods for calculating the standard or norm minerals, such as the CIPW norm, is given. This is followed by a more detailed explanation of "slatenorm" and "slatecalculation" for low and very low metamorphic rocks, such as phyllites, slates, and shales. They are particularly suitable for fine-grained rocks where the mineral content is difficult to determine. They enable the determination of a virtual mineral inventory from full chemical analysis, including the values of carbon dioxide (CO2), carbon (C), and sulfur (S). The determined norm or standard minerals include the minerals—feldspars, carbonates, micas, hydro-micas, chlorites, ore minerals, and quartz. The advantages of slatenorm and slatecalculation compared to other methods for calculating normal minerals of sedimentary rocks are discussed.

**Keywords:** slates, shales, phyllites, norm mineral calculation, CIPW, slatenorm, slatecalculation, micas, hydro-micas, illite, low- and very low-grade metamorphism

## **1. Introduction**

A norm or standard mineral inventory is a fictitious inventory that, in contrast to the modal and in fact mineral inventory, is calculated from the oxides of a chemical analysis of rock. Each oxide is then divided by its molecular weight. These molecular numbers are then the basis for further calculations (**Table 1**).

The results of the calculations are given as standard or norm minerals. They are given as abbreviations and mostly in small letters such as q (or qu) = quartz or mu = muscovite. The standard minerals each have a clearly defined chemical composition. This distinguishes them from some minerals in nature that have a more complex composition, such as pyroxenes, amphiboles, or chlorites. In these cases, simplifications or end links of a mixture series are used [1–3].

Usually, standard minerals are frequently occurring rock-forming minerals. Only in exceptional cases do you have to use minerals that occur only rarely or not at all in nature. The norm mineral inventory should come as close as possible to the actual, modal mineral inventory, which is not always possible [1–3].

The CIPW (Cross, Iddings, Pirsson, Washington) norm [4] is the most common method for magmatites. The Rittman norm for igneous rocks or the Niggli norm for igneous rocks and metamorphic rocks are less common.

*Mineralogy*

### **Table 1.**

*The full chemical analysis for standard mineral calculations.*

There are other methods for standard mineral calculations for sediments, such as SEDNORM [5], SEDMIN [6], PELNORM [7], and a linear program without a name (mainly for sandstones [8]).

The slatenorm and the slatecalculation norm are used for fine-grained sedimentary rocks and very low and low-grade metamorphic rocks, such as shales, slates, and phyllites [9]. As new methods, they are dealt with in great detail here.

## **2. CIPW norm**

The CIPW system is one of the best-known and best-elaborated chemical classifications of igneous rocks. It was developed as early as 1902. The CIPW system (CIPW norm) is based on a normative mineral inventory. This normative mineral inventory consists of a number of standard minerals (**Table 2**).

With them, groups of substances of chemical analysis are summarized and thus the quite complex chemistry of the igneous rocks is made clearer. As before, however, the CIPW standard plays a major role for the purpose of comparing the chemical properties.

The calculation of the CIPW standard is carried out according to a specified scheme. It can be found in a number of publications [3, 4]. Computer programs have also been developed since 1965 [10]. Several websites now offer online facilities for calculating CIPW [11, 12].

There are now numerous suggestions for improvement and additions to the CIPW standard. In particular, a standard method that is consistent with a rock classification as recommended by the International Union of Geological Sciences IUGS has proven to be necessary. There will be detailed step-by-step instructions for a standard igneous

### *Normative Mineralogy Especially for Shales, Slates, and Phyllites DOI: http://dx.doi.org/10.5772/intechopen.102346*

### **Table 2.**

*The standard minerals in the CIPW norm [1–3].*

norm (SIN) presented [13]. The review of the main computer programs for the classification of igneous rocks in the sense of the IUGS leads to the new program "Igneous Rock Classification System" (IgRoCS) [14].


*6.2. Sensitivity Analysis*

According to the assumptions above, *b* is the sensitivity of consumers to the price of agri-foods, while *k* is the sensitivity of consumers to the quality of agri-foods. By analyzing the sensitivity of *b* and *k*, the trend of the decision variables in the game model can be explored when the key parameters change.

### 6.2.1. Sensitivity Analysis on Consumer Price Sensitivity Factors

Based on the parameters above, the variation of each variable in the three models regarding the consumer price sensitivity factor *b* is explored. From Figure 1, it can be seen that the price compensation factor *α* and the quality of agri-foods *g* decrease with the increase of consumer price sensitivity factor *b*. The trend indicates that when consumers become more and more sensitive to the price of agri-foods, the selling price of agri-foods will decrease with the increase of consumer price elasticity in order to increase sales, and at the same time, agricultural producers will choose to reduce quality improvement inputs to reduce costs. However, in general, the centralized decision with the goal of maximizing the overall benefit of the supply chain is still the optimal strategy to realize the quality and price of agri-foods.

From Figure 2, it can be seen that the profit of the participants in the agricultural supply chain decreases as the price elasticity of demand *b* increases, and the overall profit of the supply chain under the centralized decision is the largest. Since the profit of sellers is relatively small under this set of parameters, the overall profit distribution of sellers in the supply chain is slightly lower than that of producers. When the quality of agri-foods is promoted by the seller, the seller gains more profit compared with the producer; i.e., the profit is inclined to the dominant players in the supply chain.

**Figure 1.** Variation of quality safety factor *g* and price compensation factor *α* with consumer price sensitivity factor *b*. (Variables with \* are the optimal variable values.)

**Figure 2.** Variation of profits of agricultural supply chain participants with consumer price sensitivity factor *b*. (Variables with \* are the optimal variable values).

6.2.2. Sensitivity Analysis on Consumer Quality Sensitivity Factors

Using the above parameters, the variation of each variable in the three models with respect to the consumer quality sensitivity factor *k* is analyzed. From Figure 3, it can be seen that with the increase of *k*, the price compensation factor *α* and quality safety *g* in the producer-driven Stackelberg game model are at the lowest level and do not change. However, the price compensation factor *α* and quality safety degree *g* in the seller-dominated Stackelberg game model and the centralized decision model are both on the rise. In the producer-dominated Stackelberg game model, producers dominate the quality safety degree *g,* and sellers dominate the price compensation factor *α*. The trend shows that with consumers' increasing care about the quality of agri-foods, producers are concerned that sellers will not compensate them for the cost of their efforts to improve quality. Therefore, in order to ensure their own maximum gain, producers will be stingy to increase the quality improvement input, which ultimately indicates that the producer is insensitive to the consumer's quality demand elasticity. In Model 2 and 3, when consumers pay more and more attention on the quality of agri-foods, sellers will incentivize producers to improve the quality of agri-foods by increasing the price compensation factor.

**Figure 3.** Variation of quality safety factor *g* and price compensation factor α with consumer quality sensitivity factor *k*. (Variables with \* are the optimal variable values).

As can be seen in Figure 4, the producer is insensitive to the quality elasticity of demand because the producer does not actually make quality improvements in Model 1. The maximum profit of the seller in model 2 and the total profit of the supply chain in model 3 increase with the increase of the quality elasticity of demand, and the profit of the producer decreases with the increase of the quality elasticity of demand. When the quality elasticity of demand reaches a certain threshold, if the price increase is not large, the producers of agri-foods will be unprofitable due to the high quality input cost.

From Figure 5, it can be seen that the actual market demand for agri-foods in models 2 and 3 decreases with the increase of consumer price sensitivity and diverges into two stages with the increase of quality sensitivity.

**Figure 4.** Variation of profit of agricultural supply chain participants with consumer quality sensitivity factor *k*. (Variables with \* are the optimal variable values).

**Figure 5.** Variation of real market demand *d* with consumer price sensitivity factor *b* (**A**) and quality sensitivity factor *k* (**B**) (Variables with \* are the optimal variable values).

In the first stage, when the price sensitivity of consumers is very low, the actual market demand in the centralized decision model is the lowest, followed by the game model dominated by producers, and finally the game model dominated by sellers. The second stage is when the quality sensitivity of consumers reaches a certain value, the actual market demand in the centralized decision model starts to exceed the actual market demand in the decentralized decision model with the increase of quality sensitivity.

This indicates that when consumers are not sensitive to the quality of agri-foods, low-quality agri-foods sell better. When consumers are more and more concerned about the quality of agri-foods, the "high-quality and high-priced" produce sells better.

### *6.3. Analysis of Other Parameters*

### 6.3.1. The Impact of Agricultural Selling Prices on Profits

The above parameters were also used to analyze the profit changes of supply chain participants when the retail price gradually increases from 5 to 10, and the results are shown in Figure 6A. As can be seen from the figure, the profit of sellers increases with the increase of selling price of agri-foods, while producers' profit increases first and then decreases with the increase of selling price. With the increase of unit value of agri-foods, supply chain profit gradually inclines to sellers.

**Figure 6.** Variation of profits of supply chain participants with agricultural sales price *p*0 (**A**) and wholesale price *w*0 (**B**). (Variables with \* are the optimal variable values).

Considering that the profit of sellers in the original parameters is low, in order to observe the change of profit of supply chain participants with the wholesale price of agrifoods, the retail price is assumed to be 10. When the wholesale price increases from 3 to 8, the change of profit of supply chain participants is shown in Figure 6B. From the figure, it can be seen that with the increase of wholesale price, the profit of sellers gradually decreases, and the profit of producers first increases and then decreases. The total profit of the centralized decision supply chain is the largest, mainly related to parameters such as total regional sales volume rather than prices.

### 6.3.2. The Impact of Cost-Sharing Factor

According to Proposition 8, the parameters *k* = 1 and *b* = 0.375 are reset to observe the changes of some variables, such as the quality of agri-foods, the level of price subsidy, and the profit of supply chain participants with the sharing coefficient *β*, under the costsharing contract. The results are shown in Figure 7. It is easy to find from Figure 7A that the adoption of cost-sharing contracts can significantly improve the quality of agri-foods, and also the price subsidy level is lower than that before the introduction of cost-sharing contracts, which means that the price of agri-foods is more "high-quality and low-price" at this time. From Figure 7B, it can be seen that as the cost-sharing coefficient of sellers increases, the supply chain profit keeps shifting to producers. The producer and seller can achieve the same profit at a specific moment.

**Figure 7.** Variation of the main parameters (**A**,**B**) of the supply chain with the sharing ratio *β* after the introduction of the cost-sharing contract. (Variables with \* are the optimal variable values).


**4. Discussion**

It is necessary to bear in mind that the mapping assessment was based on the surveyed calibration/validation rectangles (see Figure 1b). The use of a reliable and detailed groundtruth image is important for providing a comprehensive estimation of the area, thus preventing misclassifications detected by visual discrepancies as seen for the roof class rectangles that were mapped into the sea.


**1. Introduction**

The mathematical modeling using the advanced applied packages of computational fluid dynamics is an efficient tool for predicting various man-made and natural phenomena. The water flood of the regions and settlements takes the first place among natural spontaneous cataclysms in terms of the repetitions, extension area and annual material damage.

In this chapter, the problem of the prediction of consequences of a large-scale man-made disaster caused by the dam break is posed by the example of the Papan (near the Osh town, Kyrgyzstan) and Andijan (Uzbekistan) reservoirs.

The adopted mathematical model is presented in Section 2. The general technology of the numerical solution of the adopted mathematical model, the initial and boundary conditions, the model discretization methods are presented in Section 3. Section 4 contains the results of verifying the package OpenFOAM by various dam break test cases. Finally, the examples of using the OpenFOAM package for modeling the breaks of the dams of the Papan and Andijan reservoirs are considered in Section 5.


*3.2. Statistical Methods*

A two-stage research procedure was used to study the relationship between indicators describing the degree of implementation of Goal 7 of the 2030 Agenda and Green growth strategy regarding the economy's environmental and resource productivity. At the first stage, synthetic measures were calculated based on the indicators in each area concerned, which allowed ordering the studied countries in terms of their performance. The TOPSIS method was used to determine synthetic measures. A detailed description of this method and examples of its application can also be found in the papers [78–86]. This method is often used in the literature to study customer preferences [78–82]. There are also a growing number of its application in research on the level and directions of regional development [84–86]. Its main advantage is the ability to determine the distance from the so-called pattern and the anti-pattern of development, enabling not only to study the similarity of development in relation to the pattern but also to identify objects similar to the so-called anti-pattern. It appears, which is also confirmed by the results of the research presented in this paper, that a large distance of an object from the pattern (in this case, a country) does not mean a high similarity to the so-called anti-pattern. This observation is important for determining the paths of development of the studied objects within the scope of the studied phenomenon or for comparing objects between one another.

The basis of linear ordering is a synthetic measure whose values are estimated based on observations of diagnostic variables describing the examined objects. TOPSIS is a computational technique that belongs to a group of reference methods for which there are two reference points for objects in multidimensional space, i.e., a pattern and an antipattern. The final result of the analysis is a synthetic indicator that creates a ranking of the surveyed objects (in this case, countries). The best object is considered the one with the shortest distance from the pattern and, at the same time, the longest from the anti-pattern.

The determination of synthetic measure in the TOPSIS method is as follows [78,79]:

1. Normalization of variables:

$$z\_{ij} = \frac{\mathbf{x}\_{ij}}{\sqrt{\sum\_{i=1}^{n} \mathbf{x}\_{ij}^{2}}} \tag{1}$$

2. Determination of the coordinates of the *z*+0*j* pattern and the distance of objects from it *d*+*i*0:

*z*+0*j* = ⎧⎪⎪⎨⎪⎪⎩ max *i zij* for stimulant variables min *i zij* for destimulant variables *d*+*i*0 = *m*∑*j*=1*zij* − *z*+*ij* 2 (2)

3. Determination of the coordinates of the *z*−0*j* anti-pattern and the distance of objects from it *d*−*i*0:

$$z\_{0j}^- = \left\{ \begin{array}{c} \underbrace{\min\limits\_{i}\{z\_{ij}\}}\_{i} \text{ for estimated variables} \\ \underbrace{\max\limits\_{i}\{z\_{ij}\}}\_{i} \text{ for destination variables} \end{array} \, d\_{i0}^- = \sqrt{\sum\_{j=1}^m \left(z\_{ij} - z\_{ij}^-\right)^2} \tag{3}$$

4. Determination of the synthetic measure:

$$\eta\_i = \frac{d\_{i0}^-}{d\_{i0}^+ + d\_{i0}^-} \,\prime \tag{4}$$

with: *qi* ∈ [0; 1], max *i*{*qi*}—best object, min *i*{*qi*}—worst object.

	- • Group I: *qi* ≥ *q* + *Sq*, containing objects (countries) with the highest values of the synthetic measure;
	- • Group II: *q* + *Sq* > *qi* ≥ *q*;
	- • Group III: *q* > *qi* ≥ *q* − *Sq*;
	- • Group IV: *qi* < *q* − *Sq*, containing objects (countries) with the lowest values of the synthetic measure.

The second stage was devoted to examining the relationship between the results obtained in the two areas analyzed. The first step is to set linear correlation coefficients: *r* Pearson (for the value of synthetic measures) and *τ* Kendall (for the positions occupied by the studied countries), describing the dependencies between the determined measures and the results obtained by individual countries [83–89]. The results allowed examining the relationships between the analyzed areas and, importantly, identifying countries where the assumed objectives of the green economy supporting sustainable development are being achieved.

More advanced statistical analysis methods were used to study the relationships between the analyzed areas. The research used a multicriteria taxonomy described in the literature [90–92]. The mathematical algorithm of this method takes place in several stages. A detailed description of this method can be found in [93,94]. The first step requires a transformation of each indicator utilized in the analyses. The paper proposes that the clustering of countries should be carried out using the distances from the pattern in the TOPSIS method (*z*+0*j*) and the anti-pattern (*z*−0*j*), which replaces the normalized values of indicators used as a standard for this method. This approach allows countries to be grouped by their similarity in the distance to the pattern (the best object) and the similarity of distance to the anti-pattern (the worst object). In this paper, these distances are defined as baseline distances. The matrices containing information about the baseline distances determined for each indicator analyzed were used to determine two final distance matrices **DP** (based on distance from the pattern) and **DAP** (based on distance from the anti-pattern). Euclidean distance was used for this purpose. In the next step, based on the values in the

distance matrices, a threshold values *di* should be defined. The following formula can be utilized for this purpose:

$$d^{\vec{i}} = \min\_{\vec{i}} \max\_{\vec{j}} \{ d\_{\vec{i}\vec{j}} \} \tag{5}$$

The transformation of the **DA** and **DAP** distance matrices is carried out. For each indocator, the affinity matrix of (*n* × *n*) dimension is defined. The elements of this matrix: *cKij*(*i*, *j* = 1, . . . , *n*) are equal to:

$$c\_{i\bar{j}}^K = 1 \text{ for } d\_{i\bar{j}} \le d \tag{6}$$

$$x\_{i\bar{j}}^K = 0 \text{ for } d\_{i\bar{j}} > d \tag{7}$$

If inequality (6) is satisfied, the objects designated as *i* and *j* are treated as similar. In opposite, if inequality (7) is satisfied, the analyzed objects are deemed as dissimilar. In the second case, the affinity measure of *cij* is equal to zero. Finally, **CA**(*n*×*n*) and **CAP**(*n*×*n*) affinity matrices are determined. In this case, the following formula is applied in which *cijl* elements of these matrices are equal to the product of relevant elements of **CA** and **CAP** matrices for all the analyzed indicators:

$$c\_{i\bar{j}l} = \prod\_{K=1}^{r} c\_{i\bar{j}}^{K} \tag{8}$$

If *cij* = 1(*i*, *j* = 1, . . . , *n*), it means that each of *cKij* elements corresponding to it in **CK** matrices is equal to one, and if *cij* = 0, if one of the *cKij* elements corresponding to it are equal to zero.

Two analyzed objects (in the paper two countries) are considered to be similar to one another simultaneously on account of all the criteria if they are similar to one another separately on account of those criteria individually. Two objects are treated as dissimilar on account of all the examined criteria if they are not similar to one another, even in terms of one of such criteria. According to this assumption, sometimes it is challenging to find many similar objects in terms of every analyzed indicator.

In the following step, the analyzed objects are divided into typological groups. In the paper, for this purpose, the vector elimination method [87] is used. The procedure in this method, as in the multicriteria taxonomy, involves several stages. In the first step, the final **C**(*n*×*n*) affinity matrix is transformed into a **C\***(*n*×*n*) dissimilarity matrix. Next, based on **C\*** matrix, the *c*0 column vector is estimated with *n* components. In the second step, the row is eliminated from **C\*** matrix along with a corresponding column for which the*c*0 vector component has a maximum value. If the*c*0 vector contains several components whose value reaches the maximum, such a row and column are eliminated. The second step of the procedure is repeated until the*c*0 vector components are equal to zero. To the first sub-group, objects corresponding to the rows and columns that were not crossed off and remain in **C\*** matrix were assigned.


*Article* **A Microfluidic Platform Revealing Interactions between Leukocytes and Cancer Cells on Topographic Micropatterns**

**Xin Cui 1,\*,†, Lelin Liu 2,3,†, Jiyu Li 2,†, Yi Liu 2, Ya Liu 4, Dinglong Hu 4, Ruolin Zhang 5,6, Siping Huang 2, Zhongning Jiang 2, Yuchao Wang 2, Yun Qu 2, Stella W. Pang 5,7 and Raymond H. W. Lam 2,7,8,9,\***

	- 4 BGI-Shenzhen, Shenzhen 518083, China

**Abstract:** Immunoassay for detailed analysis of immune−cancer intercellular interactions can achieve more promising diagnosis and treatment strategies for cancers including nasopharyngeal cancer (NPC). In this study, we report a microfluidic live−cell immunoassay integrated with a microtopographic environment to meet the rising demand for monitoring intercellular interactions in different tumor microenvironments. The developed assay allows: (1) coculture of immune cells and cancer cells on tunable (flat or micrograting) substrates, (2) simultaneous detection of different cytokines in a wide working range of 5–5000 pg/mL, and (3) investigation of migration behaviors of mono- and co-cultured cells on flat/grating platforms for revealing the topography-induced intercellular and cytokine responses. Cytokine monitoring was achieved on-chip by implementing a sensitive and selective microbead-based sandwich assay with an antibody on microbeads, target cytokines, and the matching fluorescent-conjugated detection antibody in an array of active peristaltic mixer-assisted cytokine detection microchambers. Moreover, this immunoassay requires a low sample volume down to 0.5 μL and short assay time (30 min) for on-chip cytokine quantifications. We validated the biocompatibility of the co-culture strategy between immune cells and NPC cells and compared the different immunological states of undifferentiated THP-1 monocytic cells or PMA-differentiated THP-1 macrophages co-culturing with NP460 and NPC43 on topographical and planar substrates, respectively. Hence, the integrated microfluidic platform provides an efficient, broad-range and precise on-chip cytokine detection approach, eliminates the manual sampling procedures and allows on-chip continuous cytokine monitoring without perturbing intercellular microenvironments on different topographical ECM substrates, which has the potential of providing clinical significance in early immune diagnosis, personalized immunotherapy, and precision medicine.

**Keywords:** live-cell immunoassay; topographic micropatterns; on-chip cytokine detection; nasopharyngeal cancer; integrated microfluidics