**1. Introduction**

The flow number (*N*) is an empirical way of characterizing a hot-mix asphalt (HMA) mixture's rutting potential. To determine the flow number, a cyclic load in haversine form is applied on a cylindrical specimen axially as shown in Figure 1. The duration of the load pulse is 0.1 s, followed by a rest period of 0.9 s. The permanent axial deformation measured at the end of the rest period is monitored during repeated loading, and the strain is calculated by dividing by the initial gauge length. The test may be conducted with or without confining pressure. However, if confining pressure is used, it is kept constant while the flow number is tested. If confining pressure is used, it remains constant during the test.

**Figure 1.** Flow number test setup.

In the flow number test, the permanent strain at each cycle is measured while constant deviator stress is applied at each load cycle on the test sample. Permanent deformation of asphalt pavements has three stages [1]: (i) primary or initial consolidation; (ii) secondary; and (iii) tertiary or shear deformation.

Figure 2 shows the three stages of permanent deformation. The first stage of deformation is due to the initial filling of voids, particle rearrangement, etc. The second region is the actual deformation of the aggregates, asphalt film, etc. The tertiary region is the zone where drastic shear failure of the mix occurs. The *N*-value is the number of load cycles at which tertiary flow begins, i.e., where permanent deformation occurs non-linearly. Tertiary flow can be differentiated from secondary flow by a marked departure from the linear relationship between cumulative strain and number of cycles in the secondary zone, as shown in Figure 2. It is assumed that in tertiary flow, the specimen's volume remains constant. The *N*-value can be correlated with rutting potential. The higher the flow number, the better the mix is in terms of its rutting resistance.

**Figure 2.** Relationship between permanent strain and number of load cycles [1].

Mathematically, the *N*-value can be determined using the Francken model.

The Francken model is currently built into the Asphalt Mixture Performance Tester (AMPT) software (Federal Highway Administration, Washington DC, USA). At the beginning, the entire permanent strain curve is fitted using nonlinear least squares optimization, as shown in Equation (1). The flow number is then determined from the second derivative of the best fitted curve. The flow number is the number of cycles where the second derivative, Equation (2), changes from negative to positive.

$$
\varepsilon\_P = A \left( n^B \right) + \mathcal{C} \left( \varepsilon^{Dn} - 1 \right),
\tag{1}
$$

where ε*p* is the permanent strain (%); *n* is the number of cycles; and *A*, *B*, *C*, and *D* are fitting parameters.

$$\frac{d^2\varepsilon\_p}{dn^2} = AB(B-1)n^{B-2} + CD^2\varepsilon^{Dn},\tag{2}$$

where *d*2ε*p dn*2 is the second derivative of permanent strain with respect to the number of loading cycles.

The final evaluation is an evaluation of the rutting resistance of the mixture using the flow number test defined by the American Association of State Highway and Transportation Officials (AASHTO) TP 79 [2] using the AMPT. The test is conducted at the "high" pavement temperature calculated by the long-term pavement performance (LTPP) Bind 3.1 software program (Federal Highway Administration, Washington DC, USA) for a specific project location. An unconfined flow number test with a repeated deviatoric stress of 600 kPa (87 psi) and a contact deviatoric stress of 30 kPa (4.4 psi) was used in this study. The test was conducted on specimens that were short-term conditioned for two hours at the compaction temperature to simulate the binder absorption and stiffening that occurs during construction. The flow number criteria for HMA as a function of the traffic level are summarized in Table 1.

**Table 1.** Flow number criteria for hot-mix asphalt (HMA) [2].

The effects of different mix factors on the flow number have also been studied by different researchers [3–6]. Kaloush [3] determined that the flow number increases with the viscosity of binder and decreases with the test temperature, effective binder content, and air voids. Kvasnak et al. [4] determined that the flow number increases with gyrations and the viscosity of the binder and decreases with voids in mineral aggregates (VMA) when using Wisconsin dense graded mixtures. Both researchers determined that aggregate gradation also affects the flow number. Christensen [5] applied various statistical techniques to relate the flow number with the applied stress level and observed that the flow number decreases with increasing applied deviator stress. Rodezno et al. [6] determined that the flow number increases with the viscosity of the binder; however, it decreases with the test temperature and air voids and is affected by aggregate gradation. The current study was not intended to investigate the viscosity of the binder or the test temperature. Other factors such as the VMA, voids filled with asphalt (VFA), effective binder content, contractors, testing time, mix gradation, and binder types were investigated. There are some other researches on flow number. For example, Irfan et al. [7] evaluated the flow numbers for static and dynamic creep tests and then correlated it with the rutting. Ogundipe [8] studied the flow numbers of lime-modified asphalt concrete. Irfan et al. [9] investigated the flow numbers of fiber-added stone mastic asphalt concrete mixtures. Leiva-Villacorta et al. [10] evaluated the flow numbers for High-modulus asphalt concrete (HMAC) mixtures for use as base course. Tripathi [11] studied the economic benefits of fiber-reinforced asphalt mixtures by flow number including some other tests. Ziari and Divandari [12] developed a flow number prediction model using artificial neural network. Siswanto et al. [13] investigated the flow numbers of Asphalt Concrete Using Crumb Rubber Modified of Motorcycle Tire Waste. All these studies investigated the flow number

under different conditions. However, none of the studies investigated the sensitivity of different mix factors such as such as VMA, void-filled with asphalt (VFA), effective binder content, contractors, testing time, mix gradation, and binder types on the flow number of asphalt concrete.

Air void (*Va*) is the total volume of the small pockets of air between the coated aggregate particles expressed as a percentage of the bulk volume of the compacted mixture. The volume of the void space among aggregate particles of a mixture that includes the air voids and the effective asphalt content is known as VMA. The portion of the voids in the mineral aggregate that contain asphalt binder is known as VFA. The total asphalt binder content of the mix less the portion of asphalt binder that is lost by absorption into the aggregate is called the effective asphalt content (*Vbe*). This portion of binder is coated on the aggregate surface and takes part in binding aggregates. The total asphalt binder used in a mix is called the asphalt content (AC).

The flow number (*N*) test procedure recommended in the National Cooperative Highway Research Program (NCHRP) project 9-19 is a simple performance test for rutting evaluation of asphalt mixtures. The test showed good correlation with the rutting performance of mixtures at WesTrack, MnROAD, and the Federal Highway Administration's (FHWA's) accelerated loading facility. Subsequent NCHRP studies allowed the development of a provisional standard. AASHTO TP 79 [2] includes test parameters for stress, temperature, specimen conditioning, and minimum flow number criteria that were established for HMA and for warm-mix asphalt (WMA) based on the traffic level.

The current study used the testing conditions and criteria for *N* testing described in AASHTO TP 79 [2] for unconfined tests. The recommended test temperature, determined by LTPP Bind Version 3.1 software, was the average design high pavement temperature at 50% reliability for cities in Colorado. Tests were conducted at a temperature of 55 ◦C with an average deviator stress of 600 kPa (87 psi) and a minimum (contact) axial stress of 30 kPa (4.4 psi). For conditioning, samples were kept in a conditioning chamber at the testing temperature for 12 h prior to testing.

To confirm again, the objectives of this study were to study the effects of mix factors such as VMA, VFA, effective binder content (*Vbe*), contractors, testing time, mix gradation, and binder types on the flow number of asphalt concrete.

#### **2. Materials**

The eleven types of mixtures studied are listed in Table 2 along with their basic information such as nominal maximum aggregate size (NMAS), performance grade (PG) binder type, and number of gyrations used while designing the mixes. Superpave performance grading is reported using two numbers: the first being the average seven-day maximum pavement temperature (◦C) and the second being the minimum pavement design temperature likely to be experienced (◦C). Thus, a PG 64-22 is intended for use where the average seven-day maximum pavement temperature is 64◦C and the expected minimum pavement temperature is −22◦C. The letter "S" denotes an NMAS of 0.75 in. (19 mm). The letters "SX" denote an NMAS of 0.5 in. (12.5 mm). SMA is the abbreviated form of the stone mix asphalt mixture. The numbers in parentheses are the numbers of gyrations used in the mix design. All the mixes were designed following the Superpave requirements for all parameters. Every group of mixes had identical aggregate gradations.

**Table 2.** A list of the eleven mixtures used in this study

S = NMAS of 0.75 in. (19 mm); SX = NMAS of 0.5 in. (12.5 mm); SMA = stone mix asphalt mixture.

#### **3. E**ff**ects on the Flow Number**

#### *3.1. Same Mix by the Same Contractor*

To investigate the variation in the flow number within the work of a single contractor for the same mix, the following mixes were selected randomly. The information regarding the paving contractor, binder supplier, and aggregate pits is kept confidential. The mixes were manufactured in 2014.

The N-values vary from 120 to 531 with an average value of 261 and standard deviation of 125, as shown in Figure 3. The values shown are for each individual specimen. To determine whether these data are statistically significant or not, a one-sample t-test was conducted. The t-test requires the data to be normally distributed. The t-test showed the 95% Confidence Interval (CI) boundaries to be 150 and 372 with a mean value of 261. This means that all the mixes, except for 19655 P21 14 and 19655 P87 14, are statistically the same. Therefore, a conclusion can be made that the same mix may have statistically different flow numbers for the same contractor. Note that Colorado Department of Transportation (CDOT) uses a 10-digit format to express the mix identity, such as 19655 P21 14. The first five numbers denote the project and the last five digits denote the site and specimen number.

#### *3.2. Same Mix by Di*ff*erent Contractors*

To investigate the differences in flow number for the same mix prepared by different contractors, SX(100) PG 76-28 mix was selected. The average flow numbers from four contractors, 19128, 18842, 19458, and 19677, are presented in Figure 4.

**Figure 4.** Flow numbers of a mix by different contractors.

The pairwise comparison test result shows that the mixes by 19128, 18842, and 19458 are statistically the same (Table 3). Therefore, a conclusion can be made that the same mix may have statistically different flow numbers for different contractors. This is due to variations in the aggregate structures, shapes, orientation, smoothness, etc.

**Table 3.** Pairwise comparisons using *t*-tests to determine statistical difference.

#### *3.3. Groupwise Comparison*

The flow number variation for each group of mix is described in this section. An effort was made to examine whether all specimens' flow numbers were statistically equal or not. A 95% Confidence Interval (CI) was used to indicate reliability. Next a statistical regression analysis was conducted to find the effects of different mix factors.


**Conflict of interest**

The authors declare that they have no conflicts of interest to disclose.

**141**

**Author details**

Natalia Shnayder1

Russian Federation

and Evgeniy Erakhtin3

St Petersburg, Russian Federation

Krasnoyarsk, Russian Federation

provided the original work is properly cited.

, Ekaterina Narodova2

\*Address all correspondence to<EMAIL_ADDRESS>
© 2018 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,

1 V.M. Bekhterev National Medical Research Center of Psychiatry and Neurology,

3 N.S. Karpovich Krasnoyarsk Interdistrict Clinical Hospital of Emergency Care,

2 Professor V.F. Voino-Yasenetsky Krasnoyarsk State Medical University,

\*, Valeriya Narodova2

, Andrey Narodov2

*The Role of Nondrug Treatment Methods in the Management of Epilepsy*

*DOI: http://dx.doi.org/10.5772/intechopen.81912*

*The Role of Nondrug Treatment Methods in the Management of Epilepsy DOI: http://dx.doi.org/10.5772/intechopen.81912*


**1. Introduction**

In line with the Measurement Protocol for Water Meters in the Republic of Serbia, a water meter is declared unreliable for water volume measuring at flow rates lower than Qmin [1-3]. For a 20 mm rated diameter water meter, used in the households of this country, the mini‐ mum flow is about Qmin=0.016-0.060 m3 /hour. Therefore, water volume is measured unrelia‐ bly due to leakage at the tap, with a flow of 0.003-0.007 m3 /h (drop by drop) and 0.010-0.016 m3 /h (jet), at the bathroom tap at 0.010-0.014 m3 /h (in a very thin jet), and at the toilet tank at 0.004-0.025 m3 /h. As a solution to this problem, the installation of impulse valve, unmeas‐ ured-flow reducer, known as UFR, at the water meter is recommended since 2007.

UFR operates based on the difference between the upstream and downstream pressure of 0,4 bar at the valve. For pressure lower than the declared, the UFR closes flow through the water meter, since the spring force is stronger than the force generated by the difference in upstream and downstream pressure. Due to water losses through pipeline leakage, the dif‐ ference in pressure exceeds the limit value, hence the UFR opens, providing flow at a rate of at least Qmin which is then registered by the water meter. UFR manufactured by A.R.I. from Jerusalem is used for adjusting water volume measuring at flow rates lower than 0.026 m3 /h.

The papers published so far refer to measurements obtained on individual water meters and on segments of pipelines.

Operation of 33 water meters with UFR was tested in a calibration laboratory in Udine (Ita‐ ly) [5]. The water meters had a rated diameter of 20 mm, class C, Qmin=0.025 m3 /h, each 1 to 7

© 2013 Hovany; licensee InTech. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2013 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

years old. In joint operation of water meters with URF a higher water volume was meas‐ ured: it was 94% in cases of stagnating water meter propellers, 31.8% for flow rates at the commencement of the propeller rotation (further designated as Qa) and 14.4% for Qmin. The valve's most significant contribution was defined for flow at water meter propeller still‐ stand. Due to the characteristics of water meters installed in the Republic of Serbia, a similar research is necessary for water meters with 0.025 m3 /h<Qmin<0.060 m3 /h.

measuring. During the operation with URF a higher water consumption was measured: 10.4% for July 2008, 9.5% for August 2008, 4.9% for September 2008, 11.9% for October 2008, 7.6% for November 2008, 8.9% for December 2008, 3.9% for January 2009, 8.4% for February

Error in Water Meter Measuring Due to Shorter Flow and Consumption Shorter Than the Time...

Two balancing were made on a part of the supply network with 52 water meters in Palermo: from October 24 through November 14, 2008 without UFR and from December 12, 2008 through January 9, 2009 with UFR [10]. The water meters with 15 mm rated diameter were either 11 years old (33, class C) or older (17 of class B and 2 of class A). During the operation with UFR, the measured volume of consumed water was higher for 28.06-18.91=9.15%.

The use of UFR facilitates the measuring of water consumption at flow rates lower than Qmin.

and that water consumption exceeds Qmin, a water supply network for a single household was set up in the Hydraulic Laboratory of the faculty of Civil Engineering in Subotica. The aim of the test was to confirm the contribution of UFR in measuring water volume by water

ARI from Jerusalem manufactures UFR with 20 mm rated diameter in three types, designed T10, T20 and T30. Thus, conclusions of testing with valve type T30 could also be controlled

> **Class Water Discharged Permitted Time between discharge water error two**

A Qmin=0.06 10 5 0.5 10

B Qmin=0.03 5 5 0.25 10

A Qmin=0.1 20 5 1 12

B Qmin=0.05 20 5 1 24

**Table 1.** Water volume and calibrated time of water meter of 20 mm rated diameter in the function of typical flows

**m3/h litres ±% ± litres minutes**

Qt=0.15 25 2 0.5 10 Qn=1.5 100 2 2 4

Qt=0.12 25 2 0.5 12.5 Qn=1.5 100 2 2 4

Qt=0.25 30 2 0.6 7.2 Qn=2.5 100 2 2 2.4

Qt=0.2 25 2 0.5 7.5 Qn=2.5 100 2 2 2.4

/h<Qmin<0.060 m3

**volume limit readings**

/h.

http://dx.doi.org/10.5772/51046

/h

133

By fulfilling the condition, that the flow of supply network water losses is below 0.026 m3

2009 and 11.6% for March 2009.

by valve types T10 and T20.

and water meter class.

meter with 20 mm rated diameter and flow of 0.026 m3

**Figure 1.** Structure of the UFR- manufactured by A.R.I. from Jerusalem (Israel) [4] 1 - flow direction, 2 - UFR plug, 3 - UFR spring.

Tests were made on parts of the water distribution pipeline in Jerusalem, Larnaca (Cyprus), on Malta, in Kingston (Tennessee, USA) and in Palermo (Italy). Each testing has been carried out with two water balancing: one with and another without UFR in operation. By compar‐ ing the results of the balancing obtained for the mentioned statuses, the contribution of UFR to measuring water volume by water meter was determined.

Testing was also implemented in Jerusalem from March 2005 in a duration of 14 months (8 months without UFR and 6 months with UFR) on two systems, where the first comprised 120 and the second 360 water meters [4, 6]. The used class B water meters were with the fol‐ lowing characteristics: Qa=0.012 m3 /h, Qmin=0.050 m3 /h and nominal flow Qn=2.5 m3 /h. With the usage of UFR, the measured water volume was higher for 16.0-6.1=9.9% (on the system with 120 water meters) and for 26.0-18.8=7.2% (on the system with 360 water meters).

From October through December 2006, a water supply system with 280, class B and C water meters, age over 1-15 years was tested in Larnaca with weekly balancing [6]. The water vol‐ ume measured with UFR was higher for 19.58-9.66=9.92%.

Three tests were made on a system with 26 households on Malta [7-8]. The class D water meters with rated flow of 1 m3 /h were 5 years old in average. The time interval for water balancing was one week. The quantity of water measured by UFR on water meters was more for 26.7-21.2=5.5%, 28-22.2=5.8% and 18.1-12.1=6% than without the use of this valve.

UFRs were installed in a part of a supply network with 35 water meters in Kingston from June 6 to 10, 2008 [9]. The water meters (aged about 4 years) were calibrated prior to the measuring. During the operation with URF a higher water consumption was measured: 10.4% for July 2008, 9.5% for August 2008, 4.9% for September 2008, 11.9% for October 2008, 7.6% for November 2008, 8.9% for December 2008, 3.9% for January 2009, 8.4% for February 2009 and 11.6% for March 2009.

years old. In joint operation of water meters with URF a higher water volume was meas‐ ured: it was 94% in cases of stagnating water meter propellers, 31.8% for flow rates at the commencement of the propeller rotation (further designated as Qa) and 14.4% for Qmin. The valve's most significant contribution was defined for flow at water meter propeller still‐ stand. Due to the characteristics of water meters installed in the Republic of Serbia, a similar

**Figure 1.** Structure of the UFR- manufactured by A.R.I. from Jerusalem (Israel) [4] 1 - flow direction, 2 - UFR plug, 3 -

Tests were made on parts of the water distribution pipeline in Jerusalem, Larnaca (Cyprus), on Malta, in Kingston (Tennessee, USA) and in Palermo (Italy). Each testing has been carried out with two water balancing: one with and another without UFR in operation. By compar‐ ing the results of the balancing obtained for the mentioned statuses, the contribution of UFR

Testing was also implemented in Jerusalem from March 2005 in a duration of 14 months (8 months without UFR and 6 months with UFR) on two systems, where the first comprised 120 and the second 360 water meters [4, 6]. The used class B water meters were with the fol‐

the usage of UFR, the measured water volume was higher for 16.0-6.1=9.9% (on the system

From October through December 2006, a water supply system with 280, class B and C water meters, age over 1-15 years was tested in Larnaca with weekly balancing [6]. The water vol‐

Three tests were made on a system with 26 households on Malta [7-8]. The class D water

balancing was one week. The quantity of water measured by UFR on water meters was more for 26.7-21.2=5.5%, 28-22.2=5.8% and 18.1-12.1=6% than without the use of this valve.

UFRs were installed in a part of a supply network with 35 water meters in Kingston from June 6 to 10, 2008 [9]. The water meters (aged about 4 years) were calibrated prior to the

/h, Qmin=0.050 m3

with 120 water meters) and for 26.0-18.8=7.2% (on the system with 360 water meters).

/h<Qmin<0.060 m3

/h.

/h and nominal flow Qn=2.5 m3

/h were 5 years old in average. The time interval for water

/h. With

research is necessary for water meters with 0.025 m3

132 Water Supply System Analysis - Selected Topics

to measuring water volume by water meter was determined.

ume measured with UFR was higher for 19.58-9.66=9.92%.

lowing characteristics: Qa=0.012 m3

meters with rated flow of 1 m3

UFR spring.

Two balancing were made on a part of the supply network with 52 water meters in Palermo: from October 24 through November 14, 2008 without UFR and from December 12, 2008 through January 9, 2009 with UFR [10]. The water meters with 15 mm rated diameter were either 11 years old (33, class C) or older (17 of class B and 2 of class A). During the operation with UFR, the measured volume of consumed water was higher for 28.06-18.91=9.15%.

The use of UFR facilitates the measuring of water consumption at flow rates lower than Qmin.

By fulfilling the condition, that the flow of supply network water losses is below 0.026 m3 /h and that water consumption exceeds Qmin, a water supply network for a single household was set up in the Hydraulic Laboratory of the faculty of Civil Engineering in Subotica. The aim of the test was to confirm the contribution of UFR in measuring water volume by water meter with 20 mm rated diameter and flow of 0.026 m3 /h<Qmin<0.060 m3 /h.

ARI from Jerusalem manufactures UFR with 20 mm rated diameter in three types, designed T10, T20 and T30. Thus, conclusions of testing with valve type T30 could also be controlled by valve types T10 and T20.

**Table 1.** Water volume and calibrated time of water meter of 20 mm rated diameter in the function of typical flows and water meter class.

In line with the Measurement Protocol for Water Meters in the Republic of Serbia, a water meter for water consumption in households is qualified for operation with error below the permitted values, i.e. from ±5% (for Qmin) and ±2% (for Qn and Qt ) from the actual water vol‐ ume [11]. During calibration, water meter operation errors are checked for the foreseen wa‐ ter volumes.

Through this water volume and discharge, the time for which the meter is calibrated was calculated.

To eliminate the effects of opening and closing the flow switch to measuring errors during calibration, the standard in force in the Republic of Serbia stipulates the following: "The un‐ certainty introduced into the volume may be considered negligible if the times of motion of the flow switch in each direction are identical within 5% and if this time is less than 1/50 of the total time of the test" [12]. The same recommendations are given by other standards as well [13-14]. Based on that, the following is recommended: "Should there be doubts about whether the operation time of the valve affects the results of the tests, it is recommended that the tests should be made longer, and never under 60 seconds" [15]. That is to say, for neglecting the impact of flow switch manipulation on the water meter's measuring errors the standards offer a solution during the calibration of water meter only.

**Figure 2.** The test rig for water balancing by water maters on water supply system in the Hydraulic Laboratory of the Faculty of Civil Engineering in Subotica 1-3 - water meters, 4 - UFR, 5-8 - shut-off valve, 9 - storage tank, 10 - outlet pipe of water meter no. 3, 11 - balance with a bucket to measure the quantity of water flown through water meter

Error in Water Meter Measuring Due to Shorter Flow and Consumption Shorter Than the Time...

http://dx.doi.org/10.5772/51046

135

The elements of water balance in the rig were as follows: the volume of the inflow water (measured by water meter no. 1), legal consumption billed and measured (measured by wa‐ ter meter no. 2) and the total volume of water losses, which occurred due to the water me‐ ter's inaccurate measuring of flow rates lower than Qmin (measured by water meter no. 3).

The operation of the UFR was regulated by shut off valves no. 5, 6 and 7, for example, by

Water volumes flown through water meters no. 1, 2 and 3 were defined by the difference of two water meter readings. By measuring time (with stopwatch) between two readings, flows Q1, Q2 and Q3 were calculated by means of the defined water volume. The weight of the water flown through water meter no. 3 was measured by a bucket (16 litres) on a scale. The volume of the water was calculated by the density of the water measured by scale and

For the test rig for water balancing in a water supply system, new, calibrated multi-jet pro‐ peller water meters with wet mechanism were installed for water temperature of 30°C, and with rated diameter of 20 mm, class B, with the following typical flow rates: Qa<0.01 m3

The used UFR was manufactured by A.R.I. from Jerusalem, with a rated diameter of 20 mm, product type T30. It was installed upstream to water meter no. 3. In line with the manufac‐ turer's recommendation, in order to provide smooth operation of the UFR between water meter no. 3 and shut off valve no. 8, a 6 m long discharge pipe was installed (marked as no.

/h.

/h,

shutting down valves no. 5 and 6, the UFR was set out of operation.

/h and Qn=1.5 m3

no. 3.

measuring cylinder.

10 in the attachment).

/h, Qt

=0.12 m3

Qmin=0.03 m3

Water consumption in a single household is implemented by the use of taps, washing ma‐ chine, dishwasher-machine and shower in the bathroom, likewise the flushing cistern of the toilet and the like. Each consumption is characterised by the opening and closing of flow switch and the duration of water discharge from the pipeline in order to satisfy needs. The duration of consumption in households is shorter than 1 minute in 95% of consumption cas‐ es [16]. The error in measuring consumption by water meter, due to manipulating the flow switch, practically manifests as an error due to the duration of consumption shorter than the time the meter was calibrated for [17].

Owing to this fact, the primary aim of this paper is to define measuring errors of consump‐ tion shorter than 10 (for Qmin), 12.5 (for Qt ) and 4 minutes (for Qn) of class B water meter with 20 mm rated diameter and flow of Qn=1.5 m3 /h, installed in the water supply pipeline of a single household.

Water meter operation error depends on water meter reading accuracy [18]. The further aim of this paper is to define water consumption measuring error in households shorter than the time the meter was calibrated for, in the function of water meter reading accuracy.


**Yatong Wang, Yanhua Hou, Yifan Wang, Lu Zheng, Xianlei Xu, Kang Pan, Rongqi Li and Quanfu Wang \***

School of Marine Science and Technology, Harbin Institute of Technology, Weihai 264209, China<EMAIL_ADDRESS>(Y.W<EMAIL_ADDRESS>(Y.H<EMAIL_ADDRESS>(Y.W<EMAIL_ADDRESS>(L.Z<EMAIL_ADDRESS>(X.X<EMAIL_ADDRESS>(K.P<EMAIL_ADDRESS>(R.L.)

**\*** Correspondence<EMAIL_ADDRESS>Tel./Fax: +86-631-568-7240

Received: 13 September 2018; Accepted: 27 September 2018; Published: 1 October 2018

**Abstract:** L-*tert*-leucine and its derivatives are useful as pharmaceutical active ingredients, in which leucine dehydrogenase (LeuDH) is the key enzyme in their enzymatic conversions. In the present study, a novel cold-adapted LeuDH, *psleudh*, was cloned from psychrotrophic bacteria *Pseudoalteromonas* sp. ANT178, which was isolated from Antarctic sea-ice. Bioinformatics analysis of the gene *psleudh* showed that the gene was 1209 bp in length and coded for a 42.6 kDa protein containing 402 amino acids. PsLeuDH had conserved Phe binding site and NAD<sup>+</sup> binding site, and belonged to a member of the Glu/Leu/Phe/Val dehydrogenase family. Homology modeling analysis results suggested that PsLeuDH exhibited more glycine residues, reduced proline residues, and arginine residues, which might be responsible for its catalytic efficiency at low temperature. The recombinant PsLeuDH (rPsLeuDH) was purified a major band with the high specific activity of 275.13 U/mg using a Ni-NTA affinity chromatography. The optimum temperature and pH for rPsLeuDH activity were 30 ◦C and pH 9.0, respectively. Importantly, rPsLeuDH retained at least 40% of its maximum activity even at 0 ◦C. Moreover, the activity of rPsLeuDH was the highest in the presence of 2.0 M NaCl. Substrate specificity and kinetic studies of rPsLeuDH demonstrated that L-leucine was the most suitable substrate, and the catalytic activity at low temperatures was ensured by maintaining a high *k*cat value. The results of the current study would provide insight into Antarctic sea-ice bacterium LeuDH, and the unique properties of rPsLeuDH make it a promising candidate as a biocatalyst in medical and pharmaceutical industries.

**Keywords:** leucine dehydrogenase; cold-adapted; Antarctic bacterium; sea-ice; homology modeling


*2.3. Characterization*

The X−ray diffractometer (XRD, Ultima IV, Rigaku Corporation, Akishima, Japan) was selected to collect the diffraction patterns of materials using Cu Kα radiation (λ = 0.15406 nm, 40 KV, 1.64 mA) in the ranges of 10◦ to 80◦ of 2-theta angle. The morphologies of oxides were recorded with a scanning electron microscope (SEM, JSM-6010 PLUS/LA, JEOL Ltd., Tokyo, Japan). Elemental analysis of CuO/ZnO was examined using a JSM-7900F SEM attached with EDX. The chemical structures of CuO/ZnO were studied with a Fourier transform infrared (FTIR) spectrophotometer (IR Prestige-21, SHIMADZU, Kyoto, Japan).

## *2.4. Evaluation of Photocatalytic Activity*

The photocatalytic experimental conditions are presented in Table 1. Briefly, the photocatalytic performance of CuO/ZnO composites was investigated in aqueous MB solution using sunlight. Experiments were conducted under similar conditions on a sunny day between 11:00 and 14:00. In photodegradation, 20 mg of photocatalyst was added into 30 mL aqueous MB of 10 mg/L in the beakers. To equilibrate the suspension, a magnetic stirrer was used in the dark for 30 min. Then, the suspensions in the beakers were kept in sunlight for different time intervals. About 3 mL MB solution was withdrawn and separated with an Advantec membrane filter 0.45 μm. The MB concentration was calculated using a UV–visible spectrometry (UV-1700 Pharma Spec, SHIMADZU, Kyoto, Japan). The relative MB concentration (C/C0) was determined at the relative absorbance (A/A0) of λ = 662 nm, according to the Beer–Lambert law, where A0 and A were the absorbance of aqueous MB at a starting time (*t*0) of photodegradation and at any time t, respectively.

The total organic carbon (TOC) was studied using Shimadzu TOC analyzer (TOC–VCPH, Kyoto, Japan). The oxidation and titration with potassium permanganate method was applied for the measurement of chemical oxygen demand (COD).

**Table 1.** Experimental conditions.


*<IP_ADDRESS> Inorganic inhibitors*

The compounds such as As2O3, Sb2O3 have been reported as inhibitors in acid media. In this case, the protection is due to the reduction of electro positive ions and deposition on the metal surface and lowering of the over voltage of main cathodic depolarization reaction [38]. Recently it is shown that the addition of heavy metal ions such as Pb2+, Ti+ , Mn2+ and Cd2+ is found to inhibit corrosion of iron in acids.


**6. Conclusions**

In this paper, we present an effective classification framework by integrating the spectral, spatial, and hierarchical structure information into the SVM classifier in a way of multiple kernels. In this framework, the spectral kernel is constructed using directly the original HSI, the spatial kernel is modeled using the EMP method and the hierarchical kernel is introduced by combining the techniques of FMS and AMG-MHSEG. The main advantage of the proposed framework is to utilize spatial structure information in multiple scales for HSI classification. Experimental results on two benchmark HSIs confirmed the following conclusions: (1) The combination of the spectral, spatial and hierarchical kernels in the SVM-SSHK method can generate better classification results than using any single or double of these three kernels; (2) The SVM-SSHK method can achieve the most accurate classification results under different training sets, when compared to the popular kernel-based classification methods. Specifically, SVM-SSHK can be 0.02–15.24% and 0.08–15.61% higher than the other methods in average in the terms of OA for the IP and UP images, respectively; (3) SVM-SSHK can demonstrate stable classification performance in most cases of different parameter settings on the weights of the three kernels. In conclusion, the SVM-SSHK method is very promising for the improvement of classification of hyperspectral images. In the future, advanced studies will be performed by exploring more efficient SVMs with multiple kernels.

**Acknowledgments:** This work was supported by the National Natural Science Foundation of China (61271408). The authors would like to thank D. Landgrebe from Purdue University for providing the AVIRIS image of Indian Pines and the Gamba from University of Pavia for providing the ROSIS data set.

**Author Contributions:** Y.W. and H.D. implemented all the proposed classification method and conducted the experiments. H.D. finished the first draft, Y.W. supervised the research and contributed to the editing and review of the manuscript.

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


**X-Ray Digital Linear Tomosynthesis Imaging of Arthoroplasty**

Tsutomu Gomi1, Hiroshi Hirano2 and Masahiro Nakajima3 *1School of Allied Health Sciences, Kitasato University 2Department of Radiology, Shinshu University Hospital 3Department of Radiology, Dokkyo Medical University Hospital Japan*


**Acknowledgements**

M. B. M. T. acknowledges financial support (Master degree grant) from CONACYT. M. B. M. T. acknowledges Lilia Bautista from CIMAV Monterrey for their help with FT-IR and DLS, measurements and assistance, respectively. M. B. M. T acknowledges M.Sc. Lilia Torres from CIATEJ Noroeste for all the assistance. M. B. M. T acknowledges Ph.D. Guillermo Acosta and Q. Ashanti Rodríguez for their help with the analysis of the minimum inhibitory concentration (MIC) of the nanoemulsions. We acknowledge Frutech International Corporation for their donation of the citric essential oils.

**61**

**Author details**

Maira Berenice Moreno-Trejo1

Ángela Suarez-Jacobo2

provided the original work is properly cited.

Monterrey, Apodaca, Nuevo León, Mexico

A.C. Unidad Noreste, Apodaca, Nuevo León, Mexico

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

and Margarita Sánchez-Domínguez1

2 Centro de Investigación y Asistencia en Tecnología y Diseño del Estado de Jalisco,

1 Centro de Investigación en Materiales Avanzados S.C. (CIMAV) Unidad

\*Address all correspondence to<EMAIL_ADDRESS>
, Arturo Adrián Rodríguez-Rodríguez1

,

\*

*Development of Nano-Emulsions of Essential Citrus Oil Stabilized with Mesquite Gum*

*DOI: http://dx.doi.org/10.5772/intechopen.84157*