**5. Use Case Study**

To validate the presented voltage compensation algorithm, the longest branch of the IEEE 37 Node Test feeder [22] from Node 701–Node 741 was selected to simulate a mid-level distribution feeder branch with commercial loads. The transmission voltage level of 230 kV is transformed in distribution substation to 4.8 kV in the feeder. Different combinations of commercial building load profiles obtained from [23] were used as uncontrollable load of microgrids connected to each node. In addition to building loads, microgrids on node 702, 730, 708, 734, 738 and 741 had PEV chargers. Figure 5 shows the distribution grid topology of the use case. The building loads and the number of EVSEs under each node are listed in Table 1. A total of 120 EVSEs were installed in six microgrids to charge three types of PEVs. The PEV battery and charging parameters are listed in Table 2. The power factors of the building load and PEV charger were 0.95 and 0.98, respectively.

**Figure 5.** The distribution grid topology in the use case study.

**Table 1.** The building and number of EVSEs in microgrids.

**Table 2.** PEV battery and charging parameters [17].

We simulated the voltage compensation at 10:00 am and assumed that all the EVSEs were connected with PEVs. This resulted in 120 PEVs (31 Nissan Leaf 2013s, 20 BMW i3 2014s, and 69 Chevy Volt 2013s) in the simulation. These PEVs were randomly allocated to EVSEs. The initial and target SOCs of the PEVs were also randomly generated. Table 3 shows the uncontrollable load and maximal PEV charging power demand at 10:00 am. The variation and effect from other feeder branches are not considered. In addition, it was assumed that the grid was balanced, and the node loads were all connected to the same phase on the feeder branch.

One distribution voltage violation was simulated at Node 741 with 0.933 per unit when all microgrids chose to charge PEVs at maximum charging power. After all microgrids curtailed PEV charging power to critical point, the voltage violation still existed at Node 741 with 0.948 per unit. In this situation, a negotiation among the grid-level agent and microgrid agents to further curtail PEV charging power for the voltage compensation is triggered. Firstly, the voltage–load variation relationship coefficients were found to be coef = [0.2396, 0.4420, 0.7242, 1.0718, 1.1869, 1.3710, 1.5548, 1.8788, 2.2462, 2.4738, 2.6975, 2.9188], which were used as the grid voltage compensation reference. Each VGI microgrid wishes to retain a charging power close to its PEV critical charging power point. On the other hand, the grid-level agent wishes to compensate the voltage at Node 741 back to 0.9505 per unit. The negotiation process is shown in Figure 4.

**Table 3.** Uncontrollable load and PEV charging power demand at 10:00 am in each node along the distribution feeder branch.

Figures 6 and 7 show the selection of negotiation parameters, such as the penalty factor ρ and the proximal factor φ, and their effects on the residual convergence. It is shown in Figure 6 that a larger penalty factor ρ can accelerate the negotiation. However, the negotiation oscillates when the penalty factor exceeds a certain value. The introduction of a proximal term helps to improve the convergence of the negotiation process. Figure 7 shows simulation results for different values of the proximal factor φ when the penalty factor ρ = 0.2. It is observed that the proximal term enhances the possibility of convergence of the negotiation. However, an excessively large proximal factor results in divergence. After a number of simulations, an empirical conclusion was that it is relatively safe to choose a penalty factor that is smaller than 1 and a proximal factor that is 5–10 times larger than the penalty factor.

With the penalty factor, ρ = 0.2 and the proximal factor, φ = 1, the negotiation shows a fast convergence speed within 30 rounds. Figure 8 shows the update sequence of the microgrid power curtailment and the grid level-agent decisions in the negotiation process. The negotiation finally reaches an agreement that the VGI microgrids' charging power curtailments are 2.44k W (node 702), 5.37 kW (node 730), 6.79 kW (node 708), 9.19 kW (node 734), 12.02 kW (node 738), and 14.16 kW (node 741) from their critical charging points. On the other hand, the grid-level agent adjusts its Δ|V741| 2 requirement from 109.35 × 103 to 104.49 × 103.

**Figure 6.** The negotiation process with different values of penalty factor ρ. Sub-figure (**a**) shows a very slow convergence rate with ρ = 0.01, Sub-figure (**b**,**c**) show faster convergence within the range 0.05 ≤ ρ ≤ 0.1, but (**c**) demonstrates an even better convergence rate. Sub-figure (**d**) show negotiation does not converge when ρ increases and reaches 0.2.

**Figure 7.** The negotiation process with different values of proximal factor φ. Adding proper proximal factor can increase the robustness of the negotiation. Sub-figure (**a**) shows adding a small Proximal Factor, φ = 0.2, does not help negotiation with a large penalty factor ρ = 0.2 to converge. Sub-figure (**b**,**c**) show that if the proximal factor, φ, is within proper range, the robustness of negotiation increases. (**d**) demonstrates an exceedingly large proximal factor, φ, breaks the negotiation convergence.

**Figure 8.** Updates of microgrid power curtailment ΔPCap,k and the voltage square variation Δ|V741| 2 during negotiation. (**a**) shows the power capacity curtailment evolvements of different VGI Microgrids along the distribution line during the negotiation process. (**b**) shows the voltage square difference caused by change of VGI Microgrids power capacity change during the negotiation process.

Figure 9 shows the PEV charging power and CoC comparison in each microgrid before and after the voltage compensation negotiation. The charging power of some PEVs is further reduced and results in the CoC value falling below zero. It was also found that VGI microgrids that are close to the voltage violation node curtail more power than the VGI microgrids that are far away from the voltage violation node. The reason is that the load variation near the voltage violation node has a larger effect on the voltage regulation.

**Figure 9.** The negotiation effects on PEV charging in the microgrids. (**a**–**f**) show PEV Charging power and CoC value comparison before and after the negotiation process in different VGI Microgrids along the distribution lines.

The simulation result testifies to the effectiveness of the distribution voltage compensation. Figure 10 shows the distribution voltage of each node along the distribution feeder line. The comparison is shown for the PEV charging scenarios: maximal power demand charging, charging at the VGI microgrid PEV critical charging power point, and charging after voltage compensation negotiation. The voltage compensation negotiation successfully raises the Node 741 voltage to around 0.9504 per unit.

**Figure 10.** Voltage along the distribution feeder branch in different charging scenarios at 10:00 am.

### **6. Conclusions**

This paper presents a distributed VGI control to realize voltage compensation service in a distribution network. The control scheme design is composed of two levels–the microgrid level and the distribution grid level. At the top level—the distribution grid level—an ADMM-based distributed voltage compensation negotiation among the multiple VGI microgrid agents and a grid-level agent is triggered when a voltage violation occurs. This distribution grid agent aims to maintain its distribution voltage level above the lowest threshold by sacrificing the microgrids' power capacity. On the other side, each VGI microgrid agent wishes to minimize its power capacity curtailment to lower the impact to the PEV charging activities with in the VGI microgrid. Though having conflicting objectives, the negotiation coordinates the interests of all agents as an entity and finally reaches an agreement that all agents can accept. After determining the power capacity curtailment for each VGI microgrid, the CoC-based optimal microgrid VGI control algorithm aims to reasonably dispatch limited power to the charging PEVs and results in an average PEV charging satisfaction at the lower level, the VGI microgrid. We used a case study to simulate the application of the proposed algorithm in a VGI distribution grid to prove its effectiveness and advantages. First, the distributed algorithm allows each agent to pursue its own objective under the coordination of negotiation. This greatly reduces the computation burden of a single control unit compared to a centralized control design. Secondly, the two-level control design decouples the distribution grid-level control and single PEV charging control at the microgrid level. Each VGI microgrid becomes a relatively independent entity that controls the PEV charging activities within its range. This organization increases the scalability of the control scheme. However, the scenario presented in this paper applies certain simplifications. For example, distributed generation, like from renewable energy sources, was not considered. The possible utilization of a four-quadrant power inverter and large energy storage were also not in consideration. All these factors may provide both additional flexibility and uncertainty for the VGI control design in the distribution grid. We are going to consider improving the proposed control algorithm to better adapt to the factors above in future study.

**Author Contributions:** Conceptualization, C.C., Z.W. and B.C.; Methodology, C.C., Z.W. and B.C.; Software, C.C.; Validation, C.C.; Formal Analysis, C.C.; Investigation, C.C.; Resources, C.C.; Data curation, C.C.; Writing—original draft preparation, C.C.; Writing—review and editing, C.C. and B.C.; Visualization, C.C.; Supervision, B.C.; Project administration, B.C.; Funding acquisition, B.C. All authors have read and agreed to the published version of the manuscript.

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

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


**5. Conclusions**

The capacitive coupling models lead to an accurate approximation to the response of distribution network against the frequency spectrum imposed by the switching action of the converters at DG. This approximation is not feasible using simplified models because of the bandwidth limitation for high frequencies.

According to the distribution network under study, a high ground current contribution to grid provided by DG has been detected. Therefore, some preventive actions can be applied to network design stage in order to solve this problem, such as:

Fig. 15. Simulation result of the distribution network: (a) current waveform and (b) FFT analysis of the waveform obtained, at node 5.

#### **6. References**

276 Power Quality Harmonics Analysis and Real Measurements Data

Although voltage waveform meets standard regulations, it has been observed an important ground current contribution through the admittance of the underground cables. The ground voltage waveform has a considerable magnitude with peaks reaching 7 V, as shown in Fig. 14. Likewise, the ground current measurement due to the capacitive coupling of these

The fundamental component of the current waveform is 313 mA, and the THD of this waveform is 190.78%. The most predominant harmonic components are harmonic 72 with 145.22% of the fundamental component, followed by harmonic 70 and 76 with 98.29% and

3.80 3.81 3.82 3.83 3.84 3.85 3.86

Time (s)

Fig. 14. Simulation result of the distribution network ground voltage waveform at node 5. These observations point to the importance of controlling the capacitive coupling in load installations connected to networks with DG. Otherwise, end users equipments can be exposed to malfunctioning and lifetime reduction due to the capacitive ground current.

The capacitive coupling models lead to an accurate approximation to the response of distribution network against the frequency spectrum imposed by the switching action of the converters at DG. This approximation is not feasible using simplified models because of the

According to the distribution network under study, a high ground current contribution to grid provided by DG has been detected. Therefore, some preventive actions can be applied

underground cables is also significant as shown in Fig. 15.

Moreover, GPR can reach values of unsafe work conditions.

to network design stage in order to solve this problem, such as:

reduces the capacitive ground current in the installation.

GPR between PV modules and ground is minimized.

bandwidth limitation for high frequencies.

58.75%, respectively, as shown in Fig. 15a.

**5. Conclusions**

Voltage (kV)

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*Edited by Gregorio Romero Rey and Luisa Martinez Muneta*

Nowadays, the increasing use of power electronics equipment origins important distortions. The perfect AC power systems are a pure sinusoidal wave, both voltage and current, but the ever-increasing existence of non-linear loads modify the characteristics of voltage and current from the ideal sinusoidal wave. This deviation from the ideal wave is reflected by the harmonics and, although its effects vary depending on the type of load, it affects the efficiency of an electrical system and can cause considerable damage to the systems and infrastructures. Ensuring optimal power quality after a good design and devices means productivity, efficiency, competitiveness and profitability. Nevertheless, nobody can assure the optimal power quality when there is a good design if the correct testing and working process from the obtained data is not properly assured at every instant; this entails processing the real data correctly. In this book the reader will be introduced to the harmonics analysis from the real measurement data and to the study of different industrial environments and electronic devices.

Photo by FactoryTh / iStock

Power Quality Harmonics Analysis and Real Measurements Data

Power Quality Harmonics

Analysis and Real

Measurements Data

*Edited by Gregorio Romero Rey*

*and Luisa Martinez Muneta*


*4.3. Preparation of Fluorescent Glutathione Responsive* β*-cyclodextrin-Based Nanosponges*

Fluorescent GSH-responsive nanosponges were obtained by adding 6-coumarin (0.1 mg/mL) to the aforementioned aqueous GSH-NS nanosuspensions (previously described) (10 mg/mL) under stirring for 24 h at room temperature in the dark.


**4. Conclusions**

It is necessary to minimise sediment erosion to increase the turbine's lifespan. Threedimensional models based on the Tonstad power plant sand trap were created. Versions of the model include various upgrades to determine their effect on sediment settling. The numerical domain was discretised by a combination of hexahedral and tetrahedral mesh. Steady-state and transient multiphase simulations were performed on the models, using water and sand with a variable grain size. The objective was to investigate how installing rake- or rib-type structures affect particle sand trap efficiency and head loss.

By investigating the results, it was found that the sand trap with ribs at the outlet reduces the total weight of sediments exiting the sand trap by 24.5%, while increasing the head loss by around 1.8%. Installing rakes in the diffuser, although showing signs of increasing settling speed for larger sediments, was found to increase the total weight of sediments leaving the sand trap by 48.5%. This led to a reduced sand trap efficiency. In addition, the rakes caused an increased head loss of 12.7%. It is shown that in all models, sediments escaping the sand trap have a diameter smaller than one millimetre. These findings are supported by physical scale experiments on the sand trap [4,5,13]. The results show that installing ribs at the outlet of the sand trap will reduce sediment transport to the turbine and increase sand trap efficiency, thus prolonging turbine lifespan at the Tonstad power plant.

The main novelties from this work are the analysis results for the tested design of ribs and v-shaped rakes. The tested rib design has previously not been installed in a hydropower plant, and can be recommended based on the results in this work. The tested v-shaped rakes have been installed in existing hydropower plants previously, but this practice should be reconsidered.

For further work, running two-dimensional simulations along the centre line of the sand trap with the Large Eddy Simulation turbulence model could give a more accurate representation of the turbulence and sediment settling in the plane. Additional variants of the rakes should be tested to verify that they still have an adverse effect. The effects of extending the rakes to reach the crown of the tunnel so that the whole flow area is covered should also be investigated. Additionally, a model allowing for sediment resuspension should be explored to better represent sediments bouncing on or being resuspended from the bed. Further, experimental measurements of the inlet velocity profile are needed to create realistic and accurate inlet boundary conditions.

**Author Contributions:** Conceptualization, M.M.I., C.T. and K.V. methodology, M.M.I.; software, M.M.I.; formal analysis, M.M.I.; investigation, M.M.I.; resources, C.T.; data curation, M.M.I.; writing original draft preparation, M.M.I.; writing—review and editing, C.T. and K.V.; visualization, M.M.I.; supervision, C.T. and K.V.; project administration, C.T. All authors have read and agreed to the published version of the manuscript.

**Funding:** No funding is received for this work.

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

**Informed Consent Statement:** Not applicable.

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

## **1. References**


**Minimally Invasive Surgery for Treatment of Patients with Advanced Cancer and Thoraco-lumbar Spine Metastases**

Massimo Miscusi, Stefano Forcato and Antonino Raco

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/63125

#### **Abstract**

Spinal metastases are common in patients with cancer. Spinal cord compression is the initial symptom of 5–10% of patients with diffuse cancer, and about 70% of lesions are found in the thoracic vertebrae. Patients with advanced cancer are generally excluded from major spine surgery, to reduce postoperative morbidity and mortality. Minimally invasive spine surgery (MISS) has recently been advocated as a useful approach for spinal metastases, especially in advanced cancer patients, seeking to decrease the morbidity of more traditional open spine surgery; furthermore, reducing the recovery time, MISS permits the post-operative chemotherapy and radiotherapy to begin sooner.

A series of 29 cancer patients, with a short life expectancy, presenting acute myelopathy due to vertebral thoracic metastases, underwent MISS, with simple laminotomy and percutaneous stabilization; results from such series were compared to those retrospec‐ tively obtained from an homogenous series of patients operated with traditional open surgery.

No significant differences between two groups were demonstrated in terms of surgical complications and neurological recovery. Nevertheless, patients operated with MISS appear to have an earlier recovery and better quality of life in the immediate postoperative period, which is a fundamental aim for patients who have a short life expectancy.

**Keywords:** minimally invasive spine surgery, cancer, thoracic metastases, myelop‐ athy, quality of life

© 2016 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.


2.3.2. AquaCrop Model Input Data

Observed Historical Climatic Data and Projected Future

To simulate the durum wheat's grain yield for the BP (1981–2010) with the AquaCrop crop model for the experimental sites of BBA and Setif, it is necessary to introduce into this model the daily climate data of Tmin, Tmax, and P. These data were observed during the BP at the professional meteorological stations of Setif and BBA as it is necessary to introduce into the AquaCrop model, the daily data of the reference evapotranspiration (ET0). This last was calculated in advance by the ET0 calculator software according to the Penman–Monteith equation [34]. The CO2 concentration is also required by AquaCrop to simulate durum wheat grain yield. Thus, the global annual averages of CO2 concentrations from the Mauna Loa observatory in Hawaii are attached to the AquaCrop package, so they are used to simulate durum wheat yields. The same method was applied to simulate durum wheat's future yields in 2035–2064, under RCP 4.5 and RCP 8.5, using the corrected daily climate data simulated by the ICHEC-KNMI climate model for the future horizon 2035–2064, under both RCPs scenarios.


**2. Materials and Methods**

Printed beam shape specimens were prepared for tensile stress impact on printed specimens to relate creep and shrinkage property determination. Each printed specimen had four layers. They were modeled to be 40 × 40 × 1000 mm, but due to the cement composite mix flowability, the width of the specimens at the base was 83 mm, and 67 mm at the top. The used cement composite composition was similar to cement mortar. Due to the fact that the composition of the used cement composite is a trade secret, specific amounts and types of materials cannot be disclosed in this article. The mass partition of the used cement composite is shown in Table 1. The specimen printing process is shown in Figure 1.

**Table 1.** Used cement composite composition partitions.

**Figure 1.** Test specimen printing process.

When specimens were printed, they were left overnight to set. At the same time, cast specimens were prepared. They were poured into a steel prismatic cast of 40 × 40 × 160 mm. A day later, cast specimens were unmolded, and printed specimens were cut to the same shape (40 × 40 × 160 mm) as the cast specimens. They all were placed in an aqueous environment for 25 days. After 25 days, all specimens were prepared for the creep and drying shrinkage tests.

The compressive strength was determined for four specimens (prismatic specimens 40 × 40 × 160 mm) out of each specimen type. The load was applied to the specimens for creep tests according to the determined compressive strength values. Compressive strength and creep and drying shrinkage (further in the text referred to as shrinkage) tests were conducted using the identical shape specimens so that creep specimens would not have shape factor impact (if the compressive strength specimens were larger or smaller than creep specimens) in the load that they were subjected on the test stands. All of the specimens intended for creep testing were loaded with 20% of the ultimate compressive strength value. Specimen placement into the creep test stand and shrinkage stand is shown in Figure 2.

(**a**) (**b**) **Figure 2.** The 3D-printed and cast cement composite shrinkage (**a**) and creep (**b**) test setup.

Creep and shrinkage tests were carried out for 28 days. Creep and shrinkage testing procedure, except testing time, was performed according to RILEM TC 107 recommendations [10]. The laboratory conditions for the creep and shrinkage tests were 24 ± 1 ◦C and 30 ± 3% relative humidity.

After creep and shrinkage tests to determine the reasons for inequal creep and shrinkage strains to the specimen sides, as well as to see the 3D-printed layer adhesion, quantitative image analysis was performed to the specimen's polished sections that were prepared and made according to the [11] used process.


**3.1. Two-beam interferometry**

It has been noted that measuring the feature height of asphere surfaces and strongly curved surfaces using two-beam interferometers is very complicated due to the higher fringe density [7], so it has been shown that it is possible to measure the asphere form using multiple beam fringes. This is because two-beam interferometers suffer from the fact that they produce cos2 intensity distributions. **Figure 9(a)** and **(b)** compare precontour fringes of asphere surface obtained by two-beam Fizeau interferometry and multiple-beam Fizeau interferometry, respectively. As seen from **Figure 9(b)**, the multiple-beam Fizeau interferometry has the ability to resolve very small irregularities compared to common two-beam Fizeau interferometry. In this chapter, we review some of two- and multiple-beam interferometers for surface microtopography measurement.

**Figure 9.** Precontour fringes of asphere surface obtained by (a) two-beam Fizeau interferometry and (b) multiple-beam Fizeau interferometry.

### *3.1.1. Twyman-Green interferometer*

The light source used in a Twyman-Green interferometer is a quasi-monochromatic point source that is collimated by a collimating lens. This collimated light is incident on a beamsplitter which divides the beam into two copies: a reference beam and a test beam. The interferometer is used here for testing a spherical optical flat. The reference beam is incident on the known reference optical flat and returns to the beamsplitter. The test beam is incident on the unknown test part and also returns to the beamsplitter. The beams from the reference and the object interfere at the beamsplitter and constitute an interferogram relayed by an imaging lens to the observation plane. **Figure 10** shows a Twyman-Green interferometer for testing a curved surface in reflection [8, 9]. The reference is an optical flat of 1 inch in size and flatness of *λ*/20 nm. The object being tested is a curved surface of radius of curvature around. The sample is mounted carefully and four inline interferograms (no tilt between the reference and the object) are captured with phase shift between images of π/2 as shown in **Figure 11**. The intensities in the four fringe patterns can be expressed as follows:

**Figure 10.** Optical schematic of the Twyman-Green interferometer.

**3.1. Two-beam interferometry**

90 Optical Interferometry

topography measurement.

Fizeau interferometry.

*3.1.1. Twyman-Green interferometer*

the four fringe patterns can be expressed as follows:

It has been noted that measuring the feature height of asphere surfaces and strongly curved surfaces using two-beam interferometers is very complicated due to the higher fringe density [7], so it has been shown that it is possible to measure the asphere form using multiple beam fringes. This is because two-beam interferometers suffer from the fact that they produce cos2 intensity distributions. **Figure 9(a)** and **(b)** compare precontour fringes of asphere surface obtained by two-beam Fizeau interferometry and multiple-beam Fizeau interferometry, respectively. As seen from **Figure 9(b)**, the multiple-beam Fizeau interferometry has the ability to resolve very small irregularities compared to common two-beam Fizeau interferometry. In this chapter, we review some of two- and multiple-beam interferometers for surface micro-

**Figure 9.** Precontour fringes of asphere surface obtained by (a) two-beam Fizeau interferometry and (b) multiple-beam

The light source used in a Twyman-Green interferometer is a quasi-monochromatic point source that is collimated by a collimating lens. This collimated light is incident on a beamsplitter which divides the beam into two copies: a reference beam and a test beam. The interferometer is used here for testing a spherical optical flat. The reference beam is incident on the known reference optical flat and returns to the beamsplitter. The test beam is incident on the unknown test part and also returns to the beamsplitter. The beams from the reference and the object interfere at the beamsplitter and constitute an interferogram relayed by an imaging lens to the observation plane. **Figure 10** shows a Twyman-Green interferometer for testing a curved surface in reflection [8, 9]. The reference is an optical flat of 1 inch in size and flatness of *λ*/20 nm. The object being tested is a curved surface of radius of curvature around. The sample is mounted carefully and four inline interferograms (no tilt between the reference and the object) are captured with phase shift between images of π/2 as shown in **Figure 11**. The intensities in

**Figure 11.** Intensity images of a curved object with a phase shift of 0*π*, 0.5*π*, 1*π*, and 1.5*π*, for (a–d), respectively.

$$I\_{\cdot}(\mathbf{x}, \mathbf{y}) = I\_{\mathbf{o}} + I\_{\mathbf{n}} + 2\sqrt{I\_{\mathbf{o}}I\_{\mathbf{n}}} \cos(\boldsymbol{\varphi} + (\boldsymbol{j} - \mathbf{l})\boldsymbol{\pi} / 2), \tag{13}$$

where *I*O and *I*R are the intensities of the object and the reference waves, respectively, is the phase encoded in the intensity distribution, and *j* = 1, 2, 3 and 4 (four frames) is the number of the phase-shifted frames.

Using the four-phase step algorithm, the phase distribution can be expressed as follows:

$$\varphi = \tan^{-1} \left( \frac{(I\_4 - I\_2)}{(I\_1 - I\_3)} \right). \tag{14}$$

The evaluated phase is wrapped between −*π* and *π* due to arctangent function. The wrapped phase map resulted from the four frames in **Figure 11** is shown in **Figure 12(a)**.

**Figure 12.** (a) Wrapped phase map resulted from the four frames of **Figure 10**; (b) 3-D unwrapped phase map of (a); and (c) two-dimensional height at the middle of (b) in the *x*-direction.

The wrapped phase map is then unwrapped to remove the 2π ambiguity and the unwrapped phase map is shown in **Figure 12(b)** and profile along **Figure 12(b)** is shown in **Figure 12(c)**.


**Meet the editors**

Dr. Falcón-Lezama obtained his Medical degree at Juárez Autonomous University of Tabasco, a Master's degree on Infectious Diseases at Mexico's National Institute of Public Health, a PhD. on Epidemiology at National Autonomous University of Mexico, and a Specialization course on Intelligence for National Security at Mexico's National Institute of Public Administration.

He has worked at Morelos State Health Services, Mexico's Institute for Insurance and Social Services for the State Workers, and currently as Project Coordinator on Infectious Diseases at the Carlos Slim Foundation. Dr. Falcón-Lezama has taught postgraduate courses at the National Polytechnic Institute, Juarez Autonomous University of Tabasco, and Hidalgo State Autonomous University. He is member of Mexico's National Researchers System, and the Mexican Public Health Association.

Dr. Betancourt-Cravioto is Director of Global Solutions at the Carlos Slim Foundation, where he coordinates the international projects on vaccinology, genomics, and neglected tropical diseases. He is a pediatrician and has a Master's Degree in Health Policy, Planning, and Financing, and a Doctorate in Public Health from the London School of Hygiene and Tropical Medicine.

He worked for over a decade at the Ministry of Health of Mexico where he occupied managerial positions in surveillance, immunizations, public health emergencies, and disasters. Dr. Betancourt-Cravioto is fellow of the National Researchers System of Mexico and has lectured on epidemiology, health policy, and public health. He is an author of scientific papers and book chapters on NTDs, public health emergencies, dengue fever, and vaccinology.

Dr. Tapia-Conyer has been the Carlos Slim Foundation CEO for the last 12 years. In that position, he has designed and implemented innovative initiatives and models to strengthen health systems and foster the solution of demanding health problems. He served at the Mexican Ministry of Health for over 25 years. As General Director of Epidemiology, he designed and implement-

ed the National Epidemiological Surveillance System, and the National Health Surveys. As Vice-Minister of Prevention and Health Promotion, he implemented innovative public health programs that are cornerstone of Mexico's Public Health agenda. He holds a tenure position at the UNAM's School of Medicine.

Contents

**Preface VII**

**Section 1 Current Panorama of Dengue Fever 1**

Chapter 1 **Dengue Fever: A General Perspective 3**

Felipe Avella-Niño

Juan Samuel Sulca Herencia

**Section 2 New Tools for Study and Control 77**

Manrique-Saide

Majeed, Farhat Jabeen and Kanwal Ranian

Chapter 3 **Ecology of Aedes Mosquitoes, the Major Vectors of Arboviruses in Human Population 39**

Chapter 2 **The Burden of Dengue Illness and Its Economics Costs in the**

**Americas: A Review on the Most Affected Countries 21**

Germana Baraka, Lucile Lyaruu and Aneth M. Mahande

Chapter 4 **Laboratory Tests Used in the Diagnostic and Research of Dengue Virus: Present and Future 57**

Chapter 5 **Urban Ecology and the Effectiveness of Aedes Control 79** Wladimir J. Alonso and Benjamin J.J. McCormick

Chapter 6 **Challenges for the Introduction and Evaluation of the Impact of Innovative Aedes aegypti Control Strategies 95**

> Héctor Gómez-Dantés, Norma Pavía-Ruz, Fabián Correa-Morales, Abdiel Martín-Park, Gonzalo Vázquez-Prokopec and Pablo

Muhammad Kashif Zahoor, Azhar Rasul, Muhammad Asif Zahoor, Iqra Sarfraz, Muhammad Zulhussnain, Rizwan Rasool, Humara Naz

Raúl Castro Rodríguez, Jorge Armando Rueda-Gallardo and Manuel

Eliningaya J. Kweka, Vito Baraka, Leah Mathias, Beda Mwang'onde,


*Edited by Ingrid Schmid*

Flow cytometry - Select Topics is a collection of chapters that illustrate the constantly evolving application of flow cytometry to diverse areas of research or clinical investigations. It includes chapters on the utilization of flow cytometry in the fields of human reproduction and fertility, platelet function, apoptosis, inflammation research, leukemia immunophenotyping, and transplantation.

ISBN 978-953-51-2550-1

Flow Cytometry - Select Topics

Photo by fotojog / iStock

## Flow Cytometry Select Topics

*Edited by Ingrid Schmid*


*3.5. Estimation of EL, MDA and H2O2*

A substantial increase in EL was noted in both roots and shoots of wheat plants under Cr stress, as shown in Figure 4A,B. Uninoculated wheat plants showed more EL in leaves and roots under all Cr levels (0, 25, 50 and 100 mg·kg−1) as compared to inoculated plants. EL in uninoculated leaves was increased by 17.98%, 36.40% and 56.52% and EL in uninoculated roots increased by 9%, 32% and 53% under 25, 50 and 100 mg·kg−1 Cr, respectively. On the other hand, inoculation with *S. aureus* K1 increased EL in leaves by 15.83%, 33.26% and 55.90% and in roots by 13%, 33% and 56%, under 25, 50 and 100 mg·kg−1 Cr, respectively (Figure 4A,B).

**Figure 4.** Influence of the different Cr levels (0, 25, 50, 100 mg·kg−1), with and without peat-moss-based microbial inoculation, on EL in leaves (**A**), EL in roots (**B**), MDA in leaves (**C**), MDA in roots (**D**), H2O2 in leaves (**E**) and H2O2 in roots (**F**) of wheat plants. Bars indicate the mean values and standard deviation of three replicates. Different bar letters show significant changes among various treatments at *p* < 0.05.

There was a noticeable increase in MDA content of leaves, showing lipid peroxidation due to high level of Cr stress, as shown in Figure 4C,D. Maximum MDA contents were observed in leaves and roots of uninoculated plants under 100 mg·kg−1 Cr stress as compared to their respective controls. However, inoculation with *S. aureus* K1 reduced MDA content in all the plants of varying level of Cr stress compared to uninoculated plants. Likewise, a gradual rise in H2O2 of wheat leaves was observed with increasing levels of Cr (Figure 4E,F). Furthermore, a noteworthy decrease in H2O2 content was observed in *S. aureus* K1 inoculated plants, both Cr-stressed and control.

#### *3.6. E*ff*ect of S. aureus on Antioxidant Enzyme Activities*

The findings revealed that SOD activity in leaves and roots was significantly higher at the 25 mg·kg−1 Cr level but gradually decreased with increasing Cr levels, both in uninoculated and inoculated plants. SOD activity increased by 19.59%, 5.22% and 6.98% in uninoculated plant leaves and by 17.58%, 5.22% and 3.08% in uninoculated plant roots under 25, 50 and 100 mg·kg−1 Cr treatments, respectively. However, inoculation with *S. aureus* K1 enhanced the SOD activity by 24.71%, 9.64% and 3.51% in leaves and 20.83%, 9.49%, and 4.34% in roots under 25, 50 and 100 mg·kg−1 Cr, respectively (Figure 5A,B). As compared to noncontaminated treatments (control), a decline in the CAT activity was observed under Cr contamination (Figure 5C,D). Inoculation with *S. aureus* K1 provoked a substantial increase in the activity of the CAT enzyme in wheat leaves (Figure 5C). CAT activity in roots also improved (114.31 Units·g−1 FW) under bacterial inoculation as compared to uninoculated plants (102.66 Units g−1 FW) at 25 mg·kg−1 Cr (Figure 5D). Moreover, abridged CAT activity was noticed at the highest level of Cr stress (100 mg·kg−1); activity at this level was increased by 5.52% in leaves and 3.63% in roots for uninoculated plants, while inoculated plants showed increase of 5.06% in leaves and 1.37% in roots, as shown in Figure 5C,D. The POD activity substantially (*p* < 0.05) increased due to addition of Cr as compared to control (Figure 5E,F). There was a noticeable reduction in POD activity in leaves under bacterial inoculation with *S. aureus* strain K1 (22.27%, 11.99% and 0.21%) as compared to uninoculated treatments (21.63%, 10.12% and 2.92%) (Figure 5E). There was a substantial increase in the activity of the APX enzyme observed under Cr stress in wheat plants, as shown in Figure 5G,H. There was increase in APX activity in plant shoots and roots, with the maximum production occurring at the Cr concentration of 25 mg·kg−1, and the APX activity decreased at the highest Cr level in the growth medium (Figure 5G,H). Furthermore, the maximum APX activity was observed in roots without inoculation at Cr concentration of 25 mg·kg−1, as shown in Figure 5H.

**ƌŽŶĐĞŶƚƌĂƚŝŽŶ;ŵŐŬŐͲϭͿ**

Ă Đ Ğ

**Figure 5.** Influence of the different Cr levels (0, 25, 50, 100 mg·kg−1), with and without peat-moss-based microbial inoculation, on SOD in leaves (**A**), SOD in roots (**B**), CAT in leaves (**C**), CAT in roots (**D**), POD in leaves (**E**), POD in roots (**F**), APX in leaves (**G**) and APX in roots (**H**) of wheat plants. Bars indicate the mean values with standard SD of three replicates. Different bar letters show significant changes among various treatments at *p* < 0.05.

#### *3.7. Cr Accumulation in Plants*

The data regarding Cr accumulation in shoots and roots of the wheat plants are shown in Figure 6A,B. With increasing concentration of applied Cr, a gradual increase in Cr concentrations was observed in roots and shoots in a dose-additive manner. In addition, inoculation of *S. aureus* K1 significantly decreased the Cr concentrations both in shoots and roots as compared to uninoculated plants.

**Figure 6.** *Cont*.

**Figure 6.** Influence of the different Cr levels (0, 25, 50, 100 mg·kg−1), with and without peat-moss-based microbial inoculation, on Cr concentrations in shoots (**A**) and roots (**B**) of wheat plants. Bars indicate the mean values with standard SD of three replicates. Different bar letters show significant changes among various treatments at *p* < 0.05.

#### **4. Discussion**

The major objective of our research was to appraise the effectiveness of *Staphylococcus aureus* K1 treatment in reducing the toxic effects of Cr stress in wheat plants. An indigenous bacterial strain, *Staphylococcus aureus* K1 (GenBank accession no. KX685332), capable of tolerating up to 22 mM of Cr6+ was isolated from a metal-polluted environment. Numerous research studies with similar metal-tolerant bacterial isolations from metal-contaminated sites have been reported [35,50,51]. Our results also supported the findings of Mustapha and Halimoon [52], who isolated a total of 21 isolates from electroplating industries and reported that merely 5 of them were Cr-tolerant (up to 50 mg·L−1). The results of the current study show that *S. aureus* K1 increased plant growth parameters under Cr metal stress (Figure 2).

#### *4.1. Detoxification of Metals by S. aureus K1*

Microbes have a number of metal resistance mechanisms involving chromosomes, transposon-encoded genes or plasmids. These mechanisms are mostly plasmid-facilitated and show resistance to some particular anion or cation [53]. Metals can have different impacts inside cells depending upon their concentration [53]; once a certain level is exceeded, bacteria respond with the initiation of a number of resistance mechanisms, including metallothioneins, P-type ATPases, CDF transporters and RND efflux pumps [54]. The genes located on plasmids, chromosomes or transposons that are responsible for resistance can easily be transferred to new community members from their point of location [53,55].

The genotype of bacteria, the nature and type of the metal and the pH of the culturing media are among the factors responsible for showing the degree of tolerance of microbes to various metals (Hg, Co, Pb, Ag, Zn, Mn, Cu, Cr) [56]. This kind of resistance against toxic heavy metals might be recognized by employing a number of potential methods like bioaccumulation of heavy metals by microbes, ion exclusion and low-molecular-weight binding protein production [57,58]. Elevated levels of metal resistance systems in bacterial cells are an indication of environmental heavy metal bioavailability [59]. The results of Chudobova et al. [60] showed a maximum resistance and capability of *S. aureus* strains under Cd2+ and Zn2+ ions. This resistance observed in *S. aureus* might be due to the efflux system containing a P-type ATPase transport system acting against Cd2+ ions [53,61].

#### *4.2. E*ff*ect of S. aureus on Plant Growth Promotion under Cr Metal Stress*

Different wheat varieties may differ in their response to different concentration of Cr in the soil. This could be attributed to various biological aspects of wheat varieties, as different wheat varieties show differences in growth parameters (e.g., leaf size). A heavy metal like Cr can easily make its way to aerial portions of plants, where it will affect their shoot metabolism at the cellular level and cause severe damage to minerals, water and nutrients, consequently retarding plant growth [10,62]. However, bacterial inoculation may improve the nutritional requirements of both micro- (Mn, Zn, Cu and Fe) and macronutrients (N, P and K) by modifying host physiology, which results in changed uptake pattern of roots. Similarly, a recent investigation done by Islam et al. [63] showed an increase in Fe and K concentrations in maize plants under Cr stress due to bacterial inoculations. According to an observation, plants with bacterial inoculation showed a reduction in metal accumulation in their aerial parts, which might be due to delayed translocation of metals from roots to upper parts [64]. Similar observations were recorded in this current research. Moreover, we isolated *S. aureus* K1 from wastewater that was contaminated with Cr, so the microbes may have the capability of performing metal detoxification as a part of their metabolic system. There was substantial improvement in plant growth and leaf pigments due to inoculation of specific microbes [63].

#### *4.3. Chlorophyll Contents*

Higher chlorophyll contents were observed in plants with bacterial inoculation compared to uninoculated plants (Figure 3). However, with further increasing metal concentrations, a reduction in chlorophyll contents was noted. This is in agreement with the findings of another research study, where chlorophyll a and chlorophyll b in wheat plants decreased with increasing concentrations of Pb in the growth medium [65].

#### *4.4. ROS Species and Antioxidant Enzyme Production*

Reactive oxygen species can be produced in plants when exposed to Cr6+, which may damage the photosynthetic apparatus and protein complex of thylakoid membranes and result in inhibition of chlorophyll production [66]. In adverse conditions, plants release MDA contents; this reveals the level of lipid peroxidation, as MDA is the last decomposition product of membrane lipid peroxidation [67]. The increase in MDA contents found in the present study is indicative of imbalance between the generation and removal of free radicals in the cells [68]. The decreased lipid peroxidation with *S. aureus* K1 inoculation under Cr stress could be due to the increase in ROS-scavenging enzyme production in plants. This may be supported by a previously published study which revealed that the gene profile of metal detoxifying enzymes was activated by bacterial inoculation to deal with metal stress [69]. Reactive oxygen species are generated in response to stress caused by heavy metals like hexavalent Cr, and plants have a detoxifying antioxidant enzyme system for their maintenance. These enzymes are POD, SOD, APX and CAT, and they work alongside other non-enzymatic antioxidants. The activities performed by antioxidant enzymes in plants under metal stress are extremely variable and dependent on plant species, metal concentration, metal ions and exposure time period [70]. At low metal concentration, SOD activity may increase, but it becomes constant with increased metal concentration [71]. The enhancement in CAT activity was also noted in a number of plants under metal stress [72]. An increase in CAT activity was also observed as an adaptive trait of isolate CPSB21 [73]. Increased antioxidant enzyme activities in plants with inoculation of CPSB21 may be due to increases in mRNA/gene expression of antioxidant enzymes as compared to uninoculated plants [74].

#### *4.5. Reduction of Cr Concentration in Plants by Bacterial Inoculation*

A significant difference was found between uninoculated and *S. aureus* K1 inoculated plants in terms of Cr concentration. In contaminated soil, the results showed that the level of Cr was higher in the roots of wheat plants than it was in the shoots, which may be due to decreased translocation of Cr from roots to shoots of plants [75,76]. Immobilization of Cr in root cell vacuoles may lead to higher Cr accumulation in roots, which can cause toxicity in plants [77]. In the present study, inoculation of wheat plants with Cr-resistant microbes decreased the Cr concentration and its translocation from soil to roots and upper parts of wheat plants. The reduction of hexavalent Cr (Cr6+) to trivalent Cr (Cr3+) by bacterial isolates may be the reason for the improved growth of wheat plants [78] and hence the decreased level of the Cr contents in soil. Hasnain and Sabri [79] also reported a pattern of decreased Cr uptake and accumulation in roots and shoots of wheat plants inoculated with *Pseudomonas* sp. A decrease in Cr concentration in soil was observed after wheat plant harvesting. This decrease was recorded in uninoculated Cr-contaminated wheat plants as a result of increased accumulation and uptake of Cr in roots and shoots [80]. Such decrease may also be due to Cr6+ reduction into Cr3+ under the influence of bacterial inoculation [78,81]. Scientists are also considering the use genetically engineered microorganisms (GEM), which may be well adjusted to their local environment (both climatic and soil) for effective elimination of heavy metals from contaminated soils [58,82,83].


*6.1. First Test: Sensitivity to New Data on Landslide Occurrence*

The modified *AR-S* method with no bootstrap is tested firstly by using the recent addition to the WEAR data set of dated landslide events. Taking into account their date uncertainty, the 39 landslide events constituting this validation set yield 117 new weighted event dates, of which four are discarded from the analysis because they do not meet the *AR* ≥ 5 mm requirement. The 113 remaining data instances (constituting *Q*, Figure 4) are distributed in the log(*AR*)–log(*S*) space in such a manner that 6% of them are located below the 5% threshold line derived from the calibration (Equation (8)) and 8% below the 10% threshold line (Equation (9)), indicating a good performance of the calculated thresholds (Figure S2) considering the small sample size.

Another test using the validation set, which in the same time should improve the accuracy of the calibrated thresholds, has consisted in combining the data of the calibration and validation sets into a larger data set of 540 event dates in order to recalculate the thresholds. The new thresholds read as

$$AR\left(5\%\right) = 4.5 \times S^{-1.14} \text{ (}R^2 = 0.66\text{)}\tag{10}$$

$$AR\left(10\%\right) = 6.1 \times S^{-1.08}\ \left(R^2 = 0.59\right) \tag{11}$$

and do not much differ from those derived from the calibration set only (Equations (8) and (9)) (Figure 6b), confirming the relevance of the modified *AR*-*S* method. Though slightly decreased by additional noise brought in the middle- to low-*S* classes by the new data (Figure S2), their coefficients of determination remain highly significant. Likewise, their FNRs (0.04 and 0.06 for the 5% and 10% thresholds, respectively) are slightly degraded mainly as a result of an increased deficit in data in these *S* classes. Owing to the larger size of the data set, we nevertheless consider these thresholds (Equations (10) and (11)) more reliable than those based only on the calibration set, especially the 5% threshold, for which FNR ≈ TPE.


**7. HPV status and treatment response**

There are many factors attributed to the survival advantage for p16 positive oropharyngeal carcinoma. Many of the patients are younger, they have fewer comorbidities and less chance of field cancerization given reduced smoking history. HPV-positive tumours may harbour fewer or different genetic alterations. HPV-positive tumours have higher radio sensitivity, due to compromised DNA repair capacity [12]. Other studies have reported intrinsic radiation sensitivity and increased apoptosis following radiation exposure [13]. The immunologic response may play a role in the improved response to radiotherapy and chemotherapy in HPV-positive tumors.

The survival advantage noted for HPV positive OPSCC in the radiotherapy setting has been summarized in **Table 4**. Retrospective analysis of the HPV positive subgroup in the RTOG 0129 trial reported a strong association between HPV status and good survival [19]. They risk stratified the patients as having a low, intermediate, or high risk of death based on the combination of tumor HPV status, packyears of tobacco smoking, and cancer stage. In the low-risk group, which included

**Table 4.**

*Major randomized trials that have reported survival benefit for HPV positive subset.*

HPV positive and non-smokers, 3-year disease-free survival (DFS) was 93% when compared to<50% in the high-risk group which included the HPV negative and smokers. The intermediate-risk group included HPV positive patients with smoking history and HPV negative non -smokers. This led to the thought for de-intensification of the multimodality approach for low-risk category patients. In the post-op setting, the German radiation oncology group study showed a better correlation of HPV positive status with oropharyngeal carcinoma subsite and better outcomes in the patients undergoing adjuvant chemoradiation for locally advanced head and neck cancers [21]. Retrospective analysis of IMCL-9815 study, where patients were treated with radiotherapy with or without Cetuximab, the overall survival was better for p16 positive patients [22]. In the abovementioned trials, a better prognosis for HPV positive oropharyngeal carcinoma was independent of treatment modality. The association of HPV positive status with improved outcome was restricted to the oropharyngeal primary site [23].