**3. When psoriasis coexists with other skin diseases**

Often chronic skin inflammatory diseases coexist with psoriasis suggesting common pathogenic pathways.

Among them, hidradenitis suppurativa (HS) also exhibits a systemic inflammatory nature with systemic comorbidities similar to psoriasis. The systemic inflammation might explain the observation of a recent study, where it was found that in patients with both HS and psoriasis, the disease diagnosed first tended to take a more severe course than the later diagnosed (**Figure 2**) [33].

Pityriasis rubra pilaris (PRP) is an inflammatory dermatologic disorder of unknown cause, which often is misdiagnosed as psoriasis. However, differentiating between erythrodermic PRP and pustular psoriasis is challenging even histologically. The same treatment is indicated in both diseases, despite the absence of standard

#### **Figure 2.**

*A 65-year-old male patient. Hidradenitis suppurativa Hurley III coexists with psoriatic plaques. Photo from personal collection.*

recommended treatment algorithms for PRP. According to recently published data, we must consider the coexistence of psoriasis and autoimmune diseases in patients with PRP [34]. From our personal experience, a patient can present with erythrodermic PRP and the improvement of the rash might be followed by the appearance of classical plaque psoriasis after treatment with an anti-TNF-α biological agent.

One of the most paradoxical relationships is between psoriasis and atopic dermatitis (AD). The Th17 immune response is dominant in psoriasis and causes neutrophil migration, induction of innate immunity, and increased epithelial metabolism, while Th2 immunity that characterizes AD is dominated by IL-4 and IL-13 cytokines leading to an impaired epidermal barrier, dampened innate immunity, and eosinophil migration. However, the association of AD with psoriasis is not so rare. Both diseases share many characteristics: high prevalence, chronicity, primary skin inflammation, associated comorbidities, important impact on the quality of patient's life due to itch and stigmatization. Some authors consider that the co-occurrence is an overlapping syndrome [35] and others found bidirectional association [36]. In Bozek's study [35] the patients with concomitant AD and psoriasis were frequently boys and overweight and had skin lesions equally distributed throughout the body. Despite the fact that the pathogenesis of psoriasis and AD is different, a family history of atopic disease is a more frequent finding in children with concomitant AD and psoriasis and in children with AD than in children with only AD or psoriasis [35]. Genetics and epigenetics studies with a focus on this topic might provide useful data regarding the particular management of patients with AD and psoriasis.


*5.1.1 Orodispersible film/oral soluble films*

Because of its simplicity of administration, non-invasiveness, flexibility, patient compliance, and acceptance, the oral route of medication administration is the most popular. When put on the tongue, orally disintegrating films quickly hydrate via soaked saliva after the breakup and/or dissolution, liberating the active pharmacological substance from the dosage form. Orodispersible films are a type of formulation


*4.6. Thematic Accuracy Evaluation with Spectral Index*

The performance of the conventional and proposed Pan sharpening methods were evaluated with several quality indices and visual interpretation in this research. However, the effects of Pan sharpening on the information extraction, process such as image classification, segmentation and index-based analysis is another important concern that requires conservation of spectral properties of the MS image after Pan sharpening. One of the indirect methods frequently used to evaluate the abovementioned situation is to apply the spectral index on the MS and Pan sharpened images, and investigate their consistency. As only visible bands of the images were used in this research, the visible atmospherically resistant index (VARI) proposed by Gitelson et al., 2002 [54] was used for the evaluation as it uses the all visible bands for calculation.

$$VARI = \frac{Green - Red}{Green + Red - Blue}.\tag{9}$$

The test site F3 was selected for this evaluation, as it is one of the most challenging sites in the dataset due to complex and heterogeneous land cover characteristics. The VARI index was applied on both the MS and CIELab Pan sharpened images, and a binary classification was performed with the use of the same threshold to map the manmade and natural lands in the region. According to results presented in Figure 4, same level of information extraction could be achieved with CIELab Pan sharpened image and it even provided better thematic representation by providing better geometric representations of the objects and less of the salt and pepper effect observed in the vegetated areas located in the north and south parts of the image.


**2. Power Variabilities of a PV Generator**

#### *2.1. Abrupt Disturbances in PV Generation*

Cloud movements cause abrupt changes in solar irradiation, Figure 1. To study the impact of these abrupt power changes, a hybrid dc/ac system is considered in this paper as shown in Figure 2. The parameters of the dc microgrid and the ac system are shown in Tables 1 and 2, respectively. The details of the PV control used in this study are given in Section 4.1.1.

The PV generator of Figure 2 is controlled using a maximum power point tracking (MPPT) algorithm. The control structure and the parameters are shown in Section 4. Figure 3 shows the voltage and frequency fluctuations, at the point of coupling between dc and ac systems, to abrupt PV disturbances. The solar intensity falls from 1000 W/m2 to 250 W/m2 at *t* = 5.0 s, and it rises back to 1000 W/m2 at *t* = 50.0 s. The dc voltage has a peak of 10% that oscillates over a second, and the ac voltage (rms) has a peak close to 5%. The frequency oscillates with a peak of 0.23 Hz, and it takes several seconds to settle.

**Figure 1.** Solar intensity measured at Lowry Range Solar Station on 18 March 2013 [31].

**Figure 2.** A hybrid dc/ac system to study the abrupt power disturbances of the photovoltaic (PV) generator.

126

**Table 2.** Parameters of ac system.

**Figure 3.** Voltage and frequency fluctuations at point of common coupling (PCC) of the study system due to the abrupt PV disturbances.


**5. Biological amplifiers**

In signal acquisition, analyzable information is obtained by studying the physical quantities involved in the activation process. These physical quantities can be measured by sensors that convert them into electrical signals and then record them using a data acquisition system (Figure 3). Computers make data acquisition more efficient and reliable and have the advantage of combining data storage with analysis and processing capability [21].

Application of Surface Electromyography in the Dynamics of Human Movement 399

Gain is defined as the ratio between the voltage that enters and exits the amplifier. Gain should be selected to suit the characteristics of the experiment, the studied muscle, the electrode type and the use planned for the amplified signal. Considering that a sEMG signal has a maximum voluntary contraction amplitude not exceeding 5 mV peak-to-peak (Figure 6), the gain can be adjusted between 10 and 1000x. It is important to choose a gain that does not exceed at any stage the voltage expected from the system, or there will be a risk of either

Filters can be used to remove frequency components that do not belong to the signal or

The captured signal can be filtered by hardware or software. Signal-filtering hardware can be used in the amplification step, while signal filtering by means of software can be

When using surface electrodes to measure EMG signals, interference from various sources can be mixed with the EMG signal. Each type of interference has its own characteristics that must be understood in order to remove it during the measurement phase or during processing. The useful information in the sEMG signal, which is a sum of the waves of varying frequency, is located between 20 and 500 Hz [12]. The signal is reduced due to the filtering effect of tissue located between the muscle fibers and the active sensing surface. The band pass filter corresponds to the frequency between the low frequency (high pass) and high frequency (low pass) cut-offs. Specific frequencies can also be filtered out with what are

**6. Signal amplification**

**Figure 5.** Appropriate gain range [3].

performed during processing.

called "notch filters" [5, 11, 3, 23].

components that are irrelevant for a given analysis.

**7. Signal filtering**

losing part of information or damaging the system itself [1].

**Figure 3.** Diagram of a biological signal acquisition system [3].

Sensors and transducers are devices that convert physical quantities into electrical signals or current. Signal conditioners are electronic devices that modify the input signal in some way, whether by amplification, attenuation, filtering or isolation. The EMG signal, for example, enters at an amplitude of μV and must be amplified and filtered [3].

There are basically two techniques capturing an EMG signal: either monopolar or bipolar electrodes. In the monopolar configuration, only one electrode is placed on the skin over the muscle in question (Figure 4). This electrode detects the electrical potential relative to a reference electrode, which is placed in a location unaffected by the electrical activity generated by the analyzed muscle. In the bipolar configuration, two electrodes are used on the muscle as well as a reference (or ground) electrode placed in a neutral location (Figure 5). The human body is actually a good antenna for electromagnetic energy [3].

**Figure 4.** A) Schematic representation of a unipolar amplifier. B) Schematic representation of a bipolar amplifier [3].


**4. Conclusions**

We determined LOD for detection of chymotrypsin by gravimetric (LOD = 1.40 ± 0.30 nM) spectrophotometric (LOD = 0.15 ± 0.01 nM) and DLS method (LOD = 0.67 ± 0.05 nM). Spectrophotometric method showed the best value of LOD, even when compared to commercial ELISA (LOD = 0.5 nM). We also determined a steady-state constant KM for the different methods with reverse Michaelis—Menten equation. The largest KM value was found for gravimetric method of chymotrypsin detection (KM = 8.6 ± 3.6 nM), followed by spectrophotometric method (KM = 3.89 ± 1.24 nM),) and then DLS method (KM = 1.03 ± 0.26 nM). We can explain observed differences in KM values by difference in α-chymotrypsin activity, which is highest and least impeded on gold nanoparticles modified with β-casein. Addition of MCH decelerates the reaction and immobilization of β-casein on the gold surface slows the α-chymotrypsin ability to cleave β-casein. The detection time for methods that we tested was comparable and takes around 30 min for chymotrypsin determination. All methods required preparation of the sensing layers or modification of AuNPs overnight. The AuNPs or gravimetric sensors could be stored for a long time (more than one month) at 4 ◦C. In terms of difficulty in operation, the optical methods offered the easier way to measure chymotrypsin. With prepared AuNPs modified by β-casein and MCH, the spectrophotometric method required only one step of protease detection based on measurement of absorbance changes after 30 min, which was simpler in comparison with ELISA. DLS method based on AuNPs requires also only one step of measurement of the Z-average. The spectrophotometric method required only 50 μL of sample, the DLS method used 100 μL, while the gravimetric method used around 2 mL. One of the advantages of the gravimetric method is that it is more robust to "impurities" in the sample. The gravimetric method can be used with natural, no-transparent samples containing fat, minerals, or other proteins, just like in milk. Optical assays require a transparent sample; however, DLS method is a little less sensitive to changes in chymotrypsin concentrations. In terms of cost of analysis, the production of gold nanoparticles is relatively inexpensive and can be scaled to industrial amounts. For optical detection of chymotrypsin, gold nanoparticles should be surface-modified using inexpensive chemicals (β-casein and MCH). While gravimetric methods also use inexpensive chemicals for modification, but the cost of quartz crystal would raise the overall cost of the sensor. This cost offset can be reduced by multiple use of the same crystal when the sensing layer is regenerated. All methods have a distinct advantage and disadvantage compared to the currently used ELISA. In contrast with ELISA, the optical and gravimetric assay are not specific to the protease. Non-specificity of response can be addressed by using chymotrypsin-specific peptide substrate [13] or by integration of advanced machine learning algorithms [14]. In conclusion, we demonstrated advantages and disadvantages of spectrophotometric, DSL and gravimetric methods in detecting chymotrypsin. These methods can be applied also for detection of other proteases and can be useful for further application in the food industry and in medicine for real-time monitoring of the protease activity. In future work we plan to explore application of the presented techniques for analysis of natural milk samples (paying particular attention to gravimetric methods). Many new analytical methods use fluorometric or colorimetric molecules for detection of protease activity [31]. Gold nanoparticles seem to be good alternative component for colorimetric detection or for amplification of existing signal (for example increase of Raman signal from a sample using gold nanoparticles). It is clear that efforts furthering the development of new low-cost methods, easily implementable in practice, which would be sensitive, and exhibiting long-term stability, still need to be developed [32].

**Author Contributions:** Conceptualization, T.H. and I.N.I.; methodology, I.P.; formal analysis, I.P.; investigation, I.P.; resources, T.H. and I.N.I.; writing—original draft preparation, I.P.; writing—review and editing, T.H. and I.N.I.; visualization, I.P.; supervision, T.H. and I.N.I.; project administration, T.H.; funding acquisition, T.H. and I.N.I. All authors have read and agreed to the published version of the manuscript.

**Funding:** A portion of this research was conducted at the Center for Nanophase Materials Sciences, which is a DOE Office of Science User Facility, project No. CNMS2018-293. This work was funded

under the European Union's Horizon 2020 research and innovation program through the Marie Skłodowska-Curie grant agreement No 690898 and by Science Agency VEGA, project No. 1/0419/20.

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

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Not applicable.

**Conflicts of Interest:** The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.


2.2 Excitation laser beams

The four-level atom is driven by three laser fields, the Gaussian first and second excitation laser field with respective frequency ω1 and ω2 and the LG-Rydberg excitation laser field with frequency ω3. Neglecting the focusing and the radial complexity and the mode curvature of the excitation laser beams, the electric field of each one-photon transition in the cylindrical-polar coordinates is given by

$$\mathbf{E}\_{\mathsf{L},2}(R\_{\perp}, \Phi, Z) = \mathbf{e}\_{\mathsf{L},2} E\_{0\mathsf{L},2} f\_{G\mathsf{L},2}(R\_{\perp}) e^{i\left(\Theta\_{\mathsf{L},2}(\mathsf{R})\right)},\tag{1}$$

$$\mathbf{E}\_{\ell p}(\mathsf{R}\_{\perp}, \Phi, Z) = \mathbf{e}\_3 E\_{03} \xi\_{\ell p} \left(\frac{\sqrt{2}}{w\_{03}}\right)^{|\ell|} f\_{LG3}(\mathsf{R}\_{\perp}) \mathbf{e}^{i(\Theta\_{\mathbb{R}}(\mathbf{R}))},\tag{2}$$

where

$$f\_{G1,2}(R\_\perp) = e^{-\frac{\hbar^2\_\perp}{w^2\_{\text{01},2}}},\tag{3}$$

$$f\_{LG3}(R\_\perp) = R\_\perp^{|\ell|} e^{-\frac{R\_\perp^2}{w\_{03}^2}} L\_p^{|\ell|} \left(\frac{2R\_\perp^2}{w\_{03}^2}\right),\tag{4}$$

$$
\Theta\_{1,2}(\mathbf{R}) = \mathbf{k} \cdot \mathbf{R}, \tag{5}
$$

and

$$
\Theta\_3(\mathbf{R}) = \ell \rho + \mathbf{k}\_3 \cdot \mathbf{R}.\tag{6}
$$

Here ei, w0i, and ki are the polarization, beam waist at z = 0, and wave vector of the ith excitation laser field, respectively. The electric field amplitudes E0i are connected to the laser intensity Ii via E0i = √(2Ii/cε0), where c is the speed of light and ε0 is the vacuum permittivity. In Eq. (2), ℓ corresponds to the optical orbital angular momentum, the mode index p represents the number of radial nodes of LG qffiffiffiffiffiffiffiffiffiffiffiffiffi 2p! j j beam, ξℓp ¼ is the normalization constant, and L ℓ is the Laguerre poly- πðpþj j ℓ Þ p nomial. The last excitation LG beam propagating along the z-direction in the plane of the focus of the beam appears as rings with radius Rl that is scaled linearly to the optical angular momentum and proportional to the beam waist [78]. The polarization ei determines the particular transition conditions happened in ith laser beam. The appearance of the polarization vector ei depends explicitly upon the choice of

coordinate orientation. In the basis of eσ, where σ = {1, �1, 0} corresponds to the right circular, left circular, and linear polarization vector attached to the quantization axis z in xyz frame, the ei are given by

$$\mathbf{e}\_{i}(\theta\_{i},\rho\_{i}) = \sum\_{\sigma} s\_{i\sigma}(\theta\_{i},\rho\_{i})\mathbf{e}\_{\sigma} \tag{7}$$

where siσðθi; φiÞ is the relation coefficient and φi is the azimuthal angle of respective polarization according to Figure 2(b).

The ith laser excitation beam carries linear momentum ℏki, and spin angular momentum �ℏ per photon relates to the excitation laser polarization, if circularly polarized, while the last LG beam with an azimuthal phase dependence exp (ilϕ) in addition to linear and spin angular momentum carries orbital angular momentum that can be many times greater than the spin [49]. The combination of energy selectivity, associated with the laser light frequency, and sublevel selectivity, associated with polarization as well as angular momentum of light beam, provides good controls and manipulation over the qudits in quantum information processing.


Contents

### **Preface XIII**

X Contents

Contents VII

Chapter 17 **Polynomial Response Surfaces for Probabilistic**

Sergey Oladyshkin and Wolfgang Nowak

**Risk Assessment and Risk Control via Robust Design 317**

#### Chapter 17 **Polynomial Response Surfaces for Probabilistic Risk Assessment and Risk Control via Robust Design 317**  Sergey Oladyshkin and Wolfgang Nowak

VI Contents

Chapter 7 **Theories and Methods for**

Chapter 8 **Absorption and Accumulation of**

**the Emergency Rescue System 121** Jianfeng Li, Wenmao Liu and Bin Zhang

Hong Ge, Emmy Camada and Yao Yiping

**Evaluation at Nanoscale Levels – A Way Forward in Ecotoxicological Studies 167**

Chapter 10 **Polysystemic Approach to Risk Assessment 185**

Chapter 11 **Risk Assessment in the Anaesthesia Process 205**

**Endurance Time and the Corresponding**

Yuh-Chuan Shih and Yo-May Wang

**Pyrolysis Facility Designs for City of**

Philippe Côte and Fréderic Bretar

**Tools from Paper to Electronic 281**  Daniel Bergeron and Kristiina Hyrkäs

**Calibrating Risk Assessment Models 297**  Michael S. Williams, Eric D. Ebel, Jennifer A. Hoeting

**Konin, in Poland, Using SimLab® Toolpack 245**

**Diagnosis and Monitoring of Dikes and Dams 263**  Yannick Fargier, Cyrille Fauchard, Patrice Mériaux, Paul Royet, Sergio Palma-Lopes, Daniel François,

**Section 3 Risk Assessment in System Design 243**

Chapter 13 **Risk Analysis of the Waste to Energy**

Boguslaw Bieda

Chapter 14 **Methodology Applied to the**

Chapter 15 **Transforming Risk Assessment**

and James L. Withee

Chapter 16 **A Bayesian Approach for**

**Section 2 Risk Assessment in Human Health 165**

Chapter 9 **Non-Invasive Matrices Use in Pollution**

Chapter 12 **Effects of Wearing Gloves and Sex on**

**Heavy Metal Pollutants in Roadside Soil-Plant**

**Systems – A Case Study for Western Inner Mongolia 157**  Lu Zhanyuan, Zhi Yingbiao, Wang Zai-lan, Hua Yupeng,

Melinda Haydee Kovacs, Dumitru Ristoiu and Cezara Voica

Mikhail Karganov, Irina Alchinova and Nadezhda Khlebnikova

**Finger Skin Temperature During a Cold Immersion 229**

Valérie Neyns, Ophélie Carreras, Laurie Planes and Jean-Marie Cellier

Preface

human health protection.

environment and human health.

This book compiles chapters written by researchers who focus on the development and application of risk assessment approaches in various subjects of hydrology, water

Risk assessment is a critical component in the evaluation and protection of natural or anthropogenic systems. Conventionally, risk assessment is involved with some essential steps such as the identification of problem, risk evaluation, and assessment review. Other novel approaches are also discussed in the book chapters. This book is compiled to communicate the latest information on risk assessment approaches and their effectiveness. Presented materials cover subjects from environmental quality to

It's the editor's expectation that the chapters enclosed in this book will provide helpful information for risk assessment in both academic and industrial fields, and encourage the development and implementation of relevant applications for the protection of

**Yuzhou Luo, Ph.D.**

USA

University of California (Davis)

Department of Land, Air and Water Resources

quality, human health, and industrial designing.