Codes to predict zero claims:
sum(exp(-predict(Model.poi, DataValid, type = "response")))
sum(1-predict(Model.log, DataValid, type = "response"))
sum(predict(Model.zeropoi, DataValid, type = "prob")[,1])
```
#### **References**

Murphy, Kevin P. 2012. *Machine Learning—A Probabilistic Perspective*. Cambridge: The MIT Press.

c 2019 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).


• Oklahoma MESONET

The Oklahoma MESONET is an automated network of over 110 remote, meteorological stations across Oklahoma (http://www.mesonet.org). The surface types are predominantly grassland/wooded, grassland/cropland. In 1999, infrared temperature (IRT) sensors (Apogee Instruments, Inc.) were installed at 89 of the MESONET sites. A combination of automated and manual tests was applied using simultaneous soil and atmospheric measurements to inter-compare observations and ensure that the skin temperature observations are of research quality [44]. The measurements collected by the MESONET provided a unique opportunity to inter-compare observations. Fiebrich et al. [45] provide an evaluation of 5-min-resolution field measurements collected using the sensors. This sensor was chosen for use because it is water resistant and was designed for continuous outdoor use. Sensor accuracy is approximately ± 0.2 ◦C from 15 ◦C to 35 ◦C and 0.3 ◦C from 35 ◦C to 45 ◦C. The sensor is installed at a height of 1.5 m and has a field of view of a diameter circle of 0.5 m. The energy detected by the sensor is converted to a temperature using the Stefan–Boltzmann law and an assumed surface emissivity of 1.0. Slight underestimation is caused because the true emissivity of the land surface is less than 1.0. In addition, slight overestimation is caused by reflected longwave radiation from the target [46]. While surface reflection of downwelling longwave radiation is ignored, Sun et al. [32] discussed the effects of these two factors and found that the total effect may be a slight underestimation of the skin temperature. Generally, estimated impact of uncertainty in relevant parameters on in situ LST are as follows: radiometric calibration uncertainty of ±0.2 to 0.5 K can impact LST as much as 0.2 K; emissivity uncertainty of ±1% can impact LST by as much as 0.3 K; downwelling atmospheric radiance uncertainty of ±10% can impact LST by as much as 0.1 K [47].

#### *2.7. Cloud Detection*

For cloud masking, various ancillary data are needed such as surface type, snow-free channel-1 radiance, and a pixel position information, all in the same dimension and location as the satellite images. The land cover data used in this study for cloud screening implementation, are generated at 1-km resolution [48]. This product includes 14 International Geosphere–Biosphere Programme (IGBP) classes and the underlying surface types are aggregated according to the IGBP classification.

A Coupled Cloud and Snow Detection Algorithm (CCSDA) that was developed initially for use with GOES-8 satellite is adjusted as appropriate for each GOES satellite is used. The algorithm is described in [49,50]. Variants of the approach were tested and evaluated in several publications [51]. In the case of the GOES-8 imager four channels were used to detect clouds, snow, and to perform background analysis for each hour of the diurnal cycle. Beginning with GOES-12, Channel 5 is no longer available (Table 1) [52].

The CCSDA algorithm is capable of producing its own snow analysis using an algorithm that applies three tests using three GOES channels. Alternatively, there is a switch to allow the use of a snow analysis from a different source. The advantage of using the snow analysis generated by the CCSDA algorithm is that it is updated hourly, which provides a more accurate analysis of the expected background when applying the cloud tests. If a daily snow analysis is used, the snow conditions cannot change for each hour of the cloud analysis, and this may introduce error.

In Table 2 we present a description of the cloud screening tests used for GOES-8, along with an explanation of how the tests are assembled to determine a clear probability.

**Table 2.** Cloud Screening Tests for GOES-8.

Note: Reflectance Gross Contrast Test (RGCT); Channel-2 Albedo Test (C2AT); Thermal Gross Cloud Test (TGCT); Three Minus Five Test (TMFT); Four minus Five Test (FMFT); Uniform Low Stratus Test (ULST); Cirrus IR Test (CIRT).

The ultimate clear probability (*P*) can be assembled in various ways on the basis of individual test results. In this method:

$$P = \sqrt[n]{\prod\_{1}^{n} P\_{i}} \tag{7}$$

*Pi* is the clear probability from each individual cloud screening test and n is the total number of cloud screening tests. This assembly method guarantees that the target pixel is cloudy (*P* = 0) if any individual test identifies it as cloudy (*Pi* = 0). Otherwise, it compiles the confidence levels from all of the individual tests to obtain an overall clear probability.

Referring to Table 2, there was only one cloud screening test that required Channel 5, namely, the FMFT test. In the cloud screening algorithm for GOES-12 and beyond, the FMFT test will not be used, and the test assembly method described for GOES-8 is implemented with one less cloud test.

For each cloud test, threshold levels are used to differentiate between clear and cloudy pixels. For each new satellite, it is necessary to test the thresholds and modify as needed. Here, the cloud mask method applies two spatial tests and one threshold test on an 11–3.7 µm difference image. This fourth test compares the temperature from the 11 µm channel to a 20-day clear-sky composite of 11 µm temperatures, and labels the pixel as cloudy if the difference is greater than the threshold. The pixel level data were gridded to 0.05◦ and compared to the Pathfinder Atmospheres—Extended (PA TMOS-X) product [34]. Agreement above 95% for various times of the day was found. The only region which showed slight disagreement between the two independent cloud masks is over areas of complex terrain in the Western US, but even over these regions the two cloud masks agreed over 85% of the time.

The major difference between the day time and night time algorithms (Table 2) is that there are no Reflectance Gross Contrast Test (RGCT, when visible channel is missing) and Channel-2 Albedo Test (C2AT) during the night time. This will mostly affect the detection of reflective clouds. For GOES-12, the FMFT test could not be used. We have tested the cloud screening algorithm for use at nighttime. We applied the nighttime algorithm on daytime data and compared to results when the full daytime algorithm is used. Evaluation of LST estimates in each case is presented in Figure 1. As this figure shows, the daytime algorithm provides better agreement with ground observations than the nighttime one yet, the differences are small as illustrated in Figure 1.

ିଵ

− − − −

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**Figure 1.** Evaluation of LST for 2004 against a SURFRAD/BSRN station at Desert Rock, NV (DRA) for: Left: daytime; Right: nighttime. (௦ ) ௦ ↑ ↓

1

1

#### **3. LST Retrieval Algorithm Development for GOES Satellites**

Satellite observed radiance *R* ↑ *o* , can be expressed as

$$R\_o^\uparrow = \varepsilon B(T\_s) \mathcal{X} + R\_a^\uparrow + (1 - \varepsilon) R\_a^\downarrow X \tag{8}$$

where ǫ is surface emissivity, *B*(*Ts*) is blackbody emission at surface temperature *Ts* , *X* denotes the atmospheric transmittance, *R* ↑ *a* and *R* ↓ *a* are atmospheric emission to space and surface, respectively. With known surface emissivity and simulated atmospheric emission and transmittance, the surface temperature can be retrieved

$$T\_s = B^{-1} \left[ \frac{1}{\epsilon} \left( \frac{1}{X} \left( R\_o^\uparrow - R\_a^\uparrow \right) - (1 - \epsilon) R\_a^\downarrow \right) \right] \tag{9}$$

where *B* −1 denote the inverse of Planck function for GOES-12 channel 4.

Here, the approach is based on the Radiative Transfer for TOVS (RTTOV) model v11.2 [53–55] adjusted for the GEO characteristics and driven with MERRA-2 reanalysis fields. The CAMEL data are also implemented in the method. The advantage of this approach is that it is consistent with the retrieval approach used at JPL to generate the MOD21 product [56]. The processing sequence is described in Figure 2.

**Figure 2.** Flow-chart describing the derivation of LST from GOES observations.

Data processing sequence starts from raw digital counts from GOES satellites. Calibration is applied to all channels. Channel 4 (10.2 to 11.2 um) was used for LST retrieval. All channels except channel 3 (6.7 um) were used in the cloud detection algorithm. After cloud screening, GOES observations were resampled to a uniform grid of 0.05◦ resolution. The atmospheric radiation and transmittance were simulated with the RTTOV model using MERRA-2 fields as input. The MERRA-2 fields were first temporally interpolated to satellite observation time and then collocated to satellite locations. RTTOV calculated upwelling, downwelling radiances and atmospheric transmittance combined with CAMEL surface emissivity to retrieve the LST according to Equation (11).

#### **4. Evaluation of GOES-E Based LST Estimates**

We will present results of evaluation for UMD LST retrievals against MOD11 products, the BSRN/SURFRAD network over the USA, the ARM/SGP C1 site over the Southern Great Plains, and the MESONET network over Oklahoma. The issue of evaluation of satellite products of LST against ground measurements is complex, primarily, due to scale issues and known large spatial variability of LST. A comprehensive discussion on all aspects of validation issues are described by Guillevic et al. [43] and Göttsche et al. [57].

#### *4.1. Scale Issues Related to Satellite and Ground Observations*

The ground observations are point observations while the satellite LST product is at pixel level gridded to 0.05◦ . To assess the homogeneity of each site, we use the ASTER Global Emissivity Dataset at 1-km V003 (DOI: 10.5067/Community/ASTER\_GED/AG1km.003) available for the period of 2000–2008. It is based on observations from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Emissivity Dataset (GED) land surface temperature and emissivity data products using the ASTER Temperature Emissivity Separation (TES) algorithm with a Water Vapor Scaling (WVS) atmospheric correction method with MODIS MOD07 atmospheric profiles and the MODTRAN 5.2 radiative transfer model. The spatial distribution of the emissivity values is illustrated in Figure 3a and their frequency distribution is shown in Figure 3b. As shown, except for the DRA site, the 0.05◦ boxes show a high degree of homogeneity at the 1-km scale. As seen from Figure 3b, the emissivity values range between 0.965–0.980 with two distinct peaks of 0.965 and 0.975 with some lower values (0.948) at the DRA site. As also shown in the study of Hulley and Hook [58], who compared ASTER emissivity band 11 (8.6 µm) at 90 m spatial resolution to the same at 1 km, the agreement was very good. The spatial matching of ground and satellite observations is done by taking the weighted average of the pixels that fall in the cell box (0.05◦ × 0.05◦ ) around the target location of the station. The time matching is done by taking the averages of ±15 min around the start scanning time of GOES12 (this interval is selected based on the duration of the satellite scan).

**Figure 3.** (**a**) Spatial characterization of the sites used in evaluation of the LST products in terms of emissivity as obtained at 1 km spatial resolution using the ASTER Global Emissivity Dataset 1 km V003. (**b**) Frequency distribution of the emissivity values over sites used in evaluation as illustrated in Figure 3a.


**Abstract**

This study aimed to analyze the effect of incorporating different concentrations (10, 20 and 30% (w/w)) of the brown seaweed *Macrocystis pyrifera* into white maize tortillas in terms of chemical composition, color, texture, phenolic compounds, and antioxidant capacity. The moisture and lipid content decreased with the addition of seaweed, while the ash, protein and fiber content increased. The changes in carbohydrates were not significant (p > 0.05). The concentration of Na, K, Mg, and P increased significantly (p < 0.05) with the incorporation of the alga. Higher percentage of seaweed led to *masa*s and tortillas with greener tones as it affected L\*, a\*, b\* parameters, hue and chroma and to bigger differences between the control samples and the samples with seaweed. Total phenolic content increased linearly with the incorporation of seaweed, as well as FRAP values. While the *masa* with 20% of seaweed showed the highest percentage of ABTS inhibition (86%). Finally, the control sample of *masa* presented the lowest values of adhesiveness and hardness, while the control sample of tortilla showed the highest hardness value.

**Keywords:** seaweed, *Macrocystis pyrifera*, white maize, tortilla, mineral profile, texture profile analysis, antioxidant capacity


**Abstract**

This study examined information literacy, metacognitive abilities and selfconcept capabilities. The evaluation of this research indicated that self-concept is the totality of psychological, emotional, psychosomatic and mental development that provide confidence to individual in the ability to search, use, appraise and assess information resources, which are critical qualities needed to enable information literacy; an individual needs to be conscious and develop aptitude to identify useful information. Metacognitive ability is important because of the age of information overload which an individual is overwhelmed with which signified that information available is exceeding processing capacity of an average individual. Accordingly, once information overload ensues, it is possible that a decrease or decline in quality of decision-making will happen. In view of this, metacognitive ability becomes necessary in order to equip people with the critical ability to contemplate rigorously before action is taken. The objective of this research is to embark on content analysis of the subject matter of information literacy, metacognitive abilities and self-concept in which existing research was thoroughly evaluated in order to identify gap in research and bring out new knowledge. This research uses qualitative content analysis as a method of data collection in which existing journals and other information resources were evaluated. Research has been silenced on the triangular relationship of metacognitive ability, self-concept and information literacy, that is, the gap this research attempt to bridge.

**Keywords:** information literacy, self-concept, metacognitive ability, information overload, information access


**1. Introduction**

Recent trends in modern economies are focused on greenhouse gas emissions reduction and mitigation of climate change effects. Countries around the world have begun to shift their energy production to renewable energy sources (RES). Energy from renewable sources may help mitigate emissions from traditional fossil fuel energy generation [1]. Implementation of EU energy policy requires investment in power technologies based on RES. The dynamics of RES development and application can be traced to the basis of its installed capacity. According to data from 2016 [2], the highest increase of installed power was observed for wind farms (i.e., 12,490 MW, or 51% of all new installed capacity in EU) and solar energy power plants (i.e., 6700 MW, or 27.4% of all new installed capacity in EU). By 2040, RES-based EU technologies will constitute 80% of new installed power, while after 2030, wind energy is predicted to become the leading electrical energy source [3]. Wind energy, with significant growth in the RES share it represents, will cause problems associated with an uneven generation of electrical energy, resulting from variable atmospheric conditions [4]. Frequently, high electricity generation is possible during periods of low demand for electrical energy (e.g., days off), whereas during periods of higher demand (evening peak), production is much lower. Moreover, the use of renewable energy from solar and wind farms is connected with power transmission system problems because of the irregularity and instability of energy supply [5,6].

Accordingly, a significant development in energy storage technology is required to increase application of RES in electrical energy generation sector. Power-to-Gas is an example of such technology. By using this technology, electrical energy can be converted to gaseous fuel (hydrogen). Hydrogen as an energy carrier can store the largest quantities of energy and has high energy content per mass unit [4]. This makes hydrogen technology very advantageous from a technological point of view [7]. Hydrogen has great importance as a promising green energy carrier, but practically does not occur in nature freely, hence it is not the primary source of energy. Hydrogen is usually generated as a secondary energy carrier from primary sources such as natural gas or wind energy. Hydrogen will play an important role in the world energy mix in the future [8].

Requirements regarding the proportion of renewable energy sources in national electricity systems have been described in Directive 2009/28/EC. The general objective of achieving a 20% content of RES usage by 2020 in the European Union was included in this statement [7,9]. Most of the power generated in the field of renewable energy sources was comprised of onshore and offshore wind farms. Therefore, for the further development of renewable energy usage in the power generation sector, it will be necessary to make progress in the use of energy storage technologies. The use of hydrogen as an energy storage technology allows the largest amount of energy storage and is distinguished by having the highest power output. Thus, this technology is very beneficial in technical terms [10–12]. In the near future, the natural gas system will be used for transmission of the growing volume of alternative fuels (e.g., hydrogen and biomethane), which will be added to traditional natural gas mixtures.

Recently, projects and concepts for the construction of energy storage sites in salt caverns have been the main focus related to the development of renewable energy sources. Hydrogen obtained during the withdrawal of salt caverns has to be transported to the place of its utilization. Pipeline transmission of hydrogen and the possibility of hydrogen addition to the natural gas transmission system are still new solutions requiring further research, and have been confirmed by real applications in a small number of cases. Specific thermodynamic analysis of methane–hydrogen mixtures is a main novelty of this research, in particular the use of hydrogen to improve natural gas flow parameters in the pipeline while maintaining quality requirements.

#### **2. Basics of Hydrogen Transmission**

Hydrogen is presented as an effective energy carrier which can be used efficiently with minimum greenhouse gas emissions in the processes in which it is involved [13]. The use of hydrogen in the long term for the purpose of balancing energy production with the demand of the electrical energy market is a real solution to the problem of excessive amounts and shortages of energy on the market. Hydrogen is used for storing surplus electrical energy. Salt caverns, as an efficient source of hydrogen storage, provide good conditions for injection and production [14–17]. Salt caverns are located in sites which have specific geological conditions; therefore, in many cases hydrogen must be transported across long distances from the storage site. The idea of energy storage in salt caverns with the use of hydrogen is presented in Figure 1. Over recent years the pipeline transport of hydrogen has been considered mainly as an integral and significant element of the renewable energy system [18]. On the other hand, the industrial use of hydrogen is widespread, where the production of hydrogen is closely associated with specific technological processes. Hydrogen is transmitted through pipelines of various diameters and lengths, depending on the way in which hydrogen will be used. Pipeline transmission is one of the cheapest methods for transporting large quantities of hydrogen [19,20]. Pipelines for the transmission of hydrogen at long distances exist in a few places worldwide, with a total length of 4500 km.

**Figure 1.** Scheme of hydrogen energy storage processes.

Hydrogen is commonly considered a gas similar to methane (i.e., the main component of natural gas). Therefore, most technological requirements for hydrogen transmission pipelines are identical to those of natural gas pipelines, with certain modifications regarding safety, infrastructure, and materials. These conditions must be met before the transmission of hydrogen is initiated through a pipeline network. Hydrogen has its specific set of physical and chemical properties which makes the pipeline transmission of this gas significantly different from that of natural gas. Due to physicochemical properties, hydrogen pipeline transmission is much more difficult than natural gas. Even compressed hydrogen can provide only about a third of the energy when compared to methane per unit of volume [21].

Natural gas transport and distribution networks are very well developed; therefore, the hydrogen pipeline system is directly compared to the natural gas transmission system [22]. The natural gas system consists of gas compression stations, pipelines, gas stations and gas storage facilities, including caverns [23]. The gas compression station provides the energy needed to generate gas flow at a given rate and pressure. In the case of natural gas, gas networks are divided into high pressure transmission pipelines and medium or low-pressure distribution pipelines. In the case of hydrogen transmission, the distribution to smaller receiving centers worldwide is quite rare, excepting some locations, such as the Leuna industrial district in Germany. In most cases, hydrogen transportation is considered as a transmission from point A to point B, for a technologically justified purpose. Selected issues related to hydrogen pipeline transmission have been presented recently in a number of papers [24–29].

#### **3. Model Development**

#### *3.1. Basic Assumptions*

The hydraulic analysis of hydrogen transmission through the pipelines was based on a number of technological assumptions (e.g., mass flow rate from 0.3 to 3.0 kg/s, which corresponds to volume flow rate from 12,000 Nm3/h to 120,000 Nm3/h). The recommended outlet pressure for an exemplary technological installation was assumed to be 24 bar (g). In the presented exemplary case, the medium inlet temperature was set at 5 ◦C and the ambient temperature was 15 ◦C. For heat flow analysis, the pipeline was located one meter deep. The length of the exemplary pipeline chosen for analysis was 100 km.

#### *3.2. Hydraulic Friction Factor*

The zone of turbulent flow in rough pipes consists of a transient flow zone and developed roughness zone. In the transient flow zone, the linear friction coefficient (*λ*) depends on the Reynolds number (*Re*) and relative roughness (*ε*): *λ = f*(*Re, ε*). Colebrook and White presented the following formula for the linear friction coefficient *λ* in this zone [30]:

$$\frac{1}{\sqrt{\lambda}} = -2\lg\left(\frac{2.51}{Re\cdot\sqrt{\lambda}} + \frac{\varepsilon}{3.71}\right) \tag{1}$$

The Colebrook-White Equation (1) was systematically analyzed from a theoretical and experimental point of view and, as a result, considered to be the most accurate of all relationships determining *λ* coefficient in the transient flow zone. For the zone with a full roughness impact *λ = f*(*ε*)*,* the linear friction coefficient is analyzed with the Prandtl-Nikuradse Equation (2) [31]:

$$\frac{1}{\sqrt{\lambda}} = -2\lg\frac{\varepsilon}{3.71} \tag{2}$$

Equation (2) was established by Prandtl, based on experiments conducted by Nikuradse on pipes with artificial sand roughness. The Prandtl–Nikuradse equation could be used on the following assumed criterion:

$$\text{Re}\cdot\varepsilon\cdot\sqrt{\lambda}\geq200\tag{3}$$

#### *3.3. Pressure Drop Analysis*

The pressure drop in gas pipelines can be determined with one of the hydraulic equations commonly applied for high pressure gas pipelines (e.g., Renouard equation, Panhandle equation). In this paper, authors applied the General Flow Equation (4), directly derived from the Bernoulli equation [32]:

$$p\_1^2 - p\_2^2 = 7.569 \cdot 10^5 \cdot ZT\_{in} L d\lambda \cdot \left(\frac{p\_b}{T\_b}\right)^2 \cdot \frac{Q\_n^2}{D^5} \tag{4}$$

where *p*1*, p*2*—*pressure at respectively inlet and outlet of pipeline, *Z—*compressibility factor, *Tin—*temperature in pipeline, *L—*length of pipeline, *d—*relative density, *Qn—*volume flow rate, *D—*inner diameter.

The difference of levels on a given pipeline section has a significant impact on the flow hydraulics. In pressure drop equations, the influence of terrain elevation change is accounted for with the use of an equivalent length of the pipeline *Le*, which is the pipeline length corrected for the impact of terrain elevation with respect to the level of initial point of the pipeline or pipeline section [32].

$$L\_{\varepsilon} = \frac{L(\exp(s) - 1)}{s} \tag{5}$$

where *s—*dimensionless parameter which determines the influence of terrain elevation, which depends on temperature (*T*), compressibility factor (*Z*), relative density (*d*) and elevation level difference (Δ*h*).

Dimensionless parameter which describes the terrain elevation impact is defined as:

$$s = 0.0684d \left(\frac{\Delta h}{T \cdot Z}\right) \tag{6}$$

If a pipeline of length *L* is divided into a number of sections (i.e., *L*1*, L*2*, L*3, etc.) in which the terrain level significantly changes, then the parameter *j* should be introduced in such a way that the impact of the terrain elevation could be determined for each segment of the pipeline.

$$j = \frac{\exp(s) - 1}{s} \tag{7}$$

In this case, the pipeline equivalent length *Le* accounts for the effect of the terrain elevation for each pipeline section with the dependence:

$$L\_{\mathfrak{c}} = j\_1 L\_1 + j\_2 L\_2 \exp(s\_1) + j\_3 L\_3 \exp(s\_2) + \dots \tag{8}$$

#### *3.4. Temperature Changes along the Pipeline*

The temperature change basic model as a function of pipeline length was determined with the dependence combining the total heat transfer coefficient (*U*), mass flow rate ( • *M*) and isobaric heat capacity (*Cp*) [32]:

$$\int\_{T\_{in}}^{T(\mathbf{x})} \frac{dT\_{in}}{T\_{in} - T\_{out}} = \int\_{0}^{L\_{f}} \frac{\mathbf{U} \cdot \boldsymbol{\pi} \cdot \boldsymbol{D} \cdot d\mathbf{x}}{\mathbf{M} \cdot \mathbb{C}p} \tag{9}$$

For a pipeline with length *L* and diameter *D*, with the Joule–Thomson effect (*μJT*) change of temperature of the transmitted medium from *T*1 to *T*2 can be described with the equation [33]:

$$T\_2 = T\_{out} + (T\_1 - T\_{out}) \exp\left(\frac{-L \cdot IL \cdot \pi \cdot D}{\bullet}\right) + \frac{M}{\pi \cdot L \cdot D} \left(\mu\_{fT} \cdot \mathbb{C} \, p \cdot \frac{dp}{dL}\right) \left(1 - \exp\left(\frac{-L \cdot IL \cdot \pi \cdot D}{\bullet}\right)\right) \tag{10}$$

#### *3.5. Heat Transfer Analysis*

The basic principles of heat transfer analysis were formulated with heat flow laws based on conduction (Fourier law), convection (Newton law), and radiation (Stefan–Boltzman law) in association with the first law of thermodynamics. Conduction and convection are most the most important parameters for the heat flow transferred to the pipeline. Conduction, described with the Fourier law (according to cylindrical coordinates) for a pipeline in dynamic conditions, has the following form [34]:

$$\frac{1}{r}\frac{\partial}{\partial r}\left(k\cdot r\frac{\partial T}{\partial r}\right) = \rho\cdot\mathbb{C}p\frac{\partial T}{\partial \tau} \tag{11}$$

where *r*—radius, *k*—thermal conductivity, *ρ*—density, *τ*—time, *Cp*—isobaric heat capacity.

Under static conditions, the right side of Equation (11) equals zero; therefore, the total heat flow per unit of length of the pipeline between the medium within the pipeline and the environment is

$$Q = -2\pi r \cdot L \cdot k \frac{\partial T}{\partial r} \tag{12}$$

After integration of Equation (12), we have

$$Q = \frac{2\pi r \cdot L \cdot k \cdot (T\_n - T\_{n+1})}{\ln\left(\frac{r\_{n+1}}{r\_n}\right)}\tag{13}$$

The most important parameter which determines the ability of a particular cylindrical obstacle to heat transfer is the heat transfer coefficient (*U*). Taking into account convection and conductivity effects for a pipeline with complex parameters, the heat transfer coefficient equals [34,35]

$$LI = \frac{1}{\frac{1}{a\_{in}} + \frac{r\_{in}}{k\_p} \ln\left(\frac{r\_{out}}{r\_{in}}\right) + \frac{r\_{in}}{k\_{iso}} \ln\left(\frac{r\_{in}}{r\_{out}}\right) + \frac{r\_{in}}{k\_{ground}} \ln\left(\frac{2\underline{z}\_x}{r\_{iso}}\right) + \frac{r\_{in}}{\underline{z}\_x a\_{out}}} \tag{14}$$

In order to determine the heat transfer in the presented case (Figure 2), the thermal conductivity coefficient was analyzed for the pipeline wall (*kp*), thermal insulation (*kiso*), and ground in which the pipeline was buried (*kground*). *Rin* and *Rout* represent the inner and outer radius of the pipeline, respectively. *riso* is the radius including thermal insulation, and *zx* is the depth of pipeline deposition in the ground. Convection effects are described by *αin*—inner coefficient of heat penetration (assumed or determined with, for example, the Dittus–Boelter formula) and *αout*—outer coefficient of heat penetration defined with Equation (15) for a pipeline seated in the ground at a depth *zx* [35]:

$$\kappa\_{out} = \frac{2 \cdot k\_{\text{ground}}}{D\_{tot} \cdot \ln\left[\frac{2z\_x + \sqrt{4z\_x^2 - D\_{tot}^2}}{D\_{tot}}\right]} \tag{15}$$

where *Dtot* is the total diameter of pipeline with thermal insulation.

Calculations of the overall heat transfer coefficient for pure hydrogen and pure methane as a function of the pipeline diameter are presented in Figure 3. Other parameters, for example, thermal insulation or burial depth of the gas pipeline, have remained unchanged. Calculations were made for the same volume flow rates in three variants specified in the presented case (12,000 Nm3/h, 40,000 Nm3/h, 120,000 Nm3/h). Obtained results are similar for methane and hydrogen for assumed volume flow rates.

**Figure 2.** Cross section of an exemplary pipeline.

**Figure 3.** Overall heat transfer coefficient as a function of pipeline inner diameter for different flow rates of pure methane and pure hydrogen.

The final equation for total heat flux has the following form:

$$Q = \frac{2\pi r\_{in}L\left(T\_{in} - T\_{out}\right)}{\frac{1}{a\_{in}} + \frac{r\_{in}}{k\_p}\ln\left(\frac{r\_{out}}{r\_{in}}\right) + \frac{r\_{in}}{k\_{iso}}\ln\left(\frac{r\_{ins}}{r\_{out}}\right) + \frac{r\_{in}}{k\_{ground}}\ln\left(\frac{2\varepsilon\_s}{r\_{ins}}\right) + \frac{r\_{in}}{z\_s a\_{out}}}\tag{16}$$

#### *3.6. Real Gas Behavior and Thermodynamic Parameters Description*

Thermodynamic parameters of transmitted hydrogen and methane/hydrogen mixtures as real gas are calculated with the Peng–Robinson equation of state commonly applied in the oil and gas industry [36]:

$$p = \frac{RT}{v - b\_{\rm m}} - \frac{a\_{\rm m}}{v(v + b\_{\rm m}) + b(v - b\_{\rm m})} \tag{17}$$

The parameters of the equation of state *am* and *bm* are based on classic mixing rules. They depend on the critical parameters of the analyzed gas. Compressibility factor *Z* is determined on the basis of a polynomial form of the Peng–Robinson equation of state:

$$Z^3 + (B-1)Z^2 + (A - 3B^2 - 2B)Z + (B^3 + B^2 - AB) = 0\tag{18}$$

where *A* and *B* are dimensionless parameters of equation of state, depending on the present temperature and pressure conditions:

$$A = \frac{a\_m p}{R^2 T^2} \tag{19a}$$

$$B = \frac{b\_m p}{RT} \tag{19b}$$

The compressibility factor is a key parameter while determining the pressure drop in the pipeline, and changes in most of the thermodynamic parameters of the analyzed gas as well as changes in temperature is a function of the pipeline length. Another important parameter is the density of the transmitted gas, which is determined with the general form of the equation of state:

$$
\rho = \frac{p}{ZRT} \tag{20}
$$

Equation (10) also makes use of specific heat capacity at a constant pressure (*Cp*) and the Joule–Thomson coefficient (*μJT*), which have a significant impact on temperature changes of the transmitted hydrogen [37,38]:

$$\begin{cases} \mathbb{C}p = \mathbb{C}p\_{id} + \mathbb{C}p\_r = \mathbb{C}p\_{id} + R \cdot \left( T \left( \frac{\partial Z}{\partial T} \right)\_p + Z - 1 \right) + \frac{T \frac{d\_{\rm m}}{dT} - a\_{\rm m}}{2\sqrt{2}b\_{\rm m}} \cdot \\\ \left[ \frac{\left( \frac{\partial Z}{\partial T} \right)\_p + (1 + \sqrt{2}) \left( \frac{\partial B}{\partial T} \right)\_p}{Z + (1 + \sqrt{2})B} - \frac{\left( \frac{\partial Z}{\partial T} \right)\_p - (\sqrt{2} - 1) \left( \frac{\partial B}{\partial T} \right)\_p}{Z - (\sqrt{2} - 1)B} \right] + \frac{T \frac{d\_{\rm m}^2}{dT^2}}{2\sqrt{2}b\_{\rm m}} \cdot \ln \left( \frac{Z + (1 + \sqrt{2})B}{Z + (1 - \sqrt{2})B} \right) \end{cases} \tag{21}$$

where *Cpid—*isobaric heat capacity for ideal gas, *Cpr*—residual part of isobaric heat capacity.

The Joule–Thomson coefficient can be expressed with specific heat capacity at constant pressure:

$$\mu\_{JT} = \frac{1}{\mathbb{C}p} \left[ T \left( \frac{\partial v}{\partial T} \right)\_p - v \right] \tag{22}$$

Using the real gas Law (18), Equation (22) can be written as

$$\mu\_{fT} = \frac{1}{\mathbb{C}p} \left[ \frac{T}{Z \cdot \rho} \left( \frac{\partial Z}{\partial T} \right)\_p \right] \tag{23}$$

where

$$
\left(\frac{\partial Z}{\partial T}\right)\_p = \frac{\left(\frac{\partial A}{\partial T}\right)\_p (B - Z) + \left(\frac{\partial B}{\partial T}\right)\_p \left(6BZ + 2Z - 3B^2 - 2B + A - Z^2\right)}{3Z^2 + 2(B - 1)^2 + (A - 2B - 3B^2)}\tag{24}
$$

In the case of hydrogen, the description of the Joule–Thomson effect has a special meaning. Unlike for natural gas, the Joule–Thomson coefficient for hydrogen is negative, which means that hydrogen temperature increases with isenthalpic expansion.

#### *3.7. Pipeline Diameter Selection*

Prior to the hydraulic analysis of the pipeline, the optimum diameter of the pipeline should be determined for parameters such as assumed working pressure, length of the pipeline, roughness, etc. The selection of the diameter is also important for determination of the inlet pressure to the pipeline (includes associated costs) and possibility to compress the medium. In the analyzed case, the diameter was determined with a function of inlet pressure at the beginning of the pipeline for the assumed outlet pressure at the end of the pipeline of 24 bar (g). Calculations were based on the General Flow Equation (4), which directly stems from the Bernoulli law. The presented equation also contains an element (Δ*h*) referring to the change of the elevation of the pipeline with respect to the assumed reference level [32,39]:

$$D = \sqrt[5]{\frac{16\lambda \cdot Z^2 \cdot R^2 \cdot T^2 \cdot L \cdot \dot{M}^2}{\pi^2 \cdot \left(Z \cdot R \cdot T \cdot \left(p\_1^2 - p\_2^2\right) - 2 \cdot g \cdot P\_{av}^2 \cdot \Delta h\right)}}\tag{25}$$

Calculations were performed for pure hydrogen (Figure 4) and methane/hydrogen mixtures with a maximum hydrogen content of 15% mol (Figure 5).

It should be noted that from the perspective of mass flow rate, the recommended diameters for the pure hydrogen are much smaller than for methane/hydrogen mixtures, which results from the low mass of hydrogen (Figures 4 and 5).

The recommended diameters for the methane/hydrogen mixture are much larger, as the density of pure hydrogen under normal conditions equals 0.0898 kg/m3, while the density of a mixture of methane and 15% hydrogen is 0.6223 kg/m3.

Recommended pipeline diameters for the assumed flow rates of pure hydrogen and methane/(15%)hydrogen mixtures are presented in Table 1. Evidently, transmission of the same volume of methane in a mixture with 15% hydrogen content required much larger diameters.

**Table 1.** Recommended pipeline diameters for pure hydrogen and methane/hydrogen mixture transmission.

**Figure 4.** Diameter calculation for pure hydrogen pipeline as a function of pipeline inlet pressure.

**Figure 5.** Diameter calculation for methane–hydrogen (15%) mixture pipeline as a function of pipeline inlet pressure.

#### **4. Calculation Results**

Flow modeling in a hydrogen transmission pipeline covers the analysis of changes in pressure and temperature as a function of length of the pipeline. The changes of compressibility factor, density, specific heat, and the Joule–Thomson effect as parameters especially important for hydrogen pipeline transmission were presented for one of the variants. A comparative analysis was also performed for the methane/hydrogen mixture and mass flow rate of 40,000 Nm3/h.

#### *4.1. Pressure Drop*

The profiles of pressure and temperature changes for recommended pipeline diameters, assumed mass flow rates of 0.3, 1.0, 2.0 and 3.0 kg/s, (volume flow rates: 12,000 Nm3/h, 40,000 Nm3/h, 80,000 Nm3/h and 120,000 Nm3/h) and hydrogen inlet temperature of 5 ◦C are presented in Figures 6–9. Results of modelling the pressure drop profiles confirmed the preliminary calculations of the pipeline diameter. For the smallest recommended diameters for a selected flow rate, the inlet pressure in the pipeline was from 6.01 to 6.76 MPa (Figures 6–9), while for the largest recommended diameters the inlet pressure ranged from 2.91 to 3.2 MPa (Figures 6–9). The analysis of temperature changes revealed that the transmitted hydrogen warms up more slowly for smaller diameters and higher flow rates.

**Figure 6.** Pressure (*p*) (continuous lines) and temperature (*T*) (dashed lines) changes for hydrogen mass flow rate of 0.3 kg/s (12,000 Nm3/h) and different diameters.

**Figure 7.** Pressure (*p*) (continuous lines) and temperature (*T*) (dashed lines) changes for hydrogen mass flow rate of 1.0 kg/s (40,000 Nm3/h) for different diameters.

**Figure 8.** Pressure (*p*) (continuous lines) and temperature (*T*) (dashed lines) changes for hydrogen mass flow rate of 2.0 kg/s (80,000 Nm3/h) for different diameters.

**Figure 9.** Pressure (*p*) (continuous lines) and temperature (*T*) (dashed lines) changes for hydrogen mass flow rate of 3.0 kg/s (120,000 Nm3/h) for different diameters.

#### *4.2. Thermodynamic Parameters Analysis*

The analysis of selected thermodynamic parameters, such as density, flow rate, compressibility factor, isobaric heat capacity and Joule–Thomson coefficient were presented for hydrogen transmission at a flow rate of 40,000 Nm3/h (1.0 kg/s). Figure 10 illustrates the changes in hydrogen density and its flow rate as a function of pipeline length for selected pipeline diameters.

**Figure 10.** Density (*ρ*) (continuous lines) and flow velocity (*w*) (dashed lines) changes for hydrogen mass flow rate 1.0 kg/s (40,000 Nm3/h).

The density change is directly connected to compressibility factor *Z* change, as presented in Figure 11. Compressibility factor *Z* for hydrogen is higher than unity even for relatively low pressure values. This is one of the most characteristic properties of hydrogen, which distinguishes it from most of the real gases. For instance, compressibility factor *Z* > 1 for natural gas is usually only at pressures equal or greater than 40 MPa.

**Figure 11.** Compressibility factor changes for hydrogen mass flow rate 1.0 kg/s (40,000 Nm3/h).

Another characteristic parameter of hydrogen is the Joule–Thomson coefficient. The Joule–Thomson effect occurs in temperature change of the gas during isenthalpic pressure drop. For most real gases, the Joule–Thomson effect is positive (i.e., gas temperature decreases with pressure reduction). In the case of hydrogen (Figure 12), the opposite effect occurs (i.e., the Joule–Thomson coefficient is negative): with a rapid change in pressure, the hydrogen temperature increases. This is theoretically possible for the hydrogen transmission pipelines, with considerable pressure drops per unit of pipeline length (e.g., with pipeline diameters which are too small or very high flow rates).

**Figure 12.** Isobaric heat capacity (*Cp*) (continuous lines) and Joule–Thomson coefficient (*μJT*) (dashed lines) changes for hydrogen mass flow rate 1.0 kg/s (40,000 Nm3/h).

#### *4.3. Methane-Hydrogen Mixtures*

Hydrogen can also be transmitted through natural gas pipelines as an additive to natural gas. This is one of the alternative methods of hydrogen transportation. Numerous analyses and studies devoted to this issue have been performed recently [21,29,40]. Hydrogen has different thermodynamic parameters compared to methane, which is the main component of natural gas. This causes significant changes in the flow conditions of natural gas that contains hydrogen. Industrial practice and scientific publications indicate that the maximum admissible molar fraction of hydrogen in a mixture with natural gas should not exceed 15%. The maximum hydrogen content in the natural gas transmission system suggested in the United States should be in the range of 5%–15%. Several European countries have introduced limits on the content of hydrogen in natural gas pipeline systems from 0.1% to 12% by volume. The maximum hydrogen content usually depends on the technical conditions for a given pipeline [41]. Hydrogen significantly influences natural gas transmission conditions. The basic advantage is lowering the pressure drop of natural gas transmitted with a hydrogen admixture, and possibility to transmit natural gas across longer distances without additional gas compression stations. Unfortunately, the hydrogen content in natural gas significantly deteriorates the energy parameters and calorific value of natural gas. The changes in higher heating value (HHV) and lower heating value (LHV), calorific value of the mixture, and Wobbe index as a function of hydrogen content in the methane mixture are presented in Figure 13.

**Figure 13.** Changes of higher heating value (HHV), lower heating value (LHV) and Wobbe indexes as a function of hydrogen molar fraction in mixture with methane.

The pressure and temperature changes as a function of pipeline length for a mixture of methane and 15% hydrogen transmitted at a flow rate of 40,000 Nm3/h are presented in Figure 14 for three recommended pipeline diameters. The change in thermodynamic parameters was also analyzed as a function of molar fraction of hydrogen in the mixture for a 250 mm diameter.

**Figure 14.** Pressure (*p*) (continuous lines) and temperature (*T*) (dashed lines) changes for methane–15% hydrogen mixture mass flow rate of 6.93 kg/s (40,000 Nm3/h) for different diameters.

This analysis of the hydrogen molar fraction in the hydrogen/methane mixture confirms the effect of pressure drop in the analyzed pipeline. The required inlet pipeline pressure, for a 15% hydrogen content in the gas mixture, is approximately 10% lower when compared to pure methane (Figure 15). An increase in hydrogen molar content caused the temperature of the analyzed gas mixture to more rapidly approach the ambient temperature. On the other hand, the Joule–Thomson effect for methane caused slight cooling of the analyzed mixtures, and for pure hydrogen this effect did not take place.

The variability of analyzed thermodynamic parameters of a methane/hydrogen mixture as a function of hydrogen molar fraction is shown in Figures 16–18. The analyzed mixtures contained a maximum 15% of hydrogen; studies and practice have shown that this amount of hydrogen in the methane or natural gas mixture does not significantly affect the transmission parameters of the pipeline. However, it should be noted that a change in density is important: it can be altered by up to 20% for a 15% content of hydrogen in the mixture when compared to pure methane. Apart from a considerable lowering of density, the Joule–Thomson effect is also lowered with an increase in hydrogen content. With increased hydrogen content, its specific heat also increases for a unit of mass due to the high calorific value of hydrogen per unit of mass. The compressibility factor has been also observed to grow significantly. The addition of hydrogen improves to some extent the natural gas transmission conditions by pressure drop reduction in the pipeline. However, hydrogen content above 15%–20% in the gas mixture significantly influences the calorific value of natural gas. The change in thermodynamic conditions with an increased hydrogen content may also affect the natural gas transmission system (i.e., gas compression stations or gas reduction stations). Another important issue is selection of the material for pipeline construction in light of the hydrogen corrosion case [42], which affects the cost of its construction [20,43].

**Figure 15.** Pressure (*p*) (continuous line) and temperature (*T*) (dashed line) changes as a function of hydrogen content in mixture with methane and pipeline length.

**Figure 16.** Density (*ρ*) (continuous lines) and flow velocity (*w*) (dashed lines) changes as a function of hydrogen content and pipeline length.

**Figure 17.** Isobaric heat capacity (*Cp*) (continuous lines) and Joule–Thomson coefficient (*μJT*) (dashed lines) changes as a function of hydrogen content and pipeline length.

**Figure 18.** Compressibility factor changes as a function of hydrogen content and pipeline length.

#### **5. Discussion**

Hydrogen pipeline transmission analysis discussed an example of 100 km long pipeline and the required outlet pressure of 24 bar (g). Pressure drop and temperature change profiles were determined for selected pipeline diameters and mass flow rates from 0.3 to 3.0 kg/s, which corresponds to volume flow rates from 12,000 to 120,000 Nm3/h of hydrogen. An analogous analysis has been performed for a mixture of methane and hydrogen with a maximum hydrogen content of 15%. Due to the fact that hydrogen has a significantly lower mass than methane, the pipeline transmission of methane and hydrogen mixtures requires larger pipeline diameters for similar volume flow rates. On the basis of the determined profiles of pressure and temperature changes in the pipeline, a detailed analysis of thermodynamic parameters was performed. This analysis was important from a hydrogen and methane–hydrogen mixture pipeline transmission perspective. In particular, the analysis included density, flow velocity, isobaric heat capacity, the compressibility factor, and Joule-Thomson coefficient. The last two parameters, which significantly affect the conditions of transport, are specific to hydrogen. Hydrogen has negative values of Joule-Thomson coefficient and the compressibility factor value exceeds 1.0 in the range of relatively low pressures. Due to different thermodynamic parameters, the hydrogen content in a mixture with methane causes significant changes in natural gas pipeline transport conditions. The most important change is the reduction of pressure drop, which allows an increase in the distance at which it is possible to transport the assumed volume of natural gas. Significant differences also occur in the temperature change profiles in the pipeline, as the hydrogen content reduces the positive Joule-Thomson effect for natural gas. It should be noted that in the simulation it was assumed that full heat transfer between the transported gas and the ambient environment may occur. The molar fraction of hydrogen in a mixture with natural gas may have a beneficial influence on the conditions of its transmission. However, hydrogen content should not exceed 15%–20% in the mixture. With a hydrogen content above 20% in the mixture with methane, the higher heating value (HHV) drops below 35 MJ/Nm3; thus, natural gas loses its calorific value (below values described by norms and standards), even though the upper Wobbe index remains within accepted norms.


**3. Design and synthesis of boron-containing agents for boron neutron capture therapy (BNCT)**

#### **3.1 General**

As described in the Introduction, BNCT is one of the powerful cancer treatment methods utilizing two heavy particles, 4 He and 7 Li, which are produced from 10B by a neutron capture reaction [10B (n, α) 7 Li] and induce the damage of biomolecules such as DNA, RNA, and so on within a short range of 5–9 μm [4–8]. For this BNCT to be achieved, the development of cancer-specific 10B carriers is urgently needed. To date, *Design, Synthesis, and Biological Applications of Boron-Containing Polyamine and Sugar… DOI: http://dx.doi.org/10.5772/intechopen.105998*

**Figure 12.** *Structures of representative BNCT agents.*

only two boron compounds, namely disodium mercaptoundecahydrododecaborate (BSH) **23** and L-4-boronophenylalanine (BPA) **24** (used as a complex with D-fructose), have been approved for use as BNCT agents in clinical settings (**Figure 12**) [31, 32], but they are not sufficiently effective for the treatment of various tumor types. Because more selective and more efficient BNCT agents are required, the design and synthesis of new boron carriers based on sugar and macrocyclic polyamine scaffolds were conducted.


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**9.1 Glenohumeral bone defects**

42 Modern Arthroscopy

Following surgery, the arm is placed in a sling in slight abduction and reduced internal rotation. Passive external rotation is restricted to 0 degrees. Active flexion and extension of the elbow is encouraged. After 3 weeks, the sling is discontinued, forward flexion is increased and external rotation is allowed to 30 degrees. Isotonic rotator cuff and scapular muscles strengthening is initiated after the 6th week. The return to unrestricted activity and full contact sports is determined on an individual basis and usually is not anticipated until 4

The most common complication is the recurrence of instability, which may be attributed to diagnostic and technical errors, or to additional trauma. Misdiagnosis may occur when a significant glenohumeral bone loss is not properly evaluated or a multidirectional component escapes diagnosis. Inadequate capsular tensioning and restoration of the glenoid concavity are the commonest technical errors met. It is therefore crucial to reassess range of motion and humeral head alignment after the repair. In athletes, the risk of recurrence increases with return to sports, since the demands placed on the shoulder are analogous to

Hardware failure commonly involves misplacement of the suture anchors. Absorbable implants have reduced the occurrence of late anchor displacement and complications during revision surgery. However proper anchor placement is mandatory and a careful evaluation should be performed whenever symptoms appear. Osteopenia along the glenoid rim has been correlated with absorbable anchors along with disuse during the

Nerve injury is not common. Structures at risk, however, include the axillary nerve that lies 1-1.5 cm below the inferior glenohumeral capsule and the musculocutaneous nerve situated 5-8 cm below the coracoid. Manipulation at the extremes of the range of motion should be

A recent concern after arthroscopic instability repair has been chondrolysis (Levine et al, 2005). Although rare, it is devastating because it often requires additional surgery and

**8.7 Postoperative management and rehabilitation**

Fig. 11. Final view of the re-approximated capsulolabral complex.

to 6 months.

**8.8 Complications**

postoperative period.

avoided.

those that caused the initial injury.

Studies have shown that compression fractures of the posterior superior humeral head (Hill-Sachs lesion) can occur in 32% to 51% of initial anterior dislocations, while anteroinferior glenoid deficiency in 22% of primary dislocations (Rowe et al, 1978; Rowe et al, 1984). The incidence of both glenoid and humeral head bone defects approaches 100% in cases of chronic anterior shoulder instability (Burkhart and De Beer 2000).

A critical decision on shoulder stabilization today focuses on the degree of bone loss and whether soft tissue reconstruction can be successful. Diagnostic pearls for clinical and imaging evaluation of glenohumeral bone defects have been discussed above. Bone defects between 20% and 30% of the inferior glenoid have shown a high recurrence rate after arthroscopic Bankart repair. However, the size and orientation of glenoid and humeral head defects can be extremely variable, making preoperative assessment and decision making difficult. It is currently suggested that patient with glenoid bone deficiency exceeding 20 to 25% of the articular surface should better be treated with a bone-substituting procedure (Provencher et al, 2010).

Bone grafting procedures, such as iliac bone-block or distal tibia transfer, glenoid allograft augmentation and the Bristow procedure have been advocated to restore osseous glenoid defects and shoulder stability. The Latarjet procedure was introduced in 1954. It delineates an osteotomy of the coracoid just proximal to its angle, which comprises the horizontal part of the coracoid and provides a 2 to 3cm bone segment. This is then transferred along with the attached conjoined tendon and the released coracoacromial ligament through a horizontal division of the subscapularis tendon and fixed at the antero-inferior glenoid, preferably with two screws (Fig 12).

The Latarjet procedure has shown excellent and reliable results both in biomechanical testing and the clinical setting. Quantitative Computed Tomography (qCT) has shown this technique to adequately restore a mean defect of up to 28% the intact inferior glenoid (Hantes et al, 2010). Compared with a structural bone graft, it resulted in significantly less anterior and anteroinferior translation at 60° of abduction. Satisfactory clinical results have also been reported with shoulder function ranging from good to excellent with recurrence rates between 0% and 7%. Complications include bony nonunion, graft displacement, progressive impingement and hardware loosening or migration. Improper graft placement, due to lack of experience or surgical exposure, may predispose to recurrent dislocation (when placed too medially or high) or osteoarthritis (too laterally).

Arthroscopic Treatment of Recurrent Anterior Glenohumeral Instability 45

Significant humeral Hill-Sachs lesions also raise concerns on the success of soft-tissue instability repairs. There is a debate on what size humeral head defects require treatment with bony reconstruction. Some authors suggest that defects involving over 12.5% of the humeral head diameter should raise concerns as potentially significant lesions (Kropf et al, 2007). Open allograft humeral head or autograft transfer reconstructions are indicated for the treatment of engaging Hill-Sachs lesions through deltopectoral or mini-open approaches. The Latarjet procedure has also been used successfully in such cases. Recently, an arthroscopic "remplissage" technique was introduced consisting of an arthroscopic capsulotenodesis of the posterior capsule and infraspinatus tendon to fill the Hill-Sachs lesion (Purchase et al, 2008). In light of such progress, glenohumeral bone loss should no

longer be considered an absolute contraindication for arthroscopic instability repair.

Arthroscopic treatment of shoulder instability has evolved considerably over the past decades. A detailed patient history and thorough physical examination are still considered the milestones for successful treatment planning. Advanced MRI imaging has offered a more accurate diagnosis and improved understanding of the pathology to be addressed. Presently, suture anchor stabilization is the operation that best duplicates the time-tested open procedure. Patient selection criteria, improved surgical techniques and implants available have contributed to the enhancement of clinical and functional outcomes to the point that arthroscopic treatment is considered nowadays the standard of care. However, arthroscopic techniques are demanding and there is a steep learning curve. Bone loss issues, including Hill-Sachs and glenoid rim lesions, remain a concern and a challenge for

Abrams, J. S. (2007). Role of arthroscopy in treating anterior instability of the athlete's

Bigliani, L. U., R. Kelkar, et al. (1996). Glenohumeral stability. Biomechanical properties of

Boileau, P., M. Villalba, et al. (2006). Risk factors for recurrence of shoulder instability after

Bokor, D. J., V. B. Conboy, et al. (1999). Anterior instability of the glenohumeral joint with

Bottoni, C. R., E. L. Smith, et al. (2006). Arthroscopic versus open shoulder stabilization for

Bottoni, C. R., J. H. Wilckens, et al. (2002). A prospective, randomized evaluation of

traumatic, first-time shoulder dislocations. *Am J Sports Med* 30(4): 576-580. Burkhart, S. S. and J. F. De Beer (2000). Traumatic glenohumeral bone defects and their

humeral avulsion of the glenohumeral ligament. A review of 41 cases. *J Bone Joint*

recurrent anterior instability: a prospective randomized clinical trial. *Am J Sports*

arthroscopic stabilization versus nonoperative treatment in patients with acute,

relationship to failure of arthroscopic Bankart repairs: significance of the inverted-

passive and active stabilizers. *Clin Orthop Relat Res*(330): 13-30.

arthroscopic Bankart repair. *J Bone Joint Surg Am* 88(8): 1755-1763.

shoulder. *Sports Med Arthrosc* 15(4): 230-238.

**10. Conclusions**

arthroscopists to manage.

*Surg Br* 81(1): 93-96.

*Med* 34(11): 1730-1737.

**11. References**

Routinely, the Latarjet procedure is performed through a standard deltopectoral approach. However, an all-arthroscopic alternative has been advocated recently as a consequence of the success of the open procedure and the advancements in arthroscopic instrumentation and techniques. This procedure offers the potential advantages of more accurate graft placement, management of associated joint pathology, such as bidirectional shoulder instability, ease of technique conversion, and faster rehabilitation with decreased joint stiffness and better cosmetic result (Lafosse et al, 2010). Although there is inevitably a steep learning curve, excellent results with good graft positioning and minimal complications have also been reported with arthroscopic Latarjet repair.

Fig. 12. The Latarjet procedure. Notice how the coracoid process graft supplements the articular surface of the original "inverted pear" glenoid to increase its anteroposterior diameter.

Significant humeral Hill-Sachs lesions also raise concerns on the success of soft-tissue instability repairs. There is a debate on what size humeral head defects require treatment with bony reconstruction. Some authors suggest that defects involving over 12.5% of the humeral head diameter should raise concerns as potentially significant lesions (Kropf et al, 2007). Open allograft humeral head or autograft transfer reconstructions are indicated for the treatment of engaging Hill-Sachs lesions through deltopectoral or mini-open approaches. The Latarjet procedure has also been used successfully in such cases. Recently, an arthroscopic "remplissage" technique was introduced consisting of an arthroscopic capsulotenodesis of the posterior capsule and infraspinatus tendon to fill the Hill-Sachs lesion (Purchase et al, 2008). In light of such progress, glenohumeral bone loss should no longer be considered an absolute contraindication for arthroscopic instability repair.


**Abstract**

Malaria remains one of the most important and deadliest diseases in many countries in Africa, in the Americas, in South-East Asia, in the Eastern Mediterranean and in the Western Pacific regions, with high morbidity and mortality, despite important successes for the control of this disease borne by the vector *Anopheles* mosquitoes. Malaria elimination relies on different strategies including early diagnosis, improved drug therapies and better health infrastructure, and mainly the use of longlasting insecticidal nets (LLINs) and indoor residual sprayings (IRS) of insecticide. In Cameroon, a country composed of several ethnic groups, malaria transmission is endemic in some regions, while it is seasonal in others; children and pregnant women are most vulnerable. Progress has been made towards malaria control, considering these specificities, and led to a reduction in both morbidity and mortality, but these accomplishments are under threat, mainly due to the development of resistance to insecticides among mosquitoes, targeting the 4 commonly used insecticide classes. To continue our route towards malaria control and elimination, it is urgent to have more knowledge about resistance mechanisms, in the objective of elaborating new strategies with the involvement of the community; these strategies should take into consideration socio-ecological factors such as the young age of the population, low literacy rate especially among women, population's beliefs, traditions, and customs. Forest ecosystems with abundant rains, humidity and hot temperature, lower access to water for populations living in rural areas, and poverty level are other factors to consider when elaborating malaria control approaches.

**Keywords:** Malaria, Anopheles, vector resistance, sociology, novel strategies, insecticides, community, research, social change


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#### **Chapter 10**


**Author details**

Leila Martina Passerino Rafaela Research and Transfer Centre (UNRaf-CONICET), Santa Fe, Argentina

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*Breast Cancer, Gender, and Body Experience – A Qualitative Study in Argentina on the Transit… DOI: http://dx.doi.org/10.5772/intechopen.109502*

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*5.2. Minor Infections*

Children with recurrent and severe infections present a diagnostic challenge [67]. Four or more ear infections and two or more serious sinus infections or episodes of pneumonia within one year are warning signs for primary immunodeficiencies in children [68].

Secretory IgA plays an important role in maintaining the equilibrium of the body, as it takes part in the mucosal immune system and serves as the interface between the body and the microbiome. In the human body, the largest mucosal systems are the gastrointestinal tract and respiratory system, and therefore, decreased level of IgA will affect mostly them.

Symptomatic patients with minor infection usually present recurrent upper respiratory tract infections (40–90%), mainly viral, less frequently bacterial (with encapsulated bacteria etiology, such as Streptococcus pneumoniae, Hemophilus Influenzae) [7,8,69,70]. Bacterial bronchitis and pneumonia are much less common, but these infections may be complicated by bronchiectasis [71]. Infections of the ear, sinuses, conjunctiva, nose, and throat mucosa may occur. Most often, these infections are mild, not requiring hospitalization and their treatment does not differ significantly from the treatment of a patient without sIgAD. It was found that patients with sIgAD have a compensatory increase in secretory IgM level [9,72], however, these IgM cannot replace all functions of IgA [73]. In the intestines of sIgAD patients, there is 65–75% of Ig-containing plasma cells with the ability to produce IgM in comparison to about 6% in healthy volunteers, possibly due to the homology in structure and function between those two isotypes [74–77]. Besides, patients with sIgAD suffer from urinary tract infections (UTI) and gastrointestinal tract infections with viruses and bacteria. Moreover, intermittent or chronic diarrhea due to Giardia Lamblia is common, because the attachment and proliferation of this parasite on the gastrointestinal mucous are facilitated due to lack of IgA [78,79]. It is important to mention that in patients with recurrent UTI, bronchitis and pneumonia, defects in the urinary and respiratory systems should be excluded.

The diagnosis of selective IgA deficiency mostly does not significantly influence the therapeutic management of patients. Treatment of infections should be adequate to their etiology, patient's age, and clinical condition. Treatment of comorbidities and prevention of complications remain the basis. There are no clear guidelines that would suggest the need for longer and more aggressive antibiotic therapy in this disease than in patients without sIgAD. There is also no consensus on the use of antibacterial prophylaxis in this immunodeficiency, but its usage was suggested in more severe cases, at least periodically [34,48,80]. Vaccinations play a significant role in minimizing the risk of infections [48]. It is advisable to extend the standard calendar with vaccination against *S. pneumoniae*, *N. meningitidis*, *H. influenzae,* and annual vaccination against influenza [34]. It is not typically recommended to initiate IgG (i.v, s.c) replacement therapy in patients without the

coexistence of other immune-related diseases, acute, severe infections, or coexistence of specific antibodies deficiency [81]. According to one of the latest meta-analyses covering the effects of oral probiotics, parabiotics, and synbiotics on immunoglobulin levels, it has been shown that their supplementation increases significantly salivary IgA secretion, without a significant effect on the level of other immunoglobulins and with no effect on the serum IgA [82]. In addition, there are reports of an increase in the amount of IgA+ cells in the intestines of lamina propria in mice after oral ingestion of Lactobacillus-based preparations [83,84]. One prospective, randomized study demonstrated the validity of the use of oral immunomodulator bacterial extract (OM-85 BV) in patients with sIgAD and/or IgG subclass deficiency, resulting in a lower one-year infection rate [85]. A suggestion has been made to use oral IgA in patients with sIgAD, since this deficiency is associated with dysbiosis and chronic inflammation, and the present inflammation is inversely correlated with systemic anticommensal IgG response, which acts as "second line of defense" [86,87].

The importance of the IgA was raised again because of the ongoing global pandemic of coronavirus disease 2019 (COVID-19). When looking for the reasons for the varied course of the disease, questions arose on whether deficiency of IgA could be the reason for disease severity, vaccine failure, and prolonged viral shedding [88]. As mentioned above, the prevalence of sIgAD differs in various countries and the same was found for COVID-19. Naito et al. compared the number of cases of COVID-19 with the prevalence of selective IgA deficiency in different countries [89]. They found "a strong positive correlation between the frequency of sIgAD and the COVID-19 infection rate per population". It was then concluded that one of the factors contributing to the low death rate from COVID-19 infection in Japan could be the low incidence of sIgAD in the country. As primary immunodeficiencies are a group of rare diseases, there is little data on the coexistence of sIgAD and COVID-19 infection. Nevertheless, literature data showing an extremely significant effect of class A immunoglobulins on early protection against SARS-CoV-2 virus also suggest a potentially more severe/complicated course of the disease [88,90]. This thesis is supported by the aforementioned literature data: a positive correlation between a high number of COVID-19 infections and a high incidence of sIgAD has been demonstrated, and an inverse relationship was observed in the extreme example of Japan [88]. In Israel, during two "so-called" waves, 20 patients with PID were affected by COVID-19 and none of them was diagnosed with sIgAD [91]; importantly, the relationship between the development of autoimmune diseases in the course of COVID-19 in patients with sIgAD—AIHA and Guillain-Baree syndrome [92]. Researchers also point to the risk of a poor response against SARS-CoV-2 after immunization in this group of patients [88].

#### *5.3. Autoimmunity*

There is an association between IgA deficiency and a higher prevalence of autoimmune disease [93,94]. Based on extended research in that field, the prevalence of autoimmune disease in this group rises to 31.7% [95]. According to Azizi et al. the median age of the onset of the first episode of autoimmunity was 7 [95]. Among diseases with higher prevalence in sIgAD subjects, we differentiate systemic lupus erythematosus, hypo- and hyperthyroidism, type 1 diabetes mellitus, Crohn's disease, ulcerative colitis, rheumatoid arthritis, juvenile idiopathic arthritis, ankylosing spondylitis, and vitiligo. Whereas other diseases like scleroderma, celiac disease, autoimmune hepatitis, immune thrombocytopenic purpura, and autoimmune hemolytic anemia, occur less often but still with higher prevalence than in the general population [96].

The mechanism of autoimmunity in sIgAD is still not fully understood. There are six hypotheses that try to explain these phenomena, each based on a different mode of autoimmunity, such as human leukocyte antigen, cytogenic, monogenic, molecular mimicry, lingering inflammation and immune complexes, dysregulation of molecular pathways [96]. Some studies suggest that various mechanisms are likely to play concurrently. It has been found that there is also a higher incidence of autoimmunity in first-degree relatives of sIgAD patients [97].

In a recent case reported by Pfeuffer et al., authors stated that the presence of other acute diseases could induce autoimmunity in SIgAD patients [98]. In their case, it was Guillain-Barré syndrome induced by COVID-19.

#### *5.4. Allergy*

Allergy has long been a component of immune deficiency; however, allergic burden differs in different types of immunological disorders. Both PID and allergy are associated with impaired reactions of the immune system. In the case of PID, malfunctioning of some of its components will lead to infectious susceptibility. Atopy, on the other hand, is a hypersensitivity reaction of the immune system and a form of misdirected immunity.

The true prevalence of allergy among patients with sIgAD is still under debate since studies from different countries present inconsistent results. Therefore, it suggests that the prevalence varies depending on the ethnic background. There is even controversy in the scientific world whether the coexistence of IgA deficiency and allergic diseases is, in fact, true. Most publications support the relationship between sIgAD or low-IgA levels and allergic diseases [10,99–103], but some researchers deny it [104,105]. This connection has been the subject of medical research for over 50 years. In 1975, Buckley suggested that about half of the patients with sIgAD presented atopic diseases and related findings have been published later by Kemola [106,107]. A similar observation has been done in Ankara more recently, in 2017, where 45.7% of the patients diagnosed with sIgAD presented one of the following: asthma, rhinitis, eczema, atopic dermatitis, and interestingly the prevalence of allergy in a close family of this patients rose up to 43.2% [101]. Aghamohammadi, in his study on Iranian patients, revealed that allergy was observed in 84% of patients with sIgAD [10]. In a study from China, 17.6% of patients had allergic symptoms, however, most of them were allergic reactions to drugs (mostly penicillin) [108]. These results were inconsistent with typical allergies reported in other countries, such as asthma, rhinitis, food allergy, and atopic dermatitis [108]. On the other hand, there is a study with a prevalence of allergy in children with sIgAD on the percentage of 13% [70].

Many clinicians point out the frequent coexistence of IgA deficiency with bronchial asthma, allergic rhinitis, and atopic dermatitis in everyday practice but it is unclear whether it is the immunoglobulin A deficiency that promotes an allergic reaction, or the allergic reaction weakening the mucous membranes and consequently leading to a secondary IgA deficiency. There are plenty of possible explanations of this phenomenon. The connection between IgA deficiency and allergies may be caused by increased levels of circulating antigens, due to increased permeability at mucosal surfaces. It could also be a result of the inability to induce ITAMi signaling, due to decreased level of monomeric serum IgA, which, consequently, causes overactivation of the immunological system [79,109]. Another hypothesized mechanism is the deficiency of TGF-beta response. TGF-beta has properties to induce IgA synthesis, as well as inhibiting proliferation of Th2-cells. Th2-response is involved in the pathogenesis of atopic diseases [110–112]. Interestingly, there are allergenspecific A immunoglobulins, but their role in the pathogenesis of allergic diseases is unclear [113]. We do not know whether they are responsible for exacerbation or silencing the symptoms, but what we know is that they are observed in healthy people without allergic symptoms and low or undetectable IgE-levels [114,115]. Moreover, children with a tendency to allergic diseases have a more pronounced physiological IgA deficiency in the neonatal period and the lower these concentrations are, the greater is the severity of symptoms (although they usually remain within the reference values for age).

The American Academy of Allergy, Asthma & Immunology (AAAAI) and the American College of Allergy, Asthma & Immunology (ACAAI) developed practice parameters to guide the management of primary immunodeficiencies [116]. It is stated there that atopic diseases should be treated aggressively in patients with sIgAD. Since allergic inflammation facilitates the development of respiratory tract infections, it is crucial to treat allergy using all standard modalities, like avoidance of allergens, medication, and immunotherapy [116]. Our clinical experience shows that treating atopic diseases in patients with immunodeficiency is difficult and requires special attention and scrupulousness. In addition to the commonly used anti-histamine drugs, beta-mimetics, and glucocorticosteroids, in the case of treatment-resistant atopic diseases, biological drugs such as omalizumab and dupilumab might be helpful. Omalizumab is an anti-IgE antibody that is FDA approved for the treatment of moderate to severe allergic asthma, while dupilumab is an IL-4 receptor blocking antibody and is FDA approved for the treatment of moderate to severe atopic dermatitis in patients with the refractory disease [117–119]. The use of omalizumab in a young adult patient diagnosed with CVID, who suffered from chronic spontaneous urticaria, and did not respond either to an immunoglobulin substitution in immunomodulatory doses, anti-H1 and anti-H2 antihistamines, as well as leukotriene receptor antagonists, has been described. Only the inclusion of omalizumab resulted in a significant improvement in the condition of the skin and quality of life [120]. However, data suggest that such treatment could carry a risk of possible side effects—Banh et al. described a case of a 24-year-old patient diagnosed with asthma and CVID, where treatment with omalizumab might have increased the level of white blood cells and elevated myeloid cell count. Serious disorders, e.g., malignancy or severe infections were excluded. Importantly blood test results returned to normal levels shortly after drug discontinuation [121]. The use of dupilumab has been described in the context of a patient with CVID suffering from severe skin lesions such as erythematoussquamous and generalized infiltrated rash with exacerbation in sun-exposed zones and severe recurrent infections, in whom no improvement in skin condition was observed after treatment with glucocorticoids or cyclosporine. The introduction of dupilumab resulted in a reduction in the severity of skin lesions and the addition of IgG replacement therapy lowered the frequency of infections [122]. In our opinion, based on experience from other immunodeficiencies with predominantly antibody deficiency, it is possible to use the above-mentioned monoclonal antibodies in the treatment of severe allergic complications in patients with SIgAD.