**9. The composition of freezing extenders**

A number of substances have been added to boar semen during cryopreservation in order to improve FT sperm quality. It has been investigated that egg yolk added to boar semen could protect sperm acrosomes during cold shock and hence reduce cryodamage of FT boar sperm [61]. Protection has been claimed to be due to both phospholipids and the low density lipo‐ protein fraction in egg yolk [62,63]. The mechanism of action is unclear but could be mediat‐ ed by either a less intense cellular dehydration or by stabilization of the sperm plasma membrane [51].

Cryoprotective agents (CPAs) have been divided into those that penetrate the cell and those which remain extracellular. Glycerol considered as penetrating agents and other non-pene‐ trating agents such as various sugars have been evaluated for cryoprotective effect in boar sperm [64,65]. Glycerol in low concentrations (3 to 4%) has been utilized in various techni‐ ques of sperm cryopreservation [47,66]. At these concentrations, glycerol gives maximum post-thaw viability and also in vitro fertilizing capacity of sperm [43]. Both post-thaw motili‐ ty and acrosome integrity of boar sperm would be decreased when glycerol concentration reached 5%. Glycerol and other penetrating agents could improve FT sperm survival by penetrating sperm and reduce the shrinkage of the cells developed during cooling [8]. They could also lower the freezing point of extra-cellular fluid via action of non-penetrating CPAs [67]. Therefore, the damage of sperm from the formation of intracellular ice occurred during freezing is reduced.

The success of the boar sperm cryopreservation was dramatically increased when the deter‐ gent Sodium Dodecyl Sulphate (SDS; later known as Equex STM paste) was included in the cryopreservation protocol [68,69]. The addition of SDS to semen extenders decreases freezethaw damage to sperm in several species, including boar [70-72]. Pursel and co-workers stat‐ ed that the use of 0.5% Orvus Es Paste, a commercial preparation of SDS, in the BF5 extender significantly enhanced the preservation of fertilizing capacity concomitant with an increase in post-thaw percentages of normal acrosome morphology and motility of boar sperm [69]. The beneficial effect of SDS on the sperm membrane is not fully understood, but it has been suggested that its protective effect is mediated through a change in the extending medium, by solubilization of the protective lipids in the egg yolk contained in the extenders. This effect enhanced the cold shock resistance of sperm [73,74]


*3.1. Coastline Changes*

The average annual horizontal coastline change rates for 2010–2020 ranged from over −25 to +15 m/yr (Figure 4). Erosion rates increased alongshore in the same direction as the

littoral drift (east–west). The only exceptions to the predominant erosive regime occurred on the westernmost segment of the study area where accretion rates larger than +10 m/yr were identified. Localized accretion was also observed on the east side of the mouth of the CGSM and next to two groins built west of the coastal town of Ciénaga in the early 2010s (see white and green colors in Figure 4).

**Figure 4.** Coastline changes (m/yr) as derived from DSAS for the period 2010–2020.

From the mouth of the CGSM to the 20th km, erosion ranged between −1 and −10 m/yr (see pink and yellow transects in Figure 4). This erosion peaked along the stretch between the 20th km and La Atascosa lagoon (orange and red transects in Figure 4) and reached local average values up to −25 m/yr. Erosion rates progressively decreased westward from this lagoon and changed to accretion west of the El Torno lagoon (see green colors in Figure 4), where a levee, built at the mouth of the Magdalena River, hampers the westerly movement of sediment. The most significant erosion rate values for 2010–2020 occurred seaward of La Atascosa lagoon. Upon inspection of the imagery, it was observed that this largest average erosion rate was produced from the migration of an inlet after a breach of the lagoon in 2016.


**AORTIC VALVE SURGERY**

Edited by **Noboru Motomura**

**INTECHOPEN.COM**

http://dx.doi.org/10.5772/1787 Edited by Noboru Motomura

#### **Contributors**

Bilal Kaan INAN, Mustafa Sacar, Gokhan Onem, Ahmet Baltalarli, Edward Chen, Bradley Leshnower, Feruz Fathullaevich Turaev, Al. Karaskov, S. Zheleznev, M. Paz Sanz Ayan, Francisco Miguel Garzon Marquez, Carmen Urbaneja Dorado, Delia Diaz Zamudio, Jose Luis Valdivia Gallegos, Alberto Forteza Gil, Antonio Martinez Salio, Glaucio Furlanetto, Beatriz H. S. Furlanetto, Dominik Wiedemann, Nikolaos Bonaros, Alfred Kocher, Dimosthenis Mavrilas, Efstratios Apostolakis, Petros Koutsoukos, george matalanis, William Y. Shi, Michael O'Keefe, Anne Meddahi-Pellé, Emmanuel Lansac, Isabelle Di Centa, Maguette Ba, Nizar Khelil, Eric Arnaud Crozat, Olivier Bouchot, Fabien Doguet, Erick Portocarrero, Mathieu Debauchez, Aicha Abed, Anthony Paolitto, Noboru Motomura, Aya Saito, Kazumasa Orihashi, Maillet, Dominique Somme

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Statements and opinions expressed in the chapters are these of the individual contributors and not necessarily those of the editors or publisher. No responsibility is accepted for the accuracy of information contained in the published chapters. The publisher assumes no responsibility for any damage or injury to persons or property arising out of the use of any materials, instructions, methods or ideas contained in the book.

First published in Croatia, 2011 by INTECH d.o.o. eBook (PDF) Published by IN TECH d.o.o. Place and year of publication of eBook (PDF): Rijeka, 2019. IntechOpen is the global imprint of IN TECH d.o.o. Printed in Croatia

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**3. Results**

#### *3.1. Litter and Litter Carbon Input to the Stream*

The litter input to the stream showed two peaks (Figure 3A). The maximum peak (101.40 g m−2) was observed in the LGS and then decreased gradually, reaching the minimum value (18.91 g m−2) in the SMS. The second peak (59.44 g m−2) was found in the GS (Figure 3A), and these values were all averages per period. Meanwhile, the litter input to the stream ranged from 2.47 to 103.13 g m−2, and the annual value was 20.14 g m−2 for the 15 investigated streams during this one-year investigation.

**Figure 3.** Dynamics of litter ( **A**) and litter carbon (**B**) input to the subalpine forest streams in the upper reaches of the Yangtze River. LGS, SSC, SMS, EGS and GS indicate the sampling periods, i.e., later growing season (LGS: September to October), seasonal snow cover (SSC: November to April next year), snowmelt season (SMS: April to May), early growing season (EGS: May to June), and growing season (GS: July to August). The vertical coordinate is the mean of litter input accumulation of 15 streams during this period. Different lowercase letters indicate the significant difference among different periods (*p* < 0.05), while the same letter indicates no significant difference among each other.

Like litter input, the dynamic pattern of litter carbon in the streams increased gradually from September to November (LGS), reached its maximum value (44.39 mg m−2), and then decreased gradually from April to June (SMS) to reach its minimum value (7.98 mg m−2) in SMS (Figure 3B). The second peak (25.12 mg m−2) of litter carbon input to the stream was observed in the GS (Figure 3B), and these values were all average of per period. For all streams, the litter carbon input to the streams ranged from 0.11 to 40.57 mg m−2, and the annual value was 8.61 mg m−2 for all streams in this one-year investigation.

#### *3.2. Litter and Litter Carbon Output from the Stream*

The dynamic pattern of litter output from the stream also showed a similar pattern to that of the input. The maximum value (1.69 g m−2) appeared in the LGS, and then the value decreased gradually, reaching the minimum value in the SMS (0.46 g m−2). The second peak (1.72 g m−2) was observed in the EGS (Figure 4A), and these values were all average of per period. The litter output from the all streams ranged from 0.02 to 22.30 g m−2, and the annual average value was 0.56 g m−2 during this one-year investigation.

**Figure 4.** Dynamics of litter (**A**) and litter carbon (**B**) output from the subalpine forest streams in the upper reaches of the Yangtze River from 11 July 2015, to 2 August 2016. LGS, SSC, SMS, EGS and GS indicate the sampling periods, i.e., later growing season (LGS: September to October), seasonal snow cover (SSC: November to April next year), snowmelt season (SMS: April to May), early growing season (EGS: May to June), and growing season (GS: July to August). The vertical coordinate is the mean of litter input accumulation of 15 streams during this period. Different lowercase letters indicate the significant difference among different periods (*p* < 0.05), while the same letter indicates no significant difference among each other.

Consistent with the pattern of litter input to the stream, the output of litter carbon from the streams also had two peaks (Figure 4B), which also appeared in the LGS (0.63 mg m−2) and EGS (0.64 mg m−2), and the lowest point was observed in the SMS (0.31 mg m−2) (Figure 4B), and these values were all average of per period. Additionally, the litter carbon output from all streams ranged from 0.01 to 4.53 g m−2, and the annual value was 0.45 g m−2 during this one-year investigation.

#### *3.3. The Ratios of the Input to Output of Litter and Litter Carbon*

During the investigated period, the average ratios of input to output of litter and litter carbon were 188.17 and 270.01 at the forest catchment level, respectively. The ratios of litter input to output ranged from 23.85 to 619.67 (Figure 5A), and the ratios of the input to output of litter carbon ranged from 16.80 to 1147.91 (Figure 5B). Meanwhile, the ratios of both litter input to output and litter carbon input to output showed similar dynamic patterns with the two peaks appearing in the LGS (272.74, 329.70) and EGS (190.46, 304.13), and the lowest point observed in the SMS (37.99, 67.11) for litter and litter carbon, respectively. Additionally, the ratios of input to output for both litter and litter carbon varied greatly with the investigated streams, and the averaged ratios of input to output ranged from 16.42 to 577.91 for litter (Figure 6A), and from 16.80 to 1147.91 for litter carbon, respectively (Figure 6B).

**Figure 5.** The ratios of input to output of litter (**A**) and litter carbon (**B**) in the subalpine forest streams in the upper reaches of the Yangtze River from 11 July 2015, to 2 August 2016. The value of each dot is the ratio of the average for the investigated streams during the sampling time. Different lowercase letters indicate the significant difference among different periods (*p* < 0.05), while the same letter indicates no significant difference among each other.

**Figure 6.** The ratios of input to output of litter (**A**) and litter carbon (**B**) in the subalpine forest streams in the upper reaches of the Yangtze River from 11 July 2015, to 2 August 2016. Each bar is the average of 13 sampling times for each forest stream.A–O are the sampled streams in the study.

#### *3.4. Relationships of Litter and Litter Carbon Input/Output with Relative Variables*

Litter input to the streams was significantly and positively correlated with the temperature and length (Table 2). However, litter input was slightly and negatively correlated with the stream width, but slightly and positively related to the precipitation, water level, sediment depth, and flow velocity of the forest streams (Table 2). Correspondingly, litter carbon input to the streams was also showed the similar relationships with relative variables (Table 2).

**Table 2.** Relationships of litter and litter carbon input with stream characteristics in the subalpine forest catchment.

\* *p* < 0.05, \*\* *p* < 0.01. d.f.: degree of freedom.

Similarly, litter output from the streams was significantly and positively correlated with the precipitation, temperature, litter input, and flow velocity, and slightly and positively with the water level, but significantly and negatively with sediment depth, and slightly and positively with stream width and length. Correspondingly, litter carbon output from the streams was also the similar relationships with the variables mentioned above (Table 3).

**Table 3.** Relationships of litter and litter carbon output with stream characteristics in the subalpine forest streams.

\* *p* < 0.05, \*\* *p* < 0.01. d.f.: degree of freedom.


**Abstract**

This chapter proposes three main technical contributions for the development of a telerehabilitation platform, named ePHoRT, for patients recovering from hip surgery. The first contribution is the application of a diffuse 3D model for the detection of rehabilitation exercises after hip surgery. The model applies fuzzy logic, which allows identifying in real time if a patient is performing a right or wrong movement, assisted by an avatar in 3D. The avatar copies the movements of the patient through a Kinect camera. The second contribution involves the proposal of an iterative method to improve the usability of telerehabilitation platforms along the development life cycle. The proposed method involves the use of an inspection method and includes protocols and instruments. This method has been validated in the ePHoRT project. Finally, the chapter describes accessibility guidelines for educational resources. It proposes accessibility standards for the content of educational resources in video and PDF formats in the telerehabilitation platform according to the Web Content Accessibility Guidelines (WCAG).

**Keywords:** eHealth, telemedicine, telerehabilitation, hip surgery patients, fuzzy logic, usability, accessibility, educational resources, WCAG


**3.3 Heavy metals and health implications**

**Figure 5** presents the spatial distribution of analyzed heavy metals (Pb, As, Cd, Fe and Ni) in the study area. There was an observed elevated level of heavy metals above their respective permissible limits for drinking purposes as defined by [7]. For instance, eight (8) groundwater samples (representing 32% each) had levels of Fe and Cd exceeding their permissible limits of 0.3 mg/l and 0.003 mg/l respectively. The strong correlation between As-Pb (0.73) and As-Ni (0.5) as shown in **Table 4** could indicate a possible similar source. Twenty-one (21) samples out twenty-five had Pb concentrations exceeding [7] permissible limit of 0.01 mg/l while ten (10) and three (3) samples had Ni and As concentrations exceeding their permissible limits of 0.02 mg/l and 0.01 mg/l, respectively.

The observed unsuitable, very poor and poor groundwater drinking quality could therefore be due to the heavy metals such as Pb, Cd, Ni and As, which might have been released into surface waters and soils as a result of improper disposal of mined wastes by the illegal gold miners. Within the Piniwutrim, Afrensi, Amakrom and surrounding villages for instance, virtually, all streams and perennial rivers have been heavily polluted and their courses virtually blocked. In such situations, infiltration of surface waters laden with heavy metals may be enhanced, leading to the leaching of heavy metals infiltrating alongside the surface waters into the groundwater system.

#### **Table 3.**

*Estimated WQI and classification.*

**Figure 5.** *Distribution of heavy metals in the study area.*

*Effects of Illegal Artisanal Gold Mining Operations on Groundwater Quality in Ghana… DOI: http://dx.doi.org/10.5772/intechopen.100242*

> **Table 4.** *Spearman correlation matrix of analyzed water quality parameters.*