*2.2. Synthesis and Characterization of AuNPs*

All glassware used for the preparation of AuNPs was first immersed thoroughly in aqua regia (1:3 (*v*/*v*) HNO3: HCl), then thoroughly washed with distilled water (dH2O) and dried overnight at 70 ◦C in an oven. AuNPs were prepared via the reduction of HAuCl4·3H2O using sodium citrate as described by Stiolica et al. [41,42]. The spectroscopic characterization of the synthesized AuNPs was carried out using Ultraviolet–visible (UV–vis) spectrophotometry (POLARstar Omega plate reader, BMG Labtech, Offenburg, Germany). The concentration of the AuNPs was evaluated using the UV–vis spectra as described by Haiss et al. [43]. The size distribution and zeta potential (ζ- potential) characterization of the AuNPs were determined using a Malvern NanoZS90 Zetasizer (Malvern Instruments Ltd., Malvern, UK) at a scattering angle of 90◦ at 25 ◦C. For the characterization of the size and morphology of the AuNPs, one drop of the sample solution was loaded onto a carbon-coated copper grid. The grids were dried for a few minutes under a Xenon lamp. High-resolution transmission electron microscope (HR-TEM) images were captured using an FEI Tecnai G2 20 field-emission gun (FEG) HRTEM (Hillsboro, OR, USA) operated in bright field mode at an accelerating voltage of 200 kV.

#### *2.3. Development of the RBP-A-Aptasensor*

#### 2.3.1. Optimization of the Aptamer and NaCl Concentration

AuNPs are highly reactive and aggregate easily in the presence of salts; therefore, it is important to monitor the salt-induced AuNPs aggregation percentage for the development of a colorimetric aptasensor [44–46]. To optimize the performance of the developed assay, various conditions such as aptamer and NaCl concentrations were investigated. For this experiment, a total of 600 μL of different concentrations (0, 6.25, 12.5, 25, 50, 100 and 150 nM) of RBP-A was added to 1.08 mL of AuNPs in separate 2 mL Eppendorf tubes, mixed well, and incubated overnight at 25 ◦C. Then, 50 μL of the functionalized RBP-A-AuNPs (aptasensor) was added to a 96-well microtiter plate, containing 50 μL of dH2O. This was followed by the addition of different concentrations of NaCl (0, 20, 40, 60, 80 and 100 mM). The samples were incubated at 25 ◦C for 5 min and observed for colour change. The UV–vis spectra were measured using a plate reader, and the absorbance ratios (A650/A520) were calculated to determine the aggregation percentage of the AuNPs [47]. The experiment was performed in triplicate and the average absorbance ratios were calculated and used to plot bar graphs.

#### 2.3.2. RBP4 Detection Based on the Label-Free AuNPs-Based RBP-A-Aptasensor

For the detection of RBP4, 600 μL of 50 nM RBP-A and 1.08 mL of AuNPs were added to a 2 mL tube, mixed well, and incubated overnight at 25 ◦C. Subsequently, 50 μL of the aptasensor was added into the 96-well microtiter plate containing 25 μL of dH2O. Then, 25 μL of different concentrations of RBP4 (0, 7.8, 15.6, 31.2, 62.5, 125, 250 nM) were added into the aptasensor, mixed thoroughly, and incubated for another 5 min at 25 ◦C, and observed for colour change This was followed by the addition of 6 μL of 1 M NaCl solution (60 mM final concentration) and incubation at 25 ◦C for 5 min. The UV–vis spectra were measured using a plate reader and the absorbance ratios (A650/A520) were calculated to determine the aggregation percentage of the AuNPs. The experiment was performed in triplicate and the average absorbance ratios were calculated and used to plot the linear curve.

#### 2.3.3. Specificity of the Label-Free AuNPs-Based RBP-A-Aptasensor

To evaluate the specificity of the RBP-A-aptasensor, 50 μL of the aptasensor was added into the 96-well microtiter plate, containing 25 μL of dH2O. Then, 25 μL of 250 nM RBP4, A2MG, leptin and BSA were added into the aptasensor, mixed thoroughly, and incubated for another 5 min at 25 ◦C and observed for colour change. This was followed by the addition of 6 μL of 1 M NaCl solution (60 mM final concentration) and incubation at 25 ◦C for 5 min. A water sample was used as a blank. The UV–vis spectra were measured using a plate reader and the absorbance ratios (A650/A520) were calculated to determine the aggregation percentage of the AuNPs. The experiment was performed in triplicate and the average absorbance ratios were calculated and used to plot bar graphs.


**9.10 Convenience sampling**

Convenience sampling appears to be a favorite sampling technique among students, as it is cheap and simple compared to other sampling techniques. It is collection of participants since they are often readily and conveniently available.

Convenience sampling is not the preferred form of sampling for successful research as samples are taken from a particular segment of the population, so the degree of generalizability is questionable (**Figure 9**) [38].

**Figure 8.** *Snowball sampling (source: https://cuttingedgepr.com/find-mobilize-unofficial-opinion-leaders/).*

## **10. Standard error of a sample mean**

Suppose we have taken a sample of n measurements of some continuous variate, such as blood pressure or hemoglobin level. The sample mean *x* may be different from the population mean because it is based on a sample. Different samples of the same size *n* would give different values of the mean. These differences are due to sampling error. The sample mean therefore has its own distribution.

If the distribution of *x* in the population has mean *μ* and standard deviation **σ** and a sample of size *n* is taken, then the *sampling distribution* of the sample mean *x* has the following properties:

1.The mean of the distribution of *x* is the same as that of the whole population, i.e.

**E**ð Þ¼ *x*̅ *μ* ð Þ *see Appendix for proof*

or the sample mean is an unbiased estimate of the population mean.

2.The standard deviation of *x* is equal to **σ/** √**n**. The standard deviation of an estimate is referred to as the standard error (SE). The standard error of the mean is therefore [39]

$$\mathbf{SE}\left(\overline{\mathfrak{x}}\right) = \mathfrak{o}/\mathfrak{n}$$

3.By the central limit theorem, *x* is approximately Normally distributed, i.e. the distribution of *x* tends to be Normal even if the distribution in the population is markedly non-Normal. The distribution of means becomes closer to the Normal distribution as *n* increases.

The standard error of the mean is a measure of the sampling error [40]. For example, consider the measurement of lung function, forced expiratory volume, measured in liters. This is known to have a standard deviation of 0.5 in a population. If we select various sample sizes from this population, we have:

$$n = 1\text{ SE}(\bar{\mathbf{x}}) - \mathbf{0.5}/\mathbf{1} = \mathbf{0.50}$$

$$n = 9\text{ SE}(\bar{\mathbf{x}}) - \mathbf{0.5}/\mathbf{3} = \mathbf{0.17}$$

$$n = 25\text{ SE}(\bar{\mathbf{x}}) = \mathbf{0.5}/\mathbf{5} = \mathbf{0.10}$$

$$n = 100\text{ SE}(\bar{\mathbf{x}}) = \mathbf{0.5}/10 = \mathbf{0.05}$$

The larger the sample size, the smaller the sampling error. The standard error of the mean is used when we want to indicate how precise our estimate of the mean is. The standard deviation s, on the other hand, is used to show how widely spread our measurements of *x* are.


**3. Experimental procedure**

In this section, the experimental procedure was introduced: the first step was to obtain the butt welded joint, and then the out-of-plane welding displacement was measured; the next step was to measure the welding residual stress through CM. Finally, the weld profile of cross-section was obtained.

### **3.1 Welding work**

In this study, the butt welded joint was obtained by SMAW. In detail, the low carbon steel Q235 with the thickness of 30 mm was used as base metal, and the filler metal was J507 welding rod with the diameter of 4 mm. The welding groove was symmetric with the angle of 60°. The detailed dimensions and weld groove are presented in **Figure 1**.

structural integrity assessment for safety critical components, optimize the design

Up to now, several qualitative and quantitative techniques have been developed to measure residual stress, which are determined by using the specific elastic constants of material based on the measured strain rather than measured stress. All of them are divided into two categories: destructive techniques and nondestructive techniques [6]. For destructive techniques such as sectioning method, hole drilling method, and CM, the residual stress is measured by its relaxation due to the destruction of the state of the equilibrium of residual stress in a mechanical component. While for nondestructive techniques such as X-ray diffraction method and neutron diffraction method, residual stress is determined based on the relationship between residual stress crystallographic parameters of the material. Among the techniques above, according to the Bueckner's superposition principle, CM can provide a 2D cross-sectional map of residual stress normal to a plane of interest which combines the stress relaxation technology and finite element method [7]. The standard procedure of CM is implemented by the following steps [8]: (1) sample cutting on a plane of interest, (2) contour measurement of the cutting plane or surface, (3) data processing of the measurement results, and (4) residual stress back-calculation by using finite element analysis. CM has found a lot of literatures: Xie [9] estimated the residual stress in thick Ti-6Al-4V alloy welded joint by electron beam welding through finite element method and contour method. Murugan and Narayanan [10] employed both the finite element method and contour method to reveal the residual stress distribution induced by welding in tee joint and found that the experimental results agree well with the predicted stress. What's more, Turski and Edwards [11] efficiently measured the residual stress of 316L stainless steel by utilizing the contour method. Braga et al. [12] studied the welding residual stress profile of butt joints of S355 structural steel through contour method and neutron diffraction. Kainuma [13] investigated the welding residual stress in orthotropic steel decks which had a considerable effect on crack initiation and propagation by using cutting method and magnetostriction method. Woo [14] obtained the two-dimensional maps of the longitudinal residual stress through the thickness of 70-mm thick ferritic steel by using the CM. After that, Woo [15] determined the residual stress in an 80-mm thick ferritic steel by combining the neutron diffraction and CM. In addition to butt welded joint, Liu [16] measured the internal residual stress on inertia friction welding of nickel-based superalloy.

From the reviews above, the CM has obtained a lot of achievements. However,

the accuracy of novel embedded cutting contour configuration for thick plate welded joint has not been evaluated. In this paper, the welding residual stress of 30-mm thick plate butt welded joint was investigated combining TEP FEM and CM. What's more, the effect of back-gouging on the residual stress distribution of butt

In this study, the welding residual stress in the butt welded joint through shielded metal arc welding (SMAW) was predicted by TEP FEM, an uncoupled thermal/mechanical formulation procedure, which is mainly composed of two sections: (a) the thermal analysis process and (b) the stress analysis process. Because the former has decisive effect on the latter while the latter has only a small influence on the former, thermal-mechanical behavior during welding is analyzed by using uncoupled thermal/mechanical formulation [17]. During thermal analysis, the 3D

**2. Prediction of welding residual stress by TEP FEM**

welded joint was discussed.

**108**

of manufacturing routes, and validate residual stress predictions [4, 5].

*New Challenges in Residual Stress Measurements and Evaluation*


**1. Introduction**

Breast cancer is the most common cancer in women with a worldwide annual incidence of 2.3 million cases and 685,000 death per year [1]. There is a clear correlation between bone health and breast cancer [2], as bone mineral density can be severely reduced through early menopause or endocrine therapy, including aromatase inhibitors [3]. Secondly, there is also a clear relationship between osteo-oncologic treatment including densoumab and bisphosphonates and outcome in early breast cancer [4]. Thirdly, in stage IV breast cancer, bone is the most common site of metastasis [5].

Disease-specific events related to bone metastasis include complications, such as spinal cord and nerve compression and pathological fractures, needing surgical interventions and/or radiotherapy. This is therefore a major endpoint in treatment of metastatic breast cancer, since targeted therapy has the potential to significantly improve outcome in early and metastatic breast cancer [6].

This chapter will give you an overview on bone health management and prevention in early and metastatic breast cancer patients.


**4. Does carotenoid vitamin therapy only help intermediate stage AMD?**

The AREDS trials showed that supplementation with carotenoid vitamin therapy prevented progression from intermediate to advanced stages of AMD. Further, the AREDS-2 trial [1] showed that the carotenoid supplementation with lutein and zeaxanthin indeed favored treatment, particularly in those that had low serum levels at baseline. It's a fair question to ask if the carotenoid vitamin therapy does benefit other stages of AMD? An equally important question is what other benefits can be seen in individuals with dry-AMD with carotenoid vitamin therapy? These are big questions, and it would be ideal if there were additional large-scale trials like AREDS that give us all the answers for early diagnosis, prognostic, and new treatments when they become available. This aspiration may be in part impractical for all scientific questions and when such large trials are not available doctors will need to evaluate all tiers of evidence available to derive clinical guidelines for disease states. Numerous reports have shown clinical benefits, by raising the levels of xanthophylls in the retina through dietary supplementation, thus, adjunctive carotenoid vitamin therapy may offer enhanced neuroprotection by augmenting MPOD and subsequently preventing further injury [16, 17]. Higher levels of MPOD are thought to preserve retinal tissue, specifically, the layers containing photoreceptors in the fovea, through two primary mechanisms: (1) serving as an innate optical filter against blue light; and (2) as protective antioxidants, by neutralizing free radicals and reducing consequent oxidative injury [16, 17]. In a recent systematic review of carotenoids in the management of AMD showed that there are at least 20 epidemiological studies and 35 randomized controlled trials that have evaluated this topic [17]. These studies evaluated various facets of the topic: supplementation and increase in serum carotenoids, MPOD, and changes in visual function. Whereas improvements in BCVA were seen in six out of eighteen (6/18) trials, remarkable benefits in contrast sensitivity were demonstrated in ten out of fifteen (10/15) randomized controlled trials [17]. Improvements were also seen in glare disability, photostress recovery time, and improvements in multifocal electroretinogram results [17]. Thus, it was concluded that consistent evidence from large-scale epidemiology studies, and several randomized clinical trials, substantiate the synergic neuroprotective benefits afforded by carotenoid vitamin therapy in eyes with any stage of AMD [17]. It is important to note that these visual benefits may be decreased in late-stage AMD compared to early or intermediate stage AMD [17, 18]. A dose-response relationship with stronger effect and greater serum carotenoids and MPOD levels is seen with supplementation of a greater dose of carotenoids [19]. In a recent RCT [20] we found that six-month supplementation with a greater amount of ocular carotenoids (28mg) and omega 3 supplement (675 DHA and 230 EPA), when compared to AREDS-2 formulation soft-gels (12 mg) not only provided greater serum carotenoid levels but also led to significant improvements in measured contrast sensitivity in individuals at risk of AMD. Indicating that quicker and greater visual benefits can be seen if a larger dose of ocular xanthophylls is supplemented to patients. There are numerous questions that remain to be answered for example do potent antioxidants like astaxanthin reach retinal layers? Are there any synergistic effects of these carotenoids? Scientists have answered a lot of questions and a lot more remain.

Roughly one in eight individuals aged 60 or greater is suffering from AMD; it is fair to say that it deserves our special attention. It was long believed that in the chronic disease of dry-AMD not much occurs or is needed until much later in disease state; we can confidently say, that is not true. With the advancement in clinical testing like Rabin Cone Contrast testing, we can detect this disease easily and along

#### *Recent Advances and New Perspectives in Managing Macular Degeneration*

with devices that can measure MPOD we can better manage the disease and monitor its progression. The objective technology of Macular Pigment Reflectometry to measure MPOD, and individual carotenoid optical density shows promise in personalized medicine. Also, there is sufficient data from various RCTs to recommend carotenoid vitamin supplement at all stages of AMD, which may prevent its progression but definitely provides an improvement in vision, and who does not like an improved vision!


*Article* **Determinants of Lack of Recovery from Dependency and Walking Ability Six Months after Hip Fracture in a Population of People Aged 65 Years and Over**

**Enrique González Marcos 1, Enrique González García 2, Josefa González-Santos 3,\*, Jerónimo J. González-Bernal 3, Adoración del Pilar Martín-Rodríguez 2 and Mirian Santamaría-Peláez 3**

**Abstract:** Background: Hip fracture in the elderly means that between a quarter and a half of patients do not regain the levels of independence and walking ability that they previously had, according to the literature, after the fracture. Material and methods: Retrospective study of 537 patients aged ≥65 years who survived at the sixth month after fracturing their hip, of which the age, sex, type of fracture, surgical risk, independence (BI), walking ability, cognitive level (PS), comorbidities, indicated drugs, complications, surgical delay, hospital stay, and surgical technique are known. Using Pearson's χ2 test, all the variables were contrasted with respect to the limitation or not, at the sixth month of the recovery of both independence and pre-admission walking ability. Multivariate analysis provides the necessary adjustment to the previous contrast. Results: We have found that age and PS ≥ 5 at admission limit recovery from both dependency and walking ability. Surgical risk, independence (BI) upon admission, anemia, and constipation during the hospital stay limit the recovery of the BI. Worsening of walking ability during the hospital stay and the type of extra-articular fracture, which was surgically treated by osteosynthesis, limit the recovery of walking ability. Conclusions: The factors previously exposed, and perhaps the fact that patients with hip fractures are not routinely referred to rehabilitation, explain the high proportion of patients who do not recover their previous independency (36%) or walking ability (45%) to the fact of fracturing.

**Keywords:** hip fracture; age; aging; recovery of independence; recovery of walking ability


**Contemporary Developments in Child Protection**

**Volume 1**

**Policy Changes and Challenges**

This book is a reprint of the special issue that appeared in the online open access journal *Social Sciences* (ISSN 2076-0760) in 2014 (available at: http://www.mdpi.com/journal/socsci/special\_issues/child\_protection).

*Guest Editor* Nigel Parton University of Huddersfield, Queensgate, Huddersfield, HD1 3DH UK

*Editorial Office* MDPI AG Klybeckstrasse 64 Basel, Switzerland

*Publisher* Shu-Kun Lin

*Editorial Manager*  Alistair Freeland

#### **1. Edition 2015**

MDPI • Basel • Beijing • Wuhan

ISBN 978-3-03842-086-6 (PDF) Volume 1 - 3 ISBN 978-3-03842-087-3 (PDF) Volume 1 ISBN 978-3-03842-088-0 (PDF) Volume 2 ISBN 978-3-03842-089-7 (PDF) Volume 3

© 2015 by the authors; licensee MDPI, Basel, Switzerland. All articles in this volume are Open Access distributed under the Creative Commons Attribution 3.0 license (http://creativecommons.org/licenses/by/3.0/), which allows users to download, copy and build upon published articles even for commercial purposes, as long as the author and publisher are properly credited, which ensures maximum dissemination and a wider impact of our publications. However, the dissemination and distribution of copies of this book as a whole is restricted to MDPI, Basel, Switzerland.


Preface

Recently, many researchers have focused on identifying a cost-effective approach to generate biofuel, chemicals, and value-added products from various biomass. Generating alternative fuels from renewable feedstock helps with waste management, produces low-cost fuel, and reduces negative environmental effects. To achieve this, a broader knowledge of selecting renewable feedstock is essential. From an economic and environmental point of view, cellulose is considered a renewable, versatile, and biodegradable material. It is the most abundantly available biopolymer in different biomass such as plants, bacteria, tunicates, and algae. This book provides basic information about the various applications of cellulose conversion into biofuels and value-added products. It presents the basics of cellulose conversion, an integral part of the biorefinery concept, and discusses the possible routes of biofuel/value-added products derived from cellulose.

> **Rajesh Banu Jeyakumar** Department of Biotechnology, Central University of Tamil Nadu, Thiruvarur, Tamil Nadu, India

#### **Kavitha Sankarapandian**

Department of Biotechnology, Karpagam Academy of Higher Education, Coimbatore, Tamilnadu, India

#### **Yukesh Kannah Ravi**

Center for Organic and Nanohybrid Electronics, Silesian University of Technology, Gliwice, Poland

Section 1

Environmental Application

**1**

Section 1