**8. Conclusion**

In this book chapter, the properties of MSW have been discussed, which will help us to select the proper technology. Also, discussion on the gasification processes and technologies has been done to strengthen the basics on gasification. In addition, a review on energy recovery system has been made to guide and select the most viable option for energy recovery. The environmental benefits of MSW gasification has been also reported in this book chapter. Finally, a case study on pilot-scale MSW gasification to generate electricity has been presented to discuss one of the most efficient pathways to utilize it. Based on the above discussion, it is quite clear that gasification process offers considerable energy recovery and reduces the amount of potential pollutants emission. Moreover, gasification may be proposed as a viable alternative solution for waste treatment by converting waste into a gaseous energy form, syngas for further potential uses to energy production or chemicals. MSW gasification has some drawbacks due to the heterogeneous characteristics of MSW. However, a possible solution to address this issue could be production of solid refuse fuel (SRF) with homogeneous and controlled characteristics. The strongest point for gasifying MSW is its environmental performance. Several MSW gasification emission test results indicate that the gasification of MSW is able to meet the emission standard and can effectively reduce the environmental impacts, which can be considered as a sound response to the increasingly restrictive regulations applied around the world.


**2. Molecular pathogenesis**

### **2.1. Clear- cell variants renal cell carcinoma**

The discovery of von Hippel–Lindau (VHL) / hypoxia-inducible factor (HIF) oxygen-sensing pathway and its role in the pathogenesis of RCC (clear-cell as well as some of the non-clearcell variant), has led to a new approach in the systemic therapy for RCC. [1, 3] Tumour suppressor gene VHL encodes the VHL protein (pVHL), which interacts with hypoxiainducible factor (HIF) to regulate cellular response to oxygen deprivation. HIF is a gene

transcription factor and consists of two subunits: HIF α-subunit and the HIF β-subunit (also known as aryl hydrocarbon receptor nuclear translocator (ARNT) protein). In the presence of normal oxygen tension (or normoxic state), HIF-α is hydroxylated. pVHL-E3 ubiquitin ligase complex targets the hydroxylated HIF-α for proteosomal degradation. [4] VHL protein functions as the substrate-recognition subunit of this complex. [5, 6]

The traditional teaching is that cytoreductive nephrectomy lead to improved outcome from systemic therapy. This is based on phase III data that showed an improvement in response to IFN-α following nephrectomy in the metastatic setting. In the era of targeted therapy / anti-VEGF therapies, the validity of this practice has been called into question. [20] Clinical trials

New Systemic Treatment Approaches for Metastatic Renal Cell Carcinoma

http://dx.doi.org/10.5772/55280

159

Beyond surgery, the only systemic options available prior to the era of targeted therapy consisted of interleukin-2 (IL-2) and interferon-α (IFN-α). Other treatments that had been

IFN-α classically caused flu-like syndrome, depression and in some cases suicidal ideation and is certainly onerous especially in the patients with poorer performance status. [1, 22] IL-2, the other cytokine has a small long term survival benefit of 4%. This is however at the cost of potentiallylifethreateningtoxicitiessuchashypotension,oliguria,capillaryleaksyndromewith secondary multi-organ failure, somnolence and confusion. [23] Not surprisingly, the underly‐ ing enthusiasm for cytokine agents as frontline therapy in metastatic RCC has been replaced by tyrosine kinase inhibitors / targeted therapy which has a more favourable toxicity profile. [24]

The targeted therapies used in metastatic RCC consist of 1. Anti-VEGFs, which are monoclonal antibodies that bind directly to VEGF and related peptides and therefore removing them from the circulation (bevacizumab) and 2. Small molecule tyrosine kinase inhibitors (SMTKIs) that target the down-stream tyrosine kinase signaling pathways, are involved in promotion of tumour angiogenesis, endothelial growth, proliferation and ultimately tumour survival and metastasis. [25] The SMTKIs that have been approved for use in 2012 include sunitinib,

Sunitinib is a multi-kinase inhibitor targeting numerous VEGF receptors (VEGF-1, 2, 3) and additionaltyrosinekinase receptors (PDGFR, c-Kit,FLT-3,CSF-1R, andRET)[26-29]Earlytrials showed sunitinib to be effective in patients with advanced malignancies including RCC. [30]

A phase II study of sunitinib in patients with cytokine-refractory metastatic RCC assessed the clinical efficacy and safety of sunitinib as second-line therapy. [31] Sixty three patients who previously failed cytokine-based therapy received 50mg of sunitinib for 4 weeks followed by a 2 week scheduled break, in a 6 week cycle. A partial response of 40% (n=25) (PR) and a stable disease response for ≥ 3 months in 27% (n=17) of the patients were reported. The median time

A second but larger phase II trial of 106 patients similarly confirmed promising activities of sunitinib in cytokine refractory, metastatic RCC. An overall objective response of 44% was observed with 1% (n=1) of patients demonstrated a CR and 44% showed PR. [32] A further

to progression and survival were 8.7 months and 16.4 months respectively. [31]

trialed included chemo- and hormonal therapy have all been discouraging. [21]

are underway to address this very question.

sorafenib, pazopanib and axitinib.

*<IP_ADDRESS>. Sunitinib intermittent dosing*

*3.1.1. Sunitinib*

**3.1. Small molecular tyrosine kinase inhibitors**

VHL gene mutation or hypermethylation leads to intracellular accumulation of HIF-α subu‐ nits.[7]HIF-αsubunits,aftertranslocationintothenucleus,actinconcertwiththeHIF-βsubunits, andformtranscriptionalfactor complexes thatinduce transcriptionofhypoxia-response genes. [8] The endpoint is an increase in the production of pro-angiogenic factors including vascular endothelial growth factor (VEGF), platelet-derived growth factor (PDGF) and transforming growth factor alpha and beta (TGF-α and TGF-β). [9] By increasing angiogenesis through VHL-HIF pathway the tumour increases its potential to survive and progress. [10]

### **2.2. Non clear-cell variant**

Papillary carcinomas are commonly bilateral, multifocal and frequently present as small, early stage tumours. [11] They can be further subdivided histologically into papillary types I and II with underlying different genetics and molecular pathways. [12] Type I papillary renal cancers are linked to activating mutations of the methyl-nitroso-nitroguanidine induced (MET) oncogene. [13] The MET oncogene mutations activate the intracellular kinase domains and subsequently trigger the hepatocyte growth / MET pathway. [13] Type II papillary renal cancers on the other hand are associated with mutations of the fumarate hydratase (FH) tumour suppressor gene. [14] Mutational inactivation of the FH tumour suppressor gene leads to a pseudo-hypoxic state and up-regulation of the HIF α-subunits. The accumulation of fumarate is induced by the mutated FH enzyme. That in turn causes inhibition of HIF-prolyl hydroxylase(HPH), an enzymatic regulator of the intracellular HIF-α. Inactivation of the HPH disrupts the hydroxylation of HIF leading to failure of recognition by pVHL and subsequent VHL-dependent proteosomal degradation of HIFs. Accumulation of HIF leads to overexpression of pro-angiogenic factors and tumour proliferation. [15]

Chromophobe renal cell cancers accounts for 4% of all RCCs. [1] The exact pathogenesis is not established. It is thought that the VEGF-angiogenic pathway is implicated based on the elevated levels of VEGF and its receptors in this type of RCC. The KIT oncogene and the folliculin gene linked to the familial form of chromophobe/oncocytic RCC hybrid (Brit-Hogg-Dubé-Syndrome), are extra molecular targets identified in this variant [16, 17] Collecting duct RCC are very rare and the underlying pathogenesis has not been established. [18]


*Article* **Quality of Life in Presbyopes with Low and High Myopia Using Single-Vision and Progressive-Lens Correction**

**Adeline Yang 1,\*,†, Si Ying Lim 2,†, Yee Ling Wong 1, Anna Yeo 3, Narayanan Rajeev 2 and Björn Drobe 1**

**Abstract:** This study evaluates the impact of the severity of myopia and the type of visual correction in presbyopia on vision-related quality of life (QOL), using the refractive status and vision profile (RSVP) questionnaire. A total of 149 subjects aged 41–75 years with myopic presbyopia were recruited: 108 had low myopia and 41 had high myopia. The RSVP questionnaire was administered. Rasch analysis was performed on five subscales: perception, expectation, functionality, symptoms, and problems with glasses. Highly myopic subjects had a significantly lower mean QOL score (51.65), compared to low myopes (65.24) (*p* < 0.001). They also had a significantly lower functionality score with glasses (49.38), compared to low myopes (57.00) (*p* = 0.018), and they had a worse functionality score without glasses (29.12), compared to low myopes (36.24) (*p* = 0.045). Those who wore progressive addition lenses (PAL) in the high-myope group (*n* = 25) scored significantly better, compared to those who wore single-vision distance (SVD) lenses (*n* = 14), with perception scores of 61.19 and 46.94, respectively (*p* = 0.029). Highly myopic presbyopes had worse overall QOL and functionality, both with and without glasses, compared to presbyopes with low myopia. High-myopic PAL users had a better perception outcome than SVD lens wearers. Low-myopic PAL wearers had a better QOL than SVD wearers.

**Keywords:** myopia; quality of life; RSVP questionnaire; presbyopia

#### **1. Introduction**

Presbyopia is a global problem affecting 1.8 billion people worldwide [1], of which at least 826 million were not adequately corrected as of 2015 [2]. The number of presbyopes is set to increase to 2.1 billion by 2030, against a backdrop of an ageing global population where the median age could reach 40 years by 2050 [3]. While the impact of presbyopia can be minimised easily by using visual correction such as spectacles, contact lenses, or refractive surgery, up to 34% of presbyopes in developed countries do not have adequate correction [4]. This is compounded by the projected rise in myopia's prevalence and severity globally, which will have a further impact on the quality of life (QOL) for presbyopes [3].

In people with both presbyopia and myopia, adequate correction for near and far vision is crucial for daily activities. The negative impact of presbyopia on both visual functions and QOL has been demonstrated with the use of questionnaires [5,6]. Similarly, the detrimental impact of myopia on vision-related outcomes has been shown in previous studies [7–9]. However, there is a lack of studies that look at the collective impact of myopia and presbyopia on QOL, the correction habits of presbyopic patients, and the impact of the combination of corrections utilised on their QOL. The refractive status and vision profile (RSVP) questionnaire and visual analogue scale (VAS) are methods that are well established, validated, and can be used to capture outcomes that cannot be measured

**Citation:** Yang, A.; Lim, S.Y.; Wong, Y.L.; Yeo, A.; Rajeev, N.; Drobe, B. Quality of Life in Presbyopes with Low and High Myopia Using Single-Vision and Progressive-Lens Correction. *J. Clin. Med.* **2021**, *10*, 1589. https://doi.org/10.3390/ jcm10081589

Academic Editor: Kazuno Negishi

Received: 2 March 2021 Accepted: 4 April 2021 Published: 9 April 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the authors. 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 (https:// creativecommons.org/licenses/by/ 4.0/).

through objective clinical assessments, enabling better management of the clinical practice and research evaluation of new treatments [10–15].

Therefore, this study aims to evaluate the QOL of presbyopes with low and high myopia and to determine how different optical corrections, namely progressive addition lenses (PAL) and single-vision distance (SVD) lenses, affect the QOL outcomes of presbyopes with various myopia severity.

#### **2. Materials and Methods**

#### *2.1. Study Population*

A total of 149 people aged 41 to 75 years, who had both myopia and presbyopia, participated in this study in the period between August 2016 and March 2018. Presbyopia was defined as the need for reading glasses, near addition, or, in some cases, removing the distance correction. Myopia was defined as spherical equivalent (SE) of ≤−0.50 diopters (D). All participants were myopic, with no more than 2.00 D of astigmatism in either eye; with anisometropia of less than 1.50 D; and with no history of any eye diseases (such as cataracts, glaucoma, age-related macular degeneration, or other eye complications) or surgeries.

The study adhered to the tenets of the Declaration of Helsinki, and ethics approval was obtained from the Singapore Polytechnic Ethics Review Committee. All tests were administered at the Singapore Polytechnic Optometry Centre after obtaining written informed consent from all participants.

#### *2.2. Examinations*

Only participants with distance visual acuity of at least 0.3 LogMAR (measured using the Early Treatment Diabetic Retinopathy Study (ETDRS) chart), near visual acuity of at least N5 (using the N-point near chart), and at least 1.9 log contrast sensitivity (using the Pelli-Robson Contrast Sensitivity chart with habitual correction) were included in the study. Study participants did not undergo any refraction assessment; thus, their distant spectacle power was used as the refractive error. Spectacle power was measured with an automated focimeter (Topcon, CL.100; Topcon Corporation, Tokyo, Japan).

#### *2.3. Questionnaires*

A detailed questionnaire was used to collect demographic (age, gender, occupation), ocular, and general medical history from the participants for the purpose of screening. In total, 182 were screened before 149 were recruited. The questionnaire was administered by research staff and completed by the participants themselves.

The original RSVP questionnaire consists of 42 questions. Four questions were omitted, as they were contact lens-related and did not apply to our study objective. There were 38 questions on the different types of vision-dependent activities to assess the level of difficulty in performing daily activities (Table 1). The items used a five-point rating scale. The 38 items were divided into the following five subscales: perception (5 items), expectation (5 items), functionality (14 items), and visual symptoms (13 items).

The current state of health (1 item) was measured using the VAS. This is a measure of perception that ranges across a continuum of values. VAS is a horizontal line, 100 mm in length, anchored by a word descriptor at the end—in this case, the "worst imaginable health state" at zero, and the "best imaginable health state" at 100.

**Table 1.** Summary of the refractive status and vision profile (RSVP) questionnaire.

#### *2.4. Statistical Analysis*

A Rasch analysis was used to transform the data, and, for further analysis, we used the Andrich rating scale model, with Winsteps software, version 3.68; (Winsteps, Chicago, IL, USA) [16,17]. The transformed scores were scaled from 0 to 100, with a higher score indicating better satisfaction and better QOL. Rasch analysis uses the raw score from the questionnaire and expresses the respondent's outcome on a linear scale, which accounts

for the unequal difficulties across all test items. The Rasch analysis was done for the overall QOL and the five subscales of perception, expectation, functionality, symptoms, and problems with glasses.

A chi-square test was used to test for differences in the proportion of participants between groups, and an analysis of variance (ANOVA) was used for the difference in the mean QOL between the groups, using statistical software Statistica, version 13.2 (TIBCO Software Inc., Palo Alto, CA, USA). Values of *p* < 0.05 were taken to be statistically significant differences.

#### **3. Results**

Of the 149 participants with both myopia and presbyopia, 108 (72.5%) were presbyopic with low myopia (SE ≤ −0.50 D to SE > −5.00 D), and 41 (27.5%) were presbyopic with high myopia (SE ≤ −5.00 D), with a mean age (±SD) of 52.1 ± 6.9 years. Moreover, 89 (59.7%) of the participants were females, and 60 (40.3%) were males. There was a significant difference in the distribution of gender, especially in the highly myopic group (*p* = 0.04). This difference in gender distribution did not have any effect on the QOL score (F (1, 145) = 0.30; *p* = 0.49), even with the additional effect among the myope group (F (1, 145) = 0.79; *p* = 0.32). Of the 41 with high myopia, most (85%) had an SE in the range of −5.00 D to −9.00 D. The power of the study was 99.4%, with an effect size of 0.83.

Eighty (53.7%) wore PALs, 61 (40.9%) wore SVD lenses, one (0.7%) wore single-vision near lenses, four (2.7%) wore bifocals, and the remaining three (2%) did not wear glasses. Among those with high myopia, 14 (35.9%) were SVD wearers, and 25 (64.1%) were PAL wearers. Among those with low myopia, 47 (46.1%) were SVD wearers, and 55 (53.9%) were PAL wearers. There were more females in the low-myopic group than in the high-myopic group (*p* = 0.04), and the distance-corrected habitual visual acuity was significantly better in the low-myopic group (−0.09 ± 0.09 logMAR) compared to the high-myopic group (−0.04 ± 0.09 logMAR) (*p* = 0.003) (Table 2).

**Table 2.** Baseline characteristics of presbyopic participants with low myopia and high myopia (*n* = 149). Mean ± standard deviation. PAL, progression addition lens; SVD, single-vision distance lens; VAS, visual analogue scale. \* Statistically significant with *p*-value of <0.05.

The health-state score was significantly correlated with the QOL score, but the correlation was weak, r2 = 0.10 (*p* < 0.05). The health-state score was similar between the two myopic groups (*p* = 0.43), and between the PAL- and SVD-lens wearers (*p* = 0.81).

High myopes had a significantly lower overall QOL (51.7) than low myopes (65.2) (*p* < 0.001; Figure 1). High myopes also had significantly poorer functionality with glasses, with a score of 29.1, compared with those of presbyopes with low myopia, with a score of 36.2 (*p* = 0.01). Similarly, presbyopes with high myopia had poorer functionality without glasses (49.4) than low myopes (57.0; *p* = 0.04).

**Figure 1.** The quality of life (QOL) scores of presbyopes with low myopia versus high myopia, with error bars representing standard error. \* Statistically significant, with a *p*-value of <0.05; \*\* statistically significant, with a *p*-value of <0.001.

With glasses, a greater proportion of high myopes had difficulty driving at night (low myopes 27.5% vs. high myopes 54.2%) (*X*2 (1, *n* = 93) = 5.6; *p* = 0.02) and driving in the rain (11.3% low myopes vs. 36.7% high myopes; *X*2 (1, *n* = 92) = 8.3; *p* = 0.004). High myopes also had more issues swimming with correction (19.4% low myopes vs. 36.7% high myopes; *X*2 (1, *n* = 92) = 4.5; *p* = 0.03). Without glasses, high myopes had greater difficulty reading and doing near work (42% low myopes vs. 83.9% high myopes; *X*2 (1, *n* = 131) = 16.6; *p* < 0.001). They were also less able to see clearly when they woke up (42.3% vs. 88.2%; *X*2 (1, *n* = 131) = 21.4; *p* < 0.001) or see the alarm clock (40.4% vs. 80.0%; *X*2 (1, *n* = 129) = 16.0; *p* < 0.001).

For presbyopes with low myopia, the group using PAL had significantly better overall QOL than SVD lens users (*p* = 0.04; Figure 2), although there was no significant difference between SVD lens and PAL wearers in all the other subscales, such as perception, expectation, functionality, and symptoms.

In the group of presbyopes with high myopia, those who wore PAL had significantly better perception (61.2) than those who wore SVD lenses (46.9; *p* = 0.03). High myopes wearing SVD lenses stated that they were more often afraid to do things because of their vision (SVD 57.1% vs. PAL 28%; *X*2 (1, *n* = 39) = 4.3; *p* = 0.04), and were more frustrated with their glasses (71.4% vs. 32.0%; *X*2 (1, *n* = 39) = 5.6; *p* = 0.02). No other significant differences were found for the other subscales, for presbyopes with high myopia wearing PAL and SVD lenses (Figure 3).

**Figure 3.** The QOL scores of highly myopic presbyopes who wore PAL and SVD lenses for all five subscales, with error bars representing standard error. \* Statistically significant, with *p*-value of <0.05.

#### **4. Discussion**

#### *4.1. Significant Findings*

Presbyopes with high myopia had poorer overall QOL compared to those with low myopia. Similarly, high myopes had worse functionality scores compared to low myopes. Compared to SVD users, PAL users, on average, had better overall QOL scores for both myopic groups. PAL users also had better perception scores for high myopes. The difference in gender distribution did not have a significant effect on the QOL score.

The highly myopic group had significantly poorer visual acuity, with a difference of 0.05 logMAR, which equates to 2–3 letters from the visual acuity chart. This slight decrease in visual acuity may not be considered clinically significant by clinicians. However, it may have a tangible effect, contributing to poorer QOL and functionality outcomes with glasses. Therefore, this study's outcome from the QOL reflected the tangible effects of reduced vision felt by the participants, which were often dismissed as insignificant by clinicians.

Reduced best-corrected visual acuity with spectacle lenses in high myopia has been found in previous studies [9,18–25]. In addition, there was a higher proportion of high myopes who experienced severe trouble with driving at night and in the rain [26]. Besides visual acuity affecting the corrected vision of high myopes, the night vision threshold [26], higher-order aberration [20,21], and larger pupil size may also contribute to poorer vision under dim lighting, as experienced when driving at night and in the rain. Further physiological stretching from axial elongation due to myopia also reduces the function and resolution of photoreceptors [22,26]. Some studies also found reduced contrast sensitivity at high spatial frequencies in fully corrected high myopes, which may contribute to reduced functionality with glasses [27]. However, we did not find any differences in contrast sensitivity between low and high myopic groups, as found by Collins et al. [19]. Further investigation is required to measure contrast sensitivity at different spatial frequencies in order to elucidate the underlying cause of reduced functionality with glasses.

It was expected that the difference in the refractive error between high- and lowmyopic groups (−5.52 ± 2.4 D compared to −3.1 ± 1.7 D; *p* < 0.001) would have a significant impact on the unaided visual acuity of high-myopic groups, even though it was not measured. With significantly poorer vision without glasses, a higher proportion of high-myopic presbyopes would have issues seeing both far and near, as they are severely

under-corrected for both distances. This would result in a poorer outcome in functionality without glasses for the high-myopic group. The poorer outcome in QOL regarding uncorrected vision was also reflected in other studies [18,28,29]. Our study shows that a larger proportion of high myopes had difficulty reading and doing near work, as well as waking up with clear vision and looking at an alarm clock without glasses. All the affected activities, as mentioned above, were near-distance activities, as also reported in other studies [18,29]. The lack of distance activities reported without glasses was due to the inability to carry them out without glasses. No high myopes drove without glasses.

This study found that highly myopic PAL wearers had a better score for perception subscales compared to SVD lens wearers. In the perception subscale, highly myopic SVD lens wearers were more "afraid to do things due to their vision" and were also more "frustrated with their glasses." SVD lenses only correct distance vision and not near vision; hence, highly myopic SVD lens wearers will have poor near and intermediate vision, with or without glasses. To overcome blurred vision due to working distance, they may need to remove and put on SVD glasses more frequently, adding to the frustration. Compared with SVD wearers, low-myopic PAL wearers also had a significantly better overall QOL, with no other difference in the other subscales. Despite the lack of a significant difference in each subscale, the significant differences in the overall QOL may be due to the additive effect of multiple components. Other studies have found that near vision is affected while using SVD lenses for presbyopes, while having better outcomes using PAL [30–33]. Poorer near and intermediate vision with SVD lenses may significantly affect QOL outcomes in low myopes; they may also significantly affect the perception subscale for high myopes. Moreover, Pesudovs et al., 2006 found that PAL wearers have reduced sensitivity to light, eye pain, and redness compared to SVD lens wearers, while doing near work, for early presbyopes [33]. As such, the visual comfort from PAL could be another factor in this outcome.

#### *4.2. Strengths and Limitations of the Study*

This is the first study that explores the correction habits of presbyopes and the impact of the severity of myopia on QOL. This study was able to measure the subjective differences between the severity of myopia and the types of visual correction, which was otherwise not significantly different from clinical measures. However, the recruitment rate of patients with high myopia (27.5%) was much lower compared with those having low myopia (72.5%). This, however, is a reflection of myopia's prevalence in the population [3]. Refraction and axial length measurements were not conducted to directly link the causal effect of refractive error and elongation of the eye to the QOL outcome. Unaided visual acuity and contrast sensitivity with spatial frequencies need to be measured to directly understand the contribution of these factors to some of the subscales, such as functionality with and without glasses. More details such as the lens design of PAL should be included in order to further understand whether it has an impact on QOL. Though the RSVP questionnaire has been shown to be deficient in several psychometric properties with underutilised response scales, it was chosen not only because it was validated but also because it includes measures for quality of vision and life [11–15,34–36].

#### *4.3. Suggestions for Future Work*

From this study, the QOL assessment recorded outcomes that could not be measured through typical clinical tests or may be deemed clinically insignificant. Hence, such questionnaires should be administered during dispensing to achieve higher success rates. Work should be done to understand which are the important and contributing subscales for each eye condition and interventions, in order to apply the right questionnaire for each condition. A systematic review could be done on all types of vision correction used for presbyopia, such as PAL, SVD, contact lenses, and intraocular lenses, in order to understand their impact on QOL.

#### **5. Conclusions**

This study was able to measure significant subjective feedback from the RSVP questionnaire that was not found clinically (visual acuity). It was found that a significantly higher proportion of highly myopic presbyopes reported lower vision-related QOL across both the QOL and functionality subscales. Despite having similar best-corrected vision, PAL wearers had better QOL outcomes than SVD lens wearers with low myopia. Moreover, PAL wearers with high myopia had better perception than SVD wearers with high myopia. Therefore, wearing PAL could be a better option to improve the QOL in myopic presbyopes of various myopia levels.

**Author Contributions:** Conceptualisation, B.D., A.Y. (Anna Yeo) and N.R.; methodology, A.Y. (Anna Yeo), N.R., S.Y.L. and A.Y. (Adeline Yang); formal analysis, Y.L.W., S.Y.L. and A.Y. (Adeline Yang); investigation, N.R. and S.Y.L.; resources, A.Y. (Anna Yeo) and B.D.; writing—original draft preparation, S.Y.L. and A.Y. (Adeline Yang); writing—review and editing, B.D., Y.L.W., A.Y. (Anna Yeo) and N.R.; supervision, A.Y. (Adeline Yang), A.Y. (Anna Yeo) and N.R.; project administration, A.Y. (Adeline Yang), A.Y. (Anna Yeo) and N.R.; funding acquisition, B.D. and A.Y. (Anna Yeo). All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was done in collaboration with Essilor International. Students and staff were not paid by this collaboration, and participants were remunerated SGD 20 each for taking part in this study.

**Institutional Review Board Statement:** IRB approval No.: 201604-01. The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Institutional Review Board (or Ethics Committee) of Singapore Polytechnic (Protocol code: 201604-01 and Date of approval: 25-07-2016).

**Informed Consent Statement:** Informed consent was obtained from all subjects involved in the study.

**Data Availability Statement:** Please contact corresponding author for data.

**Acknowledgments:** To Charmaine, Eunice, Gao Jun, Gao Ming, Huda, Joseph, Kelly, Lynn, Rui Qi, Yi Xin, Zhan Foong, and Zhixun for their assistance in collecting the data.

**Conflicts of Interest:** Adeline Yang, Yee Ling Wong, Anna Yeo, and Björn Drobe are employees of Essilor International.

#### **Abbreviations**

Quality of life (QOL), spherical equivalent (SE), diopters (D), refractive status and vision profile (RSVP), progressive addition lenses (PAL), single vision distance (SVD) lenses, visual analogue scales (VAS).

#### **References**


**5.** *Chlorella* **as a feed supplement for humans**

Microalgae are effective producers of high-protein biomass due to their quick growth rates and use of renewable resources. Microalgae are photosynthetic heterotrophic organisms that include vital amino acids, protein, minerals, vitamins, chlorophylls, antioxidants, and bioactive compounds [64]. Microalgae have been used in food and medicine because of their qualities. Researchers have recently become interested in the immunostimulating effects of microalgae.

The use of algae as animal feed is more frequent than the use of algae in human diets. A vast number of nutritional and toxicological studies revealed that algal biomass can be employed as a beneficial feed supplement that can effectively replace conventional protein sources (soy, fish meal, rice bran, etc.) [65]. Seaweeds are also high in minerals, including salt, potassium, and iodine, as well as fiber. Supplementation of seaweeds to improve the texture of foods is another potential area where their use becomes crucial [66]. Both national governments and intergovernmental organizations have a role to play in re-evaluating the potential of *Spirulina* to meet both their own food security demands as well as a tool for their international development and emergency response initiatives [39]. Algae are high in vitamins, minerals, proteins, polyunsaturated fatty acids, antioxidants, and other nutrients [67]. The enormous potential of microalgae arises from the fact that they are less thoroughly studied than agricultural crops, that they may be cultivated in conditions that are inappropriate for plants (requiring less or no seasonality), and that some species produce several times more than plants. Their potential for producing useful molecules or biomass is generally recognized, and they can be employed to improve the nutritional value of food and feed since they use sunlight energy more efficiently.


*4.2. Determining the Number of Buses Needed to Drive the Trips*

The number of buses needed is calculated in two steps. First, the number of buses required to drive the trips are calculated. This will be determined by the highest number of buses in traffic during the peak periods, and it will be equal to the number of conventional buses required. After that, there is a calculation of how many extra buses are needed in order to have time to charge electric buses. This number can be zero or larger, depending on the timetable and charging strategy. The number of extra buses is calculated in the next section.

We start by looking in detail at each bus needed to drive the trips from one of the two end stops, and later we derive the formulas needed to calculate the number of buses from the detailed analysis. The use of the buses is illustrated in Figure 4. There, we can see that bus 1 starts the first trip at time *T*start according to the timetable, and before that, it has used some time driving from the depot to the start of the route, illustrated by the light blue bar. bus 1 drive the first trip during the time shown by the green bar, and there is a need for layover time at the end of it. One headway time after bus 1, bus 2 starts the second trip, followed by bus 3 and 4 after each additional headway time. Thus, the number of buses initially increases by one bus for each headway time that passes. The increase in number of buses stops after the gross trip time, because at this point, the buses which have been driving the route in the other direction have arrived and had their layover time, and they are ready to drive the next trip as a return trip. Therefore, after the gross trip time, the number of buses in traffic does not need to be increased as long as the headway is constant. Figure 4 shows that the buses alternate driving the route in both directions, as indicated by the green and blue bars.

**Figure 4.** Example of buses needed to drive the trips during early morning traffic.

The headway is reduced during the morning rush hours after some time in the early morning. There are no longer enough of buses returning from earlier trips to start all the trips. If the headway during rush hour is half of the headway during the early morning, the number of buses will need to increase, as shown in Figure 5, in which the morning rush hours starts at 06:00 and ends at 09:00. Note that these times show when the headway changes for the departures from the end stop. Further down the line, the reduced headway will occur later, as it takes some time for the buses to drive from the end stop. Just like at the start of the traffic in early morning, there will be a need for more buses at

the beginning of the rush hours. In this example, every second bus starting a trip from the end stop must be an additional bus coming from the depot. As before, the number of buses increases, now by one every second headway time. This continues for a time equal to the gross trip time when enough buses arrive from the other direction of the route.

**Figure 5.** Example of buses needed to drive the trips during early morning traffic and the morning rush hours.

At the end of the rush hour, when the headway is increased, not all buses arriving from the other direction are needed, so after the end of the morning peak, some of the buses are taken out of traffic and return to the depot.

Based on the previous analysis, we can determine the number of buses needed in traffic during the whole day. Note that we previously showed which bus is driving which trip, so that each row in the diagram is the schedule for one particular bus during the day. In the following analysis, we will derive a diagram that looks very similar, but it only shows how many buses are occupied by different activities during the day, without showing which bus is doing what. This way, we can simplify the analysis a lot, and do not need to plan the schedules of the buses. On the other hand, this analysis cannot capture all the small details involved in planning bus schedules, and some of the details in the scheduling are instead included as factors to take into account that it is not possible to plan bus schedules completely without slack for the bus and drivers.

The number of buses required for the traffic will vary during the day, as shown in the diagram in Figure 6, and it is derived from the timetable and data regarding driving time and layover time for the route. We will later use this diagram to determine how much time is available for charging during different parts of the day. Right now, we only need to know the number of buses required to drive during the off-peak period, during the peak times and in the evening. Note that despite being similar to the timetable diagram in Figure 2, this shows the total number of busses in traffic, while the timetable diagram shows the frequency of departures. How many buses are needed will not only depend on the timetable but also on the time it takes to drive the route. A short route of course needs fewer buses to follow a certain timetable than a longer bus route with the same timetable.

The number of buses required for driving all trips during peak traffic:

$$N\_{\text{busPeak}} = 2 \times T\_{\text{TripGrossPeak}} \times \eta\_{\text{DepPerrfloorPeak}} \tag{1}$$

where the gross trip time in the peak is:

$$T\_{\text{TripGrosakPeak}} = T\_{\text{TripNetPeak}} + T\_{\text{LaysoverPeak}} \tag{2}$$

**Figure 6.** Number of buses in traffic during the day. Derived from the timetable and route parameters.

As stated earlier we do not round this off to the nearest higher integer, but instead analyse the TCO based on a non-integer number of buses. This way of calculating the number of buses assumes that the gross trip time is shorter than the peak periods. That is the case for most routes in cities, at least in Sweden, since the peak period in the morning and afternoon are typically 2 h and 3 h or more, respectively, while very few routes have more than a 2-h trip time. The number of buses in traffic during the midday off-peak period can be calculated in the same way:

$$N\_{\text{busOfPeak}} = 2 \times T\_{\text{TripCorosOfPeak}} \times \text{rt}\_{\text{DepPerflowOfPeak}}\tag{3}$$

where the gross trip time off-peak is:

$$T\_{\text{TripCorossOfPeak}} = T\_{\text{TripNetOfPeak}} + T\_{\text{LayowerOfPeak}} \tag{4}$$

Finally, the number of buses in traffic during the evening is:

$$N\_{\text{busEvering}} = 2 \times T\_{\text{TripCoros} \text{Evering}} \times \eta\_{\text{DepPerflowEvering}} \tag{5}$$

where the evening gross trip time is:

$$T\_{\text{TripGrossEvering}} = T\_{\text{TripNetEvering}} + T\_{\text{LaycoverEvering}} \tag{6}$$


**3.2 Capacity model**

The capacity model is known as the "Capacity Outage Probability Table (COPT)" that contains all capacity states (available and non-avoidable) in an ascending order of outage magnitude. Each outage (capacity state) is multiplied by its associated probability. If the system contains identical units, the binomial distribution can be used [12].

in the preceding sections are convolved (combined) in the process. The unit of the *LOLE* is in days per year (d/y). The *LOLE* evaluation method is expressed in the

By observing the above equation, the *LOLE* would be applicable if, and only if,

In power system planning another reliability index beside the *LOLE* may be required, so as to determine the size and magnitude of the load that has been lost due to severe outages (i.e., when ), Hence, the *ϵDNS* can be

Since power systems are in fact energy systems, the expected energy not supplied index may be deduced as per **Figure 4**. The *ϵENS* index is used in order to calculate energy sale, which is the real revenue for any electric company.

The ratio of expected energy not supplied ( ) to the system's total energy

*ϵENSpu* ¼ *ϵENS*

ð Þ *oi days=year L*½ � *max* . *Reserve* (4)

ð Þ� *DNSi pi MW=year L*½ � *max* . *Reserve* (5)

ð Þ� *ENSi pi MWh=year L*½ � *max* . *Reserve* (6)

*TED* (7)

following mathematical formula:

*Reliability Evaluation of Power Systems DOI: http://dx.doi.org/10.5772/intechopen.85571*

obtained as follows:

*LOLE* ¼ ∑

**3.5 Expected demand not supplied (***ϵDNS***)**

*ϵDNS* ¼ ∑

**3.6 Expected energy not supplied (***ϵENS***)**

*ϵENS* ¼ ∑

**3.7 Energy index of reliability (***EIR***)**

demanded (*TED*) can be found as

*Load duration curve with energy not served.*

**Figure 4.**

**147**

*n i*¼1

*n i*¼1

*n i*¼1 *ti* � *pi*

the maximum load ( ) exceeds the system reserve. Consider now:


*5.3.2. Internal air quality*

Monitoring identified several spaces with very good IAQ. Given the prevalence of window opening this result was hardly surprising, but will of course have a thermal penalty. In cir‐ cumstances where window opening is common, the use of an MVHR system is not only in‐ effective but is also an additional primary energy burden on the dwelling as the fan continues to run at the same rate regardless of IAQ conditions. Where window opening was not prevalent, maximum values of CO2concentration were frequently found to rise and be sustained above recognised maximum desirable levels of 1000ppm. Figure 11 illustrates a particular situation from a bedroom in Dwelling 2 over the monitoring period but this is typical in monitored apartments throughout the project.

**Figure 12.** Physical parameters in Dwelling 2 twin bedroom – high CO2 concentrations

The bedrooms are of particular interest as windows are generally closed at night due to is‐ sues of external noise and as the occupants are asleep no further occupant intervention oc‐ curs. Accordingly these spaces are entirely reliant to the MVHR system to deliver ventilation and good IAQ.


**3. Results**

### *3.1. Attitudes and Lifestyle Factors toward Nutrition*

At the beginning of the survey, attitude-related 1–5 Likert questions were listed in order to characterize different age groups based on their opinion about health and age-related aspects of nutrition (Table 3).

**Table 3.** Attitudes toward nutrition in different age groups (level of agreement, 1–5 Likert scale).

According to the results, each age group perceived strong connection between nutrition and health. While all age groups agreed that "healthy diet has a great impact on the prevention of diseases in older adults," the oldest group attached significantly more importance to "for older adults, diet has a more important role in health" compared to other age groups. The importance of a healthy diet increases with age according to the responses.

The questionnaire also contained lifestyle-related multiple choice questions, which allowed further differentiation of age groups (Table 4).

**Table 4.** Perception of health-related lifestyle factors in different age groups.

Significant difference between age groups was not found in terms of self-estimation of health, the need for weight loss, use of dietary supplements, and alcohol consumption habits. Younger respondents exercise more often, although they still tend to think it is below the required level. Stressful lifestyle and not enough sleep are the most common problems reported by the middle-aged groups. Older adults rarely smoke and this group has significantly more time to eat and cook than the younger respondents. Consumers between 30 and 39 years and over 60 years state that they pay more attention to diet compared to the average.