Search results for: effective refractive index

Authors: Ji-Suk Kim, Dong-Pil Kim, Kee-Rae Gang, Yoon Ho Choi

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This study was conducted to investigate the characteristics of butterfly communities according to the habitat characteristics of Korean veins. The survey sites were 12 mountains located in the vein, and 12~30 quadrats (200 in total) were set. The species richness and biodiversity were different according to land use type. Two types of land use (forest and graveyard) showed lower species diversity index values ​​than other land use types. The species abundance was low in the forest and graveyards, and grasslands, forest tops, cultivated areas and urban areas showed relatively high species richness. The altitude was not statistically significant with the number of species of butterflies and biodiversity index. The degree of canopy closure showed a negative correlation. As a result of interspecific correlation analysis, it was confirmed that there was a very high correlation (R2=0.746) between Lycaena phlaeas and Pseudozizeeria maha argia, Choaspes benjaminii japonica and Argyronome ruslana.

Keywords: land use type, species diversity index, correlation, canopy closure

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Authors: Mahmoud Hassan

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Understanding the impact of market- and non-market-based environmental policy instruments on renewable energy consumption (REC) is crucial for the design and choice of policy packages. This study aims to empirically investigate the effect of environmental policy stringency index (EPS) and its components on REC in 27 OECD countries over the period from 1990 to 2015, and then use the results to identify what the appropriate environmental policy mix should look like. By relying on the two-step system GMM estimator, we provide evidence that increasing environmental policy stringency as a whole promotes renewable energy consumption in these 27 developed economies. Moreover, policymakers are able, through the market- and non-market-based environmental policy instruments, to increase the use of renewable energy. However, not all of these instruments are effective for achieving this goal. The results indicate that R&D subsidies and trading schemes have a positive and significant impact on REC, while taxes, feed-in tariff and emission standards have not a significant effect. Furthermore, R&D subsidies are more effective than trading schemes for stimulating the use of clean energy. These findings proved to be robust across the three alternative panel techniques used.

Keywords: environmental policy stringency, renewable energy consumption, two-step system-GMM estimation, linear dynamic panel data model

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Authors: Orkide Donma, Mustafa M. Donma

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Morbid obesity is a health threatening condition particularly in children. Generally, it leads to the development of metabolic syndrome (MetS) characterized by central obesity, elevated fasting blood glucose (FBG), triglyceride (TRG), blood pressure values and suppressed high density lipoprotein cholesterol (HDL-C) levels. However, some ambiguities exist during the diagnosis of MetS in children below 10 years of age. Therefore, clinicians are in the need of some surrogate markers for the laboratory assessment of pediatric MetS. In this study, the aim is to develop an index, which will be more helpful during the evaluation of further risks detected in morbid obese (MO) children. A total of 235 children with normal body mass index (N-BMI), with varying degrees of obesity; overweight (OW), obese (OB), MO as well as MetS participated in this study. The study was approved by the Institutional Ethical Committee. Informed consent forms were obtained from the parents of the children. Obesity states of the children were classified using BMI percentiles adjusted for age and sex. For the purpose, tabulated data prepared by WHO were used. MetS criteria were defined. Systolic and diastolic blood pressure values were measured. Parameters related to glucose and lipid metabolisms were determined. FBG, insulin (INS), HDL-C, TRG concentrations were determined. Diagnostic Obesity Notation Model Assessment Laboratory (DONMA_LAB) Index [ln TRG/HDL-C*INS] was introduced. Commonly used insulin resistance (IR) indices such as Homeostatic Model Assessment for IR (HOMA-IR) as well as ratios such as TRG/HDL-C, TRG/HDL-C*INS, HDL-C/TRG*INS, TRG/HDL-C*INS/FBG, log, and ln versions of these ratios were calculated. Results were interpreted using statistical package program (SPSS Version 16.0) for Windows. The data were evaluated using appropriate statistical tests. The degree for statistical significance was defined as 0.05. 35 N, 20 OW, 47 OB, 97 MO children and 36 with MetS were investigated. Mean ± SD values of TRG/HDL-C were 1.27 ± 0.69, 1.86 ± 1.08, 2.15 ± 1.22, 2.48 ± 2.35 and 4.61 ± 3.92 for N, OW, OB, MO and MetS children, respectively. Corresponding values for the DONMA_LAB index were 2.17 ± 1.07, 3.01 ± 0.94, 3.41 ± 0.93, 3.43 ± 1.08 and 4.32 ± 1.00. TRG/HDL-C ratio significantly differed between N and MetS groups. On the other hand, DONMA_LAB index exhibited statistically significant differences between N and all the other groups except the OW group. This index was capable of discriminating MO children from those with MetS. Statistically significant elevations were detected in MO children with MetS (p < 0.05). Multiple parameters are commonly used during the assessment of MetS. Upon evaluation of the values obtained for N, OW, OB, MO groups and for MO children with MetS, the [ln TRG/HDL-C*INS] value was unique in discriminating children with MetS.

Keywords: children, index, laboratory, metabolic syndrome, obesity

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Authors: Ujjwala Bhand, Mridula Goel

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Global Competitiveness Index (GCI) prepared by World Economic Forum has become a benchmark in studying the competitiveness of countries and for understanding the factors that enable competitiveness. Innovation is a key pillar in competitiveness and has the unique property of enabling exponential economic growth. This paper attempts to analyze how the pillars comprising the Global Competitiveness Index affect innovation and whether GDP growth can directly affect innovation outcomes for a country. The key objective of the study is to identify areas on which governments of developing countries can focus policies and programs to improve their country’s innovativeness. We have compiled a panel data set for top innovating countries and large emerging economies called BRICS from 2007-08 to 2014-15 in order to find the significant factors that affect innovation. The results of the regression analysis suggest that government should make policies to improve labor market efficiency, establish sophisticated business networks, provide basic health and primary education to its people and strengthen the quality of higher education and training services in the economy. The achievements of smaller economies on innovation suggest that concerted efforts by governments can counter any size related disadvantage, and in fact can provide greater flexibility and speed in encouraging innovation.

Keywords: innovation, global competitiveness index, BRICS, economic growth

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Authors: Derya Yucel, Nigar Angın, Dürdane Mart, Meltem Turkeri, Volkan Catalkaya, Celal Yucel

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Chickpea (Cicer arietinum L.) is one of the important legumes widely grown for dietery proteins in semi-arid Mediteranean climatic conditions. To evaluate the genetic diversity with improved heat and drought tolerance capacity in chickpea, thirty-four selected chickpea genotypes were tested under different field-growing conditions (rainfed winter sowing, irrigated-late sowing and rainfed-late sowing) in 2015 growing season. A factorial experiment in randomized complete block design with 3 reps was conducted at the Eastern Mediterranean Research Institute Adana, Turkey. Based on grain yields under different growing conditions, several indices were calculated to identify economically higher-yielding chickpea genotypes with greater heat and drought tolerance capacity. Average across chickpea genotypes, the values of tolerance index, mean productivity, yield index, yield stability index, stress tolerance index, stress susceptibility index, and geometric mean productivity were ranged between 1.1 to 218, 38 to 202, 0.3 to 1.7, 0.2 to 1, 0.1 to 1.2, 0.02 to 1.4, and 36 to 170 for drought stress and 3 to 54, 23 to 118, 0.3 to 1.7, 0.4 to 0.9, 0.2 to 2, 0.2to 2.3, and 23 to 118 for heat stress, respectively. There were highly significant differences observed among the tested chickpea genotypes response to drought and heat stresses. Among the chickpea genotypes, the Aksu, Arda, Çakır, F4 09 (X 05 TH 21-16189), FLIP 03-108 were identified with a higher drought and heat tolerance capacity. Based on our field studies, it is suggested that the drought and heat tolerance indicators of plants can be used by breeders to select stress-resistant economically productive chickpea genotypes suitable to grow under Mediteranean climatic conditions.

Keywords: irrigation, rainfed, stress susceptibility, tolerance indice

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Authors: Sara Tokhi Arab, Rozo Noguchi, Tofeal Ahamed

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Drought is a natural disaster that occurs in a region due to a lack of precipitation and high temperatures over a continuous period or in a single season as a consequence of climate change. Precipitation deficits and prolonged high temperatures mostly affect the agricultural sector, water resources, socioeconomics, and the environment. Consequently, it causes agricultural product loss, food shortage, famines, migration, and natural resources degradation in a region. Agriculture is the first sector affected by drought. Therefore, it is important to develop an agricultural drought risk and loss assessment to mitigate the drought impact in the agriculture sector. In this context, the main purpose of this study was to assess yield loss using composite drought indices in the drought-affected vineyards. In this study, the CDI was developed for the years 2016 to 2020 by comprising five indices: the vegetation condition index (VCI), temperature condition index (TCI), deviation of NDVI from the long-term mean (NDVI DEV), normalized difference moisture index (NDMI) and precipitation condition index (PCI). Moreover, the quantitative principal component analysis (PCA) approach was used to assign a weight for each input parameter, and then the weights of all the indices were combined into one composite drought index. Finally, Bayesian regularized artificial neural networks (BRANNs) were used to evaluate the yield variation in each affected vineyard. The composite drought index result indicated the moderate to severe droughts were observed across the Kabul Province during 2016 and 2018. Moreover, the results showed that there was no vineyard in extreme drought conditions. Therefore, we only considered the severe and moderated condition. According to the BRANNs results R=0.87 and R=0.94 in severe drought conditions for the years of 2016 and 2018 and the R= 0.85 and R=0.91 in moderate drought conditions for the years of 2016 and 2018, respectively. In the Kabul Province within the two years drought periods, there was a significate deficit in the vineyards. According to the findings, 2018 had the highest rate of loss almost -7 ton/ha. However, in 2016 the loss rates were about – 1.2 ton/ha. This research will support stakeholders to identify drought affect vineyards and support farmers during severe drought.

Keywords: grapes, composite drought index, yield loss, satellite remote sensing

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Authors: R. Vidhya, M. Navamuniyammal M. Sivakumar, S. Reeta

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The unplanned urbanization affects the environment due to pollution, conditions of the atmosphere, decreased vegetation and the pervious and impervious soil surface. Considered to be a cumulative effect of all these impacts is the Urban Heat Island. In this paper, the urban heat island effect is studied for the Chennai city, TamilNadu, South India using satellite remote sensing data. LANDSAT 8 OLI and TIRS DATA acquired on 9th September 2014 were used to Land Surface Temperature (LST) map, vegetation fraction map, Impervious surface fraction, Normalized Difference Water Index (NDWI), Normalized Difference Building Index (NDBI) and Normalized Difference Vegetation Index (NDVI) map. The relationship among LST, Vegetation fraction, NDBI, NDWI, and NDVI was calculated. The Chennai city’s Urban Heat Island effect is significant, and the results indicate LST has strong negative correlation with the vegetation present and positive correlation with NDBI. The vegetation is the main factor to control urban heat island effect issues in urban area like Chennai City. This study will help in developing measures to land use planning to reduce the heat effects in urban area based on remote sensing derivatives.

Keywords: land surface temperature, brightness temperature, emissivity, vegetation index

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Authors: Iacopo Testi, Diego Pajarito, Nicoletta Roberto, Carmen Greco

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Today, a consistent segment of the world’s population lives in urban areas, and this proportion will vastly increase in the next decades. Therefore, understanding the key trends in urbanization, likely to unfold over the coming years, is crucial to the implementation of sustainable urban strategies. In parallel, the daily amount of digital data produced will be expanding at an exponential rate during the following years. The analysis of various types of data sets and its derived applications have incredible potential across different crucial sectors such as healthcare, housing, transportation, energy, and education. Nevertheless, in city development, architects and urban planners appear to rely mostly on traditional and analogical techniques of data collection. This paper investigates the prospective of the data science field, appearing to be a formidable resource to assist city managers in identifying strategies to enhance the social, economic, and environmental sustainability of our urban areas. The collection of different new layers of information would definitely enhance planners' capabilities to comprehend more in-depth urban phenomena such as gentrification, land use definition, mobility, or critical infrastructural issues. Specifically, the research results correlate economic, commercial, demographic, and housing data with the purpose of defining the youth economic discomfort index. The statistical composite index provides insights regarding the economic disadvantage of citizens aged between 18 years and 29 years, and results clearly display that central urban zones and more disadvantaged than peripheral ones. The experimental set up selected the city of Rome as the testing ground of the whole investigation. The methodology aims at applying statistical and spatial analysis to construct a composite index supporting informed data-driven decisions for urban planning.

Keywords: data science, spatial analysis, composite index, Rome, urban planning, youth economic discomfort index

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Authors: Tran Dinh Lan, Do Thi Thu Huong

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Among the 17 goals of the United Nations, 2030 Agenda for Sustainable Development, SDG 14.2 and SDG 14.4 under SDG 14 directly address the sustainable management, exploitation, and use of marine ecosystems. To achieve these goals, it is necessary to quantify the level of sustainable use of marine ecosystems, which have been paid attention for more than two decades in the direction of a quantitative approach by indicator and index development using methods of building and analyzing indicators and indices. With the employment of the above methods, over the past two decades, a number of marine ecosystems in Vietnam have been quantitatively evaluated for sustainable use for integrated coastal and marine management. Thirty indicators for sustainable use of marine ecosystems in the Northeast of Vietnam, together with indices, have been developed to assess mangrove, coral, and beach ecosystems. An assessment shows the following results. The mangrove ecosystem declined from sustainable to unsustainable uses in the period 1989-2007. The coral ecosystem in 2003 was at a sensitive point between sustainable and unsustainable uses. The beach ecosystem was evaluated with ten selected beaches in the period 2013-2018, showing that nine beaches are at a sustainable level, and one beach is at an unsustainable level. The Thua Thien-Hue coastal lagoon ecosystem assessed by 21 indicators of environmental vulnerability in 2014 showed less sustainability. The marine ecosystems around the offshore islands of Bach Long Vi, Con Co, and Tho Chu were tested to assess the level of sustainable use by the index of total economic value. The results show that these ecosystems are being used sustainably but are also at risk of falling to an unsustainable level (Tho Chu). The use of the environmental vulnerability index or economic value index to evaluate ecosystem sustainability only reflects parts of the function or value of the system but does not fully reflect the sustainability of the system.

Keywords: index, indicators, sustainability evaluation, Vietnam marine ecosystems

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Authors: Katherine Dropiewski, Michael Yakimov, Vadim Tokranov, Allan Minns, Pavel Murat, Serge Oktyabrsky

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InAs Quantum Dots (QDs) in a GaAs matrix is a well-documented luminescent material with high light yield, as well as thermal and ionizing radiation tolerance due to quantum confinement. These benefits can be leveraged for high-efficiency, room temperature scintillation detectors. The proposed scintillator is composed of InAs QDs acting as luminescence centers in a GaAs stopping medium, which also acts as a waveguide. This system has appealing potential properties, including high light yield (~240,000 photons/MeV) and fast capture of photoelectrons (2-5ps), orders of magnitude better than currently used inorganic scintillators, such as LYSO or BaF2. The high refractive index of the GaAs matrix (n=3.4) ensures light emitted by the QDs is waveguided, which can be collected by an integrated photodiode (PD). Scintillation structures were grown using Molecular Beam Epitaxy (MBE) and consist of thick GaAs waveguiding layers with embedded sheets of modulation p-type doped InAs QDs. An AlAs sacrificial layer is grown between the waveguide and the GaAs substrate for epitaxial lift-off to separate the scintillator film and transfer it to a low-index substrate for waveguiding measurements. One consideration when using a low-density material like GaAs (~5.32 g/cm³) as a stopping medium is the matrix thickness in the dimension of radiation collection. Therefore, luminescence properties of very thick (4-20 microns) waveguides with up to 100 QD layers were studied. The optimization of the medium included QD shape, density, doping, and AlGaAs barriers at the waveguide surfaces to prevent non-radiative recombination. To characterize the efficiency of QD luminescence, low temperature photoluminescence (PL) (77-450 K) was measured and fitted using a kinetic model. The PL intensity degrades by only 40% at RT, with an activation energy for electron escape from QDs to the barrier of ~60 meV. Attenuation within the waveguide (WG) is a limiting factor for the lateral size of a scintillation detector, so PL spectroscopy in the waveguiding configuration was studied. Spectra were measured while the laser (630 nm) excitation point was scanned away from the collecting fiber coupled to the edge of the WG. The QD ground state PL peak at 1.04 eV (1190 nm) was inhomogeneously broadened with FWHM of 28 meV (33 nm) and showed a distinct red-shift due to self-absorption in the QDs. Attenuation stabilized after traveling over 1 mm through the WG, at about 3 cm⁻¹. Finally, a scintillator sample was used to test detection and evaluate timing characteristics using 5.5 MeV alpha particles. With a 2D waveguide and a small area of integrated PD, the collected charge averaged 8.4 x10⁴ electrons, corresponding to a collection efficiency of about 7%. The scintillation response had 80 ps noise-limited time resolution and a QD decay time of 0.6 ns. The data confirms unique properties of this scintillation detector which can be potentially much faster than any currently used inorganic scintillator.

Keywords: GaAs, InAs, molecular beam epitaxy, quantum dots, III-V semiconductor

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Authors: Kensuke Otsuyama

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The United Nation World Conference on Disaster Risk Reduction was held in Sendai, Japan, in 2015 and priorities for actions until 2030 were adopted for the next 15 years. Although one of these priorities is to ‘build back better’, there is neither a consensus definition of better recovery, nor indicators to measure better recovery. However, the community is considered as a key driver of recovery nowadays, and participation is a key word for effective recovery. In order to understand more about participatory community recovery, the author investigated recovery from the Great East Japan Earthquake and Tsunami (GEJET) in Kesennuma, a severely affected city. The research sought to: 1) Identify the elements that contribute to better recovery at the community level, and 2) analyze the role of community volunteers for disaster risk reduction for better recovery. A Participatory Community Recovery Index (PCRI) was created as a tool to measure community recovery. The index adopts seven primary indicators and 20 tertiary indicators, including: socio-economic aspect, housing, health, environment, self-organization, transformation, and institution. The index was applied to nine districts in Kesennuma city. Secondary and primary data by questionnaire surveys with local residents’ organization leaders and interviews with crisis management department officials in city government were also obtained. The indicator results were transformed into scores among 1 to 5, and the results were shown for each district. Based on the result of PCRI, it was found that the s Local Social Welfare Council played an important role in facilitating better recovery, enhancing community volunteer involvement to allow elderly residents to initiate local volunteer work for more affected single-living elderly people. Volunteers for the elderly by the elderly played a crucial role to strengthen community bonding in Kesennuma. In this research, the potential of community volunteers and inter-linkage with DRR activities are discussed.

Keywords: recovery, participation, the great East Japan earthquake and tsunami, community volunteers

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Authors: Arezoo Fallahi, Siamak Derakhshan, Parvaneh Taymoori, Babak Nematshahrbabaki

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Background: Osteoporosis, the most common metabolic bone disease, is an important health care issue. Not only the cost of disease is high but also is one of the causes of disability and mortality and effect on quality of life. Although self-care is effective on disease, s control and treatment but still effective factors on self-care of patient, s viewpoint have not been survey. The aim of this study was to explore effective factors on self-care in women with osteoporosis. Materials and methods: This study was done by conventional content analysis approach in year 2014. Through purposeful sampling 15 women referred to bone mass densitometry centers participated in this study. Inclusion criteria were: Women older than 50 years old with osteoporosis, final diagnosis of osteoporosis for over six –month period, T-score index below -2.5 (lower back or hip), drug use by patients with a physician’s prescription, ability in speaking and attending to participate in the study. Data was collected by face to face and group semi-structure deep interviews and analyzed via content analysis method. To support of rigor of data, criteria credibility, confirmability and transferability were used. Results: during data analysis five categories developed: “hope and disability in the face of illness”, “mutual roles of physician”, “role of family” and “administrative centers and organizations”. To perform self-care behaviors, the participations of this study emphasized on pay attention to their own healthy, regarding patients' rights by physician, pay attention to women's health by men, and the role of media especially radio and television. Conclusion: the finding of the study showed that women’s responsibility with osteoporosis for their health is not a factor but it is multifactorial. Increasing life expectancy in patients, attention to patients needs by physician, increasing health promotion programs in the media and enhancing role of family may provide conditions and infrastructure to empowerment women in doing self-care behavior.

Keywords: women, osteoporosis, self-care, content analysis

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Authors: Béchir Wanassi, Béchir Azzouz, Taher Halimi, Mohamed Ben Hassen

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Mechanical recycling of post-industrial cotton yarn wastes, as well as the effects of passage number on the properties of reclaimed fibers, have been investigated. A new Modified Fiber Quality Index (MFQI) and Spinning Consistency Index (MSCI) for the characterization of the quality are presented. This index gives the real potential of spinnability according to its physical properties. The best quality of reclaimed fibers (after 7th passage) was used to produce rotor yarns. 100% recycling cotton yarns were produced in open-end spinning system with different rotor speed (i.e. 65000, 70000, and 80000 rpm), opening roller speed (i.e. 7700, 8200, and 8700 rpm) and twist factor (i.e. 137, 165, and 183). The effects of spinning parameters were investigated to evaluate a 100% recycling cotton yarns quality (TQI, hairiness, thin places, and thick places) using DOE method.

Keywords: cotton wastes, DOE, mechanical recycling, rotor spinning

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Authors: M. Firoz Kalam, Wilfried Schuetz, Jan Hendrik Bredehoeft

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In this research, diesel oil properties, such as aniline point, density, diesel index, cetane index and cetane number before and after treatment were studied. The investigation was considered for diesel oil samples after batch adsorption process using powdered activated carbon. Batch distillation process was applied to all treated diesel oil samples for separation of the solid-liquid mixture. The diesel oil properties were studied to observe the impact of adsorptive desulfurization process on fuel quality. Results showed that the best cetane number for desulfurized diesel oil was found at the best-operating conditions 60℃, 10g activated carbon and 180 minute contact time. The best-desulfurized diesel oil cetane number was obtained around 51 while the cetane number of untreated diesel oil was 34. Results also showed that the calculated cetane number increases as the operating temperature and amounts of adsorbent increases. This behavior was same for other diesel oil properties such as aniline point, diesel index, cetane index and density. The best value for all the fuel properties was found at same operating conditions mentioned above. Thus, it can be concluded that adsorptive desulfurization using powdered activated carbon as adsorbent had significantly improved the fuel quality of diesel oil by reducing aromatic contents of diesel oil.

Keywords: activated carbon, adsorption, desulfurization, diesel oil, fuel quality

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Authors: Dwi Wijiastutik, Tarjo, Yuni Rimawati

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The purpose of this empirical study is to analyse how to the market reaction and the conservative degree changes on the adoption of International Financial Reporting Standart (IFRS) through Jakarta Islamic Index. The study also has given others additional analysis on the profitability, capital structure and size company toward IFRS adoption. The data collection methods used in this study reveals as secondary data and deep analysis to the company’s annual report and daily price stock at yahoo finance. We analyse 40 companies listed on Jakarta Islamic Index from 2010 to 2014. The result of the study concluded that IFRS has given a different on the depth analysis to the two of variance analysis: Moderated Regression Analysis and Wilcoxon Signed Rank to test developed hypotheses. Our result on the regression analysis shows that market response and conservatism principle is not significantly after IFRS Adoption in Jakarta Islamic Index. Furthermore, in addition, analysis on profitability, capital structure, and company size show that significantly after IFRS adoption. The findings of our study help investor by showing the impact of IFRS for making decided investment.

Keywords: IFRS, earnings response coefficient, conservatism principle

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Authors: D. A. Carnegie

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Whilst there is a movement towards increased digital augmentation in order to facilitate effective tertiary learning, this must come with an awareness of the limitations of such an approach. Learning is best achieved in an environment that includes their learning peers where difficulties can be shared and learning enabled. Policy that advocates for digital technology in place of a physical classroom is dangerous and is often driven by financial concerns rather than pedagogical ones. In this paper, a mostly digital-less form of teaching is presented – one that has proven to be extremely effective. Implicit is anecdotal evidence that student prefer the old overhead transparencies to PowerPoint presentations. Varying and reinforcing assessment, facilitation of effective note-taking, and just actively engaging with students is at the core of a good tertiary education experience. Digital techniques can augment and complement, but not replace these core personal teaching requirements.

Keywords: engineering education, active classroom engagement, effective note taking, reinforcing assessment

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Authors: Mesbaholdin Salami, Farzad Movahedi Sobhani, Mohammad Sadegh Ghazizadeh

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Evaluation of organizational performance is among the most important measures that help organizations and entities continuously improve their efficiency. Organizations can use the existing data and results from the comparison of units under investigation to obtain an estimation of their performance. The Malmquist Productivity Index (MPI) is an important index in the evaluation of overall productivity, which considers technological developments and technical efficiency at the same time. This article proposed a model based on the multistage MPI, considering limited data (Grey’s theory). This model can evaluate the performance of units using limited and uncertain data in a multistage process. It was applied by the electricity market manager to Iran’s electric power supply chain (EPSC), which contains uncertain data, to evaluate the performance of its actors. Results from solving the model showed an improvement in the accuracy of future performance of the units under investigation, using the Grey’s system theory. This model can be used in all case studies, in which MPI is used and there are limited or uncertain data.

Keywords: Malmquist Index, Grey's Theory, CCR Model, network data envelopment analysis, Iran electricity power chain

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Authors: Ali Abojassim, Nabeel Kadhim, Adil Jaber, Ali Hussein

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Water quality index (WQI) is valuable and unique rating to depict the total water quality status in a single term that is helpful for the selection of appropriate treatment technique to meet the concerned issues. Fifteen surface water samples were collected from the Euphrates river within AlHaydria is sub district of AL-Najaf (Iraq). The quality of surface water were evaluated by testing various physicochemical parameters such as pH, Total Dissolved Solid (TDS), , Calcium, Chloride, Sulphate and Electrical conductivity. The WQI for all samples were found in the range of 25.92 to 47.22. The highest value of WQI was observed in the Ali Hajj Hassan(SW4,SW8), El Haj Abdel Sayed (SW 10 to SW 12)and Hasan alsab(SW 14) sampling locations. Most of the water samples within study area were found good to moderate categories. most of the water samples for study area were found good as well as moderate categories

Keywords: water quality index, GIS, physicochemical parameters, Iraq Standards for irrigation purpose 2012

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Authors: Mohd Azraei Pangah Pa'at, Mohd Ruzlin Mohd Mokhtar, Norhidayu Rameli, Tashia Marie Anthony, Huzainie Shafi Abd Halim

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Partial Discharge (PD) diagnostic mapping testing is one of the main diagnostic testing techniques that are widely used in the field or onsite testing for underground power cable in medium voltage level. The existence of PD activities is an early indication of insulation weakness hence early detection of PD activities can be determined and provides an initial prediction on the condition of the cable. To effectively manage the results of PD Mapping test, it is important to have acceptable criteria to facilitate prioritization of mitigation action. Tenaga Nasional Berhad (TNB) through Distribution Network (DN) division have developed PD severity model name Severity Index (SI) for offline PD mapping test since 2007 based on onsite test experience. However, this severity index recommendation action had never been revised since its establishment. At presence, PD measurements data have been extensively increased, hence the severity level indication and the effectiveness of the recommendation actions can be analyzed and verified again. Based on the new revision, the recommended action to be taken will be able to reflect the actual defect condition. Hence, will be accurately prioritizing preventive action plan and minimizing maintenance expenditure.

Keywords: partial discharge, severity index, diagnostic testing, medium voltage, power cable

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Authors: Mustafa M. Donma, Orkide Donma

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Obesity is a clinical state associated with low-grade inflammation. It is also a major risk factor for insulin resistance (IR). In its advanced stages, metabolic syndrome (MetS), a much more complicated disease which may lead to life-threatening problems, may develop. Obesity-mediated IR seems to correlate with the inflammation. Human studies performed particularly on pediatric population are scarce. The aim of this study is to detect possible associations between inflammation and IR in terms of some related ratios. 549 children were grouped according to their age- and sex-based body mass index (BMI) percentile tables of WHO. MetS components were determined. Informed consent and approval from the Ethics Committee for Clinical Investigations were obtained. The principles of the Declaration of Helsinki were followed. The exclusion criteria were infection, inflammation, chronic diseases and those under drug treatment. Anthropometric measurements were obtained. Complete blood cell, fasting blood glucose, insulin, and C-reactive protein (CRP) analyses were performed. Homeostasis model assessment of insulin resistance (HOMA-IR), systemic immune inflammation (SII) index, tense index, alanine aminotransferase to aspartate aminotransferase ratio (ALT/AST), neutrophils to lymphocyte (NLR), platelet to lymphocyte, and lymphocyte to monocyte ratios were calculated. Data were evaluated by statistical analyses. The degree for statistical significance was 0.05. Statistically significant differences were found among the BMI values of the groups (p < 0.001). Strong correlations were detected between the BMI and waist circumference (WC) values in all groups. Tense index values were also correlated with both BMI and WC values in all groups except overweight (OW) children. SII index values of children with normal BMI were significantly different from the values obtained in OW, obese, morbid obese and MetS groups. Among all the other lymphocyte ratios, NLR exhibited a similar profile. Both HOMA-IR and ALT/AST values displayed an increasing profile from N towards MetS3 group. BMI and WC values were correlated with HOMA-IR and ALT/AST. Both in morbid obese and MetS groups, significant correlations between CRP versus SII index as well as HOMA-IR versus ALT/AST were found. ALT/AST and HOMA-IR values were correlated with NLR in morbid obese group and with SII index in MetS group, (p < 0.05), respectively. In conclusion, these findings showed that some parameters may exhibit informative differences between the early and late stages of obesity. Important associations among HOMA-IR, ALT/AST, NLR and SII index have come to light in the morbid obese and MetS groups. This study introduced the SII index and NLR as important inflammatory markers for the discrimination of normal and obese children. Interesting links were observed between inflammation and IR in morbid obese children and those with MetS, both being late stages of obesity.

Keywords: children, inflammation, insulin resistance, metabolic syndrome, obesity

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Authors: Jiameng Wang, Yunfei Yin, Xiyu Deng

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Parallel optimization is one of the important research topics of data mining at this stage. Taking Classification and Regression Tree (CART) parallelization as an example, this paper proposes a parallel data mining algorithm based on SSP-OGini-PCCP. Aiming at the problem of choosing the best CART segmentation point, this paper designs an S-SP model without data association; and in order to calculate the Gini index efficiently, a parallel OGini calculation method is designed. In addition, in order to improve the efficiency of the pruning algorithm, a synchronous PCCP pruning strategy is proposed in this paper. In this paper, the optimal segmentation calculation, Gini index calculation, and pruning algorithm are studied in depth. These are important components of parallel data mining. By constructing a distributed cluster simulation system based on SPARK, data mining methods based on SSP-OGini-PCCP are tested. Experimental results show that this method can increase the search efficiency of the best segmentation point by an average of 89%, increase the search efficiency of the Gini segmentation index by 3853%, and increase the pruning efficiency by 146% on average; and as the size of the data set increases, the performance of the algorithm remains stable, which meets the requirements of contemporary massive data processing.

Keywords: classification, Gini index, parallel data mining, pruning ahead

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Authors: Chaiyaporn Yuksen, Tapanawat Chaiwan

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Introduction: Emergency medical service (EMS) care for trauma patients must be provided on-scene assessment and essential treatment and have appropriate transporting to the trauma center. The shock index (SI), reverse shock index Glasgow Coma Scale (rSIG), and National Early Warning Score (NEWS) triage tools are easy to use in a prehospital setting. There is no standardized on-scene triage protocol in prehospital care. The primary objective was to determine the accuracy of SI, rSIG, and NEWS to predict the severity of trauma patients in the emergency department (ED). Methods: This was a retrospective cross-sectional and diagnostic research conducted on trauma patients transported by EMS to the ED of Ramathibodi Hospital, a university-affiliated super tertiary care hospital in Bangkok, Thailand, from January 2015 to September 2022. We included the injured patients receiving prehospital care and transport to the ED of Ramathibodi Hospital by the EMS team from January 2015 to September 2022. We compared the on-scene parameter (SI, rSIG, and NEWS) and ED (Emergency Severity Index) with the area under ROC. Results: 218 patients were traumatic patients transported by EMS to the ED. 161 was ESI level 1-2, and 57 was level 3-5. NEWS was a more accurate triage tool to discriminate the severity of trauma patients than rSIG and SI. The area under the ROC was 0.743 (95%CI 0.70-0.79), 0.649 (95%CI 0.59-0.70), and 0.582 (95%CI 0.52-0.65), respectively (P-value <0.001). The cut point of NEWS to discriminate was 6 points. Conclusions: The NEWs was the most accurate triage tool in prehospital seeing in trauma patients.

Keywords: on-scene triage, trauma patient, ED triage, accuracy, NEWS

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Authors: Rabab A. El Wahsh, Hatem M. Marey, Maha Yousif, Asmaa M. Ibrahim

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Background: OSA and COPD are associated with microvascular changes. Retinal microvasculature can be directly and non-invasively examined. Aim: to evaluate retinal vascular tortuosity in patients with COPD, OSA, and overlap syndrome. Subjects and method: Sixty subjects were included; 15 OSA patients, 15 COPD patients, 15 COPD-OSA overlap patients, and 15 matched controls. They underwent digital retinal photography, polysomnography, arterial blood gases, spirometry, ESS, and stop-bang questionnaires. Results: Tortuosity of most retinal vessels was higher in all patient groups compared to the control group; tortuosity was more marked in overlap syndrome. There was a negative correlation between tortuosity of retinal vessels and PO2, O2 saturation, and minimum O2 desaturation, and a positive correlation with PCO2, AHI, O2 desaturation index, BMI and smoking index. Conclusion: Retinal vascular tortuosity occurs in OSA, COPD and overlap syndrome. Retinal vascular tortuosity is correlated with arterial blood gases parameters, polysomnographic findings, smoking index and BMI.

Keywords: OSA, COPD, overlap syndrome, retinal vascular tortuosity

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Authors: Zhi Huang

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This study follows on from previous survey and focus group research exploring the effective teaching process in a translation classroom in Australian universities through case study method. The data analysis draws on social constructivist theory in translation teaching and focuses on teaching process aiming to discover how effective translation teachers conduct teaching in the classroom. The results suggest that effective teaching requires the teacher to have ability in four aspects: classroom management, classroom pedagogy, classroom communication, and teacher roles. Effective translation teachers are able to control the whole learning process, facilitate students in independent learning, guide students to be more critical about translation, giving both positive and negative feedback for students to reflect on their own, and being supportive, patient and encouraging to students for better classroom communication and learning outcomes. This study can be applied to other teachers in translation so that they can reflect on their own teaching in their education contexts and strive for being a more qualified translation teacher and achieving teaching effectiveness.

Keywords: case study, classroom observation, classroom teaching, effective translation teaching, teacher effectiveness

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Authors: Bi-Huei Tsai

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Previous studies on financial distress prediction choose the conventional failing and non-failing dichotomy; however, the distressed extent differs substantially among different financial distress events. To solve the problem, “non-distressed”, “slightly-distressed” and “reorganization and bankruptcy” are used in our article to approximate the continuum of corporate financial health. This paper explains different financial distress events using the two-stage method. First, this investigation adopts firm-specific financial ratios, corporate governance and market factors to measure the probability of various financial distress events based on multinomial logit models. Specifically, the bootstrapping simulation is performed to examine the difference of estimated misclassifying cost (EMC). Second, this work further applies macroeconomic factors to establish the credit cycle index and determines the distressed cut-off indicator of the two-stage models using such index. Two different models, one-stage and two-stage prediction models, are developed to forecast financial distress, and the results acquired from different models are compared with each other, and with the collected data. The findings show that the two-stage model incorporating financial ratios, corporate governance and market factors has the lowest misclassification error rate. The two-stage model is more accurate than the one-stage model as its distressed cut-off indicators are adjusted according to the macroeconomic-based credit cycle index.

Keywords: Multinomial logit model, corporate governance, company failure, reorganization, bankruptcy

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Authors: Binh T. T. Nguyen, Zhenyu Li, Eric Yap, Yi Zhang, Ai-Qun Liu

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Silicon-photonic-sensor system is an emerging class of analytical technologies that use evanescent field wave to sensitively measure the slight difference in the surrounding environment. The wavelength shift induced by local refractive index change is used as an indicator in the system. These devices can be served as sensors for a wide variety of chemical or biomolecular detection in clinical and environmental fields. In our study, a system including a silicon-based micro-ring resonator, microfluidic channel, and optical processing is designed, fabricated for biomolecule detection. The system is demonstrated to detect Clostridium botulinum type A neurotoxin (BoNT) in different water sources. BoNT is one of the most toxic substances known and relatively easily obtained from a cultured bacteria source. The toxin is extremely lethal with LD50 of about 0.1µg/70kg intravenously, 1µg/ 70 kg by inhalation, and 70µg/kg orally. These factors make botulinum neurotoxins primary candidates as bioterrorism or biothreat agents. It is required to have a sensing system which can detect BoNT in a short time, high sensitive and automatic. For BoNT detection, silicon-based micro-ring resonator is modified with a linker for the immobilization of the anti-botulinum capture antibody. The enzymatic reaction is employed to increase the signal hence gains sensitivity. As a result, a detection limit to 30 pg/mL is achieved by our silicon-photonic sensor within a short period of 80 min. The sensor also shows high specificity versus the other type of botulinum. In the future, by designing the multifunctional waveguide array with fully automatic control system, it is simple to simultaneously detect multi-biomaterials at a low concentration within a short period. The system has a great potential to apply for online, real-time and high sensitivity for the label-free bimolecular rapid detection.

Keywords: biotoxin, photonic, ring resonator, sensor

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Authors: Jongsung Kim, Daegun Han, Myungjin Lee, Soojun Kim, Hung Soo Kim

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Recently, the frequency and magnitude of natural disasters are gradually increasing due to climate change. Especially in Korea, large-scale damage caused by heavy rainfall frequently occurs due to rapid urbanization. Therefore, this study proposed a Heavy rain Damage Risk Index (HDRI) using PSR (Pressure – State - Response) structure for heavy rain risk assessment. We constructed pressure index, state index, and response index for the risk assessment of each local government in Gyeonggi-do province, and the evaluation indices were determined by principal component analysis. The indices were standardized using the Z-score method then HDRIs were obtained for 31 local governments in the province. The HDRI is categorized into three classes, say, the safest class is 1st class. As the results, the local governments of the 1st class were 15, 2nd class 7, and 3rd class 9. From the study, we were able to identify the risk class due to the heavy rainfall for each local government. It will be useful to develop the heavy rainfall prediction function by risk class, and this was performed in this issue. Also, this risk class could be used for the decision making for efficient disaster management. Acknowledgements: This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (2017R1A2B3005695).

Keywords: natural disaster, heavy rain risk assessment, HDRI, PSR

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Authors: Tolga Barisik, Ali Fuat Guneri, K. Dastan

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Major industrial facilities have a high potential for fire risk. In particular, the indices used for the detection of hidden fire are used very effectively in order to prevent the fire from becoming dangerous in the initial stage. These indices provide the opportunity to prevent or intervene early by determining the stage of the fire, the potential for hazard, and the type of the combustion agent with the percentage values of the ambient air components. In this system, artificial neural network will be modeled with the input data determined using the Levenberg-Marquardt algorithm, which is a multi-layer sensor (CAA) (teacher-learning) type, before modeling the modeling methods in the literature. The actual values produced by the indices will be compared with the outputs produced by the network. Using the neural network and the curves to be created from the resulting values, the feasibility of performance determination will be investigated.

Keywords: artifical neural networks, fire, Graham Index, levenberg-marquardt algoritm, oxygen decrease percentage index, risk assessment, Trickett Index

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Authors: Nurcihan Hacioglu, Cigdem Gul, Murat Tosunoglu

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In this article, the antibiogram and heavy metal resistance profile of the bacteria isolated from total 34 studied animals (Pelophylax ridibundus = 12, Mauremys rivulata = 14, Natrix natrix = 8) captured around the Biga Stream, are described. There was no database information on antibiogram and heavy metal resistance profile of bacteria from these area’s amphibians and reptiles. In this study, a total of 200 bacteria were successfully isolated from cloaca and oral samples of the aquatic amphibians and reptiles as well as from the water sample. According to Jaccard’s similarity index, the degree of similarity in the bacterial flora was quite high among the amphibian and reptile species under examination, whereas it was different from the bacterial diversity in the water sample. The most frequent isolates were A. hydrophila (31.5%), B. pseudomallei (8.5%), and C. freundii (7%). The total numbers of bacteria obtained were as follows: 45 in P. ridibundus, 45 in N. natrix 30 in M. rivulata, and 80 in the water sample. The result showed that cefmetazole was the most effective antibiotic to control the bacteria isolated in this study and that approximately 93.33% of the bacterial isolates were sensitive to this antibiotic. The Multiple Antibiotic Resistances (MAR) index indicated that P. ridibundus (0.95) > N. natrix (0.89) > M. rivulata (0.39). Furthermore, all the tested heavy metals (Pb+2, Cu+2, Cr+3, and Mn+2) inhibit the growth of the bacterial isolates at different rates. Therefore, it indicated that the water source of the animals was contaminated with both antibiotic residues and heavy metals.

Keywords: bacteriological quality, amphibian, reptile, antibiotic, heavy metal resistance

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Authors: Ankit Shah, R. K. Shrivastava

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Flood and drought are two main features of hydrology which affect the human life. Floods are natural disasters which cause millions of rupees’ worth of damage each year in India and the whole world. Flood causes destruction in form of life and property. An accurate estimate of the flood damage potential is a key element to an effective, nationwide flood damage abatement program. Also, the increase in demand of water due to increase in population, industrial and agricultural growth, has let us know that though being a renewable resource it cannot be taken for granted. We have to optimize the use of water according to circumstances and conditions and need to harness it which can be done by construction of hydraulic structures. For their safe and proper functioning of hydraulic structures, we need to predict the flood magnitude and its impact. Hydraulic structures play a key role in harnessing and optimization of flood water which in turn results in safe and maximum use of water available. Mainly hydraulic structures are constructed on ungauged sites. There are two methods by which we can estimate flood viz. generation of Unit Hydrographs and Flood Frequency Analysis. In this study, Regional Flood Frequency Analysis has been employed. There are many methods for estimating the ‘Regional Flood Frequency Analysis’ viz. Index Flood Method. National Environmental and Research Council (NERC Methods), Multiple Regression Method, etc. However, none of the methods can be considered universal for every situation and location. The Narmada basin is located in Central India. It is drained by most of the tributaries, most of which are ungauged. Therefore it is very difficult to estimate flood on these tributaries and in the main river. As mentioned above Artificial Neural Network (ANN)s and Multiple Regression Method is used for determination of Regional flood Frequency. The annual peak flood data of 20 sites gauging sites of Narmada Basin is used in the present study to determine the Regional Flood relationships. Homogeneity of the considered sites is determined by using the Index Flood Method. Flood relationships obtained by both the methods are compared with each other, and it is found that ANN is more reliable than Multiple Regression Method for the present study area.

Keywords: artificial neural network, index flood method, multi layer perceptrons, multiple regression, Narmada basin, regional flood frequency

Procedia PDF Downloads 390