Search results for: bispectral index (BIS)

Authors: Abdulkadir I.

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Scientists have come to terms with the fact that climate change has been and is expected to cause a significant increase in the severity and frequency of drought events. The northeast region of Nigeria is one of the most, if not the most, affected regions by drought in the country. Therefore, it is on this note that the present study applied ArcGIS and XLSTAT Software and explored drought and its trend in the northeast region of the country using the vegetation health index (VHI), Mann-Kendal, and Sen’s slope between 2001 and 2020. The study also explored the areas that remained under drought and no-drought conditions at intervals of five years for the period under review. The result of Mann-Kendal (-0.07) and Sen’s slope (-0.19) revealed that there was a decreasing trend in VHI over the period under review. The result further showed that the period between 2010 and 2015 had a minimum area of no-drought conditions of about 24%, with Gombe State accounting for the lowest percentage among the six States, about 0.9% of the total area of no-drought conditions. The result further showed the areas that were under drought conditions between 2010 and 2015 represented about 9.1%, with Borno State accounting for the highest percentage among the six States, about 2.5% of the total area under drought conditions. The masked-out areas stood at 66.8%, with Borno State accounting for the highest percentage among the six States, about 20.2% of the total area under drought conditions. Therefore, collective efforts are needed to put in place sustainable land management in the affected areas so as to mitigate the sprawl of desertification in the region.

Keywords: climate change, drought, Mann Kendal, sustainable land management, vegetation health index

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Authors: Meryem Aydin, Serdar Karadas, Ercan Ceyhan

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The research was conducted to determine effects of salt concentrations on emergence of cowpea genotypes. Trials were performed during the year of 2014 on the laboratory of Agricultural Faculty, Selcuk University. Emergency trial was set up according to “Randomized Plots Design” by two factors and four replications with three replications. Samandag, Akkiz-86, Karnikara and Sarigobek cowpea genotypes have been used as trial material in this study. Effects of the five doses of salt concentrations (control, 30 mM, 60 mM, 90 mM and 120 mM) on the ratio of emergency, speed of emergency, average time for emergency, index of sensibility were evaluated. Responses of the cowpea genotypes for salt concentrations were found different. Comparing to the control, all of the investigated characteristics on the cowpea genotypes showed significant reduction by depending on the increasing salt application. According to the effects of salt application, the cowpea genotypes Samandag and Karnikara were the most tolerant in respect to index of sensibility while the Sarigobek genotypes was the most sensitive.

Keywords: cowpea, Vigna sinensis, emergence, salt tolerant

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Authors: Vladyslav Povoroznyuk, Tetiana Orlуk, Nataliia Dzerovych

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Introduction: Back pain is an extremely common health care problem worldwide. Many studies show a link between an obesity and risk of lower back pain. The aim is to study correlation and peculiarities of vertebral pain in women of different age depending on their anthropometric indicators. Materials: 1886 women aged 25-89 years were examined. The patients were divided into groups according to age (25-44, 45-59, 60-74, 75-89 years old) and body mass index (BMI: to 18.4 kg/m2 (underweight), 18.5-24.9 kg/m2 (normal), 25-30 kg/m2 (overweight) and more than 30.1 kg/m2 (obese). Methods: The presence and intensity of pain was evaluated in the thoracic and lumbar spine using a visual analogue scale (VAS). BMI is calculated by the standard formula based on body weight and height measurements. Statistical analysis was performed using parametric and nonparametric methods. Significant changes were considered as p <0.05. Results: The intensity of pain in the thoracic spine was significantly higher in the underweight women in the age groups of 25-44 years (p = 0.04) and 60-74 years (p=0.005). The intensity of pain in the lumbar spine was significantly higher in the women of 45-59 years (p = 0.001) and 60-74 years (p = 0.0003) with obesity. In the women of 45-74 years BMI was significantly positively correlated with the level of pain in the lumbar spine. Obesity significantly increases the relative risk of pain in the lumbar region (RR=0.07 (95% CI: 1.03-1.12; p=0.002)), while underweight significantly increases the risk of pain in the thoracic region (RR=1.21 (95% CI: 1.00-1.46; p=0.05)). Conclusion: In women, vertebral pain syndrome may be related to the anthropometric characteristics (e.g., BMI). Underweight may indirectly influence the development of pain in the thoracic spine and increase the risk of pain in this part by 1.21 times. Obesity influences the development of pain in the lumbar spine increasing the risk by 1.07 times.

Keywords: body mass index, age, pain in thoracic and lumbar spine, women

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Authors: Gulcin Yildiz, Hao Feng

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Soybean proteins are the most widely used and researched proteins in the food industry. Due to soy allergies among consumers, however, alternative legume proteins having similar functional properties have been studied in recent years. These alternative proteins are also expected to have a price advantage over soy proteins. One such protein that has shown good potential for food applications is pea protein. Besides the favorable functional properties of pea protein, it also contains fewer anti-nutritional substances than soy protein. However, a comparison of the physicochemical properties of pea protein isolate (PPI)-starch nanocomplexes and soy protein isolate (SPI)-starch nanocomplexes treated by ultrasound has not been well documented. This study was undertaken to investigate the effects of ultrasound treatment on the physicochemical properties of PPI-starch and SPI-starch nanocomplexes. Pea protein isolate (85% pea protein) provided by Roquette (Geneva, IL, USA) and soy protein isolate (SPI, Pro-Fam® 955) obtained from the Archer Daniels Midland Company were adjusted to different pH levels (2-12) and treated with 5 minutes of ultrasonication (100% amplitude) to form complexes with starch. The soluble protein content was determined by the Bradford method using BSA as the standard. The turbidity of the samples was measured using a spectrophotometer (Lambda 1050 UV/VIS/NIR Spectrometer, PerkinElmer, Waltham, MA, USA). The volume-weighted mean diameters (D4, 3) of the soluble proteins were determined by dynamic light scattering (DLS). The emulsifying properties of the proteins were evaluated by the emulsion stability index (ESI) and emulsion activity index (EAI). Both the soy and pea protein isolates showed a U-shaped solubility curve as a function of pH, with a high solubility above the isoelectric point and a low one below it. Increasing the pH from 2 to 12 resulted in increased solubility for both the SPI and PPI-starch complexes. The pea nanocomplexes showed greater solubility than the soy ones. The SPI-starch nanocomplexes showed better emulsifying properties determined by the emulsion stability index (ESI) and emulsion activity index (EAI) due to SPI’s high solubility and high protein content. The PPI had similar or better emulsifying properties at certain pH values than the SPI. The ultrasound treatment significantly decreased the particle sizes of both kinds of nanocomplex. For all pH levels with both proteins, the droplet sizes were found to be lower than 300 nm. The present study clearly demonstrated that applying ultrasonication under different pH conditions significantly improved the solubility and emulsify¬ing properties of the SPI and PPI. The PPI exhibited better solubility and emulsifying properties than the SPI at certain pH levels

Keywords: emulsifying properties, pea protein isolate, soy protein isolate, ultrasonication

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Authors: N. R. P Withana, E. Auch

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The purpose of this study was to investigate perceptions of climate change risk to forest ecosystems and forest-based communities as well as perceived effectiveness of adaptation strategies for climate change as well as challenges for adaptation. Data was gathered using a pre-tested semi-structured questionnaire. Simple random selection technique was applied. For the majority of issues, the responses were obtained on multi-point Likert scales, and the scores provided were, in turn, used to estimate the means and other useful estimates. A composite knowledge index developed using correct responses to a set of self-rated statements were used to evaluate the issues. The mean of the knowledge index was 0.64. Also all respondents recorded values of the knowledge index above 0.25. Increase forest fire was perceived by respondents as the greatest risk to forest eco-system. Decrease access to water supplies was perceived as the greatest risk to livelihoods of forest based communities. The most effective adaptation strategy relevant to climate change risks to forest eco-systems and forest based communities livelihoods in Kathmandu valley in Nepal as perceived by the respondents was reforestation and afforestation. As well, lack of public awareness was perceived as the major limitation for climate change adaptation. However, perceived risks as well as effective adaptation strategies showed an inconsistent association with knowledge indicators and social-cultural variables. The results provide useful information to any party who involve with climate change issues in Nepal, since such attempts would be more effective once the people’s perceptions on these aspects are taken into account.

Keywords: climate change, risk perceptions, forest ecosystems, forest-based communities

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Authors: Muhardiyan Erawan, Zaenal Mutaqin

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Balingara River is one of the rivers with the type Gravel-Bed in Indonesia. Gravel-Bed Rivers easily deformed in a relatively short time due to several variables, that are climate (rainfall), river discharge, topography, rock types, and land cover. To determine stream channel changes in Balingara River used Landsat 7 and 8 and analyzed planimetric or two dimensions. Parameters to determine changes in the stream channel are sinuosity ratio, Brice Index, the extent of erosion and deposition. Changes in stream channel associated with changes in land cover then analyze with a descriptive analysis of spatial and temporal. The location of a stream channel has a low gradient in the upstream, and middle watershed with the type of rock in the form of gravel is more easily changed than other locations. Changes in the area of erosion and deposition influence the land cover changes.

Keywords: Brice Index, erosion, deposition, gravel-bed, land cover change, sinuosity ratio, stream channel change

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Authors: Lucia Billeci, Gennaro Tartarisco, Maurizio Varanini

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Fetal cardiac monitoring by fetal electrocardiogram (fECG) can provide significant clinical information about the healthy condition of the fetus. Despite this potentiality till now the use of fECG in clinical practice has been quite limited due to the difficulties in its measuring. The recovery of fECG from the signals acquired non-invasively by using electrodes placed on the maternal abdomen is a challenging task because abdominal signals are a mixture of several components and the fetal one is very weak. This paper presents an approach for fECG extraction from abdominal maternal recordings, which exploits the characteristics of pseudo-periodicity of fetal ECG. It consists of devising a quality index (fQI) for fECG and of finding the linear combinations of preprocessed abdominal signals, which maximize these fQI (quality index optimization - QIO). It aims at improving the performances of the most commonly adopted methods for fECG extraction, usually based on maternal ECG (mECG) estimating and canceling. The procedure for the fECG extraction and fetal QRS (fQRS) detection is completely unsupervised and based on the following steps: signal pre-processing; maternal ECG (mECG) extraction and maternal QRS detection; mECG component approximation and canceling by weighted principal component analysis; fECG extraction by fQI maximization and fetal QRS detection. The proposed method was compared with our previously developed procedure, which obtained the highest at the Physionet/Computing in Cardiology Challenge 2013. That procedure was based on removing the mECG from abdominal signals estimated by a principal component analysis (PCA) and applying the Independent component Analysis (ICA) on the residual signals. Both methods were developed and tuned using 69, 1 min long, abdominal measurements with fetal QRS annotation of the dataset A provided by PhysioNet/Computing in Cardiology Challenge 2013. The QIO-based and the ICA-based methods were compared in analyzing two databases of abdominal maternal ECG available on the Physionet site. The first is the Abdominal and Direct Fetal Electrocardiogram Database (ADdb) which contains the fetal QRS annotations thus allowing a quantitative performance comparison, the second is the Non-Invasive Fetal Electrocardiogram Database (NIdb), which does not contain the fetal QRS annotations so that the comparison between the two methods can be only qualitative. In particular, the comparison on NIdb was performed defining an index of quality for the fetal RR series. On the annotated database ADdb the QIO method, provided the performance indexes Sens=0.9988, PPA=0.9991, F1=0.9989 overcoming the ICA-based one, which provided Sens=0.9966, PPA=0.9972, F1=0.9969. The comparison on NIdb was performed defining an index of quality for the fetal RR series. The index of quality resulted higher for the QIO-based method compared to the ICA-based one in 35 records out 55 cases of the NIdb. The QIO-based method gave very high performances with both the databases. The results of this study foresees the application of the algorithm in a fully unsupervised way for the implementation in wearable devices for self-monitoring of fetal health.

Keywords: fetal electrocardiography, fetal QRS detection, independent component analysis (ICA), optimization, wearable

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Authors: Majid Javanmard

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In this study, the effects of coating with whey protein concentrate (7.5% w/v) alone and/or in combination with rice bran oil (0.2, 0.4, 0.6 g in 100 ml coating solution) and Zataria multiflora extract (1 and 2 μL in 100 ml coating solution) on the quality attributes and egg shelf life were carefully observed and analyzed. Weight loss, Haugh index, yolk index, pH, air cell depth, shell strength and the impact of this coating on the microbial load of the eggs surface were studied at the end of each week (during the 4 weeks of storage in a room environment temperature and humidity). After 4 weeks of storage, it was observed that the weight loss in all of the treated eggs with whey protein concentrate and 0.2 gr of rice bran oil (experimental group) was significantly lower than that of the control group(P < 0/05). With regard to Haugh index and yolk index, egg shelf life increased about 4 weeks compared with the control samples. Haugh Index changes revealed that the coated samples remained at grade A after 3 weeks of storage, while the control samples were relegated from grade AA to B after one week. Haugh and yolk Indices in all coated eggs were more than those of the control group. In the coated groups, Haugh and yolk indices of the coated samples with whey protein concentrate and 0.2 g rice bran oil and with whey protein concentrate and 0.2g of rice bran oil and 1 micro liter of Zataria multiflora extract were more than those of the other coated eggs and the control group eggs. PH values of the control group were higher than those of the coated groups during the storage of the eggs. The shell strength of the coated group was more than that of the control group (uncoated) and in coated samples, whey protein concentrate and 0.2 gr of rice bran oil coated samples had high shell strength. In the other treatments, no significant differences were observed. The depth of the air cell of the coated groups was determined to be less than that of the control group during the storage period. The minimum inhibitory concentration was 1 μL of Zataria multiflora extract. The results showed that 1 μL concentration of Zataria multiflora extract reduces the microbial load of the egg shell surface to 87% and 2 μL reduced total bacterial load to zero. In sensory evaluation, from evaluator point of view, the coated eggs had more overall acceptance than the uncoated group (control), and in the treatment group coated eggs, those containing a low percentage of rice bran oil had higher overall acceptability. In conclusion, coating as a practical and cost effective method can maintain the quality parameters of eggs and lead to durability of supply conditions in addition to the product marketability.

Keywords: edible coating, chicken egg, whey protein concentrate, rice bran oil, Zataria multiflora extract, shelf life

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Authors: Kara Gianina D. Rosas, Jade Emily L. Tong

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This study assesses the vulnerability of households to food price shocks. Using the Philippines as a case study, the researchers aim to understand how such shocks can cause food insecurity in different types of households. This paper measures the impact of actual food price changes during the food crisis of 2006-2009 on poverty in relation to their spatial location. Households are classified as rural or urban and agricultural or non-agricultural. By treating food prices and consumption patterns as heterogeneous, this study differs from conventional poverty analysis as actual prices are used. Merging the Family, Income and Expenditure Survey (FIES) with the Consumer Price Index dataset (CPI), the researchers were able to determine the effects on poverty measures, specifically, headcount index, poverty gap, and poverty severity. The study finds that, without other interventions, food inflation would lead to a significant increase in the number of households that fall below the poverty threshold, except for households whose income is derived from agricultural activities. It also finds that much of the inflation during these years was fueled by the rise in staple food prices. Essentially, this paper aims to broaden the economic perspective of policymakers with regard to the heterogeneity of impacts of inflation through analyzing the deeper microeconomic levels of different subgroups. In hopes of finding a solution to lessen the inequality gap of poverty between the rural and urban poor, this paper aims to aid policymakers in creating projects targeted towards food insecurity.

Keywords: poverty, food inflation, agricultural households, non-agricultural households, net consumption ratio, urban poor, rural poor, head count index, poverty gap, poverty severity

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Authors: Aschalew C. Workneh, K. S. Hari Prasad, C. S. P. Ojha

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The crop water stress index (CWSI) is a cost-effective, non-destructive, and simple technique for tracking the start of crop water stress. This study investigated the feasibility of CWSI derived from canopy temperature to detect the water status of wheat crops. Artificial intelligence (AI) techniques have become increasingly popular in recent years for determining CWSI. In this study, the performance of two AI techniques, adaptive neuro-fuzzy inference system (ANFIS) and self-organizing maps (SOM), are compared while determining the CWSI of paddy crops. Field experiments were conducted for varying irrigation water applications during two seasons in 2022 and 2023 at the irrigation field laboratory at the Civil Engineering Department, Indian Institute of Technology Roorkee, India. The ANFIS and SOM-simulated CWSI values were compared with the experimentally calculated CWSI (EP-CWSI). Multiple regression analysis was used to determine the upper and lower CWSI baselines. The upper CWSI baseline was found to be a function of crop height and wind speed, while the lower CWSI baseline was a function of crop height, air vapor pressure deficit, and wind speed. The performance of ANFIS and SOM were compared based on mean absolute error (MAE), mean bias error (MBE), root mean squared error (RMSE), index of agreement (d), Nash-Sutcliffe efficiency (NSE), and coefficient of correlation (R²). Both models successfully estimated the CWSI of the paddy crop with higher correlation coefficients and lower statistical errors. However, the ANFIS (R²=0.81, NSE=0.73, d=0.94, RMSE=0.04, MAE= 0.00-1.76 and MBE=-2.13-1.32) outperformed the SOM model (R²=0.77, NSE=0.68, d=0.90, RMSE=0.05, MAE= 0.00-2.13 and MBE=-2.29-1.45). Overall, the results suggest that ANFIS is a reliable tool for accurately determining CWSI in wheat crops compared to SOM.

Keywords: adaptive neuro-fuzzy inference system, canopy temperature, crop water stress index, self-organizing map, wheat

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Authors: Masoud Mahdavi, Mojtaba Farzaneh Moghadam

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The seismic forces caused by the waves created in the depths of the earth during the earthquake hit the structure and cause the building to vibrate. Creating large seismic forces will cause low-strength sections in the structure to suffer extensive surface damage. The use of new steel shear walls in steel structures has caused the strength of the building and its main members (columns) to increase due to the reduction and depreciation of seismic forces during earthquakes. In the present study, an attempt was made to evaluate a type of steel shear wall that has regular holes in the inner sheet by modeling the finite element model with Abacus software. The shear wall of the steel plate, measuring 6000 × 3000 mm (one floor) and 3 mm thickness, was modeled with four different pores with a cross-sectional area. The shear wall was dynamically subjected to a time history of 5 seconds by three accelerators, El Centro, Imperial Valley and Kobe. The results showed that increasing the distance between the geometric center of the hole and the geometric center of the inner plate in the steel shear wall (increasing the R_CS index) caused the total maximum acceleration to be transferred from the perimeter of the hole to horizontal and vertical beams. The results also show that there is no direct relationship between R_CS index and total acceleration in steel shear wall and R_CS index is separate from the peak ground acceleration value of earthquake.

Keywords: hollow steel plate shear wall, time history analysis, finite element method, abaqus software

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Authors: Cha’o-Kuang Chen, Ching-Chang Cho

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This paper investigates the natural convection heat transfer performance in a complex-wavy-wall cavity filled with power-law fluid. In performing the simulations, the continuity, Cauchy momentum and energy equations are solved subject to the Boussinesq approximation using a finite volume method. The simulations focus specifically on the effects of the flow behavior index in the power-law model and the Rayleigh number on the flow streamlines, isothermal contours and mean Nusselt number within the cavity. The results show that pseudoplastic fluids have a better heat transfer performance than Newtonian or dilatant fluids. Moreover, it is shown that for Rayleigh numbers greater than Ra=103, the mean Nusselt number has a significantly increase as the flow behavior index is decreased.

Keywords: non-Newtonian fluid, power-law fluid, natural convection, heat transfer enhancement, cavity, wavy wall

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Authors: Salmi-Laouar Sihem, Aouissi Riadh

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The Cenomanian formations of the Bellezma-Batna Range are yielding very diversified fossiliferous beds. Among the abundant and well-preserved fossils stands out Aspidiscus cristatus (Lamarck). This taxon is assigned to the Family Latomeandridae (Alloiteau) for the presence of six symmetry axes. The outer morphology of sampled specimens documents a low-energy environment with a high sedimentary rate and a mud-supported bottom. Its provincialism evidences some characteristic thermal gradients of the marked Tethysian climatic areas. Biometric measurements are given. Coral size increases from the North towards the southeastern Tethysian margin where waters are supposed warmer; this feature is also underlined by a frequent bio-erosion of sampled specimens. Its limited stratigraphic range makes it a good candidate for an index species for the Middle Cenomanian.

Keywords: Aspidiscus cristatus, coral, Middle Cenomanian, Batna, Bellezma, Algeria

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Authors: Intissar Farid

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Groundwater quality assessment is crucial for sustainable water use, especially in semi-arid regions like the Jeloula basin in Tunisia, where groundwater is essential for domestic and agricultural needs. The present research aims to characterize the suitability of groundwater for irrigational purposes by considering various parameters: total salt concentration as measured by Electrical Conductivity EC, relative proportions of Na⁺ as expressed by %Na and SAR, Kelly’s ratio, Permeability Index, Magnesium hazard and Residual Sodium chloride. Chemical data indicate that the percent sodium (%Na) in the study area ranged from 26.3 to 45.3%. According to the Wilcox diagram, the quality classification of irrigation water suggests that analyzed groundwaters are suitable for irrigation purposes. The SAR values vary between 2.1 and 5. Most of the groundwater samples plot in the Richards’C3S1 water class and indicate little danger from sodium content to soil and plant growth. The Kelly’s ratio of the analyzed samples ranged from 0.3 to 0.8. These values indicate that the waters are fit for agricultural purposes. Magnesium hazard (MH) values range from 27.5 to 52.6, with an average of 38.9 in the analyzed waters. Hence, the Mg²⁺ content of the groundwater from the shallow aquifer cannot cause any problem to the soil permeability. Permeability index (PI) values computed for the area ranged from 33.6 to 52.7%. The above result, therefore, suggests that most of the water samples fall within class I of the Doneen chart and can be categorized as good irrigation water. The groundwaters collected from the Jeloula shallow aquifer were found to be within the safe limits and thus suitable for irrigation purposes.

Keywords: Kelly's ratio, magnesium hazard, permeability index, residual sodium chloride

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Authors: Pius Babuna, Xiaohua Yang, Roberto Xavier Supe Tulcan, Bian Dehui, Mohammed Takase, Bismarck Yelfogle Guba, Chuanliang Han, Doris Abra Awudi, Meishui Lia

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Water inequality, water security, and water governance are fundamental parameters that affect the sustainable use of water resources. Through policy formulation and decision-making, water governance determines both water security and water inequality. Largely, where water inequality exists, water security is undermined through unsustainable water use practices that lead to pollution of water resources, conflicts, hoarding of water, and poor sanitation. Incidentally, the interconnectedness of water governance, water inequality, and water security has not been investigated previously. This study modified the Gini coefficient and used a Logistics Growth of Water Resources (LGWR) Model to access water inequality and water security mathematically, and discussed the connected role of water governance. We tested the validity of both models by calculating the actual water inequality and water security of Ghana. We also discussed the implications of water inequality on water security and the overarching role of water governance. The results show that regional water inequality is widespread in some parts. The Volta region showed the highest water inequality (Gini index of 0.58), while the central region showed the lowest (Gini index of 0.15). Water security is moderately sustainable. The use of water resources is currently stress-free. It was estimated to maintain such status until 2132 ± 18, when Ghana will consume half of the current total water resources of 53.2 billion cubic meters. Effectively, water inequality is a threat to water security, results in poverty, under-development heightens tensions in water use, and causes instability. With proper water governance, water inequality can be eliminated through formulating and implementing approaches that engender equal allocation and sustainable use of water resources.

Keywords: water inequality, water security, water governance, Gini coefficient, moran index, water resources management

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Authors: Mohammad Y. Alfaifi

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Anything that poses a challenge or a threat to our well-being is a stress. Understanding the genetic material and cellular response of rats threatened with Repeated swimming stress provides insights that can influence human health. The aim of the present study was to assess the genetical damage and cytological changes caused by exposure of the test organism (Rattus rattus) to forced swimming stress. For this purpose, animals have been submerged in water path 15 minutes daily for 2 weeks. Following that, we performed a micronuclei (MN) test using MNNCE (Micronucleated normocromatic erythrocytes) and MNPCE (Micronucleated polychromatic erythrocytes), NDI (Nuclear division index) and cytological parameters using NDCI (nuclear division cytotoxicity index), necrotic and apoptotic cells in rat's bone marrow samples. Results showed that there was a slightly but not significant increase in the frequency of micronucleated as well as in cytological parameters in bone marrow cells.

Keywords: submergence stress, micronucleus, NDI, NDCI, toxicity, chromosomal aberrations

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Authors: Khalid Mujaljal, Hassan Alhajhoj

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This paper empirically investigates the influence of oil price fluctuations on the key macroeconomic variables of the Kingdom of Saudi Arabia using unrestricted VAR methodology. Two analytical tools- Granger-causality and variance decomposition are used. The Granger-causality test reveals that almost all specifications of oil price shocks significantly Granger-cause GDP and demonstrates evidence of causality between oil price changes and money supply (M3) and consumer price index percent (CPIPC) in the case of positive oil price shocks. Surprisingly, almost all specifications of oil price shocks do not Granger-cause government expenditure. The outcomes from variance decomposition analysis suggest that positive oil shocks contribute about 25 percent in causing inflation in the country. Also, contribution of symmetric linear oil price shocks and asymmetric positive oil price shocks is significant and persistent with 25 percent explaining variation in world consumer price index till end of the period.

Keywords: Granger causality, oil prices changes, Saudi Arabian economy, variance decomposition

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Authors: Chakraborty Sudipta, A. R. Kambekar, Sarma Arnab

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Sea-level rise being one of the most important impacts of anthropogenic induced climate change resulting from global warming and melting of icebergs at Arctic and Antarctic, the investigations done by various researchers both on Indian Coast and elsewhere during the last decade has been reviewed in this paper. The paper aims to ascertain the propensity of consistency of different suggested methods to predict the near-accurate future sea level rise along the coast of Mumbai. Case studies at East Coast, Southern Tip and West and South West coast of India have been reviewed. Coastal Vulnerability Index of several important international places has been compared, which matched with Intergovernmental Panel on Climate Change forecasts. The application of Geographic Information System mapping, use of remote sensing technology, both Multi Spectral Scanner and Thematic Mapping data from Landsat classified through Iterative Self-Organizing Data Analysis Technique for arriving at high, moderate and low Coastal Vulnerability Index at various important coastal cities have been observed. Instead of data driven, hindcast based forecast for Significant Wave Height, additional impact of sea level rise has been suggested. Efficacy and limitations of numerical methods vis-à-vis Artificial Neural Network has been assessed, importance of Root Mean Square error on numerical results is mentioned. Comparing between various computerized methods on forecast results obtained from MIKE 21 has been opined to be more reliable than Delft 3D model.

Keywords: climate change, Coastal Vulnerability Index, global warming, sea level rise

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Authors: Chuanqiao Zheng, Wei Zeng, Haozhen Lin

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As of March 2020, the number of Chinese netizens has reached 904 million. The proportion of Internet users accessing the Internet through mobile phones is as high as 99.3%. Under the background of 'Internet +', tourists have a stronger sense of independence in the choice of tourism destinations and tourism products. Tourists are more inclined to learn about the relevant information on tourism destinations and other tourists' evaluations of tourist products through the Internet. The search engine, as an integrated platform that contains a wealth of information, is highly valuable to the analysis of the characteristics of the Internet attention given to various tourism destinations, through big data mining and analysis. This article uses the Baidu Index as the data source, which is one of the products of Baidu Search. The Baidu Index is based on big data, which collects and shares the search results of a large number of Internet users on the Baidu search engine. The big data used in this article includes search index, demand map, population profile, etc. The main research methods used are: (1) based on the search index, analyzing the Internet attention given to the tourism in five cities in Northeast Sichuan at different times, so as to obtain the overall trend and individual characteristics of tourism development in the region; (2) based on the demand map and the population profile, analyzing the demographic characteristics and market positioning of the tourist groups in these cities to understand the characteristics and needs of the target groups; (3) correlating the Internet attention data with the permanent population of each province in China in the corresponding to construct the Boston matrix of the Internet attention rate of the Northeast Sichuan tourism, obtain the tourism target markets, and then propose development strategies for different markets. The study has found that: a) the Internet attention given to the tourism in the region can be categorized into tourist off-season and peak season; the Internet attention given to tourism in different cities is quite different. b) tourists look for information including tour guide information, ticket information, traffic information, weather information, and information on the competing tourism cities; with regard to the population profile, the main group of potential tourists searching for the keywords of tourism in the five prefecture-level cities in Northeast Sichuan are youth. The male to female ratio is about 6 to 4, with males being predominant. c) through the construction of the Boston matrix, it is concluded that the star market for tourism in the Northeast Sichuan Economic Zone includes Sichuan and Shaanxi; the cash cows market includes Hainan and Ningxia; the question market includes Jiangsu and Shanghai; the dog market includes Hubei and Jiangxi. The study concludes with the following planning strategies and recommendations: i) creating a diversified business format that integrates cultural and tourism; ii) creating a brand image of niche tourism; iii) focusing on the development of tourism products; iv) innovating composite three-dimensional marketing channels.

Keywords: Baidu Index, big data, internet attention, tourism

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Authors: Nour El Houda Arabi, Aicha Iratni, Talaighil Razika, Bruno Capoen, Mohamed Bouazaoui

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In this paper, we report the effect of the calcination temperature and SiO2 addition on structural, optical and hydrophilicity of TiO2 films deposited by deep-coating sol-gel process. XRD investigation of the structural TiO2 films with increasing the temperature calcination, reveals that rutile phase will appear for the high temperature (>1000°C). However, the addition of SiO2 relate the densification of TiO2 films. Ellipsometric and UV-visible measure show that the refractive index grow with increasing temperature, against the film thickness decreases. On the other hand, the addition of SiO2 decreases the refractive index and increases the TiO2 film thickness. Finally, the hydrophilicity is assisted by contact angle measurement. It is found that addition of 50% of SiO2 to TiO2 is most effective for reducing the contact angle of water.

Keywords: physical properties, sol, gel, TiO2/SiO2 composite films

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Authors: Arafan Traore, Teiji Watanabe

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Conakry, the capital city of the Republic of Guinea, has experienced a rapid urban expansion and population increased in the last two decades, which has resulted in remarkable local weather and climate change, raise energy demand and pollution and treating social, economic and environmental development. In this study, the spatiotemporal variation of the land surface temperature (LST) is retrieved to characterize the effect of urban growth on the thermal environment and quantify its relationship with biophysical indices, a normalized difference vegetation index (NDVI) and a normalized difference built up Index (NDBI). Landsat data TM and OLI/TIRS acquired respectively in 1986, 2000 and 2016 were used for LST retrieval and Land use/cover change analysis. A quantitative analysis based on the integration of a remote sensing and a geography information system (GIS) has revealed an important increased in the LST pattern in the average from 25.21°C in 1986 to 27.06°C in 2000 and 29.34°C in 2016, which was quite eminent with an average gain in surface temperature of 4.13°C over 30 years study period. Additionally, an analysis using a Pearson correlation (r) between (LST) and the biophysical indices, normalized difference vegetation index (NDVI) and a normalized difference built-up Index (NDBI) has revealed a negative relationship between LST and NDVI and a strong positive relationship between LST and NDBI. Which implies that an increase in the NDVI value can reduce the LST intensity; conversely increase in NDBI value may strengthen LST intensity in the study area. Although Landsat data were found efficient in assessing the thermal environment in Conakry, however, the method needs to be refined with in situ measurements of LST in the future studies. The results of this study may assist urban planners, scientists and policies makers concerned about climate variability to make decisions that will enhance sustainable environmental practices in Conakry.

Keywords: Conakry, land surface temperature, urban heat island, geography information system, remote sensing, land use/cover change

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Authors: Sachin Singh, Thomas Penzel, Dinesh Nandan

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Accurate identification of Sleep Apnea Hypopnea Syndrom Diagnosis is difficult problem for human expert because of variability among persons and unwanted noise. This paper proposes the diagonosis of Sleep Apnea Hypopnea Syndrome (SAHS) using airflow, ECG, Pulse and SaO2 signals. The features of each type of these signals are extracted using statistical methods and ANN learning methods. These extracted features are used to approximate the patient's Apnea Hypopnea Index(AHI) using sample signals in model. Advance signal processing is also applied to snore sound signal to locate snore event and SaO2 signal is used to support whether determined snore event is true or noise. Finally, Apnea Hypopnea Index (AHI) event is calculated as per true snore event detected. Experiment results shows that the sensitivity can reach up to 96% and specificity to 96% as AHI greater than equal to 5.

Keywords: neural network, AHI, statistical methods, autoregressive models

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Authors: Zakirul Islam, Yugo Kumokawa, Quoc Thinh Tran, Motoki Kubo

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Clubroot is a disease of cruciferous plant caused by soil born pathogen Plasmodiophora brassicae and can significantly limit the production through rapid spreading. The present study was designed to investigate the effect of cultivation practices (chemical and organic soils) on clubroot disease development in Brassica rapa. Disease index and root bacterial composition were investigated for both chemical and organic soils. The bacterial biomass and diversity in organic soil were higher than those in chemical soil. Disease severity was distinct for two different cultivation methods. The number of endophytic bacteria decreased in the infected root for both soils. The increased number of endophytic bacterial number led to reduce the proliferation of pathogen spore inside the root and thus reduced the disease severity in organic plants.

Keywords: clubroot disease, bacterial biomass, root infection, disease index, chemical cultivation, organic cultivation

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Authors: Yose Rizal, Nuraini, Mirnawati, Maria Endo Mahata, Rio Darman, Dendi Kurniawan

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An experiment had been conducted to determine the effects of several levels of Neurospora crassa- fermented palm kernel cake in the diet on the production performance and egg-yolk quality of Arab laying-hens, and to obtain the appropriate level of this fermented palm kernel cake for reducing the utilization of concentrated feed in the diet. Three hundred Arab laying-hens of 72 weeks old were employed in this experiment, and randomly assigned to four treatments (0, 7.25, 10.15, and 13.05% fermented palm kernel cake in diets) in a completely randomized design with five replicates. Measured variables were production performance (feed consumption, egg-mass production, feed conversion, egg weight and hen-day egg production), and egg-yolk quality (ether extract and cholesterol contents, and egg-yolk color index). Results of experiment indicated that feed consumption, egg-mass production, feed conversion, egg weight, hen-day egg production and egg-yolk color index were not influenced (P>0.05) by diets. However, the ether extract and cholesterol contents of egg-yolk were very significantly reduced (P<0.01) by diets. In conclusion, Neurospora crassa-fermented palm kernel cake could be included up to 13.05% to effectively replace 45% concentrated feed in Arab laying-hens diet without adverse effect on the production performance.

Keywords: neurospora crassa-fermented palm kernel cake, Arab laying-hens, production performance, ether extract, cholesterol, egg-yolk color index

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Authors: Jing Jiang, Yuguang Gao, Yang Yu

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Facing increasingly challenging insurance payment pressures, the Chinese healthcare system is undergoing significant transformations, akin to the implementation of DRG payment models by the United States' Medicare. Consequently, there is a pressing need for Chinese hospitals to establish optimizations in departmental operations tailored to the ongoing healthcare payment reforms. This abstract delineates the meticulous construction of a scientifically rigorous and comprehensive index system at the departmental level in China strategically aligned with the evolving landscape of healthcare payment reforms. Methodologically, it integrates key process areas and maturity assessment theories, synthesizing relevant literature and industry standards to construct a robust framework and indicator pool. Employing the Delphi method, consultations with 21 experts were conducted, revealing a collective demonstration of high enthusiasm, authority, and coordination in designing the index system. The resulting model comprises four primary indicators -technical capabilities, cost-effectiveness, operational efficiency, and disciplinary potential- supported by 14 secondary indicators and 23 tertiary indicators with varied coefficient adjustment for department types (platform or surgical). The application of this evaluation system in a Chinese hospital within the northeastern region yielded results aligning seamlessly with the actual operational scenario. In conclusion, the index system comprehensively considers the integrity and effectiveness of structural, process, and outcome indicators and stands as a comprehensive reflection of the collective expertise of the engaged experts, manifesting in a model designed to elevate the operational management of hospital departments. Its strategic alignment with healthcare payment reforms holds practical significance in guiding departmental development positioning, brand cultivation, and talent development.

Keywords: Chinese healthcare system, Delphi method, departmental management, evaluation indicators, hospital operations, weight coefficients

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Authors: Sukhwinder Singh, Julian Park, Dinesh Kumar Benbi

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Although soil health, which is recognized as one of the key determinants of sustainable agricultural development, can be measured by a range of physical, chemical and biological parameters, the widely used parameters include pH, electrical conductivity (EC), organic carbon (OC), plant available phosphorus (P) and potassium (K). Soil health is largely affected by the occurrence of natural events or human activities and can be improved by various land management practices. A database of 120 soil samples collected from farmers’ fields spread across three major agro-climatic zones of Punjab suggested that the average pH, EC, OC, P and K was 8.2 (SD = 0.75, Min = 5.5, Max = 9.1), 0.27 dS/m (SD = 0.17, Min = 0.072 dS/m, Max = 1.22 dS/m), 0.49% (SD = 0.20, Min = 0.06%, Max = 1.2%), 19 mg/kg soil (SD = 22.07, Min = 3 mg/kg soil, Max = 207 mg/kg soil) and 171 mg/kg soil (SD = 47.57, Min = 54 mg/kg soil, Max = 288 mg/kg soil), respectively. Region-wise, pH, EC and K were the highest in south-western district of Ferozpur whereas farmers in north-eastern district of Gurdaspur had the best soils in terms of OC and P. The soils in the central district of Barnala had lower OC, P and K than the respective overall averages while its soils were normal but skewed towards alkalinity. Besides agro-climatic conditions, the size of landholding and farmer education showed a significant association with Soil Fertility Index (SFI), a composite index calculated using the aforementioned parameters’ normalized weightage. All the four stakeholder groups cited the current cropping patterns, burning of rice crop residue, and imbalanced use of chemical fertilizers for change in soil health. However, the current state of soil health in Punjab is unclear, which needs further investigation based on temporal data collected from the same field to see the short and long-term impacts of various crop combinations and varied cropping intensity levels on soil health.

Keywords: soil health, punjab agriculture, sustainability, soil fertility index

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Authors: M. Sirhan, S. Bekhor, A. Sidess

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In-service pavements deteriorate with time due to traffic wheel loads, environment, and climate conditions. Pavement deterioration leads to a reduction in their serviceability and structural behavior. Consequently, proper maintenance and rehabilitation (M&R) are necessary actions to keep the in-service pavement network at the desired level of serviceability. Due to resource and financial constraints, the pavement management system (PMS) prioritizes roads most in need of maintenance and rehabilitation action. It recommends a suitable action for each pavement based on the performance and surface condition of each road in the network. The pavement performance and condition are usually quantified and evaluated by different types of roughness-based and stress-based indices. Examples of such indices are Pavement Serviceability Index (PSI), Pavement Serviceability Ratio (PSR), Mean Panel Rating (MPR), Pavement Condition Rating (PCR), Ride Number (RN), Profile Index (PI), International Roughness Index (IRI), and Pavement Condition Index (PCI). PCI is commonly used in PMS as an indicator of the extent of the distresses on the pavement surface. PCI values range between 0 and 100; where 0 and 100 represent a highly deteriorated pavement and a newly constructed pavement, respectively. The PCI value is a function of distress type, severity, and density (measured as a percentage of the total pavement area). PCI is usually calculated iteratively using the 'Paver' program developed by the US Army Corps. The use of soft computing techniques, especially Artificial Neural Network (ANN), has become increasingly popular in the modeling of engineering problems. ANN techniques have successfully modeled the performance of the in-service pavements, due to its efficiency in predicting and solving non-linear relationships and dealing with an uncertain large amount of data. Typical regression models, which require a pre-defined relationship, can be replaced by ANN, which was found to be an appropriate tool for predicting the different pavement performance indices versus different factors as well. Subsequently, the objective of the presented study is to develop and train an ANN model that predicts the PCI values. The model’s input consists of percentage areas of 11 different damage types; alligator cracking, swelling, rutting, block cracking, longitudinal/transverse cracking, edge cracking, shoving, raveling, potholes, patching, and lane drop off, at three severity levels (low, medium, high) for each. The developed model was trained using 536,000 samples and tested on 134,000 samples. The samples were collected and prepared by The National Transport Infrastructure Company. The predicted results yielded satisfactory compliance with field measurements. The proposed model predicted PCI values with relatively low standard deviations, suggesting that it could be incorporated into the PMS for PCI determination. It is worth mentioning that the most influencing variables for PCI prediction are damages related to alligator cracking, swelling, rutting, and potholes.

Keywords: artificial neural networks, computer programming, pavement condition index, pavement management, performance prediction

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Authors: Shah Fahad

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Managing the Urban Heat Island (UHI) effects is a pressing concern for achieving sustainable urban development and ensuring thermal comfort in major cities of developing nations, such as Lahore, Pakistan. The current UHI effect is mostly triggered by climate change and rapid urbanization. This study explored UHI over the Lahore district and its adjoining urban and rural-urban fringe areas. Landsat satellite data was utilized to investigate spatiotemporal patterns of Land Use and Land Cover changes (LULC), Land Surface Temperature (LST), UHI, Normalized Difference Built-up Index (NDBI), Normalized Difference Vegetation Index (NDVI), and Urban Thermal Field Variance Index (UTFVI). The built-up area increased very fast, with a coverage of 22.99% in 2000, 36.06% in 2010, and 47.17% in 2020, while vegetation covered 53.21 % in 2000 and 46.16 % in 2020. It also revealed a significant increase in the mean LST, from 33°C in 2000 to 34.8°C in 2020. The results indicated a significantly positive correlation between LST and NDBI, a weak correlation was also observed between LST and NDVI. The study used scatterplots to show the correlation between NDBI and NDVI with LST, results revealed that the NDBI and LST had an R² value of 0.6831 in 2000 and 0.06541 in 2022, while NDVI and LST had an R² value of 0.0235 in 1998 and 0.0295 in 2022. Proper environmental planning is vital in specific locations to enhance quality of life, protect the ecosystem, and mitigate climate change impacts.

Keywords: land use land cover, spatio-temporal analysis, remote sensing, land surface temperature, urban heat island, lahore pakistan

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Authors: Eheneden Iyobosa, Rongchang Wang, Adesina Odunayo Blessing, Gaoxiang Chen, Haijing Ren, Jianfu Zhao

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In the treatment of ammonium-rich wastewater with 500 μg/L sulfamethoxazole (SMX) antibiotic by a Microalgae-Bacteria Consortium, diverse parameters were monitored to assess treatment efficacy. Over 14 days, residual SMX concentrations decreased markedly from 500 μg/L to 45.6 μg/L, and removal rates declined from 102.4 to 9.9 μg/L/day. Biomass exhibited consistent growth, reaching a peak of 542.6 mg/L on day 10. Chlorophyll-a, chlorophyll-b, and carotenoid levels varied over time, reflecting fluctuations in microalgal activity. Extracellular polymeric substances (EPS) production showed temporal variations, with protein content ranging from 69.4 to 162.3 mg/g Dry cell weight (DCW) and polysaccharides content from 50.6 to 82.8 mg/g DCW. Ammonium nitrogen concentration decreased steadily from 300 mg/L to 5 mg/L throughout the treatment period. The bacterial community composition was significantly altered in the presence of antibiotics, with notable increases in Bacteroidota and Proteobacteria. Community richness and diversity indices were higher in the antibiotics-treated group than in the control group, as evidenced by the Chao index (258 compared to 181), Shannon index (1.8085 compared to 1.1545), and Simpson index (0.5032 compared to 0.6478), indicating notable shifts in microbial community structure. These findings demonstrate the efficacy of the Microalgae-Bacteria Consortium in removing SMX from wastewater and suggest its potential to mitigate antibiotic pollution while maintaining microbial diversity.

Keywords: ammonium-rich wastewater, microalgae-bacteria consortium, sulfamethoxazole removal, microbial community diversity, biomass growth

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Authors: Maria Miranda-Medina, Sara Salopek, Andras Vernes, Martin Jech

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Sliding lubricated surfaces induce the formation of tribofilms that reduce friction, wear and prevent large-scale damage of contact parts. Engine oils and lubricants use antiwear and antioxidant additives such as zinc dialkyldithiophosphate (ZDDP) from where protective tribofilms are formed by degradation. The ZDDP tribofilms are described as a two-layer structure composed of inorganic polymer material. On the top surface, the long chain polyphosphate is a zinc phosphate and in the bulk, the short chain polyphosphate is a mixed Fe/Zn phosphate with a gradient concentration. The polyphosphate chains are partially adherent to steel surface through a sulfide and work as anti-wear pads. In this contribution, ZDDP tribofilms formed on gray cast iron surfaces are studied. The tribofilms were generated in a reciprocating sliding tribometer with a piston ring-cylinder liner configuration. Fully formulated oil of SAE grade 5W-30 was used as lubricant during two tests at 40Hz and 50Hz. For the estimation of the tribofilm thicknesses, spectroscopic ellipsometry was used due to its high accuracy and non-destructive nature. Ellipsometry works under an optical principle where the change in polarisation of light reflected by the surface, is associated with the refractive index of the surface material or to the thickness of the layer deposited on top. Ellipsometrical responses derived from tribofilms are modelled by effective medium approximation (EMA), which includes the refractive index of involved materials, homogeneity of the film and thickness. The materials composition was obtained from x-ray photoelectron spectroscopic studies, where the presence of ZDDP, O and C was confirmed. From EMA models it was concluded that tribofilms formed at 40 Hz are thicker and more homogeneous than the ones formed at 50 Hz. In addition, the refractive index of each material is mixed to derive an effective refractive index that describes the optical composition of the tribofilm and exhibits a maximum response in the UV range, being a characteristic of glassy semitransparent films.

Keywords: effective medium approximation, reciprocating sliding tribometer, spectroscopic ellipsometry, zinc dialkyldithiophosphate

Procedia PDF Downloads 251