Search results for: cluster synchronization

Authors: Alfiah Hasanah, Silvia Mendolia, Oleg Yerokhin

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This paper explores the impacts of adult child migration on the health of elderly parents left behind. The maternal and children health are a priority of health-related policy in most low and middle-income country, and so there is lack of evidence on the health of older population particularly in Indonesia. With increasing life expectancy and limited access to social security and social services for the elderly in this country, the consequences of increasing number of out-migration of adult children to parent health are important to investigate. This study use Indonesia Family Life Survey (IFLS), the only large-scale continuing longitudinal socioeconomic and health survey that based on a sample of households representing about 83 percent of the Indonesian population in its first wave. Using four waves of IFLS including the recent wave of 2014, several indicators of the self-rated health status, interviewer-rated health status and days of illness are used to estimate the impact of labour out-migration of adult children on parent health status. Incorporate both individual fixed effects to control for unobservable factors in migrant and non-migrant households and the ordered response of self-rated health, this study apply the ordered logit of “Blow-up and Cluster” (BUC ) estimator. The result shows that labour out-migration of adult children significantly improves the self-rated health status of the elderly parent left behind. Findings of this study are consistent with the view that migration increases family resources and contribute to better health care and nutrition of the family left behind.

Keywords: aging, migration, panel data, self-rated health

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Authors: Saravanan Govindaraju, Kyusik Yun

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The purpose of this study is to develop the chitosan doped curcumin gold cluster nanofiber for wound healing and skin cancer drug delivery applications. Chitosan is a typical marine polysaccharide composed of glucosamine and n-acetyl glucosamine biodegradable and biocompatible polymer. Curcumin is a natural bioactive molecule obtained from Curcuma longo, it mostly occurs in some Asian countries like India and China. It has naturally antioxidant, antimicrobial, wound healing and anticancer property. Due to this advantage, we prepared a combination of natural polymer chitosan with Curcumin and gold nanocluster nanofiber (CH-CUR-AuNCs nanofibers). The prepared nanofiber was characterized by using Fourier transform infrared spectroscopy (FT-IR), and scanning electron microscopy (SEM). Antibacterial studies were performed with E.coli and S.aureus. Antioxidant assay, drug release test, and cytotoxicity will be evaluated. Prepared nanofiber emits low intensity of red fluorescent. The FTIR confirm the presence of chitosan and Curcumin in the nanofiber. In vitro study clearly shows the antibacterial activity against the gram negative and gram positive bacteria. Particularly, synthesised nanofibers provide better antibacterial activity against gram negative than gram positive. Cytotoxicity study also provides better killing rate in cancer cell, biocompatible with normal cell. Prepared CH-CUR-AuNCs nanofibers provide the better killing rate to bacterial strains and cancer cells. Finally, prepared nanofiber can be possible to use for wound healing dressing, patch for skin cancer and other biomedical applications.

Keywords: curcumin, chitosan, gold clusters, nanofibers

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Authors: Bhat Geetalaxmi Jairam, D. V. Ashoka

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Wireless Sensor Networks are used in many applications to collect sensed data from different sources. Sensed data has to be delivered through sensors wireless interface using multi-hop communication towards the sink. The data collection in wireless sensor networks consumes energy. Energy consumption is the major constraints in WSN .Reducing the energy consumption while increasing the amount of generated data is a great challenge. In this paper, we have implemented two data gathering protocols with multiple mobile sinks/elements to collect data from sensor nodes. First, is Energy-Efficient Data Gathering with Tour Length-Constrained Mobile Elements in Wireless Sensor Networks (EEDG), in which mobile sinks uses vehicle routing protocol to collect data. Second is An Intelligent Agent-based Routing Structure for Mobile Sinks in WSNs (IAR), in which mobile sinks uses prim’s algorithm to collect data. Authors have implemented concepts which are common to both protocols like deployment of mobile sinks, generating visiting schedule, collecting data from the cluster member. Authors have compared the performance of both protocols by taking statistics based on performance parameters like Delay, Packet Drop, Packet Delivery Ratio, Energy Available, Control Overhead. Authors have concluded this paper by proving EEDG is more efficient than IAR protocol but with few limitations which include unaddressed issues likes Redundancy removal, Idle listening, Mobile Sink’s pause/wait state at the node. In future work, we plan to concentrate more on these limitations to avail a new energy efficient protocol which will help in improving the life time of the WSN.

Keywords: aggregation, consumption, data gathering, efficiency

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Authors: Liu Yi Hui

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The COVID-19 pandemic in 2020 has globally affected all aspects of life, with social distancing and quarantine orders causing turmoil and learning in community colleges being temporarily paused. In fact, this is the first time that adult education has faced such a severe challenge. It forces researchers to reflect on the impact of pandemics on adult education and ways to respond. Distance learning appears to be one of the pedagogical tools capable of dealing with interpersonal isolation and social distancing caused by the pandemic. This research aims to examine whether the impact of social distancing during COVID-19 will lead to increased acceptance of technology and, subsequently, an increase in adults ’ willingness to participate in distance learning. The hypothesis that social distancing and the desire to participate in distance learning affects learners’ tendency to accept technology is investigated. Teachers ’ participation in distance education and acceptance of technology are used as adjustment variables with the relationship to “social distancing,” “participation in distance learning,” and “acceptance of technology” of learners. A questionnaire survey was conducted over a period of twelve months for teachers and learners at all community colleges in Taiwan who enrolled in a basic unit course. Community colleges were separated using multi-stage cluster sampling, with their locations being metropolitan, non-urban, south, and east as criteria. Using the G*power software, 660 samples were selected and analyzed. The results show that through appropriate pedagogical strategies or teachers ’ own acceptance of technology, adult learners’ willingness to participate in distance learning could be influenced. A diverse model of participation can be developed, improving adult education institutions’ ability to plan curricula to be flexible to avoid the risk associated with epidemic diseases.

Keywords: social distancing, adult learning, community colleges, technology acceptance model

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Authors: Donghwan Lee, Gichun Cha, Jooyoung Park, Junkyeong Kim, Seunghee Park

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3D shape models of the existing structure are required for many purposes such as safety and operation management. The traditional 3D modeling methods are based on manual or semi-automatic reconstruction from close-range images. It occasions great expense and time consuming. The Terrestrial Laser Scanner (TLS) is a common survey technique to measure quickly and accurately a 3D shape model. This TLS is used to a construction site and cultural heritage management. However there are many limits to process a TLS point cloud, because the raw point cloud is massive volume data. So the capability of carrying out useful analyses is also limited with unstructured 3-D point. Thus, segmentation becomes an essential step whenever grouping of points with common attributes is required. In this paper, members segmentation algorithm was presented to separate a raw point cloud which includes only 3D coordinates. This paper presents a clustering approach based on a fuzzy method for this objective. The Fuzzy C-Means (FCM) is reviewed and used in combination with a similarity-driven cluster merging method. It is applied to the point cloud acquired with Lecia Scan Station C10/C5 at the test bed. The test-bed was a bridge which connects between 1st and 2nd engineering building in Sungkyunkwan University in Korea. It is about 32m long and 2m wide. This bridge was used as pedestrian between two buildings. The 3D point cloud of the test-bed was constructed by a measurement of the TLS. This data was divided by segmentation algorithm for each member. Experimental analyses of the results from the proposed unsupervised segmentation process are shown to be promising. It can be processed to manage configuration each member, because of the segmentation process of point cloud.

Keywords: fuzzy c-means (FCM), point cloud, segmentation, terrestrial laser scanner (TLS)

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Authors: Mehwish Azam, Muhammad Imran, Humaira Jabeen, Sumreen Begum, Rashida Qasim

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Background: Metabolic syndrome is a cluster of metabolic risk factors including obesity, glucose intolerance, insulin resistance, dyslipidemia and hypertension. Metabolic syndrome in obese and type 2 diabetic subjects increases the risk of cardiovascular diseases (CVD). Globally, the prevalence of metabolic syndrome ranges from 10%-50% and in Pakistan ranges from 18%-46%. The objective of the present study is to estimate the prevalence of metabolic syndrome (MS) in obese type 2 diabetic subjects by using International Diabetes Federation (IDF) and National Cholesterol Education Program-Adult Treatment Panel III (NCEP-ATP III) definitions. Methods: Obese type 2 diabetic subjects and normal healthy subjects of both genders were selected from diabetic clinics and hospitals of various localities of Karachi, Pakistan. The frequency of metabolic syndrome was estimated by the proposed definitions of IDF and NCEP-ATP III. Results: The prevalence of metabolic syndrome using International Diabetes Federation (IDF) definition in obese type 2 diabetic subjects was 85.7%. It is significantly higher (p<0.05) in females (47.1%) as compared to males (38.6%). While, using National Cholesterol Education Program-Adult Treatment Panel III (NCEP-ATP III) definition the overall prevalence of metabolic syndrome in obese type 2 diabetic subjects was 75.7%, the prevalence is significantly higher (p<0.05) in females (45.7%) than males (30.0%). Conclusion: It is concluded that, the overall prevalence of metabolic syndrome is increasing significantly in obese type 2 diabetic subjects by using IDF and NCEP–ATP III definitions. Therefore, it is need to initiate the preventive measures by arranging public awareness programmes to highlight the significance of a healthy lifestyle and emphasis should be given to reduce weight, increase physical activity, and increase intake of healthy low-glycemic-index foods.

Keywords: metabolic syndrome, diabetes mellitus, obesity, IDF, NCEP-ATP III

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Authors: Devansh Desai, Rahul Nigam

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Crop water stress (W) at a given growth stage starts to set in as moisture availability (M) to roots falls below 75% of maximum. It has been found that ratio of crop evapotranspiration (ET) and reference evapotranspiration (ET0) is an indicator of moisture adequacy and is strongly correlated with ‘M’ and ‘W’. The spatial variability of ET0 is generally less over an agricultural farm of 1-5 ha than ET, which depends on both surface and atmospheric conditions, while the former depends only on atmospheric conditions. Solutions from surface energy balance (SEB) and thermal infrared (TIR) remote sensing are now known to estimate latent heat flux of ET. In the present study, ET and moisture adequacy index (MAI) (=ET/ET0) have been estimated over two contrasting western India agricultural farms having rice-wheat system in semi-arid climate and arid grassland system, limited by moisture availability. High-resolution multi-band TIR sensing observations at 65m from ECOSTRESS (ECOsystemSpaceborne Thermal Radiometer Experiment on Space Station) instrument on-board International Space Station (ISS) were used in an analytical SEB model, STIC (Surface Temperature Initiated Closure) to estimate ET and MAI. The ancillary variables used in the ET modeling and MAI estimation were land surface albedo, NDVI from close-by LANDSAT data at 30m spatial resolution, ET0 product at 4km spatial resolution from INSAT 3D, meteorological forcing variables from short-range weather forecast on air temperature and relative humidity from NWP model. Farm-scale ET estimates at 65m spatial resolution were found to show low RMSE of 16.6% to 17.5% with R2 >0.8 from 18 datasets as compared to reported errors (25 – 30%) from coarser-scale ET at 1 to 8 km spatial resolution when compared to in situ measurements from eddy covariance systems. The MAI was found to show lower (<0.25) and higher (>0.5) magnitudes in the contrasting agricultural farms. The study showed the potential need of high-resolution high-repeat spaceborne multi-band TIR payloads alongwith optical payload in estimating farm-scale ET and MAI for estimating consumptive water use and water stress. A set of future high-resolution multi-band TIR sensors are planned on-board Indo-French TRISHNA, ESA’s LSTM, NASA’s SBG space-borne missions to address sustainable irrigation water management at farm-scale to improve crop water productivity. These will provide precise and fundamental variables of surface energy balance such as LST (Land Surface Temperature), surface emissivity, albedo and NDVI. A synchronization among these missions is needed in terms of observations, algorithms, product definitions, calibration-validation experiments and downstream applications to maximize the potential benefits.

Keywords: thermal remote sensing, land surface temperature, crop water stress, evapotranspiration

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Authors: Marina Benito-Parejo, Raul Perez-Lopez, Miguel Herraiz, Carolina Guardiola-Albert, Cesar Martinez

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Persistency, long-term memory and randomness are intrinsic properties of time-series of earthquakes. The Rescaled Range Analysis (RS-Analysis) was introduced by Hurst in 1956 and modified by Mandelbrot and Wallis in 1964. This method represents a simple and elegant analysis which determines the range of variation of one natural property (the seismic energy released in this case) in a time interval. Despite the simplicity, there is complexity inherent in the property measured. The cumulative curve of the energy released in time is the well-known fractal geometry of a devil’s staircase. This geometry is used for determining the maximum and minimum value of the range, which is normalized by the standard deviation. The rescaled range obtained obeys a power-law with the time, and the exponent is the Hurst value. Depending on this value, time-series can be classified in long-term or short-term memory. Hence, an algorithm has been developed for compiling the RS-Analysis for time series of earthquakes by days. Completeness time distribution and locally stationarity of the time series are required. The interest of this analysis is their application for a complex seismic crisis where different earthquakes take place in clusters in a short period. Therefore, the Hurst exponent has been obtained for the seismic crisis of Alhoceima (Mediterranean Sea) of January-March, 2016, where at least five medium-sized earthquakes were triggered. According to the values obtained from the Hurst exponent for each cluster, a different mechanical origin can be detected, corroborated by the focal mechanisms calculated by the official institutions. Therefore, this type of analysis not only allows an approach to a greater understanding of a seismic series but also makes possible to discern different types of seismic origins.

Keywords: Alhoceima crisis, earthquake time series, Hurst exponent, rescaled range analysis

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Authors: Ho Yeon Park, Kyoung-Jae Kim

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Recently, user’s interests for location-based social network service increases according to the advances of social web and location-based technologies. It may be easy to recommend preferred items if we can use user’s preference, context and social network information simultaneously. In this study, we propose context-aware POI (point-of-interests) recommender systems using location-based network analysis and sentiment analysis which consider context, social network information and implicit user’s preference score. We propose a context-aware POI recommendation system consisting of three sub-modules and an integrated recommendation system of them. First, we will develop a recommendation module based on network analysis. This module combines social network analysis and cluster-indexing collaboration filtering. Next, this study develops a recommendation module using social singular value decomposition (SVD) and implicit SVD. In this research, we will develop a recommendation module that can recommend preference scores based on the frequency of POI visits of user in POI recommendation process by using social and implicit SVD which can reflect implicit feedback in collaborative filtering. We also develop a recommendation module using them that can estimate preference scores based on the recommendation. Finally, this study will propose a recommendation module using opinion mining and emotional analysis using data such as reviews of POIs extracted from location-based social networks. Finally, we will develop an integration algorithm that combines the results of the three recommendation modules proposed in this research. Experimental results show the usefulness of the proposed model in relation to the recommended performance.

Keywords: sentiment analysis, network analysis, recommender systems, point-of-interests, business analytics

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Authors: Yahaya Abdullahi, Ben Coetzee, Linda Van Den Berg

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The study aimed at establishing the global positioning system (GPS) determined singles match characteristics that act as predictors of successful and less-successful male singles badminton players’ group classification. Twenty-two (22) male single players (aged: 23.39 ± 3.92 years; body stature: 177.11 ± 3.06cm; body mass: 83.46 ± 14.59kg) who represented 10 African countries participated in the study. Players were categorised as successful and less-successful players according to the results of five championships’ of the 2014/2015 season. GPS units (MinimaxX V4.0), Polar Heart Rate Transmitter Belts and digital video cameras were used to collect match data. GPS-related variables were corrected for match duration and independent t-tests, a cluster analysis and a binary forward stepwise logistic regression were calculated. A Receiver Operating Characteristic Curve (ROC) was used to determine the validity of the group classification model. High-intensity accelerations per second were identified as the only GPS-determined variable that showed a significant difference between groups. Furthermore, only high-intensity accelerations per second (p=0.03) and low-intensity efforts per second (p=0.04) were identified as significant predictors of group classification with 76.88% of players that could be classified back into their original groups by making use of the GPS-based logistic regression formula. The ROC showed a value of 0.87. The identification of the last-mentioned GPS-related variables for the attainment of badminton performances, emphasizes the importance of using badminton drills and conditioning techniques to not only improve players’ physical fitness levels but also their abilities to accelerate at high intensities.

Keywords: badminton, global positioning system, match analysis, inertial movement analysis, intensity, effort

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Authors: An Chengrui, Yin Zi, Wu Bingbing, Ma Yuanzhu, Jin Kaixiu, Chen Xiao, Ouyang Hongwei

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Single cell RNA sequence (scRNA-seq) is one of the effective tools to study transcriptomics of biological processes. Recently, similarity measurement of cells is Euclidian distance or its derivatives. However, the process of scRNA-seq is a multi-variate Bernoulli event model, thus we hypothesize that it would be more efficient when the divergence between cells is valued with relative entropy than Euclidian distance. In this study, we compared the performances of Euclidian distance, Spearman correlation distance and Relative Entropy using scRNA-seq data of the early, medial and late stage of limb development generated in our lab. Relative Entropy is better than other methods according to cluster potential test. Furthermore, we developed KL-SNE, an algorithm modifying t-SNE whose definition of divergence between cells Euclidian distance to Kullback–Leibler divergence. Results showed that KL-SNE was more effective to dissect cell heterogeneity than t-SNE, indicating the better performance of relative entropy than Euclidian distance. Specifically, the chondrocyte expressing Comp was clustered together with KL-SNE but not with t-SNE. Surprisingly, cells in early stage were surrounded by cells in medial stage in the processing of KL-SNE while medial cells neighbored to late stage with the process of t-SNE. This results parallel to Heatmap which showed cells in medial stage were more heterogenic than cells in other stages. In addition, we also found that results of KL-SNE tend to follow Gaussian distribution compared with those of the t-SNE, which could also be verified with the analysis of scRNA-seq data from another study on human embryo development. Therefore, it is also an effective way to convert non-Gaussian distribution to Gaussian distribution and facilitate the subsequent statistic possesses. Thus, relative entropy is potentially a better way to determine the divergence of cells in scRNA-seq data analysis.

Keywords: Single cell RNA sequence, Similarity measurement, Relative Entropy, KL-SNE, t-SNE

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Authors: Yasir Ali, Farhatullah

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The present study was conducted to estimate the genetic variability, heritability and genetic advance in six parental lines and their 56 genotypes derived from five introgressed brassica populations on the basis of morphological and biochemical traits. The experiment was laid out in a randomized complete block design with two replications at The University of Agriculture Peshawar-Pakistan during growing season of 2015-2016. The ANOVA of all traits of F5:6 populations showed highly significant differences (P ≤ 0.01) for all morphological and biochemical traits. Among F5:6 populations, the genotype 2(526) was earlier in flowering (108.65 days), and genotype 14(485) was earlier in maturity (170 days). Tallest plants (182.5 cm), largest main raceme (91.5 cm) and maximum number of pods (80.5) on main raceme were recorded for genotype 17(34). Maximum primary branches plant-1(6.2) and longest pods (10.26 cm) were recorded for genotype 15, while genotype 16(171) had more seeds pod⁻¹ (22) and gave maximum yield plant-1 (30.22 g). The maximum 100-seed weight (0.60 g) was observed for genotype 10(506) while high protein content (22.61%) was recorded for genotype 4(99). Maximum oil content (54.08 %) and low linoleic acid (7.07 %) were produced by genotype (12(138) and low glucosinolate (59.01 µMg⁻¹) was recorded for genotype 21(113). The genotype 27(303) having high oleic acid content (51.73 %) and genotype 1(209) gave low erucic acid (35.97 %). Among the F5:6 populations moderate to high heritability observed for all morphological and biochemical traits coupled with high genetic advance. Cluster analysis grouped the 56 F5:6 populations along their parental lines into seven different groups. Each group was different from the other group on the basis of morphological and biochemical traits. Moreover all the F5:6 populations showed sufficient variability. Genotypes 10(506) and 16(171) were superior for high seed yield⁻¹, 100-seeds weight, and seed pod⁻¹ and are recommended for future breeding program.

Keywords: Brassicaceae, biochemical characterization, introgression, morphological characterization

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Authors: A. Rezazadeh, N. Omidvar, H. Eini-Zinab

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Food insecurity (FI) influences may result in poor physical and mental health outcomes. Minor ethnic group may experience higher level of FI, and this situation may be related with higher depression prevalence. The aim of this study was to determine the association of depression with food security status in major (Azeri) and minor (Kurdish) ethnicity living in Urmia, West Azerbaijan, north of Iran. In this cross-sectional study, 723 participants (427 women and 296 men) aged 20–64 years old, from two ethnic groups (445 Azeri and 278 Kurdish), were selected through a multi stage cluster systematic sampling. Depression rate was assessed by “Beck” short form questionnaire (validated in Iranians) through interviews. Household FI status (HFIS) was measured using adapted HFI access scale through face-to-face interviews at homes. Multinomial logistic regression was used to estimate odds ratios (OR) of depression across HFIS. Higher percent of Kurds had moderate and severe depression in comparison with Azeri group (73 [17.3%] vs. 86 [27.9%]). There were not any significant differences between the two ethnicities in mild depression. Also, of all the subjects, moderate-to-sever FI was more prevalent in Kurds (28.5%), compared to Azeri group (17.3%) [P < 0.01]. Kurdish ethnic group living in food security or mild FI households had lower chance to have symptom of severe depression in comparison to those with sever FI (OR=0.097; 95% CI: 0.02-0.47). However, there was no significant association between depression and HFI in Azeri group. Findings revealed that the severity of HFI was related with severity depression in minor studied ethnic groups. However, in Azeri ethnicity as a major group, other confounders may have influence on the relation with depression and FI, that were not studied in the present study.

Keywords: depression, ethnicity, food security status, Iran

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Authors: Hussain Sajid, Jung-Hun Shin, Kum-Won Cho

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Image super-resolution is the most common computer vision problem with many important applications. Generative adversarial networks (GANs) have promoted remarkable advances in single-image super-resolution (SR) by recovering photo-realistic images. However, high memory requirements of GAN-based SR (mainly generators) lead to performance degradation and increased energy consumption, making it difficult to implement it onto resource-constricted devices. To relieve such a problem, In this paper, we introduce an optimized and highly efficient architecture for SR-GAN (generator) model by utilizing model compression techniques such as Knowledge Distillation and pruning, which work together to reduce the storage requirement of the model also increase in their performance. Our method begins with distilling the knowledge from a large pre-trained model to a lightweight model using different loss functions. Then, iterative weight pruning is applied to the distilled model to remove less significant weights based on their magnitude, resulting in a sparser network. Knowledge Distillation reduces the model size by 40%; pruning then reduces it further by 18%. To accelerate the learning process, we employ the Horovod framework for distributed training on a cluster of 2 nodes, each with 8 GPUs, resulting in improved training performance and faster convergence. Experimental results on various benchmarks demonstrate that the proposed compressed model significantly outperforms state-of-the-art methods in terms of peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), and image quality for x4 super-resolution tasks.

Keywords: single-image super-resolution, generative adversarial networks, knowledge distillation, pruning

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Authors: Aneek Kuila, Yaron Paz

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MIP 177 LT and HT are two-phase transformable metal organic frameworks consisting of a Ti12O15 oxocluster and a tetracarboxylate ligand that exhibits robust chemical stability and improved photoactivity. LT to HT only shows the changes in dimensionality from 0D to 1D without any change in the overall chemical structure. In terms of chemical and photoactivity MIP 177 LT is found to perform better than the MIP 177HT. Step-scan Fourier transform absorption difference time-resolved spectroscopy has been used to collect mid-IR time-resolved infrared spectra of the transient electronic excited states of a nano-porous metal–organic framework MIP 177-LT and HT with 2.5 ns time resolution. Analyzing the time-resolved vibrational data after 355nm LASER excitation reveals the presence of the temporal changes of ν (O-Ti-O) of Ti-O metal cluster and ν (-COO) of the ligand concluding the fact that these moieties are the ultimate acceptors of the excited charges which are localized over those regions on the nanosecond timescale. A direct negative correlation between the differential absorbance (Δ Absorbance) reveals the charge transfer relation among these two moieties. A longer-lived transient signal up to 180ns for MIP 177 LT compared to the 100 ns of MIP 177 HT shows the extended lifetime of the reactive charges over the surface that exerts in their effectivity. An ultrafast change of bidentate to monodentate bridging in the -COO-Ti-O ligand-metal coordination environment was observed after the photoexcitation of MIP 177 LT which remains and lives with for seconds after photoexcitation is halted. This phenomenon is very unique to MIP 177 LT but not observed with HT. This in-situ change in the coordination denticity during the photoexcitation was not observed previously which can rationalize the reason behind the ability of MIP 177 LT to accumulate electrons during continuous photoexcitation leading to a superior photocatalytic activity.

Keywords: time resolved FTIR, metal organic framework, denticity, photoacatalysis

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Authors: Radka Sefcu, Vaclava Antuskova, Ivana Turkova

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A growing market with modern artworks of a high price leads to the creation and selling of artwork counterfeits. Material analysis is an important part of the process of assessment of authenticity. Knowledge of materials and techniques used by original authors is also necessary. The contribution presents possibilities of non-invasive methods of structural analysis in research on paintings. It was proved that unambiguous identification of many art materials is feasible without sampling. The combination of Raman spectroscopy with FTIR-external reflection enabled the identification of pigments and binders on selected artworks of prominent Czech painters from the first half of the 20th century – Josef Čapek, Emil Filla, Václav Špála and Jan Zrzavý. Raman spectroscopy confirmed the presence of a wide range of white pigments - lead white, zinc white, titanium white, barium white and also Freeman's white as a special white pigment of painting. Good results were obtained for red, blue and most of the yellow areas. Identification of green pigments was often impossible due to strong fluorescence. Oil was confirmed as a binding medium on most of the analyzed artworks via FTIR - external reflection. Collected data present the valuable background for the determination of art materials characteristic for each painter (his palette) and its development over time. Obtained results will further serve as comparative material for the authentication of artworks. This work has been financially supported by the project of the Ministry of the Interior of the Czech Republic: The Development of a Strategic Cluster for Effective Instrumental Technological Methods of Forensic Authentication of Modern Artworks (VJ01010004).

Keywords: non-invasive analysis, Raman spectroscopy, FTIR-external reflection, forgeries

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Authors: M. Mohan, J. P. Roise, G. P. Catts

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Despite living in an era where conservation zones are de-facto the central element in any sustainable wildlife management strategy, we still find ourselves grappling with several pareto-optimal situations regarding resource allocation and area distribution for the same. In this paper, a multi-objective decision making (MODM) model is presented to answer the question of whether or not we can establish mutual relationships between these contradicting objectives. For our study, we considered a Red-cockaded woodpecker (Picoides borealis) habitat conservation scenario in the coastal plain of North Carolina, USA. Red-cockaded woodpecker (RCW) is a non-migratory territorial bird that excavates cavities in living pine trees for roosting and nesting. The RCW groups nest in an aggregation of cavity trees called ‘cluster’ and for our model we use the number of clusters to be established as a measure of evaluating the size of conservation zone required. The case study is formulated as a linear programming problem and the objective function optimises the Red-cockaded woodpecker clusters, carbon retention rate, biofuel, public safety and Net Present Value (NPV) of the forest. We studied the variation of individual objectives with respect to the amount of area available and plotted a two dimensional dynamic graph after establishing interrelations between the objectives. We further explore the concept of interdependency by integrating the MODM model with GIS, and derive a raster file representing carbon distribution from the existing forest dataset. Model results demonstrate the applicability of interdependency from both linear and spatial perspectives, and suggest that this approach holds immense potential for enhancing environmental investment decision making in future.

Keywords: conservation, interdependency, multi-objective decision making, red-cockaded woodpecker

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Authors: Vitor M. Vilas Boas, Cleison D. Silva, Gustavo S. Mafra, Alexandre Trofino Neto

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Motor imagery (MI) based brain-computer interfaces (BCI) uses event-related (de)synchronization (ERS/ ERD), typically recorded using electroencephalography (EEG), to translate brain electrical activity into control commands. To mitigate undesirable artifacts and noise measurements on EEG signals, methods based on band-pass filters defined by a specific frequency band (i.e., 8 – 30Hz), such as the Infinity Impulse Response (IIR) filters, are typically used. Spatial techniques, such as Common Spatial Patterns (CSP), are also used to estimate the variations of the filtered signal and extract features that define the imagined motion. The CSP effectiveness depends on the subject's discriminative frequency, and approaches based on the decomposition of the band of interest into sub-bands with smaller frequency ranges (SBCSP) have been suggested to EEG signals classification. However, despite providing good results, the SBCSP approach generally increases the computational cost of the filtering step in IM-based BCI systems. This paper proposes the use of the Fast Fourier Transform (FFT) algorithm in the IM-based BCI filtering stage that implements SBCSP. The goal is to apply the FFT algorithm to reduce the computational cost of the processing step of these systems and to make them more efficient without compromising classification accuracy. The proposal is based on the representation of EEG signals in a matrix of coefficients resulting from the frequency decomposition performed by the FFT, which is then submitted to the SBCSP process. The structure of the SBCSP contemplates dividing the band of interest, initially defined between 0 and 40Hz, into a set of 33 sub-bands spanning specific frequency bands which are processed in parallel each by a CSP filter and an LDA classifier. A Bayesian meta-classifier is then used to represent the LDA outputs of each sub-band as scores and organize them into a single vector, and then used as a training vector of an SVM global classifier. Initially, the public EEG data set IIa of the BCI Competition IV is used to validate the approach. The first contribution of the proposed method is that, in addition to being more compact, because it has a 68% smaller dimension than the original signal, the resulting FFT matrix maintains the signal information relevant to class discrimination. In addition, the results showed an average reduction of 31.6% in the computational cost in relation to the application of filtering methods based on IIR filters, suggesting FFT efficiency when applied in the filtering step. Finally, the frequency decomposition approach improves the overall system classification rate significantly compared to the commonly used filtering, going from 73.7% using IIR to 84.2% using FFT. The accuracy improvement above 10% and the computational cost reduction denote the potential of FFT in EEG signal filtering applied to the context of IM-based BCI implementing SBCSP. Tests with other data sets are currently being performed to reinforce such conclusions.

Keywords: brain-computer interfaces, fast Fourier transform algorithm, motor imagery, sub-band common spatial patterns

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Authors: Khadijat Olabisi Abdulwahab, Mohammad Azad Malik, Paul O'Brien, Grigore Timco, Floriana Tuna

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The synthesis of spinel ferrite nanoparticles with a narrow size distribution is very crucial in their numerous applications including information storage, hyperthermia treatment, drug delivery, contrast agent in magnetic resonance imaging, catalysis, sensors, and environmental remediation. Ferrites have the general formula MFe₂O₄ (M = Fe, Co, Mn, Ni, Zn e.t.c) and possess remarkable electrical and magnetic properties which depend on the cations, method of preparation, size and their site occupancies. To the best of our knowledge, there are no reports on the use of a single source precursor to synthesise quaternary ferrite nanoparticles. Here in, we demonstrated the use of trimetallic iron pivalate cluster [CrCoFeO(O₂CᵗBu)₆(HO₂CᵗBu)₃] as a single source precursor to synthesise monodisperse cobalt chromium ferrite (FeCoCrO₄) nanoparticles by the hot injection thermolysis method. The precursor was thermolysed in oleylamine, oleic acid, with diphenyl ether as solvent at 260 °C. The effect of reaction time on the stoichiometry, phases or morphology of the nanoparticles was studied. The p-XRD patterns of the nanoparticles obtained after one hour was pure phase of cubic iron cobalt chromium ferrite (FeCoCrO₄). TEM showed that a more monodispersed spherical ferrite nanoparticles were obtained after one hour. Magnetic measurements revealed that the ferrite particles are superparamagnetic at room temperature. The nanoparticles were characterised by Powder X-ray Diffraction (p-XRD), Transmission Electron Microscopy (TEM), Energy Dispersive Spectroscopy (EDS) and Super Conducting Quantum Interference Device (SQUID).

Keywords: cobalt chromium ferrite, colloidal, hot injection thermolysis, monodisperse, reaction time, single source precursor, quaternary ferrite nanoparticles

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Authors: D. Calogine, O. Chau, S. Dotti, O. Ramiarinjanahary, P. Rasoavonjy, F. Tovondahiniriko

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Mafate is a natural circus in the north-western part of Reunion Island, without an electrical grid and road network. A micro-grid concept is being experimented in this area, composed of a photovoltaic production combined with electrochemical batteries, in order to meet the local population for self-consumption of electricity demands. This work develops a discrete model as well as a stochastic model in order to reach an optimal equilibrium between production and consumptions for a cluster of houses. The management of the energy power leads to a large linearized programming system, where the time interval of interest is 24 hours The experimental data are solar production, storage energy, and the parameters of the different electrical devices and batteries. The unknown variables to evaluate are the consumptions of the various electrical services, the energy drawn from and stored in the batteries, and the inhabitants’ planning wishes. The objective is to fit the solar production to the electrical consumption of the inhabitants, with an optimal use of the energies in the batteries by satisfying as widely as possible the users' planning requirements. In the discrete model, the different parameters and solutions of the linear programming system are deterministic scalars. Whereas in the stochastic approach, the data parameters and the linear programming solutions become random variables, then the distributions of which could be imposed or established by estimation from samples of real observations or from samples of optimal discrete equilibrium solutions.

Keywords: photovoltaic production, power consumption, battery storage resources, random variables, stochastic modeling, estimations of probability distributions, mixed integer linear programming, smart micro-grid, self-consumption of electricity.

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Authors: Kerem Rızvanoğlu, Serhat Güney, Emre Kızılkaya, Betül Aydoğan, Ayşegül Boyalı, Onurcan Güden

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This study addresses the re-construction and implementation process of the methodological framework developed to evaluate how locative media applications accompany the urban experiences of international students coming to Istanbul with exchange programs in 2022. The research design was built on a three-stage model. The research team conducted a qualitative questionnaire in the first stage to gain exploratory data. These data were then used to form three persona groups representing the sample by applying cluster analysis. In the second phase, a semi-structured digital diary study was carried out on a gamified task list with a sample selected from the persona groups. This stage proved to be the most difficult to obtaining valid data from the participant group. The research team re-evaluated the design of this second phase to reach the participants who will perform the tasks given by the research team while sharing their momentary city experiences, to ensure the daily data flow for two weeks, and to increase the quality of the obtained data. The final stage, which follows to elaborate on the findings, is the “Walk & Talk,” which is completed with face-to-face and in-depth interviews. It has been seen that the multiple methods used in the research process contribute to the depth and data diversity of the research conducted in the context of urban experience and locative technologies. In addition, by adapting the research design to the experiences of the users included in the sample, the differences and similarities between the initial research design and the research applied are shown.

Keywords: digital diary study, gamification, multi-model research, persona analysis, research design for urban experience, user-centered research, “Walk & Talk”

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Authors: Khadijat O. Abdulwahab, Mohammad A. Malik, Paul O’Brien, Grigore A. Timco, Floriana Tuna

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The synthesis of spinel ferrite nanoparticles with a narrow size distribution is very crucial in their numerous applications including information storage, hyperthermia treatment, drug delivery, contrast agent in magnetic resonance imaging, catalysis, sensors, and environmental remediation. Ferrites have the general formula MFe2O4 (M = Fe, Co, Mn, Ni, Zn etc.) and possess remarkable electrical and magnetic properties which depend on the cations, method of preparation, size and their site occupancies. To the best of our knowledge, there are no reports on the use of a single source precursor to synthesise quaternary ferrite nanoparticles. Herein, we demonstrated the use of trimetallic iron pivalate cluster [CrCoFeO(O2CtBu)6(HO2CtBu)3] as a single source precursor to synthesise monodisperse cobalt chromium ferrite (FeCoCrO4) nanoparticles by the hot injection thermolysis method. The precursor was thermolysed in oleylamine, oleic acid, with diphenyl ether as solvent at its boiling point (260°C). The effect of concentration on the stoichiometry, phases or morphology of the nanoparticles was studied. The p-XRD patterns of the nanoparticles obtained at both concentrations were matched with cubic iron cobalt chromium ferrite (FeCoCrO4). TEM showed that a more monodispersed spherical ferrite nanoparticles of average diameter 4.0 ± 0.4 nm were obtained at higher precursor concentration. Magnetic measurements revealed that all the ferrite particles are superparamagnetic at room temperature. The nanoparticles were characterised by Powder X-ray Diffraction (p-XRD), Transmission Electron Microscopy (TEM), Inductively Coupled Plasma (ICP), Electron Probe Microanalysis (EPMA), Energy Dispersive Spectroscopy (EDS) and Super Conducting Quantum Interference Device (SQUID).

Keywords: quaternary ferrite nanoparticles, single source precursor, monodisperse, cobalt chromium ferrite, colloidal, hot injection thermolysis

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Authors: Vidula Shevade, B. J. Nagare, Sajeev Chacko

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First principles simulation, meaning density functional theory (DFT) calculations with plane waves and pseudopotential, has become a prized technique in condensed matter theory. Nanoparticles (NP) have been known to possess good catalytic activities, especially for molecules such as CO, O₂, etc. Among the metal NPs, Aluminium based NPs are also widely known for their catalytic properties. Aluminium metal is a lightweight, excellent electrical, and thermal abundant chemical element in the earth’s crust. Aluminium NPs, when added to solid rocket fuel, help improve the combustion speed and considerably increase combustion heat and combustion stability. Adding aluminium NPs into normal Al/Al₂O₃ powder improves the sintering processes of the ceramics, with high heat transfer performance, increased density, and enhanced thermal conductivity of the sinter. We used VASP and Gaussian 0₃ package to compute the geometries, electronic structure, and bonding properties of Al₁₂Ni as well as its interaction with O₂ and CO molecules. Several MD simulations were carried out using VASP at various temperatures from which hundreds of structures were optimized, leading to 24 unique structures. These structures were then further optimized through a Gaussian package. The lowest energy structure of Al₁₂Ni has been reported to be a singlet. However, through our extensive search, we found a triplet state to be lower in energy. In our structure, the Ni atom is found to be on the surface, which gives the non-zero magnetic moment. Incidentally, O2 and CO molecules are also triplet in nature, due to which the Al₁₂-Ni cluster is likely to facilitate the oxidation process of the CO molecule. Our results show that the most favourable site for the CO molecule is the Ni atom and that for the O₂ molecule is the Al atom that is nearest to the Ni atom. Al₁₂Ni-O₂ and Al₁₂-Ni-CO structures we extracted using VMD. Al₁₂Ni nanocluster, due to in triplet electronic structure configuration, indicates it to be a potential candidate as a catalyst for oxidation of CO molecules.

Keywords: catalyst, gaussian, nanoparticles, oxidation

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Authors: Mehak Masood

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This paper aims to design an integrated solid waste management plan for industrial estates taking Sundar Industrial Estate as case model. The issue of solid waste management is on the rise in Pakistan especially in the industrial sector. In this regard, the concept of development and establishment of industrial estates is gaining popularity nowadays. Without proper solid waste management plan it is very difficult to manage day to day affairs of industrial estates. An industrial estate contains clusters of different types of industrial units. It is necessary to identify different types of solid waste streams from each industrial cluster within the estate. In this study, Sundar Industrial Estate was taken as a case model. Primary and secondary data collection, waste assessment, waste segregation and weighing and field surveys were essential elements of the study. Wastes from each industrial process were identified and quantified. Currently 130 industries are in production but after full colonization of industries this number would reach 385. Elaborated process flow diagrams were made to characterize the recyclable and non-recyclables waste. From the study it was calculated that about 12354.1 kg/captia/day of solid waste is being generated in Sundar Industrial Estate. After the full colonization of the industrial estate, the estimated quantity will be 4756328.5 kg/captia/day. Furthermore, solid waste generated from each industrial sector was estimated. Suggestions for collection and transportation are given. Environment friendly solid waste management practices are suggested. If an effective integrated waste management system is developed and implemented it will conserve resources, create jobs, reduce poverty, conserve natural resources, protect the environment, save collection, transportation and disposal costs and extend the life of disposal sites. A major outcome of this study is an integrated solid waste management plan for the Sundar Industrial Estate which requires immediate implementation.

Keywords: integrated solid waste management plan, industrial estates, Sundar Industrial Estate, Pakistan

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Authors: Ayodeji Adebayo, Tolulope Soyannwo, Oluwakemi A. Sigbeku

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Intimate Partner Violence (IPV) is a significant public health problem with adverse health consequences. There is increasing evidence of association of IPV with mental health problems. Understanding the association between IPV and mental health status of women of reproductive aged group in the rural communities in Nigeria can provide information to improve maternal health status. Therefore, this study was conducted to examine the relationship between experience of IPV and mental health status of women of reproductive aged group in a rural community in Southwest Nigeria. A community based cross-sectional survey was conducted using a cluster sampling technique to select 283 non-pregnant women of reproductive age group (15-49 years Mental health was assessed based on respondents’ experience of any symptoms of depression, anxiety and/or low self-esteem. IPV was assessed over a period of 12 months and the forms of IPV assessed were emotional, physical and sexual. An interviewer administered questionnaire was used to collect information on experience of IPV, reproductive history and factors influencing mental health. Data was analyzed using descriptive statistics, Chi-square and multivariate logistic regression at 5% level of significance. The mean age of respondents was 26.1± 7.8 with 57.1% aged 15-24years. More than half (58.0%) were married. Overall, 60.7% of respondents had mental health problems while 84.8% experienced all categories of violence. The pattern of IPV includes physical violence (10.7%), emotional violence (82.7%) and sexual violence (20.8%). Women who experienced sexual violence by a partner are most likely to suffer from all mental issues. Also, gynaecological morbidities are associated with increasing risk of mental health problems. The research demonstrates an urgent need for mental health policies to recognize the relationship between intimate partner violence, gynaecological morbidities and mental health problems in women in Nigeria.

Keywords: intimate partner violence, mental health, reproductive age group, women

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Authors: Y. S. Lin, H. L. Lin

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Climate change and land-use change caused by urban expansion increase the frequency of urban flooding. To mitigate the increase in runoff volume, low-impact development (LID) is a green approach for reducing the area of impervious surface and managing stormwater at the source with decentralized micro-scale control measures. However, the current benefit assessment and practical application of LID in Taiwan is still tending to be development plan in the community and building site scales. As for urban design, site-based moisture-holding capacity has been common index for evaluating LID’s effectiveness of urban design, which ignore the diversity, and complexity of the urban built environments, such as different densities, positive and negative spaces, volumes of building and so on. Such inflexible regulations not only probably make difficulty for most of the developed areas to implement, but also not suitable for every different types of built environments, make little benefits to some types of built environments. Looking toward to enable LID to strength the link with urban design to reduce the runoff in coping urban flooding, the research consider different characteristics of different types of built environments in developing LID strategy. Classify the built environments by doing the cluster analysis based on density measures, such as Ground Space Index (GSI), Floor Space Index (FSI), Floors (L), and Open Space Ratio (OSR), and analyze their impervious surface rates and runoff volumes. Simulate flood situations by using quasi-two-dimensional flood plain flow model, and evaluate the flood mitigation effectiveness of different types of built environments in different low-impact development strategies. The information from the results of the assessment can be more precisely implement in urban design. In addition, it helps to enact regulations of low-Impact development strategies in urban design more suitable for every different type of built environments.

Keywords: low-impact development, urban design, flooding, density measures

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Authors: Barry Majeed, Eka Febriana, Seto Julianto

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Kepulauan Seribu National Parks is a marine preservation region in Indonesia. It is located in 5°23' - 5°40' LS, 106°25' - 106°37' BT North of Jakarta City. Covered with area 107,489 ha, Kepulauan Seribu has a lot of tourism spots such as cluster islands, fringing reef and many more. Kepulauan Seribu is also nominated as Strategic Tourism Region In Indonesia (KSPN). So, these islands have a lot of potential sides more than preservation function as a national park, hence the development of sustainable geotourism. The aim of this study is for enhancing the development of eco-geotourism in Kepulauan Seribu. This study concern for three main aspect of eco-geotourism such as tourism, form and process. Study for the tourism aspect includes attractions, accommodations, tours, activities, interpretation, and planning & management in Kepulauan Seribu. Study for the form aspect focused on the carbonate platform situated between two islands. Primarily in carbonate reef such as head coral, branchy coral, platy coral that created the carbonate sequence in Kepulauan Seribu. Study for the process aspect primarily discussed the process of forming of carbonate from carbonate factory later becomes Kepulauan Seribu. Study for the regional geology of Kepulauan Seribu has been conducted and suggested that Kepulauan Seribu lithologies are mainly quarternary limestone. In this study, primary data was taken from an observation of quarternary carbonate platform between two islands from Hati Island, Macan Island, Bulat Island, Ubi Island and Kelapa Island. From this observation, the best routes for tourist have been made from Island to Island. Qualitative methods such as depth interview to the local people in purposive sampling also have been made. Finally, this study also giving education about geological site – carbonate sequence - in Kepulauan Seribu for the local wisdom so that this study can support the development of sustainable eco-geotourism in Kepulauan Seribu.

Keywords: carbonate factory, carbonate platform, geotourism, Kepulauan Seribu

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Authors: Chang-Fa Liu, Yi-Ting Wang, Yuan Liu, Hai-Feng Wei, Lei Fang, Jin Li

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Heavy metals in sediments can cause adverse ecological effects while it exceeds a given criteria. The present study investigated sediment environmental quality, pollutant enrichment, ecological risk, and source identification for copper, cadmium, lead, zinc, mercury, and arsenic in the sediments collected from tidal flat marsh of Shuangtai estuary, China. The arithmetic mean integrated pollution index, geometric mean integrated pollution index, fuzzy integrated pollution index, and principal component score were used to characterize sediment environmental quality; fuzzy similarity and geo-accumulation Index were used to evaluate pollutant enrichment; correlation matrix, principal component analysis, and cluster analysis were used to identify source of pollution; environmental risk index and potential ecological risk index were used to assess ecological risk. The environmental qualities of sediment are classified to very low degree of contamination or low contamination. The similar order to element background of soil in the Liaohe plain is region of Sanjiaozhou, Honghaitan, Sandaogou, Xiaohe by pollutant enrichment analysis. The source identification indicates that correlations are significantly among metals except between copper and cadmium. Cadmium, lead, zinc, mercury, and arsenic will be clustered in the same clustering as the first principal component. Copper will be clustered as second principal component. The environmental risk assessment level will be scaled to no risk in the studied area. The order of potential ecological risk is As > Cd > Hg > Cu > Pb > Zn.

Keywords: ecological risk assessment, heavy metals, sediment, marsh, Shuangtai estuary

Procedia PDF Downloads 347

Authors: Erin V. Kelly, Nicola C. Newton, Lexine A. Stapinski, Maree Teesson

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Introduction: There is a lack of targeted prevention programs for reducing bullying and distress among adolescents involved in bullying. The current study aimed to examine the impact of a personality-targeted intervention (Preventure) on bullying (victimization and perpetration) and distress among adolescent victims/bullies with high-risk personality types. Method: A cluster randomized trial (RCT) was conducted in 26 secondary schools (2190 students) in NSW and Victoria, Australia, as part of the Climate Schools and Preventure trial. The schools were randomly allocated to Preventure (13 schools received Preventure, 13 did not). Students were followed up at 4 time points (6, 12, 24 and 36 months post-baseline). Preventure involves two group sessions, based on cognitive behavioral therapy, and tailored to four personality types shown to increase risk of substance misuse and other emotional and behavioural problems, including impulsivity, sensation-seeking, anxiety sensitivity and hopelessness. Students were allocated to the personality-targeted groups based on their scores on the Substance Use Risk Profile Scale. Bullying was measured using an amended version of the Revised Olweus Bully/Victim Scale. Psychological distress was measured using the Kessler Psychological Distress Scale. Results: Among high-risk students classified as victims at baseline, those in Preventure schools reported significantly less victimization and distress over time than those in control schools. Among high-risk students classified as bullies at baseline, those in Preventure schools reported significantly less distress over time than those in control schools (no difference for perpetration). Conclusion: Preventure is a promising intervention for reducing bullying victimization and psychological distress among adolescents involved in bullying.

Keywords: adolescents, bullying, personality, prevention

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Authors: Naveeda Akhtar Qureshi, Wajiha

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Coccidiosis is a protozoan parasitic disease of genus Eimeria. It is an avian infection causing a great economic loss of 3 billion USD per year globally. A number of anticoccidial drugs are in use however many of them have side effects and cost effective. With increase in poultry demand throughout the world there is a need of more drugs and vaccines against coccidiosis. The present study is based upon the use of F. racemosa a medicinal plant to be a potential source of anticoccidial agents. The methanolic leaves extract was fractionated by column and thin layer chromatography and got nineteen fractions. Each fraction different concentrations was evaluated for its anticoccidial properties in an invitro experiment against E. tenella, E. necatrix and E. mitis. The anticoccidial active fractions were further characterized by spectroscopy (UV-Vis, FTIR) and GC-MS analysis. The in silico molecular docking of active fractions identified compounds were carried out. Among all fractions significantly maximum sporulation inhibition efficacy was shown by F-19 (67.11±2.18) followed by F-15 (65.21±1.34) at concentration of 30mg/ml against E. tenella. The significantly highest sporozoites viability inhibition was shown by F-19 (69.23±2.11) followed by F-15 (67.14±1.52) against E. necatrix at concentration 30mg/ml. Anticoccidial active fractions 15 and 19 showed peak spectrum at 207 and 202nm respectively by UV analysis. Their FTIR analysis confirmed the presence of carboxylic acid, amines, phenols, etc. Anticoccidial active compounds like Cyclododecane methanol, oleic acid, Octadecanoic acid, etc were identified by GC-MS analysis. Identified compounds in silico molecular docking study showed that cyclododecane methanol of F-19 and oleic acid of F-15 showed highest binding affinity with target S-Adenosylmethionine synthase. Hence for further authentication in vivo anticoccidial studies are recommended.

Keywords: ficus racemosa, cluster fig, column chromatography, anticoccidial fractions, GC-MS, molecular docking., s-adenosylmethionine synthase

Procedia PDF Downloads 85