Search results for: gold clusters

Authors: Fitri CaturLestari

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According to National Population and Family Planning Board (BKKBN), demographic bonus will occur in 2025-2035, when the number of people within the productive age bracket is higher than the number of elderly people and children. This time will be a gold moment for Indonesia to achieve maximum productivity and prosperity. But it will be a demographic bomb if it isn’t balanced by economic and social aspect considerations. Therefore it is important to make a prediction mapping of all provinces in Indonesia whether in demographic bomb or bonus condition after 100 years Indonesian independence. The purpose of this research were to make the demographic mapping based on the economic and social aspects of the provinces in Indonesia and categorizing them into demographic bomb and bonus condition. The research data are gained from Statistics Indonesia (BPS) as the secondary data. The multiregional component method, regression and quadrant analysis were used to predict the number of people, economic growth, Human Development Index (HDI), and gender equality in education and employment. There were different characteristic of provinces in Indonesia from economic aspect and social aspect. The west Indonesia was already better developed than the east one. The prediction result, many provinces in Indonesia will get demographic bonus but the others will get demographic bomb. It is important to prepare particular strategy to particular provinces with all of their characteristic based on the prediction result so the demographic bomb can be minimalized.

Keywords: demography, economic growth, gender, HDI

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Authors: Yogi Priyo Pradana, Heriansyah Putra, Regina Aprilia Zulfikar, Maulana Rafiq Ramadhan, Devyan Meisnnehr, Zalfa Maulida Insani

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This paper studied the effects and mechanisms of fine-grained tailing by Enzyme-Mediated Calcite Precipitation (EMCP). Grouting solution used consists of reagents (CaCl₂ and (CO(NH₂)₂) and urease enzymes which react to produce CaCO₃. In sample preparation, the test tube is used to investigate the precipitation rate of calcite. The grouting solution added is 75 mL for one mold sample. The solution was poured into a mold sample up to as high as 5 mm from the top surface of the tailing to ensure the entire surface is submerged. The sample is left open in a cylinder for up to 3 days for curing. The direct mixing method is conducted so that the cementation process occurs by evenly distributed. The relationship between the results of the UCS test and the calcite precipitation rate likely indicates that the amount of calcite deposited in treated tailing could control the strength of the tailing. The sample results are analyzed using atomic absorption spectroscopy (AAS) to evaluate metal and metalloid content. Calcium carbonate deposited in the tailing is expected to strengthen the bond between tailing granules, which are easily slipped on the banks of the tailing dam. The EMCP method is expected to strengthen tailing in erosion-control surfaces.

Keywords: tailing, EMCP, UCS, AAS

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Authors: Katarzyna Niewiadomska

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Many technology startups fail to achieve a worthwhile return on investment for their funders, founders, and employees. Failures in product development, to-market strategy, sales, and delivery are commonly recognized. Founder failures are not as obvious and harder to identify. This paper explores six critical failure points that entrepreneurs and innovators are susceptible to and aims to link their emotional intelligence and behavioral profile to the points at which they experienced self-perceived failure. A model of six failure points from the perspective of the technology entrepreneur ranging from pre-startup to maturity is provided. By analyzing emotional and behavioral profile data from entrepreneurs and recording in-person accounts, certain key emotional and behavioral clusters contributing to each failure point are determined, and several underlying factors are defined and discussed. Recommendations that support entrepreneurs and innovators stalling at each failure point are given. This work can enable stakeholders to evaluate founder emotional and behavioral profiles and to take risk-mitigating action, either through coaching or through more robust team creation, to avoid founder-related company failure. The paper will be of interest to investors funding startups, executives leading them and mentors supporting them.

Keywords: behavior, emotional intelligence, entrepreneur, failure

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Authors: Chellammal Surianarayanan

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Healthcare industry is generating large amounts of data driven by various needs such as record keeping, physician’s prescription, medical imaging, sensor data, Electronic Patient Record(EPR), laboratory, pharmacy, etc. Healthcare data is so big and complex that they cannot be managed by conventional hardware and software. The complexity of healthcare big data arises from large volume of data, the velocity with which the data is accumulated and different varieties such as structured, semi-structured and unstructured nature of data. Despite the complexity of big data, if the trends and patterns that exist within the big data are uncovered and analyzed, higher quality healthcare at lower cost can be provided. Hadoop is an open source software framework for distributed processing of large data sets across clusters of commodity hardware using a simple programming model. The core components of Hadoop include Hadoop Distributed File System which offers way to store large amount of data across multiple machines and MapReduce which offers way to process large data sets with a parallel, distributed algorithm on a cluster. Hadoop ecosystem also includes various other tools such as Hive (a SQL-like query language), Pig (a higher level query language for MapReduce), Hbase(a columnar data store), etc. In this paper an analysis has been done as how healthcare big data can be processed and analyzed using Hadoop ecosystem.

Keywords: big data analytics, Hadoop, healthcare data, towards quality healthcare

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Authors: Nana Saralidze, Nino Sharashenidze, Zurab Kevanishvili

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Hidden hearing loss may occur in humans exposed to prolonged high-level sound. It is the loss of ability to hear high-level background noise while having normal hearing in quiet. We compared the hearing of people who regularly listen 3 hours and more to personal music players and those who do not. Forty participants aged 18-30 years were divided into two groups: regular users of music players and people who had never used them. And the third group – elders aged 50-55 years, had 15 participants. Pure-tone audiometry (125-16000 Hz), auditory brainstem response (ABR) (70dB SPL), and ability to identify speech in noise (4-talker babble with a 65-dB signal-to-noise ratio at 80 dB) were measured in all participants. All participants had normal pure-tone audiometry (all thresholds < 25 dB HL). A significant difference between groups was observed in that regular users of personal audio systems correctly identified 53% of words, whereas the non-users identified 74% and the elder group – 63%. This contributes evidence supporting the presence of a hidden hearing loss in humans and demonstrates that speech-in-noise audiometry is an effective method and can be considered as the GOLD standard for detecting hidden hearing loss.

Keywords: mp3 player, hidden hearing loss, speech audiometry, pure tone audiometry

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Authors: Fayyaz Rasool, Shakeela Parveen

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The studies on genetic diversity of Labeo rohita by using molecular markers were carried out to investigate the genetic structure by RAPAD marker and the levels of polymorphism and similarity amongst the different groups of five populations of wild and farmed types. The samples were collected from different five locations as representatives of wild and hatchery raised populations. RAPAD data for Jaccard’s coefficient by following the un-weighted Pair Group Method with Arithmetic Mean (UPGMA) for Hierarchical Clustering of the similar groups on the basis of similarity amongst the genotypes and the dendrogram generated divided the randomly selected individuals of the five populations into three classes/clusters. The variance decomposition for the optimal classification values remained as 52.11% for within class variation, while 47.89% for the between class differences. The Principal Component Analysis (PCA) for grouping of the different genotypes from the different environmental conditions was done by Spearman Varimax rotation method for bi-plot generation of the co-occurrence of the same genotypes with similar genetic properties and specificity of different primers indicated clearly that the increase in the number of factors or components was correlated with the decrease in eigenvalues. The Kaiser Criterion based upon the eigenvalues greater than one, first two main factors accounted for 58.177% of cumulative variability.

Keywords: variation, clustering, PCA, wild, hatchery, RAPAD, Labeo rohita

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Authors: María Molinos-Senante, Giulia Romano

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This paper aims at investigating the effect of ownership in the efficiency assessment of municipal solid waste management. In doing so, the Data Envelopment Analysis meta-frontier approach integrating unsorted waste as undesirable output was applied. Three different clusters of municipalities have been created on the basis of the ownership type of municipal waste operators. In the second stage of analysis, the paper investigates factors affecting efficiency, in order to provide an outlook of levers to be used by policy and decision makers to improve efficiency, taking into account different management models in force. Results show that public waste management firms have better performance than mixed and private ones since their efficiency scores are significantly larger. Moreover, it has been demonstrated that the efficiency of waste management firms is statistically influenced by the age of population, population served, municipal size, population density and tourism rate. It evidences the importance of economies of scale on the cost efficiency of waste management. This issue is relevant for policymakers to define and implement policies aimed to improve the long-term sustainability of waste management in municipalities.

Keywords: data envelopment analysis, efficiency, municipal solid waste, ownership, undesirable output

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Authors: Eylem Koç, Hasan Arda Burhan

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Location selection presents a crucial decision problem in today’s business world where strategic decision making processes have critical importance. Thus, location selection has strategic importance for companies in boosting their strength regarding competition, increasing corporate performances and efficiency in addition to lowering production and transportation costs. A right choice in location selection has a direct impact on companies’ commercial success. In this study, a store location selection problem of Carglass Turkey which operates in vehicle glass branch is handled. As this problem includes both tangible and intangible criteria, Analytic Network Process (ANP) was accepted as the main methodology. The model consists of control hierarchy and BOCR subnetworks which include clusters of actors, alternatives and criteria. In accordance with the management’s choices, five different locations were selected. In addition to the literature review, a strict cooperation with the actor group was ensured and maintained while determining the criteria and during whole process. Obtained results were presented to the management as a report and its feasibility was confirmed accordingly.

Keywords: analytic network process (ANP), BOCR, multi-actor decision making, multi-criteria decision making, real-life problem, location selection

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Authors: Shan-Ying Wu, Sheng-Hui Lan, Xi-Zhang Lin, Ih-Jen Su, Ting-Fen Tsai, Chia-Jui Yen, Tsung-Hsueh Lu, Fu-Wen Liang, Huey-Jen Su, Chun-Li Su, Hsiao-Sheng Liu

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In hepatocelluar carcinoma (HCC), dysregulated expression of cyclin D1 and impaired autophagy has been reported separately. However, the relationship between them has not been explored. In this study, we demonstrated that autophagy was inversely correlated with cyclin D1 expression in 147 paired HCC patient specimens. HCC specimen with highly expression of cyclin D1 shows correlation with poor overall survival rate. Furthermore, induction of autophagy by amiodarone (antiarrhythmic drug) in Hep 3B cells, cyclin D1 was recruited into autophagosomes demonstrated by immune-gold labeling of cyclin D1 after extraction of autophagosomes. We further demonstrated that autophagy suppresses Hep 3B cell proliferation, and further analysis revealed that cell cycle was arrested at G1 phase. The interaction between LC3 (maker of autophagy) and cyclin D1 was increased after autophagy induction. In addition, ubiquitinated-cyclin D1 was also increased after autophagy induction, which is selectively degraded by autophagosome through binding with SQSTM1/p62 (an adaptor protein). In vivo study showed that amiodarone induced autophagy suppresses liver tumor formation in xenograft mouse and orthotopic rat model through decreasing cyclin D1 expression and inhibition of cell proliferation. Altogether, we reveal a novel mechanism that ubiquitinated cyclin D1 degraded by autophagic pathway by p62 and amiodarone is a promising drug for targeting cyclin D1 in liver cancer therapy.

Keywords: autophagy, cyclin D1, hepatocellular carcinoma, amiodarone

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Authors: Simeon Mayala, Ida Herdlevær, Jonas Bull Haugsøen, Shamundeeswari Anandan, Sonia Gavasso, Morten Brun

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In this paper, we propose a minimum spanning tree-based method for segmenting brain tumors. The proposed method performs interactive segmentation based on the minimum spanning tree without tuning parameters. The steps involve preprocessing, making a graph, constructing a minimum spanning tree, and a newly implemented way of interactively segmenting the region of interest. In the preprocessing step, a Gaussian filter is applied to 2D images to remove the noise. Then, the pixel neighbor graph is weighted by intensity differences and the corresponding minimum spanning tree is constructed. The image is loaded in an interactive window for segmenting the tumor. The region of interest and the background are selected by clicking to split the minimum spanning tree into two trees. One of these trees represents the region of interest and the other represents the background. Finally, the segmentation given by the two trees is visualized. The proposed method was tested by segmenting two different 2D brain T1-weighted magnetic resonance image data sets. The comparison between our results and the standard gold segmentation confirmed the validity of the minimum spanning tree approach. The proposed method is simple to implement and the results indicate that it is accurate and efficient.

Keywords: brain tumor, brain tumor segmentation, minimum spanning tree, segmentation, image processing

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Authors: Anusha Vaddiraj Pallapu

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Measuring urban sustainable development is at the forefront in contributing to overall sustainability, and it refers to attaining social equity, environmental protection and minimizing the impacts of urbanization. Assessing performance of urban issues ranging from larger consumption of natural resources by humans in terms of lifestyle to creating a polluted nearby environment, social and even economic dimensions of sustainability major issues observed such as water quality, transportation, management of solid waste and traffic pollution. However, relying on the framework of the project to do the goals of sustainable development or minimization of urban impacts through management practices is not enough to deal with the present urban issues. The aim of the sustainability is to know how severely the resources are depleted because of human consumption and how issues are characterized. The paper aims to assign benchmarks for the selected sustainability indicators for research, and analysis is done through multivariate analysis in Indian context a case of Nagpur city to identify the play role of each urban issues in the overall sustainability. The main objectives of this paper are to examine the indicators over by time basis on various scenarios and how benchmarking is used, what and which categories of values should be considered as the performance of indicators function.

Keywords: environmental sustainability indicators, principal component analysis, urban sustainability, urban clusters, benchmarking

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Authors: I. Shuro

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The crystal structure of Tin Sulfide prepared by certain chemical methods is investigated using High-Resolution Transmission Electron Microscopy (HRTEM), Scanning Electron Microscopy (SEM), and X-ray diffraction (XRD) methods. An anomalous HRTEM Fast Fourier Transform (FFT) exhibited a central scatter of diffraction spots, which is surrounded by secondary clusters of spots arranged in a hexagonal pattern around the central cluster was observed. FFT analysis has revealed a long lattice parameter and mostly viewed along a hexagonal axis where there many columns of atoms slightly displaced from one another. This FFT analysis has revealed that the metal sulfide has a long-range order interwoven chain of atoms in its crystal structure. The observed crystalline structure is inconsistent with commonly observed FFT patterns of chemically synthesized Tin Sulfide nanocrystals and thin films. SEM analysis showed the morphology of a myriad of multi-shaped crystals ranging from hexagonal, cubic, and spherical micro to nanostructured crystals. This study also investigates the presence of quasi-crystals as reflected by the presence of mixed local symmetries.

Keywords: fast fourier transform, high resolution transmission electron microscopy, tin sulfide, crystalline structure

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Authors: Stanley Yap, Mahadevan Supramaniam, Chong Wei Ying, Fatemeh Kimiyaghalam

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Purpose: The paper shows the framework of financial planning in a different paradigm. It highlights the results from a focus group on retirement planning in the aspect of financial literacy and wealth accumulation in Malaysia. Design/methodology/approach: A focus group consisted of thirty individuals and divided into six different clusters amongst 25 to 55 years old. The selection of focus group members is pertaining to retirement planning behavior and saving profile from the different level of educations. Findings: Our results show, firstly, the focus group reflects individual capacity on saving attitude, financial literacy and awareness towards financial products. Secondly, availability, accessibility and affordability which are the significant factors that influence saving attitude, financial literacy and awareness on personal retirement planning behavior. Practical implications: The participants express the concerns of retirement planning during their golden years and the current financial products in the Malaysian financial market. Originality/value: This study is a different approach that recognizes the needs of the consumers in the context of retirement planning and wealth accumulation. Therefore, customers should obtain financial services and products from financial providers to achieve financial independence.

Keywords: retirement planning, wealth accumulation, financial literacy, focus group, saving attitude, availability, accessibility, affordability

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Authors: Hasan Bulent Kantarci

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This paper examine how Zakat provide a fair income redistribution and struggle with poverty. To provide a fair income redistribution and struggle with poverty take place among the fundamental tasks of all countries. Each country seeks a solution for this problem according to their political, economical and administrative styles through applying various economic and financial policies. The same situation gets handled via zakat association in the Islam. Nowadays, we observe different versions of zakat in developed countries. The applications such as negative income tax denote merely a difference from the zakat being applied almost the same way under changed names. But the minimum values to donate the zakat (e.g. 85 gr. gold and 40 animals) get altered and various amounts are put into practice. It might be named as negative income tax instead of zakat, nonetheless, these applications are based on the Holy Koran and the hadith released 1400 years ago. Besides, considering the savage and slavery in the world at those times, we might easily recognize the true value of the zakat applied the first time then in Islamic system. Through zakat is enabled an income transfer by the government so that the poor could reach the minimum level of life standard. To whom the zakat would be donated was not left to people’s heart and encouraged to determine according to objective criteria. Since the zakat is obligatory, the transfer do not get forward by hand but via the government and get distributed, which requires a vast government organization. Through applying the zakat as it must be would achieve to reduce the poverty mostly and ensuring the fair income redistribution.

Keywords: Islamic finance, zakat, income redistribution, circle of poverty, negatif income tax

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Authors: M.F. Elkady, Sahar Zaki, Desouky Abd-El-Haleem

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Silver nanoparticles (AgNPs) are already widely prepared using different technologies. However, there are limited data on the effects of hydrogen ion concentration on nano-silver production. In this investigation, the impact of the pH reaction medium toward the particle size, agglomeration and the yield of the produced bio-synthesized silver were established. Quasi-spherical silver nanoparticles were synthesized through the biosynthesis green production process using the Egyptian E. coli bacterial strain 23N at different pH values. The formation of AgNPs has been confirmed with ultraviolet–visible spectra through identification of their characteristic peak at 410 nm. The quantitative production yield and the orientation planes of the produced nano-silver were examined using X-ray spectroscopy (EDS) and X-ray diffraction (XRD). Quantitative analyses indicated that the silver production yield was promoted at elevated pH regarded to increase the reduction rate of silver precursor through both chemical and biological processes. As a result, number of the nucleus and thus the size of the silver nanoparticles were tunable through changing pH of the reaction system. Accordingly, the morphological structure and size of the produced silver and its aggregates were determined using scanning electron microscopy (SEM) and transmission electron microscopy (TEM) images. It was considered that the increment in pH value of the reaction media progress the aggregation of silver clusters. However, the presence of stain 23N biomass decreases the possibility of silver aggregation at the pH 7.

Keywords: silver nanoparticles, biosynthesis, reaction media pH, nano-silver characterization

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Authors: Pei-Wen Lin, Ta-I Yang

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Cancer has been one of the leading causes of human death for centuries. Considerable effort has been devoted to developing new treatments to reduce and control cancers. Magnetic particle hyperthermia and near-infrared photothermal therapy are the promising strategies to treat cancers due to its effectiveness with only mild side effects. This study focused on synthesizing magnetic Ag@Fe3O4 nanoparticles applicable for both of magnetic hyperthermia and near-infrared photothermal therapy. The hydrophilic poly(diallyldimethylammonium chloride) polymer was utilized to prepare superparamagnetic Fe3O4 clusters and to promote silver nanoparticles grown on Fe3O4 surfaces, obtaining Ag@Fe3O4 nanoparticles. The morphology (shape and dimension) of Ag nanoparticles was subsequently tailored using commercial LED lights. Therefore, the resulting Ag@Fe3O4 nanoparticles can absorb specific wavelength of light ranging from 400 nm to 800 nm by adjusting the wavelength of LED lights and the free silver ions in reaction solution. Heating performance tests confirmed that the synthesized Ag@Fe3O4 nanoparticles show appreciable heating capability for both of magnetic particle hyperthermia and near-infrared photothermal therapy. The findings in this study could provide new ideas to design functional materials to treat cancers.

Keywords: light-emitting diode assisted synthesis, magnetic particles, photothermal materials, hyperthermia

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Authors: Feda Negesse

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One of the most important indicators of research quality is a good data - collection instrument that can yield reliable and valid data. The Swadesh wordlist has been used for more than half a century for collecting data in comparative and historical linguistics though arbitrariness is observed in its application and size. This research compare s the classification results of the 100 Swadesh wordlist with those of its subsets to determine if reducing the size of the wordlist impact s its effectiveness. In the comparison, the 100, 50 and 40 wordlists were used to compute lexical distances of 29 Cushitic and Semitic languages spoken in Ethiopia and neighbouring countries. Gabmap, a based application, was employed to compute the lexical distances and to divide the languages into related clusters. The study shows that the subsets are not as effective as the 100 wordlist in clustering languages into smaller subgroups but they are equally effective in di viding languages into bigger groups such as subfamilies. It is noted that the subsets may lead to an erroneous classification whereby unrelated languages by chance form a cluster which is not attested by a comparative study. The chance to get a wrong result is higher when the subsets are used to classify languages which are not closely related. Though a further study is still needed to settle the issues around the size of the Swadesh wordlist, this study indicates that the 50 and 40 wordlists cannot be recommended as reliable substitute s for the 100 wordlist under all circumstances. The choice seems to be determined by the objective of a researcher and the degree of affiliation among the languages to be classified.

Keywords: classification, Cushitic, Swadesh, wordlist

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Authors: Yan Cheng, Yijun Shao, James Rudolph, Charlene R. Weir, Beth Sahlmann, Qing Zeng-Treitler

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Supervised predictive models require labeled data for training purposes. Complete and accurate labeled data, i.e., a ‘gold standard’, is not always available, and imperfectly labeled data may need to serve as an alternative. An important question is if the accuracy of the labeled data creates a performance ceiling for the trained model. In this study, we trained several models to recognize the presence of delirium in clinical documents using data with annotations that are not completely accurate (i.e., weakly-supervised learning). In the external evaluation, the support vector machine model with a linear kernel performed best, achieving an area under the curve of 89.3% and accuracy of 88%, surpassing the 80% accuracy of the training sample. We then generated a set of simulated data and carried out a series of experiments which demonstrated that models trained on imperfect data can (but do not always) outperform the accuracy of the training data, e.g., the area under the curve for some models is higher than 80% when trained on the data with an error rate of 40%. Our experiments also showed that the error resistance of linear modeling is associated with larger sample size, error type, and linearity of the data (all p-values < 0.001). In conclusion, this study sheds light on the usefulness of imperfect data in clinical research via weakly-supervised learning.

Keywords: weakly-supervised learning, support vector machine, prediction, delirium, simulation

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Authors: Joshi Manisha, Shivaram, Anand Vinekar, Tanya Susan Mathews, Yeshaswini Nagaraj

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Retinopathy of prematurity (ROP) is abnormal blood vessel development in the retina of the eye in a premature infant. The principal object of the invention is to provide a technique for detecting demarcation line and ridge detection for a given ROP image that facilitates early detection of ROP in stage 1 and stage 2. The demarcation line is an indicator of Stage 1 of the ROP and the ridge is the hallmark of typically Stage 2 ROP. Thirty Retcam images of Asian Indian infants obtained during routine ROP screening have been used for the analysis. A graphical user interface has been developed to detect demarcation line/ridge and to extract ground truth. This novel algorithm uses multilevel vessel enhancement to enhance tubular structures in the digital ROP images. It has been observed that the orientation of the demarcation line/ridge is normal to the direction of the blood vessels, which is used for the identification of the ridge/ demarcation line. Quantitative analysis has been presented based on gold standard images marked by expert ophthalmologist. Image based analysis has been based on the length and the position of the detected ridge. In image based evaluation, average sensitivity and positive predictive value was found to be 92.30% and 85.71% respectively. In pixel based evaluation, average sensitivity, specificity, positive predictive value and negative predictive value achieved were 60.38%, 99.66%, 52.77% and 99.75% respectively.

Keywords: ROP, ridge, multilevel vessel enhancement, biomedical

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Authors: Hooshag Asadi Haroni, Maryam Veiskarami, Yongjun Lu

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The Dalli gold-rich porphyry deposit (17 Mt @ 0.5% Cu and 0.65 g/t Au) is located in the Urumieh-Dokhtar Magmatic Arc (UDMA), a small segment of the Tethyan metallogenic belt, hosting several porphyry Cu (Mo-Au) systems in Iran. This research characterizes the Dalli deposit to define exploration criteria in advanced exploration such as the drilling of possible blind porphyry centers. Geological map, trench/drill hole geochemical and ground magnetic data, and age dating and isotope trace element analyses, carried out at the John De Laeter Research Center of Curtin University, were used to characterize the Delli deposit. Mineralization at Dalli is hosted by NE-trending quartz-diorite porphyry stocks (~ 200m in diameter) intruded by a wall-rock andesite porphyry. Disseminated and stockwork Cu-Au mineralization is related to potassic alteration, comprising magnetite, late K-feldspar and biotite, and quartz-sericite-specularite overprint, surrounded by extensive barren argillic and propylitic alterations. In the peripheries of the porphyry centers, there are N-trending vuggy quartz veins, hosting epithermal Au-Ag-As-Sb mineralization. Geochemical analyses of drill core samples showed that the core of the porphyry stocks is low-grade, whereas the high-grade disseminated and stockwork mineralization (~ 1% Cu and ~ 1.2 g/t Au) occurred at the contact of the porphyry stocks and andesite porphyry. Geochemical studies of the drill hole and trench samples showed a strong correlation between Cu and Au and both show a second-order correlation with Fe and As. Magnetic survey revealed two significant magnetic anomalies, associated with intensive potassic alteration, in the reduced-to-the-pole magnetic map of the area. A relatively weaker magnetic anomaly, showing no surface porphyry expressions, is located on a lithocap, consisting of advanced argillic alteration, vuggy quartz veins, and surface expressions of epithermal geochemical signatures. The association of the lithocap and the weak magnetic anomaly could be indicative of a hidden mineralized porphyry center. Litho-geochemical analyses of the least altered Dalli intrusions and volcanic rocks indicated high Sr/Y (49-61) and Eu/Eu* (0.89-0.92), features typical of Cu porphyries. The U-Pb dating of zircons of the mineralized quartz diorite and andesite porphyry, carried out by laser ablation inductively coupled plasma mass spectrometry, yielded magmatic crystallization ages of 15.4-16.0 Ma (Middle Miocene). The zircon trace element concentrations of Dalli are characterized by high Eu/Eu* (0.3-0.8), (Ce/Nd)/Y (0.01-0.3), and 10000*(Eu/Eu*)/Y (2-15) ratios, similar to fertile porphyry suites such as the giant Sar-Cheshmeh and Qulong porphyry Cu deposits along the Tethyan belt. This suggests that the Middle Miocene Dalli intrusions are fertile and require extensive deep drillings to define their potential. Chondrite-normalized rare earth element (REE) patterns show no significant Eu anomalies, and are characterized by light-REE enrichments (La/Sm)n = 2.57–6.40). In normalized multi-element diagrams, analyzed rocks are characterized by enrichments in large ion lithophile elements (LILE) and depletions in high field strength elements (HFSE), and display typical features of subduction-related calc-alkaline magmas. The characteristics of the Dalli deposit provided several recognition criteria for detailed exploration of Cu-Au porphyry deposits and highlighted the importance of the UDMA as a potentially significant, economically important, but relatively underexplored porphyry province.

Keywords: porphyry, gold, geochronology, magnetic, exploration

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Authors: Hongmeng Su, Luyu Zhao, Yanyan Qian, Hong Fan

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Aim: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors that endanger human health seriously. RNA methylation, especially N6-methyladenosine (m⁶A) and 5-methylcytosine (m⁵C), a crucial epigenetic transcriptional regulatory mechanism, plays an important role in tumorigenesis, progression and prognosis. This research aims to systematically evaluate the prognostic value of m⁶A and m⁵C modulators in HCC patients. Methods: Twenty-four modulators of m⁶A and m⁵C were candidates to analyze their expression level and their contribution to predict the prognosis of HCC. Consensus clustering analysis was applied to classify HCC patients. Cox and LASSO regression were used to construct the risk model. According to the risk score, HCC patients were divided into high-risk and low/medium-risk groups. The clinical pathology factors of HCC patients were analyzed by univariate and multivariate Cox regression analysis. Results: The HCC patients were classified into 2 clusters with significant differences in overall survival and clinical characteristics. Nine-gene risk model was constructed including METTL3, VIRMA, YTHDF1, YTHDF2, NOP2, NSUN4, NSUN5, DNMT3A and ALYREF. It was indicated that the risk score could serve as an independent prognostic factor for patients with HCC. Conclusion: This study constructed a Nine-gene risk model by modulators of m⁶A and m⁵C and investigated its effect on the clinical prognosis of HCC. This model may provide important consideration for the therapeutic strategy and prognosis evaluation analysis of patients with HCC.

Keywords: hepatocellular carcinoma, m⁶A, m⁵C, prognosis, RNA methylation

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Authors: Karthik Mittal

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This study performs an unsupervised machine learning analysis to find clusters of related SNPs which highlight biological pathways that are important for the biological mechanisms of breast cancer. Studying genetic variations in isolation is illogical because these genetic variations are known to modulate protein production and function; the downstream effects of these modifications on biological outcomes are highly interconnected. After extracting the SNPs and their effect on different types of breast cancer using the MRBase library, two unsupervised machine learning clustering algorithms were implemented on the genetic variants: a k-means clustering algorithm and a hierarchical clustering algorithm; furthermore, principal component analysis was executed to visually represent the data. These algorithms specifically used the SNP’s beta value on the three different types of breast cancer tested in this project (estrogen-receptor positive breast cancer, estrogen-receptor negative breast cancer, and breast cancer in general) to perform this clustering. Two significant genetic pathways validated the clustering produced by this project: the MAPK signaling pathway and the connection between the BRCA2 gene and the ESR1 gene. This study provides the first proof of concept showing the importance of unsupervised machine learning in interpreting GWAS summary statistics.

Keywords: breast cancer, computational biology, unsupervised machine learning, k-means, PCA

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Authors: M. Karthigayan, M. Rizon, Sazali Yaacob, R. Nagarajan, M. Muthukumaran, Thinaharan Ramachandran, Sargunam Thirugnanam

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In this paper, using a set of irregular and regular ellipse fitting equations using Genetic algorithm (GA) are applied to the lip and eye features to classify the human emotions. Two South East Asian (SEA) faces are considered in this work for the emotion classification. There are six emotions and one neutral are considered as the output. Each subject shows unique characteristic of the lip and eye features for various emotions. GA is adopted to optimize irregular ellipse characteristics of the lip and eye features in each emotion. That is, the top portion of lip configuration is a part of one ellipse and the bottom of different ellipse. Two ellipse based fitness equations are proposed for the lip configuration and relevant parameters that define the emotions are listed. The GA method has achieved reasonably successful classification of emotion. In some emotions classification, optimized data values of one emotion are messed or overlapped to other emotion ranges. In order to overcome the overlapping problem between the emotion optimized values and at the same time to improve the classification, a fuzzy clustering method (FCM) of approach has been implemented to offer better classification. The GA-FCM approach offers a reasonably good classification within the ranges of clusters and it had been proven by applying to two SEA subjects and have improved the classification rate.

Keywords: ellipse fitness function, genetic algorithm, emotion recognition, fuzzy clustering

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Authors: Manpreet Kaur, Amita Rani, Sanjay Kumar

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The Internet of Things (IoT), a cyber-physical paradigm, allows a large number of devices to connect and send the sensory data in the network simultaneously. This tremendous amount of data generated leads to very high network load consequently resulting in network congestion. It further amounts to frequent loss of useful information and depletion of significant amount of nodes’ energy. Therefore, there is a need to control congestion in IoT so as to prolong network lifetime and improve the quality of service (QoS). Hence, we propose a two-level clustering based routing algorithm considering congestion score and packet priority metrics that focus on minimizing the network congestion. In the proposed Priority based Congestion Control (PBCC) protocol the sensor nodes in IoT network form clusters that reduces the amount of traffic and the nodes are prioritized to emphasize important data. Simultaneously, a congestion score determines the occurrence of congestion at a particular node. The proposed protocol outperforms the existing Packet Discard Network Clustering (PDNC) protocol in terms of buffer size, packet transmission range, network region and number of nodes, under various simulation scenarios.

Keywords: internet of things, cyber-physical systems, congestion control, priority, transmission rate

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Authors: Anand K. Patel

Abstract:

Background: Patients with COPD have decreased pulmonary functions, which in turn reflect on their day-to-day activities. Objectives: To assess the correlation between functional vital capacity (FVC) and forced expiratory volume in one second (FEV1) with 6 minutes walk test (6MWT). To correlate the Borg rating for perceived exertion scale (Borg scale) and Modified medical research council (MMRC) dyspnea scale with the 6MWT, FVC and FEV1. Method: In this prospective study total 72 patients with COPD diagnosed by the GOLD guidelines were enrolled after taking written consent. They were first asked to rate physical exertion on the Borg scale as well as the modified medical research council dyspnea scale and then were subjected to perform pre and post bronchodilator spirometry followed by 6 minute walk test. The findings were correlated by calculating the Pearson coefficient for each set and obtaining the p-values, with a p < 0.05 being clinically significant. Result: There was a significant correlation between spirometry and 6MWT suggesting that patients with lower measurements were unable to walk for longer distances. However, FVC had the stronger correlation than FEV1. MMRC scale had a stronger correlation with 6MWT as compared to the Borg scale. Conclusion: The study suggests that 6MWT is a better test for monitoring the patients of COPD. In spirometry, FVC should be used in monitoring patients with COPD, instead of FEV1. MMRC scale shows a stronger correlation than the Borg scale, and we should use it more often.

Keywords: spirometry, 6 minute walk test, MMRC, Borg scale

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Authors: Nhleko Monique Chiloane

Abstract:

The gold mining industry has predominantly used ammonium nitrate fuel oil (ANFO) explosives for decades, although these are known to be “gassier” and their detonation results in toxic fumes, for example, carbon monoxide (CO), nitrogen oxides (NOx) and ammonia. Re-entry into underground workings too soon after blasting can lead to fatal exposure to toxic fumes. It is, therefore, required that the polluted air be removed from the affected areas within a reasonable period before employees' re-entry into the working area. Post-blast re-entry times have therefore been described as a productivity bottleneck. The known causes of post-blast fumes are water ingress, incorrect fuel to oxygen ratio, confinement, explosive additives etc. To prevent or minimize post-blast fumes, some researchers have used neutralization, re-burning technique and non-explosive products or different oxidizing agents. The use of commercial explosives without nitrate oxidizing agents can also minimize the production of blasting fumes and thereby reduce the time needed for the clearance of these fumes to allow workers to re-enter the underground workings safely. The reduction in non-production time directly contributes to an increase in the available time per shift for productive work, thus leading to continuous mining. However, owing to its low cost and ease of use, ANFO is still widely used in South African underground blasting operations.

Keywords: post-blast fumes, continuous mining, ammonium nitrate explosive, non-explosive blasting, re-entry period

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Authors: Pejman Hosseinioun, Hasan Shakeri, Ghasem Ghorbanirostam

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In recent years, we have seen an increasing importance of research and study on knowledge source, decision support systems, data mining and procedure of knowledge discovery in data bases and it is considered that each of these aspects affects the others. In this article, we have merged information source and knowledge source to suggest a knowledge based system within limits of management based on storing and restoring of knowledge to manage information and improve decision making and resources. In this article, we have used method of data mining and Apriori algorithm in procedure of knowledge discovery one of the problems of Apriori algorithm is that, a user should specify the minimum threshold for supporting the regularity. Imagine that a user wants to apply Apriori algorithm for a database with millions of transactions. Definitely, the user does not have necessary knowledge of all existing transactions in that database, and therefore cannot specify a suitable threshold. Our purpose in this article is to improve Apriori algorithm. To achieve our goal, we tried using fuzzy logic to put data in different clusters before applying the Apriori algorithm for existing data in the database and we also try to suggest the most suitable threshold to the user automatically.

Keywords: decision support system, data mining, knowledge discovery, data discovery, fuzzy logic

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Authors: Seung Oh, Satoshi Okada

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This study is information-intensive research that provides insight from the factual history, social perception, and robust ideas derived from the social conflict in the most progressively thriving district in the world, Times Square. The case study provides the socio-environmental setup since the Inceptive Point of the development, the Great Depression, the history archives, and evaluation based on the master-level journals as standard. The Great Depression invited macro-sized changes, including financial systems, to raise fluidity by gutting off the debt limit by the gold value, organizing the labor, and social problems in the major cities. The locality of Times Square was implemented by the socio-political changes, overturning ownerships of properties, including theaters, delocalizing tourism, and re-entering the labors with organizations through infrastructure projects and civil activities for minorities and preservations amid the progressive developments over time. Naturally, chasing the media for factual research before and after Inceptive Points. Times Square is understood not just the ‘tower with subway’ progression but also social conflicts raised for adjustment for civil rights, preservations, and progression to deliver the environmental background to trigger the 42nd Street Development (42DP) in the 1990s.

Keywords: development, district, progressive, preservation, social conflict, value chasing

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Authors: H. Abu-Ali, A. Nabok, T. Smith

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Aptamers are single-strand of DNA or RNA nucleotides sequence which is designed in vitro using selection process known as SELEX (systematic evolution of ligands by exponential enrichment) were developed for the selective detection of many toxic materials. In this work, we have developed an electrochemical biosensor for highly selective and sensitive detection of Hg2+ and Pb2+ using a specific aptamer probe (SAP) labelled with ferrocene (or methylene blue) in (5′) end and the thiol group at its (3′) termini, respectively. The SAP has a specific coil structure that matching with G-G for Pb2+ and T-T for Hg2+ interaction binding nucleotides ions, respectively. Aptamers were immobilized onto surface of screen-printed gold electrodes via SH groups; then the cyclic voltammograms were recorded in binding buffer with the addition of the above metal salts in different concentrations. The resulted values of anode current increase upon binding heavy metal ions to aptamers and analyte due to the presence of electrochemically active probe, i.e. ferrocene or methylene blue group. The correlation between the anodic current values and the concentrations of Hg2+ and Pb2+ ions has been established in this work. To the best of our knowledge, this is the first example of using a specific DNA aptamers for electrochemical detection of heavy metals. Each increase in concentration of 0.1 μM results in an increase in the anode current value by simple DC electrochemical test i.e (Cyclic Voltammetry), thus providing an easy way of determining Hg2+ and Pb2+concentration.

Keywords: aptamer, based, biosensor, DNA, electrochemical, highly, specific

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Authors: Vladyslav Povoroznyuk, Oksana Ivanyk, Nataliia Dzerovych

Abstract:

In the diagnostics of osteoporosis, the gold standard is considered to be bone mineral density; however, X-ray densitometry is not an accurate indicator of osteoporotic fracture risk under all circumstances. In this regard, the search for new methods that could determine the indicators not only of the mineral density, but of the bone tissue quality, is a logical step for diagnostic optimization. One of these methods is the evaluation of trabecular bone quality. The aim of this study was to examine the quality and mineral density of spine bone tissue, femoral neck, and body composition of women depending on the duration of the postmenopausal period, to determine the correlation of body fat with indicators of bone mineral density and quality. The study examined 179 women in premenopausal and postmenopausal periods. The patients were divided into the following groups: Women in the premenopausal period and women in the postmenopausal period at various stages (early, middle, late postmenopause). A general examination and study of the above parameters were conducted with General Electric X-ray densitometer. The results show that bone quality and mineral density probably deteriorate with advancing of postmenopausal period. Total fat and lean mass ratio is not likely to change with age. In the middle and late postmenopausal periods, the bone tissue mineral density of the spine and femoral neck increases along with total fat mass.

Keywords: osteoporosis, bone tissue mineral density, bone quality, fat mass, lean mass, postmenopausal osteoporosis

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