Search results for: Squared Error (SE) loss function

Authors: Ahmed Shaboub, Yusuf Jasim Althawadi, Shadi Alaa Abdelaal, Mohamed Hussein Abdalla, Hatem Amr Elzahaby, Mohamed Mohamed, Hazem S. Ghaith, Ahmed Negida

Abstract:

Objectives: We aimed to compare the safety and outcomes of the minimally invasive approaches versus conventional sternotomy procedures for aortic valve replacement. Methods: We conducted a PRISMA-compliant systematic review and meta-analysis. We ran an electronic search of PubMed, Cochrane CENTRAL, Scopus, and Web of Science to identify the relevant published studies. Data were extracted and pooled as standardized mean difference (SMD) or risk ratio (RR) using StataMP version 17 for macOS. Results: Forty-one studies with a total of 15,065 patients were included in this meta-analysis (minimally invasive approaches n=7231 vs. conventional sternotomy n=7834). The pooled effect size showed that minimally invasive approaches had lower mortality rate (RR 0.76, 95%CI [0.59 to 0.99]), intensive care unit and hospital stays (SMD -0.16 and -0.31, respectively), ventilation time (SMD -0.26, 95%CI [-0.38 to -0.15]), 24-h chest tube drainage (SMD -1.03, 95%CI [-1.53 to -0.53]), RBCs transfusion (RR 0.81, 95%CI [0.70 to 0.93]), wound infection (RR 0.66, 95%CI [0.47 to 0.92]) and acute renal failure (RR 0.65, 95%CI [0.46 to 0.93]). However, minimally invasive approaches had longer operative time, cross-clamp, and bypass times (SMD 0.47, 95%CI [0.22 to 0.72], SMD 0.27, 95%CI [0.07 to 0.48], and SMD 0.37, 95%CI [0.20 to 0.45], respectively). There were no differences between the two groups in blood loss, endocarditis, cardiac tamponade, stroke, arrhythmias, pneumonia, pneumothorax, bleeding reoperation, tracheostomy, hemodialysis, or myocardial infarction (all P>0.05). Conclusion: Current evidence showed higher safety and better operative outcomes with minimally invasive aortic valve replacement compared to the conventional approach. Future RCTs with long-term follow-ups are recommended.

Keywords: aortic replacement, minimally invasive, sternotomy, mini-sternotomy, aortic valve, meta analysis

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Authors: Mile Vuković, Lana Jerkić Rajić

Abstract:

Introduction: Broca's aphasia is a non-fluent type of aphasic syndrome, which is primarily manifested by impairment of language production. In connected speech, patients with this type of aphasia produce short sentences in which they often omit function words and morphemes or choose inadequate forms. Aim: This research was conducted to examine the morphosyntactic abilities of people with Broca's aphasia, comparing them with neurologically healthy subjects without a language disorder. Method: The sample included 15 patients with Broca's post-stroke aphasia, who had the relatively intact ability of auditory comprehension. The diagnosis of aphasia was based on the Boston Diagnostic Aphasia Examination. The control group comprised 16 neurologically healthy subjects without data on the presence of disorders in speech and language development. The patients' mother tongue was Serbian. The new Serbian Morphosyntactic Abilities Test (SMAT) was used. Descriptive (frequency, percentage, mean, SD, min, max) and inferential (Mann-Whitney U-test) statistics were used in data processing. Results: We noticed statistically significant differences between people with Broca's aphasia and neurotypical subjects on the SMAT (U = 1.500, z = -4.982, p = 0.000). The results showed that people with Broca's aphasia had achieved low scores on the SMAT, regardless of age (ρ = -0.045, p = 0.873) and time post onset (ρ = 0.330, p = 0.229). Conclusion: Preliminary results show that the SMAT has the potential to detect morphosyntactic deficits in Serbian speakers with Broca's aphasia.

Keywords: Broca’s aphasia, morphosyntactic abilities, agrammatism, Serbian language

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Authors: L. Kloetzer, M. Poştaru, A. I. Galaction, D. Caşcaval

Abstract:

Gentamicin is an aminoglycoside antibiotic industrially obtained by biosynthesis of Micromonospora purpurea or echinospora, the product being a complex mixture of components with very similar structures. Among them, three exhibit the most important biological activity: gentamicins C1, C1a, C2, and C2a. The separation of gentamicin from the fermentation broths at industrial scale is rather difficult and it does not allow the fractionation of the complex mixture of gentamicins in order to increase the therapeutic activity of the product. The aim of our experiments is to analyze the possibility to selectively separate the less active gentamicin, namely gentamicin C1, from the biosynthetic mixture by reactive extraction with di-(2-ethylhexyl) phosphoric acid (D2EHPA) dissolved in dichloromethane, followed selective re-extraction of the most active gentamicins C1a, C2, and C2a. The experiments on the reactive extraction of gentamicins indicated the possibility to separate selectively the gentamicin C1 from the mixture obtained by biosynthesis. The extraction selectivity is positively influenced by increasing the pH-value of an aqueous solution and by using a D2EHPA concentration in organic phase closer to the value needed for an equimolecular ratio between the extractant and this gentamicin. For quantifying the selectivity of separation, the selectivity factor, calculated as the ratio between the degree of reactive extraction of gentamicin C1 and the overall extraction degree of gentamicins were used. The possibility to remove the gentamicin C1 at an extractant concentration of 10 g l-1 and pH = 8 is presented. In these conditions, it was obtained the maximum value of the selectivity factor of 2.14, which corresponds to the modification of the gentamicin C1 concentration from 31.92% in the biosynthetic mixture to 72% in the extract. The re-extraction of gentamicins C1, C1a, C2, and C2a with sulfuric acid from the extract previously obtained by reactive extraction (mixture A – extract obtained by non-selective reactive extraction; mixture B – extract obtained by selective reactive extraction) allows for separating selectively the most active gentamicins C1a, C2, and C2a. For recovering only the active gentamicins C1a, C2, and C2a, the re-extraction must be carried out at very low acid concentrations, far below those corresponding to the stoichiometry of its chemical reactions with these gentamicins. Therefore, the mixture resulted by re-extraction contained 92.6% gentamicins C1a, C2, and C2a. By bringing together the aqueous solutions obtained by reactive extraction and re-extraction, the overall content of the active gentamicins in the final product becomes 89%, their loss reaching 0.3% related to the initial biosynthetic product.

Keywords: di-(2-ethylhexyl) phosphoric acid, gentamicin, reactive extraction, selectivity factor

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Authors: Serdal Pamuk, Irem Cay

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Our model is based on the theory of reinforced random walks coupled with Michealis-Menten mechanisms which view endothelial cell receptors as the catalysts for transforming both tumor and macrophage derived tumor angiogenesis factor (TAF) into proteolytic enzyme which in turn degrade the basal lamina. The model consists of two main parts. First part has seven differential equations (DE’s) in one space dimension over the capillary, whereas the second part has the same number of DE’s in two space dimensions in the extra cellular matrix (ECM). We connect these two parts via some boundary conditions to move the cells into the ECM in order to initiate capillary formation. But, when does this movement begin? To address this question we estimate the thresholds that activate the transport equations in the capillary. We do this by using steady-state analysis of TAF equation under some assumptions. Once these equations are activated endothelial, pericyte and macrophage cells begin to move into the ECM for the initiation of angiogenesis. We do believe that our results play an important role for the mechanisms of cell migration which are crucial for tumor angiogenesis. Furthermore, we estimate the long time tendency of these three cells, and find that they tend to the transition probability functions as time evolves. We provide our numerical solutions which are in good agreement with our theoretical results.

Keywords: angiogenesis, capillary formation, mathematical analysis, steady-state, transition probability function

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Authors: Kwan Hee Han

Abstract:

In today’s business environments, frequent change of customer requirements is a tough challenge to manufacturing company. To cope with these challenges, a production planning and scheduling (PP&S) function might be established to provide accountability for both customer service and operational efficiency. Nowadays, many manufacturing firms have utilized PP&S software solutions to generate a realistic production plan and schedule to adapt to external changes efficiently. However, companies which consider the introduction of PP&S software solution, still have difficulties for selecting adequate solution to meet their specific needs. Since the task of PP&S is the one of major building blocks of SCM (Supply Chain Management) architecture, which deals with short term decision making in the production process of SCM, it is needed that the functionalities of PP&S should be analysed within the whole SCM process. The aim of this paper is to analyse the PP&S functionalities and its system architecture from the SCM perspective by using the criteria of level of planning hierarchy, major 4 SCM processes and problem-solving approaches, and finally propose a classification framework of PP&S solutions to facilitate the comparison among various commercial software solutions. By using proposed framework, several major PP&S solutions are classified and positioned according to their functional characteristics in this paper. By using this framework, practitioners who consider the introduction of computerized PP&S solutions in manufacturing firms can prepare evaluation and benchmarking sheets for selecting the most suitable solution with ease and in less time.

Keywords: production planning, production scheduling, supply chain management, the advanced planning system

Procedia PDF Downloads 185

Authors: Hao Qu, Xiang Liu, Michael Crosby, Brian Kozak, Andreas K. Freund

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The outstanding performance of highly oriented pyrolytic graphite (HOPG) as an optical element for neutron beam conditioning is unequaled by any other crystalline material in the applications of monochromator, analyzer, and filter. This superiority stems from the favorable nuclear properties of carbon (small absorption and incoherent scattering cross-sections, big coherent scattering length) and the specific crystalline structure (small thermal diffuse scattering cross-section, layered crystal structure). The real crystal defect structure revealed by imaging techniques is correlated with the parameters used in the mosaic model (mosaic spread, mosaic block size, uniformity). The diffraction properties (rocking curve width as determined by both the intrinsic mosaic spread and the diffraction process, peak and integrated reflectivity, filter transmission) as a function of neutron wavelength or energy can be predicted with high accuracy and reliability by diffraction theory using empirical primary extinction coefficients extracted from a great amount of existing experimental data. The results of these calculations are given as graphs and tables permitting to optimize HOPG characteristics (mosaic spread, thickness, curvature) for any given experimental situation.

Keywords: neutron optics, pyrolytic graphite, mosaic spread, neutron scattering, monochromator, analyzer

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Authors: Tejaswi Agarwal, Amritansh Agarwal

Abstract:

Forest ecosystem plays very important role in the global carbon cycle. It stores about 80% of all above ground and 40% of all below ground terrestrial organic carbon. There is much interest in the extent of tropical forests and their rates of deforestation for two reasons: greenhouse gas contributions and the impact of profoundly negative biodiversity. Deforestation has many ecological, social and economic consequences, one of which is the loss of biological diversity. The rapid deployment of remote sensing (RS) satellites and development of RS analysis techniques in the past three decades have provided a reliable, effective, and practical way to characterize terrestrial ecosystem properties. Global estimates of tropical deforestation vary widely and range from 50,000 to 170,000km2 /yr Recent FAO tropical deforestation estimates for 1990–1995 cite 116,756km2 / yr globally. Remote Sensing can prove to be a very useful tool in monitoring of forests and associated deforestation to a sufficient level of accuracy without the need of physically surveying the forest areas as many of them are physically inaccessible. The methodology for the assessment of forest cover using digital image processing (ERDAS) has been followed. The satellite data for the study was procured from Indian institute of remote Sensing (IIRS), Dehradoon in the digital format. While procuring the satellite data, care was taken to ensure that the data was cloud free and did not belong to dry and leafless season. The Normalized Difference Vegetation Index (NDVI) has been used as a numerical indicator of the reduction in ground biomass. NDVI = (near I.R - Red)/ (near I.R + Red). After calculating the NDVI variations and associated mean, we have analysed the change in ground biomass. Through this paper, we have tried to indicate the rate of deforestation over a given period of time by comparing the forest cover at different time intervals. With the help of remote sensing and GIS techniques, it is clearly shown that the total forest cover is continuously degrading and transforming into various land use/land cover category.

Keywords: remote sensing, deforestation, supervised classification, NDVI, change detection

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Authors: Shohei Maruyama, Yasuo Matsuyama, Sachiyo Aburatani

Abstract:

The development of the method to annotate unknown gene functions is an important task in bioinformatics. One of the approaches for the annotation is The identification of the metabolic pathway that genes are involved in. Gene expression data have been utilized for the identification, since gene expression data reflect various intracellular phenomena. However, it has been difficult to estimate the gene function with high accuracy. It is considered that the low accuracy of the estimation is caused by the difficulty of accurately measuring a gene expression. Even though they are measured under the same condition, the gene expressions will vary usually. In this study, we proposed a feature extraction method focusing on the variability of gene expressions to estimate the genes' metabolic pathway accurately. First, we estimated the distribution of each gene expression from replicate data. Next, we calculated the similarity between all gene pairs by KL divergence, which is a method for calculating the similarity between distributions. Finally, we utilized the similarity vectors as feature vectors and trained the multiclass SVM for identifying the genes' metabolic pathway. To evaluate our developed method, we applied the method to budding yeast and trained the multiclass SVM for identifying the seven metabolic pathways. As a result, the accuracy that calculated by our developed method was higher than the one that calculated from the raw gene expression data. Thus, our developed method combined with KL divergence is useful for identifying the genes' metabolic pathway.

Keywords: metabolic pathways, gene expression data, microarray, Kullback–Leibler divergence, KL divergence, support vector machines, SVM, machine learning

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Authors: Marco Sewald

Abstract:

Comparing present to past the numbers of Americans expatriating U. S. citizenship have risen. Even though these numbers are small compared to the immigrants, U. S. citizens expatriations have historically been much lower, making the uptick worrisome. In addition, the published lists and numbers from the U.S. government seems incomplete, with many not counted. Different branches of the U. S. government report different numbers and no one seems to know exactly how big the real number is, even though the IRS and the FBI both track and/or publish numbers of Americans who renounce. Since there is no single explanation, anecdotal evidence suggests this uptick is caused by global tax law and increased compliance burdens imposed by the U.S. lawmakers on U.S. citizens abroad. Within a research project the question arose about the reasons why a constant growing number of U.S. citizens are expatriating – the answers are believed helping to explain the underlying governmental policy rational, leading to such activities. While it is impossible to locate former U.S. citizens to conduct a survey on the reasons and the U.S. government is not commenting on the reasons given within the process of expatriation, the chosen methodology is Structural Equation Modeling (SEM), in the first step by re-using current surveys conducted by different researchers within the population of U. S. citizens residing abroad during the last years. Surveys questioning the personal situation in the context of tax, compliance, citizenship and likelihood to repatriate to the U. S. In general SEM allows: (1) Representing, estimating and validating a theoretical model with linear (unidirectional or not) relationships. (2) Modeling causal relationships between multiple predictors (exogenous) and multiple dependent variables (endogenous). (3) Including unobservable latent variables. (4) Modeling measurement error: the degree to which observable variables describe latent variables. Moreover SEM seems very appealing since the results can be represented either by matrix equations or graphically. Results: the observed variables (items) of the construct are caused by various latent variables. The given surveys delivered a high correlation and it is therefore impossible to identify the distinct effect of each indicator on the latent variable – which was one desired result. Since every SEM comprises two parts: (1) measurement model (outer model) and (2) structural model (inner model), it seems necessary to extend the given data by conducting additional research and surveys to validate the outer model to gain the desired results.

Keywords: expatriation of U. S. citizens, SEM, structural equation modeling, validating

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Authors: Khadija Amin

Abstract:

The significant contribution of foreign investment in promoting economic recovery, especially in countries recovering from conflict, is generally recognized. This study examines the influence of foreign investment on the economic development of countries that have had long-lasting internal conflicts. The study examines the complex correlation between foreign investment and economic progress using the production function framework based on endogenous growth theory. In addition to foreign investment, the research considers a range of factors that affect economic growth, such as trade dynamics, the spread of information, attempts to promote peace, changes in the labor market, and the accumulation of domestic capital. The study challenges common beliefs by revealing a statistically negligible negative association between GDP growth and foreign investment (FI) inflows in post-war economies. The existing literature highlights the positive impact of trade and foreign investment on economic growth. However, this study emphasizes that these impacts are complex and depend on various contextual factors such as trade policies, infrastructure development, domestic investment levels, human capital development, and macroeconomic stability. The results emphasize the crucial significance of foreign investment in stimulating development while also drawing attention to the intricacies of precisely assessing its economic consequences. Measuring the economic impact of foreign investment is a difficult task that requires detailed analysis considering many contextual elements and changing socioeconomic conditions.

Keywords: economic grouths, foreign investment, trade policies, domestic investment

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Authors: Maaike Maria Augustina Hommes

Abstract:

This paper reviews the emergence of the recently approved lust enhancing pill for women (sold under the brand name of Addyi) and its status as ‘medicine’ from a cultural studies perspective to understand the way in which the usage of the pill can be seen as a medicalization of sexual desire. It asks where this medicalization can be localized to understand the current placement of and notions on female sexuality. Via a close reading of a woman’s narration of her usage of the pill that appeared in Shape Magazine, this paper critically reviews the pill’s relation to the concept of ‘cure’ and assesses the way this Pink Pill functions as a cure to the DSM-IV based disorder called Hypoactive Sexual Desire Disorder. As such it finds that in the diagnosis with HSDD meant a huge relief. Now this woman was not just ‘bad at life and bad at marriage’ but ‘just had this health issue’. In order to get to an understanding of the different structures that conjoin in this expression of relief this paper reviews the emergence of the sexual desire disorder within psychology and the way that the loss of desire becomes localized in the brain. This localization will be related to two ways of looking at the human body; the medical gaze as described by Michel Foucault, and the neuromolecular gaze, as introduced by Nikolas Rose and Joelle M.Abi-Rached. Both these penetrating gazes bring about a certain reductionism in which the human body is either viewed as an objectified ‘sick body’ or as a set of chemical reactions. By referring to these modes of looking as reductionist one assumes that something is lost, or forgotten in the act of reducing. It is both what is gained in the formulation of the disorder, as what is lost in reduction of the disorder in medical knowledge that is at the central inquiry of this paper. As such, this paper brings forward the way in which medicine and cultural narrative are deeply intertwined. It is this way in which different forces of subject formation come together that is addressed via an interdisciplinary and object-centered focus on the pink pill.

Keywords: disorder and cure, female sexual desire, medical gaze, neuromolecular gaze

Procedia PDF Downloads 261

Authors: Nadia A. Mohamed, Mehrevan M. Abdel-Moniem

Abstract:

Zingiber officinale (ginger) has been cultivated for medicinal purposes due to their various proprieties both in vitro and in vivo, so we designed to evaluate the ginger’s potential effect on nephrin m RNA expression in cisplatin-induced nephrotoxic rats. Method: Forty male albino rats were divided into group I was injected (IP) with one ml saline, group II(cisplatin) injected (IP) with a single dose of 12 mg/kg cisplatin, group III (ginger) received (PO) 310 mg/kg for 30 successive days, and group IV(cisplatin and ginger) rats received ginger extract (310 mg/kg) daily for 20 successive days (PO), and then on day 20 of ginger extract administration each rat was injected(IP) with a single dose of 12 mg/kg cisplatin. The blood was sampled to assess urea, creatinine (SC), while the levels of malondialdehyde (MDA), nitric oxide (NO) and paraoxonase (PON1) were measured in kidney tissue homogenate. Expression of urinary nephrin gene (nephrin mRNA) was detected using qRT-PCR. Results: Treatment with ginger significantly decreased the levels of kidney function parameters as well as MDA and NO elevated by cisplatin injection, while PON1 was significantly reduced in the cisplatin group. However, the protection of male rats with ginger significantly increased the levels of nephrin gene expression and PON1 compared with the cisplatin-treated group. Our results generated a proposal on the ameliorating effect of ginger on nephrin mRNA gene expression reduction in cisplatin-induced nephrotoxicity.

Keywords: nephrin mRNA, ginger, cisplatin, nephrotoxicity

Procedia PDF Downloads 133

Authors: Amritansh Agarwal, Tejaswi Agarwal

Abstract:

Forest ecosystem plays very important role in the global carbon cycle. It stores about 80% of all above ground and 40% of all below ground terrestrial organic carbon. There is much interest in the extent of tropical forests and their rates of deforestation for two reasons: greenhouse gas contributions and the impact of profoundly negative biodiversity. Deforestation has many ecological, social and economic consequences, one of which is the loss of biological diversity. The rapid deployment of remote sensing (RS) satellites and development of RS analysis techniques in the past three decades have provided a reliable, effective, and practical way to characterize terrestrial ecosystem properties. Global estimates of tropical deforestation vary widely and range from 50,000 to 170,000 km2 /yr Recent FAO tropical deforestation estimates for 1990–1995 cite 116,756km2 / yr globally. Remote Sensing can prove to be a very useful tool in monitoring of forests and associated deforestation to a sufficient level of accuracy without the need of physically surveying the forest areas as many of them are physically inaccessible. The methodology for the assessment of forest cover using digital image processing (ERDAS) has been followed. The satellite data for the study was procured from USGS website in the digital format. While procuring the satellite data, care was taken to ensure that the data was cloud and aerosol free by making using of FLAASH atmospheric correction technique. The Normalized Difference Vegetation Index (NDVI) has been used as a numerical indicator of the reduction in ground biomass. NDVI = (near I.R - Red)/ (near I.R + Red). After calculating the NDVI variations and associated mean we have analysed the change in ground biomass. Through this paper we have tried to indicate the rate of deforestation over a given period of time by comparing the forest cover at different time intervals. With the help of remote sensing and GIS techniques it is clearly shows that the total forest cover is continuously degrading and transforming into various land use/land cover category.

Keywords: remote sensing, deforestation, supervised classification, NDVI change detection

Procedia PDF Downloads 380

Authors: A. Nawaz

Abstract:

The present study uses Halliday’s transitivity model to analyze and interpret ideological stance in PM Nawaz Sharif’s political discourse. His famous speech at the 71st UN assembly was analyzed qualitatively using clausal analysis approach to investigate the communicative functions of the linguistic choices made in the address. The study discovers that among the six process types under the transitivity model, material, relational and mental processes appear most frequently in the speech, making up almost 86% of the whole. Verbal processes rank 4th, whereas existential and behavioral are the least occurring processes covering only 2 and 1 percent respectively. The dominant use of material processes suggests that Nawaz Sharif and his government are the main actors working on several concrete projects to produce a sense of developmental progression and continuity. Using relational and mental processes the PM, along with establishing proximity with masses and especially Kashmiri, gives guarantees and promises. The linguistic analysis concludes Kashmir dispute as being the central theme of the address, since it covers more than half of the discourse. The address calls for a strong action instead of formal assurances and wishful thoughts. The study establishes that language structures can yield certain connotations and ideologies which are not overt for readers. This is in affirmation to the supposition that language form performs a communicative function and is not merely fortuitous.

Keywords: Hallidian perspective on language, implicit meanings, Nawaz Sharif, political ideologies, political speeches, transitivity, UN Assembly

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Authors: Iftikhar Hussain Gul, Syeda Aatika

Abstract:

Nickel ferrite was prepared via wet chemical co-precipitation route. Carbon Nano Fibers (CNFs) were used to prepare NiFe₂O₄/CNFs nanohybrids. Polar solvent (ortho-xylene) was used for the dispersion of CNFs in ferrite matrix. X-ray diffraction patterns confirmed the formation of NiFe₂O₄/CNFs nanohybrids without any impurity peak. FTIR patterns showed two consistent characteristic absorption bands for tetrahedral and octahedral sites, confirming the formation of spinel structure of NiFe₂O₄. Scanning Electron Microscopy (SEM) images confirmed the coating of nickel ferrite nanoparticles on CNFs, which confirms the efficiency of deployed method. The dielectric properties were measured as a function of frequency at room temperature. Pure NiFe₂O₄ showed dielectric constant of 1.79 ×10³ at 100 Hz, which increased massively to 2.92 ×10⁶ at 100 Hz with the addition of 20% by weight of CNFs, proving it to be potential candidate for applications in supercapacitors. The impedance analysis showed a considerable decrease of resistance, reactance and cole-cole plot which confirms the decline of impedance on addition of CNFs. The pure NiFe₂O₄ has highest impedance values of 5.89 ×10⁷ Ohm at 100 Hz while the NiFe₂O₄/CNFs nanohybrid with CNFs (20% by weight) has the lowest impedance values of 4.25×10³ Ohm at 100 Hz, which proves this nanohybrid is useful for high-frequency applications.

Keywords: AC impedance, co-precipitation, nanohybrid, Fourier transform infrared spectroscopy, x-ray diffraction

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Authors: Ngoc Trung Ngo, Buddhima Indraratna, Cholachat Rujikiathmakjornr

Abstract:

For several hundred years, the design of railway tracks has practically remained unchanged. Traditionally, rail tracks are placed on a ballast layer due to several reasons, including economy, rapid drainage, and high load bearing capacity. The primary function of ballast is to distributing dynamic track loads to sub-ballast and subgrade layers, while also providing lateral resistance and allowing for rapid drainage. Upon repeated trainloads, the ballast becomes fouled due to ballast degradation and the intrusion of fines which adversely affects the strength and deformation behaviour of ballast. This paper presents the use of three-dimensional discrete element method (DEM) in studying the shear behaviour of the fouled ballast subjected to direct shear loading. Irregularly shaped particles of ballast were modelled by grouping many spherical balls together in appropriate sizes to simulate representative ballast aggregates. Fouled ballast was modelled by injecting a specified number of miniature spherical particles into the void spaces. The DEM simulation highlights that the peak shear stress of the ballast assembly decreases and the dilation of fouled ballast increases with an increase level of fouling. Additionally, the distributions of contact force chain and particle displacement vectors were captured during shearing progress, explaining the formation of shear band and the evolutions of volumetric change of fouled ballast.

Keywords: railway ballast, coal fouling, discrete element modelling, discrete element method

Procedia PDF Downloads 435

Authors: Tanya Keni

Abstract:

Efforts to link culture and self, have been the focus, initially of Anthropology and later of Psychology in the first half of the 20th century. In doing so, cross-cultural researchers have endeavored to identify factors valuable for classifying cultures. One such central classification is that of individualism and collectivism which remains prominent. However, it overlooks certain other cultural dimensions that can be of interest and need attention. The current paper tries to move beyond this classic distinction, to cultures that are termed to be honor and dignity oriented. Both honor and dignity, refer to the worth of a person but bear different connotations and psychological consequences. While dignity is an independent concept of self-worth whose locus lies deep within the individual, honor is an interdependent concept that needs both personal as well as societal acknowledgment. This research takes an exploratory and qualitative approach to draw the individual, structural and contextual understanding of personal honor and dignity in broad cultures that are conceptualized as honor and dignity aimed. The aim is to understand the cultural influence on an individual’s self-worth, considering gender. 12 Focus group discussions were conducted across North India and Germany with four participants each. The research process was inspired by the approaches of social constructivism and critical realism. These discussions were transcribed and further analyzed using thematic analysis and the results have revealed differential themes for the concepts of honor and dignity. Certain dimensional similarities were also observed for both the cultural groups, however with differential usage of language. In particular, the North Indian group was seen using phrases that were oriented towards safeguarding against loss of honor or dignity. While the phrases of the German group were aligned towards worth-enhancement. The research also gives an illustration of how honor and dignity translate into behavioral practice that can exert an influence on important life decisions, especially about self and family for both males and females. In addition to these, the study also contributes to the literature on self-worth by developing the concept of ‘dignity’ for which there exists a dearth of research.

Keywords: culture, dignity, honor, self, self-worth

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Authors: Sally Kafelghazal

Abstract:

Introduction: Arab Americans, who include immigrants, refugees, or U.S. born persons of Middle Eastern or North African descent, may experience significant difficulties during acculturation to Western society. Influential stressors include relocation, loss of social support, language barriers, and economic factors, all of which can impact mental health. There is limited research investigating the effects of acculturation on the mental health of the Arab American population. Objectives: The purpose of this study is to identify ways in which acculturation impacts the mental health of Arab Americans, specifically the development of depression and anxiety. Method: A literature search was conducted using PubMed and PsycArticles (ProQuest), utilizing the following search terms: “Arab Americans,” “Arabs,” “mental health,” “depression,” “anxiety,” “acculturation.” Thirty-nine articles were identified and of those, nine specifically investigated the relationship between acculturation and mental health in Arab Americans. Three of the nine focused exclusively on depression. Results: Several risk factors were identified that contribute to poor mental health associated with acculturation, which include immigrant or refugee status, facing discrimination, and religious ideology. Protective factors include greater levels of acculturation, being U.S. born, and greater heritage identity. Greater mental health disorders were identified in Arab Americans compared to normative samples, perhaps particularly depression; none of the articles specifically addressed anxiety. Conclusion: The current research findings support the potential association between the process of acculturation and greater levels of mental health disorders in Arab Americans. However, the diversity of the Arab American population makes it difficult to draw consistent conclusions. Further research needs to be conducted in order to assess which subgroups in the Arab American population are at highest risk for developing new or exacerbating existing mental health disorders in order to devise more effective interventions.

Keywords: arab americans, arabs, mental health, anxiety, depression, acculturation

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Authors: Taoufik Bettaieb, Sihem Soufi

Abstract:

As a bioactive metalloid, silicon (Si) is an essential element for plant growth and development. It also plays a crucial role in enhancing plants’ resilience to different abiotic and biotic stresses. The morpho-physiological, biochemical, and molecular background of Si-mediated stress tolerance in plants were unraveled. Cold stress is a severe abiotic stress response to the decrease of plant growth and yield by affecting various physiological activities in plants. Several approaches have been used to alleviate the adverse effects generated from cold stress exposure, but the cost-effective, environmentally friendly, and defensible approach is the supply of silicon. Silicon has the ability to neutralize the harmful impacts of cold stress. Therefore, based on these hypotheses, this study was designed in order to investigate the morphological and physiological background of silicon effects applied at different concentrations on cold stress mitigation during early growth of a turfgrass, namely Paspalum vaginatum Sw. Results show that silicon applied at different concentrations improved the morphological development of Paspalum subjected to cold stress. It is also effective on the photosynthetic apparatus by maintaining stability the photochemical efficiency. As the primary component of cellular membranes, lipids play a critical function in maintaining the structural integrity of plant cells. Silicon application decreased membrane lipid peroxidation and kept on membrane frontline barrier relatively stable under cold stress.

Keywords: crops, cold stress, silicon, abiotic stress

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Authors: Arjun Chatterjee

Abstract:

The India-China border clash in Galwan valley in June 2020, the first deadly skirmish between the two Asian giants in the Himalayan border area in over four decades, highlighted the need to examine the notion of ‘authenticity’ in journalistic practices. Information emanating from such remotely located, sparsely populated, and not well-demarcated international land borders have limited sources, restricted to official sources, which have their own narrative. Geopolitical goals and ambitions embolden narratives of nationalism in the media, and these often challenge the notion and understanding of authenticity in journalism. The Indian press, contrary to the Chinese press, which is state-owned, is diverse and also confrontational, where narratives of nationalism are differentially interpreted, embedded, and realised. This paper examines how authenticity has become a variable, rather than a constant, in conflict reporting of the Sino-Indian border clash and how authenticity is interpreted similarly or differently in conflict journalism. The paper reports qualitative textual analysis of two leading English language newspapers – The Times of India and The Hindu, and two mainstream regional language newspapers, Amar Ujala (Hindi) and Ananda Bazar Patrika (Bengali), to evaluate the ways in which representations of information function in conflict reporting and to recontextualize (and thus change or modify the meaning of) that which they represent, and with what political and cultural implications.

Keywords: India-China, framing, conflict, media narratives, border dispute

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Authors: Dmytro Zubov, Francesco Volponi

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In this paper, D-Wave quantum computing Ising model is used for the forecasting of positive extremes of daily mean air temperature. Forecast models are designed with two to five qubits, which represent 2-, 3-, 4-, and 5-day historical data respectively. Ising model’s real-valued weights and dimensionless coefficients are calculated using daily mean air temperatures from 119 places around the world, as well as sea level (Aburatsu, Japan). In comparison with current methods, this approach is better suited to predict heat wave values because it does not require the estimation of a probability distribution from scarce observations. Proposed forecast quantum computing algorithm is simulated based on traditional computer architecture and combinatorial optimization of Ising model parameters for the Ronald Reagan Washington National Airport dataset with 1-day lead-time on learning sample (1975-2010 yr). Analysis of the forecast accuracy (ratio of successful predictions to total number of predictions) on the validation sample (2011-2014 yr) shows that Ising model with three qubits has 100 % accuracy, which is quite significant as compared to other methods. However, number of identified heat waves is small (only one out of nineteen in this case). Other models with 2, 4, and 5 qubits have 20 %, 3.8 %, and 3.8 % accuracy respectively. Presented three-qubit forecast model is applied for prediction of heat waves at other five locations: Aurel Vlaicu, Romania – accuracy is 28.6 %; Bratislava, Slovakia – accuracy is 21.7 %; Brussels, Belgium – accuracy is 33.3 %; Sofia, Bulgaria – accuracy is 50 %; Akhisar, Turkey – accuracy is 21.4 %. These predictions are not ideal, but not zeros. They can be used independently or together with other predictions generated by different method(s). The loss of human life, as well as environmental, economic, and material damage, from extreme air temperatures could be reduced if some of heat waves are predicted. Even a small success rate implies a large socio-economic benefit.

Keywords: heat wave, D-wave, forecast, Ising model, quantum computing

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Authors: Esmail Sadipour

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The use of social networks is increasing day by day in all societies. The purpose of this research was to know the relationship between the use of social networks (Instagram, WhatsApp, and Telegram) with executive functions and academic performance in first-year female high school students. This research was applied in terms of purpose, quantitative in terms of data type, and correlational in terms of technique. The population of this research consisted of all female high school students in the first year of district 2 of Tehran. Using Green's formula, the sample size of 150 people was determined and selected by cluster random method. In this way, from all 17 high schools in district 2 of Tehran, 5 high schools were selected by a simple random method and then one class was selected from each high school, and a total of 155 students were selected. To measure the use of social networks, a researcher-made questionnaire was used, the Barclay test (2012) was used for executive functions, and last semester's GPA was used for academic performance. Pearson's correlation coefficient and multivariate regression were used to analyze the data. The results showed that there is a negative relationship between the amount of use of social networks and self-control, self-motivation and time self-management. In other words, the more the use of social networks, the fewer executive functions of students, self-control, self-motivation, and self-management of their time. Also, with the increase in the use of social networks, the academic performance of students has decreased.

Keywords: social networks, executive function, academic performance, working memory

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Authors: Ibrahim Suliman Hanaish

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Disaggregation daily rainfall using stochastic models formulated based on multivariate approach (MuDRain) is discussed in this paper. Seven rain gauge stations are considered in this study for different distances from the referred station starting from 4 km to 160 km in Peninsular Malaysia. The hourly rainfall data used are covered the period from 1973 to 2008 and July and November months are considered as an example of dry and wet periods. The cross-correlation among the rain gauges is considered for the available hourly rainfall information at the neighboring stations or not. This paper discussed the applicability of the MuDRain model for disaggregation daily rainfall to hourly rainfall for both sources of cross-correlation. The goodness of fit of the model was based on the reproduction of fitting statistics like the means, variances, coefficients of skewness, lag zero cross-correlation of coefficients and the lag one auto correlation of coefficients. It is found the correlation coefficients based on extracted correlations that was based on daily are slightly higher than correlations based on available hourly rainfall especially for neighboring stations not more than 28 km. The results showed also the MuDRain model did not reproduce statistics very well. In addition, a bad reproduction of the actual hyetographs comparing to the synthetic hourly rainfall data. Mean while, it is showed a good fit between the distribution function of the historical and synthetic hourly rainfall. These discrepancies are unavoidable because of the lowest cross correlation of hourly rainfall. The overall performance indicated that the MuDRain model would not be appropriate choice for disaggregation daily rainfall.

Keywords: rainfall disaggregation, multivariate disaggregation rainfall model, correlation, stochastic model

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Authors: Sagri Sharma

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Analysis of diseases integrating multi-factors increases the complexity of the problem and therefore, development of frameworks for the analysis of diseases is an issue that is currently a topic of intense research. Due to the inter-dependence of the various parameters, the use of traditional methodologies has not been very effective. Consequently, newer methodologies are being sought to deal with the problem. Supervised Learning Algorithms are commonly used for performing the prediction on previously unseen data. These algorithms are commonly used for applications in fields ranging from image analysis to protein structure and function prediction and they get trained using a known dataset to come up with a predictor model that generates reasonable predictions for the response to new data. Gene expression profiles generated by DNA analysis experiments can be quite complex since these experiments can involve hypotheses involving entire genomes. The application of well-known machine learning algorithm - Support Vector Machine - to analyze the expression levels of thousands of genes simultaneously in a timely, automated and cost effective way is thus used. The objectives to undertake the presented work are development of a methodology to identify genes relevant to Hepatocellular Carcinoma (HCC) from gene expression dataset utilizing supervised learning algorithms and statistical evaluations along with development of a predictive framework that can perform classification tasks on new, unseen data.

Keywords: artificial intelligence, biomarker, gene expression datasets, hepatocellular carcinoma, machine learning, supervised learning algorithms, support vector machine

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Authors: Mohammed Qutishat, Omar Al-Omari, Kholoud Al-Damery, Mohammed Al-Qadiri

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Objective: The current study aims to explore the relationship between Night Eating Syndrome and the experiences of Fear of Missing out (FOMO) among college students in Oman. Methods: The study adopted a descriptive correlational design. The total sample was 366 based on defined inclusion criteria. The questionnaires were distributed over one month during the spring semester of 2020. We used a self-report instrument as a measurement tool to investigate the extents of the research phenomena, and it consists of two major sections: fear of missing out Questionnaires and Night Eating Questionnaire. Results: The respondents' age ranged between 18 and 30. The majority of the participants were female 76.7% (204), single 97.7% (266), in their third academic year 28.6% (76), live in –campus, 57.1% (152). The findings of this study showed that fear of missing out experiences are significantly correlated with age (P=.010), gender (P= .005), and daily sleeping hours (P= .007). However, night eating experiences are significantly associated with age (p=018), living arrangement (P= .017), and sleeping hours (P= .000). Conclusion: This article can define a limiting aspect of the relationship between fear of missing out and night eating behaviors. During academic life, students may find themselves overloaded and use their smartphones to do the simplest tasks they have, leading them to skip their meals frequently and interfere with their eating patterns and psychological function. Health awareness programs or the implementation of healthy eating standards and technology uses can be introduced for undergraduates.

Keywords: fear of missing out, night eating syndrome, smartphone, addiction

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Authors: Ririt Aprilin Sumarsono

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Composite member (concrete and steel) has been widely advanced for structural utilization due to its best performance in resisting load, reducing the total weight of the structure, increasing stiffness, and other available advantages. On the other hand, the environment load such as corrosion (e.g. chloride ingress) creates significant time-dependent degradation for steel. Analysis performed in this paper is mainly considered uniform corrosion for evaluating the composite beam without examining the pit corrosion as the initial corrosion formed. Corrosion level in terms of weight loss is modified in yield stress and modulus elasticity of steel. Those two mechanical properties are utilized in this paper for observing the stresses due to corrosion attacked. As corrosion level increases, the effective width of the composite beam in the concrete section will be wider. The position of a neutral axis of composite section will indicate the composite action due to corrosion of composite beam so that numerous shear connectors provided must be reconsidered. Flexure capacity quantification provides stresses, and shear capacity calculation derives connectors needed in overcoming the shear problem for composite beam under corrosion. A model of simply supported composite beam examined in this paper under uniform corrosion where the stresses as the focus of the evaluation. Principal stress at the first stage of composite construction decline as the corrosion level incline, parallel for the second stage stress analysis where the tension region held by the steel undergoes lower capacity due to corrosion. Total stresses of the composite section for steel to be born significantly decreases particularly in the outermost fiber of tension side. Whereas, the available compression side is smaller as the corrosion level increases so that the stress occurs on the compression side shows reduction as well. As a conclusion, the increment of corrosion level will degrade both compression and tension side of stresses.

Keywords: composite beam, modulus of elasticity, stress analysis, yield strength, uniform corrosion

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Authors: Siu-Siu Guo, Qingxuan Shi

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In this paper, single-degree-of-freedom (SDOF) systems to white noise and colored noise excitations are investigated. By expressing colored noise excitation as a second-order filtered white noise process and introducing colored noise as an additional state variable, the equation of motion for SDOF system under colored noise is then transferred artificially to multi-degree-of-freedom (MDOF) system under white noise excitations. As a consequence, corresponding Fokker-Planck-Kolmogorov (FPK) equation governing the joint probabilistic density function (PDF) of state variables increases to 4-dimension (4-D). Solution procedure and computer programme become much more sophisticated. The exponential-polynomial closure (EPC) method, widely applied for cases of SDOF systems under white noise excitations, is developed and improved for cases of systems under colored noise excitations and for solving the complex 4-D FPK equation. On the other hand, Monte Carlo simulation (MCS) method is performed to test the approximate EPC solutions. Two examples associated with Gaussian and non-Gaussian colored noise excitations are considered. Corresponding band-limited power spectral densities (PSDs) for colored noise excitations are separately given. Numerical studies show that the developed EPC method provides relatively accurate estimates of the stationary probabilistic solutions. Moreover, statistical parameter of mean-up crossing rate (MCR) is taken into account, which is important for reliability and failure analysis.

Keywords: filtered noise, narrow-banded noise, nonlinear dynamic, random vibration

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Authors: Arash Yousefi

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Experts suggest that relying exclusively on parameters to convey a situation or establish a condition may not be adequate. Assessing and appraising incidents in a system based on accident parameters, such as accident frequency, lost workdays, or fatalities, may not always be precise and occasionally erroneous. The frequency rate of accidents is a metric that assesses the correlation between the number of accidents causing work-time loss due to injuries and the total working hours of personnel over a year. Traditionally, this has been calculated based on one million working hours, but the American Occupational Safety and Health Organization has updated its standards. The new coefficient of 200/000 working hours is now used to compute the frequency rate of accidents. It's crucial to ensure that the total working hours of employees are equally represented when calculating individual event and incident numbers. The accident severity rate is a metric used to determine the amount of time lost or wasted during a given period, often a year, in relation to the total number of working hours. It measures the percentage of work hours lost or wasted compared to the total number of useful working hours, which provides valuable insight into the number of days lost or wasted due to work-related incidents for each working hour. Calculating the severity of an incident can be difficult if a worker suffers permanent disability or death. To determine lost days, coefficients specified in the "tables of days equivalent to OSHA or ANSI standards" for disabling injuries are used. The accident frequency coefficient denotes the rate at which accidents occur, while the accident severity coefficient specifies the extent of damage and injury caused by these accidents. These coefficients are crucial in accurately assessing the magnitude and impact of accidents.

Keywords: incidents, safety, analysis, frequency, severity, injuries, determine

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Authors: Sofia M. Karadimitriou, Kostas Triantafyllopoulos, Timothy Heaton

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Reduced dimension Dynamic Spatio-Temporal Models (DSTMs) jointly describe the spatial and temporal evolution of a function observed subject to noise. A basic state space model is adopted for the discrete temporal variation, while a continuous autoregressive structure describes the continuous spatial evolution. Application of such a DSTM relies upon the pre-selection of a suitable reduced set of basic functions and this can present a challenge in practice. In this talk, we propose an online estimation method for high dimensional spatio-temporal data based upon DSTM and we attempt to resolve this issue by allowing the basis to adapt to the observed data. Specifically, we present a wavelet decomposition in order to obtain a parsimonious approximation of the spatial continuous process. This parsimony can be achieved by placing a Laplace prior distribution on the wavelet coefficients. The aim of using the Laplace prior, is to filter wavelet coefficients with low contribution, and thus achieve the dimension reduction with significant computation savings. We then propose a Hierarchical Bayesian State Space model, for the estimation of which we offer an appropriate particle filter algorithm. The proposed methodology is illustrated using real environmental data.

Keywords: multidimensional Laplace prior, particle filtering, spatio-temporal modelling, wavelets

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Authors: Buruk Kitachew Wossenyeleh

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Groundwater is the largest freshwater reservoir in the world. Like the other reservoirs of the hydrologic cycle, it is a finite resource. This study focused on the groundwater modeling of the Ter Kamerenbos well field to understand the groundwater flow system and the impact of different scenarios. The study area covers 68.9Km2 in the Brussels Capital Region and is situated in two river catchments, i.e., Zenne River and Woluwe Stream. The aquifer system has three layers, but in the modeling, they are considered as one layer due to their hydrogeological properties. The catchment aquifer system is replenished by direct recharge from rainfall. The groundwater recharge of the catchment is determined using the spatially distributed water balance model called WetSpass, and it varies annually from zero to 340mm. This groundwater recharge is used as the top boundary condition for the groundwater modeling of the study area. During the groundwater modeling using Processing MODFLOW, constant head boundary conditions are used in the north and south boundaries of the study area. For the east and west boundaries of the study area, head-dependent flow boundary conditions are used. The groundwater model is calibrated manually and automatically using observed hydraulic heads in 12 observation wells. The model performance evaluation showed that the root means the square error is 1.89m and that the NSE is 0.98. The head contour map of the simulated hydraulic heads indicates the flow direction in the catchment, mainly from the Woluwe to Zenne catchment. The simulated head in the study area varies from 13m to 78m. The higher hydraulic heads are found in the southwest of the study area, which has the forest as a land-use type. This calibrated model was run for the climate change scenario and well operation scenario. Climate change may cause the groundwater recharge to increase by 43% and decrease by 30% in 2100 from current conditions for the high and low climate change scenario, respectively. The groundwater head varies for a high climate change scenario from 13m to 82m, whereas for a low climate change scenario, it varies from 13m to 76m. If doubling of the pumping discharge assumed, the groundwater head varies from 13m to 76.5m. However, if the shutdown of the pumps is assumed, the head varies in the range of 13m to 79m. It is concluded that the groundwater model is done in a satisfactory way with some limitations, and the model output can be used to understand the aquifer system under steady-state conditions. Finally, some recommendations are made for the future use and improvement of the model.

Keywords: Ter Kamerenbos, groundwater modelling, WetSpass, climate change, well operation

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