Search results for: anchoring bias

Authors: Etta Conteh, Tracy Macintosh

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Introduction: Restraints are often used in the Emergency Department when it is necessary for a patient to be restrained in order to decrease their agitation and better treat them. Chemical and physical restraints may be used on these patients at the discretion of the medical provider. Racism and injustice are rampant within our country, and medicine and healthcare are not spared. While racism and racial bias in medicine and healthcare have been studied, information on the differences in the use of restraints by race are scarce. Objective: The objective of this study is to determine if African Americans and Hispanic-American patients are restrained at higher rates compared to their White counterparts. Methods: This study will be carried out through a retrospective analysis utilizing the Hospital Corporation of America (HCA) national Emergency Department (ED) and inpatient database with patient visits from 2016-2019. All patient visits, with patients aged 18 years or older, will be reviewed, looking specifically for the race and the use and type of restraints. Other factors, such a pre-existing psychiatric condition, will be used for sub-analysis. Rationale: The outcome of this project will demonstrate the absence or presence of a racial disparity in the use of restraints in the Emergency Department. These results can be used as a foundation for improving racial equity in healthcare treatment.

Keywords: emergency medicine, public health, racism, restraint use

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Authors: Rebecca Owusu Coffie, Atakelty Hailu

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Variants of production frontier models have emerged, however, only a limited number of them are applied in empirical research. Hence the effects of these alternative frontier models are not well understood, particularly within sub-Saharan Africa. In this paper, we apply recent advances in the production frontier to examine levels of technical efficiency and efficiency drivers. Specifically, we compare the heteroscedastic parametric and the semiparametric stochastic smooth coefficient (SPSC) models. Using rice production data from Ghana, our empirical estimates reveal that alternative specification of efficiency estimators results in either downward or upward bias in the technical efficiency estimates. Methodologically, we find that the SPSC model is more suitable and generates high-efficiency estimates. Within the parametric framework, we find that parameterization of both the mean and variance of the pre-truncated function is the best model. For the drivers of technical efficiency, we observed that longer farm distances increase inefficiency through a reduction in labor productivity. High soil quality, however, increases productivity through increased land productivity.

Keywords: pre-truncated, rice production, smooth coefficient, technical efficiency

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Authors: Peng Li, Luan Wang, Haifeng Fei, Renhong Xie, Yibin Rui, Shanhong Guo

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The applications of satellite-based automatic identification system (S-AIS) pave the road for wide-range maritime traffic monitoring and management. But the coverage of satellite’s view includes multiple AIS self-organizing networks, which leads to the collision of AIS signals from different cells. The contribution of this work is to propose an improved multi-channel blind source separation algorithm based on Artificial Bee Colony (ABC) and advanced stochastic optimization to perform separation of the mixed AIS signals. The proposed approach adopts modified ABC algorithm to get an optimized initial separating matrix, which can expedite the initialization bias correction, and utilizes the Adaptive Moment Estimation (Adam) to update the separating matrix by adjusting the learning rate for each parameter dynamically. Simulation results show that the algorithm can speed up convergence and lead to better performance in separation accuracy.

Keywords: satellite-based automatic identification system, blind source separation, artificial bee colony, adaptive moment estimation

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Authors: Chih Hung Shih

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Eyewitness identification is one of the efficient information to identify suspects during criminal investigation. However eyewitness identification is improved frequently, inaccurate and plays vital roles in wrongful convictions. Most eyewitness misidentifications are made during police criminal investigation stage and then accepted by juries. Four failure investigation case studies in Taiwan are conduct to demonstrate how misidentifications are caused during the police investigation context. The result shows that there are several common grounds among these cases: (1) investigators lacked for knowledge about eyewitness memory so that they couldn’t evaluate the validity of the eyewitnesses’ accounts and identifications, (2) eyewitnesses were always asked to filter out several suspects during the investigation, and received investigation information which contaminated the eyewitnesses’ memory, (3) one to one live individual identifications were made in most of cases, (4) eyewitness identifications were always used to support the hypotheses of investigators, and exaggerated theirs powers when conform with the investigation lines, (5) the eyewitnesses’ confidence didn’t t reflect the validity of their identifications , but always influence the investigators’ beliefs for the identifications, (6) the investigators overestimated the power of the eyewitness identifications and ignore the inconsistency with other evidence. Recommendations have been proposed for future academic research and police practice of eyewitness identification in Taiwan.

Keywords: criminal investigation, eyewitness identification, investigative bias, investigative failures

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Authors: Shih-Yu Lo

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Stereotypes exist in almost every society, affecting how people interact with each other. However, to our knowledge, the influence of stereotypes was rarely explored in the context of basic perceptual processes. This study aims to explore how the gender stereotype affects object recognition. Participants were presented with a series of scene pictures, followed by a target display with a man or a woman, holding a weapon or a non-weapon object. The task was to identify whether the object in the target display was a weapon or not. Although the gender of the object holder could not predict whether he or she held a weapon, and was irrelevant to the task goal, the participant nevertheless tended to identify the object as a weapon when the object holder was a man than a woman. The analysis based on the signal detection theory showed that the stereotype effect on object recognition mainly resulted from the participant’s bias to make a 'weapon' response when a man was in the scene instead of a woman in the scene. In addition, there was a trend that the participant’s sensitivity to differentiate a weapon from a non-threating object was higher when a woman was in the scene than a man was in the scene. The results of this study suggest that the irrelevant social cues implied in the visual scene can be very powerful that they can modulate the basic object recognition process.

Keywords: gender stereotype, object recognition, signal detection theory, weapon

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Authors: Shruti Sengupta

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According to the nationally representative data, about 73% of India's rural workforce is engaged in agriculture. While women make significant contributions to total agriculture production, they contribute to about one-third in India. In terms of gender composition, about 80% of the female and 69% of the male workforce is engaged in agriculture in rural India. Still, it is common to find gender differences in plot management within the household. In the last two and half years, India's agri-food system has undergone several changes due to this pandemic, both the demand and supply side, making agriculture more information and knowledge-intensive. Therefore, this paper investigates, using a nationally representative sample, how information asymmetry affects the net returns per hectare of land between female and male farm managers. Empirical results show that information intensity has a significant positive effect on net farm returns per hectare. Results suggest that if females have the same access to technical information as their male counterparts, their farm income can go up by .96 pp compared to male-headed farms. Results also indicate that literate females have higher farm incomes than non-literate females. The study contributes to the literature by employing gender differentials in farm income due to the information gap.

Keywords: agriculture, gender, information asymmetry, farm income, social bias

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Authors: Sajeeha Ansar, Asad Ali Safi, Sheikh Ziauddin, Ahmad R. Shahid, Faraz Ahsan

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Gliomas are most challenging and aggressive type of tumors which appear in different sizes, locations, and scattered boundaries. CNN is most efficient deep learning approach with outstanding capability of solving image analysis problems. A fully automatic deep learning based 2D-CNN model for brain tumor segmentation is presented in this paper. We used small convolution filters (3 x 3) to make architecture deeper. We increased convolutional layers for efficient learning of complex features from large dataset. We achieved better results by pushing convolutional layers up to 16 layers for HGG model. We achieved reliable and accurate results through fine-tuning among dataset and hyper-parameters. Pre-processing of this model includes generation of brain pipeline, intensity normalization, bias correction and data augmentation. We used the BRATS-2015, and Dice Similarity Coefficient (DSC) is used as performance measure for the evaluation of the proposed method. Our method achieved DSC score of 0.81 for complete, 0.79 for core, 0.80 for enhanced tumor regions. However, these results are comparable with methods already implemented 2D CNN architecture.

Keywords: brain tumor segmentation, convolutional neural networks, deep learning, HGG

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Authors: Shruti Sengupta

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According to the nationally representative data, about 73% of India's rural workforce is engaged in agriculture. While women make significant contributions to total agriculture production, they contribute to about one-third in India. In terms of gender composition, about 80% of the female and 69% of the male workforce is engaged in agriculture in rural India. Still, it is common to find gender differences in plot management within the household. In the last two and half years, India's agri-food system has undergone several changes due to this pandemic, both the demand and supply side, making agriculture more information and knowledge-intensive. Therefore, this paper investigates, using a nationally representative sample, how information asymmetry affects the net returns per hectare of land between female and male farm managers. Empirical results show that information intensity has a significant positive effect on net farm returns per hectare. Results suggest that if females have the same access to technical information as their male counterparts, their farm income can go up by .96 pp compared to male-headed farms. Results also indicate that literate females have higher farm incomes than non-literate females. The study contributes to the literature by employing gender differentials in farm income due to the information gap.

Keywords: agriculture, gender, information asymmetry, farm income, social bias

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Authors: Joseph Wolff, Jeffrey Eilbott

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Autism Spectrum Disorders (ASD) are a spectrum of social disorders characterized by deficits in social communication, verbal ability, and interaction that can vary in severity. In recent years, researchers have used magnetic resonance imaging (MRI) to help detect how neural patterns in individuals with ASD differ from those of neurotypical (NT) controls for classification purposes. This study analyzed the classification of ASD within males and females using functional MRI data. Functional connectivity (FC) correlations among brain regions were used as feature inputs for machine learning algorithms. Analysis was performed on 558 cases from the Autism Brain Imaging Data Exchange (ABIDE) I dataset. When trained specifically on females, the algorithm underperformed in classifying the ASD subset of our testing population. Although the subject size was relatively smaller in the female group, the manual matching of both male and female training groups helps explain the algorithm’s bias, indicating the altered sex abnormalities in functional brain networks compared to typically developing peers. These results highlight the importance of taking sex into account when considering how generalizations of findings on males with ASD apply to females.

Keywords: autism spectrum disorder, machine learning, neuroimaging, sex differences

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Authors: Robert Jacobsen

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Flood inundation maps (FIMs) are an essential tool in communicating flood threat scenarios to the public as well as in floodplain governance. With an increasing demand for online raster FIMs, the FIM State-of-the-Practice (SOP) is rapidly advancing to meet the dual requirements for high-resolution and high-accuracy—or High-Definition. Importantly, today’s technology also enables the resolution of problems of local—neighborhood-scale—bias errors that often occur in FIMs, even with the use of SOP two-dimensional flood modeling. To facilitate the development of HD-FIMs, a new GIS method--Raster Adjustment with Scenario Profiles, RASPTM—is described for adjusting kernel raster FIMs to match refined scenario profiles. With RASPTM, flood professionals can prepare HD-FIMs for a wide range of scenarios with available kernel rasters, including kernel rasters prepared from vector FIMs. The paper provides detailed procedures for RASPTM, along with an example of applying RASPTM to prepare an HD-FIM for the August 2016 Flood in Louisiana using both an SOP kernel raster and a kernel raster derived from an older vector-based flood insurance rate map. The accuracy of the HD-FIMs achieved with the application of RASPTM to the two kernel rasters is evaluated.

Keywords: hydrology, mapping, high-definition, inundation

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Authors: Mabrook Saleh Amera, Prabhakarn Arunachalama, Maged N. Shaddadb, Abdulhadi Al-Qadia

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Global energy crises and water pollution have negatively impacted sustainable development in recent years. It is most promising to use Bismuth vanadate (BiVO4) as an electrode for photoelectrocatalytic (PEC) oxidation of water and pollution degradation. However, BiVO4 anodes suffer from poor charge separation and slow water oxidation. In this paper, a Zr:BiVO4/NiFeOOH heterojunction was successfully prepared by electrodeposition and photoelectrochemical transformation process. The method resulted in a notable 5-fold improvement in photocurrent features (1.27 mAcm−2 at 1.23 VRHE) and a lower onset potential of 0.6 VRHE. Photoanodes with high photocatalytic features and high photocorrosion resistance may be attributed their high conformity and amorphous nature of the coating. In this study, PEC was compared to electrocatalysis (EC), and the effect of bias potential on PEC degradation was discussed for tetracycline (TCH), riboflavin, and streptomycin. In PEC, TCH was degraded in the most efficient way (96 %) by Zr:BiVO4/NiFeOOH, three times larger than Zr:BiVO4 and EC (55 %). Thus, this study offers a potential solution for oxidizing PEC water and treating water pollution.

Keywords: photoelectrochemical, water splitting, pharmaceutical pollutants degradation, photoanodes, cocatalyst

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Authors: Mário Ernesto Sitoe, Orlando Zacarias

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University education is influenced by several factors that range from the adoption of strategies to strengthen the whole process to the academic performance improvement of the students themselves. This work uses data mining techniques to develop a predictive model to identify students with a tendency to evasion and retention. To this end, a database of real students’ data from the Department of University Admission (DAU) and the Department of Mathematics and Informatics (DMI) was used. The data comprised 388 undergraduate students admitted in the years 2009 to 2014. The Weka tool was used for model building, using three different techniques, namely: K-nearest neighbor, random forest, and logistic regression. To allow for training on multiple train-test splits, a cross-validation approach was employed with a varying number of folds. To reduce bias variance and improve the performance of the models, ensemble methods of Bagging and Stacking were used. After comparing the results obtained by the three classifiers, Logistic Regression using Bagging with seven folds obtained the best performance, showing results above 90% in all evaluated metrics: accuracy, rate of true positives, and precision. Retention is the most common tendency.

Keywords: evasion and retention, cross-validation, bagging, stacking

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Authors: Angelo Aloisio Dag, Pasquale Pasca, Massimo Fragiacomo, Ferdinando Totani, Gianfranco Totani

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The estimate of the velocity of shear waves (Vs) is essential in seismic engineering to characterize the dynamic response of soils. There are various direct methods to estimate the Vs. The authors report the results of site characterization in Macerata, where they measured the Vs using the seismic dilatometer in a 100m deep borehole. The standard Vs estimation originates from the cross-correlation between the signals acquired by two geophones at increasing depths. This paper focuses on the estimate of the dependence of Vs on the wavenumber. The dispersion curves reveal an unexpected hyperbolic dispersion curve typical of Lamb waves. Interestingly, the contribution of Lamb waves may be notable up to 100m depth. The amplitude of surface waves decrease rapidly with depth: still, their influence may be essential up to depths considered unusual for standard geotechnical investigations, where their effect is generally neglected. Accordingly, these waves may bias the outcomes of the standard Vs estimations, which ignore frequency-dependent phenomena. The paper proposes an enhancement of the accepted procedure to estimate Vs and addresses the importance of Lamb waves in soil characterization.

Keywords: dispersion curve, seismic dilatometer, shear wave, soil mechanics

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Authors: A. Porshnev, A. Zaporozhtchuk

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Motivation regarded as a key factor of labor turnover, is especially important for volunteers working on an altruistic basis in NGO. Despite the motivational letter, candidate selection depends on the impression of the selection committee, which can be subject to human bias. We expect that structured and unstructured information provided in motivation letters could be used to improve candidate selection procedures. In our paper, we perform qualitative and quantitative analysis of 2280 motivation letters, create logistic regression, and build a decision tree to improve selection procedures. Our analysis showed that motivation factors are significant and enable human resources department to forecast labor turnover and provide extra information to demographic, professional and timing questions. In spite of the average level of accuracy the model demonstrates the selection procedures of company of under consideration can be improved. We also discuss interrelation between answers to open and closed motivation questions, recommend changes in motivational letter templates to ensure more relevant information about applicants and further steps to create more accurate model.

Keywords: decision trees, logistic regression, model, motivational letter, non-governmental organization, retention, turnover

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Authors: Fatma Ismailia, Malek Saihi

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This research provides an explanation of exchange incentives on the Tunis stock market from a behavioural point of view. The elucidation of the anomalies of excessive volume of transactions and that of excessive volatility cannot be done without the recourse to the psychological aspects of investors. The excessive confidence has been given the predominant role for the explanation of these phenomena. Indeed, when investors store increments, they become more confident about the precision of their private information and their exchange activities then become more aggressive on the subsequent periods. These overconfident investors carry out the intensive exchanges leading to an increase of securities volatility. The objective of this research is to identify whether the trading volume and the excessive volatility of securities observed on the Tunisian stock market come from the excessive exchange of overconfident investors. We use a sample of daily observations over the period January 1999 - October 2007 and we relied on various econometric tests including the VAR model. Our results provide evidence on the importance to consider the bias of overconfidence in the analysis of Tunis stock exchange specificities. The results reveal that the excess of confidence has a major impact on the trading volume while using daily temporal intervals.

Keywords: overconfidence, trading volume, efficiency, rationality, anomalies, behavioural finance, cognitive biases

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Authors: Van Son Nguyen, Van Huy Mai, Alec Moradpour, Pascale Auban Senzier, Claude Pasquier, Kang Wang, Pierre-Antoine Albouy, Marcelo J. Rozenberg, John Giapintzakis, Christian N. Mihailescu, Charis M. Orfanidou, Thomas Maroutian, Philippe Lecoeur, Guillaume Agnus, Pascal Aubert, Sylvain Franger, Raphaël Salot, Nathalie Brun, Katia March, David Alamarguy, Pascal ChréTien, Olivier Schneegans

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In the field of Nanoelectronics, a major research activity is being developed towards non-volatile memories. To face the limitations of existing Flash memory cells (endurance, downscaling, rapidity…), new approaches are emerging, among them resistive switching memories (Re-RAM). In this work, we analysed the behaviour of LixCoO2 oxide thin films in electrode/film/electrode devices. Preliminary results have been obtained concerning the influence of bias pulses characteristics (duration, value) on some performance parameters, such as endurance and resistance ratio (ROFF/RON). Besides, Conducting Probe Atomic Force Microscopy (CP-AFM) characterizations of the devices have been carried out to better understand some causes of performance failure, and thus help optimizing the switching performance of such devices.

Keywords: non volatile resistive memories, resistive switching, thin films, endurance

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Authors: Surangrat Srisurapanon, Chatchawal Wongjitrat, Navin Horthongkham, Ruengpung Sutthent

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HBV infection causes a potential serious public health problem. The ability to detect the HBV DNA concentration is of the importance and improved continuously. By using quantitative Polymerase Chain Reaction (qPCR), several factors in standardized; source of material, calibration standard curve and PCR efficiency are inconsistent. Digital PCR (dPCR) is an alternative PCR-based technique for absolute quantification using Poisson's statistics without requiring a standard curve. Therefore, the aim of this study is to compare the data set of HBV DNA generated between dPCR and qPCR methods. All samples were quantified by Abbott’s real time PCR and 54 samples with 2 -6 log10 HBV DNA were selected for comparison with dPCR. Of these 54 samples, there were two outlier samples defined as negative by dPCR. Of these two, samples were defined as negative by dPCR, whereas 52 samples were positive by both the tests. The difference between the two assays was less than 0.25 log IU/mL in 24/52 samples (46%) of paired samples; less than 0.5 log IU/mL in 46/52 samples (88%) and less than 1 log in 50/52 samples (96%). The correlation coefficient was r=0.788 and P-value <0.0001. Comparison to qPCR, data generated by dPCR tend to be the overestimation in the sample with low HBV DNA concentration and underestimated in the sample with high viral load. The variation in DNA by dPCR measurement might be due to the pre-amplification bias, template. Moreover, a minor drawback of dPCR is the large quantity of DNA had to be used when compare to the qPCR. Since the technology is relatively new, the limitations of this assay will be improved.

Keywords: hepatitis B virus, real time PCR, digital PCR, DNA quantification

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Authors: Ezgi Nevruz, Kasirga Yildirak, Ashis SenGupta

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Comparing or ranking risks is the main motivating factor behind the human trait of making choices. Cumulative prospect theory (CPT) is a preference theory approach that evaluates perception and bias in decision making under risk and uncertainty. We aim to investigate the aggregate claims of different risk classes in terms of their comparability and amenability to ordering when the impact of risk perception is considered. For this aim, we prioritize the aggregate claims taken as actuarial risks by using various stochastic ordering relations. In order to prioritize actuarial risks, we use stochastic relations such as stochastic dominance and stop-loss dominance that are proposed in the frame of partial order theory. We take into account the dependency of the individual claims exposed to similar environmental risks. At first, we modify the zero-utility premium principle in order to obtain a solution for the stop-loss premium under CPT. Then, we propose a stochastic stop-loss dominance of the aggregate claims and find a relation between the stop-loss dominance and the first-order stochastic dominance under the dependence assumption by using properties of the familiar as well as some emerging multivariate claim distributions.

Keywords: cumulative prospect theory, partial order theory, risk perception, stochastic dominance, stop-loss dominance

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Authors: Malika Hammouche

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The novel Pillars of Salt, written by Fadia Faqir in 1996, is a good example where storytelling is utilized as a traditional material to underline the author’s womanist ideology. A study of narrative could be fruitfully combined with that of ideology in this case. This combination could be demonstrated through the narrative technique used by Fadia Faqir in Pillars of Salt (1996), reflecting her anti-colonial ideology. The first step of this work will highlight the storyteller’s narrative in the novel representing, on the one hand, the imperial voice, and on the other exoticism and orientalism. The second step will demonstrate how Faqir’s narrative technique uses focalization as a narratological tool to negotiate her space. Faqir gives a voice to the female protagonist of the novel within the androcentric bias of Arab narrative theory to point to and amend the orientalist discourse typical to colonial literature. The orientalist discourse is represented through the voice of the storyteller in the novel. The juxtaposition of the storyteller’s and the female protagonist narratives is borrowed from the Arab literary background. It is a postcolonial counter-discursive strategy used by the author as a traditional material to underline her Arabo Islamic Womanist ideology in this novel.

Keywords: Arabo Islamic womanism, focalization, ideology, narrative technique, orientalist

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Authors: Rajan Vohra, Ravinder Singh Sawhney, Kunwar Partap Singh

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Electrical charge transport through two basic strands thymine and adenine of DNA have been investigated and analyzed using the jellium model approach. The FFT-2D computations have been performed for semi-empirical Extended Huckel Theory using atomistic tool kit to contemplate the charge transport metrics like current and conductance. The envisaged data is further evaluated in terms of transmission spectrum, HOMO-LUMO Gap and number of electrons. We have scrutinized the behavior of the devices in the range of -2V to 2V for a step size of 0.2V. We observe that both thymine and adenine can act as molecular devices when sandwiched between two gold probes. A prominent observation is a drop in HLGs of adenine and thymine when working as a device as compared to their intrinsic values and this is comparative more visible in case of adenine. The current in the thymine based device exhibit linear increase with voltage in spite of having low conductance. Further, the broader transmission peaks represent the strong coupling of electrodes to the scattering molecule (thymine). Moreover, the observed current in case of thymine is almost 3-4 times than that of observed for adenine. The NDR effect has been perceived in case of adenine based device for higher bias voltages and can be utilized in various future electronics applications.

Keywords: adenine, DNA, extended Huckel, thymine, transmission spectra

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Authors: Adekunle Saheed Ajisebiyawo, Christie Omoduwa Achime

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In Nigerian society, women have very little or no involvement in the decision-making process and this is large because women are objectified as effective means of reproduction and provision of emotional support to the society. Despite the movements and awareness by international, national and local bodies to promote and encourage women's empowerment, there are still many factors daunting to the efforts of women in society. This paper examined the critical role of feminism in the quest for women's emancipation in public life. Guided by African feminism theory, this paper utilizes both historical and descriptive methods to examine these factors. The paper argues that gender bias in Nigeria's public life is often traced to the onset of colonialism in Nigeria. Thus the Western cultural notion of colonialism woven around male superiority is reflected in their relations with Nigerians. The study outlines how women have strategized pathways through patriarchal structures by deploying their femininity. The paper concludes that women are strong, courageous, natural leaders and indeed have a major strategic role to play in public life; thus, women's movements and groups remain an important and necessary means of social cohesion and strength, especially in a country such as Nigeria.

Keywords: African feminism, democratic governance, feminism, patriarchy, women emancipation.

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Authors: Lianzhong Zhang, Chao Huang

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Sea-land segmentation is a basic step in many tasks such as sea surface monitoring and ship detection. The existing sea-land segmentation algorithms have poor segmentation accuracy, and the parameter adjustments are cumbersome and difficult to meet actual needs. Also, the current sea-land segmentation adopts traditional deep learning models that use Convolutional Neural Networks (CNN). At present, the transformer architecture has achieved great success in the field of natural images, but its application in the field of radar images is less studied. Therefore, this paper proposes a sea-land segmentation method based on the transformer architecture to strengthen edge supervision. It uses a self-attention mechanism with a gating strategy to better learn relative position bias. Meanwhile, an additional edge supervision branch is introduced. The decoder stage allows the feature information of the two branches to interact, thereby improving the edge precision of the sea-land segmentation. Based on the Gaofen-3 satellite image dataset, the experimental results show that the method proposed in this paper can effectively improve the accuracy of sea-land segmentation, especially the accuracy of sea-land edges. The mean IoU (Intersection over Union), edge precision, overall precision, and F1 scores respectively reach 96.36%, 84.54%, 99.74%, and 98.05%, which are superior to those of the mainstream segmentation models and have high practical application values.

Keywords: SAR, sea-land segmentation, deep learning, transformer

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Authors: Shu-Ching Chiu, Shu-Fang Chang

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The World Health Organization (WHO) has been actively developing intervention programs to deal with geriatric frailty. In its White Paper on Healthcare Policy 2020, the Department of Health, Bureau of Health Promotion proposed that active aging and the prevention of disability are essential for elderly people to maintain good health. The paper recommended five main policies relevant to this objective, one of which is the prevention of frailty and disability. Scholars have proposed a number of different criteria to diagnose and assess frailty; no consistent or normative standard of measurement is currently available. In addition, many methods of assessment are recursive, which can easily result in recall bias. Due to the relationship between frailty and physical fitness with regard to co-morbidity, it is important that academics optimize the criteria used to assess frailty by objectively evaluating the physical fitness of senior citizens. This study used a review of the literature to identify fitness indicators suitable for measuring frailty in the elderly. This study recommends that measurement criteria be integrated to produce an optimized predictive value for frailty score. Healthcare professionals could use this data to detect frailty at an early stage and provide appropriate care to prevent further debilitation and increase longevity.

Keywords: frailty, aging, physical fitness, optimized criteria, healthcare

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Authors: WooJin KANG

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Contrary to the ideal, in the cartelized democracy, meritocracy is revealed to be a system that gives arrogance to the winners and humiliation to the losers, and more and more studies are asserting the upper-class bias of meritocracy. However, only some studies have analyzed the determinants of the perception of meritocracy and fairness among young people. This article was an attempt to fill this gap. According to the empirical results of this article, the determinants of fairness of the meritocracy in the youth were multidimensional. The social status model, the political ideology model, and the future prospect model all significantly impacted the perception of meritocracy fairness among young people. Contrary to the predictions of the system justification theory and the compensatory control theory of previous studies, the lower-class youth were critical of meritocracy. In addition, the more negative the future outlook, the less they accepted the fairness of meritocracy. In addition, ideological debates over solutions to inequality of opportunity, which began in earnest during the 20th presidential election, turned out to be a variable that significantly influenced the perception of fairness based on meritocracy among young people. The results of the empirical analysis in this article reaffirmed the multidimensional structure of the youth. This suggests the need for policy responses leading to education tailored to various subgroups within the youth.

Keywords: Meritocracy, Exam-Meritocracy, Fairness, Multiple-inequality

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Authors: Vineel Inampudi, Arjun Prakash, Joseph Vinod

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Aims and Objectives: To evaluate the interrater reliability in grading ASPECTS score, between emergency medicine physician at first contact and radiologist among patients with acute ischemic stroke. Materials and Methods: We conducted a retrospective analysis of 86 acute ischemic stroke cases referred to the Department of Radiodiagnosis during November 2014 to January 2016. The imaging (plain CT scan) was performed using GE Bright Speed Elite 16 Slice CT Scanner. ASPECTS score was calculated separately by an emergency medicine physician and radiologist. Interrater reliability for total and dichotomized ASPECTS (≥ 6 and < 6) scores were assessed using statistical analysis (ICC and Cohen ĸ coefficients) on SPSS software (v17.0). Results: Interrater agreement for total and dichotomized ASPECTS was substantial (ICC 0.79 and Cohen ĸ 0.68) between the emergency physician and radiologist. Mean difference in ASPECTS between the two readers was only 0.15 with standard deviation of 1.58. No proportionality bias was detected. Bland Altman plot was constructed to demonstrate the distribution of ASPECT differences between the two readers. Conclusion: Substantial interrater agreement was noted in grading ASPECTS between emergency medicine physician at first contact and radiologist thereby confirming its robustness even in a rural setting.

Keywords: ASPECTS, computed tomography, MCA territory, stroke

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Authors: M. Zake, I. Barmina, R. Valdmanis, A. Kolmickovs

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Experimental investigations of the DC electric field effect on thermal decomposition of biomass, formation of the axial flow of volatiles (CO, H2, CxHy), mixing of volatiles with swirling airflow at low swirl intensity (S ≈ 0.2-0.35), their ignition and on formation of combustion dynamics are carried out with the aim to understand the mechanism of electric field influence on biomass gasification, combustion of volatiles and heat energy production. The DC electric field effect on combustion dynamics was studied by varying the positive bias voltage of the central electrode from 0.6 kV to 3 kV, whereas the ion current was limited to 2 mA. The results of experimental investigations confirm the field-enhanced biomass gasification with enhanced release of volatiles and the development of endothermic processes at the primary stage of thermochemical conversion of biomass determining the field-enhanced heat energy consumption with the correlating decrease of the flame temperature and heat energy production at this stage of flame formation. Further, the field-enhanced radial expansion of the flame reaction zone correlates with a more complete combustion of volatiles increasing the combustion efficiency by 3 % and decreasing the mass fraction of CO, H2 and CxHy in the products, whereas by 10 % increases the average volume fraction of CO2 and the heat energy production downstream the combustor increases by 5-10 %

Keywords: biomass, combustion, electrodynamic control, gasification

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Authors: Elizabeth R. LaFave, Grayson Sink, Anna Vassallo, Samantha Mills, Eli G. Hvastkovs

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Throughout history and into modern times, the continuation of male influence over female healthcare has created inadequacies in availability and access to treatments, often further limited in rural communities. The historical plight of women in healthcare can be understood by studying the advancements made by women in the field, both through their career arcs and by delving into the treatments they offer. An early example is the case of Martha Ballard (1735-1812), a midwife in New York who practiced when female practitioners were dismissed in favor of less educated male physicians, which was a well-accepted practice into the twentieth century. In order to overcome these setbacks, a strategy used by some female practitioners was to develop and market their own remedies in an attempt to better serve female patients. By highlighting the compromises and social manipulation of female entrepreneurs, in comparison with the medicines they developed and used, we can map their ability to carve a specific niche for themselves and their targeted customers. The application of modern chemical approaches in a historical context serves to enhance a variety of perspectives within the museum sphere necessary for the comprehension and understanding of the female plight in both medical care and service. In order to further examine the overall bias and scrutiny for women in the medical field, specifically those undertaking entrepreneurial roles, examples of alternative remedies from female founders will be analyzed utilizing these approaches. Modern analytical chemistry techniques, specifically mass spectrometry (MS), have been successful in offering compositional analyses for both labeled and unlabeled ingredients in old medicines. Previously, we have analyzed two forms of alternative treatment options created by male medical professionals to address lingering historical questions of purity and validity. Although primarily sugar based, both Humphreys’ Specifics and Boericke & Tafel remedies also contained unique ingredients, albeit in small quantities, with medicinal properties. Here, we applied the same methodology to study another highly politicized 19th-century debate surrounding the contribution and role of women in the medical profession through analyzing three remedies, each from a different female-led manufacturing company; Mrs. Joe Persons, Lydia Pinkham, and Winslow’s Syrups. Following MS analyses for both labeled and unlabeled ingredients, both Winslow’s and Pinkham’s remedies were similar to their male counterparts in advertisement strategy, targeted customer base, and overall composition of remedy (primarily sugar-based with small amounts of unique ingredients). In effect, these unbiased chemical assessments are used to dissect the rationality of both market and physician criticism for each individual manufacturer through assessment of authenticity, benefaction, and comparison among female entrepreneurs and their aims to enter the medical community (i.e., geographic location, market size). Our work aims to increase collaboration between STEM (Science, Technology, Engineering, Mathematics)-based fields and historical museum studies on a larger scale while also answering questions of potential bias towards females in the medical community as means of comparison to their male counterparts and in-depth historical analyses to unravel individual strategies to overcome the setback.

Keywords: nineteenth-century medicine, alternative remedies, female healthcare, chemical analyses, mass spectrometry

Procedia PDF Downloads 62

Authors: Daniela Ailincai, Bogdan C. Simionescu, Luminita Marin

Abstract:

Polymer dispersed liquid crystals (PDLC) represent an interesting class of materials which combine the ability of polymers to form films and their mechanical strength with the opto-electronic properties of liquid crystals. The proper choice of the two components - the liquid crystal and the polymeric matrix - leads to materials suitable for a large area of applications, from electronics to biomedical devices. The objective of our work was to obtain PDLC films with potential applications in the biomedical field, using poly vinyl alcohol boric acid (PVAB) as a polymeric matrix for the first time. Presenting all the tremendous properties of poly vinyl alcohol (such as: biocompatibility, biodegradability, water solubility, good chemical stability and film forming ability), PVAB brings the advantage of containing the electron deficient boron atom, and due to this, it should promote the liquid crystal anchoring and a narrow liquid crystal droplets polydispersity. Two different PDLC systems have been obtained, by the use of two liquid crystals, a nematic commercial one: 4-cyano-4’-penthylbiphenyl (5CB) and a new smectic liquid crystal, synthesized by us: buthyl-p-[p’-n-octyloxy benzoyloxy] benzoate (BBO). The PDLC composites have been obtained by the encapsulation method, working with four different ratios between the polymeric matrix and the liquid crystal, from 60:40 to 90:10. In all cases, the composites were able to form free standing, flexible films. Polarized light microscopy, scanning electron microscopy, differential scanning calorimetry, RAMAN- spectroscopy and the contact angle measurements have been performed, in order to characterize the new composites. The new smectic liquid crystal has been characterized using 1H-NMR and single crystal X-ray diffraction and its thermotropic behavior has been established using differential scanning calorimetry and polarized light microscopy. The polarized light microscopy evidenced the formation of round birefringent droplets, anchored homeotropic in the first case and planar in the second, with a narrow dimensional polydispersity, especially for the PDLC containing the largest amount of liquid crystal, fact evidenced by SEM, also. The obtained values for the water to air contact angle showed that the composites have a proper hydrophilic-hydrophobic balance, making them potential candidates for bioapplications. More than this, our studies demonstrated that the water to air contact angle varies as a function of PVAB matrix crystalinity degree, which can be controled as a function of time. This fact allowed us to conclude that the use of PVAB as matrix for PDLCs obtaining offers the possibility to modulate their properties for specific applications.

Keywords: 4-cyano-4’-penthylbiphenyl, buthyl-p-[p’-n-octyloxy benzoyloxy] benzoate, contact angle, polymer dispersed liquid crystals, poly vinyl alcohol boric acid

Procedia PDF Downloads 430

Authors: Asadullah I. Qazi, Mansoor Ahsan, Zahir Ashraf, Uzair Ahmad

Abstract:

System identification of an Unmanned Aerial Vehicle (UAV), to acquire its mathematical model, is a significant step in the process of aircraft flight automation. The need for reliable mathematical model is an established requirement for autopilot design, flight simulator development, aircraft performance appraisal, analysis of aircraft modifications, preflight testing of prototype aircraft and investigation of fatigue life and stress distribution etc.  This research is aimed at system identification of a fixed wing UAV by means of specifically designed flight experiment. The purposely designed flight maneuvers were performed on the UAV and aircraft states were recorded during these flights. Acquired data were preprocessed for noise filtering and bias removal followed by parameter estimation of longitudinal dynamics transfer functions using MATLAB system identification toolbox. Black box identification based transfer function models, in response to elevator and throttle inputs, were estimated using least square error   technique. The identification results show a high confidence level and goodness of fit between the estimated model and actual aircraft response.

Keywords: fixed wing UAV, system identification, black box modeling, longitudinal dynamics, least square error

Procedia PDF Downloads 295

Authors: Ishapathik Das

Abstract:

The purpose of this article is to find a method of comparing designs for ordinal regression models using quantile dispersion graphs in the presence of linear predictor misspecification. The true relationship between response variable and the corresponding control variables are usually unknown. Experimenter assumes certain form of the linear predictor of the ordinal regression models. The assumed form of the linear predictor may not be correct always. Thus, the maximum likelihood estimates (MLE) of the unknown parameters of the model may be biased due to misspecification of the linear predictor. In this article, the uncertainty in the linear predictor is represented by an unknown function. An algorithm is provided to estimate the unknown function at the design points where observations are available. The unknown function is estimated at all points in the design region using multivariate parametric kriging. The comparison of the designs are based on a scalar valued function of the mean squared error of prediction (MSEP) matrix, which incorporates both variance and bias of the prediction caused by the misspecification in the linear predictor. The designs are compared using quantile dispersion graphs approach. The graphs also visually depict the robustness of the designs on the changes in the parameter values. Numerical examples are presented to illustrate the proposed methodology.

Keywords: model misspecification, multivariate kriging, multivariate logistic link, ordinal response models, quantile dispersion graphs

Procedia PDF Downloads 360