Search results for: negative data
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 27928

Search results for: negative data

25648 Transformation of the Business Model in an Occupational Health Care Company Embedded in an Emerging Personal Data Ecosystem: A Case Study in Finland

Authors: Tero Huhtala, Minna Pikkarainen, Saila Saraniemi

Abstract:

Information technology has long been used as an enabler of exchange for goods and services. Services are evolving from generic to personalized, and the reverse use of customer data has been discussed in both academia and industry for the past few years. This article presents the results of an empirical case study in the area of preventive health care services. The primary data were gathered in workshops, in which future personal data-based services were conceptualized by analyzing future scenarios from a business perspective. The aim of this study is to understand business model transformation in emerging personal data ecosystems. The work was done as a case study in the context of occupational healthcare. The results have implications to theory and practice, indicating that adopting personal data management principles requires transformation of the business model, which, if successfully managed, may provide access to more resources, potential to offer better value, and additional customer channels. These advantages correlate with the broadening of the business ecosystem. Expanding the scope of this study to include more actors would improve the validity of the research. The results draw from existing literature and are based on findings from a case study and the economic properties of the healthcare industry in Finland.

Keywords: ecosystem, business model, personal data, preventive healthcare

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25647 Design of an Instrumentation Setup and Data Acquisition System for a GAS Turbine Engine Using Suitable DAQ Software

Authors: Syed Nauman Bin Asghar Bukhari, Mohtashim Mansoor, Mohammad Nouman

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Engine test-Bed system is a fundamental tool to measure dynamic parameters, economic performance, and reliability of an aircraft Engine, and its automation and accuracy directly influences the precision of acquired and analysed data. In this paper, we present the design of digital Data Acquisition (DAQ) system for a vintage aircraft engine test bed that lacks the capability of displaying all the analyzed parameters at one convenient location (one panel-one screen). Recording such measurements in the vintage test bed is not only time consuming but also prone to human errors. Digitizing such measurement system requires a Data Acquisition (DAQ) system capable of recording these parameters and displaying them on one screen-one panel monitor. The challenge in designing upgrade to the vintage systems arises with a need to build and integrate digital measurement system from scratch with a minimal budget and modifications to the existing vintage system. The proposed design not only displays all the key performance / maintenance parameters of the gas turbine engines for operator as well as quality inspector on separate screens but also records the data for further processing / archiving.

Keywords: Gas turbine engine, engine test cell, data acquisition, instrumentation

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25646 A Study of Sources and Control of Environmental Noise Pollution on Selected Areas of Osogbo, Capital of Osun State, Nigeria

Authors: Abdulrazaq Adepoju

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Climate change and its negative environmental challenges to humanity has for decades, taken the centre stage globally receiving attention on ways to take care of the menace and keep the damaging effects to manageable and tolerable level. However, noise pollution, another major environmental hazard militating against human habitation particularly in the developing countries of the world, is not receiving enough attention by the concerned authorities at all tiers of governance. A good knowledge of the major sources of environmental noise pollution will go a long way in assisting relevant stakeholders in planning, designing, and management of problems associated with noise pollution. This paper seeks to identify the major sources of noise in the built environment on selected areas of Osogbo, Nigeria. The paper adopted a survey research method of collecting data from surveys carried out on buildings around old Garage-Okefia axis, Old garage-Oja Oba axis, and Okefia-Olaiya junction axis, all within Osogbo metropolis using sound surveying metre. It was discovered that noise from vehicular and pedestrian traffic, commercial activities such as advertising vendors and religious buildings (churches and mosques) constitute major causes of noise in the study area. The paper recommends some measures to the affected stakeholders particularly government agencies on means of reducing noise pollution to a tolerable level in the study areas and places of the same industrial layout.

Keywords: built environment, climate change, environmental pollution, noise

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25645 Differential Impacts of Whole-Growth-Duration Warming on the Grain Yield and Quality between Early and Late Rice

Authors: Shan Huang, Guanjun Huang, Yongjun Zeng, Haiyuan Wang

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The impacts of whole-growth warming on grain yield and quality in double rice cropping systems still remain largely unknown. In this study, a two-year field whole-growth warming experiment was conducted with two inbred indica rice cultivars (Zhongjiazao 17 and Xiangzaoxian 45) for early season and two hybrid indica rice cultivars (Wanxiangyouhuazhan and Tianyouhuazhan) for late season. The results showed that whole-growth warming did not affect early rice yield but significantly decreased late rice yield, which was caused by the decreased grain weight that may be related to the increased plant respiration and reduced translocation of dry matter accumulated during the pre-heading phase under warming. Whole-growth warming improved the milling quality of late rice but decreased that of early rice; however, the chalky rice rate and chalkiness degree were increased by 20.7% and 33.9% for early rice and 37.6 % and 51.6% for late rice under warming, respectively. We found that the crude protein content of milled rice was significantly increased by warming in both early and late rice, which would result in deterioration of eating quality. Besides, compared with the control treatment, the setback of late rice was significantly reduced by 17.8 % under warming, while that of early rice was not significantly affected by warming. These results suggest that the negative impacts of whole-growth warming on grain quality may be more severe in early rice than in late rice. Therefore, adaptation in both rice breeding and agronomic practices is needed to alleviate climate warming on the production of a double rice cropping system. Climate-smart agricultural practices ought to be implemented to mitigate the detrimental effects of warming on rice grain quality. For instance, fine-tuning the application rate and timing of inorganic nitrogen fertilizers, along with the introduction of organic amendments and the cultivation of heat-tolerant rice varieties, can help reduce the negative impact of rising temperatures on rice quality. Furthermore, to comprehensively understand the influence of climate warming on rice grain quality, future research should encompass a wider range of rice cultivars and experimental sites.

Keywords: climate warming, double rice cropping, dry matter, grain quality, grain yield

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25644 Water End-Use Classification with Contemporaneous Water-Energy Data and Deep Learning Network

Authors: Khoi A. Nguyen, Rodney A. Stewart, Hong Zhang

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‘Water-related energy’ is energy use which is directly or indirectly influenced by changes to water use. Informatics applying a range of mathematical, statistical and rule-based approaches can be used to reveal important information on demand from the available data provided at second, minute or hourly intervals. This study aims to combine these two concepts to improve the current water end use disaggregation problem through applying a wide range of most advanced pattern recognition techniques to analyse the concurrent high-resolution water-energy consumption data. The obtained results have shown that recognition accuracies of all end-uses have significantly increased, especially for mechanised categories, including clothes washer, dishwasher and evaporative air cooler where over 95% of events were correctly classified.

Keywords: deep learning network, smart metering, water end use, water-energy data

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25643 Domestic Violence against Women and the Nutritional Status of Their Under-5 Children: A Cross Sectional Survey in Urban Slums of Chittagong, Bangladesh

Authors: Mohiuddin Ahsanul Kabir Chowdhury, Ahmed Ehsanur Rahman, Nazia Binte Ali, Abdullah Nurus Salam Khan, Afrin Iqbal, Mohammad Mehedi Hasan, Salma Morium, Afsana Bhuiyan, Shams El Arifeen

Abstract:

Violence against women has been treated as a global epidemic which is as fatal as any serious disease or accidents. Like many other low-income countries it is also common in Bangladesh. In spite of existence of a few documented evidences in some other countries, in Bangladesh, domestic violence against women (DVAW) is not considered as a factor for malnutrition in children yet. Hence, the aim of the study was to investigate the association between DVAW and the nutritional status of their under-5 children in the context of slum areas of Chittagong, Bangladesh. A Cross-sectional survey was conducted among 87 women of reproductive age having at least one child under-5 years of age and staying with husband for at least last 1 year in selected slums under Chittagong City Corporation area. Data collection tools were structured questionnaire for the study participants and mid-upper arm circumference (MUAC) to measure the nutritional status of the under-5 children. The data underwent descriptive and regression analysis. Out of 87 respondents, 50 (57.5%) reported to suffer from domestic violence by their husband during last one year. Physical violence was found to be significantly associated with age (p=0.02), age at marriage (p=0.043), wealth score (p=0.000), and with knowledge regarding law (p=0.017). According to the measurement of mid-upper arm circumference (MUAC) 21% children were suffering from severe acute malnutrition (SAM) and the same percentage of children were suffering from moderate acute malnutrition (MAM). However, unadjusted odds ratio suggested that there was negative association with domestic violence and nutritional status. But, the logistic regression confounding for other variable showed significant association with total family income (p=0.006), wealth score (p=0.031), age at marriage (p=0.029) and number of child (p=0.006). Domestic violence against women and under nutrition of the children, both are highly prevalent in Bangladesh. More extensive research should be performed to identify the factors contributing to the high prevalence of domestic violence and malnutrition in urban slums of Bangladesh. Household-based intervention is needed to limit this burning problem. In a nutshell, effective community participation, education and counseling are essential to create awareness among the community.

Keywords: Bangladesh, cross sectional survey, domestic violence against women, nutritional status, under-5 children, urban slums

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25642 Synthesis, Structural, Spectroscopic and Nonlinear Optical Properties of New Picolinate Complex of Manganese (II) Ion

Authors: Ömer Tamer, Davut Avcı, Yusuf Atalay

Abstract:

Novel picolinate complex of manganese(II) ion, [Mn(pic)2] [pic: picolinate or 2-pyridinecarboxylate], was prepared and fully characterized by single crystal X-ray structure determination. The manganese(II) complex was characterized by FT-IR, FT-Raman and UV–Vis spectroscopic techniques. The C=O, C=N and C=C stretching vibrations were found to be strong and simultaneously active in IR and spectra. In order to support these experimental techniques, density functional theory (DFT) calculations were performed at Gaussian 09W. Although the supramolecular interactions have some influences on the molecular geometry in solid state phase, the calculated data show that the predicted geometries can reproduce the structural parameters. The molecular modeling and calculations of IR, Raman and UV-vis spectra were performed by using DFT levels. Nonlinear optical (NLO) properties of synthesized complex were evaluated by the determining of dipole moment (µ), polarizability (α) and hyperpolarizability (β). Obtained results demonstrated that the manganese(II) complex is a good candidate for NLO material. Stability of the molecule arising from hyperconjugative interactions and charge delocalization was analyzed using natural bond orbital (NBO) analysis. The highest occupied and the lowest unoccupied molecular orbitals (HOMO and LUMO) which is also known the frontier molecular orbitals were simulated, and obtained energy gap confirmed that charge transfer occurs within manganese(II) complex. Molecular electrostatic potential (MEP) for synthesized manganese(II) complex displays the electrophilic and nucleophilic regions. From MEP, the the most negative region is located over carboxyl O atoms while positive region is located over H atoms.

Keywords: DFT, picolinate, IR, Raman, nonlinear optic

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25641 Strategy Management of Soybean (Glycine max L.) for Dealing with Extreme Climate through the Use of Cropsyst Model

Authors: Aminah Muchdar, Nuraeni, Eddy

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The aims of the research are: (1) to verify the cropsyst plant model of experimental data in the field of soybean plants and (2) to predict planting time and potential yield soybean plant with the use of cropsyst model. This research is divided into several stages: (1) first calibration stage which conducted in the field from June until September 2015.(2) application models stage, where the data obtained from calibration in the field will be included in cropsyst models. The required data models are climate data, ground data/soil data,also crop genetic data. The relationship between the obtained result in field with simulation cropsyst model indicated by Efficiency Index (EF) which the value is 0,939.That is showing that cropsyst model is well used. From the calculation result RRMSE which the value is 1,922%.That is showing that comparative fault prediction results from simulation with result obtained in the field is 1,92%. The conclusion has obtained that the prediction of soybean planting time cropsyst based models that have been made valid for use. and the appropriate planting time for planting soybeans mainly on rain-fed land is at the end of the rainy season, in which the above study first planting time (June 2, 2015) which gives the highest production, because at that time there was still some rain. Tanggamus varieties more resistant to slow planting time cause the percentage decrease in the yield of each decade is lower than the average of all varieties.

Keywords: soybean, Cropsyst, calibration, efficiency Index, RRMSE

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25640 The Impact of Research Anxiety on Research Orientation and Interest in Research Courses in Social Work Students

Authors: Daniel Gredig, Annabelle Bartelsen-Raemy

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Social work professionals should underpin their decisions with scientific knowledge and research findings. Hence, research is used as a framework for social work education and research courses have become a taken-for-granted component of study programmes. However, it has been acknowledged that social work students have negative beliefs and attitudes as well as frequently feelings of fear of research courses. Against this background, the present study aimed to establish the relationship between student’s fear of research courses, their research orientation and interest in research courses. We hypothesized that fear predicts the interest in research courses. Further, we hypothesized that research orientation (perceived importance and attributed usefulness for research for social work practice and perceived unbiased nature of research) was a mediating variable. In the years 2014, 2015 and 2016, we invited students enrolled for a bachelor programme in social work in Switzerland to participate in the study during their introduction day to the school taking place two weeks before their programme started. For data collection, we used an anonymous self-administered on-line questionnaire filled in on site. Data were analysed using descriptive statistics and structural equation modelling (generalized least squares estimates method). The sample included 708 students enrolled in a social work bachelor-programme, 501 being female, 184 male, and 5 intersexual, aged 19–56, having various entitlements to study, and registered for three different types of programme modes (full time programme; part time study with field placements in blocks; part time study involving concurrent field placement). Analysis showed that the interest in research courses was predicted by fear of research courses (β = -0.29) as well as by the perceived importance (β = 0.27), attributed usefulness of research (β = 0.15) and perceived unbiased nature of research (β = 0.08). These variables were predicted, in turn, by fear of research courses (β = -0.10, β = -0.23, and β = -0.13). Moreover, interest was predicted by age (β = 0.13). Fear of research courses was predicted by age (β = -0.10) female gender (β = 0.28) and having completed a general baccalaureate (β = -0.09). (GFI = 0.997, AGFI = 0.988, SRMR = 0.016, CMIN/df = 0.946, adj. R2 = 0.312). Findings evidence a direct as well as a mediated impact of fear on the interest in research courses in entering first-year students in a social work bachelor-programme. It highlights one of the challenges social work education in a research framework has to meet with. It seems, there have been considerable efforts to address the research orientation of students. However, these findings point out that, additionally, research anxiety in terms of fear of research courses should be considered and addressed by teachers when conceptualizing research courses.

Keywords: research anxiety, research courses, research interest, research orientation, social work students, teaching

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25639 Influence of the Substitution of C for Mg and Ni on the Microstructure and Hydrogen Storage Characteristics of Mg2Ni Alloys

Authors: Sajad Haghanifar, Seyed-Farshid Kashani Bozorg

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Nano-crystalline Mg2Ni-based powder was produced by mechanical alloying technique using binary and ternary powder mixtures with stoichiometric compositions of Mg2Ni, Mg1.9C0.1Ni and Mg2C0.1Ni0.9. The structures and morphologies of the milled products were studied by XRD, SEM and HRTEM. Their electrochemical hydrogen storage characteristics were investigated in 6 M KOH solution. X-Ray diffraction, scanning and transmission electron microscopy of the milled products showed the formation of Mg2Ni-based nano-crystallites after 5, 15 and 30 h of milling using the initial powder mixtures of Mg1.9C0.1Ni, Mg2Ni and Mg2C0.1Ni0.9, respectively. It was found that partial substitution of C for Mg has beneficial effect on the formation kinetic of nano-crystalline Mg2Ni. Contrary to this, partial substitution of C for Ni was resulted in retardation of formation kinetic of nano-crystalline Mg2Ni. In addition, the negative electrode made from Mg1.9C0.1Ni ternary milled product after 30 hour of milling exhibited the highest initial discharge capacity and longest discharge life. Thus, partial substitution of C for Mg is beneficial to electrode properties of the Mg2Ni-based crystallites. The relation between the discharge capacity and cycling number of mechanically alloyed products was proposed on the basis of the fact that the degradation of discharge capacity was mainly caused by the oxidation of magnesium and nickel. The experimental data fitted the deduced equation well.

Keywords: Mg2Ni, hydrogen absorbing materials, electrochemical properties, nano-crystalline, amorphous, mechanical alloying, carbon

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25638 Numerical Simulation of the Production of Ceramic Pigments Using Microwave Radiation: An Energy Efficiency Study Towards the Decarbonization of the Pigment Sector

Authors: Pedro A. V. Ramos, Duarte M. S. Albuquerque, José C. F. Pereira

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Global warming mitigation is one of the main challenges of this century, having the net balance of greenhouse gas (GHG) emissions to be null or negative in 2050. Industry electrification is one of the main paths to achieving carbon neutrality within the goals of the Paris Agreement. Microwave heating is becoming a popular industrial heating mechanism due to the absence of direct GHG emissions, but also the rapid, volumetric, and efficient heating. In the present study, a mathematical model is used to simulate the production using microwave heating of two ceramic pigments, at high temperatures (above 1200 Celsius degrees). The two pigments studied were the yellow (Pr, Zr)SiO₂ and the brown (Ti, Sb, Cr)O₂. The chemical conversion of reactants into products was included in the model by using the kinetic triplet obtained with the model-fitting method and experimental data present in the Literature. The coupling between the electromagnetic, thermal, and chemical interfaces was also included. The simulations were computed in COMSOL Multiphysics. The geometry includes a moving plunger to allow for the cavity impedance matching and thus maximize the electromagnetic efficiency. To accomplish this goal, a MATLAB controller was developed to automatically search the position of the moving plunger that guarantees the maximum efficiency. The power is automatically and permanently adjusted during the transient simulation to impose stationary regime and total conversion, the two requisites of every converged solution. Both 2D and 3D geometries were used and a parametric study regarding the axial bed velocity and the heat transfer coefficient at the boundaries was performed. Moreover, a Verification and Validation study was carried out by comparing the conversion profiles obtained numerically with the experimental data available in the Literature; the numerical uncertainty was also estimated to attest to the result's reliability. The results show that the model-fitting method employed in this work is a suitable tool to predict the chemical conversion of reactants into the pigment, showing excellent agreement between the numerical results and the experimental data. Moreover, it was demonstrated that higher velocities lead to higher thermal efficiencies and thus lower energy consumption during the process. This work concludes that the electromagnetic heating of materials having high loss tangent and low thermal conductivity, like ceramic materials, maybe a challenge due to the presence of hot spots, which may jeopardize the product quality or even the experimental apparatus. The MATLAB controller increased the electromagnetic efficiency by 25% and global efficiency of 54% was obtained for the titanate brown pigment. This work shows that electromagnetic heating will be a key technology in the decarbonization of the ceramic sector as reductions up to 98% in the specific GHG emissions were obtained when compared to the conventional process. Furthermore, numerical simulations appear as a suitable technique to be used in the design and optimization of microwave applicators, showing high agreement with experimental data.

Keywords: automatic impedance matching, ceramic pigments, efficiency maximization, high-temperature microwave heating, input power control, numerical simulation

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25637 The Impact of Human Intervention on Net Primary Productivity for the South-Central Zone of Chile

Authors: Yannay Casas-Ledon, Cinthya A. Andrade, Camila E. Salazar, Mauricio Aguayo

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The sustainable management of available natural resources is a crucial question for policy-makers, economists, and the research community. Among several, land constitutes one of the most critical resources, which is being intensively appropriated by human activities producing ecological stresses and reducing ecosystem services. In this context, net primary production (NPP) has been considered as a feasible proxy indicator for estimating the impacts of human interventions on land-uses intensity. Accordingly, the human appropriation of NPP (HANPP) was calculated for the south-central regions of Chile between 2007 and 2014. The HANPP was defined as the difference between the potential NPP of the naturally produced vegetation (NPP0, i.e., the vegetation that would exist without any human interferences) and the NPP remaining in the field after harvest (NPPeco), expressed in gC/m² yr. Other NPP flows taken into account in HANPP estimation were the harvested (NPPh) and the losses of NPP through land conversion (NPPluc). The ArcGIS 10.4 software was used for assessing the spatial and temporal HANPP changes. The differentiation of HANPP as % of NPP0 was estimated by each landcover type taken in 2007 and 2014 as the reference years. The spatial results depicted a negative impact on land use efficiency during 2007 and 2014, showing negative HANPP changes for the whole region. The harvest and biomass losses through land conversion components are the leading causes of loss of land-use efficiency. Furthermore, the study depicted higher HANPP in 2014 than in 2007, representing 50% of NPP0 for all landcover classes concerning 2007. This performance was mainly related to the higher volume of harvested biomass for agriculture. In consequence, the cropland depicted the high HANPP followed by plantation. This performance highlights the strong positive correlation between the economic activities developed into the region. This finding constitutes the base for a better understanding of the main driving force influencing biomass productivity and a powerful metric for supporting the sustainable management of land use.

Keywords: human appropriation, land-use changes, land-use impact, net primary productivity

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25636 Sparse Coding Based Classification of Electrocardiography Signals Using Data-Driven Complete Dictionary Learning

Authors: Fuad Noman, Sh-Hussain Salleh, Chee-Ming Ting, Hadri Hussain, Syed Rasul

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In this paper, a data-driven dictionary approach is proposed for the automatic detection and classification of cardiovascular abnormalities. Electrocardiography (ECG) signal is represented by the trained complete dictionaries that contain prototypes or atoms to avoid the limitations of pre-defined dictionaries. The data-driven trained dictionaries simply take the ECG signal as input rather than extracting features to study the set of parameters that yield the most descriptive dictionary. The approach inherently learns the complicated morphological changes in ECG waveform, which is then used to improve the classification. The classification performance was evaluated with ECG data under two different preprocessing environments. In the first category, QT-database is baseline drift corrected with notch filter and it filters the 60 Hz power line noise. In the second category, the data are further filtered using fast moving average smoother. The experimental results on QT database confirm that our proposed algorithm shows a classification accuracy of 92%.

Keywords: electrocardiogram, dictionary learning, sparse coding, classification

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25635 Analyzing Restrictive Refugee Policies in Japan and the United Kingdom: An Examination of Fundamental Causes and Implications

Authors: Shalini Shawari Matharage

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The worldwide refugee challenge has arisen as a critical concern, with millions of individuals fleeing their home countries owing to conflict, persecution, and human rights violations. Since the establishment of an international framework in 1951 for tackling the humanitarian needs of refugees and asylum seekers, many developed and developing countries have adopted a refugee admittance framework into their national immigration policy and steadily changed their domestic legislation to assist the resettlement of refugees. However, many developed nations have put forth strict limitations on refugee admission in the midst of the continuing refugee crisis, claiming factors including national sovereignty, security of their borders, and national economy. Two such developed nations that have been restrictive on refugees is Japan and the United Kingdom. Despite their contrasting histories, migration methods, and viewpoints on diversity in modern society, the two notably developed nations have taken similar restrictive approaches in refugee policy in the recent years. This study attempts to investigate the underlying causes that led these countries to adopt strict refugee policies and how those policies have affected their compliance with international human rights responsibilities. The study employs a head-to-head methodology to examine the structural inequities in Japan and the United Kingdom's refugee policies. Using data from the UNHCR Refugee Data Finder, official government policy proposals, statements, and academic works, the study evaluates the contemporary refugee legislations, fundamental causes, and subsequent implications. The study illustrates a combination of economic, security, and demographic issues, as well as political rigidity and negative public perceptions, as major determinants of the two countries' restrictive refugee policies. The findings shed light on the restrictive actions taken by Japan and the UK, raising concerns about potential breaches in obligations to their commitments to international law and human rights obligations. Understanding the underlying issues influencing these policies allows lawmakers and activists to establish more compassionate refugee policies that adhere to international human rights and protect vulnerable individuals fleeing persecution. Ultimately, this study aims to contribute to the development of sensible refugee policies that uphold human rights and humanitarian values.

Keywords: immigration, Japan, refugee policy, united kingdom

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25634 A Deletion-Cost Based Fast Compression Algorithm for Linear Vector Data

Authors: Qiuxiao Chen, Yan Hou, Ning Wu

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As there are deficiencies of the classic Douglas-Peucker Algorithm (DPA), such as high risks of deleting key nodes by mistake, high complexity, time consumption and relatively slow execution speed, a new Deletion-Cost Based Compression Algorithm (DCA) for linear vector data was proposed. For each curve — the basic element of linear vector data, all the deletion costs of its middle nodes were calculated, and the minimum deletion cost was compared with the pre-defined threshold. If the former was greater than or equal to the latter, all remaining nodes were reserved and the curve’s compression process was finished. Otherwise, the node with the minimal deletion cost was deleted, its two neighbors' deletion costs were updated, and the same loop on the compressed curve was repeated till the termination. By several comparative experiments using different types of linear vector data, the comparison between DPA and DCA was performed from the aspects of compression quality and computing efficiency. Experiment results showed that DCA outperformed DPA in compression accuracy and execution efficiency as well.

Keywords: Douglas-Peucker algorithm, linear vector data, compression, deletion cost

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25633 Multimedia Container for Autonomous Car

Authors: Janusz Bobulski, Mariusz Kubanek

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The main goal of the research is to develop a multimedia container structure containing three types of images: RGB, lidar and infrared, properly calibrated to each other. An additional goal is to develop program libraries for creating and saving this type of file and for restoring it. It will also be necessary to develop a method of data synchronization from lidar and RGB cameras as well as infrared. This type of file could be used in autonomous vehicles, which would certainly facilitate data processing by the intelligent autonomous vehicle management system. Autonomous cars are increasingly breaking into our consciousness. No one seems to have any doubts that self-driving cars are the future of motoring. Manufacturers promise that moving the first of them to showrooms is the prospect of the next few years. Many experts believe that creating a network of communicating autonomous cars will be able to completely eliminate accidents. However, to make this possible, it is necessary to develop effective methods of detection of objects around the moving vehicle. In bad weather conditions, this task is difficult on the basis of the RGB(red, green, blue) image. Therefore, in such situations, you should be supported by information from other sources, such as lidar or infrared cameras. The problem is the different data formats that individual types of devices return. In addition to these differences, there is a problem with the synchronization of these data and the formatting of this data. The goal of the project is to develop a file structure that could be containing a different type of data. This type of file is calling a multimedia container. A multimedia container is a container that contains many data streams, which allows you to store complete multimedia material in one file. Among the data streams located in such a container should be indicated streams of images, films, sounds, subtitles, as well as additional information, i.e., metadata. This type of file could be used in autonomous vehicles, which would certainly facilitate data processing by the intelligent autonomous vehicle management system. As shown by preliminary studies, the use of combining RGB and InfraRed images with Lidar data allows for easier data analysis. Thanks to this application, it will be possible to display the distance to the object in a color photo. Such information can be very useful for drivers and for systems in autonomous cars.

Keywords: an autonomous car, image processing, lidar, obstacle detection

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25632 Mobile Crowdsensing Scheme by Predicting Vehicle Mobility Using Deep Learning Algorithm

Authors: Monojit Manna, Arpan Adhikary

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In Mobile cloud sensing across the globe, an emerging paradigm is selected by the user to compute sensing tasks. In urban cities current days, Mobile vehicles are adapted to perform the task of data sensing and data collection for universality and mobility. In this work, we focused on the optimality and mobile nodes that can be selected in order to collect the maximum amount of data from urban areas and fulfill the required data in the future period within a couple of minutes. We map out the requirement of the vehicle to configure the maximum data optimization problem and budget. The Application implementation is basically set up to generalize a realistic online platform in which real-time vehicles are moving apparently in a continuous manner. The data center has the authority to select a set of vehicles immediately. A deep learning-based scheme with the help of mobile vehicles (DLMV) will be proposed to collect sensing data from the urban environment. From the future time perspective, this work proposed a deep learning-based offline algorithm to predict mobility. Therefore, we proposed a greedy approach applying an online algorithm step into a subset of vehicles for an NP-complete problem with a limited budget. Real dataset experimental extensive evaluations are conducted for the real mobility dataset in Rome. The result of the experiment not only fulfills the efficiency of our proposed solution but also proves the validity of DLMV and improves the quantity of collecting the sensing data compared with other algorithms.

Keywords: mobile crowdsensing, deep learning, vehicle recruitment, sensing coverage, data collection

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25631 Influence of Water Physicochemical Properties and Vegetation Type on the Distribution of Schistosomiasis Intermediate Host Snails in Nelson Mandela Bay

Authors: Prince S. Campbell, Janine B. Adams, Melusi Thwala, Opeoluwa Oyedele, Paula E. Melariri

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Schistosomiasis is an infectious water-borne disease that holds substantial medical and veterinary importance and is transmitted by Schistosoma flatworms. The transmission and spread of the disease are geographically and temporally confined to water bodies (rivers, lakes, lagoons, dams, etc.) inhabited by its obligate intermediate host snails and human water contact. Human infection with the parasite occurs via skin penetration subsequent to exposure to water infested with schistosome cercariae. Environmental factors play a crucial role in the spread of the disease, as the survival of intermediate host snails is dependent on favourable conditions. These factors include physical and chemical components of water, including pH, salinity, temperature, electrical conductivity, dissolved oxygen, turbidity, water hardness, total dissolved solids, and velocity, as well as biological factors such as predator-prey interactions, competition, food availability, and the presence and density of aquatic vegetation. This study evaluated the physicochemical properties of the water bodies, vegetation type, distribution, and habitat presence of the snail intermediate host. A quantitative cross-sectional research design approach was employed in this study. Eight sampling sites were selected based on their proximity to residential areas. Snails and water physicochemical properties were collected over different seasons for 9 months. A simple dip method was used for surface water samples and measurements were done using multiparameter meters. Snails captured using a 300 µm mesh scoop net and predominant plant species were gathered and transported to experts for identification. Vegetation composition and cover were visually estimated and recorded at each sampling point. Data was analysed using R software (version 4.3.1). A total of 844 freshwater snails were collected, with Physa genera accounting for 95.9% of the snails. Bulinus and Biomphalaria snails, which serve as intermediate hosts for the disease, accounted for (0.9%) and (0.6%) respectively. Indicator macrophytes such as Eicchornia crassipes, Stuckenia pectinate, Typha capensis, and floating macroalgae were found in several water bodies. A negative and weak correlation existed between the number of snails and physicochemical properties such as electrical conductivity (r=-0.240), dissolved oxygen (r=-0.185), hardness (r=-0.210), pH (r=-0.235), salinity (r=-0.242), temperature (r=-0.273), and total dissolved solids (r=-0.236). There was no correlation between the number of snails and turbidity (r=-0.070). Moreover, there was a negative and weak correlation between snails and vegetation coverage (r=-0.127). Findings indicated that snail abundance marginally declined with rising physicochemical concentrations, and the majority of snails were located in regions with less vegetation cover. The reduction in Bulinus and Biomphalaria snail populations may also be attributed to other factors, such as competition among the snails. Snails of the Physa genus were abundant due to their noteworthy resilience in difficult environments. These snails have the potential to function as biological control agents in areas where the disease is endemic, as they outcompete other snails, including schistosomiasis intermediate host snails.

Keywords: intermediate host snails, physicochemical properties, schistosomiasis, vegetation type

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25630 Six Years Antimicrobial Resistance Trends among Bacterial Isolates in Amhara National Regional State, Ethiopia

Authors: Asrat Agalu Abejew

Abstract:

Background: Antimicrobial resistance (AMR) is a silent tsunami and one of the top global threats to health care and public health. It is one of the common agendas globally and in Ethiopia. Emerging AMR will be a double burden to Ethiopia, which is facing a series of problems from infectious disease morbidity and mortality. In Ethiopia, although there are attempts to document AMR in healthcare institutions, comprehensive and all-inclusive analysis is still lacking. Thus, this study is aimed to determine trends in AMR from 2016-2021. Methods: A retrospective analysis of secondary data recorded in the Amhara Public Health Institute (APHI) from 2016 to 2021 G.C was conducted. Blood, Urine, Stool, Swabs, Discharge, body effusions, and other Microbiological specimens were collected from each study participants, and Bacteria identification and Resistance tests were done using the standard microbiologic procedure. Data was extracted from excel in August 2022, Trends in AMR were analyzed, and the results were described. In addition, the chi-square (X2) test and binary logistic regression were used, and a P. value < 0.05 was used to determine a significant association. Results: During 6 years period, there were 25143 culture and susceptibility tests. Overall, 265 (46.2%) bacteria were resistant to 2-4 antibiotics, 253 (44.2%) to 5-7 antibiotics, and 56 (9.7%) to >=8 antibiotics. The gram-negative bacteria were 166 (43.9%), 155 (41.5%), and 55 (14.6%) resistant to 2-4, 5-7, and ≥8 antibiotics, respectively, whereas 99(50.8%), 96(49.2% and 1 (0.5%) of gram-positive bacteria were resistant to 2-4, 5-7 and ≥8 antibiotics respectively. K. pneumonia 3783 (15.67%) and E. coli 3199 (13.25%) were the most commonly isolated bacteria, and the overall prevalence of AMR was 2605 (59.9%), where K. pneumonia 743 (80.24%), E. cloacae 196 (74.81%), A. baumannii 213 (66.56%) being the most common resistant bacteria for antibiotics tested. Except for a slight decline during 2020 (6469 (25.4%)), the overall trend of AMR is rising from year to year, with a peak in 2019 (8480 (33.7%)) and in 2021 (7508 (29.9%). If left un-intervened, the trend in AMR will increase by 78% of variation from the study period, as explained by the differences in years (R2=0.7799). Ampicillin, Augmentin, ciprofloxacin, cotrimoxazole, tetracycline, and Tobramycin were almost resistant to common bacteria they were tested. Conclusion: AMR is linearly increasing during the last 6 years. If left as it is without appropriate intervention after 15 years (2030 E.C), AMR will increase by 338.7%. A growing number of multi-drug resistant bacteria is an alarm to awake policymakers and those who do have the concern to intervene before it is too late. This calls for a periodic, integrated, and continuous system to determine the prevalence of AMR in commonly used antibiotics.

Keywords: AMR, trend, pattern, MDR

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25629 A Biometric Template Security Approach to Fingerprints Based on Polynomial Transformations

Authors: Ramon Santana

Abstract:

The use of biometric identifiers in the field of information security, access control to resources, authentication in ATMs and banking among others, are of great concern because of the safety of biometric data. In the general architecture of a biometric system have been detected eight vulnerabilities, six of them allow obtaining minutiae template in plain text. The main consequence of obtaining minutia templates is the loss of biometric identifier for life. To mitigate these vulnerabilities several models to protect minutiae templates have been proposed. Several vulnerabilities in the cryptographic security of these models allow to obtain biometric data in plain text. In order to increase the cryptographic security and ease of reversibility, a minutiae templates protection model is proposed. The model aims to make the cryptographic protection and facilitate the reversibility of data using two levels of security. The first level of security is the data transformation level. In this level generates invariant data to rotation and translation, further transformation is irreversible. The second level of security is the evaluation level, where the encryption key is generated and data is evaluated using a defined evaluation function. The model is aimed at mitigating known vulnerabilities of the proposed models, basing its security on the impossibility of the polynomial reconstruction.

Keywords: fingerprint, template protection, bio-cryptography, minutiae protection

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25628 Improving Digital Data Security Awareness among Teacher Candidates with Digital Storytelling Technique

Authors: Veysel Çelik, Aynur Aker, Ebru Güç

Abstract:

Developments in information and communication technologies have increased both the speed of producing information and the speed of accessing new information. Accordingly, the daily lives of individuals have started to change. New concepts such as e-mail, e-government, e-school, e-signature have emerged. For this reason, prospective teachers who will be future teachers or school administrators are expected to have a high awareness of digital data security. The aim of this study is to reveal the effect of the digital storytelling technique on the data security awareness of pre-service teachers of computer and instructional technology education departments. For this purpose, participants were selected based on the principle of volunteering among third-grade students studying at the Computer and Instructional Technologies Department of the Faculty of Education at Siirt University. In the research, the pretest/posttest half experimental research model, one of the experimental research models, was used. In this framework, a 6-week lesson plan on digital data security awareness was prepared in accordance with the digital narration technique. Students in the experimental group formed groups of 3-6 people among themselves. The groups were asked to prepare short videos or animations for digital data security awareness. The completed videos were watched and evaluated together with prospective teachers during the evaluation process, which lasted approximately 2 hours. In the research, both quantitative and qualitative data collection tools were used by using the digital data security awareness scale and the semi-structured interview form consisting of open-ended questions developed by the researchers. According to the data obtained, it was seen that the digital storytelling technique was effective in creating data security awareness and creating permanent behavior changes for computer and instructional technology students.

Keywords: digital storytelling, self-regulation, digital data security, teacher candidates, self-efficacy

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25627 A Remote Sensing Approach to Calculate Population Using Roads Network Data in Lebanon

Authors: Kamel Allaw, Jocelyne Adjizian Gerard, Makram Chehayeb, Nada Badaro Saliba

Abstract:

In developing countries, such as Lebanon, the demographic data are hardly available due to the absence of the mechanization of population system. The aim of this study is to evaluate, using only remote sensing data, the correlations between the number of population and the characteristics of roads network (length of primary roads, length of secondary roads, total length of roads, density and percentage of roads and the number of intersections). In order to find the influence of the different factors on the demographic data, we studied the degree of correlation between each factor and the number of population. The results of this study have shown a strong correlation between the number of population and the density of roads and the number of intersections.

Keywords: population, road network, statistical correlations, remote sensing

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25626 Diagnostic Accuracy of the Tuberculin Skin Test for Tuberculosis Diagnosis: Interest of Using ROC Curve and Fagan’s Nomogram

Authors: Nouira Mariem, Ben Rayana Hazem, Ennigrou Samir

Abstract:

Background and aim: During the past decade, the frequency of extrapulmonary forms of tuberculosis has increased. These forms are under-diagnosed using conventional tests. The aim of this study was to evaluate the performance of the Tuberculin Skin Test (TST) for the diagnosis of tuberculosis, using the ROC curve and Fagan’s Nomogram methodology. Methods: This was a case-control, multicenter study in 11 anti-tuberculosis centers in Tunisia, during the period from June to November2014. The cases were adults aged between 18 and 55 years with confirmed tuberculosis. Controls were free from tuberculosis. A data collection sheet was filled out and a TST was performed for each participant. Diagnostic accuracy measures of TST were estimated using ROC curve and Area Under Curve to estimate sensitivity and specificity of a determined cut-off point. Fagan’s nomogram was used to estimate its predictive values. Results: Overall, 1053 patients were enrolled, composed of 339 cases (sex-ratio (M/F)=0.87) and 714 controls (sex-ratio (M/F)=0.99). The mean age was 38.3±11.8 years for cases and 33.6±11 years for controls. The mean diameter of the TST induration was significantly higher among cases than controls (13.7mm vs.6.2mm;p=10-6). Area Under Curve was 0.789 [95% CI: 0.758-0.819; p=0.01], corresponding to a moderate discriminating power for this test. The most discriminative cut-off value of the TST, which were associated with the best sensitivity (73.7%) and specificity (76.6%) couple was about 11 mm with a Youden index of 0.503. Positive and Negative predictive values were 3.11% and 99.52%, respectively. Conclusion: In view of these results, we can conclude that the TST can be used for tuberculosis diagnosis with a good sensitivity and specificity. However, the skin induration measurement and its interpretation is operator dependent and remains difficult and subjective. The combination of the TST with another test such as the Quantiferon test would be a good alternative.

Keywords: tuberculosis, tuberculin skin test, ROC curve, cut-off

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25625 A Multicopy Strategy for Improved Security Wireless Sensor Network

Authors: Tuğçe Yücel

Abstract:

A Wireless Sensor Network(WSN) is a collection of sensor nodes which are deployed randomly in an area for surveillance. Efficient utilization of limited battery energy of sensors for increased network lifetime as well as data security are major design objectives for WSN. Moreover secure transmission of data sensed to a base station for further processing. Producing multiple copies of data packets and sending them on different paths is one of the strategies for this purpose, which leads to redundant energy consumption and hence reduced network lifetime. In this work we develop a restricted multi-copy multipath strategy where data move through ‘frequently’ or ‘heavily’ used sensors is copied by the sensor incident to such central nodes and sent on node-disjoint paths. We develop a mixed integer programing(MIP) model and heuristic approach present some preleminary test results.

Keywords: MIP, sensor, telecommunications, WSN

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25624 Dishonesty and Achievement: An Experiment of Self-Revealing Individual Cheating

Authors: Gideon Yaniv, Erez Siniver, Yossef Tobol

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The extensive body of economic and psychological research correlating between students' cheating and their grade point average (GPA) consistently finds a significant negative relationship between cheating and the GPA. However, this literature is entirely based on students' responses to direct question surveys that inquire whether they have ever cheated on their academic assignments. The present paper reports the results of a two-round experiment designed to expose student cheating at the individual level and correlate it with their GPAs. The experiment involved two classes of third-year economics students incentivized by a competitive reward to answer a multiple-choice trivia quiz without consulting their electronic devices. While this forbiddance was deliberately overlooked in the first round, providing an opportunity to cheat, it was strictly enforced in the second, conducted two months later in the same classes with the same quiz. A comparison of subjects' performance in the two rounds, self-revealed a considerable extent of cheating in the first one. Regressing the individual cheating levels on subjects' gender and GPA exhibited no significant differences in cheating between males and females. However, cheating of both genders was found to significantly increase with their GPA, implying, in sharp contrast with the direct question surveys, that higher achievers are bigger cheaters. A second experiment, which allowed subjects to answer the quiz in the privacy of their own cars, reveals that when really feeling safe to cheat, many subjects would cheat maximally, challenging the literature's claim that people generally cheat modestly.

Keywords: academic achievement, cheating behavior, experimental data, grade-point average

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25623 Wikipedia World: A Computerized Process for Cultural Heritage Data Dissemination

Authors: L. Rajaonarivo, M. N. Bessagnet, C. Sallaberry, A. Le Parc Lacayrelle, L. Leveque

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TCVPYR is a European FEDER (European Regional Development Fund) project which aims to promote tourism in the French Pyrenees region by leveraging its cultural heritage. It involves scientists from various domains (geographers, historians, anthropologists, computer scientists...). This paper presents a fully automated process to publish any dataset as Wikipedia articles as well as the corresponding linked information on Wikidata and Wikimedia Commons. We validate this process on a sample of geo-referenced cultural heritage data collected by TCVPYR researchers in different regions of the Pyrenees. The main result concerns the technological prerequisites, which are now in place. Moreover, we demonstrated that we can automatically publish cultural heritage data on Wikimedia.

Keywords: cultural heritage dissemination, digital humanities, open data, Wikimedia automated publishing

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25622 Adaptive Decision Feedback Equalizer Utilizing Fixed-Step Error Signal for Multi-Gbps Serial Links

Authors: Alaa Abdullah Altaee

Abstract:

This paper presents an adaptive decision feedback equalizer (ADFE) for multi-Gbps serial links utilizing a fix-step error signal extracted from cross-points of received data symbols. The extracted signal is generated based on violation of received data symbols with minimum detection requirements at the clock and data recovery (CDR) stage. The iterations of the adaptation process search for the optimum feedback tap coefficients to maximize the data eye-opening and minimize the adaptation convergence time. The effectiveness of the proposed architecture is validated using the simulation results of a serial link designed in an IBM 130 nm 1.2V CMOS technology. The data link with variable channel lengths is analyzed using Spectre from Cadence Design Systems with BSIM4 device models.

Keywords: adaptive DFE, CMOS equalizer, error detection, serial links, timing jitter, wire-line communication

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25621 Data-Driven Market Segmentation in Hospitality Using Unsupervised Machine Learning

Authors: Rik van Leeuwen, Ger Koole

Abstract:

Within hospitality, marketing departments use segmentation to create tailored strategies to ensure personalized marketing. This study provides a data-driven approach by segmenting guest profiles via hierarchical clustering based on an extensive set of features. The industry requires understandable outcomes that contribute to adaptability for marketing departments to make data-driven decisions and ultimately driving profit. A marketing department specified a business question that guides the unsupervised machine learning algorithm. Features of guests change over time; therefore, there is a probability that guests transition from one segment to another. The purpose of the study is to provide steps in the process from raw data to actionable insights, which serve as a guideline for how hospitality companies can adopt an algorithmic approach.

Keywords: hierarchical cluster analysis, hospitality, market segmentation

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25620 Comprehensive Analysis of RNA m5C Regulator ALYREF as a Suppressive Factor of Anti-tumor Immune and a Potential Tumor Prognostic Marker in Pan-Cancer

Authors: Yujie Yuan, Yiyang Fan, Hong Fan

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Objective: The RNA methylation recognition protein Aly/REF export factor (ALYREF) is considered one type of “reader” protein acting as a recognition protein of m5C, has been reported involved in several biological progresses including cancer initiation and progression. 5-methylcytosine (m5C) is a conserved and prevalent RNA modification in all species, as accumulating evidence suggests its role in the promotion of tumorigenesis. It has been claimed that ALYREF mediates nuclear export of mRNA with m5C modification and regulates biological effects of cancer cells. However, the systematical regulatory pathways of ALYREF in cancer tissues have not been clarified, yet. Methods: The expression level of ALYREF in pan-cancer and their normal tissues was compared through the data acquired from The Cancer Genome Atlas (TCGA). The University of Alabama at Birmingham Cancer data analysis Portal UALCAN was used to analyze the relationship between ALYREF and clinical pathological features. The relationship between the expression level of ALYREF and prognosis of pan-cancer, and the correlation genes of ALYREF were figured out by using Gene Expression Correlation Analysis database GEPIA. Immune related genes were obtained from TISIDB (an integrated repository portal for tumor-immune system interactions). Immune-related research was conducted by using Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) and TIMER. Results: Based on the data acquired from TCGA, ALYREF has an obviously higher-level expression in various types of cancers compared with relevant normal tissues excluding thyroid carcinoma and kidney chromophobe. The immunohistochemical images on The Human Protein Atlas showed that ALYREF can be detected in cytoplasm, membrane, but mainly located in nuclear. In addition, a higher expression level of ALYREF in tumor tissue generates a poor prognosis in majority of cancers. According to the above results, cancers with a higher expression level of ALYREF compared with normal tissues and a significant correlation between ALYREF and prognosis were selected for further analysis. By using TISIDB, we found that portion of ALYREF co-expression genes (such as BIRC5, H2AFZ, CCDC137, TK1, and PPM1G) with high Pearson correlation coefficient (PCC) were involved in anti-tumor immunity or affect resistance or sensitivity to T cell-mediated killing. Furthermore, based on the results acquired from GEPIA, there was significant correlation between ALYREF and PD-L1. It was exposed that there is a negative correlation between the expression level of ALYREF and ESTIMATE score. Conclusion: The present study indicated that ALYREF plays a vital and universal role in cancer initiation and progression of pan-cancer through regulating mitotic progression, DNA synthesis and metabolic process, and RNA processing. The correlation between ALYREF and PD-L1 implied ALYREF may affect the therapeutic effect of immunotherapy of tumor. More evidence revealed that ALYREF may play an important role in tumor immunomodulation. The correlation between ALYREF and immune cell infiltration level indicated that ALYREF can be a potential therapeutic target. Exploring the regulatory mechanism of ALYREF in tumor tissues may expose the reason for poor efficacy of immunotherapy and offer more directions of tumor treatment.

Keywords: ALYREF, pan-cancer, immunotherapy, PD-L1

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25619 High Heating Value Bio-Chars from a Bio-Oil Upgrading Process

Authors: Julius K. Gane, Mohamad N. Nahil, Paul T. Williams

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In today’s world of rapid population growth and a changing climate, one way to mitigate various negative effects is via renewable energy solutions. Energy and power as basic requirements in almost all human endeavours are also the banes of the changing climate and the impacts thereof. Thus it is crucial to develop innovative and environmentally friendly energy options to ameliorate various negative repercussions. Upgrading of fast pyrolysis bio-oil via hydro-treatment offers such opportunities, as quality renewable liquid transportation fuels can be produced. The process, however, is typically accompanied by bio-char formation as a by-product. The goal of this work was to study the yield and some properties of bio-chars formed from a hydrotreatment process, with an overall aim to promote the valuable utilization of wastes or by-products from renewable energy technologies. It is assumed that bio-chars that have comparable energy contents with coals will be more desirable as solid energy materials due to renewability and environmental friendliness. Therefore, the analytical work in this study focused mainly on determining the higher heating value (HHV) of the chars. The method involved the reaction of bio-oil in an autoclave supplied by the Parr Instrument Company, IL, USA. Two main parameters (different temperatures and resident times) were investigated. The chars were characterized using a Thermo EA2000 CHNS analyser, then oxygen contents and HHVs computed based on the literature. From the results, these bio-chars can readily serve as feedstocks for the production of renewable solid fuels. Their HHVs ranged between 29.26-39.18 MJ/kg, affected by different temperatures and retention times. There was an inverse relationship between the oxygen content and the HHVs of the chars. It can, therefore, be concluded that it is possible to optimize the process efficiency of the hydrotreatment process used through the production of renewable energy materials from the 'waste’ char by-products. Future work should consider developing a suitable balance between the primary objective of bio-oil upgrading processes (which is to improve the quality of the liquid fuels) and the conversion of its solid wastes into value-added products such as smokeless briquettes.

Keywords: bio-char, renewable solid biofuels, valorisation, waste-to-energy

Procedia PDF Downloads 124