Search results for: data protection

Authors: Maryam Khalilzadeh Poshtegal, Seyed Ahmad Mirbagheri, Mojtaba Noury

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In this paper, by application of the input yearly data of rainfall, temperature and flow to the Urmia Lake, the simulation of water level fluctuation were applied by means of three models. According to the climate change investigation the fluctuation of lakes water level are of high interest. This study investigate data-driven models, support vector machines (SVM), SVM method which is a new regression procedure in water resources are applied to the yearly level data of Lake Urmia that is the biggest and the hyper saline lake in Iran. The evaluated lake levels are found to be in good correlation with the observed values. The results of SVM simulation show better accuracy and implementation. The mean square errors, mean absolute relative errors and determination coefficient statistics are used as comparison criteria.

Keywords: simulation, water level fluctuation, urmia lake, support vector machine

Procedia PDF Downloads 358

Authors: H. Elmsellem, A. Aouniti, S. Radi, A. Chetouani, B. Hammouti

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The synthesis of new organic molecules offers various molecular structures containing heteroatoms and substituents for corrosion protection in acid pickling of metals. The most synthesized compounds are the nitrogen heterocyclic compounds, which are known to be excellent complex or chelate forming substances with metals. The choice of the inhibitor is based on two considerations: first it could be synthesized conveniently from relatively cheap raw materials, secondly, it contains the electron cloud on the aromatic ring or, the electro negative atoms such as nitrogen and oxygen in the relatively long chain compounds. In the present study, (NE)‐2‐methyl‐N‐(thiophen‐2‐ylmethylidene) aniline(T) was synthesized and its inhibiting action on the corrosion of mild steel in 1 M hydrochloric acid was examined by different corrosion methods, such as weight loss, potentiodynamic polarization and electrochemical impedance spectroscopy (EIS). The experimental results suggest that this compound is an efficient corrosion inhibitor and the inhibition efficiency increases with the increase in inhibitor concentration. Adsorption of this compound on mild steel surface obeys Langmuir’s isotherm. Correlation between quantum chemical calculations and inhibition efficiency of the investigated compound is discussed using the Density Functional Theory method (DFT).

Keywords: mild steel, Schiff base, inhibition, corrosion, HCl, quantum chemical

Procedia PDF Downloads 323

Authors: Nor Mazlin Zahari, Lian Gan, Xuerui Mao

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The power production in wind farms and the mechanical loads on the turbines are strongly impacted by the wake of the wind turbine. Thus, there is a need for understanding and modelling the turbine wake dynamic in the wind farm and the layout optimization. Having a good wake model is important in predicting plant performance and understanding fatigue loads. In this paper, the Dynamic Mode Decomposition (DMD) was applied to the simulation data generated by a Direct Numerical Simulation (DNS) of flow around a turbine, perturbed by upstream inflow noise. This technique is useful in analyzing the wake flow, to predict its future states and to reflect flow dynamics associated with the coherent structures behind wind turbine wake flow. DMD was employed to describe the dynamic of the flow around turbine from the DNS data. Since the DNS data comes with the unstructured meshes and non-uniform grid, the interpolation of each occurring within each element in the data to obtain an evenly spaced mesh was performed before the DMD was applied. DMD analyses were able to tell us characteristics of the travelling waves behind the turbine, e.g. the dominant helical flow structures and the corresponding frequencies. As the result, the dominant frequency will be detected, and the associated spatial structure will be identified. The dynamic mode which represented the coherent structure will be presented.

Keywords: coherent structure, Direct Numerical Simulation (DNS), dominant frequency, Dynamic Mode Decomposition (DMD)

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Authors: Laura Fernanda Pedreros Araque, Sebastian Rivera Pardo

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The massive removal phenomena have been one of the most frequent natural disasters in the world, causing thousands of deaths, victims, damage to homes and diseases. In Pitalito, and Campoalegre department of Huila municipalities - Colombia, disasters have occurred due to various events such as high rainfall, earthquakes; it has caused landslides, floods, among others, affected the economy, the community, and transportation. For this reason, a study was carried out on the area’s most prone to suffer these phenomena to take preventive measures in favor of the protection of the population, the resources of management, and the planning of civil works. For the proposed object, the Mora-Varshon method was used, which allows classifying the degree of susceptibility to landslides in which the areas are found. Also, various factors or parameters were evaluated such as the soil moisture, lithology, slope, seismicity, and rain, each of these indicators were obtained using information from IDEAM, Servicio Geologico Colombiano (SGC) and using geographic information for geoprocessing in the Arcgis software to realize a mapping to indicate the susceptibility to landslides, classifying the areas of the municipalities such as very low, low, medium, moderate, high or very high.

Keywords: geographic information system, landslide, mass removal phenomena, Mora-Varshon method

Procedia PDF Downloads 137

Authors: Amadou Fall Dia, Maurras Ulbricht Togbe, Aliou Boly, Zakia Kazi Aoul, Elisabeth Metais

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Existing RDF (Resource Description Framework) Stream Processing (RSP) systems allow continuous processing of RDF data issued from different application domains such as weather station measuring phenomena, geolocation, IoT applications, drinking water distribution management, and so on. However, processing window phase often expires before finishing the entire session and RSP systems immediately delete data streams after each processed window. Such mechanism does not allow optimized exploitation of the RDF data streams as the most relevant and pertinent information of the data is often not used in a due time and almost impossible to be exploited for further analyzes. It should be better to keep the most informative part of data within streams while minimizing the memory storage space. In this work, we propose an RDF graph summarization system based on an explicit and implicit expressed needs through three main approaches: (1) an approach for user queries (SPARQL) in order to extract their needs and group them into a more global query, (2) an extension of the closeness centrality measure issued from Social Network Analysis (SNA) to determine the most informative parts of the graph and (3) an RDF graph summarization technique combining extracted user query needs and the extended centrality measure. Experiments and evaluations show efficient results in terms of memory space storage and the most expected approximate query results on summarized graphs compared to the source ones.

Keywords: centrality measures, RDF graphs summary, RDF graphs stream, SPARQL query

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Authors: Khuram Nawaz Sadozai, Rizwan Ahmad, Munawar Raza Kazmi, Awais Habib

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Climate change and crop production are intrinsically associated with each other. Therefore, this research study is designed to assess the impact of climate change on pulses production in Southern districts of Khyber Pakhtunkhwa (KP) Province of Pakistan. Two pulses (i.e. chickpea and mung bean) were selected for this research study with respect to climate change. Climatic variables such as temperature, humidity and precipitation along with pulses production and area under cultivation of pulses were encompassed as the major variables of this study. Secondary data of climatic variables and crop variables for the period of thirty four years (1986-2020) were obtained from Pakistan Metrological Department and Agriculture Statistics of KP respectively. Panel data set of chickpea and mung bean crops was estimated separately. The analysis validate that both data sets were a balanced panel data. The Hausman specification test was run separately for both the panel data sets whose findings had suggested the fixed effect model can be deemed as an appropriate model for chickpea panel data, however random effect model was appropriate for estimation of the panel data of mung bean. Major findings confirm that maximum temperature is statistically significant for the chickpea yield. This implies if maximum temperature increases by 1 0C, it can enhance the chickpea yield by 0.0463 units. However, the impact of precipitation was reported insignificant. Furthermore, the humidity was statistically significant and has a positive association with chickpea yield. In case of mung bean the minimum temperature was significantly contributing in the yield of mung bean. This study concludes that temperature and humidity can significantly contribute to enhance the pulses yield. It is recommended that capacity building of pulses growers may be made to adapt the climate change strategies. Moreover, government may ensure the availability of climate change resistant varieties of pulses to encourage the pulses cultivation.

Keywords: climate change, pulses productivity, agriculture, Pakistan

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Authors: Anna Wszołek

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For a very long time, the doctor-patient relationship had a paternalistic character. The events of the II World War, as well as fast development of the biotechnology and medicine caused an important change in that relationship. Human beings and their dignity were put in the centre of philosophical and legal debate. The increasing frequency of clinical trials led to the emergence of bioethics, which dealt with the topic of the possibilities and boundaries of such research in relation to individual’s autonomy. Thus, there was a transformation from a paternalistic relationship to a more collaborative one in which the patient has more room for self-determination. Today, patients are more and more aware of their rights and the obligations placed on doctors and the health care system, which is linked to an increase in medical malpractice claims. Unfortunately, these claims are not always justified. There is a strong concentration around the topic of patient’s good, however, at the other side there are doctors who feel, on the example of Poland, they might be easily accused and sued for medical malpractice even though they fulfilled their duties. Such situation may have a negative impact on the quality of health care services and patient’s interests. This research is going to present doctor’s perspective on the topic of medical malpractice allegations. It is supposed to show possible damage to a doctor’s reputation caused by frivolous and weakly justified medical malpractice accusations, as well as means to protect this reputation.

Keywords: doctor's reputation, medical malpractice, personal rights, unjustified allegations

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Authors: Huang Dennis, Aurelio Aziel, Burra Venkata Durga Kumar

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Nowadays, smartphones and mobile operating systems have been popularly widespread in our daily lives. As people use smartphones, they tend to store more private and essential data on their devices, because of this it is very important to develop more secure mobile operating systems and cloud storage to secure the data. However, several factors can cause security risks in mobile operating systems such as malware, malicious app, phishing attacks, ransomware, and more, all of which can cause a big problem for users as they can access the user's private data. Those problems can cause data loss, financial loss, identity theft, and other serious consequences. Other than that, during the pandemic, people will use their mobile devices more and do all sorts of transactions online, which may lead to more victims of online scams and inexperienced users being the target. With the increase in attacks, researchers have been actively working to develop several countermeasures to enhance the security of operating systems. This study aims to provide an overview of the security and privacy issues in mobile operating systems, identifying the potential risk of operating systems, and the possible solutions. By examining these issues, we want to provide an easy understanding to users and researchers to improve knowledge and develop more secure mobile operating systems.

Keywords: mobile operating system, security, privacy, Malware

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Authors: Stella C. Okenu, Stephen O. Adikwu, Martins E. Okoro

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The geothermal energy resource potential of the Lower Benue Trough (LBT) in Nigeria was evaluated in this study using spectral analysis of high-resolution aeromagnetic (HRAM) data. The reduced to the equator aeromagnetic data was divided into sixteen (16) overlapping blocks, and each of the blocks was analyzed to obtain the radial averaged power spectrum which enabled the computation of the top and centroid depths to magnetic sources. The values were then used to assess the Curie Point Depth (CPD), geothermal gradients, and heat flow variations in the study area. Results showed that CPD varies from 7.03 to 18.23 km, with an average of 12.26 km; geothermal gradient values vary between 31.82 and 82.50°C/km, with an average of 51.21°C/km, while heat flow variations range from 79.54 to 206.26 mW/m², with an average of 128.02 mW/m². Shallow CPD zones that run from the eastern through the western and southwestern parts of the study area correspond to zones of high geothermal gradient values and high subsurface heat flow distributions. These areas signify zones associated with anomalous subsurface thermal conditions and are therefore recommended for detailed geothermal energy exploration studies.

Keywords: geothermal energy, curie-point depth, geothermal gradient, heat flow, aeromagnetic data, LBT

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Authors: K. M. Somawathie, V. Rizliya, H. A. M. Wickrmasinghe, Terrence Madhujith

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The main objective of our study was to determine the in vitro antioxidant and DNA protectant activity of aqueous extract of S. melongena with different skin colors; dark purple (DP), moderately purple (MP), light purple (LP) and purple and green (PG). The antioxidant activity was evaluated using the DPPH and ABTS free radical scavenging assay, ferric reducing antioxidant power (FRAP), ferric thiocyanate (FTC) and the egg yolk model. The effectiveness of eggplant extracts against radical induced DNA damage was also determined. There was a significant difference (p < 0.0001) between the skin color and antioxidant activity. TPC and FRAP values of eggplant extracts ranged from 48.67±0.27-61.11±0.26 (mg GAE/100 g fresh weight) and 4.19±0.11-7.46±0.26 (mmol of FeS04/g of fresh weight) respectively. MP displayed the highest percentage of DPPH radical scavenging activity while, DP demonstrated the strongest total antioxidant capacity. In the FTC and egg yolk model, DP and MP showed better antioxidant activity than PG and LP. All eggplant extracts showed potent antioxidant activity in retaining DNA against AAPH mediated radical damage. DP and MP demonstrated better antioxidant activity which may be attributed to the higher phenolic content since a positive correlation was observed between the TPC and the antioxidant parameters.

Keywords: Solanum melongena, skin color, antioxidant, DNA protection, lipid peroxidation

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Authors: Vo Thi Hai Quan

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Nam Con Son sedimentary basin is one of the very important oil and gas basins in offshore Vietnam. Hai Thach field of block 05-2 contains mostly gas accumulations in fine-grained, sand/mud-rich turbidite system, which was deposited in a turbidite channel and fan environment. Major Upper Miocene reservoir of HT-3X lies above a well-developed unconformity. The main objectives of this study are to reconstruct depositional environment and to assess the reservoir quality using data from 14 meters of core samples and digital wireline data of the well HT-3X. The wireline log and core data showed that the vertical sequences of representative facies of the well mainly range from Tb to Te divisions of Bouma sequences with predominance of Tb and Tc compared to Td and Te divisions. Sediments in this well were deposited in a submarine fan association with very fine to fine-grained, homogeneous sandstones that have high porosity and permeability, high- density turbidity currents with longer transport route from the sediment source to the basin, indicating good quality of reservoir. Sediments are comprised mainly of the following sedimentary structures: massive, laminated sandstones, convoluted bedding, laminated ripples, cross-laminated ripples, deformed sandstones, contorted bedding.

Keywords: Hai Thach field, Miocene sand, turbidite, wireline data

Procedia PDF Downloads 291

Authors: Jeremy Moloney

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A major oil and gas operator in western Canada producing approximately 50,000 BOE per day of sour fluids was experiencing increased water production along with decreased oil production over several years. The higher water volumes being produced meant an increase in the operator’s incumbent corrosion inhibitor (CI) chemical requirements but with reduced oil production revenues. Thus, a cost-effective corrosion inhibitor solution was sought to deliver enhanced corrosion mitigation of the carbon steel pipeline infrastructure but at reduced chemical injection dose rates. This paper presents the laboratory work conducted on the development of a corrosion inhibitor under the operator’s simulated sour operating conditions and then subsequent field testing of the product. The new CI not only provided extremely good levels of general and localized corrosion inhibition and outperformed the incumbent CI under the laboratory test conditions but did so at vastly lower concentrations. In turn, the novel CI product facilitated field chemical injection rates to be optimized and reduced by 40% compared with the incumbent whilst maintaining superior corrosion protection resulting in significant cost savings and associated sustainability benefits for the operator.

Keywords: carbon steel, sour gas, hydrogen sulphide, localized corrosion, pitting, corrosion inhibitor

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Authors: Ji Wenzhan, Zhang Tao, Li Guoyou

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Concrete is the most widely used building material in the world. At the same time, the world produces a large amount of construction waste each year. Waste concrete is processed and treated, and the recycled aggregate is used to make pervious concrete, which enables the construction waste to be recycled. Pervious concrete has many advantages such as permeability to water, protection of water resources, and so on. This paper tests the recycled aggregate obtained by crushing high-strength waste concrete (TOU) and low-strength waste concrete (PU), and analyzes the effect of porosity, amount of cement, mineral admixture and recycled aggregate on the strength of permeable concrete. The porosity is inversely proportional to the strength, and the amount of cement used is proportional to the strength. The mineral admixture can effectively improve the workability of the mixture. The quality of recycled aggregates had a significant effect on strength. Compared with concrete using "PU" aggregates, the strength of 7d and 28d concrete using "TOU" aggregates increased by 69.0% and 73.3%, respectively. Therefore, the quality of recycled aggregates should be strictly controlled during production, and the mix ratio should be designed according to different use environments and usage requirements. This test prepared a recycled aggregate permeable concrete with a compressive strength of 35.8 MPa, which can be used for light load roads and provides a reference for engineering applications.

Keywords: recycled aggregate, permeable concrete, compressive strength, permeability

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Authors: Saseyi Olaitan Olaoluwa, Osifeko Olalekan Remigious

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The study was meant to identify the impediments to female sports management and participation in the selected colleges. Seven colleges of education in the south west parts of the country were selected for the study. A total of one hundred and five subjects were sampled to supply data. Only one hundred adequately completed and returned, copies of the questionnaire were used for data analysis. The collected data were analysed descriptively. The result of the study showed that inadequate fund, personnel, facilities equipment, supplies, management of sports, supervision and coaching were some of the impediments to female sports management and participation. Athletes were not encouraged to participate. Based on the findings, it was recommended that the government should come to the aid of the colleges by providing fund and other needs that will make sports attractive for enhanced participation.

Keywords: female sports, impediments, management, Nigeria, south west, colleges

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Authors: Saba Belgheisi

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Food packaging, is an important discipline in the area of food technology, concerns preservation and protection of foods. The objective of this research was to determine of the effect of whey protein based edible coating on the moisture loss and sensory attributes of fresh mutton after 0, 1, 3 and 5 days at 5° C. The moisture content, moisture loss and sensory attributes (juiciness, color and odor) of the coated and uncoated samples were analyzed. The results showed that, moisture content, moisture loss, juiciness and color of the coated and uncoated samples have significant differences (p < 0.05) at the intervals of 0 to 1 and 1 to 3 days of storage. But no significant difference was observed at interval time 3 to 5 days of storage (p > 0.05). Also, there was no significant differences in the odor values of the coated and uncoated samples (p > 0.05). Therefore, the coated samples had consistently more moisture, juiciness and colored values than uncoated samples after 3 days at 5° C. So, whey protein edible coating could enhance product presentation and eliminate the need for placing absorbent pads at the bottom of the trays.

Keywords: coating, whey protein, mutton, moisture, sensory

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Authors: Kulwinder Singh Mann

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The innovative features of information system, known as Radiology Information System (RIS), for electronic medical records has shown a good impact in the hospital. The objective is to help and make their work easier; such as for a physician to access the patient’s data and for a patient to check their bill transparently. The interoperability of RIS with the other intra-hospital information systems it interacts with, dealing with the compatibility and open architecture issues, are accomplished by two novel mechanisms. The first one is the particular message handling system that is applied for the exchange of information, according to the Health Level Seven (HL7) protocol’s specifications and serves the transfer of medical and administrative data among the RIS applications and data store unit. The second one implements the translation of information between the formats that HL7 and Digital Imaging and Communication in Medicine (DICOM) protocols specify, providing the communication between RIS and Picture and Archive Communication System (PACS) which is used for the increasing incorporation of modern medical imaging equipment.

Keywords: RIS, PACS, HIS, HL7, DICOM, messaging service, interoperability, digital images

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Authors: Win Thandar Soe, Innocent Mpawenimana, Mathieu Di Fazio, Cécile Belleudy, Aung Ze Ya

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Intelligent electronic equipment and automation network is the brain of high-tech energy management systems in critical role of smart homes dominance. Smart home is a technology integration for greater comfort, autonomy, reduced cost, and energy saving as well. These services can be provided to home owners for managing their home appliances locally or remotely and consequently allow them to automate intelligently and responsibly their consumption by individual or collective control systems. In this study, three smart plugs are described and one of them tested on typical household appliances. This article proposes to collect the data from the wireless technology and to extract some smart data for energy management system. This smart data is to quantify for three kinds of load: intermittent load, phantom load and continuous load. Phantom load is a waste power that is one of unnoticed power of each appliance while connected or disconnected to the main. Intermittent load and continuous load take in to consideration the power and using time of home appliances. By analysing the classification of loads, this smart data will be provided to reduce the communication of wireless sensor network for energy management system.

Keywords: energy management, load profile, smart plug, wireless sensor network

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Authors: Angel Fabian Mijangos, Jaime Alvarez Quintana

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Key concepts like waste heat recycling or waste heat recovery are the basic ideas in thermoelectricity so as to the design the newest solid state sources of energy for a stable supply of electricity and environmental protection. According to several theoretical predictions; at device level, the geometry and configuration of the thermoelectric legs are crucial in the thermoelectric performance of the thermoelectric modules. Thus, in this work, it has studied the geometry effect of legs on the thermoelectric figure of merit ZT of the device. First, asymmetrical legs are proposed in order to reduce the overall thermal conductance of the device so as to increase the temperature gradient in the legs, as well as by harnessing the Thomson effect, which is generally neglected in conventional symmetrical thermoelectric legs. It has been developed a novel design of a thermoelectric module having asymmetrical legs, and by first time it has been validated experimentally its thermoelectric performance by realizing a proof-of-concept device which shows to have almost twofold the thermoelectric figure of merit as compared to conventional one. Moreover, it has been also varied the length of thermoelectric legs in order to analyze its effect on the thermoelectric performance of the device. Along with this, it has studied the impact of contact resistance in these systems. Experimental results show that device architecture can improve up to twofold the thermoelectric performance of the device.

Keywords: asymmetrical legs, heat recovery, heat recycling, thermoelectric module, Thompson effect

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Authors: Xian-Peng Jiang, Catherine C. Baucom, Toby Jiang, Robert L. Elliott

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HLA-G binds to the inhibitory receptors of uterine NK cells and plays an important role in protection of fetal cells from maternal NK lysis. HLA-G also mediates tumor escape, but the immunosuppressive role is often neglected. These studies have focused on the examination of HLA-G expression in human breast carcinoma and HLA-G immunosuppressive role in NK cytolysis. We examined HLA-G expression in breast cell lines by real time PCR, ELISA and immunofluorescent staining. We treated the breast cancer cell lines with anti-human HLA-G antibody or progesterone. Then, NK cytolysis was measured by using MTT assay. We find that breast carcinoma cell lines increase the expression of HLA-G mRNA and protein, compared to normal cells. Blocking HLA-G of the breast cancer cells by the antibody increases NK cytolysis. Progesterone upregulates HLA-G mRNA and protein of human breast cancer cell lines. The increased HLA-G expression suppresses NK cytolysis. In summary, human breast carcinoma overexpress HLA-G immunosuppressive molecules. Blocking HLA-G protein by antibody improves NK cytolysis. In contrast, upregulation of HLA-G expression by progesterone impairs NK cytolytic function. Thus, HLA-G is a new immunosuppressive checkpoint and potential cancer immunotherapeutic target.

Keywords: HLA-G, Breast carcinoma, NK cells, Immunosuppressive checkpoint

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Authors: Christina Kalogirou

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Investigating the integration of bioclimatic design into vernacular architecture could lead to interesting results regarding the preservation of cultural heritage while enhancing the energy efficiency of historic buildings. Furthermore, these recognized principles and systems of bioclimatic design in vernacular settlements could be applied to modern architecture and thus to new buildings in such areas. This study introduces an approach to categorizing distinct technologies and design principles of bioclimatic design based on a thoughtful approach to various climatic zones and environment in Greece (mountainous areas, islands and lowlands). For this purpose, various types of dwellings are evaluated for their response to climate, regarding the layout of the buildings (orientation, floor plans’ shape, semi-open spaces), the site planning, the openings (size, position, protection), the building envelope (walls: construction materials-thickness, roof construction detailing) and the migratory living pattern according to seasonal needs. As a result, various passive design principles (that could be adapted to current architectural practice in such areas, in order to optimize the relationship between site, building, climate and energy efficiency) are proposed.

Keywords: bioclimatic design, buildings physics, climatic zones, energy efficiency, vernacular architecture

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Authors: Rao Fu, Jie Chen, Shutian Zeng, Yiping Zhuang, Agus Sudjianto

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Generative Adversarial Net (GAN) has proved to be a powerful machine learning tool in image data analysis and generation. In this paper, we propose to use Conditional Generative Adversarial Net (CGAN) to learn and simulate time series data. The conditions include both categorical and continuous variables with different auxiliary information. Our simulation studies show that CGAN has the capability to learn different types of normal and heavy-tailed distributions, as well as dependent structures of different time series. It also has the capability to generate conditional predictive distributions consistent with training data distributions. We also provide an in-depth discussion on the rationale behind GAN and the neural networks as hierarchical splines to establish a clear connection with existing statistical methods of distribution generation. In practice, CGAN has a wide range of applications in market risk and counterparty risk analysis: it can be applied to learn historical data and generate scenarios for the calculation of Value-at-Risk (VaR) and Expected Shortfall (ES), and it can also predict the movement of the market risk factors. We present a real data analysis including a backtesting to demonstrate that CGAN can outperform Historical Simulation (HS), a popular method in market risk analysis to calculate VaR. CGAN can also be applied in economic time series modeling and forecasting. In this regard, we have included an example of hypothetical shock analysis for economic models and the generation of potential CCAR scenarios by CGAN at the end of the paper.

Keywords: conditional generative adversarial net, market and credit risk management, neural network, time series

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Authors: Kien Vu, Jien Min Soh, Mohamed Jahangir Abubacker, Piyawut Pattamanon, Soojin Lee, Suvro Banerjee

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Recent advances in Generative Artificial Intelligence (GenAI), in particular Large Language Models (LLMs) have shown promise to disrupt multiple industries at scale. However, LLMs also present unique challenges, notably, these so-called "hallucination" which is the generation of outputs that are not grounded in the input data that hinders its adoption into production. Common practice to mitigate hallucination problem is utilizing Retrieval Agmented Generation (RAG) system to ground LLMs'response to ground truth. RAG converts the grounding documents into embeddings, retrieve the relevant parts with vector similarity between user's query and documents, then generates a response that is not only based on its pre-trained knowledge but also on the specific information from the retrieved documents. However, the RAG system is not suitable for tabular data and subsequent data analysis tasks due to multiple reasons such as information loss, data format, and retrieval mechanism. In this study, we have explored a novel methodology that combines planning-and-execution and code generation agents to enhance LLMs' data analysis capabilities. The approach enables LLMs to autonomously dissect a complex analytical task into simpler sub-tasks and requirements, then convert them into executable segments of code. In the final step, it generates the complete response from output of the executed code. When deployed beta version on DataSense, the property insight tool of PropertyGuru, the approach yielded promising results, as it was able to provide market insights and data visualization needs with high accuracy and extensive coverage by abstracting the complexities for real-estate agents and developers from non-programming background. In essence, the methodology not only refines the analytical process but also serves as a strategic tool for real estate professionals, aiding in market understanding and enhancement without the need for programming skills. The implication extends beyond immediate analytics, paving the way for a new era in the real estate industry characterized by efficiency and advanced data utilization.

Keywords: large language model, reasoning, planning and execution, code generation, natural language processing, prompt engineering, data analysis, real estate, data sense, PropertyGuru

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Authors: Dulal Bhaumik, Fei Jie, Runa Bhaumik, Bikas Sinha

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Human brain is an amazingly complex network. Aberrant activities in this network can lead to various neurological disorders such as multiple sclerosis, Parkinson’s disease, Alzheimer’s disease and autism. fMRI has emerged as an important tool to delineate the neural networks affected by such diseases, particularly autism. In this paper, we propose mixed-effects models together with an appropriate procedure for controlling false discoveries to detect disrupted connectivities in whole brain studies. Results are illustrated with a large data set known as Autism Brain Imaging Data Exchange or ABIDE which includes 361 subjects from 8 medical centers. We believe that our findings have addressed adequately the small sample inference problem, and thus are more reliable for therapeutic target for intervention. In addition, our result can be used for early detection of subjects who are at high risk of developing neurological disorders.

Keywords: ABIDE, autism spectrum disorder, fMRI, mixed-effects model

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Authors: K. Y. Chen, H. Chua, C. W. Kan

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In this study, we will analyze Germany’s environmental situation such as water and air quality and review its environmental policy. In addition, we will collect the yearly environmental data as well as information concerning public environmental investment. Based on the data collect, we try to find out the relationship between public environmental investment and sustainable development in Germany. In addition, after comparing the trend of environmental quality and situation of environmental policy and investment, we may have some conclusions and learnable aspects to refer to. Based upon the data collected, it was revealed that Germany has established a well-developed institutionalization of environmental education. And the ecological culture at school is dynamic and continuous renewal. The booming of green markets in Germany is a very successful experience for learning. The green market not only creates a number of job opportunities, but also helps the government to improve and protect the environment. Acknowledgement: Authors would like to thank the financial support from the Hong Kong Polytechnic University for this work.

Keywords: Germany, public environmental investment, environment quality, sustainable development

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Authors: Jeonghwan Jeon

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With the advent of IPTV in the fierce competition with existing broadcasting system, it is emerged as an important issue to predict how much the adoption of IPTV service will be. This paper aims to suggest a prediction model for adopting IPTV using classification and Ranking Belief Simplex (CaRBS). A simplex plot method of representing data allows a clear visual representation to the degree of interaction of the support from the variables to the prediction of the objects. CaRBS is applied to the survey data on the IPTV adoption.

Keywords: prediction, adoption, IPTV, CaRBS

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Authors: R. Clancy, M. Ahern, D. O’Sullivan, K. Bruton

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The manufacturing industry is currently undergoing a digital transformation as part of the mega-trend Industry 4.0. As part of this phase of the industrial revolution, traditional manufacturing processes are being combined with digital technologies to achieve smarter and more efficient production. To successfully digitally transform a manufacturing facility, the processes must first be digitized. This is the conversion of information from an analogue format to a digital format. The objective of this study was to explore the research area of digitizing manufacturing data as part of the worldwide paradigm, Industry 4.0. The formal methodology of a systematic mapping study was utilized to capture a representative sample of the research area and assess its current state. Specific research questions were defined to assess the key benefits and limitations associated with the digitization of manufacturing data. Research papers were classified according to the type of research and type of contribution to the research area. Upon analyzing 54 papers identified in this area, it was noted that 23 of the papers originated in Germany. This is an unsurprising finding as Industry 4.0 is originally a German strategy with supporting strong policy instruments being utilized in Germany to support its implementation. It was also found that the Fraunhofer Institute for Mechatronic Systems Design, in collaboration with the University of Paderborn in Germany, was the most frequent contributing Institution of the research papers with three papers published. The literature suggested future research directions and highlighted one specific gap in the area. There exists an unresolved gap between the data science experts and the manufacturing process experts in the industry. The data analytics expertise is not useful unless the manufacturing process information is utilized. A legitimate understanding of the data is crucial to perform accurate analytics and gain true, valuable insights into the manufacturing process. There lies a gap between the manufacturing operations and the information technology/data analytics departments within enterprises, which was borne out by the results of many of the case studies reviewed as part of this work. To test the concept of this gap existing, the researcher initiated an industrial case study in which they embedded themselves between the subject matter expert of the manufacturing process and the data scientist. Of the papers resulting from the systematic mapping study, 12 of the papers contributed a framework, another 12 of the papers were based on a case study, and 11 of the papers focused on theory. However, there were only three papers that contributed a methodology. This provides further evidence for the need for an industry-focused methodology for digitizing and analyzing manufacturing data, which will be developed in future research.

Keywords: analytics, digitization, industry 4.0, manufacturing

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Authors: L. Kamandulytė-Merfeldienė

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The paper deals with the main issues of methodology of the Corpus of Spoken Lithuanian which was started to be developed in 2006. At present, the corpus consists of 300,000 grammatically annotated word forms. The creation of the corpus consists of three main stages: collecting the data, the transcription of the recorded data, and the grammatical annotation. Collecting the data was based on the principles of balance and naturality. The recorded speech was transcribed according to the CHAT requirements of CHILDES. The transcripts were double-checked and annotated grammatically using CHILDES. The development of the Corpus of Spoken Lithuanian has led to the constant increase in studies on spontaneous communication, and various papers have dealt with a distribution of parts of speech, use of different grammatical forms, variation of inflectional paradigms, distribution of fillers, syntactic functions of adjectives, the mean length of utterances.

Keywords: CHILDES, corpus of spoken Lithuanian, grammatical annotation, grammatical disambiguation, lexicon, Lithuanian

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Authors: Mohammad Bakhshi, Firas Al Janabi

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High resolution rain data are very important to fulfill the input of hydrological models. Among models of high-resolution rainfall data generation, the temporal disaggregation was chosen for this study. The paper attempts to generate three different rainfall resolutions (4-hourly, hourly and 10-minutes) from daily for around 20-year record period. The process was done by DiMoN tool which is based on random cascade model and method of fragment. Differences between observed and simulated rain dataset are evaluated with variety of statistical and empirical methods: Kolmogorov-Smirnov test (K-S), usual statistics, and Exceedance probability. The tool worked well at preserving the daily rainfall values in wet days, however, the generated data are cumulated in a shorter time period and made stronger storms. It is demonstrated that the difference between generated and observed cumulative distribution function curve of 4-hourly datasets is passed the K-S test criteria while in hourly and 10-minutes datasets the P-value should be employed to prove that their differences were reasonable. The results are encouraging considering the overestimation of generated high-resolution rainfall data.

Keywords: DiMoN Tool, disaggregation, exceedance probability, Kolmogorov-Smirnov test, rainfall

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Authors: Rui Teixeira, Alan O’Connor, Maria Nogal

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The statistical theory of extreme events is progressively a topic of growing interest in all the fields of science and engineering. The changes currently experienced by the world, economic and environmental, emphasized the importance of dealing with extreme occurrences with improved accuracy. When it comes to the design of offshore structures, particularly offshore wind turbines, the importance of efficiently characterizing extreme events is of major relevance. Extreme events are commonly characterized by extreme values theory. As an alternative, the accurate modeling of the tails of statistical distributions and the characterization of the low occurrence events can be achieved with the application of the Peak-Over-Threshold (POT) methodology. The POT methodology allows for a more refined fit of the statistical distribution by truncating the data with a minimum value of a predefined threshold u. For mathematically approximating the tail of the empirical statistical distribution the Generalised Pareto is widely used. Although, in the case of the exceedances of significant wave data (H_s) the 2 parameters Weibull and the Exponential distribution, which is a specific case of the Generalised Pareto distribution, are frequently used as an alternative. The Generalized Pareto, despite the existence of practical cases where it is applied, is not completely recognized as the adequate solution to model exceedances over a certain threshold u. References that set the Generalised Pareto distribution as a secondary solution in the case of significant wave data can be identified in the literature. In this framework, the current study intends to tackle the discussion of the application of statistical models to characterize exceedances of wave data. Comparison of the application of the Generalised Pareto, the 2 parameters Weibull and the Exponential distribution are presented for different values of the threshold u. Real wave data obtained in four buoys along the Irish coast was used in the comparative analysis. Results show that the application of the statistical distributions to characterize significant wave data needs to be addressed carefully and in each particular case one of the statistical models mentioned fits better the data than the others. Depending on the value of the threshold u different results are obtained. Other variables of the fit, as the number of points and the estimation of the model parameters, are analyzed and the respective conclusions were drawn. Some guidelines on the application of the POT method are presented. Modeling the tail of the distributions shows to be, for the present case, a highly non-linear task and, due to its growing importance, should be addressed carefully for an efficient estimation of very low occurrence events.

Keywords: extreme events, offshore structures, peak-over-threshold, significant wave data

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Authors: Zi-Han Li, Zi-Jun Sun, Dong-Yuan Chang, Li Zhu, Min Chen, Ming-Hui Zhao

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Aims: A genome-wide association study (GWAS) reported that patients with the rs55703767 minor allele in collagen type IV α3 chain encoding gene COL4A3 showed protection against diabetic kidney disease (DKD) in type 1 diabetes mellitus (T1DM). However, the role of rs55703767 in type 2 DKD has not been elucidated. The aim of the current study was to investigate the association between COL4A3 variant rs55703767 and DKD risk in Chinese patients with type 2 diabetes mellitus (T2DM). Methods: This nested case-control study was performed on 1311 patients who had T2DM for at least 10 years, including 580 with DKD and 731 without DKD. We detected the genotypes of all patients by TaqMan SNP Genotyping Assay and analyzed the association between COL4A3 variant rs55703767 and DKD risk. Results: Genetic analysis revealed that there was no significant difference between T2DM patients with DKD and those without DKD regarding allele or genotype frequencies of rs55703767, and the effect of this variant was not hyperglycemia specific. Conclusion: Our findings suggested that there was no detectable association between the COL4A3 variant rs55703767 and the susceptibility to DKD in the Chinese T2DM population.

Keywords: collagen type IV α3 chain, gene polymorphism, type 2 diabetes, diabetic kidney disease

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