Search results for: partially observed data

Authors: Ľudmila Ballová, Slavomír Kurhajec, Eva Petrovová, Jarmila Eftimová

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Angiogenesis, a formation of new blood vessels from a pre-existing vasculature, plays an important role in pathologic processes such as the growth and metastasis of tumours. Tumours cannot grow beyond a few millimetres without blood supply from the newly formed blood vessels from the host tissue, a process called tumour-induced angiogenesis. The successful research of antiangiogenic treatment of cancer has focused on nutraceuticals with angiogenesis-modulating properties. Berberine, as a major active component of the bark of Phellodendron amurense Rupr., has shown antitumour activity by intervening into different steps of carcinogenesis. The influence of ethanolic extract of Phellodendron amurese bark on the angiogenesis was tested in vivo on chick chorioallantoic membrane (CAM). The irritancy of the CAM after the application of the crude bark extract dissolved in normal saline (10 mg/mL) was investigated on embryonic day 7. No significant signs of the irritancy, such as vasoconstriction, hyperaemia, haemorrhage or coagulation were observed which indicates the harmless character of the extract. A significant reduction in vessel sprouting and higher percentage of avascular zone was observed in the case of CAM treated with the extract in comparison with non-treated CAM (control), which is a proof of the antiangiogenic potential of the extract. These results could contribute to the development of novel drugs for the treatment of cancer or other diseases, in which angiogenesis plays a significant role.

Keywords: angiogenesis, berberine, chorioallantoic membrane, irritancy, phellodendron amurense

Procedia PDF Downloads 381

Authors: Chuping Lo

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This paper presents a simple model demonstrating that ceteris paribus countries with lower barriers to accessing global data tend to earn higher incomes than other countries. Therefore, large countries that inherently have greater data resources tend to have higher incomes than smaller countries, such that the former may be more hesitant than the latter to liberalize cross-border data flows to maintain this advantage. Furthermore, countries with higher artificial intelligence (AI) intensity in production technologies tend to benefit more from economies of scale in data aggregation, leading to higher income and more trade as they are better able to utilize global data.

Keywords: digital intensity, digital divide, international trade, scale of economics

Procedia PDF Downloads 66

Authors: A. Asambe

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A study was conducted to determine the level of compliance with sanitary measures in piggeries, and awareness and risk factors of African swine fever in Benue State, Nigeria. Questionnaires were distributed to 74 respondents consisting of piggery owners and attendants in different piggeries across 12 LGAs to collect data for this study. Sanitary measures in piggeries were observed to be generally very poor, though respondents admitted being aware of ASF. Piggeries located within a 1 km radius of a slaughter slab (OR=9.2, 95% CI - 3.0-28.8), piggeries near refuse dump sites (OR=3.0, 95% CI - 1.0-9.5) and piggeries where farm workers wear their work clothes outside of the piggery premises (OR=0.2, 95% CI - 0.1-0.7) showed higher chances of ASFV infection and were significantly associated (p < 0.0001), (p < 0.05) and (p < 0.01), and were identified as potential risk factors. The study concluded that pigs in Benue State are still at risk of an ASF outbreak. Proper sanitary and hygienic practices is advocated and emphasized in piggeries, while routine surveillance for ASFV antibodies in pigs in Benue State is strongly recommended to provide a reliable reference data base to plan for the prevention of any devastating ASF outbreak.

Keywords: African swine fever, awareness, piggery, risk factors, sanitary measures

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Authors: G. R. Navaneesh, E. Nagarajan, C. H. Rajam Raju

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Nowadays the multimedia data are used to store some secure information. All previous methods allocate a space in image for data embedding purpose after encryption. In this paper, we propose a novel method by reserving space in image with a boundary surrounded before encryption with a traditional RDH algorithm, which makes it easy for the data hider to reversibly embed data in the encrypted images. The proposed method can achieve real time performance, that is, data extraction and image recovery are free of any error. A secure transmission process is also discussed in this paper, which improves the efficiency by ten times compared to other processes as discussed.

Keywords: secure communication, reserving room before encryption, least significant bits, image encryption, reversible data hiding

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Authors: Fuad M. Alkoot

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DNA data have been used in forensics for decades. However, current research looks at using the DNA as a biometric identity verification modality. The goal is to improve the speed of identification. We aim at using gene data that was initially used for autism detection to find if and how accurate is this data for identification applications. Mainly our goal is to find if our data preprocessing technique yields data useful as a biometric identification tool. We experiment with using the nearest neighbor classifier to identify subjects. Results show that optimal classification rate is achieved when the test set is corrupted by normally distributed noise with zero mean and standard deviation of 1. The classification rate is close to optimal at higher noise standard deviation reaching 3. This shows that the data can be used for identity verification with high accuracy using a simple classifier such as the k-nearest neighbor (k-NN). 

Keywords: biometrics, genetic data, identity verification, k nearest neighbor

Procedia PDF Downloads 253

Authors: Solomon Sisay, Belete Mengistu, Woldargay Erku, Desalegne Woldeyohannes

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Background: Tuberculosis is still the leading cause of illness in the world which accounted for 2.5% of the global burden of disease, and 25% of all avoidable deaths in developing countries. Objectives: The aim of study was to assess impact of DOTS strategy on tuberculosis case finding and treatment outcome in Gambella Regional State, Ethiopia from 2003 up to 2012 and from 2002 up to 2011, respectively. Methods: Health facility-based retrospective study was conducted. Data were collected and reported in quarterly basis using WHO reporting format for TB case finding and treatment outcome from all DOTS implementing health facilities in all zones of the region to Federal Ministry of Health. Results: A total of 10024 all form of TB cases had been registered between the periods from 2003 up to 2012. Of them, 4100 (40.9%) were smear-positive pulmonary TB, 3164 (31.6%) were smear-negative pulmonary TB and 2760 (27.5%) had extra-pulmonary TB. Case detection rate of smear-positive pulmonary TB had increased from 31.7% to 46.5% from the total TB cases and treatment success rate increased from 13% to 92% with average mean value of being 40.9% (SD= 0.1) and 55.7% (SD=0.28), respectively for the specified year periods. Moreover, the average values of treatment defaulter and treatment failure rates were 4.2% and 0.3%, respectively. Conclusion: It is possible to achieve the recommended WHO target which is 70% of CDR for smear-positive pulmonary TB, and 85% of TSR as it was already been fulfilled the targets for treatments more than 85% from 2009 up to 2011 in the region. However, it requires strong efforts to enhance case detection rate of 40.9% for smear-positive pulmonary TB through implementing alternative case finding strategies.

Keywords: Gambella Region, case detection rate, directly observed treatment short-course, treatment success rate, tuberculosis

Procedia PDF Downloads 342

Authors: N. Fhafhiem, P. Krachodnok, R. Wongsan

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This paper proposes the development and design of double layer metamaterials based on electromagnetic band gap (EBG) rods as a superstrate of a resonator antenna to enhance required antenna characteristics for the mobile base station. The metallic rod type metamaterial can partially reflect wave of a primary radiator. The antenna was designed and analyzed by a simulation result from CST Microwave Studio and designed technique could be confirmed by a measurement results from prototype antenna that agree with simulation results. The results indicate that the antenna can also generate a dual polarization by using a 45˚ oriented curved strip dipole located at the center of the reflector plane with double layer superstrate. It can be used to simplify the feed system of an antenna. The proposed antenna has a bandwidth covering the frequency range of 1920 – 2200 MHz, the gain of the antenna increases up to 14.06 dBi. In addition, an interesting sectoral 60˚ pattern is presented in horizontal plane.

Keywords: metamaterial, electromagnetic band gap, dual polarization, resonator antenna

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Authors: R Palson Kennedy, P.Kiran Sai

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This article introduces machine learning (ML) researchers to the hurdles that geoscience problems present, as well as the opportunities for improvement in both ML and geosciences. This article presents a review from the data life cycle perspective to meet that need. Numerous facets of geosciences present unique difficulties for the study of intelligent systems. Geosciences data is notoriously difficult to analyze since it is frequently unpredictable, intermittent, sparse, multi-resolution, and multi-scale. The first half addresses data science’s essential concepts and theoretical underpinnings, while the second section contains key themes and sharing experiences from current publications focused on each stage of the data life cycle. Finally, themes such as open science, smart data, and team science are considered.

Keywords: Data science, intelligent system, machine learning, big data, data life cycle, recent development, geo science

Procedia PDF Downloads 133

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

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In United States (US), the environmental policy went through two stages that are government control period and market mechanism period. In the government control period in the 1970s, environmental problems in U.S. are treated by mandatory direct control method, including promulgation of laws, formulation of emission standards and mandatory installation of pollution treatment equipment. After the 1980s, the environmental policy in U.S. went into the second stage, in which the government strengthened the incentives and coordination effects of market. Since then, environmental governance had been partially replaced by means of economic regulation of the market. Green Tax Policy and Marketable Pollution Permits are good examples of government's economic interventions. U.S. Federal Government regards environmental industry as high-tech industry which is promoted in this period. Therefore, in the paper, we aim to analyse the effect of environmental investment on the sustainable development in the US. Acknowledgment: Authors would like to thank the financial support from the Hong Kong Polytechnic University for this work.

Keywords: United States, public environmental investment, analysis, sustainable development

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Authors: Devender Sharma, Shweta Goyal

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Sustainable development is a key to protect the environment for a secure future. Accelerated carbonation curing is a comparatively new technique for curing of concrete which involves sequestration of carbon dioxide gas into the precast concrete, resulting in improvement of the properties of concrete. This paper presents the results of a study to evaluate the effect of carbonation curing on cement mortars incorporating cement kiln dust (CKD) as partial replacement of cement. The mortar specimens were prepared by replacing cement with CKD in varying percentages of 0-50% by the weight of cement. The specimens were subjected to 12 hour carbonation curing, followed by sealed packing till testing age. The results were compared with the normal curing procedure, in which the specimens were water cured till the testing age. Compressive strength and microstructure of the mix were studied. It was noted that on increasing the percentage of CKD up to 10% by the weight of the cement, no considerable change was observed in the compressive strength. But as the percentage of CKD was further increased, there was a decrease in compressive strength, with strength decreasing up to 40% when 50% of the cement was replaced with CKD. The decrease in strength is due to the lesser lime content in CKD as compared to cement. High ettringite formation was observed in mixes with high percentages of CKD, thus indicating a decrease in the compressive strength. With carbonation curing, an early age strength gain was observed in mortars, even with higher percentages of CKD. The early strength of the carbonation cured mixes was found to be greater than water cured mixes irrespective of the percentage of CKD. 7 days and 28 days compressive strength of the mix was comparable for both the carbonation cured and water cured specimen. The increase in compressive strength can be attributed to the conversion of unstable Ca(OH)2 into stable CaCO3, which causes densification of the mix. CaCO3 precipitation and greater CSH gel formation was clearly observed in the SEM images of carbonation cured specimen, indicating higher compressive strength. Thus, carbonation curing can be used as an efficient method to enhance the properties of concrete.

Keywords: carbonation, cement kiln dust, compressive strength, microstructure

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Authors: Éva Pintér, Péter Bagó, Nikolett Deutsch, Miklós Hetényi

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The process of digital transformation has a profound influence on all sectors of the worldwide economy and the business environment. The influence of blockchain technology can be observed in the digital economy and e-government, rendering it an essential element of a nation's growth strategy. The banking industry is experiencing significant expansion and development of financial technology firms. Utilizing developing technologies such as artificial intelligence (AI), machine learning (ML), and big data (BD), these entrants are offering more streamlined financial solutions, promptly addressing client demands, and presenting a challenge to incumbent institutions. The advantages of digital transformation are evident in the corporate realm, and firms that resist its adoption put their survival at risk. The advent of digital technologies has revolutionized the business environment, streamlining processes and creating opportunities for enhanced communication and collaboration. Thanks to the aid of digital technologies, businesses can now swiftly and effortlessly retrieve vast quantities of information, all the while accelerating the process of creating new and improved products and services. Big data analytics is generally recognized as a transformative force in business, considered the fourth paradigm of science, and seen as the next frontier for innovation, competition, and productivity. Big data, an emerging technology that is shaping the future of the banking sector, offers numerous advantages to banks. It enables them to effectively track consumer behavior and make informed decisions, thereby enhancing their operational efficiency. Banks may embrace big data technologies to promptly and efficiently identify fraud, as well as gain insights into client preferences, which can then be leveraged to create better-tailored products and services. Moreover, the utilization of big data technology empowers banks to develop more intelligent and streamlined models for accurately recognizing and focusing on the suitable clientele with pertinent offers. There is a scarcity of research on big data analytics in the banking industry, with the majority of existing studies only examining the advantages and prospects associated with big data. Although big data technologies are crucial, there is a dearth of empirical evidence about the role of big data analytics (BDA) capabilities in bank performance. This research addresses a gap in the existing literature by introducing a model that combines the resource-based view (RBV), the technical organization environment framework (TOE), and dynamic capability theory (DC). This study investigates the influence of Big Data Analytics (BDA) utilization on the performance of market and risk management. This is supported by a comparative examination of Hungarian mobile banking services.

Keywords: big data, digital transformation, dynamic capabilities, mobile banking

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Authors: Reza Talebi

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Wheat (Triticum aestivum) is one of the most important food staples in Iran. Understanding genetic variability among the landrace wheat germplasm is important for breeding. Landraces endemic to Iran are a genetic resource that is distinct from other wheat germplasm. In this study, 60 Iranian landrace wheat accessions were characterized AFLP and ISSR markers. Twelve AFLP primer pairs detected 128 polymorphic bands among the sixty genotypes. The mean polymorphism rate based on AFLP data was 31%; however, a wide polymorphism range among primer pairs was observed (22–40%). Polymorphic information content (PIC value) calculated to assess the informativeness of each marker ranged from 0.28 to 0.4, with a mean of 0.37. According to AFLP molecular data, cluster analysis grouped the genotypes in five distinct clusters. .ISSR markers generated 68 bands (average of 6 bands per primer), which 31 were polymorphic (45%) across the 60 wheat genotypes. Polymorphism information content (PIC) value for ISSR markers was calculated in the range of 0.14 to 0.48 with an average of 0.33. Based on data achieved by ISSR-PCR, cluster analysis grouped the genotypes in three distinct clusters. Both AFLP and ISSR markers able to showed that high level of genetic diversity in Iranian landrace wheat accessions has maintained a relatively constant level of genetic diversity during last years.

Keywords: wheat, genetic diversity, AFLP, ISSR

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Authors: Serife Gulden Yilmaz, Suleyman Karaman

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Sheep breeding is important in terms of meeting both the demand of red meat consumption and the availability of industrial raw materials and the employment of the rural sector in Turkey. It is also very important to ensure the selection and continuity of the breeds that are raised in order to increase quality and productive products related to sheep breeding. The protection of local breeds and crossbreds also enables the development of the sector in the region and the reduction of imports. In this study, the data were obtained from the records of the Turkish Statistical Institute and Antalya Sheep & Goat Breeders' Association. Spatial distribution of sheep breeds in Antalya is reviewed statistically in terms of concentration at the local level for 2015 period spatially. For this reason; mapping, box plot, linear regression are used in this study. Concentration is introduced by means of studbook data on sheep breeding as locals and total sheep farm by mapping. It is observed that Pırlak breed (17.5%) and Merinos crossbreed (16.3%) have the highest concentration in the region. These breeds are respectively followed by Akkaraman breed (11%), Pirlak crossbreed (8%), Merinos breed (7.9%) Akkaraman crossbreed (7.9%) and Ivesi breed (7.2%).

Keywords: sheep breeds, local, spatial distribution, agglomeration, Antalya

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Authors: Brian Marsh

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Nitrogen fertilizer is the most used and often the most mismanaged nutrient input. Nitrogen management has tremendous implications on crop productivity, quality and environmental stewardship. Sufficient nitrogen is needed to optimum yield and quality. Soil and in-season plant tissue testing for nitrogen status are a time consuming and expensive process. Real time sensing of plant nitrogen status can be a useful tool in managing nitrogen inputs. The objectives of this project were to assess the reliability of remotely sensed non-destructive plant nitrogen measurements compared to wet chemistry data from sampled plant tissue, develop in-season nitrogen recommendations based on remotely sensed data for improved nitrogen use efficiency and assess the potential for determining yield and quality from remotely sensed data. Very good correlations were observed between early-season remotely sensed crop nitrogen status and plant nitrogen concentrations and subsequent in-season fertilizer recommendations. The transmittance/absorbance type meters gave the most accurate readings. Early in-season fertilizer recommendation would be to apply 40 kg nitrogen per hectare plus 16 kg nitrogen per hectare for each unit difference measured with the SPAD meter between the crop and reference area or 25 kg plus 13 kg per hectare for each unit difference measured with the CCM 200. Once the crop was sufficiently fertilized meter readings became inconclusive and were of no benefit for determining nitrogen status, silage yield and quality and grain yield and protein.

Keywords: wheat, nitrogen fertilization, chlorophyll meter

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Authors: Ayesha Anjum, Arbaz Basha

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Active Galactic Nuclei (AGN) are the actively accreting centers of the galaxies that host supermassive black holes. AGN emits radiation in all wavelengths and also shows variability across all the wavelength bands. The analysis of flux variability tells us about the morphology of the site of emission radiation. Some of the major classifications of AGN are (a) Blazars, with featureless spectra. They are subclassified as BLLacertae objects, Flat Spectrum Radio Quasars (FSRQs), and others; (b) Seyferts with prominent emission line features are classified into Broad Line, Narrow Line Seyferts of Type 1 and Type 2 (c) quasars, and other types. Sloan Digital Sky Survey (SDSS) is an optical telescope based in Mexico that has observed and classified billions of objects based on automated photometric and spectroscopic methods. A sample of blazars is obtained from the third Fermi catalog. For variability analysis, we searched for light curves for these objects in Wide-Field Infrared Survey Explorer (WISE) and Near Earth Orbit WISE (NEOWISE) in two bands: W1 (3.4 microns) and W2 (4.6 microns), reducing the final sample to 256 objects. These objects are also classified into 155 BLLacs, 99 FSRQs, and 2 Narrow Line Seyferts, namely, PMNJ0948+0022 and PKS1502+036. Mid-infrared variability studies of these objects would be a contribution to the literature. With this as motivation, the present work is focused on studying a final sample of 256 objects in general and the Seyferts in particular. Owing to the fact that the classification is automated, SDSS has miclassified these objects into quasars, galaxies, and stars. Reasons for the misclassification are explained in this work. The variability analysis of these objects is done using the method of flux amplitude variability and excess variance. The sample consists of observations in both W1 and W2 bands. PMN J0948+0022 is observed between MJD from 57154.79 to 58810.57. PKS 1502+036 is observed between MJD from 57232.42 to 58517.11, which amounts to a period of over six years. The data is divided into different epochs spanning not more than 1.2 days. In all the epochs, the sources are found to be variable in both W1 and W2 bands. This confirms that the object is variable in mid-infrared wavebands in both long and short timescales. Also, the sources are observed for color variability. Objects either show a bluer when brighter trend (BWB) or a redder when brighter trend (RWB). The possible claim for the object to be BWB (present objects) is that the longer wavelength radiation emitted by the source can be suppressed by the high-energy radiation from the central source. Another result is that the smallest radius of the emission source is one day since the epoch span used in this work is one day. The mass of the black holes at the centers of these sources is found to be less than or equal to 108 solar masses, respectively.

Keywords: active galaxies, variability, Seyfert galaxies, SDSS, WISE

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Authors: K. Mohon Singh

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Cambro-Ordovician (512.5 ± 8.7 Ma) felsic magmatism in the Kyrdem region of Meghalaya plateau, herewith referred to as Kyrdem granitoids (KG), intrudes the low-grade Shillong Group of metasediments and Precambrian Basement Gneissic complex forming an oval-shaped plutonic body with longer axis almost trending N-S. Thermal aureole is poorly developed or covered under the alluvium. KG exhibit very coarse grained porphyritic texture with abundant K-feldspar megacrysts (up to 9cm long) and subordinate amount of amphibole, biotite, plagioclase, and quartz. The size of K-feldspar megacrysts increases from margin (Dwarksuid) to the interior (Kyrdem) of the KG pluton. Late felsic pulses as fine grained granite, leucocratic (aplite), and pegmatite veins intrude the KG at several places. Grey and pink varieties of KG can be recognized, but pink colour of KG is the result of post-magmatic fluids, which have not affected the magnetic properties of KG. Modal composition of KG corresponds to quartz monzonite, monzogranite, and granodiorite. KG has been geochemically characterized as metaluminous (I-type) to peraluminous (S-type) granitoids. The KG is characterized by development of variable attitude of primary foliations mostly marked along the margin of the pluton and is located at the proximity of Tyrsad-Barapani lineament. The KG contains country rock xenoliths (amphibolite, gneiss, schist, etc.) which are mostly confined to the margin of the pluton, and microgranular enclaves (ME) are hosted in the porphyritic variety of KG. Microgranular Enclaves (ME) in Kyrdem Granitoids are fine- to medium grained, mesocratic to melanocratic, phenocryst bearing or phenocryst-free, rounded to ellipsoidal showing typical magmatic textures. Mafic-felsic phenocrysts in ME are partially corroded and dissolved because of their involvement in magma-mixing event, and thus represent xenocrysts. Sharp to diffused contacts of ME with host Kyrdem Granitoids, fine grained nature and presence of acicular apatite in ME suggest comingling and undercooling of coeval, semi-solidified ME magma within partly crystalline felsic host magma. Geochemical features recognize the nature of ME (molar A/CNK=0.76-1.42) and KG (molar A/CNK =0.41-1.75) similar to hybrid-type formed by mixing of mantle-derived mafic and crustal-derived felsic magmas. Major and trace including rare earth elements variations of ME suggest the involvement of combined processes such as magma mixing, mingling and crystallization differentiation in the evolution of ME but KG variations appear primarily controlled by fractionation of plagioclase, hornblende biotite, and accessory phases. Most ME are partially to nearly re-equilibrate chemically with felsic host KG during magma mixing and mingling processes.

Keywords: geochemistry, Kyrdem Granitoids, microgranular enclaves, Northeast India

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Authors: Padmanabhan D, Kavitha S

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The purpose of the study is to investigate arsenic resistance ability of indigenous microflora and its ability to utilize arsenic species form containing water source. PS-6 potential arsenic tolerance bacterium was screened from thirty isolates from Pichavaram Mangroves of India having tolerance to grow up to 1000 mg/l of As (V) and 800 mg/l of As (III) and arsenic utilization ability of 98 % of As (V) and 97% of As (III) with initial concentration of 3-5 mg/l within 48 hrs. Optimum pH and temperature was found to be ~7-7.4 and 37°C. Active growth of PS-6 in minimal salt media (MSB) helps in cost effective biomass production. Dry weight analysis of PS-6 has shown significant difference in biomass when exposed to As (III) and As (V). Protein level study of PS-6 after exposing to As (V) and As (III) shown modification in total protein concentration and variation in SDS-PAGE pattern. PS-6 was identified as Bacillus licheniformis based on partially sequenced of 16S rRNA using NCBI Blast. Further investigation will help in using this potential bacterium as a well-grounded source for urgency.

Keywords: arsenite, arsenate, Bacillus licheniformis, utilization

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Authors: Oluwatofunmi Musa-Ajakaiye, Paul Olorunfemi M.D MPH, John Obafaiye

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Introduction: The U.S Food and Drug Administration (FDA) reports the public notices for recalled FDA-regulated products over periods of time. It study reviewed the primary reasons for recalls of products of various types over a period of 7 years. Methods: The study analyzed data provided in the FDA’s archived recalls for the years 2010-2017. It identified the various reasons for product recalls in the categories of foods, beverages, drugs, medical devices, animal and veterinary products, and dietary supplements. Using SPSS version 29, descriptive statistics and chi-square analysis of the data were performed. Results (numbers, percentages, p-values, chi-square): Over the period of analysis, a total of 931 recalls were reported. The most frequent reason for recalls was undeclared products (36.7%). The analysis showed that the most recalled product type in the data set was foods and beverages, representing 591 of all recalled products (63.5%).In addition, it was observed that foods and beverages represent 77.2% of products recalled due to the presence of microorganisms. Also, a sub-group analysis of recall reasons of food and beverages found that the most prevalent reason for such recalls was undeclared products (50.1%) followed by Listeria (17.3%) then Salmonella (13.2%). Conclusion: This analysis shows that foods and beverages have the greatest percentages of total recalls due to the presence of undeclared products listeria contamination and Salmonella contamination. The prevalence of Salmonella and Listeria contamination suggests that there is a high risk of microbial contamination in FDA-approved products and further studies on the effects of such contamination must be conducted to ensure consumer safety.

Keywords: food, beverages, listeria, salmonella, FDA, contamination, microbial

Procedia PDF Downloads 62

Authors: Şakir Bingöl, Abdullah Emre Aydemir, Abdullah Saado, Ahmet Akıl, Elif Canbaz, Feyza Nur Bulgurcu, Gizem Uzun, Günsu Bilge Dal, Muhammedcan Pirinççi

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Smart contracts, which can be applied in many different areas, from financial applications to the internet of things, come to the fore with their security, low cost, and self-executing features. In this paper, it is focused on peer-to-peer (P2P) energy trading and the implementation of the smart contract on the Ethereum blockchain. It is assumed a microgrid consists of consumers and prosumers that can produce solar and wind energy. The proposed architecture is a system where the prosumer makes the purchase or sale request in the smart contract and the maximum price obtained through the distribution system operator (DSO) by forecasting. It is aimed to forecast the hourly maximum unit price of energy by using deep learning instead of a fixed pricing. In this way, it will make the system more reliable as there will be more dynamic and accurate pricing. For this purpose, Istanbul's energy generation, energy consumption and market clearing price data were used. The consistency of the available data and forecasting results is observed and discussed with graphs.

Keywords: energy trading smart contract, deep learning, microgrid, forecasting, Ethereum, peer to peer

Procedia PDF Downloads 136

Authors: Kohkan Shamsi

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Background: MRI and PET are now extensively utilized in Alzheimer's disease (AD) trials for patient eligibility, efficacy assessment, and safety evaluations but including imaging in AD trials impacts site selection process, patient recruitment, and patient retention. Methods: PET/MRI are performed at baseline and at multiple follow-up timepoints. This requires prospective site imaging qualification, evaluation of phantom data, training and continuous monitoring of machines for acquisition of standardized and consistent data. This also requires prospective patient/caregiver training as patients must go to multiple facilities for imaging examinations. We will share our experience form one of the largest AD programs. Lesson learned: Many neurological diseases have a similar presentation as AD or could confound the assessment of drug therapy. The inclusion of wrong patients has ethical and legal issues, and data could be excluded from the analysis. Centralized eligibility evaluation read process will be discussed. Amyloid related imaging abnormalities (ARIA) were observed in amyloid-β trials. FDA recommended regular monitoring of ARIA. Our experience in ARIA evaluations in large phase III study at > 350 sites will be presented. Efficacy evaluation: MRI is utilized to evaluate various volumes of the brain. FDG PET or amyloid PET agents has been used in AD trials. We will share our experience about site and central independent reads. Imaging logistic issues that need to be handled in the planning phase will also be discussed as it can impact patient compliance thereby increasing missing data and affecting study results. Conclusion: imaging must be prospectively planned to include standardizing imaging methodologies, site selection process and selecting assessment criteria. Training should be transparently conducted and documented. Prospective patient/caregiver awareness of imaging requirement is essential for patient compliance and reduction in missing imaging data.

Keywords: Alzheimer's disease, ARIA, MRI, PET, patient recruitment, retention

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Authors: Marc Bachelet, Abhijit Kumar Chatterjee, José Manuel Avila

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Data quality is a key component of any data-driven organization. Without data quality, organizations cannot effectively make data-driven decisions, which often leads to poor business performance. Therefore, it is important for an organization to ensure that the data they use is of high quality. This is where the concept of data mesh comes in. Data mesh is an organizational and architectural decentralized approach to data management that can help organizations improve the quality of data. The concept of data mesh was first introduced in 2020. Its purpose is to decentralize data ownership, making it easier for domain experts to manage the data. This can help organizations improve data quality by reducing the reliance on centralized data teams and allowing domain experts to take charge of their data. This paper intends to discuss how a set of elements, including data mesh, are tools capable of increasing data quality. One of the key benefits of data mesh is improved metadata management. In a traditional data architecture, metadata management is typically centralized, which can lead to data silos and poor data quality. With data mesh, metadata is managed in a decentralized manner, ensuring accurate and up-to-date metadata, thereby improving data quality. Another benefit of data mesh is the clarification of roles and responsibilities. In a traditional data architecture, data teams are responsible for managing all aspects of data, which can lead to confusion and ambiguity in responsibilities. With data mesh, domain experts are responsible for managing their own data, which can help provide clarity in roles and responsibilities and improve data quality. Additionally, data mesh can also contribute to a new form of organization that is more agile and adaptable. By decentralizing data ownership, organizations can respond more quickly to changes in their business environment, which in turn can help improve overall performance by allowing better insights into business as an effect of better reports and visualization tools. Monitoring and analytics are also important aspects of data quality. With data mesh, monitoring, and analytics are decentralized, allowing domain experts to monitor and analyze their own data. This will help in identifying and addressing data quality problems in quick time, leading to improved data quality. Data culture is another major aspect of data quality. With data mesh, domain experts are encouraged to take ownership of their data, which can help create a data-driven culture within the organization. This can lead to improved data quality and better business outcomes. Finally, the paper explores the contribution of AI in the coming years. AI can help enhance data quality by automating many data-related tasks, like data cleaning and data validation. By integrating AI into data mesh, organizations can further enhance the quality of their data. The concepts mentioned above are illustrated by AEKIDEN experience feedback. AEKIDEN is an international data-driven consultancy that has successfully implemented a data mesh approach. By sharing their experience, AEKIDEN can help other organizations understand the benefits and challenges of implementing data mesh and improving data quality.

Keywords: data culture, data-driven organization, data mesh, data quality for business success

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Authors: Chabungbam Niranjit Khuman, Makarand Madhao Ghangrekar, Arunabha Mitra

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The cost of aeration is one of the limiting factors in the upscaling of microbial fuel cells (MFC) for field-scale applications. Wetland macrophytes have the ability to release oxygen into the water to maintain aerobic conditions in their root zone. In this experiment, the efficacy of rhizospheric oxygen release of wetland macrophytes as a source of oxygen in the cathodic chamber of MFC was conducted. The experiment was conducted in an MFC consisting of a three-liter anodic chamber made of ceramic cylinder and a 27 L cathodic chamber. Untreated carbon felts were used as electrodes (i.e., anode and cathode) and connected to an external load of 100 Ω using stainless steel wire. Wetland macrophytes (Canna indica) were grown in the cathodic chamber of the MFC in a hydroponic fashion using a styrofoam sheet (termed as macrophytes assisted-microbial fuel cell, M-MFC). The catholyte (i.e., water) in the M-MFC had negligible contact with atmospheric air due to the styrofoam sheet used for maintaining the hydroponic condition. There was no mixing of the catholyte in the M-MFC. Sucrose based synthetic wastewater having chemical oxygen demand (COD) of 3000 mg/L was fed into the anodic chamber of the MFC in fed-batch mode with a liquid retention time of four days. The C. indica thrived well throughout the duration of the experiment without much care. The average dissolved oxygen (DO) concentration and pH value in the M-MFC were 3.25 mg/L and 7.07, respectively, in the catholyte. Since the catholyte was not in contact with air, the DO in the catholyte might be considered as solely liberated from the rhizospheric oxygen release of C. indica. The maximum COD removal efficiency of M-MFC observed during the experiment was 76.9%. The inadequacy of terminal electron acceptor in the cathodic chamber in M-MFC might have hampered the electron transfer, which in turn, led to slower specific microbial activity, thereby resulting in lower COD removal efficiency than the traditional MFC with aerated catholyte. The average operating voltage (OV) and open-circuit voltage (OCV) of 294 mV and 594 mV, respectively, were observed in M-MFC. The maximum power density observed during polarization was 381 mW/m³, and the maximum sustainable power density observed during the experiment was 397 mW/m³ in M-MFC. The maximum normalized energy recovery and coulombic efficiency of 38.09 Wh/m³ and 1.27%, respectively, were observed. Therefore, it was evidenced that rhizospheric oxygen release of wetland macrophytes (C. indica) was capable of sustaining the cathodic reaction in MFC for field-scale applications.

Keywords: hydroponic, microbial fuel cell, rhizospheric oxygen release, wetland macrophytes

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Authors: H. Bouaziz, M. Sefi, J. de Lapuente, M. Borras, N. Zeghal

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Although arsenic trioxide has been the subject of toxicological research, in vitro cytotoxicity and genotoxicity studies using relevant cell models and uniform methodology are not well elucidated. Hence, the aim of the present study was to evaluate the cytotoxicity and genotoxicity induced by arsenic trioxide in human keratinocytes (HaCaT) using the MTT [3-(4, 5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide] and alkaline single cell gel electrophoresis (Comet) assays, respectively. Human keratinocytes were treated with different doses of arsenic trioxide for 4 h prior to cytogenetic assessment. Data obtained from the MTT assay indicated that arsenic trioxide significantly reduced the viability of HaCaT cells in a dose-dependent manner, showing a IC50 value of 34.18 ± 0.6 µM. Data generated from the comet assay also indicated a significant dose-dependent increase in DNA damage in HaCaT cells associated with arsenic trioxide exposure. We observed a significant increase in comet tail length and tail moment, showing an evidence of arsenic trioxide -induced genotoxic damage in HaCaT cells. This study confirms that the comet assay is a sensitive and effective method to detect DNA damage caused by arsenic.

Keywords: arsenic trioxide, cytotoxixity, genotoxicity, HaCaT

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Authors: Islam Zeb

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Water of poor quality has a potential of probable contamination and a way to spread pollutant in the field and surrounding environment. A number of comprehensive reviews articles have been published which highlight irrigation water as a source of pathogenic microorganisms and heavy metals toxicity that leads to chronic diseases in human. Here a study was plan to determine the microbial status of irrigation water collected from various location of district Swat in various months. The analyses were carried out at Environmental Horticulture Laboratory, Department of Horticulture, The University of Agriculture Peshawar, during the year 2018 – 19. The experiment was laid out in Randomized Complete Block Design (RCBD) with two factors and three replicates. Factor A consist of different locations, and factor B represent various months. The results of microbial status for various locations in irrigation water showed the highest value for Total Bacterial Count, Enterobacteriacea, E. coli, Salmonella, and Listeria (9.05, 8.54, 6.01, 5.84, and 5.03 log cfu L-1 respectively) for samples collected from mingora location, whereas the lowest values for Total Bacterial Count, Enterobacteriacea, E. coli, Salmonella and Listeria (6.70, 6.38, 4.47, 4.42 and 3.77 log cfu L-1 respectively) were observed for matta location. Data for various months showed maximum Total Bacterial Count, Enterobacteriacea, E. coli, Salmonella, and Listeria (12.01, 11.70, 8.46, 8.41, and 6.88 log cfu L-1, respectively) were noted for the irrigation water samples collected in May/June whereas the lowest range for Total Bacterial Count, Enterobacteriacea, E. coli, Salmonella and Listeria (4.41, 4.08, 2.61, 2.55 and 3.39 log cfu L-1 respectively) were observed in Jan/Feb. A significant interaction was found for all the studied parameters it was concluded that maximum bacterial groups were recorded in the months of May/June from Mingora location, it might be due to favorable weather condition.

Keywords: contamination, irrigation water, microbes, SWAT, various months

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Authors: Neha P. Amin, Maliha Zainib, Sean Parker, Malcolm Mattes

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Purpose/Objectives: Combination immunotherapy (IT) and radiation therapy (RT) is an actively growing field of clinical investigation due to promising findings of synergistic effects from immune-mediated mechanisms observed in preclinical studies and clinical data from case reports of abscopal effects. While there are many ongoing trials of combined IT-RT, there are still limited data on toxicity and outcome optimization regarding RT dose, fractionation, and sequencing of RT with IT. Nivolumab (NIVO), an anti-PD-1 monoclonal antibody, has been rapidly adopted in the clinic over the past 2 years, resulting in more patients being considered for concurrent RT-NIVO. Knowledge about the toxicity profile of combined RT-NIVO is important for both the patient and physician when making educated treatment decisions. The acute toxicity profile of concurrent RT-NIVO was analyzed in this study. Materials/Methods: A retrospective review of all consecutive patients who received NIVO from 1/2015 to 5/2017 at 4 separate centers within two separate institutions was performed. Those patients who completed a course of RT from 1 day prior to initial NIVO infusion through 1 month after last NIVO infusion were considered to have received concurrent therapy and included in the subsequent analysis. Descriptive statistics are reported for patient/tumor/treatment characteristics and observed acute toxicities within 3 months of RT completion. Results: Among 261 patients who received NIVO, 46 (17.6%) received concurrent RT to 67 different sites. The median f/u was 3.3 (.1-19.8) months, and 11/46 (24%) were still alive at last analysis. The most common histology, RT prescription, and treatment site included non-small cell lung cancer (23/46, 50%), 30 Gy in 10 fractions (16/67, 24%), and central thorax/abdomen (26/67, 39%), respectively. 79% (53/67) of irradiated sites were treated with 3D-conformal technique and palliative dose-fractionation. Grade 3, 4, and 5 toxicities were experienced by 11, 1, and 2 patients, respectively. However all grade 4 and 5 toxicities were outside of the irradiated area and attributed to the NIVO alone, and only 4/11 (36%) of the grade 3 toxicities were attributed to the RT-NIVO. The irradiated site in these cases included the brain [2/10 (20%)] and central thorax/abdomen [2/19 (10.5%)], including one unexpected grade 3 pancreatitides following stereotactic body RT to the left adrenal gland. Conclusions: Concurrent RT-NIVO is generally well tolerated, though with potentially increased rates of severe toxicity when irradiating the lung, abdomen, or brain. Pending more definitive data, we recommend counseling patients on the potentially increased rates of side effects from combined immunotherapy and radiotherapy to these locations. Future prospective trials assessing fractionation and sequencing of RT with IT will help inform combined therapy recommendations.

Keywords: combined immunotherapy and radiation, immunotherapy, Nivolumab, toxicity of concurrent immunotherapy and radiation

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Authors: Abou Bakr Merdji, Alaa Mhawish, Xiaofeng Xu, Chunsong Lu

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The characteristics of optical and microphysical properties of aerosols near deserts are analyzed using 11 AErosol RObotic NETwork (AERONET) sites located in 6 major desert areas (the Sahara, Arabia, Thar, Karakum, Taklamakan, and Gobi) between 1998 and 2021. The regional mean of Aerosol Optical Depth (AOD) (coarse AOD (CAOD)) are 0.44 (0.187), 0.38 (0.26), 0.35 (0.24), 0.23 (0.11), 0.20 (0.14), 0.10 (0.05) in the Thar, Arabian, Sahara, Karakum, Taklamakan and Gobi Deserts respectively, while an opposite for AE and Fine Mode Fraction (FMF). Higher extinctions are associated with larger particles (dust) over all the main desert regions. This is shown by the almost inversely proportional variations of AOD and CAOD compared with AE and FMF. Coarse particles contribute the most to the total AOD over the Sahara Desert compared to those in the other deserts all year round. Related to the seasonality of dust events, the maximum AOD (CAOD) generally appears in summer and spring, while the minimum is in winter. The mean values of absorbing AOD (AAOD), Absorbing AE (AAE), and the Single Scattering Albedo (SSA) for all sites ranged from 0.017 to 0.037, from 1.16 to 2.81 and from 0.844 to 0.944, respectively. Generally, the highest absorbing aerosol load are observed over the Thar, followed by the Karakum, the Sahara, the Gobi, and then the Taklamakan Deserts, while the largest absorbing particles are observed in the Sahara followed by Arabia, Thar, Karakum, Gobi, and the smallest over the Taklamakan Desert. Similar absorption qualities are observed over the Sahara, Arabia, Thar, and Karakum Deserts, with SSA values varying between 0.90 and 0.91, whereas the most and least absorbing particles are observed at the Taklamakan and the Gobi Deserts, respectively. The seasonal AAODs are distinctly different over the deserts, with parts of Sahara and Arabia, and the Dalanzadgad sites experiencing the maximum in summer, the Southern Sahara, Western Arabia, Jaipur, and Dushanbe in winter, while the Eastern Arabia and the Muztagh Ata in autumn. AAOD and SSA spectra are consistent with dust-dominated conditions that resulted from aerosol typing (dust and polluted dust) at most deserts, with a possible presence of other absorbing particles apart from dust at Arabia, the Taklamakan, and the Gobi Desert sites.

Keywords: sahara, AERONET, desert, dust belt, aerosols, optical properties

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Authors: Z. Jamalzadeh, A. Niaei, H. Erfannia

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Due to developing industries, the emission of pollutants such as NOx, SOx, and CO2 are rapidly increased. Generally, NOx is attributed to the mono nitrogen oxides of NO and NO2 that is one of the most important atmospheric contaminants. Hence, controlling the emission of nitrogen oxides is environmentally urgent. Selective catalytic reduction of NOx is one of the most common techniques for NOx removal in which zeolites have wide application due to their high performance. In zeolitic processes, the catalytic reaction occurs mostly in the pores. Therefore, investigation of the adsorption phenomena of the molecules in order to gain an insight and understand the catalytic cycle is of important. Hence, in current study, benefiting from molecular simulations, the adsorption phenomena in the nanocatalysts of SCR of NOx process was investigated in order to get a good insight of the catalysts’ behavior. The effect of cation addition to the support in the catalysts’ behavior through adsorption step was explored by Mont Carlo (MC) using Materials Studio Package. Simulation time of 1 Ns accompanying 1 fs time step, COMPASS27 Force Field and the cut off radios of 12.5 Ȧ was applied for performed runs. It was observed that the adsorption capacity increases in the presence of cations. The sorption isotherms demonstrated the behavior of type I isotherm categories and sorption capacity diminished with increase in temperature whereas an increase was observed at high pressures. Besides, NO sorption showed higher sorption capacity than NH3 in H–ZSM5. In this respect, the energy distributions signified that the molecules could adsorb in just one sorption site at the catalyst and the sorption energy of NO was stronger than the NH3 in H-ZSM5. Furthermore, the isosteric heat of sorption data showed nearly same values for the molecules; however, it indicated stronger interactions of NO molecules with H-ZSM5 zeolite compared to the isosteric heat of NH3 which was low in value.

Keywords: Monte Carlo simulation, adsorption, NOx, ZSM5

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Authors: Jia Xue, Frederica G. Lamar, Siyu Lin, Jennifer G. Lamori, Samendra Sherchan

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Brackish water samples from Lake Pontchartrain in Louisiana were assessed for the presence of pathogenic amoeba Naegleria fowleri, which causes primary amoebic meningoencephalitis (PAM). In our study, quantitative polymerase chain reaction (qPCR) methods were used to determine N. fowleri, E. coli, and Enterococcus in water collected from Lake Pontchartrain. A total of 158 water samples were analyzed over the 10-month sampling period. Statistically significant positive correlation between water temperature and N. fowleri concentration was observed. N. fowleri target sequence was detected at 35.4% (56/158) of the water samples from ten sites around the Lake ranged from 11.6 GC/100 ml water to 457.8 GC/100 ml water. A single factor (ANOVA) analysis shows the average concentration of N. fowleri in summer (119.8 GC/100 ml) was significantly higher than in winter (58.6 GC/100 ml) (p < 0.01). Statistically significant positive correlations were found between N. fowleri and qPCR E. coli results and N. fowleri and colilert E. coli (culture method), respectively. A weak positive correlation between E. coli and Enterococcus was observed from both qPCR (r = 0.27, p < 0.05) and culture based method (r = 0.52, p < 0.05). Meanwhile, significant positive correlation between qPCR and culture based methods for E. coli (r = 0.30, p < 0.05) and Enterococcus concentration was observed (r = 0.26, p < 0.05), respectively. Future research is needed to determine whether sediment is a source of N. fowleri found in the water column.

Keywords: brackish water, Escherichia coli, Enterococcus, Naegleria fowleri, primary amoebic meningoencephalitis (PAM), qPCR

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Authors: Julia Ive, Lucia Specia

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Understanding and detecting toxicity is an important problem to support safer human interactions online. Our work focuses on the important problem of contextual toxicity detection, where automated classifiers are tasked with determining whether a short textual segment (usually a sentence) is toxic within its conversational context. We use “toxicity” as an umbrella term to denote a number of variants commonly named in the literature, including hate, abuse, offence, among others. Detecting toxicity in context is a non-trivial problem and has been addressed by very few previous studies. These previous studies have analysed the influence of conversational context in human perception of toxicity in controlled experiments and concluded that humans rarely change their judgements in the presence of context. They have also evaluated contextual detection models based on state-of-the-art Deep Learning and Natural Language Processing (NLP) techniques. Counterintuitively, they reached the general conclusion that computational models tend to suffer performance degradation in the presence of context. We challenge these empirical observations by devising better contextual predictive models that also rely on NLP data augmentation techniques to create larger and better data. In our study, we start by further analysing the human perception of toxicity in conversational data (i.e., tweets), in the absence versus presence of context, in this case, previous tweets in the same conversational thread. We observed that the conclusions of previous work on human perception are mainly due to data issues: The contextual data available does not provide sufficient evidence that context is indeed important (even for humans). The data problem is common in current toxicity datasets: cases labelled as toxic are either obviously toxic (i.e., overt toxicity with swear, racist, etc. words), and thus context does is not needed for a decision, or are ambiguous, vague or unclear even in the presence of context; in addition, the data contains labeling inconsistencies. To address this problem, we propose to automatically generate contextual samples where toxicity is not obvious (i.e., covert cases) without context or where different contexts can lead to different toxicity judgements for the same tweet. We generate toxic and non-toxic utterances conditioned on the context or on target tweets using a range of techniques for controlled text generation(e.g., Generative Adversarial Networks and steering techniques). On the contextual detection models, we posit that their poor performance is due to limitations on both of the data they are trained on (same problems stated above) and the architectures they use, which are not able to leverage context in effective ways. To improve on that, we propose text classification architectures that take the hierarchy of conversational utterances into account. In experiments benchmarking ours against previous models on existing and automatically generated data, we show that both data and architectural choices are very important. Our model achieves substantial performance improvements as compared to the baselines that are non-contextual or contextual but agnostic of the conversation structure.

Keywords: contextual toxicity detection, data augmentation, hierarchical text classification models, natural language processing

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Authors: Sabiu Bala Muhammad, Rosli Saad

Abstract:

Multiple linear regression (MLR) models for fast estimation of true subsurface resistivity from apparent resistivity field measurements are developed and assessed in this study. The parameters investigated were apparent resistivity (ρₐ), horizontal location (X) and depth (Z) of measurement as the independent variables; and true resistivity (ρₜ) as the dependent variable. To achieve linearity in both resistivity variables, datasets were first transformed into logarithmic domain following diagnostic checks of normality of the dependent variable and heteroscedasticity to ensure accurate models. Four MLR models were developed based on hierarchical combination of the independent variables. The generated MLR coefficients were applied to another data set to estimate ρₜ values for validation. Contours of the estimated ρₜ values were plotted and compared to the observed data plots at the colour scale and blanking for visual assessment. The accuracy of the models was assessed using coefficient of determination (R²), standard error (SE) and weighted mean absolute percentage error (wMAPE). It is concluded that the MLR models can estimate ρₜ for with high level of accuracy.

Keywords: apparent resistivity, depth, horizontal location, multiple linear regression, true resistivity

Procedia PDF Downloads 273