Search results for: extraction technique

Authors: Yasuyuki Takahashi, Hayato Ishimura, Masao Miyagawa, Teruhito Mochizuki

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Quantitative measurement of myocardium perfusion is possible with single photon emission computed tomography (SPECT) using a semiconductor detector. However, accumulation of ^99mTc-tetrofosmin in the liver may make it difficult to assess that accurately in the inferior myocardium. Our idea is to reduce the high accumulation in the liver by using dynamic SPECT imaging and a technique called time subtraction. We evaluated the performance of a new SPECT system with a cadmium-zinc-telluride solid-state semi- conductor detector (Discovery NM 530c; GE Healthcare). Our system acquired list-mode raw data over 10 minutes for a typical patient. From the data, ten SPECT images were reconstructed, one for every minute of acquired data. Reconstruction with the semiconductor detector was based on an implementation of a 3-D iterative Bayesian reconstruction algorithm. We studied 20 patients with coronary artery disease (mean age 75.4 ± 12.1 years; range 42-86; 16 males and 4 females). In each subject, 259 MBq of ^99mTc-tetrofosmin was injected intravenously. We performed both a phantom and a clinical study using dynamic SPECT. An approximation to a liver-only image is obtained by reconstructing an image from the early projections during which time the liver accumulation dominates (0.5~2.5 minutes SPECT image-5~10 minutes SPECT image). The extracted liver-only image is then subtracted from a later SPECT image that shows both the liver and the myocardial uptake (5~10 minutes SPECT image-liver-only image). The time subtraction of liver was possible in both a phantom and the clinical study. The visualization of the inferior myocardium was improved. In past reports, higher accumulation in the myocardium due to the overlap of the liver is un-diagnosable. Using our time subtraction method, the image quality of the ^99mTc-tetorofosmin myocardial SPECT image is considerably improved.

Keywords: 99mTc-tetrofosmin, dynamic SPECT, time subtraction, semiconductor detector

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Authors: R. Bouhennache, T. Bouden, A. A. Taleb, A. Chaddad

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In this paper we propose a method to map the urban areas. The method uses an arithmetic calculation processed from the land features indexes and Tasseled cap transformation TC of multi spectral Thematic Mapper Landsat TM image. For this purpose the derived indexes image from the original image such SAVI the soil adjusted vegetation index, UI the urban Index, and EBBI the enhanced built up and bareness index were staked to form a new image and the bands were uncorrelated, also the Spectral Angle Mapper (SAM) and Spectral Information Divergence (SID) supervised classification approaches were first applied on the new image TM data using the reference spectra of the spectral library and subsequently the four urban, vegetation, water and soil land cover categories were extracted with their accuracy assessment.The urban features were represented using a logic calculation applied to the brightness, UI-SAVI, NDBI-greenness and EBBI- brightness data sets. The study applied to Blida and mentioned that the urban features can be mapped with an accuracy ranging from 92 % to 95%.

Keywords: EBBI, SAVI, Tasseled Cap Transformation, UI

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Authors: Fani Sakellariadou, Danae Antivachis

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Purpose of this paper is to evaluate the environmental status of a coastal Mediterranean lake, named Koumoundourou, located in the northeastern coast of Elefsis Bay, in the western region of Attiki in Greece, 15 km far from Athens. It is preserved from ancient times having an important archaeological interest. Koumoundourou lake is also considered as a valuable wetland accommodating an abundant flora and fauna, with a variety of bird species including a few world’s threatened ones. Furthermore, it is a heavily modified lake, affected by various anthropogenic pollutant sources which provide industrial, urban and agricultural contaminants. The adjacent oil refineries and the military depot are the major pollution providers furnishing with crude oil spills and leaks. Moreover, the lake accepts a quantity of groundwater leachates from the major landfill of Athens. The environmental status of the lake results from the intensive land uses combined with the permeable lithology of the surrounding area and the existence of karstic springs which discharge calcareous mountains. Sediment samples were collected along the shoreline of the lake using a Van Veen grab stainless steel sampler. They were studied for the determination of the total metal content and the metal fractionation in geochemical phases as well as the characterization of the dissolved organic matter (DOM). These constituents have a significant role in the ecological consideration of the lake. Metals may be responsible for harmful environmental impacts. The metal partitioning offers comprehensive information for the origin, mode of occurrence, biological and physicochemical availability, mobilization and transport of metals. Moreover, DOM has a multifunctional importance interacting with inorganic and organic contaminants leading to biogeochemical and ecological effects. The samples were digested using microwave heating with a suitable laboratory microwave unit. For the total metal content, the samples were treated with a mixture of strong acids. Then, a sequential extraction procedure was applied for the removal of exchangeable, carbonate hosted, reducible, organic/sulphides and residual fractions. Metal content was determined by an ICP-MS (Perkin Elmer, ICP MASS Spectrophotometer NexION 350D). Furthermore, the DOM was removed via a gentle extraction procedure and then it was characterized by fluorescence spectroscopy using a Perkin-Elmer LS 55 luminescence spectrophotometer equipped with the WinLab 4.00.02 software for data processing (Agilent, Cary Eclipse Fluorescence). Mono dimensional emission, excitation, synchronous-scan excitation and total luminescence spectra were recorded for the classification of chromophoric units present in the aqueous extracts. Total metal concentrations were determined and compared with those of the Elefsis gulf sediments. Element partitioning showed the anthropogenic sources and the contaminant bioavailability. All fluorescence spectra, as well as humification indices, were evaluated in detail to find out the nature and origin of DOM. All the results were compared and interpreted to evaluate the environmental quality of Koumoundourou lake and the need for environmental management and protection.

Keywords: anthropogenic contaminant, dissolved organic matter, lake, metal, pollution

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Authors: Takahiro Nishigaki, Takashi Onoda

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In recent years, the number of document data has been increasing since the spread of the Internet. Many methods have been studied for extracting topics from large document data. We proposed Independent Topic Analysis (ITA) to extract topics independent of each other from large document data such as newspaper data. ITA is a method for extracting the independent topics from the document data by using the Independent Component Analysis. The topic represented by ITA is represented by a set of words. However, the set of words is quite different from the topics the user imagines. For example, the top five words with high independence of a topic are as follows. Topic1 = {"scor", "game", "lead", "quarter", "rebound"}. This Topic 1 is considered to represent the topic of "SPORTS". This topic name "SPORTS" has to be attached by the user. ITA cannot name topics. Therefore, in this research, we propose a method to obtain topics easy for people to understand by using the web search engine, topics given by the set of words given by independent topic analysis. In particular, we search a set of topical words, and the title of the homepage of the search result is taken as the topic name. And we also use the proposed method for some data and verify its effectiveness.

Keywords: independent topic analysis, topic extraction, topic naming, web search engine

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Authors: Daira Radouane, Naim Boudmagh, Hamada Adel

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The but of this handling is to use the technique of the shearing with a mechanism lapping machine of image: a prism of Wollaston. We want to characterize this prism in order to be able to employ it later on in an analysis by shearing. A prism of Wollaston is a prism produced in a birefringent material i.e. having two indexes of refraction. This prism is cleaved so as to present the directions associated with these indices in its face with entry. It should be noted that these directions are perpendicular between them.

Keywords: non destructive control, aluminium, interferometry, treatment of image

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Authors: Shraddha Srivastava, N. K. Painuly, S. P. Mishra, Navin Singh, Muhsin Punchankandy, Kirti Srivastava, M. L. B. Bhatt

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Various optimization methods used in interstitial brachytherapy are based on dwell positions and dwell weights alteration to produce dose distribution based on the implant geometry. Since these optimization schemes are not anatomy based, they could lead to deviations from the desired plan. This study was henceforth carried out to compare anatomy-based Inverse Planning Simulated Annealing (IPSA) optimization technique with graphical and geometrical optimization methods in interstitial high dose rate brachytherapy planning of cervical carcinoma. Six patients with 12 CT data sets of MUPIT implants in HDR brachytherapy of cervical cancer were prospectively studied. HR-CTV and organs at risk (OARs) were contoured in Oncentra treatment planning system (TPS) using GYN GEC-ESTRO guidelines on cervical carcinoma. Three sets of plans were generated for each fraction using IPSA, graphical optimization (GrOPT) and geometrical optimization (GOPT) methods. All patients were treated to a dose of 20 Gy in 2 fractions. The main objective was to cover at least 95% of HR-CTV with 100% of the prescribed dose (V100 ≥ 95% of HR-CTV). IPSA, GrOPT, and GOPT based plans were compared in terms of target coverage, OAR doses, homogeneity index (HI) and conformity index (COIN) using dose-volume histogram (DVH). Target volume coverage (mean V100) was found to be 93.980.87%, 91.341.02% and 85.052.84% for IPSA, GrOPT and GOPT plans respectively. Mean D90 (minimum dose received by 90% of HR-CTV) values for IPSA, GrOPT and GOPT plans were 10.19 ± 1.07 Gy, 10.17 ± 0.12 Gy and 7.99 ± 1.0 Gy respectively, while D100 (minimum dose received by 100% volume of HR-CTV) for IPSA, GrOPT and GOPT plans was 6.55 ± 0.85 Gy, 6.55 ± 0.65 Gy, 4.73 ± 0.14 Gy respectively. IPSA plans resulted in lower doses to the bladder (D₂

Keywords: cervical cancer, HDR brachytherapy, IPSA, MUPIT

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Authors: Dana Alina Magdas, Nicoleta Simona Vedeanu, Ioana Feher, Rares Stiufiuc

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Food and beverages authentication using rapid and non-expensive analytical tools represents nowadays an important challenge. In this regard, the potential of vibrational techniques in food authentication has gained an increased attention during the last years. For wines discrimination, Raman spectroscopy appears more feasible to be used as compared with IR (infrared) spectroscopy, because of the relatively weak water bending mode in the vibrational spectroscopy fingerprint range. Despite this, the use of Raman technique in wine discrimination is in an early stage. Taking this into consideration, the wine discrimination potential of surface-enhanced Raman scattering (SERS) technique is reported in the present work. The novelty of this study, compared with the previously reported studies, concerning the application of vibrational techniques in wine discrimination consists in the fact that the present work presents the wines differentiation based on the individual signals obtained from deconvoluted spectra. In order to achieve wines classification with respect to variety, geographical origin and vintage, the peaks intensities obtained after spectra deconvolution were compared using supervised chemometric methods like Linear Discriminant Analysis (LDA). For this purpose, a set of 20 white Romanian wines from different viticultural Romanian regions four varieties, was considered. Chemometric methods applied directly to row SERS experimental spectra proved their efficiency, but discrimination markers identification found to be very difficult due to the overlapped signals as well as for the band shifts. By using this approach, a better general view related to the differences that appear among the wines in terms of compositional differentiation could be reached.

Keywords: chemometry, SERS, variety, wines discrimination

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Authors: M. Alsharqawi, T. Zayed, S. Abu Dabous

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To ensure safety and serviceability of bridge infrastructure, accurate condition assessment and rating methods are needed to provide basis for bridge Maintenance, Repair and Replacement (MRR) decisions. In North America, the common practices to assess condition of bridges are through visual inspection. These practices are limited to detect surface defects and external flaws. Further, the thresholds that define the severity of bridge deterioration are selected arbitrarily. The current research discusses the main deteriorations and defects identified during visual inspection and Non-Destructive Evaluation (NDE). NDE techniques are becoming popular in augmenting the visual examination during inspection to detect subsurface defects. Quality inspection data and accurate condition assessment and rating are the basis for determining appropriate MRR decisions. Thus, in this paper, a novel method for bridge condition assessment using the Quality Function Deployment (QFD) theory is utilized. The QFD model is designed to provide an integrated condition by evaluating both the surface and subsurface defects for concrete bridges. Moreover, an integrated condition rating index with four thresholds is developed based on the QFD condition assessment model and using K-means clustering technique. Twenty case studies are analyzed by applying the QFD model and implementing the developed rating index. The results from the analyzed case studies show that the proposed threshold model produces robust MRR recommendations consistent with decisions and recommendations made by bridge managers on these projects. The proposed method is expected to advance the state of the art of bridges condition assessment and rating.

Keywords: concrete bridge decks, condition assessment and rating, quality function deployment, k-means clustering technique

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Authors: M. R. Ahmad, I. Musirin, M. M. Othman, N. A. Rahmat

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Plug-in Hybrid-Electric Vehicle (PHEV) has gained immense popularity in recent years. PHEV offers numerous advantages compared to the conventional internal-combustion engine (ICE) vehicle. Millions of PHEVs are estimated to be on the road in the USA by 2020. Uncoordinated PHEV charging is believed to cause severe impacts to the power grid; i.e. feeders, lines and transformers overload and voltage drop. Nevertheless, improper PHEV data model used in such studies may cause the findings of their works is in appropriated. Although smart charging is more attractive to researchers in recent years, its implementation is not yet attainable on the street due to its requirement for physical infrastructure readiness and technology advancement. As the first step, it is finest to study the impact of charging PHEV based on real vehicle travel data from National Household Travel Survey (NHTS) and at present charging rate. Due to the lack of charging station on the street at the moment, charging PHEV at home is the best option and has been considered in this work. This paper proposed a technique that comprehensively presents the impact of charging PHEV on power system networks considering huge numbers of PHEV samples with its traveling data pattern. Vehicles Charging Load Profile (VCLP) is developed and implemented in IEEE 30-bus test system that represents a portion of American Electric Power System (Midwestern US). Normalization technique is used to correspond to real time loads at all buses. Results from the study indicated that charging PHEV using opportunity charging will have significant impacts on power system networks, especially whereas bigger battery capacity (kWh) is used as well as for higher penetration level.

Keywords: plug-in hybrid electric vehicle, transportation electrification, impact of charging PHEV, electricity demand profile, load profile

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Authors: Khalil H. Al-Bayati, Khalid Omar Al-Baiti

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The energy expectation value for Li-like ions systems (Li, Be+ and Be2+) hasbeen calculated and examined within the ground state (1s2sα)^2 S and the excited state (1s3sα)^2 S in position space. The partitioning technique of Hartree-Fock (H-F) has been used for existing wavefnctions.

Keywords: energy expectation value, atomic systems, ground and excited states, Hartree-Fock approximation

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Authors: Nadia Masood Khan, Muhammad Salman Khan, Gul Muhammad Khan

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Cardiologists perform cardiac auscultation to detect abnormalities in heart sounds. Since accurate auscultation is a crucial first step in screening patients with heart diseases, there is a need to develop computer-aided detection/diagnosis (CAD) systems to assist cardiologists in interpreting heart sounds and provide second opinions. In this paper different algorithms are implemented for automated heart sound classification using unsegmented phonocardiogram (PCG) signals. Support vector machine (SVM), artificial neural network (ANN) and cartesian genetic programming evolved artificial neural network (CGPANN) without the application of any segmentation algorithm has been explored in this study. The signals are first pre-processed to remove any unwanted frequencies. Both time and frequency domain features are then extracted for training the different models. The different algorithms are tested in multiple scenarios and their strengths and weaknesses are discussed. Results indicate that SVM outperforms the rest with an accuracy of 73.64%.

Keywords: pattern recognition, machine learning, computer aided diagnosis, heart sound classification, and feature extraction

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Authors: Jaspreet Singh, Gurvinder Singh, Prabhsimran Singh, Rajinder Singh, Prithvipal Singh, Karanjeet Singh Kahlon, Ravinder Singh Sawhney

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Morphological evaluation of Indian languages is one of the burgeoning fields in the area of Natural Language Processing (NLP). The evaluation of a language is an eminent task in the era of information retrieval and text mining. The extraction and classification of knowledge from text can be exploited for sentiment analysis and morphological evaluation. This study coalesce morphological evaluation and sentiment analysis for the task of classification of farmer suicide cases reported in Punjab state of India. The pre-processing of Punjabi text involves morphological evaluation and normalization of Punjabi word tokens followed by the training of proposed model using deep learning classification on Punjabi language text extracted from online Punjabi news reports. The class-wise accuracies of sentiment prediction for four negatively oriented classes of farmer suicide cases are 93.85%, 88.53%, 83.3%, and 95.45% respectively. The overall accuracy of sentiment classification obtained using proposed framework on 275 Punjabi text documents is found to be 90.29%.

Keywords: deep neural network, farmer suicides, morphological processing, punjabi text, sentiment analysis

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Authors: Aaron Akinloye

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this research focuses on the impact of jungle justice on the emotional health challenges experienced by residents in the Lagos metropolitan city in Nigeria. Jungle justice refers to the practice of individuals taking the law into their own hands and administering punishment without proper legal procedures. The aim of this study is to investigate the influence of jungle justice on the emotional challenges faced by residents in Lagos. The specific objectives of the study are to examine the effects of jungle justice on trauma, pressure, fear, and depression among residents. The study adopts a descriptive survey research design and uses a questionnaire as the research instrument. The population of the study consisted of residents in the three senatorial districts that make up Lagos State. A simple random sampling technique was used to select two Local Government Areas (Yaba and Shomolu) from each of the three senatorial districts of Lagos State. Also, a simple random sampling technique was used to select fifty (50) residents from each of the chosen Local Government Areas to make three hundred (300) residents that formed the sample of the study. Accidental sampling technique is employed to select a sample of 300 residents. Data on the variables of interest is collected using a self-developed questionnaire. The research instrument undergoes validation through face, content, and construct validation processes. The reliability coefficient of the instrument is found to be 0.84. The study reveals that jungle justice significantly influences trauma, pressure, fear, and depression among residents in Lagos metropolitan city. The statistical analysis shows significant relationships between jungle justice and these emotional health challenges (df (298) t= 2.33, p< 0.05; df (298) t= 2.16, p< 0.05; df (298) t= 2.20, p< 0.05; df (298) t= 2.14, p< 0.05). This study contributes to the literature by highlighting the negative effects of jungle justice on the emotional well-being of residents. It emphasizes the importance of addressing this issue and implementing measures to prevent such vigilante actions. Data is collected through the administration of the self-developed questionnaire to the selected residents. The collected data is then analyzed using inferential statistics, specifically mean analysis, to examine the relationships between jungle justice and the emotional health challenges experienced by the residents. The main question addressed in this study is how jungle justice affects the emotional health challenges faced by residents in Lagos metropolitan city. Conclusion: The study concludes that jungle justice has a significant influence on trauma, pressure, fear, and depression among residents. To address this issue, recommendations are made, including the implementation of comprehensive awareness campaigns, improvement of law enforcement agencies, development of support systems for victims, and revision of the legal framework to effectively address jungle justice. Overall, this research contributes to the understanding of the consequences of jungle justice and provides recommendations for intervention to protect the emotional well-being of residents in Lagos metropolitan city.

Keywords: jungle justice, emotional health, depression, anger

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Authors: Min-Ha Hong, Kee-Won Kim, Seung-Hoon Kim

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The character in the story-based content, such as novels and movies, is one of the core elements to understand the story. In particular, the character’s tendency is an important factor to analyze the story-based content, because it has a significant influence on the storyline. If readers have the knowledge of the tendency of characters before reading a novel, it will be helpful to understand the structure of conflict, episode and relationship between characters in the novel. It may therefore help readers to select novel that the reader wants to read. In this paper, we propose a method of extracting the tendency of the characters from a novel written in Korean. In advance, we build the dictionary with pairs of the emotional words in Korean and English since the emotion words in the novel’s sentences express character’s feelings. We rate the degree of polarity (positive or negative) of words in our emotional words dictionary based on SenticNet. Then we extract characters and emotion words from sentences in a novel. Since the polarity of a word grows strong or weak due to sentence features such as quotations and modifiers, our proposed method consider them to calculate the polarity of characters. The information of the extracted character’s polarity can be used in the book search service or book recommendation service.

Keywords: character tendency, data mining, emotion word, Korean novel

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Authors: Vijay H. Ingole, Efthimia Lioliou

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Indirubin, a key bioactive component of traditional Chinese medicine, has gained increasing recognition for its potential in modern biomedical applications, particularly in pharmacology and therapeutics. The present work aimed to harness the potential by engineering an Escherichia coli strain capable of high-yield indirubin production. Through meticulous genetic engineering, we optimized the metabolic pathways in E. coli to enhance indirubin synthesis. Further, to explored the optimization of culture media and indirubin yield via batch and fed-batch fermentation techniques. By fine-tuning upstream process (USP) parameters, including nutrient composition, pH, temperature, and aeration, we established conditions that maximized both cell growth and indirubin production. Additionally, significant efforts were dedicated to refining downstream process (DSP) conditions for the extraction, purification, and quantification of indirubin. Utilizing advanced biochemical methods and analytical techniques such as UHPLC, we ensured the production of high purity indirubin. This approach not only improved the economic viability of indirubin bioproduction but also aligned with the principles of green production and sustainability.

Keywords: indirubin, bacterial strain, fermentation, HPLC

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Authors: Soraya Hoornam, Zeinab Sanaee

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Lithium-ion batteries are widely used for providing energy for mobile electronic devices. Graphite is a traditional anode material that was used in almost all commercialized lithium-ion batteries. It gives a specific capacity of 372 mAh/g for lithium storage. But there are multiple better choices for storing lithium that propose significantly higher specific capacities. As an example, silicon-based materials can be mentioned. In this regard, SiO₂ material can offer a huge specific capacity of 1965 mAh/g. Due to this high lithium storage ability, large volume change occurs in this electrode material during insertion and extraction of lithium, which may lead to cracking and destruction of the electrode. The use of nanomaterials instead of bulk material can significantly solve this problem. In addition, if we insert lithium in the active material of the battery before its cycling, which is called pre-lithiation, a further enhancement in the performance is expected. Here, we have fabricated an anode electrode of the battery using SiO₂ nanomaterial mixed with Graphite and assembled a lithium-ion battery half-cell with this electrode. Next, a pre-lithiation was performed on the SiO₂ nanoparticle-containing electrode, and the resulting anode material was investigated. This electrode has great potential for high-performance lithium-ion batteries.

Keywords: SiO₂ nanoparticles, lithium-ion battery, pre-lithiation, anode material

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Authors: Cátia Gonçalves, Teresa Nunes, Inês Pina, Ana Vicente, C. Alves, Felix Charvet, Daniel Neves, A. Matos

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The production of charcoal relies on rudimentary technologies using traditional brick kilns. Charcoal is produced under pyrolysis conditions: breaking down the chemical structure of biomass under high temperature in the absence of air. The amount of the pyrolysis products (charcoal, pyroligneous extract, and flue gas) depends on various parameters, including temperature, time, pressure, kiln design, and wood characteristics like the moisture content. This activity is recognized for its inefficiency and high pollution levels, but it is poorly characterized. This activity is widely distributed and is a vital economic activity in certain regions of Portugal, playing a relevant role in the management of woody residues. The location of the units establishes the biomass used for charcoal production. The Portalegre district, in the Alto Alentejo region (Portugal), is a good example, essentially with rural characteristics, with a predominant farming, agricultural, and forestry profile, and with a significant charcoal production activity. In this district, a recent inventory identifies almost 50 charcoal production units, equivalent to more than 450 kilns, of which 80% appear to be in operation. A field campaign was designed with the objective of determining the composition of the emissions released during a charcoal production cycle. A total of 30 samples of particulate matter and 20 gas samples in Tedlar bags were collected. Particulate and gas samplings were performed in parallel, 2 in the morning and 2 in the afternoon, alternating the inlet heads (PM₁₀ and PM₂.₅), in the particulate sampler. The gas and particulate samples were collected in the plume as close as the emission chimney point. The biomass (dry basis) used in the carbonization process was a mixture of cork oak (77 wt.%), holm oak (7 wt.%), stumps (11 wt.%), and charred wood (5 wt.%) from previous carbonization processes. A cylindrical batch kiln (80 m³) with 4.5 m diameter and 5 m of height was used in this study. The composition of the gases was determined by gas chromatography, while the particulate samples (PM₁₀, PM₂.₅) were subjected to different analytical techniques (thermo-optical transmission technique, ion chromatography, HPAE-PAD, and GC-MS after solvent extraction) after prior gravimetric determination, to study their organic and inorganic constituents. The charcoal production cycle presents widely varying operating conditions, which will be reflected in the composition of gases and particles produced and emitted throughout the process. The concentration of PM₁₀ and PM₂.₅ in the plume was calculated, ranging between 0.003 and 0.293 g m⁻³, and 0.004 and 0.292 g m⁻³, respectively. Total carbon, inorganic ions, and sugars account, in average, for PM10 and PM₂.₅, 65 % and 56 %, 2.8 % and 2.3 %, 1.27 %, and 1.21 %, respectively. The organic fraction studied until now includes more than 30 aliphatic compounds and 20 PAHs. The emission factors of particulate matter to produce charcoal in the traditional kiln were 33 g/kg (wooddb) and 27 g/kg (wooddb) for PM₁₀ and PM₂.₅, respectively. With the data obtained in this study, it is possible to fill the lack of information about the environmental impact of the traditional charcoal production in Portugal. Acknowledgment: Authors thanks to FCT – Portuguese Science Foundation, I.P. and to Ministry of Science, Technology and Higher Education of Portugal for financial support within the scope of the project CHARCLEAN (PCIF/GVB/0179/2017) and CESAM (UIDP/50017/2020 + UIDB/50017/2020).

Keywords: brick kilns, charcoal, emission factors, PAHs, total carbon

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Authors: Amber Dhoot, Tarush Gupta, Andrea Gurr, William Jenkins, Sandro Pietrunti, Alexis Tang

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Background: The COVID-19 pandemic has driven pharmacovigilance towards a new paradigm. Nowadays, more people than ever before are recognising and reporting adverse reactions from medications, treatments, and vaccines. In the modern era, with over 3.8 billion users, social media has become the most accessible medium for people to voice their opinions and so provides an opportunity to engage with more patient-centric and accessible pharmacovigilance. However, the pharmaceutical industry has been slow to incorporate social media into its modern pharmacovigilance strategy. This project aims to make social media a more effective tool in pharmacovigilance, and so reduce drug costs, improve drug safety and improve patient outcomes. This will be achieved by firstly uncovering and categorising the barriers facing the widespread adoption of social media in pharmacovigilance. Following this, the potential opportunities of social media will be explored. We will then propose realistic, practical recommendations to make social media a more effective tool for pharmacovigilance. Methodology: A comprehensive systematic literature review was conducted to produce a categorised summary of these barriers. This was followed by conducting 11 semi-structured interviews with pharmacovigilance experts to confirm the literature review findings whilst also exploring the unpublished and real-life challenges faced by those in the pharmaceutical industry. Finally, a survey of the general public (n = 112) ascertained public knowledge, perception, and opinion regarding the use of their social media data for pharmacovigilance purposes. This project stands out by offering perspectives from the public and pharmaceutical industry that fill the research gaps identified in the literature review. Results: Our results gave rise to several key analysis points. Firstly, inadequacies of current Natural Language Processing algorithms hinder effective pharmacovigilance data extraction from social media, and where data extraction is possible, there are significant questions over its quality. Social media also contains a variety of biases towards common drugs, mild adverse drug reactions, and the younger generation. Additionally, outdated regulations for social media pharmacovigilance do not align with new, modern General Data Protection Regulations (GDPR), creating ethical ambiguity about data privacy and level of access. This leads to an underlying mindset of avoidance within the pharmaceutical industry, as firms are disincentivised by the legal, financial, and reputational risks associated with breaking ambiguous regulations. Conclusion: Our project uncovered several barriers that prevent effective pharmacovigilance on social media. As such, social media should be used to complement traditional sources of pharmacovigilance rather than as a sole source of pharmacovigilance data. However, this project adds further value by proposing five practical recommendations that improve the effectiveness of social media pharmacovigilance. These include: prioritising health-orientated social media; improving technical capabilities through investment and strategic partnerships; setting clear regulatory guidelines using multi-stakeholder processes; creating an adverse drug reaction reporting interface inbuilt into social media platforms; and, finally, developing educational campaigns to raise awareness of the use of social media in pharmacovigilance. Implementation of these recommendations would speed up the efficient, ethical, and systematic adoption of social media in pharmacovigilance.

Keywords: adverse drug reaction, drug safety, pharmacovigilance, social media

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Authors: Carol Anne Hargreaves

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A key issue in stock investment is how to select representative features for stock selection. The objective of this paper is to firstly determine whether an automated stock investment system, using machine learning techniques, may be used to identify a portfolio of growth stocks that are highly likely to provide returns better than the stock market index. The second objective is to identify the technical features that best characterize whether a stock’s price is likely to go up and to identify the most important factors and their contribution to predicting the likelihood of the stock price going up. Unsupervised machine learning techniques, such as cluster analysis, were applied to the stock data to identify a cluster of stocks that was likely to go up in price – portfolio 1. Next, the principal component analysis technique was used to select stocks that were rated high on component one and component two – portfolio 2. Thirdly, a supervised machine learning technique, the logistic regression method, was used to select stocks with a high probability of their price going up – portfolio 3. The predictive models were validated with metrics such as, sensitivity (recall), specificity and overall accuracy for all models. All accuracy measures were above 70%. All portfolios outperformed the market by more than eight times. The top three stocks were selected for each of the three stock portfolios and traded in the market for one month. After one month the return for each stock portfolio was computed and compared with the stock market index returns. The returns for all three stock portfolios was 23.87% for the principal component analysis stock portfolio, 11.65% for the logistic regression portfolio and 8.88% for the K-means cluster portfolio while the stock market performance was 0.38%. This study confirms that an automated stock investment system using machine learning techniques can identify top performing stock portfolios that outperform the stock market.

Keywords: machine learning, stock market trading, logistic regression, cluster analysis, factor analysis, decision trees, neural networks, automated stock investment system

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Authors: Naeem Ullah, Menglan Duan, Mac Darlington Uche Onuoha

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The lowering of subsea equipment into the deep waters is a challenging job due to the harsh offshore environment. Many researchers have introduced various installation systems to deploy the payload safely into the deep oceans. In general practice, dual floating vessels are not employed owing to the prevalent safety risks and hazards caused by ever-increasing dynamical effects sourced by mutual interaction between the bodies. However, while keeping in the view of the optimal grounds, such as economical one, the Y-method, the two conventional tugboats supporting the equipment by the two independent strands connected to a tri-plate above the equipment, has been employed to study multibody dynamics of the dual barge lifting operations. In this study, the two tugboats and the suspended payload (Y-method) are deployed for the lowering of subsea equipment into the deep waters as a multibody dynamic system. The two-wire ropes are used for the lifting and installation operation by this Y-method installation system. 6-dof (degree of freedom) for each body are considered to establish coupled 18-dof multibody model by embedding technique or velocity transformation technique. The fundamental and prompt advantage of this technique is that the constraint forces can be eliminated directly, and no extra computational effort is required for the elimination of the constraint forces. The inertial frame of reference is taken at the surface of the water as the time-independent frame of reference, and the floating frames of reference are introduced in each body as the time-dependent frames of reference in order to formulate the velocity transformation matrix. The local transformation of the generalized coordinates to the inertial frame of reference is executed by applying the Euler Angle approach. The spherical joints are articulated amongst the multibody as the kinematic joints. The hydrodynamic force, the two-strand forces, the hydrostatic force, and the mooring forces are taken into consideration as the external forces. The radiation force of the hydrodynamic force is obtained by employing the Cummins equation. The wave exciting part of the hydrodynamic force is obtained by using force response amplitude operators (RAOs) that are obtained by the commercial solver ‘OpenFOAM’. The strand force is obtained by considering the wire rope as an elastic spring. The nonlinear hydrostatic force is obtained by the pressure integration technique at each time step of the wave movement. The mooring forces are evaluated by using Faltinsen analytical approach. ‘The Runge Kutta Method’ of Fourth-Order is employed to evaluate the coupled equations of motion obtained for 18-dof multibody model. The results are correlated with the simulated Orcaflex Model. Moreover, the results from Orcaflex Model are compared with the MOSES Model from previous studies. The MBDS of single barge lifting operation from the former studies are compared with the MBDS of the established dual barge lifting operation. The dynamics of the dual barge lifting operation are found larger in magnitude as compared to the single barge lifting operation. It is noticed that the traction at the top connection point of the cable decreases with the increase in the length, and it becomes almost constant after passing through the splash zone.

Keywords: dual barge lifting operation, Y-method, multibody dynamics, shipbuilding, installation of subsea equipment, shipbuilding

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Authors: Beilei Xu, Wencheng Wu, Lei Lin, Rachel Melnyk, Ahmed Ghazi

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In operating rooms, excessive cognitive stress can impede the performance of a surgeon, while low engagement can lead to unavoidable mistakes due to complacency. As a consequence, there is a strong desire in the surgical community to be able to monitor and quantify the cognitive stress of a surgeon while performing surgical procedures. Quantitative cognitiveload-based feedback can also provide valuable insights during surgical training to optimize training efficiency and effectiveness. Various physiological measures have been evaluated for quantifying cognitive stress for different mental challenges. In this paper, we present a study using the cognitive stress measured by the task evoked pupillary response extracted from the time series eye-tracking measurements to predict task difficulties in a virtual reality based robotic surgery training environment. In particular, we proposed a differential-task-difficulty scale, utilized a comprehensive feature extraction approach, and implemented a multitask learning framework and compared the regression accuracy between the conventional single-task-based and three multitask approaches across subjects.

Keywords: surgical metric, task evoked pupillary response, multitask learning, TSFresh

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Authors: Amani Jaber-Awida

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This study examines two bilingual phenomena in the narratives of Arabic Hebrew and Hebrew-English bilingual adults in Israel: CO memories and code-switching (CS). The study examined these phenomena in the context of autobiographical memory, using a cue word technique. Student experimenters held two sessions in the homes of the participants. In separate language sessions, the participant was asked to look first at each of 16 cue words and then to state a concrete memory. After stating the memory, participants reported whether their memories were in the same language of the experiment session or different. Memories were classified as ‘Crossovers’ (CO) or ‘Same Language’ (SL) according to participants' self-reports. Participants were also required to elaborate about the setting, interlocutors and other languages involved in the specific memory. Beyond replicating the procedure of cuing technique, one memory from a specific lifespan period was chosen per participant, and the participant was required to provide further details about it. For the more detailed memories, CS count was conducted. Both bilingual groups confirmed the Reminiscence Bump phenomenon, retrieving more memories in the 10-30 age period. CO memories prevailed in second language sessions (L2). Same language memories were more abundant in first language sessions (L1). Higher CS frequency was found in L2 sessions. Finally, as predicted, 'individual' CS was prevalent in L2 sessions, but 'community-based' CS was not higher in L1 sessions. The two bilingual measures in this study, crossovers, and CS came from different research traditions, the former from an experimental paradigm in the psychology of autobiographical memory based on self-reported judgments, the latter a behavioral measure from linguistics. This merger of approaches offers new insight into the field of bilingual autobiographical memory. In addition, the study attempted to shed light on the investigation of motivations for CS, beginning with Walters’ SPPL Model and concluding with a distinction between ‘community-based’ and individual motivations.

Keywords: bilinguals, code-switching, crossover memories, narratives

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Authors: Reza Fardid, Aliyeh Alipour

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Introduction: Coronary heart disease (CHD) is the most common and deadliest diseases. A coronary angiography is an important tool for the diagnosis and treatment of this disease. Because angiography is performed by exposure to ionizing radiation, it can lead to harmful effects. Ionizing radiation induces double-stranded breaks in DNA, which is a potentially life-threatening injury. The purpose of the present study is an investigation of the phosphorylation of histone H2AX in the location of the double-stranded break in Peripheral blood lymphocytes as an indication of Biological effects of radiation on angiography patients. Materials and Methods: This method is based on measurement of the phosphorylation of histone (gamma-H2AX, gH2AX) level on serine 139 after formation of DNA double-strand break. 5 cc of blood from 24 patients with angiography were sampled before and after irradiation. Blood lymphocytes were removed, fixed and were stained with specific ϒH2AX antibodies. Finally, ϒH2AX signal as an indicator of the double-strand break was measured with Flow Cytometry Technique. Results and discussion: In all patients, an increase was observed in the number of breaks in double-stranded DNA after irradiation (20.15 ± 14.18) compared to before exposure (1.52 ± 0.34). Also, the mean of DNA double-strand break was showed a linear correlation with DAP. However, although induction of DNA double-strand breaks associated with radiation dose in patients, the effect of individual factors such as radiosensitivity and regenerative capacity should not be ignored. If in future we can measure DNA damage response in every patient angiography and it will be used as a biomarker patient dose, will look very impressive on the public health level. Conclusion: Using flow cytometry readings which are done automatically, it is possible to detect ϒH2AX in the number of blood cells. Therefore, the use of this technique could play a significant role in monitoring patients.

Keywords: coronary angiography, DSB of DNA, ϒH2AX, ionizing radiation

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Authors: A. Gokulram

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Industrial waste is often categorized as commercial and non-commercial waste by market value. In many Indian industries and other industrialized countries, the commercial value waste is capitalized and non-commercial waste is dumped to landfill. A lack of adequate research on industrial waste leads to the failure of effective resource management and the non-commercial waste are being considered as commercially non-viable residues. The term Industrial symbiosis refers to the direct inter-firm reuse or exchange of material and energy resource. The resource efficiency of commercial waste is mainly followed by an informal symbiosis in our research area. Some Industrial residues are reused within the facility where they are generated, others are reused directly nearby industrial facilities and some are recycled via the formal and informal market. The act of using industrial waste as a resource for another product faces challenges in India. This research study has observed a major negligence of trust and communication among several bodies to implement effective circular economy in India. This study applies interviewing process across researchers, government bodies, industrialist and designers to understand the challenges of circular economy in India. The study area encompasses an industrial estate in Ahmedabad in the state of Gujarat which comprises of 1200 industries. The research study primarily focuses on making industrial waste as commercial ready resource and implementing Indigenous sustainable practice in modern context to improve resource efficiency. This study attempted to initiate waste exchange platform among several industrialist and used varied methodologies from mail questionnaire to telephone survey. This study makes key suggestions to policy change and sustainable finance to improve circular economy in India.

Keywords: effective resource management, environmental policy, indigenous technique, industrial symbiosis, sustainable finance

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Authors: Sher Muhammad, Mirza Muhammad Waqar

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It is necessary to monitor and identify mangroves types and spatial extent near coastal areas because it plays an important role in coastal ecosystem and environmental protection. This research aims at identifying and mapping mangroves types along Karachi coast ranging from 24.79 to 24.85 degree in latitude and 66.91 to 66.97 degree in longitude using hyperspectral remote sensing data and techniques. Image acquired during February, 2012 through Hyperion sensor have been used for this research. Image preprocessing includes geometric and radiometric correction followed by Minimum Noise Fraction (MNF) and Pixel Purity Index (PPI). The output of MNF and PPI has been analyzed by visualizing it in n-dimensions for end-member extraction. Well-distributed clusters on the n-dimensional scatter plot have been selected with the region of interest (ROI) tool as end members. These end members have been used as an input for classification techniques applied to identify and map mangroves species including Spectral Angle Mapper (SAM), Spectral Feature Fitting (SFF), and Spectral Information Diversion (SID). Only two types of mangroves namely Avicennia Marina (white mangroves) and Avicennia Germinans (black mangroves) have been observed throughout the study area.

Keywords: mangrove, hyperspectral, hyperion, SAM, SFF, SID

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Authors: Strahinja Kovačević, Jelena Vladić, Senka Vidović, Zoran Zeković, Lidija Jevrić, Sanja Podunavac Kuzmanović

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Supercritical extracts of highly valuated medicinal plant Satureja montana were prepared by application of supercritical carbon dioxide extraction in the carbon dioxide pressure range from 125 to 350 bar and temperature range from 40 to 60°C. Using GC/MS method of analysis chemical profiles (aromatic constituents) of S. montana extracts were obtained. Self-training artificial neural networks were applied to predict the retention time of the analyzed terpenes in GC/MS system. The best ANN model obtained was multilayer perceptron (MLP 11-11-1). Hidden activation was tanh and output activation was identity with Broyden–Fletcher–Goldfarb–Shanno training algorithm. Correlation measures of the obtained network were the following: R(training) = 0.9975, R(test) = 0.9971 and R(validation) = 0.9999. The comparison of the experimental and predicted retention times of the analyzed compounds showed very high correlation (R = 0.9913) and significant predictive power of the established neural network.

Keywords: ANN regression, GC/MS, Satureja montana, terpenes

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Authors: Insaf Bellamine, Hamid Tairi

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Detecting moving objects in sequences is an essential step for video analysis. This paper mainly contributes to the Color Space-Time Interest Points (CSTIP) extraction and detection. We propose a new method for detection of moving objects. Two main steps compose the proposed method. First, we suggest to apply the algorithm of the detection of Color Space-Time Interest Points (CSTIP) on both components of the Color Structure-Texture Image Decomposition which is based on a Partial Differential Equation (PDE): a color geometric structure component and a color texture component. A descriptor is associated to each of these points. In a second stage, we address the problem of grouping the points (CSTIP) into clusters. Experiments and comparison to other motion detection methods on challenging sequences show the performance of the proposed method and its utility for video analysis. Experimental results are obtained from very different types of videos, namely sport videos and animation movies.

Keywords: Color Space-Time Interest Points (CSTIP), Color Structure-Texture Image Decomposition, Motion Detection, clustering

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Authors: G. Traini, G. Battistoni, F. Collamati, E. De Lucia, R. Faccini, C. Mancini-Terracciano, M. Marafini, I. Mattei, S. Muraro, A. Sarti, A. Sciubba, E. Solfaroli Camillocci, M. Toppi, S. M. Valle, C. Voena, V. Patera

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In Particle Therapy (PT) treatments a large amount of secondary particles, whose emission point is correlated to the dose released in the crossed tissues, is produced. The measurement of the secondary charged fragments component could represent a valid technique to monitor the beam range during the PT treatments, that is a still missing item in the clinical practice. A sub-millimetrical precision on the beam range measurement is required to significantly optimise the technique and to improve the treatment quality. In this contribution, a detector, named Dose Profiler (DP), is presented. It is specifically planned to monitor on-line the beam range exploiting the secondary charged particles produced in PT Carbon ions treatment. In particular, the DP is designed to track the secondary fragments emitted at large angles with respect to the beam direction (mainly protons), with the aim to reconstruct the spatial coordinates of the fragment emission point extrapolating the measured track toward the beam axis. The DP is currently under development within of the INSIDE collaboration (Innovative Solutions for In-beam Dosimetry in hadrontherapy). The tracker is made by six layers (20 × 20 cm²) of BCF-12 square scintillating fibres (500 μm) coupled to Silicon Photo-Multipliers, followed by two plastic scintillator layers of 6 mm thickness. A system of front-end boards based on FPGAs arranged around the detector provides the data acquisition. The detector characterization with cosmic rays is currently undergoing, and a data taking campaign with protons will take place in May 2017. The DP design and the performances measured with using MIPs and protons beam will be reviewed.

Keywords: fragmentation, monitoring, particle therapy, tracking

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Authors: Donatella Giuliani

Abstract:

In this research, we propose an unsupervised grayscale image segmentation method based on a combination of the Firefly Algorithm and the Gaussian Mixture Model. Firstly, the Firefly Algorithm has been applied in a histogram-based research of cluster means. The Firefly Algorithm is a stochastic global optimization technique, centered on the flashing characteristics of fireflies. In this context it has been performed to determine the number of clusters and the related cluster means in a histogram-based segmentation approach. Successively these means are used in the initialization step for the parameter estimation of a Gaussian Mixture Model. The parametric probability density function of a Gaussian Mixture Model is represented as a weighted sum of Gaussian component densities, whose parameters are evaluated applying the iterative Expectation-Maximization technique. The coefficients of the linear super-position of Gaussians can be thought as prior probabilities of each component. Applying the Bayes rule, the posterior probabilities of the grayscale intensities have been evaluated, therefore their maxima are used to assign each pixel to the clusters, according to their gray-level values. The proposed approach appears fairly solid and reliable when applied even to complex grayscale images. The validation has been performed by using different standard measures, more precisely: the Root Mean Square Error (RMSE), the Structural Content (SC), the Normalized Correlation Coefficient (NK) and the Davies-Bouldin (DB) index. The achieved results have strongly confirmed the robustness of this gray scale segmentation method based on a metaheuristic algorithm. Another noteworthy advantage of this methodology is due to the use of maxima of responsibilities for the pixel assignment that implies a consistent reduction of the computational costs.

Keywords: clustering images, firefly algorithm, Gaussian mixture model, meta heuristic algorithm, image segmentation

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Authors: Spyridon Komaitis, Christos Koutsarnakis, Evangelos Drosos, Aristotelis Kalyvas

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This study opts to investigate the intrinsic architecture, morphology, and spatial relationship of the subcortical pathways implicated in the connectivity of the motor/premotor cortex and SMA/pre-SMA complex. Twenty normal, adult, formalin-fixed cerebral hemispheres were explored through the fiber micro-dissection technique. Lateral to medial and medial to lateral dissections focused on the area of interest were performed in a tandem manner and under the surgical microscope. We traced the subcortical architecture, spatial relationships, and axonal connectivity of four major pathways: a) the dorsal component of the SLF (SLF-I) was found to reside in the medial aspect of the hemisphere and seen to connect the precuneus with the SMA and pre-SMA complex, b) the frontal longitudinal system (FLS) was consistently encountered as the natural anterior continuation of the SLF-II and SLF-III and connected the premotor and prefrontal cortices c) the fronto-caudate tract (FCT), a fan-shaped tract, was documented to participate in connectivity of the prefrontal and premotor cortices to the head and body of the caudate nucleus and d) the cortico-tegmental tract(CTT) was invariably recorded to subserve the connectivity of the tegmental area with the fronto-parietal cortex. No hemispheric asymmetries were recorded for any of the implicated pathways. Sub-segmentation systems were also proposed for each of the aforementioned tracts. The structural connectivity and functional specialization of motor and premotor areas in the human brain remain vague to this day as most of the available evidence derives either from animal or tractographic studies. By using the fiber-microdissection technique as our main method of investigation, we provide sound structural evidence on the delicate anatomy of the related white matter pathways.

Keywords: neuroanatomy, premotor, motor, connectivity

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