Search results for: geophysical database referenced navigation

Authors: Jocelyn B. Barbosa, Angeli L. Magbaril, Mariel T. Sabanal, John Paul T. Galario, Mikka P. Baldovino

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The use of technology has become ubiquitous in different areas of business today. With the advent of digital imaging and database technology, business owners have been motivated to integrate technology to their business operation ranging from small, medium to large enterprises. Technology has been found to have brought many benefits that can make a business grow. Hog or swine raising, for example, is a very popular enterprise in the Philippines, whose challenges in production monitoring can be addressed through technology integration. Swine production monitoring can become a tedious task as the enterprise goes larger. Specifically, problems like delayed and inconsistent reports are most likely to happen if counting of swine per pen of which building is done manually. In this study, we present iCount, which aims to ensure efficient swine detection and counting that hastens the swine production monitoring task. We develop a system that automatically detects and counts swine based on Sobel filter and ellipse fitting model, given the still photos of the group of swine captured in a pen. We improve the Sobel filter detection result through 8-neigbhorhood rule implementation. Ellipse fitting technique is then employed for proper swine detection. Furthermore, the system can generate periodic production reports and can identify the specific consumables to be served to the swine according to schedules. Experiments reveal that our algorithm provides an efficient way for detecting swine, thereby providing a significant amount of accuracy in production monitoring.

Keywords: automatic swine counting, swine detection, swine production monitoring, ellipse fitting model, sobel filter

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Authors: Yung-Feng Yen, I-an Jen, Yi-Ming Arthur Chen

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The molecular mimicry between human immunodeficiency virus (HIV) protein and red blood cell (RBC) antigens could induce the production of anti-RBC autoantibodies. However, the association between HIV infection and subsequent development of autoimmune hemolytic anemia (AIHA) remains unclear. This nationwide population-based cohort study aimed to determine the association between incident AIHA and HIV in Taiwan. From 2000–2012, we identified adult people living with HIV/AIDS (PLWHA) from the Taiwan centers for disease control HIV Surveillance System. HIV-infected individuals were defined by positive HIV-1 western blot. Age- and sex-matched controls without HIV infection were selected from the Taiwan National Health Insurance Research Database for comparison. All patients were followed until Dec. 31, 2012, and observed for occurrence of AIHA. Of 171,468 subjects (19,052 PLWHA, 152,416 controls), 30 (0.02%) had incident AIHA during a mean follow-up of 5.45 years, including 23 (0.12%) PLWHA and 7 (0.01%) controls. After adjusting for potential confounders, HIV infection was found to be an independent risk factor of incident AIHA (adjusted hazard ratio [AHR], 20.9; 95% confidence interval [CI], 8.34-52.3). Moreover, PLWHA receiving HAART were more likely to develop AIHA than those not receiving HAART (AHR, 10.8; 95% CI, 2.90-40.1). Additionally, the risk of AIHA was significantly increased in those taking efavirenz (AHR, 3.15; 95% CI, 1.18-8.43) or atazanavir (AHR, 6.58; 95% CI, 1.88-22.9) component of the HAART. In conclusion, HIV infection is an independent risk factor for incident AIHA. Clinicians need to be aware of the higher risk of AIHA in PLWHA.

Keywords: autoimmune disease , hemolytic anemia, HIV, highly active antiretroviral treatment

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Authors: Jiashu Shen

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Objectives: Spirometry is a basic reference for health evaluation which is widely used in clinical. Previous reference of spirometry is not applicable because of drastic changes of social and natural circumstance in China. A new reference values for the spirometry of the Chinese population is extremely needed. Method: Spirometric reference value was established using the statistical modeling method Generalized Additive Models for Location, Scale and Shape for forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), FEV1/FVC, and maximal mid-expiratory flow (MMEF). Results: Data from 236,606 healthy non-smokers aged 4–90 years was collected from the MJ Health Check database. Spirometry equations for FEV1, FVC, MMEF, and FEV1/FVC were established, including the predicted values and lower limits of normal (LLNs) by sex. The predictive equations that were developed for the spirometric results elaborated the relationship between spirometry and age, and they eliminated the effects of height as a variable. Most previous predictive equations for Chinese spirometry were significantly overestimated (to be exact, with mean differences of 22.21% in FEV1 and 31.39% in FVC for males, along with differences of 26.93% in FEV1 and 35.76% in FVC for females) or underestimated (with mean differences of -5.81% in MMEF and -14.56% in FEV1/FVC for males, along with a difference of -14.54% in FEV1/FVC for females) the results of lung function measurements as found in this study. Through cross-validation, our equations were established as having good fit, and the means of the measured value and the estimated value were compared, with good results. Conclusions: Our study updates the spirometric reference equations for Chinese people of all ages and provides comprehensive values for both physical examination and clinical diagnosis.

Keywords: Chinese, GAMLSS model, reference values, spirometry

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Authors: Yazan Al-Kofahi, Jamal Alqawasmi.

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In this study, a comprehensive literature review (SLR) was conducted, with the main goal of assessing the existing literature about how artificial intelligence (AI), machine learning (ML), deep learning (DL) models are used in sustainable architecture applications and issues including thermal comfort satisfaction, energy efficiency, cost prediction and many others issues. For this reason, the search strategy was initiated by using different databases, including Scopus, Springer and Google Scholar. The inclusion criteria were used by two research strings related to DL, ML and sustainable architecture. Moreover, the timeframe for the inclusion of the papers was open, even though most of the papers were conducted in the previous four years. As a paper filtration strategy, conferences and books were excluded from database search results. Using these inclusion and exclusion criteria, the search was conducted, and a sample of 59 papers was selected as the final included papers in the analysis. The data extraction phase was basically to extract the needed data from these papers, which were analyzed and correlated. The results of this SLR showed that there are many applications of ML and DL in Sustainable buildings, and that this topic is currently trendy. It was found that most of the papers focused their discussions on addressing Environmental Sustainability issues and factors using machine learning predictive models, with a particular emphasis on the use of Decision Tree algorithms. Moreover, it was found that the Random Forest repressor demonstrates strong performance across all feature selection groups in terms of cost prediction of the building as a machine-learning predictive model.

Keywords: machine learning, deep learning, artificial intelligence, sustainable building

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Authors: Ahmed Boufedah Badissi, Ahmed Beroual, Farid Boursas

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This research aims to elucidate the role of coarse aggregate in influencing the fresh properties of normal-strength concrete. Specifically, it is aimed to identify the optimal gradation of coarse aggregate to enhance workability. While existing literature discusses the impact of aggregate granularity on concrete workability, more numerical data or models need to quantify the relationship between workability, granularity, and coarse aggregate shape. The main objective is to create a model that describes how coarse aggregate morphology contributes to fresh concrete properties. To investigate the effect of coarse aggregate gradation on Normal Strength Concrete (NSC) workability, various combinations of coarse aggregates (4/22.4 mm) were produced in the laboratory, utilizing three elementary classes: finer coarse aggregate 4/8 mm (Fca), medium coarse aggregate 8/16 mm (Mca), and coarser coarse aggregate 16/22.4 mm (Cca). We introduced a factor, FCR (Finer to Coarser coarse aggregate Ratio), as a numerical parameter to provide a quantitative evaluation and more detailed results analysis. Quantitative characterization parameters for coarse aggregate morphology were established, exploring the influence of particle size distribution, specific surface, and aggregate shape on workability. The research findings are significant for establishing correlations between coarse aggregate morphology and concrete properties. FCR emerges as a valuable tool for predicting the impact of aggregate gradation variations on concrete. The results of this study create a valuable database for construction professionals and concrete producers, affirming that the fresh properties of NSC are intricately linked to coarse aggregate morphology, particularly gradation.

Keywords: morphology, coarse aggregate, workability, fresh properties, gradation

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Authors: Linung Kresno Adikusumo, Ivan Ramos Sampe Immanuel, Liston Sitanggang

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An excellent, well work program in the oil and gas industry can have numerous positive business impacts, contributing to operational efficiency, increased production, enhanced safety, and improved financial performance. In summary, an excellent, well work program not only ensures the immediate success of specific projects but also has a broader positive impact on the overall business performance and reputation of the oil and gas company. It positions the company for long-term success in a competitive and dynamic industry. Nevertheless, a number of challenges were encountered when developing a good work program, such as the poor quality and lack of integration of well documentation, the incompleteness of the well history, and the low accessibility of well documentation. As a result, the well work program was delivered less accurately, plus well damage was managed slowly. Our solution implementing digital technology by developing a web-based database and application not only solves those issues but also provides an easy-to-access report and user-friendly display for management as well as engineers to analyze the report’s content. This application aims to revolutionize the documentation of well history in the field of oil and gas exploration and production. The current lack of a streamlined and comprehensive system for capturing, organizing, and accessing well-related data presents challenges in maintaining accurate and up-to-date records. Our innovative solution introduces a user-friendly and efficient platform designed to capture well history documentation seamlessly.

Keywords: digital, drilling, well work, application

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Authors: Qasim HamaKhurshid HamaMurad, Normal Mat Jusoh, Uznir Ujang

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The concept of the city with an infrastructure of (information and communication) Technology embraces several definitions depending on the meanings of the word "smart" are (intelligent city, smart city, knowledge city, ubiquitous city, sustainable city, digital city). Many definitions of the city exist, but this chapter explores which one has been universally acknowledged. From literature analysis, it emerges that Smart City is the most used terminologies in literature through the digital database to indicate the smartness of a city. This paper share exploration the research from main seven website digital databases and journal about Smart City from "January 2015 to the February of 2020" to (a) Time research, to examine the causes of the Smart City phenomenon and other concept literature in the last five years (b) Review of words, to see how and where the smart city specification and relation different definition And(c) Geographical research to consider where Smart Cities' greatest concentrations are in the world and are Malaysia has interacting with the smart city, and (d) how many papers published from all Malaysia from 2015 to 2020 about smart citie. Three steps are followed to accomplish the goal. (1)The analysis covered publications Build a systematic literature review search strategy to gather a representative sub-set of papers on Smart City and other definitions utilizing (GoogleScholar, Elsevier, Scopus, ScienceDirect, IEEEXplore, WebofScience, Springer) January2015-February2020. (2)A bibliometric map was formed based on the bibliometric evaluation using the mapping technique VOSviewer to visualize differences. (3)VOSviewer application program was used to build initial clusters. The Map of Bibliometric Visualizes the analytical findings which targeted the word harmony.

Keywords: bibliometric research, smart city, ICT, VOSviewer, urban modernization

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Authors: Aisultan Shoiynbek, Darkhan Kuanyshbay, Paulo Menezes, Akbayan Bekarystankyzy, Assylbek Mukhametzhanov, Temirlan Shoiynbek

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Speech emotion recognition (SER) has received increasing research interest in recent years. It is a common practice to utilize emotional speech collected under controlled conditions recorded by actors imitating and artificially producing emotions in front of a microphone. There are four issues related to that approach: emotions are not natural, meaning that machines are learning to recognize fake emotions; emotions are very limited in quantity and poor in variety of speaking; there is some language dependency in SER; consequently, each time researchers want to start work with SER, they need to find a good emotional database in their language. This paper proposes an approach to create an automatic tool for speech emotion extraction based on facial emotion recognition and describes the sequence of actions involved in the proposed approach. One of the first objectives in the sequence of actions is the speech detection issue. The paper provides a detailed description of the speech detection model based on a fully connected deep neural network for Kazakh and Russian. Despite the high results in speech detection for Kazakh and Russian, the described process is suitable for any language. To investigate the working capacity of the developed model, an analysis of speech detection and extraction from real tasks has been performed.

Keywords: deep neural networks, speech detection, speech emotion recognition, Mel-frequency cepstrum coefficients, collecting speech emotion corpus, collecting speech emotion dataset, Kazakh speech dataset

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Authors: Timothy Francis Grant

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There are conflicting purposes at play with the design of sustainable packaging which include material reduction, recycling compatibility, use of secondary content and performance of the package in protecting and delivering the product. Life Cycle Assessment (LCA) is able to evaluate these different strategies against environmental metrics such as climate change, land and water use and marine litter pollution. However, LCA has traditionally been too time consuming and expensive to be used effectively in packaging design process. To make LCA practical for packaging technologist and designers a simplified tool is needed to make LCA possible for non-environmental specialists. The Packaging Quick Evaluation Tool (PIQET) is a web-based solution for undertaking LCA of new and existing packaging designs considering the global supply chain and impacts from cradle to grave. PIQET is based on a pre-calculated LCA database covering the materials and processes involved in the packaging lifecycle from cradle to grave. This includes both virgin materials and recycled content, conversion of materials into packaging, and the transportation of packaging to the product filling. In addition, PIQET assesses the impacts once the package is filled looking at storage, transport and product loss through the supply chain. When applied to consumer packaging light weight packages which are note recyclable have lower impacts than more recyclable packages which have a higher mass. Its also apparent that for many products the impacts of product failure and product loss are more important environmentally compared to packaging material efficiency.

Keywords: Climate change, Life Cycle Assessment, Marine litter, Packaging sustainability

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Authors: Romeo A. Botes, Imelda Smit

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The demands of an ever changing and complex higher education environment, along with the profile of modern learners challenge current approaches to assessment and feedback. More learners enter the education system every year. The younger generation expects immediate feedback. At the same time, feedback should be meaningful. The assessment of practical activities in programming poses a particular problem, since both lecturers and learners in the information and computer science discipline acknowledge that paper-based assessment for programming subjects lacks meaningful real-life testing. At the same time, feedback lacks promptness, consistency, comprehensiveness and individualisation. Most of these aspects may be addressed by modern, technology-assisted assessment. The focus of this paper is the continuous development of an artefact that is used to assist the lecturer in the assessment and feedback of practical programming activities in a senior database programming class. The artefact was developed using three Design Science Research cycles. The first implementation allowed one programming activity submission per assessment intervention. This pilot provided valuable insight into the obstacles regarding the implementation of this type of assessment tool. A second implementation improved the initial version to allow multiple programming activity submissions per assessment. The focus of this version is on providing scaffold feedback to the learner – allowing improvement with each subsequent submission. It also has a built-in capability to provide the lecturer with information regarding the key problem areas of each assessment intervention.

Keywords: programming, computer-aided assessment, technology-assisted assessment, programming assessment software, design science research, mixed-method

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Authors: T. Botelho de Sousa, F. Raphael Cabral Furtado, O. Eduardo da Silva Ferri, A. Batista, W. Augusto Varella, C. Eduardo Pinto, J. Mimar Santa Cruz Yabarrena, S. Gibran Ruwer, F. Müller Guerrini, L. Adalberto Philippsen Júnior

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Lean Supply Chain Management (LSCM) is an emerging research field in Operations Management (OM). As a strategic model that focuses on reduced cost and waste with fulfilling the needs of customers, LSCM attracts great interest among researchers and practitioners. The purpose of this paper is to present an overview of Lean Supply Chains literature, based on bibliometric analysis through 57 papers published in indexed journals by SCOPUS and/or Web of Science databases. The results indicate that the last three years (2015, 2016, and 2017) were the most productive on LSCM discussion, especially in Supply Chain Management and International Journal of Lean Six Sigma journals. India, USA, and UK are the most productive countries; nevertheless, cross-country studies by collaboration among researchers were detected, by social network analysis, as a research practice, appearing to play a more important role on LSCM studies. Despite existing limitation, such as limited indexed journal database, bibliometric analysis helps to enlighten ongoing efforts on LSCM researches, including most used technical procedures and collaboration network, showing important research gaps, especially, for development countries researchers.

Keywords: Lean Supply Chains, Bibliometric Study, SCOPUS, Web of Science

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Authors: Seden Demirtaş, Feyza Tantekin Erden

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The importance of research in early childhood education is growing all around the world. This study aims to investigate research trends in graduate theses written in Turkey in the area of early childhood education. Descriptive, contextual and methodological aspects of graduate theses were analyzed to investigate the trends. A sample of the study consisted of 1000 graduate theses (n= 1000) including both MS theses and Ph.D. dissertations. Theses and dissertations were obtained from the thesis database of Council of Higher Education (CoHE). An investigation form was developed by the researcher to analyze graduate theses. The investigation forms validated by expert opinion from early childhood education department. To enhance the reliability of the investigation form, inter-coder agreement was measured by Cohen’s Kappa value (.86). Data were gathered via using the investigation form, and content analysis method was used to analyze the data. Results of the analysis were presented by descriptive statistics and frequency tables. Analysis of the study is on-going and preliminary results of the study show that master theses related to early childhood education have started to be written in 1986, and the number of the theses has increased gradually. In most of the studies, sample group consisted of children especially in between 5-6 age group. Child development, activities (applied in daily curriculum of preschools) and teaching methods are the mostly examined concepts in graduate theses. Qualitative and quantitative research methods were referred equally by researchers in these theses.

Keywords: content analysis, early childhood education, graduate thesis, research trends

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Authors: Jacob J. Shila, Xiaoyu O. Wu

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As the applications of unmanned aerial vehicles (UAV) continue to increase across the world, it is critical to understand the factors that contribute to incidents and accidents associated with these systems. Given the variety of daily applications that could utilize the operations of the UAV (e.g., medical, security operations, construction activities, landscape activities), the main discussion has been how to safely incorporate the UAV into the national airspace system. The types of UAV incidents being reported range from near sightings by other pilots to actual collisions with aircraft or UAV. These incidents have the potential to impact the rest of aviation operations in a variety of ways, including human lives, liability costs, and delay costs. One of the largest causes of these incidents cited is the human factor; other causes cited include maintenance, aircraft, and others. This work investigates the key human factors associated with UAV incidents. To that end, the data related to UAV incidents that have occurred in the United States is both reviewed and analyzed to identify key human factors related to UAV incidents. The data utilized in this work is gathered from the Federal Aviation Administration (FAA) drone database. This study adopts the human factor analysis and classification system (HFACS) to identify key human factors that have contributed to some of the UAV failures to date. The uniqueness of this work is the incorporation of UAV incident data from a variety of applications and not just military data. In addition, identifying the specific human factors is crucial towards developing safety operational models and human factor guidelines for the UAV. The findings of these common human factors are also compared to similar studies in other countries to determine whether these factors are common internationally.

Keywords: human factors, incidents and accidents, safety, UAS, UAV

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Authors: Mohd Iz'aan Paiz Bin Zamri, Anis Salwa Mohd Khairuddin, Norrima Mokhtar, Rubiyah Yusof

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Effective statistical feature extraction and classification are important in image-based automatic inspection and analysis. An automatic wood species recognition system is designed to perform wood inspection at custom checkpoints to avoid mislabeling of timber which will results to loss of income to the timber industry. The system focuses on analyzing the statistical pores properties of the wood images. This paper proposed a fuzzy-based feature extractor which mimics the experts’ knowledge on wood texture to extract the properties of pores distribution from the wood surface texture. The proposed feature extractor consists of two steps namely pores extraction and fuzzy pores management. The total number of statistical features extracted from each wood image is 38 features. Then, a backpropagation neural network is used to classify the wood species based on the statistical features. A comprehensive set of experiments on a database composed of 5200 macroscopic images from 52 tropical wood species was used to evaluate the performance of the proposed feature extractor. The advantage of the proposed feature extraction technique is that it mimics the experts’ interpretation on wood texture which allows human involvement when analyzing the wood texture. Experimental results show the efficiency of the proposed method.

Keywords: classification, feature extraction, fuzzy, inspection system, image analysis, macroscopic images

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Authors: Haneen Alrawashdeh, Naciye Kunt

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Intercultural communicative competence or (ICC), is an extension of communicative competence that takes into account the intercultural aspect of learning a foreign language. Accordingly, this study aimed at investigating the intercultural interaction impact on English as a foreign language learners' academic achievement of language as a scholastic subject and their motivation towards learning it. To achieve the aim of the study, a qualitative research approach was implemented by means of semi-structured interviews. Interview sessions were conducted with eight teachers of English as well as ten English language learners who work in the tourism industry in a variety of career paths, such as selling antiques and traditional costumes. An analysis of learners' grades of English subjects from 2014 to 2019 academic years was performed by using the Open Education Management Information System Database in Jordan to support the findings of the study. The results illustrated that due to the fact that they work in the tourism sector, students gain skills and knowledge that assist them in better academic achievement in the subject of English by practicing intercultural communication with different nationalities on a daily basis; intercultural communication enhances students speaking skills, lexicon, and fluency; however, despite that their grades showed increasing, from teachers perspectives, intercultural communicative competence reduces their linguistic accuracy and ability to perform English academic writing in academic contexts such as exams.

Keywords: intercultural communicative competence, Jordan, language learning motivation, language academic achievement

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Authors: Zoe Goldberger, Priscilla S. Briquez, Jeffrey A. Hubbell

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Tumor cells have mutations resulting from genetic instability that the immune system can actively recognize. Immune checkpoint immunotherapy (ICI) is commonly used in the clinic to re-activate immune reactions against mutated proteins, called neoantigens, resulting in tumor remission in cancer patients. However, only around 20% of patients show durable response to ICI. While tumor mutational burden (TMB) has been approved by the Food and Drug Administration (FDA) as a criterion for ICI therapy, the relevance of the subcellular localizations of the mutated proteins within the tumor cell has not been investigated. Here, we hypothesized that localization of mutations impacts the effect of immune responsiveness to ICI. We analyzed publicly available tumor mutation sequencing data of ICI treated patients from 3 independent datasets. We extracted the subcellular localization from the UniProtKB/Swiss-Prot database and quantified the proportion of membrane, cytoplasmic, nuclear, or secreted mutations per patient. We analyzed this information in relation to response to ICI treatment and overall survival of patients showing with 1722 ICI-treated patients that high mutational burden localized at the membrane (mTMB), correlate with ICI responsiveness, and improved overall survival in multiple cancer types. We anticipate that our results will ameliorate predictability of cancer patient response to ICI with potential implications in clinical guidelines to tailor ICI treatment. This would not only increase patient survival for those receiving ICI, but also patients’ quality of life by reducing the number of patients enduring non-effective ICI treatments.

Keywords: cancer, immunotherapy, membrane neoantigens, efficacy prediction, biomarkers

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Authors: Anna Vanderbruggen, Kai Bachmann, Martin Rudolph, Rodrigo Serna

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Recycling of lithium-ion batteries has attracted a lot of attention in recent years and focuses primarily on valuable metals such as cobalt, nickel, and lithium. Despite the growth in graphite consumption and the fact that it is classified as a critical raw material in the European Union, USA, and Australia, there is little work focusing on graphite recycling. Thus, graphite is usually considered waste in recycling treatments, where graphite particles are concentrated in the “black mass”, a fine fraction below 1mm, which also contains the foils and the active cathode particles such as LiCoO2 or LiNiMnCoO2. To characterize the material, various analytical methods are applied, including X-Ray Fluorescence (XRF), X-Ray Diffraction (XRD), Atomic Absorption Spectrometry (AAS), and SEM-based automated mineralogy. The latter consists of the combination of a scanning electron microscopy (SEM) image analysis and energy-dispersive X-ray spectroscopy (EDS). It is a powerful and well-known method for primary material characterization; however, it has not yet been applied to secondary material such as black mass, which is a challenging material to analyze due to fine alloy particles and to the lack of an existing dedicated database. The aim of this research is to characterize the black mass depending on the metals recycling process in order to understand the liberation mechanisms of the active particles from the foils and their effect on the graphite particle surfaces and to understand their impact on the subsequent graphite flotation. Three industrial processes were taken into account: purely mechanical, pyrolysis-mechanical, and mechanical-hydrometallurgy. In summary, this article explores various and common challenges for graphite and secondary material characterization.

Keywords: automated mineralogy, characterization, graphite, lithium ion battery, recycling

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Authors: Adel M. Zakri, Mohammed A. Al-Saleh, Judith. K. Brown, Ali M. Idris

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Betasatellites are small circular single stranded DNA molecules found associated with begomoviruses on field symptomatic plants. Their genome size is about half that of the helper begomovirus, ranging between 1.3 and 1.4 kb. The helper begomoviruses are usually members of the family Geminiviridae. Okra leaves showing vein thickening were collected from okra plants growing in Jazan, Saudi Arabia. Total DNA was extracted from leaves and used as a template to amplify circular DNA using rolling circle amplification (RCA) technology. Products were digested with PstI to linearize the helper viral genome(s), and associated DNA satellite(s), yielding a 2.8kbp and 1.4kbp fragment, respectively. The linearized fragments were cloned into the pGEM-5Zf (+) vector and subjected to DNA sequencing. The 2.8 kb fragment was identified as Cotton leaf curl Gezira virus genome, at 2780bp, an isolate closely related to strains reported previously from Saudi Arabia. A clone obtained from the 1.4 kb fragments he 1.4kb was blasted to GeneBank database found to be a betasatellite. The genome of betasatellite was 1357-bp in size. It was found to be a recombinant containing one fragment (877-bp) that shared 91% nt identity with Cotton leaf curl Gezira betasatellite [KM279620], and a smaller fragment [133--bp) that shared 86% nt identity with Tomato leaf curl Sudan virus [JX483708]. This satellite is thus a recombinant between a malvaceous-infecting satellite and a solanaceous-infecting begomovirus.

Keywords: begomovirus, betasatellites, cotton leaf curl Gezira virus, okra plants

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Authors: Khalid Hussein, Waleed Abdalati, Pakorn Petchprayoon, Khaula Alkaabi

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In this study, we integrated ASTER thermal data with an area-based spatial insolation model to identify and delineate geothermally active areas in Yellowstone National Park (YNP). Two pairs of L1B ASTER day- and nighttime scenes were used to calculate land surface temperature. We employed the Emissivity Normalization Algorithm which separates temperature from emissivity to calculate surface temperature. We calculated the incoming solar radiation for the area covered by each of the four ASTER scenes using an insolation model and used this information to compute temperature due to solar radiation. We then identified the statistical thermal anomalies using land surface temperature and the residuals calculated from modeled temperatures and ASTER-derived surface temperatures. Areas that had temperatures or temperature residuals greater than 2σ and between 1σ and 2σ were considered ASTER-modeled thermal anomalies. The areas identified as thermal anomalies were in strong agreement with the thermal areas obtained from the YNP GIS database. Also the YNP hot springs and geysers were located within areas identified as anomalous thermal areas. The consistency between our results and known geothermally active areas indicate that thermal remote sensing data, integrated with a spatial-based insolation model, provides an effective means for identifying and locating areas of geothermal activities over large areas and rough terrain.

Keywords: thermal remote sensing, insolation model, land surface temperature, geothermal anomalies

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Authors: Sana Ilyas

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Parry-Romberg syndrome is a rare condition clinically defined by slowly progressive atrophy of the skin and soft tissues. This usually effects one side of the face, although a few cases have been documented of bilateral presentation. It is more prevalent in females and usually affects the left side of the face. The syndrome can also be accompanied by neurological abnormalities. It usually occurs in the first two decades of life with a variable rate of progression. The aetiology is unknown, and the disease eventually stabilises. The treatment options usually involve surgical management. The least invasive of these options is the management of facial asymmetry, associated with Parry Romberg syndrome, through the use of tissue fillers. This paper will review the existing literature on the management of Parry Romberg syndrome with tissue filler. Aim: The aim of the study is to explore the current published literature for the management of Parry Romberg syndrome with fillers. It is to assess the development that has been made in this method of management, its benefits and limitations, and its effectiveness for the management of Parry Romberg syndrome. Methodology: There was a thorough assessment of the current literature published on this topic. PubMed database was used for search of the published literature on this method of the management. Papers were analysed and compared with one another to assess the success and limitation of the management of Parry Romberg with dermal fillers Results and Conclusion: Case reports of the use of tissue fillers discuss the varying degrees of success with the treatment. However, this procedure has it’s limitation, which are discussed in the paper in detail. However, it is still the least invasive of all the surgical options for the management of Parry Romberg Syndrome, and therefore, it is important to explore this option with patients, as they may be more comfortable with pursuingtreatment that is less invasive and can still improve their facial asymmetry

Keywords: dermal fillers, facial asymmetry, parry romberg syndrome, tissue fillers

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Authors: Vun Yee Thien, Kenneth Francis Rodrigues, Clemente Michael Vui Ling Wong, Wilson Thau Lym Yong

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Transcriptomes associated with the process of photosynthesis have offered insights into the mechanism of gene regulation in terrestrial plants; however, limited information is available as far as macroalgae are concerned. This investigation aims to decipher the underlying mechanisms associated with photosynthesis in the red alga, Kappaphycus alvarezii, by performing a differential expression analysis on a de novo assembled transcriptomes. Comparative analysis of gene expression was designed to examine the alteration of light qualities and its effect on physiological mechanisms in the red alga. High-throughput paired-end RNA-sequencing was applied to profile the transcriptome of K. alvarezii irradiated with different wavelengths of light (blue 492-455 nm, green 577-492 nm and red 780-622 nm) as compared to the full light spectrum, resulted in more than 60 million reads individually and assembled using Trinity and SOAPdenovo-Trans. The transcripts were annotated in the NCBI non-redundant (nr) protein, SwissProt, KEGG and COG databases with a cutoff E-value of 1e-5 and nearly 30% of transcripts were assigned to functional annotation by Blast searches. Differential expression analysis was performed using edgeR. The DEGs were designated to six categories: BL (blue light) regulated, GL (green light) regulated, RL (red light) regulated, BL or GL regulated, BL or RL regulated, GL or RL regulated, and either BL, GL or RL regulated. These DEGs were mapped to terms in KEGG database and compared with the whole transcriptome background to search for genes that regulated by light quality. The outcomes of this study will enhance our understanding of molecular mechanisms underlying light-induced responses in red algae.

Keywords: de novo transcriptome sequencing, differential gene expression, Kappaphycus alvareziired, red alga

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Authors: Akintayo Opawole, Godwin O. Jagboro

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Research efforts on infrastructure development in Nigeria had not provided adequate assessment of issues essential for policy response by the government to address infrastructure deficiency. One major gap existing in previous studies is the assessment of challenges facing the budgetary financing model. Based on a case study of Osun State in Southwestern Nigeria, factors affecting budgetary financing of public infrastructure were identified from literature and brainstorming. Respondents were: 6 architects, 4 quantity surveyors, 6 town planners, 5 estate surveyors, 4 builders, 21 engineers and 26 economists/accountants ranging from principal to director who have been involved in policy making process with respect to infrastructure development in the public service of Osun state. The identified variables were subjected to factor analysis. The Kaiser-Meyer-Olkin measure of sampling adequacy tests carried out (KMO, 0.785) showed that the data collected were adequate for the analysis and the Bartlett’s test of sphericity (0.000) showed the data upon which the analysis was carried out was reliable. Results showed that factors such as poor collaboration between the state and local government establishments, absence of credible database system and inadequate funding of maintenance were the most significant to infrastructure development in the State. Policy responses to address challenges of infrastructure development in the state were identified to focus on creation of legal framework for liberation policy, enforcement of ‘due process’ in the procurement and establishment of monitoring system for project delivery.

Keywords: development, infrastructure, financing, procurement

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Authors: Balogun R. Ayodeji, Adefisan E. Adesanya, Adeyewa Z. Debo, E. C. Okogbue

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Deep convective systems during active periods of the West African monsoon season have not been properly investigated over better temporal and spatial resolution in West Africa. Deep convective systems are investigated over seven climatic zones of the West African sub-region, which are; west-coast rainforest, dry rainforest, Nigeria-Cameroon rainforest, Nigeria savannah, Central African and South Sudan (CASS) Savannah, Sudano-Sahel, and Sahel, using data from Tropical Rainfall Measurement Mission (TRMM) Precipitation Feature (PF) database. The vertical structure of the convective systems indicated by the presence of at least one 40 dBZ and reaching (attaining) at least 1km in the atmosphere showed strong core (highest frequency (%)) of reflectivity values around 2 km which is below the freezing level (4-5km) for all the zones. Echoes are detected above the 15km altitude much more frequently in the rainforest and Savannah zones than the Sudano and Sahel zones during active periods in March-May (MAM), whereas during active periods in June-September (JJAS) the savannahs, Sudano and Sahel zones convections tend to reach higher altitude more frequently than the rainforest zones. The percentage frequencies of deep convection indicated that the occurrences of the systems are within the range of 2.3-2.8% during both March-May (MAM) and June-September (JJAS) active periods in the rainforest and savannah zones. On the contrary, the percentage frequencies were found to be less than 2% in the Sudano and Sahel zones, except during the active-JJAS period in the Sudano zone.

Keywords: active periods, convective system, frequency, reflectivity

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Authors: Qasim Munye, Juned Islam, Haseeb Qureshi, Syed Jung

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Lung nodules are commonly identified in computed tomography (CT) scans by experienced radiologists at a relatively late stage. Early diagnosis can greatly increase survival. We propose using a pix2pix conditional generative adversarial network to generate realistic images simulating early-stage lung nodule growth. We have applied deep images prior to 2341 slices from 895 computed tomography (CT) scans from the Lung Image Database Consortium (LIDC) dataset to generate pseudo-healthy medical images. From these images, 819 were chosen to train a pix2pix network. We observed that for most of the images, the pix2pix network was able to generate images where the nodule increased in size and intensity across epochs. To evaluate the images, 400 generated images were chosen at random and shown to a medical student beside their corresponding original image. Of these 400 generated images, 384 were defined as satisfactory - meaning they resembled a nodule and were visually similar to the corresponding image. We believe that this generated dataset could be used as training data for neural networks to detect lung nodules at an early stage or to improve the accuracy of such networks. This is particularly significant as datasets containing the growth of early-stage nodules are scarce. This project shows that the combination of deep image prior and generative models could potentially open the door to creating larger datasets than currently possible and has the potential to increase the accuracy of medical classification tasks.

Keywords: medical technology, artificial intelligence, radiology, lung cancer

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Authors: Ibrahim Ahmed, Richard Amoateng, Akhil Jain, Mohamed Ahmed

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Alcoholic cardiomyopathy (ACM) is a type of acquired cardiomyopathy caused by chronic alcohol consumption. Frequently ACM is associated with arrhythmias such as atrial flutter. Our aim was to characterize the patient demographics and investigate the effect of atrial flutter (AF) on ACM. This was a retrospective cohort study using the Nationwide Inpatient Sample database to identify admissions in adults with principal and secondary diagnoses of alcoholic cardiomyopathy and atrial flutter from 2019. Multivariate linear and logistic regression models were adjusted for age, gender, race, household income, insurance status, Elixhauser comorbidity score, hospital location, bed size, and teaching status. The primary outcome was all-cause mortality, and secondary outcomes were the length of stay (LOS) and total charge in USD. There was a total of 21,855 admissions with alcoholic cardiomyopathy, of which 1,635 had atrial flutter (AF-ACM). Compared to Non-AF-ACM cohort, AF-ACM cohort had fewer females (4.89% vs 14.54%, p<0.001), were older (58.66 vs 56.13 years, p<0.001), fewer Native Americans (0.61% vs2.67%, p<0.01), had fewer smaller (19.27% vs 22.45%, p<0.01) & medium-sized hospitals (23.24% vs28.98%, p<0.01), but more large-sized hospitals (57.49% vs 48.57%, p<0.01), more Medicare (40.37% vs 34.08%, p<0.05) and fewer Medicaid insured (23.55% vs 33.70%, p=<0.001), fewer hypertension (10.7% vs 15.01%, p<0.05), and more obesity (24.77% vs 16.35%, p<0.001). Compared to Non-AF-ACM cohort, there was no difference in AF-ACM cohort mortality rate (6.13% vs 4.20%, p=0.0998), unadjusted mortality OR 1.49 (95% CI 0.92-2.40, p=0.102), adjusted mortality OR 1.36 (95% CI 0.83-2.24, p=0.221), but there was a difference in LOS 1.23 days (95% CI 0.34-2.13, p<0.01), total charge $28,860.30 (95% CI 11,883.96-45,836.60, p<0.01). In patients admitted with ACM, the presence of AF was not associated with a higher all-cause mortality rate or odds of all-cause mortality; however, it was associated with 1.23 days increase in LOS and a $28,860.30 increase in total hospitalization charge. Native Americans, older age and obesity were risk factors for the presence of AF in ACM.

Keywords: alcoholic cardiomyopathy, atrial flutter, cardiomyopathy, arrhythmia

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Authors: Yuan Yan

Abstract:

Interlayer interactions or hybridization in van der Waals (vdW) heterostructures of two-dimensional (2D) materials significantly influence their physical characteristics, including layer-dependent electronic and vibrational structures, magic-angle superconductivity, interlayer antiferromagnetism, and interlayer excitons. These interactions are sensitive to a set of interdependent and externally tunable parameters. To fully exploit the potential of these materials, it is crucial to understand the physical origins of interlayer interaction and hybridization. Traditional theories often attribute these interactions to the sharing of electrons via p orbital lone pairs or π electrons, based on the octet rule, which posits that p electrons are the primary occupants of the outermost atomic shells, except in hydrogen. However, our study challenges this prevailing belief. Through geometry-based analysis, we conducted a high-throughput screening of the Materials Project database and identified 1,623 layered materials. By examining the atomic structure and bonding characteristics of surface atoms, we demonstrate that s-orbital lone pairs can also drive interlayer interactions in two-dimensional materials. Using density functional theory, we further analyzed charge distribution and electronic localization. The crystal field and inert pair effect induce a Stark-like phenomenon, leading to energy level splitting and the formation of directional electron clouds. This allows these electrons to directly participate in the hybridization of interlayer wavefunctions without forming chemical bonds. it findings expand the understanding of interlayer interactions, revealing new mechanisms that govern these properties and providing a theoretical foundation for manipulating interlayer phenomena in 2D materials.

Keywords: interlayer interaction, nanomaterials, 2D materials, van der waals, heterostructures

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Authors: Xizhen Zhou, Yanjie Ji

Abstract:

In advancing the management of integrated electric vehicle (EV) parking-charging behaviors, this study uses Changshu City in Suzhou as a case study to establish a data association mechanism for parking-charging platforms and to develop a database for EV parking-charging behaviors. Key indicators, such as charging start time, initial state of charge, final state of charge, and parking-charging time difference, are considered. Utilizing the K-S test method, the paper examines the heterogeneity of parking-charging behavior preferences among pure EV and non-pure EV users. The K-means clustering method is employed to analyze the characteristics of parking-charging behaviors for both user groups, thereby enhancing the overall understanding of these behaviors. The findings of this study reveal that using a classification model, the parking-charging behaviors of pure EVs can be classified into five distinct groups, while those of non-pure EVs can be separated into four groups. Among them, both types of EV users exhibit groups with low range anxiety for complete charging with special journeys, complete charging at destination, and partial charging. Additionally, both types have a group with high range anxiety, characterized by pure EV users displaying a preference for complete charging with specific journeys, while non-pure EV users exhibit a preference for complete charging. Notably, pure EV users also display a significant group engaging in nocturnal complete charging. The findings of this study can provide technical support for the scientific and rational layout and management of integrated parking and charging facilities for EVs.

Keywords: traffic engineering, potential preferences, cluster analysis, EV, parking-charging behavior

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Authors: Micheale Yifter Weldemichael

Abstract:

Sesame (Sesamum indicum L.) is among the most important oilseed crops for its high edible oil quality and quantity. Sesame is grown for food, medicinal, pharmaceutical, and industrial uses. Sesame is also cultivated as a main cash crop in Asia and Africa by smallholder farmers. Despite the global exponential increase in sesame cultivation area, its production and productivity remain low, mainly due to biotic and abiotic constraints. Notwithstanding the efforts to solve these problems, a low level of genetic variation and inadequate genomic resources hinder the progress of sesame improvement. The objective of this paper is, therefore, to review recent advances in the area of molecular breeding and transformation to overcome major production constraints and could result in enhanced and sustained sesame production. This paper reviews various researches conducted to date on molecular breeding and genetic transformation in sesame focusing on molecular markers used in assessing the available online database resources, genes responsible for key agronomic traits as well as transgenic technology and genome editing. The review concentrates on quantitative and semi-quantitative studies on molecular breeding for key agronomic traits such as improvement of yield components, oil and oil-related traits, disease and insect/pest resistance, and drought, waterlogging and salt tolerance, as well as sesame genetic transformation and genome editing techniques. Pitfalls and limitations of existing studies and methodologies used so far are identified and some priorities for future research directions in sesame genetic improvement are identified in this review.

Keywords: abiotic stress, biotic stress, improvement, molecular breeding, oil, sesame, shattering

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Authors: Manish Kumar Asthana, Alicia Bundis, Zahn Xu, Braj Bhushan

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Despite ample cross-cultural studies with emotional valence, it is unclear if the emotions are universal or particular. Previous studies have shown that the individualist culture favors high-valence emotions compared to low-valence emotions. In contrast, collectivist culture favors low-valence emotions compared to high-valence emotions. In this current study, Chinese, Mexicans, and Indians reported valence and semantic-contingency. In total, 120 healthy participants were selected by ethnicity and matched for age and education. Each participant was presented 45 non-chromatic pictures, which were converted from chromatic pictures selected from International Affective Picture Database (IAPS) belonging to five-categories, i.e. (i) less pleasant, (ii) high pleasant, (iii) less unpleasant (iv) high unpleasant (v) neutral. The valence scores assigned to neutral, less-unpleasant, and high-pleasant pictures differed significantly between Chinese, Indian, and Mexicans participants. Significant effects demonstrated from the two-way ANOVAs, confirmed main significant effects of valence (F(1,117) = 24.83, p =0.000) and valence x country (F(2,117) = 2.74, p = 0.035). Significant effects emerging from the one-way ANOVAs were followed up through Bonferroni’s test post-hoc comparisons (p < 0.01). This analysis showed significant effect of neutral (F(2,119) = 6.50, p =0.002), less-unpleasant (F(2,119) = 13.79, p =0.000), and high-unpleasant (F(2,119) = 5.99, p =0.003). There were no significant differences in valence scores for the less-pleasant and more-pleasant between participants from three countries. The IAPS norms require modification for their appropriate application in individualist and collectivist cultures.

Keywords: cultural difference, affective processing, valence, non-chromatic, international affective picture system (IAPS)

Procedia PDF Downloads 140

Authors: Nabila Mohamed, Santiago Aparicio, Bahman Tohidi, Mert Atilhan

Abstract:

Qatar's one of the biggest problem in processing its natural resource, which is natural gas, is the often occurring blockage in the pipelines caused due to uncontrolled gas hydrate formation in the pipelines. Several millions of dollars are being spent at the process site to dehydrate the blockage safely by using chemical inhibitors. We aim to establish national database, which addresses the physical conditions that promotes Qatari natural gas to form gas hydrates in the pipelines. Moreover, we aim to design and test novel hydrate inhibitors that are suitable for Qatari natural gas and its processing facilities. From these perspectives we are aiming to provide more effective and sustainable reservoir utilization and processing of Qatari natural gas. In this work, we present the initial findings of a QNRF funded project, which deals with the natural gas hydrate formation characteristics of Qatari type gas in both experimental (PVTx) and computational (molecular simulations) methods. We present the data from the two fully automated apparatus: a gas hydrate autoclave and a rocking cell. Hydrate equilibrium curves including growth/dissociation conditions for multi-component systems for several gas mixtures that represent Qatari type natural gas with and without the presence of well known kinetic and thermodynamic hydrate inhibitors. Ionic liquids were designed and used for testing their inhibition performance and their DFT and molecular modeling simulation results were also obtained and compared with the experimental results. Results showed significant performance of ionic liquids with up to 0.5 % in volume with up to 2 to 4 0C inhibition at high pressures.

Keywords: gas hydrates, natural gas, ionic liquids, inhibition, thermodynamic inhibitors, kinetic inhibitors

Procedia PDF Downloads 1320