Search results for: computer processing of large databases

Authors: Rasha Ahmadi

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Glioblastoma is one of the most frequent brain malignancies, having a high mortality rate and limited survival in individuals with this malignancy. Despite different treatments and surgery, recurrence of glioblastoma cancer stem cells may arise as a subsequent tumor. For this reason, it is crucial to research the markers associated with glioblastoma stem cells and specifically their microenvironment. In this study, using bioinformatics analysis, we analyzed and nominated genes in the microenvironment pathways of glioblastoma stem cells. In this study, an appropriate database was selected for analysis by referring to the GEO database. This dataset comprised gene expression patterns in stem cells derived from glioblastoma patients. Gene clusters were divided as high and low expression. Enrichment databases such as Enrichr, STRING, and GEPIA were utilized to analyze the data appropriately. Finally, we extracted the potential genes 2700 high-expression and 1100 low-expression genes are implicated in the metabolic pathways of glioblastoma cancer progression. Cellular senescence, MAPK, TNF, hypoxia, zimosterol biosynthesis, and phosphatidylinositol metabolism pathways were substantially expressed and the metabolic pathways were downregulated. After assessing the association between protein networks, MSMP, SOX2, FGD4 ,and CNTNAP3 genes with high expression and DMKN and SBSN genes with low were selected. All of these genes were observed in the survival curve, with a survival of fewer than 10 percent over around 15 months. hsa-mir-192-5p, hsa-mir-129-5p, hsa-mir-215-5p, hsa-mir-335-5p, and hsa-mir-340-5p played key function in glioblastoma cancer stem cells microenviroments. We introduced critical genes through integrated and regular bioinformatics studies by assessing the amount of gene expression profile data that can play an important role in targeting genes involved in the energy and microenvironment of glioblastoma cancer stem cells. Have. This study indicated that hsa-mir-192-5p, and hsa-mir-129-5p are appropriate candidates for this.

Keywords: Glioblastoma, Cancer Stem Cells, Biomarker Discovery, Gene Expression Profiles, Bioinformatics Analysis, Tumor Microenvironment

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Authors: Sadeq Alyaari, Muhammad Alkhunayn, Montaha Al Yaari, Ayman Al Yaari, Ayah Al Yaari, Adham Al Yaari, Sajedah Al Yaari, Fatehi Eissa

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Introduction. The purpose of this Systematic Literature Review and Meta-analysis ((SLR & Meta-analysis) was to examine the differences between Asperger syndrome (AS) individuals and typically developing and achieving individuals (TD) regarding language competence and how these differences related to AS individuals’ age and the significance such differences add to our knowledge of understanding their language performance as issues that are still underdiagnosed and ill-treated entities. Methods. The study followed SLR & Meta-analysis protocol and was armed with data of 456 AS subjects and controls (231 and 225, respectively) abstracted from 14 studies that have been collected from different electronic bibliographic databases including web of science, Scopus, EMBASE, Cochrane library, PubMed, PsycInfo and google scholar along with unpublished literature. Results. Outlined results show deterioration in language competence of AS subjects in comparison to TD controls. Such deterioration impairs conversational implicature more than it does conventional maxims of AS individuals’ pragmatic language and has no relationship with their age. Results also show that the difference in intelligence features of the mental reality in the language competence becomes smaller with increasing age and that the difference in representational content features becomes larger. Conclusions. These findings help experts in the field not only predict pragmatic language impairments in AS individuals but also enable AS individuals themselves to decode and/or interpret speech inputs; therefore, perceive the world around them and interact with their community members. Outcomes should be considered to lay out a path for further exploration of genetics, etiology, and response to treatment of all these premises that are currently unsearched in AS individuals.

Keywords: pragmatic language characteristics, language competence, mental faculty, mental reality, features, language performance, pragmatics, conventional maxims

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Authors: Tadesse Melaku Abegaz, Akshaya Srikanth Bahagavathula, Abdulla Shehab Sheab, Asim Hassen

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Objectives: Non-adherence and discontinuation of anticoagulant therapy lead to increased ischemic stroke risk and contributes to suboptimal outcomes of the anticoagulant treatment. This systematic review and meta-analysis were aimed to investigate the adherence to NOACs and adverse events in patients with AF. Methods: Original research articles conducted on patients with AF and using any NOACs (dabigatran, rivoraxaban and apixaban) reporting adherence for at least 35 days were included. Scientific databases including PubMed, Web of Science, and Google Scholar were searched using MeSH keywords to obtaining literature researched between 2008 to till June, 2016. Study characteristics, patient’s sociodemographic and clinical characteristics, medication adherence levels and bleeding events reported were recorded. Results: The overall sample size of the six studies is 1,640,157, with CHADS2 scores < 2 in 551 patients, CHADS2-VASc ≥ 2 in 62,232 AF patients. Three-forth [75.6% (95%CI= 66.5-84.8), p < 0.001] are adherent to NOACs. However, a higher rate [72.7% (62.5-82.9), p < 0.001] of adherence was observed with Dabigatran than Apixaban [59.9% (3.2-123.1), p=0.063] and Rivaroxaban [59.3% (38.7-80.0), p<0.001]. Sub-group analysis revealed that nearly 57% of the AF patients on NOACs have CHADS2 scores < 2 and 20% of these patients were non-adherent to NOACs. Overall bleeding events rate associated with NOACs non-adherent AF patients was found to be 7.5% (0.2-14.8), p=0.045. However, nearly 11.2% of AF patients experienced bleeding events were non-adherent to NOAC medications. A higher proportion of bleeding events were noticed with Dabigatran (14.7%). Conclusions: Adherence rates, while uniformly suboptimal, nevertheless varied considerably, lowest at 59.3% for rivaroxaban and 59.9% for apixaban, followed by dabigatran (75.6%). Overall bleeding events associated with NOACs rates were 7.5%. However, lower adherence to NOACs was associated with worse outcomes among patients with greater stroke risk.

Keywords: atrial fibrillation, bleeding events, meta-analysis, novel oral anticoagulants

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Authors: Fikret Yalcinkaya, Hamza Unsal

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To understand how neurons work, it is required to combine experimental studies on neural science with numerical simulations of neuron models in a computer environment. In this regard, the simplicity and applicability of spiking neuron modeling functions have been of great interest in computational neuron science and numerical neuroscience in recent years. Spiking neuron models can be classified by exhibiting various neuronal behaviors, such as spiking and bursting. These classifications are important for researchers working on theoretical neuroscience. In this paper, three different spiking neuron models; Izhikevich, Adaptive Exponential Integrate Fire (AEIF) and Hindmarsh Rose (HR), which are based on first order differential equations, are discussed and compared. First, the physical meanings, derivatives, and differential equations of each model are provided and simulated in the Matlab environment. Then, by selecting appropriate parameters, the models were visually examined in the Matlab environment and it was aimed to demonstrate which model can simulate well-known biological neuron behaviours such as Tonic Spiking, Tonic Bursting, Mixed Mode Firing, Spike Frequency Adaptation, Resonator and Integrator. As a result, the Izhikevich model has been shown to perform Regular Spiking, Continuous Explosion, Intrinsically Bursting, Thalmo Cortical, Low-Threshold Spiking and Resonator. The Adaptive Exponential Integrate Fire model has been able to produce firing patterns such as Regular Ignition, Adaptive Ignition, Initially Explosive Ignition, Regular Explosive Ignition, Delayed Ignition, Delayed Regular Explosive Ignition, Temporary Ignition and Irregular Ignition. The Hindmarsh Rose model showed three different dynamic neuron behaviours; Spike, Burst and Chaotic. From these results, the Izhikevich cell model may be preferred due to its ability to reflect the true behavior of the nerve cell, the ability to produce different types of spikes, and the suitability for use in larger scale brain models. The most important reason for choosing the Adaptive Exponential Integrate Fire model is that it can create rich ignition patterns with fewer parameters. The chaotic behaviours of the Hindmarsh Rose neuron model, like some chaotic systems, is thought to be used in many scientific and engineering applications such as physics, secure communication and signal processing.

Keywords: Izhikevich, adaptive exponential integrate fire, Hindmarsh Rose, biological neuron behaviours, spiking neuron models

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Authors: Yusuf Adebayo Oduwole

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The evaluation of blockchain technology's potential effects on the accounting and auditing fields is the main objective of this essay. It also adds to the existing body of work by examining how these practices alter technological concerns, including cryptocurrency accounting, regulation, governance, accounting practices, and technical challenges. Examples of this advancement include the growth of the concept of blockchain and its application in accounting. This technology is being considered one of the digital revolutions that could disrupt the world and civilization as it can transfer large volumes of virtual currencies like cryptocurrencies with the help of a third party. The basis for this research is a systematic review of the articles using Vosviewer to display and reflect on the bibliometric information of the articles accessible on the Scopus database. Also, as the practice of using blockchain technology in the field of accounting and auditing is still in its infancy, it may be useful to carry out a more thorough analysis of any implications for accounting and auditing regarding aspects of governance, regulation, and cryptocurrency that have not yet been discussed or addressed to any significant extent. The main findings on the relationship between blockchain and accounting show that the application of smart contracts, such as triple-entry accounting, has increased the quality of accounting records as well as reliance on the information available. This results in fewer cyclical assignments, no need for resolution, and real-time accounting, among others. Thereby, to integrate blockchain through a computer system, one must continuously learn and remain naive when using blockchain-integrated accounting software. This includes learning about how cryptocurrencies are accounted for and regulated. In this study, three original and contributed efforts are presented. To offer a transparent view of the state of previous relevant studies and research works in accounting and auditing that focus on blockchain, it begins by using bibliographic visibility analysis and a Scopus narrative analysis. Second, it highlights legislative, governance, and ethical concerns, such as education, where it tackles the use of blockchain in accounting and auditing. Lastly, it examines the impact of blockchain technologies on the accounting recognition of cryptocurrencies. Users of the technology should, therefore, take their time and learn how it works, as well as keep abreast of the different developments. In addition, the accounting industry must integrate blockchain certification and practice, most likely offline or as part of university education for those intending to become auditors or accountants.

Keywords: blockchain, crypto assets, governance, regulation & smart contracts

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Authors: Khalida Douibi, Rodrigo Balp, Solène Le Bars

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In the medical field, applications related to human experiments are frequently linked to reduced samples size, which makes the training of machine learning models quite sensitive and therefore not very robust nor generalizable. This is notably the case in Brain-Computer Interface (BCI) studies, where the sample size rarely exceeds 20 subjects or a few number of trials. To address this problem, several resampling approaches are often used during the data preparation phase, which is an overly critical step in a data science analysis process. One of the naive approaches that is usually applied by data scientists consists in the transformation of the entire database before the resampling phase. However, this can cause model’ s performance to be incorrectly estimated when making predictions on unseen data. In this paper, we explored the effect of data leakage observed during our BCI experiments for device control through the real-time classification of SSVEPs (Steady State Visually Evoked Potentials). We also studied potential ways to ensure optimal validation of the classifiers during the calibration phase to avoid overfitting. The results show that the scaling step is crucial for some algorithms, and it should be applied after the resampling phase to avoid data leackage and improve results.

Keywords: data leackage, data science, machine learning, SSVEP, BCI, overfitting

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Authors: E. Y. Igde, S. Aydogan, F. E. Boran, D. Akay

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Patent data have an increasingly important role in economic growth, innovation, technical advantages and business strategies and even in countries competitions. Analyzing of patent data is crucial since patents cover large part of all technological information of the world. In this paper, we have used the linguistic summarization technique to prove the validity of the hypotheses related to patent data stated in the literature.

Keywords: data mining, fuzzy sets, linguistic summarization, patent data

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Authors: Fasil Wagnew, Kerri Viney, Kefyalew Addis Alene, Matthew Kelly, Darren Gray

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Background: Undernutrition is a risk factor for tuberculosis (TB), including poor treatment outcomes. However, evidence regarding the effect of undernutrition on TB treatment outcomes is not well understood. We aimed to evaluate the effect of undernutrition on sputum culture conversion and treatment outcomes among people with multi-drug resistance (MDR)-TB. Methods: We searched for publications in the Medline, Embase, Scopus, and Web of Science databases without restrictions on geography or year of publication. We conducted a random-effect meta-analysis to estimate the effects of undernutrition on sputum culture conversion and treatment outcomes. Two reviewers independently assessed the study eligibility, extracted the necessary information, and assessed the risk of bias. Depending on the nature of the data, odds ratio (OR) and hazard ratio (HR) with 95% confidence intervals (CIs) were used to summarize the effect estimates. Potential publication bias was checked using funnel plots and Egger’s tests. Results: Of 2358 records screened, 59 studies comprising a total of 31,254 people with MDR-TB were included. Undernutrition was significantly associated with a lower sputum culture conversion rate (HR 0·7, 95% CI 0·6–0·9, I2=67·1%) and a higher rate of mortality (OR 2·9, 95%CI 2·1–3·8, I2=23·7%) and unfavourable treatment outcomes (OR 1·8, 95%CI 1·5–2·0, I2=72·7%). There was no statistically significant publication bias in the included studies. Three studies were low, forty-two studies were moderate, and fourteen studies were high quality. Interpretations: Undernutrition was significantly associated with unfavourable treatment outcomes, including mortality and lower sputum culture conversion among people with MDR-TB. These findings have implications for supporting targeted nutritional interventions alongside standardised second-line TB drugs.

Keywords: undernutrition, MDR-TB, sputum culture conversion, treatment outcomes, meta-analysis

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Authors: Shashwat, Sandra G. L. Persiani, Yew Wah Wong, Pramod S. Kamath, Avinash H. Anantharam, Hui Ling Aw, Yann Grynberg

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Achieving zero-energy targets in existing buildings is known to be a difficult task, hence targets are addressed at new buildings almost exclusively. Although these ultra-efficient case-studies remain essential to develop future technologies and drive the concepts of Zero-energy, the immediate need to cut the consumption of the existing building stock remains unaddressed. This work aims to present a reliable and straightforward methodology for assessing the potential of energy-efficient upgrading in existing buildings. Public Singaporean school buildings, characterized by low energy use intensity and large roof areas, were identified as potential objects for conversion to highly-efficient buildings with a positive energy balance. A first study phase included the development of a detailed energy model for two case studies (a primary and a secondary school), based on the architectural drawings provided, site-visits and calibrated using measured end-use power consumption of different spaces. The energy model was used to demonstrate compliances or predict energy consumption of proposed changes in the two buildings. As complete energy monitoring is difficult and substantially time-consuming, short-term energy data was collected in the schools by taking spot measurements of power, voltage, and current for all the blocks of school. The figures revealed that the bulk of the consumption is attributed in decreasing order of magnitude to air-conditioning, plug loads, and lighting. In a second study-phase, a number of energy-efficient technologies and strategies were evaluated through energy-modeling to identify the alternatives giving the highest energy saving potential, achieving a reduction in energy use intensity down to 19.71 kWh/m²/y and 28.46 kWh/m²/y for the primary and the secondary schools respectively. This exercise of field evaluation and computer simulation of energy saving potential aims at a preliminary assessment of the positive-energy feasibility enabling future implementation of the technologies on the buildings studied, in anticipation of a broader and more widespread adoption in Singaporean schools.

Keywords: energy simulation, school building, tropical climate, zero energy buildings, positive energy

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Authors: Afnan Al-Romi, Iman Al-Momani

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The urge of applying the Software Engineering (SE) processes is both of vital importance and a key feature in critical, complex large-scale systems, for example, safety systems, security service systems, and network systems. Inevitably, associated with this are risks, such as system vulnerabilities and security threats. The probability of those risks increases in unsecured environments, such as wireless networks in general and in Wireless Sensor Networks (WSNs) in particular. WSN is a self-organizing network of sensor nodes connected by wireless links. WSNs consist of hundreds to thousands of low-power, low-cost, multi-function sensor nodes that are small in size and communicate over short-ranges. The distribution of sensor nodes in an open environment that could be unattended in addition to the resource constraints in terms of processing, storage and power, make such networks in stringent limitations such as lifetime (i.e. period of operation) and security. The importance of WSN applications that could be found in many militaries and civilian aspects has drawn the attention of many researchers to consider its security. To address this important issue and overcome one of the main challenges of WSNs, security solution systems have been developed by researchers. Those solutions are software-based network Intrusion Detection Systems (IDSs). However, it has been witnessed, that those developed IDSs are neither secure enough nor accurate to detect all malicious behaviours of attacks. Thus, the problem is the lack of coverage of all malicious behaviours in proposed IDSs, leading to unpleasant results, such as delays in the detection process, low detection accuracy, or even worse, leading to detection failure, as illustrated in the previous studies. Also, another problem is energy consumption in WSNs caused by IDS. So, in other words, not all requirements are implemented then traced. Moreover, neither all requirements are identified nor satisfied, as for some requirements have been compromised. The drawbacks in the current IDS are due to not following structured software development processes by researches and developers when developing IDS. Consequently, they resulted in inadequate requirement management, process, validation, and verification of requirements quality. Unfortunately, WSN and SE research communities have been mostly impermeable to each other. Integrating SE and WSNs is a real subject that will be expanded as technology evolves and spreads in industrial applications. Therefore, this paper will study the importance of Requirement Engineering when developing IDSs. Also, it will study a set of existed IDSs and illustrate the absence of Requirement Engineering and its effect. Then conclusions are drawn in regard of applying requirement engineering to systems to deliver the required functionalities, with respect to operational constraints, within an acceptable level of performance, accuracy and reliability.

Keywords: software engineering, requirement engineering, Intrusion Detection System, IDS, Wireless Sensor Networks, WSN

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Authors: Ming-Hong Chen

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In the study, the mechanical and financial feasibility for the compressed air energy storage (CAES) system in the porous media reservoir in Taiwan is evaluated. In 2035, Taiwan aims to install 16.7 GW of wind power and 40 GW of photovoltaic (PV) capacity. However, renewable energy sources often generate more electricity than needed, particularly during winter. Consequently, Taiwan requires long-term, large-scale energy storage systems to ensure the security and stability of its power grid. Currently, the primary large-scale energy storage options are Pumped Hydro Storage (PHS) and Compressed Air Energy Storage (CAES). Taiwan has not ventured into CAES-related technologies due to geological and cost constraints. However, with the imperative of achieving net-zero carbon emissions by 2050, there's a substantial need for the development of a considerable amount of renewable energy. PHS has matured, boasting an overall installed capacity of 4.68 GW. CAES, presenting a similar scale and power generation duration to PHS, is now under consideration. Taiwan's geological composition, being a porous medium unlike salt caves, introduces flow field resistance affecting gas injection and extraction. This study employs a program analysis model to establish the system performance analysis capabilities of CAES. The finite volume model is then used to assess the impact of porous media, and the findings are fed back into the system performance analysis for correction. Subsequently, the financial implications are calculated and compared with existing literature. For Taiwan, the strategic development of CAES technology is crucial, not only for meeting energy needs but also for decentralizing energy allocation, a feature of great significance in regions lacking alternative natural resources.

Keywords: compressed-air energy storage, efficiency, porous media, financial feasibility

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Authors: Parker Townes, Aisouda Savadlou, Shoshana Weiss, Marina Jarenova, Suzzane Ferris, Dan Devoe, Russel Schachar, Scott Patten, Tomas Lange, Marlena Colasanto, Holly McGinn, Paul Arnold

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Some research suggests obsessive-compulsive disorder (OCD) is associated with impaired executive functioning: higher-level mental processes involved in carrying out tasks and solving problems. Relevant literature was identified systematically through online databases. Meta-analyses were conducted for task performance metrics reported by at least two articles. Results were synthesized by the executive functioning domain measured through each performance metric. Heterogeneous literature was identified, typically involving few studies using consistent measures. From 29 included studies, analyses were conducted on 33 performance metrics from 12 tasks. Results suggest moderate associations of working memory (two out of five tasks presented significant findings), planning (one out of two tasks presented significant findings), and visuospatial abilities (one out of two tasks presented significant findings) with OCD in youth. There was inadequate literature or contradictory findings for other executive functioning domains. These findings suggest working memory, planning, and visuospatial abilities are impaired in pediatric OCD, with mixed results. More work is needed to identify the effect of age and sex on these results. Acknowledgment: This work was supported by the Alberta Innovates Translational Health Chair in Child and Youth Mental Health. The funders had no role in the design, conducting, writing, or decision to submit this article for publication.

Keywords: obsessive-compulsive disorder, neurocognition, executive functioning, adolescents, children

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Authors: Ahmad Alsolami, Darren Mundy, Manuel Hernandez-Perez

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Social media networks, such as Twitter, offer the perfect opportunity to either positively or negatively affect political attitudes on large audiences. A most important factor contributing to this effect is the existence of influential users, who have developed a reputation for their awareness and experience on specific subjects. Therefore, knowledge of the mechanisms to identify influential users on social media is vital for understanding their effect on their audience. The concept of the influential user is based on the pioneering work of Katz and Lazarsfeld (1959), who created the concept of opinion leaders' to indicate that ideas first flow from mass media to opinion leaders and then to the rest of the population. Hence, the objective of this research was to provide reliable and accurate structural mechanisms to identify influential users, which could be applied to different platforms, places, and subjects. Twitter was selected as the platform of interest, and Saudi Arabia as the context for the investigation. These were selected because Saudi Arabia has a large number of Twitter users, some of whom are considerably active in setting agendas and disseminating ideas. The study considered the scientific methods that have been used to identify public opinion leaders before, utilizing metrics software on Twitter. The key findings propose multiple novel metrics to compare Twitter influencers, including the number of followers, social authority and the use of political hashtags, and four secondary filtering measures. Thus, using ratio and percentage calculations to classify the most influential users, Twitter accounts were filtered, analyzed and included. The structured approach is used as a mechanism to explore the top ten influencers on Twitter from the political domain in Saudi Arabia.

Keywords: twitter, influencers, structured mechanism, Saudi Arabia

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Authors: Wanying Xie

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Under the background of the increasing Sino-US trade friction, the two nations pay more attention to the medias’ words. This paper mainly studies the causality, effectiveness, and influence of discourse construction between traditional media and social media. Based on the Network Agenda Setting theory, a kind of associative memory pattern in Psychology, who focuses on how media affect audiences’ cognition of issues and attributes, as well as the significance of the relation between people and matters. The date of the sample chosen in this paper ranges from March 23, 2018, to April 30, 2019. A total of 395 Tweets of Donald Trump are obtained, and 731 related reports are collected from the mainstream American newspapers including New York Times, the Washington Post and the Washington Street, by using Factiva and other databases. The sample data are processed by MAXQDA while the media discourses are analyzed by SPSS and Cite Space, with an aim to study: 1) whether the inter-media discourse construction exists; 2) which media (traditional media V.S. social media) is dominant; 3) the causality between two media. The results show: 1) the discourse construction between three American mainstream newspapers and Donald Trump's Twitter is proved in some periods; 2) the dominant position is extremely depended on the events; 3) the causality between two media is decided by many reasons. New media technology shortens the time of agenda-setting effect to one day or less. By comparing the specific relation between the three major American newspapers and Donald Trump’s Twitter, whose popularity and influence could be reflected. Hopefully, this paper could enable readers to have a more comprehensive understanding of the international media language and political environment.

Keywords: discourse construction, media language, network agenda-setting theory, sino-us trade friction

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Authors: Rachel Wachtendonk, John Calambokidis, Kiirsten Flynn

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Large marine mammals can serve as an indicator of the overall state of the environment due to their long lifespan and apex position in marine food webs. Reductions in prey, driven by changes in environmental conditions can have resounding impacts on the trophic system as a whole; this can manifest in reduced fat stores that are visible on large whales. Poor health can lead to reduced survivorship and fitness, both of which can be detrimental to a recovering population. A non-invasive technique was used for monitoring blue whale health and for seeing if it changes with ocean conditions. Digital photographs of blue whales taken in the NE Pacific by Cascadia Research and collaborators from 2005-2018 (n=3,545) were scored for overall body condition based on visible vertebrae and body shape on a scale of 0-3 where a score of 0 indicated best body condition and a score of 3 indicated poorest. The data was analyzed to determine if there were patterns in the health of whales across years and whether overall poor health was related to oceanographic conditions and predictors of prey abundance on the California coast. The year was a highly significant factor in body condition (Chi-Square, p<0.001). The proportion of whales showing poor body condition (scores 2 & 3) overall was 33% but by year varied widely from a low of 18% (2008) to a high of 55% (2015). The only two years where >50% of animals had poor body condition were 2015 and 2017 (no other year was above 45%). The 2015 maximum proportion of whales in poor body condition coincide with the marine heat wave that affected the NE Pacific 2014-16 and impacted other whale populations. This indicates that the scoring method was an effective way to evaluate blue whale health and how they respond to a changing ocean.

Keywords: blue whale, body condition, environmental variability, photo-identification

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Authors: Tei Kim, Brooklynn McNeil, Kathryn Dunn, Douglas I. Walker

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To better characterize the relationship between complex chemical exposures and disease, our laboratory uses an approach that combines low-cost, polydimethylsiloxane (silicone) wristband samplers that absorb many of the chemicals we are exposed to with untargeted high-resolution mass spectrometry (HRMS) to characterize 1000’s of chemicals at a time. In studies with human populations, these wristbands can provide an important measure of our environment: however, there is a need to use this approach in large cohorts to study exposures associated with the disease. To facilitate the use of silicone samplers in large scale population studies, the goal of this research project was to establish automated sample preparation methods that improve throughput, robustness, and scalability of analytical methods for silicone wristbands. Using the Opentron OT2 automated liquid platform, which provides a low-cost and opensource framework for automated pipetting, we created two separate workflows that translate the manual wristband preparation method to a fully automated protocol that requires minor intervention by the operator. These protocols include a sequence generation step, which defines the location of all plates and labware according to user-specified settings, and a transfer protocol that includes all necessary instrument parameters and instructions for automated solvent extraction of wristband samplers. These protocols were written in Python and uploaded to GitHub for use by others in the research community. Results from this project show it is possible to establish automated and open source methods for the preparation of silicone wristband samplers to support profiling of many environmental exposures. Ongoing studies include deployment in longitudinal cohort studies to investigate the relationship between personal chemical exposure and disease.

Keywords: bioinformatics, automation, opentrons, research

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Authors: Pei-Hsing Huang, Wei-Ju Huang

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Investment casting is commonly used in the production of metallic components with complex shapes, due to its high dimensional precision, good surface finish, and low cost. However, the process is cumbersome, and the period between trial casting and final production can be very long, thereby limiting business opportunities and competitiveness. In this study, we replaced conventional wax injection with stereolithography (SLA) 3D printing to speed up the trial process and reduce costs. We also used silicone molds to further reduce costs to avoid the high costs imposed by photosensitive resin.

Keywords: investment casting, stereolithography, wax molding, 3D printing

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Authors: Aanh Eduardo Dimate-Garcia, Diana Carolina Rodriguez-Romero, Edna Yuliana Gonzalez Rincon, Diana Marcela Pardo Lopez, Yessica Garibello Cubillos

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Musculoskeletal disorders (MD) are the new epidemic of chronic diseases, are multifactorial and affect the different productive sectors. Although there are multiple instruments to evaluate the static and dynamic load, the method of repetitive occupational action (OCRA) seems to be an attractive option. Objective: It is aimed to analyze the use of the OCRA method and the prevalence of MD in workers of various productive sectors according to the literature (2007-2018). Materials and Methods: A literature review (following the PRISMA statement) of studies aimed at assessing the level of biomechanical risk (OCRA) and the prevalence of MD in the databases Scielo, Science Direct, Scopus, ProQuest, Gale, PubMed, Lilacs and Ebsco was realized; 7 studies met the selection criteria; the majority are quantitative (cross section). Results: it was evidenced (gardening and flower-growers) in this review that 79% of the conditions related to the task require physical requirements and involve repetitive movements. In addition, of the high appearance of DM in the high-low back, upper and lower extremities that are produced by the frequency of the activities carried out (footwear production). Likewise, there was evidence of 'very high risks' of developing MD (salmon industry) and a medium index (OCRA) for repetitive movements that require special care (U-Assembly line). Conclusions: the review showed the limited use of the OCRA method for the detection of MD in workers from different sectors, and this method can be used for the detection of biomechanical risk and the appearance of MD.

Keywords: checklist, cumulative trauma disorders, musculoskeletal diseases, repetitive movements

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Authors: Mohammad Besharatloo

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Intrusion detection is an important research topic in network security because of increasing growth in the use of computer network services. Intrusion detection is done with the aim of detecting the unauthorized use or abuse in the networks and systems by the intruders. Therefore, the intrusion detection system is an efficient tool to control the user's access through some predefined regulations. Since, the data used in intrusion detection system has high dimension, a proper representation is required to show the basis structure of this data. Therefore, it is necessary to eliminate the redundant features to create the best representation subset. In the proposed method, a hybrid model of differential evolution and firefly algorithms was employed to choose the best subset of properties. In addition, decision tree and support vector machine (SVM) are adopted to determine the quality of the selected properties. In the first, the sorted population is divided into two sub-populations. These optimization algorithms were implemented on these sub-populations, respectively. Then, these sub-populations are merged to create next repetition population. The performance evaluation of the proposed method is done based on KDD Cup99. The simulation results show that the proposed method has better performance than the other methods in this context.

Keywords: intrusion detection system, differential evolution, firefly algorithm, support vector machine, decision tree

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Authors: Keisuke Konishi, Yoshinari Hiroshiro, Kento Terashima, Atsushi Tsutsumi

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Imazu Bay plays an important role for endangered species such as horseshoe crabs and black-faced spoonbills that stay in the bay for spawning or the passing of winter. However, this bay is semi-enclosed with slow water exchange, which could lead to eutrophication under the condition of excess nutrient inflow to the bay. Therefore, quantification of nutrient inflow is of great importance. Generally, analysis of nutrient inflow to the bays takes into consideration nutrient inflow from only the river, but that from groundwater should not be ignored for more accurate results. The main objective of this study is to estimate the amounts of nutrient inflow from river and groundwater to Imazu Bay by analyzing water budget in Zuibaiji River Basin and loads of T-N, T-P, NO3-N and NH4-N. The water budget computation in the basin is performed using groundwater recharge model and quasi three-dimensional two-phase groundwater flow model, and the multiplication of the measured amount of nutrient inflow with the computed discharge gives the total amount of nutrient inflow to the bay. In addition, in order to evaluate nutrient inflow to the bay, the result is compared with nutrient inflow from geologically similar river basins. The result shows that the discharge is 3.50×107 m3/year from the river and 1.04×107 m3/year from groundwater. The submarine groundwater discharge accounts for approximately 23 % of the total discharge, which is large compared to the other river basins. It is also revealed that the total nutrient inflow is not particularly large. The sum of NO3-N and NH4-N loadings from groundwater is less than 10 % of that from the river because of denitrification in groundwater. The Shin Seibu Sewage Treatment Plant located below the observation points discharges treated water of 15,400 m3/day and plans to increase it. However, the loads of T-N and T-P from the treatment plant are 3.9 mg/L and 0.19 mg/L, so that it does not contribute a lot to eutrophication.

Keywords: Eutrophication, groundwater recharge model, nutrient inflow, quasi three-dimensional two-phase groundwater flow model, submarine groundwater discharge

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Authors: Laiba Amin, Rashna H. Sukhia, Mubassar Fida

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Introduction: This study evaluates the accuracy of responses from ChatGPT, Google Bard, and Microsoft Copilot regarding dentofacial orthopedic appliances. As artificial intelligence (AI) increasingly enhances various fields, including healthcare, understanding its reliability in specialized domains like orthodontics becomes crucial. By comparing the accuracy of different AI models, this study aims to shed light on their effectiveness and potential limitations in providing technical insights. Materials and Methods: A total of 110 questions focused on dentofacial orthopedic appliances were posed to each AI model. The responses were then evaluated by five experienced orthodontists using a modified 5-point Likert scale to ensure a thorough assessment of accuracy. This structured approach allowed for consistent and objective rating, facilitating a meaningful comparison between the AI systems. Results: The results revealed that Google Bard demonstrated the highest accuracy at 74%, followed by Microsoft Copilot, with an accuracy of 72.2%. In contrast, ChatGPT was found to be the least accurate, achieving only 52.2%. These results highlight significant differences in the performance of the AI models when addressing orthodontic queries. Conclusions: Our study highlights the need for caution in relying on AI for orthodontic insights. The overall accuracy of the three chatbots was 66%, with Google Bard performing best for removable Class II appliances. Microsoft Copilot was more accurate than ChatGPT, which, despite its popularity, was the least accurate. This variability emphasizes the importance of human expertise in interpreting AI-generated information. Further research is necessary to improve the reliability of AI models in specialized healthcare settings.

Keywords: artificial intelligence, large language models, orthodontics, dentofacial orthopaedic appliances, accuracy assessment.

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Authors: Eugene Y. C. Wong

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The increased market competition, customer expectation, and warehouse operating cost in third-party logistics have motivated the continuous exploration in improving operation efficiency in warehouse logistics. Cargo tracing in ordering picking process consumes excessive time for warehouse operators when handling enormous quantities of goods flowing through the warehouse each day. Internet of Things (IoT) with mobile cargo tracing apps and database management systems are developed this research to facilitate and reduce the cargo tracing time in order picking process of a third-party logistics firm. An operation review is carried out in the firm with opportunities for improvement being identified, including inaccurate inventory record in warehouse management system, excessive tracing time on stored products, and product misdelivery. The facility layout has been improved by modifying the designated locations of various types of products. The relationship among the pick and pack processing time, cargo tracing time, delivery accuracy, inventory turnover, and inventory count operation time in the warehouse are evaluated. The correlation of the factors affecting the overall cycle time is analysed. A mobile app is developed with the use of MIT App Inventor and the Access management database to facilitate cargo tracking anytime anywhere. The information flow framework from warehouse database system to cloud computing document-sharing, and further to the mobile app device is developed. The improved performance on cargo tracing in the order processing cycle time of warehouse operators have been collected and evaluated. The developed mobile voice picking and tracking systems brings significant benefit to the third-party logistics firm, including eliminating unnecessary cargo tracing time in order picking process and reducing warehouse operators overtime cost. The mobile tracking device is further planned to enhance the picking time and cycle count of warehouse operators with voice picking system in the developed mobile apps as future development.

Keywords: warehouse, order picking process, cargo tracing, mobile app, third-party logistics

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Authors: Rehana Akhter, Sajad A. Rather, F. A. Masoodi, Adil Gani, S. M. Wani

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During recent years probiotic food products receive market interest as health-promoting, functional foods, which are believed to contribute health benefits. In order to deliver the health benefits by probiotic bacteria, it has been recommended that they must be present at a minimum level of 106 CFU/g to 107 CFU/g at point of delivery or be eaten in sufficient amounts to yield a daily intake of 108 CFU. However a major challenge in relation to the application of probiotic cultures in food matrix is the maintenance of viability during processing which might lead to important losses in viability as probiotic cultures are very often thermally labile and sensitive to acidity, oxygen or other food constituents for example, salts. In this study Lactobacillus plantarum and Lactobacillus casei were encapsulated in calcium alginate beads with the objective of enhancing their survivability and preventing exposure to the adverse conditions of the gastrointestinal tract and where then inoculated in mutton nuggets. Micro encapsulated Lactobacillus plantarum and Lactobacillus casei were resistant to simulated gastric conditions (pH 2, 2h) and bile solution (3%, 2 h) resulting in significantly (p ≤ 0.05) improved survivability when compared with free cell counterparts. A high encapsulation yield was found due to the encapsulation procedure. After incubation at low pH-values, micro encapsulation yielded higher survival rates compared to non-encapsulated probiotic cells. The viable cell numbers of encapsulated Lactobacillus plantarum and Lactobacillus casei were 107-108 CFU/g higher compared to free cells after 90 min incubation at pH 2.5. The viable encapsulated cells were inoculated into mutton nuggets at the rate of 108 to 1010 CFU/g. The micro encapsulated Lactobacillus plantarum and Lactobacillus casei achieved higher survival counts (105-107 CFU/g) than the free cell counterparts (102-104 CFU/g). Thus micro encapsulation offers an effective means of delivery of viable probiotic bacterial cells to the colon and maintaining their survival during simulated gastric, intestinal juice and processing conditions during nugget preparation.

Keywords: survival, Lactobacillus plantarum, Lactobacillus casei, micro-encapsulation, nugget

Procedia PDF Downloads 279

Authors: Biaou Jean-Baptiste Kouchoro, Anissa Meziane, Philippe Micheau, Mathieu Renier, Nicolas Quaegebeur

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Numerous experimental and numerical studies have shown the interest of the local defects resonance (LDR) for the Non-Destructive Testing of metallic and composite plates. Indeed, guided ultrasonic waves such as Lamb waves, which are increasingly used for the inspection of these flat structures, enable the generation of local resonance phenomena by their interaction with a damaged area, allowing the detection of defects. When subjected to a large amplitude motion, a nonlinear behavior can predominate in the damaged area. This work presents a 2D Finite Element Model of the local resonance of a 12 mm long and 5 mm deep Flat Bottom Hole (FBH) in a 6 mm thick aluminum plate under the excitation induced by an incident A0 Lamb mode. The analysis of the transient response of the FBH enables the precise determination of its resonance frequencies and the associate modal deformations. Then, a linear parametric study varying the geometrical properties of the FBH highlights the sensitivity of the resonance frequency with respect to the plate thickness. It is demonstrated that the resonance effect disappears when the ratio of thicknesses between the FBH and the plate is below 0.1. Finally, the nonlinear behavior of the FBH is considered and studied introducing geometrical (taken into account the nonlinear component of the strain tensor) nonlinearities that occur at large vibration amplitudes. Experimental analysis allows observation of the resonance effects and nonlinear response of the FBH. The differences between these experimental results and the numerical results will be commented on. The results of this study are promising and allow to consider more realistic defects such as delamination in composite materials.

Keywords: guided waves, non-destructive testing, dynamic field testing, non-linear ultrasound/vibration

Procedia PDF Downloads 134

Authors: Gabrielle Veloso, Melanie Porter, Kelsie Boulton, Adam Guastella

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The aim of the current systematic review was to examine child and parent factors and their associations with parent sensitivity towards children with Autism Spectrum Disorder (ASD). Eight bibliographic databases were used to identify peer-reviewed journal articles examining these associations via quantitative analyses, with parent sensitivity measured via validated and reliable observation coding systems. Thirty-one studies were finalized as having met full criteria for inclusion. The review found agreement across studies that parent sensitivity was positively associated with the child’s initiations and responsiveness toward their parent, with more frequent parent-directed behaviors providing greater opportunity for parents to act and react in sensitive manner. There was also substantial evidence that parent sensitivity predicted later growth in child language ability and child social skills. Other factors such as child attachment, parent insightfulness toward their child, and parent resolution of the diagnosis were also identified across a number of studies as being positively associated with parent sensitivity, however, interpretations of these findings were limited by the absence of covariates identified in the literature as explaining much of the variance in parent sensitivity. With respect to non-significant associations, the literature reliably found that parents showed sensitivity toward their child with ASD, regardless of child age, ASD symptomology, concurrent child social skills, and concurrent child cognitive abilities. The robust associations found in this review and their potential explanations can serve as a jump off point in identifying an understanding protective and risk factors for families of children with ASD. With regard to future directions in research, assessment of the studies’ methodological quality identified points for improvement with respect to the measurement of parent sensitivity, as well as the consideration of several important methodological confounds that may be controlled for in statistical analyses.

Keywords: ASD, autism, parenting, parent sensitivity

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Authors: Rajwanlop Kumpoopong, Sukit Yindeesuk, Pornchai Silarom

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On May 5, 2014, an earthquake of magnitude 6.3 Richter hit the Northern part of Thailand. The epicenter was in Phan District, Chiang Rai Province. This earthquake or the so-called 2014-Chiang Rai Earthquake is the strongest ground shaking that Thailand has ever been experienced in her modern history. The 2014-Chiang Rai Earthquake confirms the geological evidence, which has previously been ignored by most engineers, that earthquakes of considerable magnitudes 6 to 7 Richter can occurr within the country. This promptly stimulates authorized agencies to pay more attention at the safety of their assets and promotes the comprehensive review of seismic resistance design of their building structures. The focus of this paper is to summarize the damages of highway bridges as a result of the 2014-Chiang Rai ground shaking, the remedy actions, and the research needs. The 2014-Chiang Rai Earthquake caused considerable damages to nearby structures such as houses, schools, and temples. The ground shaking, however, caused damage to only one highway bridge, Mae Laos Bridge, located several kilometers away from the epicenter. The damage of Mae Laos Bridge was in the form of concrete spalling caused by pounding of cap beam on the deck structure. The damage occurred only at the end or abutment span. The damage caused by pounding is not a surprise, but the pounding by only one bridge requires further investigation and discussion. Mae Laos Bridge is a river crossing bridge with relatively large approach structure. In as much, the approach structure is confined by strong retaining walls. This results in a rigid-like approach structure which vibrates at the acceleration approximately equal to the ground acceleration during the earthquake and exerts a huge force to the abutment causing the pounding of cap beam on the deck structure. Other bridges nearby have relatively small approach structures, and therefore have no capability to generate pounding. The effect of mass of the approach structure on pounding of cap beam on the deck structure is also evident by the damage of one pedestrian bridge in front of Thanthong Wittaya School located 50 meters from Mae Laos Bridge. The width of the approach stair of this bridge is wider than the typical one to accommodate the stream of students during pre- and post-school times. This results in a relatively large mass of the approach stair which in turn exerts a huge force to the pier causing pounding of cap beam on the deck structure during ground shaking. No sign of pounding was observed for a typical pedestrian bridge located at another end of Mae Laos Bridge. Although pounding of cap beam on the deck structure of the above mentioned bridges does not cause serious damage to bridge structure, this incident promotes the comprehensive review of seismic resistance design of highway bridges in Thailand. Given a proper mass and confinement of the approach structure, the pounding of cap beam on the deck structure can be easily excited even at the low to moderate ground shaking. In as much, if the ground shaking becomes stronger, the pounding is certainly more powerful. This may cause the deck structure to be unseated and fall off in the case of unrestrained bridge. For the bridge with restrainer between cap beam and the deck structure, the restrainer may prevent the deck structure from falling off. However, preventing free movement of the pier by the restrainer may damage the pier itself. Most highway bridges in Thailand have dowel bars embedded connecting cap beam and the deck structure. The purpose of the existence of dowel bars is, however, not intended for any seismic resistance. Their ability to prevent the deck structure from unseating and their effect on the potential damage of the pier should be evaluated. In response to this expected situation, Thailand Department of Highways (DOH) has set up a team to revise the standard practices for the seismic resistance design of highway bridges in Thailand. In addition, DOH has also funded the research project 'Seismic Resistance Evaluation of Pre- and Post-Design Modifications of DOH’s Bridges' with the scope of full-scale tests of single span bridges under reversed cyclic static loadings for both longitudinal and transverse directions and computer simulations to evaluate the seismic performance of the existing bridges and the design modification bridges. The research is expected to start in October, 2015.

Keywords: earthquake, highway bridge, Thailand, damage, pounding, seismic resistance

Procedia PDF Downloads 290

Authors: El Mahdi Barrah, Said Safi, Abdessamad Malaoui

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In this paper, we present an algorithm for reconstruction from incomplete 2D scans for tifinagh characters. This algorithm is based on using correlation between the lost block and its neighbors. This system proposed contains three main parts: pre-processing, features extraction and recognition. In the first step, we construct a database of tifinagh characters. In the second step, we will apply “shape analysis algorithm”. In classification part, we will use Neural Network. The simulation results demonstrate that the proposed method give good results.

Keywords: Tifinagh character recognition, neural networks, local cost computation, ANN

Procedia PDF Downloads 334

Authors: M. Kouyate, M. Sangare, S. Samake, S. Keita, H. G. Kim, D. H. Geschwind

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Background & Objectives: Human genetic studies can be expensive, even unaffordable, in developing countries, partly due to the sequencing costs. Our aim is to pilot the use of bioinformatics tools to guide scientifically valid, locally relevant, and economically sound autism genetic research in Mali. Methods: The following databases, NCBI, HGMD, and LSDB, were used to identify hot point mutations. Phenotype, transmission pattern, theoretical protein expression in the brain, the impact of the mutation on the 3D structure of the protein) were used to prioritize selected autism genes. We used the protein database, Modeller, and clustal W. Results: We found Mef2c (Gly27Ala/Leu38Gln), Pten (Thr131IIle), Prodh (Leu289Met), Nme1 (Ser120Gly), and Dhcr7 (Pro227Thr/Glu224Lys). These mutations were associated with endonucleases BseRI, NspI, PfrJS2IV, BspGI, BsaBI, and SpoDI, respectively. Gly27Ala/Leu38Gln mutations impacted the 3D structure of the Mef2c protein. Mef2c protein sequences across species showed a high percentage of similarity with a highly conserved MADS domain. Discussion: Mef2c, Pten, Prodh, Nme1, and Dhcr 7 gene mutation frequencies in the Malian population will be very informative. PCR coupled with restriction enzyme digestion can be used to screen the targeted gene mutations. Sanger sequencing will be used for confirmation only. This will cut down considerably the sequencing cost for gene-to-gene mutation screening. The knowledge of the 3D structure and potential impact of the mutations on Mef2c protein informed the protein family and altered function (ex. Leu38Gln). Conclusion & Future Work: Bio-informatics will positively impact autism research in Mali. Our approach can be applied to another neuropsychiatric disorder.

Keywords: bioinformatics, endonucleases, autism, Sanger sequencing, point mutations

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Authors: Kuni Vergauwen, Ivan P. J. Huijnen, Astrid Depuydt, Jasmine Van Regenmortel, Mira Meeus

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A lower activity level and imbalanced activity pattern are frequently observed in persons with chronic fatigue syndrome (CFS) / myalgic encephalomyelitis (ME) due to debilitating fatigue and post-exertional malaise (PEM). Identification of measurement instruments to evaluate the activity level and pattern is therefore important. The objective is to identify measurement instruments suited to evaluate the activity level and/or pattern in patients with CFS/ME and review their psychometric properties. A systematic literature search was performed in the electronic databases PubMed and Web of Science until 12 October 2016. Articles including relevant measurement instruments were identified and included for further analysis. The psychometric properties of relevant measurement instruments were extracted from the included articles and rated based on the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) checklist. The review was performed and reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. A total of 49 articles and 15 unique measurement instruments were found, but only three instruments were evaluated in patients with CFS/ME: the Chronic Fatigue Syndrome-Activity Questionnaire (CFS-AQ), Activity Pattern Interview (API) and International Physical Activity Questionnaire-Short Form (IPAQ-SF), three self-report instruments measuring the physical activity level. The IPAQ-SF, CFS-AQ and API are all equally capable of evaluating the physical activity level, but none of the three measurement instruments are optimal to use. No studies about the psychometric properties of activity monitors in patients with CFS/ME were found, although they are often used as the gold standard to measure the physical activity pattern. More research is needed to evaluate the psychometric properties of existing instruments, including the use of activity monitors.

Keywords: chronic fatigue syndrome, data collection, physical activity, psychometrics

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Authors: Nsimbe Allan

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The study examines the impact of Building Information Modeling (BIM) on the cost management of engineering projects, focusing specifically on the Mombasa Port Area Development Project. The objective of this research venture is to determine the mechanisms through which Building Information Modeling (BIM) facilitates stakeholder collaboration, reduces construction-related expenses, and enhances the precision of cost estimation. Furthermore, the study investigates barriers to execution, assesses the impact on the project's transparency, and suggests approaches to maximize resource utilization. The study, selected for its practical significance and intricate nature, conducted a Systematic Literature Review (SLR) using credible databases, including ScienceDirect and IEEE Xplore. To constitute the diverse sample, 69 individuals, including project managers, cost estimators, and BIM administrators, were selected via stratified random sampling. The data were obtained using a mixed-methods approach, which prioritized ethical considerations. SPSS and Microsoft Excel were applied to the analysis. The research emphasizes the crucial role that project managers, architects, and engineers play in the decision-making process (47% of respondents). Furthermore, a significant improvement in cost estimation accuracy was reported by 70% of the participants. It was found that the implementation of BIM resulted in enhanced project visibility, which in turn optimized resource allocation and facilitated the process of budgeting. In brief, the study highlights the positive impacts of Building Information Modeling (BIM) on collaborative decision-making and cost estimation, addresses challenges related to implementation, and provides solutions for the efficient assimilation and understanding of BIM principles.

Keywords: cost management, resource utilization, stakeholder collaboration, project transparency

Procedia PDF Downloads 67