Search results for: Maximum Entropy Bootstrapping approach

Authors: Ali Ben Abbes, Imed Riadh Farah

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Due to the considerable advances in Multi-Temporal Satellite Images (MTSI), remote sensing application became more accurate. Recently, many advances in modeling MTSI are developed using various models. The purpose of this article is to present an overview of studies using Hidden Markov Model (HMM). First of all, we provide a background of using HMM and their applications in this context. A comparison of the different works is discussed, and possible areas and challenges are highlighted. Secondly, we discussed the difference on vegetation monitoring as well as urban growth. Nevertheless, most research efforts have been used only stationary data. From another point of view, in this paper, we describe a new non-stationarity HMM, that is defined with a set of parts of the time series e.g. seasonal, trend and random. In addition, a new approach giving more accurate results and improve the applicability of the HMM in modeling a non-stationary data series. In order to assess the performance of the HMM, different experiments are carried out using Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI time series of the northwestern region of Tunisia and Landsat time series of tres Cantos-Madrid in Spain.

Keywords: multi-temporal satellite image, HMM , nonstationarity, vegetation, urban

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Authors: Eduardo Garcia Agustin

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This paper focuses on how Mickey – the 10-year-old main character and narrator in Paul McVeigh’s novel The Good Son (2015) – becomes aware of his own queerness and its implications in a conflicting place and time such as Belfast during ‘The Troubles’ in the 1980s. Queer theory allows a comparative reading of identity issues such as national and gender discourses. As opposed to some other excluding social constructs that classify identities in an Us-Others binomial, queer has become a sort of umbrella term where there is room for more identities other than LGTBQ. Therefore, it offers some relevant tools to read this highly awarded novel by focusing on the intersectional construction of Mickey’s identity in progress within the social and familiar realms. The aim of this paper is to offer a queer reading of the The Good Son, which was awarded with the Polari First Book Prize in 2016, by showing the key role of Mickey’s conflictive realization of his own queerness in the polarized society of Northern Ireland in the 1980s, where there is no shade of grey. Within such a polarized context, Mickey’s perception of his own internal and external identity conflicts he is exposed to will show how necessary a certain touch of pink is as a potential escape to those conflicts.

Keywords: conflict, national identity, Northern Ireland, queer identity

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Authors: Sheetla Prasad

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The focus issue of this article is to determine the mechanism of mind with geometrical analysis of human face. Research paradigm has been designed for study of spatial dynamic of face and it was found that different shapes of face have their own function for determine the action of mind. The functional ratio (FR) of face has determined the behaviour operation of human beings. It is not based on the formulistic approach of prediction but scientific dogmatism and mathematical analysis is the root of the prediction of behaviour. For analysis, formulae were developed and standardized. It was found that human psyche is designed in three forms; manipulated, manifested and real psyche. Functional output of the psyche has been determined by degree of energy flow in the psyche and reserve energy for future. Face is the recipient and transmitter of energy but distribution and control is the possible by mind. Mind directs behaviour. FR indicates that the face is a power house of energy and as per its geometrical domain force of behaviours has been designed and actions are possible in the nature of individual. The impact factor of this study is the promotion of human capital for job fitness objective and minimization of criminalization in society.

Keywords: functional ratio, manipulated psyche, manifested psyche, real psyche

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Authors: Amitkumar Barot, Vijaykumar Sinha

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There is growing interest in the development of new materials based on recycled polymers from plastic waste, and also in the field of lubricants much effort has been spent on substitution of petro-based raw materials by natural-based renewable ones. This is due to the facts of depleting fossil fuels and due to strict environmental laws. In relevance to this, new technique for the formulation of grease that combines the chemical recycling of poly (ethylene terephthalate) PET with the use of castor oil (CO) has been developed. Comparison to diols used in chemical recycling of PET, castor oil is renewable, easily available, environmentally friendly, economically cheaper and hence sustainability indeed. The process parameters like CO concentration and temperature were altered, and further, the influences of the process parameters have been studied in order to establish technically and commercially viable process. Further thereby formed depolymerized product find an application as base oil in the formulation of grease. A depolymerized product has been characterized by various chemical and instrumental methods, while formulated greases have been evaluated for its tribological properties. The grease formulated using this new environmentally friendly approach presents applicative properties similar, and in some cases superior, compared to those of a commercial grease obtained from non-renewable resources.

Keywords: castor oil, grease formulation, recycling, sustainability

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Authors: S. Sonkham, U. Pinsopon, W. Chatlatanagulchai

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This paper presents a method of sliding mode control (SMC) designing and developing for the servo system in a dual-stage actuator (DSA) hard disk drive. Mathematical modelling of hard disk drive actuators is obtained, extracted from measuring frequency response of the voice-coil motor (VCM) and PZT micro-actuator separately. Matlab software tools are used for mathematical model estimation and also for controller design and simulation. A model-reference approach for tracking requirement is selected as a proposed technique. The simulation results show that performance of a model-reference SMC controller design in DSA servo control can be satisfied in the tracking error, as well as keeping the positioning of the head within the boundary of +/-5% of track width under the presence of internal and external disturbance. The overall results of model-reference SMC design in DSA are met per requirement specifications and significant reduction in %off track is found when compared to the single-state actuator (SSA).

Keywords: hard disk drive, dual-stage actuator, track following, hdd servo control, sliding mode control, model-reference, tracking control

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Authors: Sangeeta Palekar, Neeraj Rangwani, Akash Poddar, Jayu Kalambe

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The bio-medical analysis is an indispensable procedure for identifying health-related diseases like diabetes. Monitoring the glucose level in our body regularly helps us identify hyperglycemia and hypoglycemia, which can cause severe medical problems like nerve damage or kidney diseases. This paper presents a method for predicting the glucose concentration in blood samples using image processing and machine learning algorithms. The glucose solution is prepared by the glucose oxidase (GOD) and peroxidase (POD) method. An experimental database is generated based on the colorimetric technique. The image of the glucose solution is captured by the raspberry pi camera and analyzed using image processing by extracting the RGB, HSV, LUX color space values. Regression algorithms like multiple linear regression, decision tree, RandomForest, and XGBoost were used to predict the unknown glucose concentration. The multiple linear regression algorithm predicts the results with 97% accuracy. The image processing and machine learning-based approach reduce the hardware complexities of existing platforms.

Keywords: artificial intelligence glucose detection, glucose oxidase, peroxidase, image processing, machine learning

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Authors: Ghada Moussa, Mamoud Owais

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Transit Route Network Design Problem (TrNDP) is the most important component in Transit planning, in which the overall cost of the public transportation system highly depends on it. The main purpose of this study is to develop a novel solution methodology for the TrNDP, which goes beyond pervious traditional sophisticated approaches. The novelty of the solution methodology, adopted in this paper, stands on the deterministic operators which are tackled to construct bus routes. The deterministic manner of the TrNDP solution relies on using linear and integer mathematical formulations that can be solved exactly with their standard solvers. The solution methodology has been tested through Mandl’s benchmark network problem. The test results showed that the methodology developed in this research is able to improve the given network solution in terms of number of constructed routes, direct transit service coverage, transfer directness and solution reliability. Although the set of routes resulted from the methodology would stand alone as a final efficient solution for TrNDP, it could be used as an initial solution for meta-heuristic procedures to approach global optimal. Based on the presented methodology, a more robust network optimization tool would be produced for public transportation planning purposes.

Keywords: integer programming, transit route design, transportation, urban planning

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Authors: Jessie Fazel, Kristen Smith

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Human trafficking is a multi-billion-dollar criminal industry that affects 24.9 million people around the world. There are several different types of trafficking, the most common being sex trafficking, labor trafficking, and domestic servitude. Survival sex is common in the pediatric population, as they engage in sex for food, a place to sleep, or other basic needs. Statistics show that health care workers are at a unique advantage to help identify victims and get them the help they need, as 88% of trafficked victims encounter a health care worker while being trafficked. Unfortunately, victims don’t usually self-identify that they are being trafficked and the situations they face can vary dramatically. It is imperative to remember that traditional red flags are not always present in the pediatric population. Risk factors and red flags with their history and physical exam are one of the best indicators that health care providers need to be vigilant in looking at. There are numerous barriers for disclosure in the healthcare setting. Periods of time before and after disclosure are often emotionally difficult and could be dangerous for the victim. It is extremely important to have a plan in place for intervention if the victim does disclose trafficking. A trauma informed approach to medical and mental health interventions, that focus on safety, are vital in this population. This is happening where you live and you can make a difference in their lives.

Keywords: human trafficking, public health, emergency medicine, sexual health

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Authors: Georg Brunnthaller, Sandra Stein, Wilfried Sihn

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Logistics service providers are facing increasing volatility concerning future transport demand. Short-term planning horizons and planning uncertainties lead to reduced capacity utilisation and increasing empty mileage. To overcome these challenges, a model is proposed to continuously pre-plan future transport capacity in order to redesign and adjust the intermodal fleet accordingly. It is expected that the model will enable logistics service providers to organise more economically and ecologically sustainable transport chains in a more flexible way. To further describe such planning aspects, this paper gives a structured literature review on transport planning problems. The focus is on strategic and tactical planning levels, comprising relevant fleet-sizing-, network-design- and choice-of-carriers-problems. Models and their developed solution techniques are presented and the literature review is concluded with an outlook to our future research objectives

Keywords: choice of transport mode, fleet-sizing, freight transport planning, multimodal, review, service network design

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Authors: Yen Yen Tan, Lynn Lam, Cynthia Lam, Angela Koh, Edwin Seng

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Entrepreneurial education plays a crucial role in nurturing future innovators and change-makers. Over time, significant progress has been made in refining instructional approaches to develop the necessary skills among learners effectively. Two highly valuable frameworks, Kearney's "4 Principles of Entrepreneurial Pedagogy" and Bloom's "Three Domains of Learning," serve as guiding principles in entrepreneurial education. Kearney's principles align with experiential and student-centric learning, which are crucial for cultivating an entrepreneurial mindset. The potential synergies between these frameworks hold great promise for enhancing entrepreneurial acumen among students. However, despite this potential, their integration remains largely unexplored. This study aims to bridge this gap by building upon the Business Essentials through Action (BETA) module and investigating its contributions to nurturing the entrepreneurial mindset. This study employs a quasi-experimental mixed-methods approach, combining quantitative and qualitative elements to ensure comprehensive and insightful data. A cohort of 235 students participated, with 118 enrolled in the BETA module and 117 in a traditional curriculum. Their Personal Entrepreneurial Competencies (PECs) were assessed before admission (pre-Y1) and one year into the course (post-Y1) using a comprehensive 55-item PEC questionnaire, enabling measurement of critical traits such as opportunity-seeking, persistence, and risk-taking. Rigorous computations of individual entrepreneurial competencies and overall PEC scores were performed, including a correction factor to mitigate potential self-assessment bias. The orchestration of Kearney's principles and Bloom's domains within the BETA module necessitates a granular examination. Here, qualitative revelations surface, courtesy of structured interviews aligned with contemporary research methodologies. These interviews act as a portal, ushering us into the transformative journey undertaken by students. Meanwhile, the study pivots to explore the BETA module's influence on students' entrepreneurial competencies from the vantage point of faculty members. A symphony of insights emanates from intimate focus group discussions featuring six dedicated lecturers, who share their perceptions, experiences, and reflective narratives, illuminating the profound impact of pedagogical practices embedded within the BETA module. Preliminary findings from ongoing data analysis indicate promising results, showcasing a substantial improvement in entrepreneurial skills among students participating in the BETA module. This study promises not only to elevate students' entrepreneurial competencies but also to illuminate the broader canvas of applicability for Kearney's principles and Bloom's domains. The dynamic interplay of quantitative analyses, proffering precise competency metrics, and qualitative revelations, delving into the nuanced narratives of transformative journeys, engenders a holistic understanding of this educational endeavour. Through a rigorous quasi-experimental mixed-methods approach, this research aims to establish the BETA module's effectiveness in fostering entrepreneurial acumen among students at Singapore Polytechnic, thereby contributing valuable insights to the broader discourse on educational methodologies.

Keywords: entrepreneurial education, experiential learning, pedagogical frameworks, innovative competencies

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Authors: George R. Puno, Eric N. Bruno

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The natural landscape of the Philippine archipelago plus the current realities of climate change make the country vulnerable to flood hazards. Flooding becomes the recurring natural disaster in the country resulting to lose of lives and properties. Musimusi is among the rivers which exhibited inundation particularly at the inhabited floodplain portion of its watershed. During the event, rescue operations and distribution of relief goods become a problem due to lack of high resolution flood maps to aid local government unit identify the most affected areas. In the attempt of minimizing impact of flooding, hydrologic modelling with high resolution mapping is becoming more challenging and important. This study focused on the analysis of flood extent as a function of different geomorphologic characteristics of Musimusi watershed. The methods include the delineation of morphometric parameters in the Musimusi watershed using Geographic Information System (GIS) and geometric calculations tools. Digital Terrain Model (DTM) as one of the derivatives of Light Detection and Ranging (LiDAR) technology was used to determine the extent of river inundation involving the application of Hydrologic Engineering Center-River Analysis System (HEC-RAS) and Hydrology Modelling System (HEC-HMS) models. The digital elevation model (DEM) from synthetic Aperture Radar (SAR) was used to delineate watershed boundary and river network. Datasets like mean sea level, river cross section, river stage, discharge and rainfall were also used as input parameters. Curve number (CN), vegetation, and soil properties were calibrated based on the existing condition of the site. Results showed that the drainage density value of the watershed is low which indicates that the basin is highly permeable subsoil and thick vegetative cover. The watershed’s elongation ratio value of 0.9 implies that the floodplain portion of the watershed is susceptible to flooding. The bifurcation ratio value of 2.1 indicates higher risk of flooding in localized areas of the watershed. The circularity ratio value (1.20) indicates that the basin is circular in shape, high discharge of runoff and low permeability of the subsoil condition. The heavy rainfall of 167 mm brought by Typhoon Seniang last December 29, 2014 was characterized as high intensity and long duration, with a return period of 100 years produced 316 m3s-1 outflows. Portion of the floodplain zone (1.52%) suffered inundation with 2.76 m depth at the maximum. The information generated in this study is helpful to the local disaster risk reduction management council in monitoring the affected sites for more appropriate decisions so that cost of rescue operations and relief goods distribution is minimized.

Keywords: flooding, geomorphology, mapping, watershed

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Authors: Fahrur Rozi, Daniswara Krisna Prabatha, Latief Zulfikar Chusaini

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Amidst the backdrop of Pertamina Plaju Refinery, which stands as the oldest and historically less technologically advanced among Pertamina's refineries, lies a unique challenge. Originally integrating facilities established by Shell in 1904 and Stanvac (originally Standard Oil) in 1926, the primary challenge at Plaju Refinery does not solely revolve around complexity; instead, it lies in ensuring reliability, considering its operational history of over a century. After centuries of existence, Plaju Refinery has never undergone a comprehensive major turnaround encompassing all its units. The usual practice involves partial turnarounds that are sequentially conducted across its primary, secondary, and tertiary units (utilities and offsite). However, a significant shift is on the horizon. In the Q-IV of 2023, the refinery embarks on its first-ever major turnaround since its establishment. This decision was driven by the alignment of maintenance timelines across various units. Plaju Refinery's major turnaround was scheduled for October-November 2023, spanning 45 calendar days, with the objective of enhancing the operational reliability of all refinery units. The extensive job list for this turnaround encompasses 1583 tasks across 18 units/areas, involving approximately 9000 contracted workers. In this context, the Strategy of Simultaneous Operations (SIMOPS) execution emerges as a pivotal tool to optimize time efficiency and ensure safety. A Hazard Effect Management Process (HEMP) has been employed to assess the risk ratings of each task within the turnaround. Out of the tasks assessed, 22 are deemed high-risk and necessitate mitigation. The SIMOPS approach serves as a preventive measure against potential incidents. It is noteworthy that every turnaround period at Pertamina Plaju Refinery involves SIMOPS-related tasks. In this context, enhancing the implementation strategy of "Simultaneous Operations (SIMOPS)" becomes imperative to minimize the occurrence of incidents. At least four improvements have been introduced in the enhancement process for the major turnaround at Refinery Plaju. The first improvement involves conducting systematic risk assessment and potential hazard mitigation studies for SIMOPS tasks before task execution, as opposed to the previous on-site approach. The second improvement includes the completion of SIMOPS Job Mitigation and Work Matrices Sheets, which was often neglected in the past. The third improvement emphasizes comprehensive awareness to workers/contractors regarding potential hazards and mitigation strategies for SIMOPS tasks before and during the major turnaround. The final improvement is the introduction of a daily program for inspecting and observing work in progress for SIMOPS tasks. Prior to these improvements, there was no established program for monitoring ongoing activities related to SIMOPS tasks during the turnaround. This study elucidates the steps taken to enhance SIMOPS within Pertamina, drawing from the experiences of Plaju Refinery as a guide. A real actual case study will be provided from our experience in the operational unit. In conclusion, these efforts are essential for the success of the first-ever major turnaround at Plaju Refinery, with the SIMOPS strategy serving as a central component. Based on these experiences, enhancements have been made to Pertamina's official Internal Guidelines for Executing SIMOPS Risk Mitigation, benefiting all Pertamina units.

Keywords: process safety management, turn around, oil refinery, risk assessment

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Authors: Justine Kiiza, Xu Jiafang

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The world’s demand for energy is increasing rapidly due to population growth and a reduction in shallow conventional oil and gas reservoirs, resorting to deeper and mostly unconventional reserves like shale oil and gas. Most shale formations contain a large amount of expansive sodium montmorillonite (Na-Mnt), due to high water adsorption, hydration, and when the drilling fluid filtrate enters the formation with high Mnt content, the wellbore wall can be unstable due to hydration and swelling, resulting to shrinkage, sticking, balling, time wasting etc., and well collapse in extreme cases causing complex downhole accidents and high well costs. Recently, polyamines like 1, 6 – hexane diamine (HEDA) have been used as typical drilling fluid shale inhibitors to minimize and/or cab clay mineral swelling and maintain the wellbore stability. However, their application is limited to shallow drilling due to their sensitivity to elevated temperature and pressure. Inorganic potassium salts i.e., KCl, have long been applied for restriction of shale formation hydration expansion in deep wells, but their use is limited due to toxicity. Understanding the adsorption behaviour of HEDA on Na-Mnt surfaces in present of organo-salts, organic K-salts e.g., HCO₂K - main component of organo-salt drilling fluid, is of great significance in explaining the inhibitory performance of polyamine inhibitors. Molecular dynamic simulations (MD) were applied to investigate the influence of HCO₂K and KCl on the adsorption mechanism of HEDA on the Na-Mnt surface. Simulation results showed that adsorption configurations of HEDA are mainly by terminal amine groups with a flat-lying alkyl hydrophobic chain. Its interaction with the clay surface decreased the H-bond number between H₂O-clay and neutralized the negative charge of the Mnt surface, thus weakening the surface hydration ability of Na-Mnt. The introduction of HCO₂K greatly improved inhibition ability, coordination of interlayer ions with H₂O as they were replaced by K+, and H₂O-HCOO- coordination reduced H₂O-Mnt interactions, mobility and transport capability of H₂O molecules were more decreased. While KCl showed little ability and also caused more hydration with time, HCO₂K can be used as an alternative for offshore drilling instead of toxic KCl, with a maximum concentration noted in this study as 1.65 wt%. This study provides a theoretical elucidation for the inhibition mechanism and adsorption characteristics of HEDA inhibitor on Na-Mnt surfaces in the presence of K+-salts and may provide more insight into the evaluation, selection, and molecular design of new clay-swelling high-performance WBDF systems used in oil and gas complex offshore drilling well sections.

Keywords: shale, hydration, inhibition, polyamines, organo-salts, simulation

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Authors: S. Alansary, M. Nagi

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This paper presents an approach of conducting semantic annotation of Arabic corpus using the Universal Networking Language (UNL) framework. UNL is intended to be a promising strategy for providing a large collection of semantically annotated texts with formal, deep semantics rather than shallow. The result would constitute a semantic resource (semantic graphs) that is editable and that integrates various phenomena, including predicate-argument structure, scope, tense, thematic roles and rhetorical relations, into a single semantic formalism for knowledge representation. The paper will also present the Interactive Analysis​ tool for automatic semantic annotation (IAN). In addition, the cornerstone of the proposed methodology which are the disambiguation and transformation rules, will be presented. Semantic annotation using UNL has been applied to a corpus of 20,000 Arabic sentences representing the most frequent structures in the Arabic Wikipedia. The representation, at different linguistic levels was illustrated starting from the morphological level passing through the syntactic level till the semantic representation is reached. The output has been evaluated using the F-measure. It is 90% accurate. This demonstrates how powerful the formal environment is, as it enables intelligent text processing and search.

Keywords: semantic analysis, semantic annotation, Arabic, universal networking language

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Authors: Imen Ben Abda

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Languages have been classified into different rhythm classes. 'Stress-timed' languages are exemplified by English, 'syllable-timed' languages by French and 'mora-timed' languages by Japanese. However, to our best knowledge, acoustic studies have not been unanimous in strictly establishing which rhythm category a given language belongs to and failed to show empirical evidence for isochrony. Perception seems to be a good approach to categorize languages into different rhythm classes. This study, within the scope of experimental phonetics, includes an account of different perceptual experiments using cues from natural and inverted speech, as well as pitch extracted from speech data. It is an attempt to categorize speech rhythm over a large set of Arabic (Tunisian, Algerian, Lebanese and Moroccan) and English dialects (Welsh, Irish, Scottish and Texan) as well as other languages such as Chinese, Japanese, French, and German. Listeners managed to classify the different languages and dialects into different rhythm classes using suprasegmental cues mainly rhythm and pitch (F0). They also perceived rhythmic differences even among languages and dialects belonging to the same rhythm class. This may show that there are different subclasses within very broad rhythmic typologies.

Keywords: F0, inverted speech, mora-timing, rhythm variation, stress-timing, syllable-timing

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Authors: K. Indra Gandhi

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Wireless Sensor Networks (WSNs) have always been characterized for application-specific sensing, relaying and collection of information for further analysis. However, software development was not considered as a separate entity in this process of data collection which has posed severe limitations on the software development for WSN. Software development for WSN is a complex process since the components involved are data-driven, network-driven and application-driven in nature. This implies that there is a tremendous need for the separation of concern from the software development perspective. A layered approach for developing data acquisition design based on Model Driven Development (MDD) has been proposed as the sensed data collection process itself varies depending upon the application taken into consideration. This work focuses on the layered view of the data acquisition process so as to ease the software point of development. A metamodel has been proposed that enables reusability and realization of the software development as an adaptable component for WSN systems. Further, observing users perception indicates that proposed model helps in improving the programmer's productivity by realizing the collaborative system involved.

Keywords: data acquisition, model-driven development, separation of concern, wireless sensor networks

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Authors: William Whiteley, Jens Gregor

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In recent developments of direct neural network based positron emission tomography (PET) reconstruction, two prominent architectures have emerged for converting measurement data into images: 1) networks that contain fully-connected layers; and 2) networks that primarily use a convolutional encoder-decoder architecture. In this paper, we present a multi-modal direct PET reconstruction method called MDPET, which is a hybrid approach that combines the advantages of both types of networks. MDPET processes raw data in the form of sinograms and histo-images in concert with attenuation maps to produce high quality multi-slice PET images (e.g., 8x440x440). MDPET is trained on a large whole-body patient data set and evaluated both quantitatively and qualitatively against target images reconstructed with the standard PET reconstruction benchmark of iterative ordered subsets expectation maximization. The results show that MDPET outperforms the best previously published direct neural network methods in measures of bias, signal-to-noise ratio, mean absolute error, and structural similarity.

Keywords: deep learning, image reconstruction, machine learning, neural network, positron emission tomography

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Authors: Asma A. Alsufyani, Maram A. Alharthi, Maha J. Althobaiti, Manal S. Alharthi, Huda Rizq

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Twitter is one of the most popular microblogging sites that allows users to publish short text messages called 'tweets'. Increasing the number of accounts to follow (followings) increases the number of tweets that will be displayed from different topics in an unclassified manner in the timeline of the user. Therefore, it can be a vital solution for many Twitter users to have their tweets in a timeline classified into general categories to save the user’s time and to provide easy and quick access to tweets based on topics. In this paper, we developed a classifier for timeline tweets trained on a dataset consisting of 3600 tweets in total, which were collected from Saudi Twitter and annotated manually. We experimented with the well-known Bag-of-Words approach to text classification, and we used support vector machines (SVM) in the training process. The trained classifier performed well on a test dataset, with an average F1-measure equal to 92.3%. The classifier has been integrated into an application, which practically proved the classifier’s ability to classify timeline tweets of the user.

Keywords: corpus creation, feature extraction, machine learning, short text classification, social media, support vector machine, Twitter

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Authors: Celine Bonnaud, Isabelle Billard, Nicolas Papaiconomou, Eric Chainet

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Thanks to their high magnetization and low mass, permanent magnets (NdFeB and SmCo) have quickly became essential for new energies (wind turbines, electrical vehicles…). They contain large quantities of neodymium, samarium and dysprosium, that have been recently classified as critical elements and that therefore need to be recycled. Electrochemical processes including electrodissolution followed by electrodeposition are an elegant and environmentally friendly solution for the recycling of such lanthanides contained in permanent magnets. However, electrochemistry of the lanthanides is a real challenge as their standard potentials are highly negative (around -2.5V vs ENH). Consequently, non-aqueous solvents are required. Ionic liquids (IL) are novel electrolytes exhibiting physico-chemical properties that fulfill many requirements of the sustainable chemistry principles, such as extremely low volatility and non-flammability. Furthermore, their chemical and electrochemical properties (solvation of metallic ions, large electrochemical windows, etc.) render them very attractive media to implement alternative and sustainable processes in view of integrated processes. All experiments that will be presented were carried out using butyl-methylpyrrolidinium bis(trifluoromethanesulfonyl)imide. Linear sweep, cyclic voltammetry and potentiostatic electrochemical techniques were used. The reliability of electrochemical experiments, performed without glove box, for the classic three electrodes cell used in this study has been assessed. Deposits were obtained by chronoamperometry and were characterized by scanning electron microscopy and energy-dispersive X-ray spectroscopy. The IL cathodic behavior under different constraints (argon, nitrogen, oxygen atmosphere or water content) and using several electrode materials (Pt, Au, GC) shows that with argon gas flow and gold as a working electrode, the cathodic potential can reach the maximum value of -3V vs Fc+/Fc; thus allowing a possible reduction of lanthanides. On a gold working electrode, the reduction potential of samarium and neodymium was found to be -1.8V vs Fc+/Fc while that of dysprosium was -2.1V vs Fc+/Fc. The individual deposits obtained were found to be porous and presented some significant amounts of C, N, F, S and O atoms. Selective deposition of neodymium in presence of dysprosium was also studied and will be discussed. Next, metallic Sm, Nd and Dy electrodes were used in replacement of Au, which induced changes in the reduction potential values and the deposit structures of lanthanides. The individual corrosion potentials were also measured in order to determine the parameters influencing the electrodissolution of these metals. Finally, a full recycling process was investigated. Electrodissolution of a real permanent magnet sample was monitored kinetically. Then, the sequential electrodeposition of all lanthanides contained in the IL was investigated. Yields, quality of the deposits and consumption of chemicals will be discussed in depth, in view of the industrial feasibility of this process for real permanent magnets recycling.

Keywords: electrodeposition, electrodissolution, ionic liquids, lanthanides, rcycling

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Authors: Melissa C. LaDuke

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The overarching purpose of this study was to determine the relationship between the current format of online delivery for Defense Acquisition University (DAU) courses and Air Force Acquisition (AFA) personnel participation. AFA personnel (hereafter named “student”) were particularly of interest, as they have been mandated to take anywhere from 3 to 30 online courses to earn various DAU specialization certifications. Participants in this qualitative case study were AFA personnel who pursued DAU certifications in science and technology management, program/contract management, and other related fields. Air Force personnel were interviewed about their experiences with online courses. The data gathered were analyzed and grouped into 12 major themes. The themes tied into the theoretical framework and spoke to either teacher-centered or student-centered educational practices within Defense Acquisitions University. Based on the results of the data analysis, various factors contributed to student perceptions of DAU courses, including the online course construct and relevance to their job. The analysis also found students want to learn the information presented but would like to be able to apply the information learned in meaningful ways.

Keywords: educational theory, computer-based training, interview, student perceptions, online course design, teacher positionality

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Authors: Jiamin Chen, Liping Yang

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In 2007, sociologist Putnam proposed a pessimistic forecast in the United States' "Social Capital Community Benchmark Survey," suggesting that "ethnic diversity would challenge social unity and undermine social cohesion." If this pessimistic assumption were proven true, it would indicate a risk of division in diverse societies. China, with 56 ethnic groups, is a multi-ethnic country. On May 26, 2014, General Secretary Xi Jinping proposed "building ethnically inter-embedded communities to promote deeper development in interactions, exchanges, and integration among ethnic groups." Researchers unanimously agree that ethnic inter-embedded communities can serve as practical arenas and pathways for solidifying the sense of the Chinese national community However, there is no research providing evidence that ethnic inter-embedded communities can foster the sense of the Chinese national community, and the influencing factors remain unclear. This study adopts a constructivist grounded theory research approach. Convenience sampling and snowball sampling were used in the study. Data were collected in three communities in Kunming City. Twelve individuals were eventually interviewed, and the transcribed interviews totaled 187,000 words. The research has obtained ethical approval from the Ethics Committee of Nanjing Normal University (NNU202310030). The research analyzed the data and constructed theories, employing strategies such as coding, constant comparison, and theoretical sampling. The study found that: firstly, ethnic inter-embedded communities exhibit characteristics of diversity, including ethnic diversity, cultural diversity, and linguistic diversity. Diversity has positive functions, including increased opportunities for contact, promoting self-expansion, and increasing happiness; negative functions of diversity include highlighting ethnic differences, causing ethnic conflicts, and reminding of ethnic boundaries. Secondly, individuals typically engage in interactions within the community using active embedding and passive embedding strategies. Active embedding strategies include maintaining openness, focusing on similarities, and pro-diversity beliefs, which can increase external group identification, intergroup relational identity, and promote ethnic integration. Individuals using passive embedding strategies tend to focus on ethnic stereotypes, perceive stigmatization of their own ethnic group, and adopt an authoritarian-oriented approach to interactions, leading to a perception of more identity threats and ultimately rejecting ethnic integration. Thirdly, the commonality of the Chinese nation is reflected in the 56 ethnic groups as an "identity community" and "interest community," and both active and passive embedding paths affect individual understanding of the commonality of the Chinese nation. Finally, community work and environment can influence the embedding process. The research constructed a social psychological process and mechanism model for solidifying sense of the Chinese national community in ethnic inter-embedded communities. Based on this theoretical model, future research can conduct more micro-level psychological mechanism tests and intervention studies to enhance Chinese national cohesion.

Keywords: diversity, sense of the chinese national community, ethnic inter-embedded communities, ethnic group

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Authors: C. P. Providakis, G. M. Angeli, M. J. Favvata, N. A. Papadopoulos, C. E. Chalioris, C. G. Karayannis

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An effort for the detection of damages in the reinforcement bars of reinforced concrete members using PZTs is presented. The damage can be the result of excessive elongation of the steel bar due to steel yielding or due to local steel corrosion. In both cases the damage is simulated by considering reduced diameter of the rebar along the damaged part of its length. An integration approach based on both electromechanical admittance methodology and guided wave propagation technique is used to evaluate the artificial damage on the examined longitudinal steel bar. Two actuator PZTs and a sensor PZT are considered to be bonded on the examined steel bar. The admittance of the Sensor PZT is calculated using COMSOL 3.4a. Fast Furrier Transformation for a better evaluation of the results is employed. An effort for the quantification of the damage detection using the root mean square deviation (RMSD) between the healthy condition and damage state of the sensor PZT is attempted. The numerical value of the RSMD yields a level for the difference between the healthy and the damaged admittance computation indicating this way the presence of damage in the structure. Experimental measurements are also presented.

Keywords: concrete reinforcement, damage detection, electromechanical admittance, experimental measurements, finite element method, guided waves, PZT

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Authors: Stacey Herzog, Mitchell McCleary, Istvan Kovacs

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Purpose: Maximal strength and maximal power are key athletic abilities in many sports disciplines. In recent years, velocity-based training (VBT) with a relatively high 75-85% 1RM resistance has been popularized in preparation for powerlifting and various other sports. The purpose of this study was to discover differences between beginner/intermediate and advanced lifters’ push/press performances after a heavy resistance-based BP training program. Methods: A six-week, three-workouts per week program was administered to 52 young, physically active adults (age: 22.4±5.1; 12 female). The majority of the participants (84.6%) had prior experience in bench pressing. Typical workouts began with BP using 75-95% 1RM in the 1-5 repetition range. The sets in the lower part of the range (75-80% 1RM) were performed with velocity-focus as well. The BP sets were followed by seated dumbbell presses and six additional upper-body assistance exercises. Pre- and post-tests were conducted on five test exercises: one-repetition maximum BP (1RM), calculated relative strength index: BP/BW (RSI), four-repetition maximal-effort dynamic BP for peak concentric velocity with 80% 1RM (4RV), 4-repetition ballistic pushups (BPU) for height (4PU), and seated medicine ball toss for distance (MBT). For analytic purposes, the participant group was divided into two subgroups: self-indicated beginner or intermediate initial resistance training status (BITS) [n=21, age: 21.9±3.6; 10 female] and advanced initial resistance training status (ATS) [n=31, age: 22.7±5.9; 2 female]. Pre- and post-test results were compared within subgroups. Results: Paired-sample t-tests indicated significant within-group improvements in all five test exercises in both groups (p < 0.05). BITS improved 18.1 lbs. (13.0%) in 1RM, 0.099 (12.8%) in RSI, 0.133 m/s (23.3%) in 4RV, 1.55 in. (27.1%) in BPU, and 1.00 ft. (5.8%) in MBT, while the ATS group improved 13.2 lbs. (5.7%) in 1RM, 0.071 (5.8%) in RSI, 0.051 m/s (9.1%) in 4RV, 1.20 in. (13.7%) in BPU, and 1.15 ft. (5.5%) in MBT. Conclusion: While the two training groups had different initial resistance training backgrounds, both showed significant improvements in all test exercises. As expected, the beginner/intermediate group displayed better relative improvements in four of the five test exercises. However, the medicine ball toss, which had the lightest resistance among the tests, showed similar relative improvements between the two groups. These findings relate to two important training principles: specificity and transfer. The ATS group had more specific experiences with heavy-resistance BP. Therefore, fewer improvements were detected in their test performances with heavy resistances. On the other hand, while the heavy resistance-based training transferred to increased power outcomes in light-resistance power exercises, the difference in the rate of improvement between the two groups disappeared. Practical applications: Based on initial training status, S&C coaches should expect different performance gains in maximal strength training-specific test exercises. However, the transfer from maximal strength to a non-training-specific performance category along the F-v curve continuum (i.e., light resistance and high velocity) might not depend on initial training status.

Keywords: exercise, power, resistance training, strength

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Authors: Aishatu Ibrahim Birma, Aminu Tukur, Abdulkarim Abbass Gora

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Machine translation plays a vital role in the Field of Natural Language Processing (NLP), breaking down language barriers and enabling communication across diverse communities. In the context of Hausa, a widely spoken language in West Africa, mainly in Nigeria, effective translation systems are essential for enabling seamless communication and promoting cultural exchange. However, due to the unique linguistic characteristics of Hausa, accurate translation remains a challenging task. The research proposes an approach to improving the machine learning translation of Hausa by integrating Named Entity Recognition (NER) techniques. Named entities, such as person names, locations, organizations, and dates, are critical components of a language's structure and meaning. Incorporating NER into the translation process can enhance the quality and accuracy of translations by preserving the integrity of named entities and also maintaining consistency in translating entities (e.g., proper names), and addressing the cultural references specific to Hausa. The NER will be incorporated into Neural Machine Translation (NMT) for the Hausa to English Translation.

Keywords: machine translation, natural language processing (NLP), named entity recognition (NER), neural machine translation (NMT)

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Authors: Dhanesh Sing Das, Bharat Tadikonda Venkata

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Collapsible soils undergo significant volume reduction upon wetting under the pre-existing mechanically applied normal stress (inundation pressure). These soils exhibit a very high strength in air-dried conditions and can carry up to a considerable magnitude of normal stress without undergoing significant volume change. The soil strength is, however, lost upon saturation and results in a sudden collapse of the soil structure under the existing mechanical stress condition. The intrusion of water into the dry deposits of such soil causes ground subsidence leading to damages in the overlying buildings/structures. A study on the wetting-induced volume change behavior of collapsible soils is essential in dealing with the ground subsidence problems in various geotechnical engineering practices. The collapse of loosely compacted Kaolin soil upon wetting under various inundation pressures has been reported in recent studies. The collapse in the Kaolin soil is attributed to the alteration in the soil particle-particle association (fabric) resulting due to the changes in the various inter-particle (microscale) forces induced by the water saturation. The inundation pressure plays a significant role in the fabric evolution during the wetting process, thus controls the collapse potential of the compacted soil. A microstructural study is useful to understand the collapse mechanisms at various pore-fabric levels under different inundation pressure. Kaolin soil compacted to a dry density of 1.25 g/cc was used in this work to study the wetting-induced volume change behavior under different inundation pressures in the range of 10-1600 kPa. The compacted specimen of Kaolin soil exhibited a consistent collapse under all the studied inundation pressure. The collapse potential was observed to be increasing with an increase in the inundation pressure up to a maximum value of 13.85% under 800 kPa and then decreased to 11.7% under 1600 kPa. Microstructural analysis was carried out based on the fabric images and the pore size distributions (PSDs) obtained from FESEM analysis and mercury intrusion porosimetry (MIP), respectively. The PSDs and the soil fabric images of ‘as-compacted’ specimen and post-collapse specimen under 400 kPa were analyzed to understand the changes in the soil fabric and pores due to wetting. The pore size density curve for the post-collapse specimen was found to be on the finer side with respect to the ‘as-compacted’ specimen, indicating the reduction of the larger pores during the collapse. The inter-aggregate pores in the range of 0.1-0.5μm were identified as the major contributing pore size classes to the macroscopic volume change. Wetting under an inundation pressure results in the reduction of these pore sizes and lead to an increase in the finer pore sizes. The magnitude of inundation pressure influences the amount of reduction of these pores during the wetting process. The collapse potential was directly related to the degree of reduction in the pore volume contributed by these pore sizes.

Keywords: collapse behavior, inundation pressure, kaolin, microstructure

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Authors: Zabihur Rahman

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In present day we see in our surroundings and in different societies of the world an uprising approach of understanding Quran without the help of Hadith and Sunnah. As they believe that ‘Quran is sufficient for our guidance’. They do not give any preference to Prophetic traditions (Hadith and Sunnah), to understand or realize the actual meaning and purpose of the reveling of Quranic verses. Based on the afore mentioned idea we are going to pin point an analytical and inductive study of tafsir Ahkâm-ul Qu’ran by: Ibn-ul Arabi al-Mâliki. In this study we are trying to show the importance of Hadith and Sunnah in interpretation and understanding of Quran by presenting various examples from tafsir Ahkâm-ul Quran. This book is for being an important source in the relative filed of Ahkam-ul Quran we are going to highlight the method of Ibn-ul Arabi in dealing with Quranic verses in the light of Hadith. Furthermore, the impact of quoting different types of hadith in Tefsir is also taken into account. Besides, while citing these Prophetic traditions it is also inevitable to kept in view the sciences of hadith and its application on the context in order to orientate the proper meaning. The study also includes the scrutiny of these narrations by their chain of narrators and text to ensure the perfection of these prophetic traditions. So that, a person can have accesses to the righteous understanding and interpretation of the Holy Quran.

Keywords: Hadith, interpretation, narrators, verses

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Authors: Ana B. Carrera-Aguilar , Rodrigo T. Sepulveda-Hirose, Diego A. Bernal-Gurrusquieta, Francisco A. Ramirez Casas

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In recent years, Mexico City has presented high levels of atmospheric pollution; the city is also an example of inequality and poverty that impact metropolitan areas around the world. This combination of social and economic exclusion, coupled with high levels of pollution evidence the loss of well-being among the population. The effect of air pollution on quality of life is an area of study that has been overlooked. The purpose of this study is to find relations between air quality and quality of life in Mexico City through statistical analysis of a regression model and principal component analysis of several atmospheric contaminants (CO, NO₂, ozone, particulate matter, SO₂) and well-being indexes (HDI, poverty, inequality, life expectancy and health care index). The data correspond to official information (INEGI, SEDEMA, and CEPAL) for 2000-2018. Preliminary results show that the Human Development Index (HDI) is affected by the impacts of pollution, and its indicators are reduced in the presence of contaminants. It is necessary to promote a strong interest in this issue in Mexico City. Otherwise, the problem will not only remain but will worsen affecting those who have less and the population well-being in a generalized way.

Keywords: air quality, Mexico City, quality of life, statistics

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Authors: Jianyong Xue, Olivier L. Georgeon, Salima Hassas

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During the initial phase of cognitive development, infants exhibit amazing abilities to generate novel behaviors in unfamiliar situations, and explore actively to learn the best while lacking extrinsic rewards from the environment. These abilities set them apart from even the most advanced autonomous robots. This work seeks to contribute to understand and replicate some of these abilities. We propose the Bottom-up hiErarchical sequential Learning algorithm with Constructivist pAradigm (BEL-CA) to design agents capable of learning autonomously and continuously through interactions. The algorithm implements no assumption about the semantics of input and output data. It does not rely upon a model of the world given a priori in the form of a set of states and transitions as well. Besides, we propose a toolkit to analyze the learning process at run time called GAIT (Generating and Analyzing Interaction Traces). We use GAIT to report and explain the detailed learning process and the structured behaviors that the agent has learned on each decision making. We report an experiment in which the agent learned to successfully interact with its environment and to avoid unfavorable interactions using regularities discovered through interaction.

Keywords: cognitive development, constructivist learning, hierarchical sequential learning, self-adaptation

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Authors: Jameela Ali Alkrimi, Abdul Rahim Ahmad, Azizah Suliman, Loay E. George

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Red blood cells (RBCs) are among the most commonly and intensively studied type of blood cells in cell biology. The lack of RBCs is a condition characterized by lower than normal hemoglobin level; this condition is referred to as 'anemia'. In this study, a software was developed to isolate RBCs by using a machine learning approach to classify anemic RBCs in microscopic images. Several features of RBCs were extracted using image processing algorithms, including principal component analysis (PCA). With the proposed method, RBCs were isolated in 34 second from an image containing 18 to 27 cells. We also proposed that PCA could be performed to increase the speed and efficiency of classification. Our classifier algorithm yielded accuracy rates of 100%, 99.99%, and 96.50% for K-nearest neighbor (K-NN) algorithm, support vector machine (SVM), and neural network ANN, respectively. Classification was evaluated in highly sensitivity, specificity, and kappa statistical parameters. In conclusion, the classification results were obtained for a short time period with more efficient when PCA was used.

Keywords: red blood cells, pre-processing image algorithms, classification algorithms, principal component analysis PCA, confusion matrix, kappa statistical parameters, ROC

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Authors: Sundaram Arulmozhiraja, Kanade Shimizu, Yuta Yamamoto, Satoshi Ichikawa, Maenaka Katsumi, Hiroaki Tokiwa

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Drug discovery is shifting from small molecule based drugs targeting local active site to middle molecules (MM) targeting large, flat, and groove-shaped binding sites, for example, protein-protein interface because at least half of all targets assumed to be involved in human disease have been classified as “difficult to drug” with traditional small molecules. Hence, MMs such as peptides, natural products, glycans, nucleic acids with various high potent bioactivities become important targets for drug discovery programs in the recent years as they could be used for ‘undruggable” intracellular targets. Cell membrane permeability is one of the key properties of pharmacodynamically active MM drug compounds and so evaluating this property for the potential MMs is crucial. Computational prediction for cell membrane permeability of molecules is very challenging; however, recent advancement in the molecular dynamics simulations help to solve this issue partially. It is expected that MMs with high membrane permeability will enable drug discovery research to expand its borders towards intracellular targets. Further to understand the chemistry behind the permeability of MMs, it is necessary to investigate their conformational changes during the permeation through membrane and for that their interactions with the membrane field should be studied reliably because these interactions involve various non-bonding interactions such as hydrogen bonding, -stacking, charge-transfer, polarization dispersion, and non-classical weak hydrogen bonding. Therefore, parameters-based classical mechanics calculations are hardly sufficient to investigate these interactions rather, quantum mechanical (QM) calculations are essential. Fragment molecular orbital (FMO) method could be used for such purpose as it performs ab initio QM calculations by dividing the system into fragments. The present work is aimed to study the cell permeability of middle molecules using molecular dynamics simulations and FMO-QM calculations. For this purpose, a natural compound syringolin and its analogues were considered in this study. Molecular simulations were performed using NAMD and Gromacs programs with CHARMM force field. FMO calculations were performed using the PAICS program at the correlated Resolution-of-Identity second-order Moller Plesset (RI-MP2) level with the cc-pVDZ basis set. The simulations clearly show that while syringolin could not permeate the membrane, its selected analogues go through the medium in nano second scale. These correlates well with the existing experimental evidences that these syringolin analogues are membrane-permeable compounds. Further analyses indicate that intramolecular -stacking interactions in the syringolin analogues influenced their permeability positively. These intramolecular interactions reduce the polarity of these analogues so that they could permeate the lipophilic cell membrane. Conclusively, the cell membrane permeability of various middle molecules with potent bioactivities is efficiently studied using molecular dynamics simulations. Insight of this behavior is thoroughly investigated using FMO-QM calculations. Results obtained in the present study indicate that non-bonding intramolecular interactions such as hydrogen-bonding and -stacking along with the conformational flexibility of MMs are essential for amicable membrane permeation. These results are interesting and are nice example for this theoretical calculation approach that could be used to study the permeability of other middle molecules. This work was supported by Japan Agency for Medical Research and Development (AMED) under Grant Number 18ae0101047.

Keywords: fragment molecular orbital theory, membrane permeability, middle molecules, molecular dynamics simulation

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