Search results for: actionable pattern discovery

Authors: Jiahao Tian, Michael D. Porter

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Law enforcement agencies are tasked with crime prevention and crime reduction under limited resources. Having an accurate temporal estimate of the crime rate would be valuable to achieve such a goal. However, estimation is usually complicated by the interval-censored nature of crime data. We cast the problem of intensity estimation as a Poisson regression using an EM algorithm to estimate the parameters. Two special penalties are added that provide smoothness over the time of day and day of the week. This approach presented here provides accurate intensity estimates and can also uncover day-of-week clusters that share the same intensity patterns. Anticipating where and when crimes might occur is a key element to successful policing strategies. However, this task is complicated by the presence of interval-censored data. The censored data refers to the type of data that the event time is only known to lie within an interval instead of being observed exactly. This type of data is prevailing in the field of criminology because of the absence of victims for certain types of crime. Despite its importance, the research in temporal analysis of crime has lagged behind the spatial component. Inspired by the success of solving crime-related problems with a statistical approach, we propose a statistical model for the temporal intensity estimation of crime with censored data. The model is built on Poisson regression and has special penalty terms added to the likelihood. An EM algorithm was derived to obtain maximum likelihood estimates, and the resulting model shows superior performance to the competing model. Our research is in line with the smart policing initiative (SPI) proposed by the Bureau Justice of Assistance (BJA) as an effort to support law enforcement agencies in building evidence-based, data-driven law enforcement tactics. The goal is to identify strategic approaches that are effective in crime prevention and reduction. In our case, we allow agencies to deploy their resources for a relatively short period of time to achieve the maximum level of crime reduction. By analyzing a particular area within cities where data are available, our proposed approach could not only provide an accurate estimate of intensities for the time unit considered but a time-variation crime incidence pattern. Both will be helpful in the allocation of limited resources by either improving the existing patrol plan with the understanding of the discovery of the day of week cluster or supporting extra resources available.

Keywords: cluster detection, EM algorithm, interval censoring, intensity estimation

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Authors: Helena Maragou

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Introducing Toni Morrison’s fiction to a classroom overseas entails a significant pedagogical investment, from monitoring students’ uncertain journey through Morrison’s shifty semantics to filling in the gaps of cultural knowledge and understanding for the students to be able to relate text to context. A rewarding process, as Morrison’s works present a tremendous opportunity for transnational dialogue, an opportunity that hinges upon Toni Morrison’s bringing to the fore the untold and unspeakable lives of racial ‘Others’, but also, crucially, upon her broader critique of Western ideological hegemony. This critique is a fundamental aspect of Toni Morrison’s politics and one that appeals to young readers of Toni Morrison in Greece at a time when the questioning of institutions and ideological traditions is precipitated by regional and global change. It is more or less self-evident that to help a class of international students get aboard a Morrison novel, an instructor should begin by providing them with cultural context. These days, students’ exposure to Hollywood representations of the African American past and present, as well as the use of documentaries, photography, music videos, etc., as supplementary class material, provide a starting point, a workable historical and cultural framework for textual comprehension. The true challenge, however, lies ahead: it is one thing for students to intellectually grasp the historical hardships and traumas of Morrison’s characters and to even engage in aesthetic appreciation of Morrison’s writing; quite another to relate to her works as articulations of experiences akin to their own. The great challenge, then, is in facilitating students’ discovery of the universal Morrison, the author who speaks across cultures while voicing the untold tales of her own people; this process of discovery entails, on a pedagogical level, that students be guided through the works’ historical context, to plunge into the intricacies of Morrison’s discourse, itself an elaborate linguistic booby trap, so as to be finally brought to reconsider their own historical experiences using the lens of Morrison’s fiction. The paper will be based on experience of teaching a Toni Morrison seminar to a class of Greek students at the American College of Greece and will draw from students’ exposure and responses to Toni Morrison’s “Nobel Prize Lecture,” as well as her novels Song of Solomon and Home.

Keywords: toni morrison, international classroom, pedagogy, African American literature

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Authors: Sifeddine Abderrahmani, Sonia Bouafia

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The finite element method is the most practical tool for the analysis of structures, whatever the geometrical shape and behavior. It is extensively used in many high-tech industries, such as civil or military engineering, for the modeling of bridges, motor bodies, fuselages, and airplane wings. Additionally, experience demonstrates that engineers like modeling their structures using the most basic finite elements. Numerous models of finite elements may be utilized in the numerical analysis depending on the interpolation field that is selected, and it is generally known that convergence to the proper value will occur considerably more quickly with a good displacement pattern than with a poor pattern, saving computation time. The method for creating finite elements using the strain approach (S.B.A.) is presented in this presentation. When the results are compared with those provided by equivalent displacement-based elements, having the same total number of degrees of freedom, an excellent convergence can be obtained through some application and validation tests using recently developed membrane elements, plate bending elements, and flat shell elements. The effectiveness and performance of the strain-based finite elements in modeling structures are proven by the findings for deflections and stresses.

Keywords: finite elements, plate bending, strain approach, displacement formulation, shell element

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Authors: Vanessa Cho, Janet Hsiao, Nigel King, Robert Anthonappa

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Background: The personal protective equipment (PPE) requirements for health care workers (HCWs) have changed significantly during the COVID-19 pandemic. Aim: To ascertain, using eye-tracking technology, what children notice the most when seeing HCWs in various PPE. Design: A Tobii nano pro-eye-tracking camera tracked 156 children's visual attention while they viewed photographs of HCWs in various PPEs. Eye Movement analysis with Hidden Markov Models (EMHMM) was employed to analyse 624 recordings using two approaches, namely (i) data-driven where children's fixation determined the regions of interest (ROIs), and (ii) fixed ROIs where the investigators predefined the ROIs. Results: Two significant eye movement patterns, namely distributed(85.2%) and selective(14.7%), were identified(P<0.05). Most children fixated primarily on the face regardless of the different PPEs. Children fixated equally on all PPE images in the distributed pattern, while a strong preference for unmasked faces was evident in the selective pattern (P<0.01). Conclusion: Children as young as 2.5 years used a top-down visual search behaviour and demonstrated their face processing ability. Most children did not show a strong visual preference for a specific PPE, while a minority preferred PPE with distinct facial features, namely without masks and loupes.

Keywords: COVID-19, PPE, dentistry, pediatric

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Authors: Billel Kenidra, Mohamed Benmohammed

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Data mining technique used in the field of clustering is a subject of active research and assists in biological pattern recognition and extraction of new knowledge from raw data. Clustering means the act of partitioning an unlabeled dataset into groups of similar objects. Each group, called a cluster, consists of objects that are similar between themselves and dissimilar to objects of other groups. Several clustering methods are based on partitional clustering. This category attempts to directly decompose the dataset into a set of disjoint clusters leading to an integer number of clusters that optimizes a given criterion function. The criterion function may emphasize a local or a global structure of the data, and its optimization is an iterative relocation procedure. The K-Means algorithm is one of the most widely used partitional clustering techniques. Since K-Means is extremely sensitive to the initial choice of centers and a poor choice of centers may lead to a local optimum that is quite inferior to the global optimum, we propose a strategy to initiate K-Means centers. The improved K-Means algorithm is compared with the original K-Means, and the results prove how the efficiency has been significantly improved.

Keywords: microarray data mining, biological pattern recognition, partitional clustering, k-means algorithm, centroid initialization

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Authors: Libo Jiang, Huan Li, Rongling Wu

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Ordinary differentiation equations (ODE) have proven to be powerful for reconstructing precise and informative gene regulatory networks (GRNs) from dynamic gene expression data. However, joint modeling and analysis of all genes, essential for the systematical characterization of genetic interactions, are challenging due to high dimensionality and a complex pattern of genetic regulation including activation, repression, and antitermination. Here, we address these challenges by unifying variable selection and game theory through ODE. Each gene within a GRN is co-expressed with its partner genes in a way like a game of multiple players, each of which tends to choose an optimal strategy to maximize its “fitness” across the whole network. Based on this unifying theory, we designed and conducted a real experiment to infer salt tolerance-related GRNs for Euphrates poplar, a hero tree that can grow in the saline desert. The pattern and magnitude of interactions between several hub genes within these GRNs were found to determine the capacity of Euphrates poplar to resist to saline stress.

Keywords: gene regulatory network, ordinary differential equation, game theory, LASSO, saline resistance

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Authors: Helena Macedo, Larissa Tomaz, Levi Guimarães, Luís Cerqueira-Pinto, José Dinis-Carvalho

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In the context of retail logistics, the pursuit of operational efficiency and cost optimization involves a rigorous distinction between value-added and non-value-added activities. In today's competitive market, optimizing efficiency and reducing operational costs are paramount for retail businesses. This research paper focuses on the development of a classification model adapted to the retail sector, specifically examining internal logistics processes. Based on a comprehensive analysis conducted in a retail supermarket located in the north of Portugal, which covered various aspects of internal retail logistics, this study questions the concept of value and the definition of wastes traditionally applied in a manufacturing context and proposes a new way to assess activities in the context of internal logistics. This study combines quantitative data analysis with qualitative evaluations. The proposed classification model offers a systematic approach to categorize operations within the retail logistics chain, providing actionable insights for decision-makers to streamline processes, enhance productivity, and allocate resources more effectively. This model contributes not only to academic discourse but also serves as a practical tool for retail businesses, aiding in the enhancement of their internal logistics dynamics.

Keywords: lean retail, lean logisitcs, retail logistics, value-added and non-value-added

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Authors: Sanchari Mukhopadhyay

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Today, almost the entire realm of human activities are becoming increasingly dependent on the power of information, where through ICTs it is now possible to cater distances and avail various services at a few clicks. In principle, ICTs are thus expected to blur location-specific differences and affiliations of development and bring in an inclusive society at the wake of globalization. However, eventually researchers and policy analysts realized that ICTs are also generating inequality in spite of the hope for an integrated world and widespread social well-being. Regarding this unevenness, location plays a major role as often ICT development is seen to be concentrated into pockets, leaving behind large tracks as underprivileged. Thus, understanding the spatial pattern of ICT development and distribution is significant in relation to exploring the extent to which ICTs are fulfilling the promises or reassuring the existing divisions. In addition, it is also profoundly crucial to investigate how regions are connecting and competing both locally and globally. The focus of the research paper is to evaluate the spatial structure of ICT led development in India. Thereby, it attempts to understand the state level (four selected states) pattern of ICT penetration, the pattern of diffusion across districts with respect to large urban centres and the rural-urban disparity of technology adoption. It also tries to assess the changes in access dynamisms of ICTs as one move away from a large metropolitan city towards the periphery. In brief, the analysis investigates into the tendency towards the uneven growth of development through the identification of the core areas of ICT advancement within the country and its diffusion from the core to the periphery. In order to assess the level of ICT development and rural-urban disparity across the districts of selected states, two indices named ICT Development Index and Rural-Urban Digital Divide Index have been constructed. The study mostly encompasses the latest Census (2011) of the country and TRAI (Telecom Regulatory Authority of India) in some cases.

Keywords: ICT development, diffusion, core-periphery, digital divide

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Authors: Khries Sawsan

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the phenomenon of urbanization is considered as one of the most important tourism resources that differ from one country to another and from one region to another in the same country. Our concern in tourism accommodation is explained by the fact that their location is directly related to the movement to tourist sites .Besides, these constructions comport security considered as the most important motivation for tourists in their choice of any destination. Hotels are the most representative expression of tourism. This is due to their physical prominence in the landscape and being the sole urban component totally unique to tourism. This study sheds light on the impact of tourism development on the spatial pattern in Jordan. It describes the linkages between existing tourism development policies and the spatial development patterns that have occurred as a result throughout Jordan, particularly looking at the impact that tourism has had on the physical environment of major tourism destinations. It puts an illustrative plan of the impact of the augmentation of tourism accommodations in Jordan in the past 40 years ago. The findings of this study help us to understand better the operation of Jordan’ dynamic changes in the location An intensive analysis is then applied on a representative case study in three regions: Amman, Petra and Aqaba. The study proceeds from an historical perspective to, show the evolution of the current development patterns an increase of tourism’s impact on spatial, in the presence of factors as political and economic stability, is expected.

Keywords: spatial patterns, urbanisation, spatial transformations, tourism planning, Jordan

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Authors: Joshua Harrell, Gideon Osei Bonsu, Susan Garza, Clarence Conner, Da’Neisha Harris, Emma Bukoswki, Zohreh Safari

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The Social Vulnerability Index (SVI) stands as a pivotal tool for gauging community resilience amidst diverse stressors, including pandemics like COVID-19. This paper synthesizes recent research and underscores the significance of SVI in elucidating the differential impacts of crises on communities. Drawing on studies by Fox et al. (2023) and Mah et al. (2023), we delve into the application of SVI alongside emerging data sources to uncover nuanced insights into community vulnerability. Specifically, we explore the utilization of SVI in conjunction with mobility data from platforms like SafeGraph to probe the intricate relationship between social vulnerability and mobility dynamics during the COVID-19 pandemic. By leveraging 16 community variables derived from the American Community Survey, including socioeconomic status and demographic characteristics, SVI offers actionable intelligence for guiding targeted interventions and resource allocation. Building upon recent advancements, this paper contributes to the discourse on harnessing AI techniques to mitigate health disparities and fortify public health resilience in the face of pandemics and other crises.

Keywords: social vulnerability index, mobility dynamics, data analytics, health equity, pandemic preparedness, targeted interventions, data integration

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Authors: Bang-Fuh Chen, Chih-Chun Chu

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The flow induced cylinder vibration or earthquake-induced cylinder motion are moving in an arbitrary direction with time. The phenomenon of flow across cylinder is highly nonlinear and a linear-superposition of flow pattern across separated oscillating direction of cylinder motion is not valid to obtain the flow pattern across a cylinder oscillating in multiple directions. A novel finite difference scheme is developed to simulate the viscous flow across an arbitrary moving circular cylinder and we call this a complete 2D (two-dimensional) flow-cylinder interaction. That is, the cylinder is simultaneously oscillating in x- and y- directions. The time-dependent domain and meshes associated with the moving cylinder are mapped to a fixed computational domain and meshes, which are time independent. The numerical results are validated by several bench mark studies. Several examples are introduced including flow across steam-wise, transverse oscillating cylinder and flow across rotating cylinder and flow across arbitrary moving cylinder. The Morison’s formula can not describe the complex interaction phenomenon between cross flow and oscillating circular cylinder. And the completed 2D computational fluid dynamic analysis should be made to obtain the correct hydrodynamic force acting on the cylinder.

Keywords: 2D cylinder, finite-difference method, flow-cylinder interaction, flow induced vibration

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Authors: Emmanuel Olamijuwon

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Despite laws against child marriage - a violation against child rights, the practice remains widespread in sub-Saharan Africa and globally partly because of persistent poverty, gender inequality, protection and the need to reinforce family ties. Using pooled data from the recent demographic and health surveys of 20-sub-Saharan African countries with a regional representative sample of 36,943 girls under 18 years, this study explores the prevalence, pattern and infant mortality implications of this marriage type while also examining its regional variations. Indications from the study are that child marriage is still very high in the region with variations above one-tenth in West, Central and Southern Africa regions except in the East African region where only about 7% of children under 18 were already married. Preliminary findings also suggest that about one-in-ten infant deaths were to child brides many of whom were residing in poor households, rural residence, unemployed and have less than secondary education. Based on these findings, it is, therefore, important that government of African countries addresses critical issues through increased policies towards increasing enrollment of girl children in schools as many of these girls are not likely to have any economic benefit to the region if the observed pattern continues.

Keywords: child marriage, infant mortality, Africa, child brides

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Authors: Arnab Mondal, Sanjeev Kumar Sharma, Ranjit Kumar Upadhyay

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We study the spatiotemporal dynamics of a neuronal cable. The processes of one- dimensional (1D) and 2D diffusion are considered for a single variable, which is the membrane voltage, i.e., membrane voltage diffusively interacts for spatiotemporal pattern formalism. The recovery and other variables interact through the membrane voltage. A 3D Leech-Heart (LH) model is introduced to investigate the nonlinear responses of an excitable neuronal cable. The deterministic LH model shows different types of firing properties. We explore the parameter space of the uncoupled LH model and based on the bifurcation diagram, considering v_k2_ashift as a bifurcation parameter, we analyze the 1D diffusion dynamics in three regimes: bursting, regular spiking, and a quiescent state. Depending on parameters, it is shown that the diffusive system may generate regular and irregular bursting or spiking behavior. Further, it is explored a 2D diffusion acting on the membrane voltage, where different types of patterns can be observed. The results show that the LH neurons with different firing characteristics depending on the control parameters participate in a collective behavior of an information processing system that depends on the overall network.

Keywords: bifurcation, pattern formation, spatio-temporal dynamics, stability analysis

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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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Authors: Bhaskar Chakravorti, Christopher Tunnard, Ravi Shankar Chaturvedi

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This report introduces the Digital Evolution Index (DEI) as a way to gauge the transformation of economies in the advanced and developing world from traditional brick-and-mortar to digitally enabled. The DEI measures the digital trajectories of 50 countries to provide actionable, data-informed insights for businesses, investors and policymakers. Created by The Fletcher School, in collaboration with MasterCard Worldwide and DataCash, the DEI analyzes the key underlying drivers and barriers that govern a country’s evolution into a digital economy: Demand, Supply, Institutional Environment and Innovation. A longitudinal analysis of these four drivers during the years 2008 to 2013 reveals both the current state of a country’s digital economy, as well as changes over time. Combining these two measures allows us to assign each country to one of four Trajectory Zones: • Stand Out countries have shown high levels of digital development in the past and continue to remain on an upward trajectory. • Stall Out countries have achieved a high level of evolution in the past but are losing momentum and risk falling behind. • Break Out countries have the potential to develop strong digital economies. Though their overall score is still low, they are moving upward and are poised to become Stand Out countries in the future. • Watch Out countries face significant opportunities and challenges, with low scores on both current level and upward motion of their DEI. Some may be able to overcome limitations with clever innovations and stopgap measures, while others seem to be stuck.

Keywords: e-commerce, digital evolution, digital commerce ecosystems, e-consumer

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Authors: Hamed Najafi, Ghasem Nikjou

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Nowadays, there is an increasing attention to the resources scarcity issues. Because of failure in present patterns in the field of the allocation of exhaustible resources between generations and the challenges related to economic justice supply, it is supposed, to present a pattern from the Islamic perspective in this essay. By using content analysis of religious texts, we conclude that governments should remove the gap which is exists between the per capita income of the poor and their minimum consumption (necessary consumption). In order to preserve the exhaustible resources for poor people) not for all), between all generations, government should invest exhaustible resources on endless resources according to Hartwick’s criteria and should spend these benefits for poor people. But, if benefits did not cover the gap between minimum consumption and per capita income of poor levels in one generation, in this case, the government is responsible for covering this gap through the direct consumption of exhaustible resources. For an exact answer to this question, ‘how much of exhaustible resources should expense to maintain justice between generations?’ The theoretical and mathematical modeling has been used and proper function has been provided. The consumption pattern is presented for economic policy makers in Muslim countries, and non-Muslim even, it can be useful.

Keywords: exhaustible resources, Islamic justice, intergenerational justice, distribution of resources, Hartwick criteria

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Authors: J. Julius Adebayo

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The objective of this paper is to assess the agro-climatic condition of Ibadan in the rain forest ecological zone of Nigeria, using rainfall pattern and temperature between 1978-2018. Data on rainfall and temperature in Ibadan, Oyo State for a period of 40 years were obtained from Meteorological Section of Forestry Research Institute of Nigeria, Ibadan and Oyo State Meteorology Centre. Time series analysis was employed to analyze the data. The trend revealed that rainfall is decreasing slowly and temperature is averagely increasing year after year. The model for rainfall and temperature are Yₜ = 1454.11-8*t and Yₜ = 31.5995 + 2.54 E-02*t respectively, where t is the time. On this basis, a forecast of 20 years (2019-2038) was generated, and the results showed a further downward trend on rainfall and upward trend in temperature, this indicates persistence rainfall shortage and very hot weather for agricultural practices in the southwest rain forest ecological zone. Suggestions on possible solutions to avert climate change crisis and also promote climate-smart agriculture for sustainable food and nutrition security were also discussed.

Keywords: climate change, rainfall pattern, temperature, time series analysis, food and nutrition security

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Authors: Amartya Hatua, Trung Nguyen, Andrew Sung

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In this paper, we study the information diffusion process on Twitter as a multivariate time series problem. Our model concerns three measures (volume, network influence, and sentiment of tweets) based on 10 features, and we collected 27 million tweets to build our information diffusion time series dataset for analysis. Then, different time series clustering techniques with Dynamic Time Warping (DTW) distance were used to identify different patterns of information diffusion. Finally, we built the information diffusion prediction models for new hashtags which comprise two phrases: The first phrase is recognizing the pattern using k-NN with DTW distance; the second phrase is building the forecasting model using the traditional Autoregressive Integrated Moving Average (ARIMA) model and the non-linear recurrent neural network of Long Short-Term Memory (LSTM). Preliminary results of performance evaluation between different forecasting models show that LSTM with clustering information notably outperforms other models. Therefore, our approach can be applied in real-world applications to analyze and predict the information diffusion characteristics of selected topics or memes (hashtags) in Twitter.

Keywords: ARIMA, DTW, information diffusion, LSTM, RNN, time series clustering, time series forecasting, Twitter

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Authors: Ugo Rovigatti

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Neuroblastoma (NBL) has epitomized for at least 40 years our understanding of cancer cellular and molecular biology and its potential applications to novel therapeutic strategies. This includes the discovery of the very first oncogene aberrations and tumorigenesis suppression by differentiation in the 80s; the potential role of suppressor genes in the 90s; the relevance of immunotherapy in the millennium first, and the discovery of additional mutations by NGS technology in the millennium second decade. Similar discoveries were achieved in the majority of human cancers, and similar therapeutic interventions were obtained subsequently to NBL discoveries. Unfortunately, targeted therapies suggested by specific mutations (such as MYCN amplification –MNA- present in ¼ or 1/5 of cases) have not elicited therapeutic successes in aggressive NBL, where the prognosis is still dismal. The reasons appear to be linked to Tumor Heterogeneity, which is particularly evident in NBL but also a clear hallmark of aggressive human cancers generally. The new avenue of cancer immunotherapy (CIT) provided new hopes for cancer patients, but we still ignore the cellular or molecular targets. CIT is emblematic of high-risk disease (HR-NBL) since the mentioned GD2 passive immunotherapy is still providing better survival. We recently critically reviewed and evaluated the literature depicting the genomic landscapes of HR-NBL, coming to the qualified conclusion that among hundreds of affected genes, potential targets, or chromosomal sites, none correlated with anti-GD2 sensitivity. A better explanation is provided by the Micro-Foci inducing Virus (MFV) model, which predicts that neuroblasts infection with the MFV, an RNA virus isolated from a cancer-cluster (space-time association) of HR-NBL cases, elicits the appearance of MNA and additional genomic aberrations with mechanisms resembling chromothripsis. Neuroblasts infected with low titers of MFV amplified MYCN up to 100 folds and became highly transformed and malignant, thus causing neuroblastoma in young rat pups of strains SD and Fisher-344 and larger tumor masses in nu/nu mice. An association was discovered with GD2 since this glycosphingolipid is also the receptor for the family of MFV virus (dsRNA viruses). It is concluded that a dsRNA virus, MFV, appears to provide better explicatory mechanisms for the genesis of i) specific genomic aberrations such as MNA; ii) extensive tumor heterogeneity and chromothripsis; iii) the effects of passive immunotherapy with anti-GD2 monoclonals and that this and similar models should be further investigated in both pediatric and adult cancers.

Keywords: neuroblastoma, MYCN, amplification, viruses, GD2

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Authors: Andrey Khalov

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The rapid proliferation of unstructured data in IT infrastructure management demands innovative approaches for extracting actionable knowledge. This paper presents a framework for ontology-based knowledge extraction that combines relational graph neural networks (R-GNN) with large language models (LLMs). The proposed method leverages the DOLCE framework as the foundational ontology, extending it with concepts from ITSMO for domain-specific applications in IT service management and outsourcing. A key component of this research is the use of transformer-based models, such as DeBERTa-v3-large, for automatic entity and relationship extraction from unstructured texts. Furthermore, the paper explores how transfer learning techniques can be applied to fine-tune large language models (LLaMA) for using to generate synthetic datasets to improve precision in BERT-based entity recognition and ontology alignment. The resulting IT Ontology (ITO) serves as a comprehensive knowledge base that integrates domain-specific insights from ITIL processes, enabling more efficient decision-making. Experimental results demonstrate significant improvements in knowledge extraction and relationship mapping, offering a cutting-edge solution for enhancing cognitive computing in IT service environments.

Keywords: ontology expansion, synthetic dataset, transformer fine-tuning, concept extraction, DOLCE, BERT, taxonomy, LLM, NER

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Authors: Marina Passero, Tianhua Zhai, Zuyi (Jacky) Huang

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Alzheimer’s disease has become a major public health issue, as indicated by the increasing populations of Americans living with Alzheimer’s disease. After decades of extensive research in Alzheimer’s disease, only seven drugs have been approved by Food and Drug Administration (FDA) to treat Alzheimer’s disease. Five of these drugs were designed to treat the dementia symptoms, and only two drugs (i.e., Aducanumab and Lecanemab) target the progression of Alzheimer’s disease, especially the accumulation of amyloid-b plaques. However, controversial comments were raised for the accelerated approvals of either Aducanumab or Lecanemab, especially with concerns on safety and side effects of these two drugs. There is still an urgent need for further drug discovery to target the biological processes involved in the progression of Alzheimer’s disease. Excessive cholesterol has been found to accumulate in the brain of those with Alzheimer’s disease. Cholesterol can be synthesized in both the blood and the brain, but the majority of biosynthesis in the adult brain takes place in astrocytes and is then transported to the neurons via ApoE. The blood brain barrier separates cholesterol metabolism in the brain from the rest of the body. Various proteins contribute to the metabolism of cholesterol in the brain, which offer potential targets for Alzheimer’s treatment. In the astrocytes, SREBP cleavage-activating protein (SCAP) binds to Sterol Regulatory Element-binding Protein 2 (SREBP2) in order to transport the complex from the endoplasmic reticulum to the Golgi apparatus. Cholesterol is secreted out of the astrocytes by ATP-Binding Cassette A1 (ABCA1) transporter. Lipoprotein receptors such as triggering receptor expressed on myeloid cells 2 (TREM2) internalize cholesterol into the microglia, while lipoprotein receptors such as Low-density lipoprotein receptor-related protein 1 (LRP1) internalize cholesterol into the neuron. Cytochrome P450 Family 46 Subfamily A Member 1 (CYP46A1) converts excess cholesterol to 24S-hydroxycholesterol (24S-OHC). Cholesterol has been approved for its direct effect on the production of amyloid-beta and tau proteins. The addition of cholesterol to the brain promotes the activity of beta-site amyloid precursor protein cleaving enzyme 1 (BACE1), secretase, and amyloid precursor protein (APP), which all aid in amyloid-beta production. The reduction of cholesterol esters in the brain have been found to reduce phosphorylated tau levels in mice. In this work, a computational pipeline was developed to identify the protein targets involved in cholesterol regulation in brain and further to identify chemical compounds as the inhibitors of a selected protein target. Since extensive evidence shows the strong correlation between brain cholesterol regulation and Alzheimer’s disease, a detailed literature review on genes or pathways related to the brain cholesterol synthesis and regulation was first conducted in this work. An interaction network was then built for those genes so that the top gene targets were identified. The involvement of these genes in Alzheimer’s disease progression was discussed, which was followed by the investigation of existing clinical trials for those targets. A ligand-protein docking program was finally developed to screen 1.5 million chemical compounds for the selected protein target. A machine learning program was developed to evaluate and predict the binding interaction between chemical compounds and the protein target. The results from this work pave the way for further drug discovery to regulate brain cholesterol to combat Alzheimer’s disease.

Keywords: Alzheimer’s disease, drug discovery, ligand-protein docking, gene-network analysis, cholesterol regulation

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Authors: Ajeevan Gautam, Gulam Anwer Khan, Pratibha Pokhrel

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Introduction: Dermatoglyphics is the science which deals with the study of dermal ridge configuration on the digits, palms and soles. It is grooved by ridges and forms variety of configurations. The aim of the study was to identify dermal ridge patterns on fingertip of hypertensive patients and in normal population and to compare patterns among them. Methods: The subjects of the study were 130 hypertensives and 130 non-hypertensives cases of Kathmandu Valley aged between 40 to 80 years. Case history was recorded after consent finger prints were taken. Different parameters as whorl, loop, arch and composite patterns were studied and analysed. Result: It revealed, increased whorl pattern in hypertensive. It showed 65.69% whorl, 29.23% loop and 5.07% arch patterns in right hand of hypertensive people. In control, it was found to be 34.46% whorl, 58.15% loop and 5.38% arch patterns respectively. Similarly in left hand 63.69% whorl, 32% loop and 4.30% arch in hypertensive group. In control group it was 60.15% as loop, 35.69% as whorl and 15% as arch. Discussion: Based on findings of the result, it was concluded that the whorl, loop and arch patterns observed as 65.69%, 29.23% and 5.07% respectively in hypertensive cases in right hand. Similarly in left hand, it was found to be 4.30% as arch, 32% as loop and 63.69% as whorl patterns, but in normotensive subjects these patterns were recorded as 36.43%, 58.15%, 5.38% in right hand and 35.69%, 60.15%, 4.15% in left hand as whorl, loop and arch respectively.

Keywords: arch, dermatoglyphics, hypertension, loop, whorl

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Authors: Syafinatul Fitri

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Cakrawala Baca is one of social organization in Indonesia that realize to transform its organization into social enterprise to create more sustainable organization that result more sustainable social impact. Cakrawala Baca implements voluntary system for its organization and it has passive social target. It funds its program by several fund rising activities that depend on donors or sponsor. Therefore social activity that held does not create sustainable social impact. It is different with social enterprise that usually more independent in funding its activity through social business and implement active social target and professional work for organization member. Therefore social enterprise can sustain its organization and then able to create sustainable social impact. Developing transformation model from social movement into social enterprise is the focus of this study. To achieve the aim of study, benchmark approach from successful social enterprise in Indonesia that has previously formed as social movement is employed. The benchmark is conducted through internal and external scanning that result the understanding of how they transformed into social enterprise. After understanding SAM and Agritektur transformation, transformation pattern is formulated based on their transformation similarities. This transformation pattern will be implemented to formulate the transformation plan for Cakrawala Baca to be a social enterprise.

Keywords: social movement/social organization, non-profit organization (NPO), social enterprise, transformation, Benchmarks approach

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Authors: Naser Safdarian, Nader Jafarnia Dabanloo

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In this paper we used four features i.e. Q-wave integral, QRS complex integral, T-wave integral and total integral as extracted feature from normal and patient ECG signals to detection and localization of myocardial infarction (MI) in left ventricle of heart. In our research we focused on detection and localization of MI in standard ECG. We use the Q-wave integral and T-wave integral because this feature is important impression in detection of MI. We used some pattern recognition method such as Artificial Neural Network (ANN) to detect and localize the MI. Because these methods have good accuracy for classification of normal and abnormal signals. We used one type of Radial Basis Function (RBF) that called Probabilistic Neural Network (PNN) because of its nonlinearity property, and used other classifier such as k-Nearest Neighbors (KNN), Multilayer Perceptron (MLP) and Naive Bayes Classification. We used PhysioNet database as our training and test data. We reached over 80% for accuracy in test data for localization and over 95% for detection of MI. Main advantages of our method are simplicity and its good accuracy. Also we can improve accuracy of classification by adding more features in this method. A simple method based on using only four features which extracted from standard ECG is presented which has good accuracy in MI localization.

Keywords: ECG signal processing, myocardial infarction, features extraction, pattern recognition

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Authors: Amir Andria Gad Shehata

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Minimizing the inventory cost, optimizing the inventory quantities, and increasing system operational availability are the main motivations to enhance forecasting demand of spare parts in a major power utility company in Medina. This paper reports in an effort made to optimize the orders quantities of spare parts by improving the method of forecasting the demand. The study focuses on equipment that has frequent spare parts purchase orders with uncertain demand. The pattern of the demand considers a lumpy pattern which makes conventional forecasting methods less effective. A comparison was made by benchmarking various methods of forecasting based on experts’ criteria to select the most suitable method for the case study. Three actual data sets were used to make the forecast in this case study. Two neural networks (NN) approaches were utilized and compared, namely long short-term memory (LSTM) and multilayer perceptron (MLP). The results as expected, showed that the NN models gave better results than traditional forecasting method (judgmental method). In addition, the LSTM model had a higher predictive accuracy than the MLP model.

Keywords: spare part, spare part inventory, inventory model, optimization, maintenanceneural network, LSTM, MLP, forecasting demand, inventory management

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Authors: Zoran Jovanovic, Zoran Masonicic, S. Dragutinovic, Z. Sakota

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In this paper, results concerning flame propagation of various fuels in a particular combustion chamber with four tilted valves were elucidated. Flame propagation was represented by the evolution of spatial distribution of temperature in various cut-planes within combustion chamber while the flame front location was determined by dint of zones with maximum temperature gradient. The results presented are only a small part of broader on-going scrutinizing activity in the field of multidimensional modeling of reactive flows in combustion chambers with complicated geometries encompassing various models of turbulence, different fuels and combustion models. In the case of turbulence two different models were applied i.e. standard k-ε model of turbulence and k-ξ-f model of turbulence. In this paper flame propagation results were analyzed and presented for two different hydrocarbon fuels, such as CH4 and C8H18. In the case of combustion all differences ensuing from different turbulence models, obvious for non-reactive flows are annihilated entirely. Namely the interplay between fluid flow pattern and flame propagation is invariant as regards turbulence models and fuels applied. Namely the interplay between fluid flow pattern and flame propagation is entirely invariant as regards fuel variation indicating that the flame propagation through unburned mixture of CH4 and C8H18 fuels is not chemically controlled.

Keywords: automotive flows, flame propagation, combustion modelling, CNG

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Authors: Mayowa Philips Ibitola, Abe Oluwaseun Banji, Olorunfemi Akinade-Solomon

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A total of 20 bottom sediment samples were collected from the Lekki Lagoon during the wet and dry season. The study was carried out to determine the textural characteristics, sediment distribution pattern and energy of transportation within the lagoon system. The sediment grain sizes and depth profiling was analyzed using dry sieving method and MATLAB algorithm for processing. The granulometric reveals fine grained sand both for the wet and dry season with an average mean value of 2.03 ϕ and -2.88 ϕ, respectively. Sediments were moderately sorted with an average inclusive standard deviation of 0.77 ϕ and -0.82 ϕ. Skewness varied from strongly coarse and near symmetrical 0.34- ϕ and 0.09 ϕ. The kurtosis average value was 0.87 ϕ and -1.4 ϕ (platykurtic and leptokurtic). Entirely, the bathymetry shows an average depth of 4.0 m. The deepest and shallowest area has a depth of 11.2 m and 0.5 m, respectively. High concentration of fine sand was observed at deep areas compared to the shallow areas during wet and dry season. Statistical parameter results show that the overall sediments are sorted, and deposited under low energy condition over a long distance. However, sediment distribution and sediment transport pattern of Lekki Lagoon is controlled by a low energy current and the down slope configuration of the bathymetry enhances the sorting and the deposition rate in the Lekki Lagoon.

Keywords: Lekki Lagoon, Marine sediment, bathymetry, grain size distribution

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Authors: Adebusoye Michael, Anthony Gloria, Fasan Temitope, Jacob Anayo

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Background: The culture of fast food consumption has gradually become a common lifestyle in Nigeria especially among young people in urban areas, in spite of the associated adverse health consequences. The adolescent pattern of fast foods consumption and their perception of this practice, as a risk factor for Non-Communicable Diseases (NCDs), have not been fully explored. This study was designed to assess fast food consumption pattern and the perception of it as a risk factor for NCDs among undergraduates of Federal Polytechnic, Bauchi. Methodology: The study was descriptive cross-sectional in design. One hundred and eighty-five students were recruited using systematic random sampling method from the two halls of residence. A structured questionnaire was used to assess the consumption pattern of fast foods. Data collected from the questionnaires were analysed using statistical package for the social sciences (SPSS) version 16. Simple descriptive statistics, such as frequency counts and percentages were used to interpret the data. Results: The age range of respondents was 18-34 years, 58.4% were males, 93.5% singles and 51.4% of their parents were employed. The majority (100%) were aware of fast foods and (75%) agreed to its implications as NCD. Fast foods consumption distribution included meat pie (4.9%), beef roll/ sausage (2.7%), egg roll (13.5%), doughnut (16.2%), noodles(18%) and carbonated drinks (3.8%). 30.3% consumed thrice in a week and 71% attached workload to high consumption of fast food. Conclusion: It was revealed that a higher social pressure from peers, time constraints, class pressure and school programme had the strong influence on high percentages of higher institutions’ students consume fast foods and therefore nutrition educational campaigns for campus food outlets or vendors and behavioural change communication on healthy nutrition and lifestyles among young people are hereby advocated.

Keywords: fast food consumption, Nigerian polytechnic, risk factors, undergraduate

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Authors: B. Hamidu, A. Abdulhamid, S. Mohammed, S. Idi

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This study examined the household expenditure pattern on animal products in Bauchi metropolis. A cross-sectional data were collected from 157 households using systematic sampling technique. The data were analyzed using descriptive statistics, correlation and regression models. The results reveal that the mean age, mean household size, mean monthly income and mean total expenditure on animal products were found to be 39 years, 7 persons, N28,749 and N1,740 respectively. It was also found that household monthly income, number of children and educational level of the household heads (P<0.01) significantly influence the level of household expenditure on animal products. Similarly, income was found to be the most important factor determining the proportion of total expenditure on animal products (20.91%). Income elasticity was found to be 0.66 indicating that for every 1% increase in income, expenditure on animal products would increase by 0.66%. Furthermore, beef was found to be the most preferred (54.83%) and most regularly consumed (61.84%) animal products. However, it was discovered that the major constraints affecting the consumption of animal products were low-income level of the households (29.85%), high cost of animal products (15.82%) and increase in prices of necessities (15.82%). Therefore to improve household expenditure on animal products per capita real income of the households should be improved through creation of employment opportunities. Also stabilization of market prices of animal products and other foods items of necessities through increased production are recommended.

Keywords: animal products, economics, expenditure, households

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Authors: Hemabushan K., Manikandan

Abstract:

In a swirl atomizer, fluid undergoes a swirling motion as a result of centrifugal force created by opposed tangential inlets in the swirl chamber. The angular momentum of fluid continually increases as it reaches the exit orifice and forms a hollow sheet. Which disintegrates to form ligaments and droplets respectively as it flows downstream. This type of atomizers used in rocket injectors and oil burner furnaces. In this present investigation a swirl atomizer with two opposed tangential inlets has been designed. Water as working fluid, experiments had been conducted for the fluid injection pressures in regime of 0.033 bar to 0.519 bar. The fluid has been pressured by a 0.5hp pump and regulated by a pressure regulator valve. Injection pressure of fluid has been measured by a U-tube mercury manometer. The spray pattern and the droplets has been captured with a high resolution camera in black background with a high intensity flash highlighting the fluid. The unprocessed images were processed in ImageJ processing software for measuring the droplet diameters and its shape characteristics along the downstream. The parameters such as mean droplet diameter and distribution, wave pattern, rupture distance and spray angle were studied for this atomizer. The above results were compared with theoretical results and also analysed for deviation with design parameters.

Keywords: swirl atomizer, injector, spray, SWIRL

Procedia PDF Downloads 490