Search results for: identification of risks

Authors: Rhaptyalyani Herno Della, Nyimas Septi Rika Putri, Rika Nabila

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The growth of population and economic activities in urban areas needs support economic development, needs to be balanced with adequate environmental infrastructure development. Settlement can avoid from rundown condition and uninhabitable if the development of urban area accordance with healthy development. Identifying database of slum in this study reference to the Review of the Spatial Plan Development of Palembang City, Laws of Public Works Department about Technical Guidelines on the Quality Improvement Housing and Slum and Urban Spatial Global Report on Human Settlements 2003. A case study for identifying in Palembang riverbanks area are located in two districts; Ilir Timur I and Ilir Timur II. This study do the identification of slum areas based on several variables about physical and non physical aspect, then the result of identification are used to define a policy that can be used to improve the area.

Keywords: slum, riverbanks area, urban area, infrastructure

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Authors: Dimitrios J. Dimitriou, Maria F. Sartzetaki

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Transport infrastructure assets are key components of the national asset portfolio. The decision to invest in a new infrastructure in transports could take from a few years to some decades. This is mainly because of the need to reserve and spent many capitals, the long payback period, the number of the stakeholders involved in decision process and –many times- the investment and business risks are high. Therefore, the decision assessment framework is an essential challenge linked with the key decision factors meet the stakeholder expectations highlighting project trade-offs, financial risks, business uncertainties and market limitations. This paper examines the decision process for new transport infrastructure projects in cross border regions, where a wide range of stakeholders with different expectation is involved. According to a consequences analysis systemic approach, the relationship of transport infrastructure development, economic system development and stakeholder expectation is analyzed. Adopting the on system of system methodological approach, the decision making framework, variables, inputs and outputs are defined, highlighting the key shareholder’s role and expectations. The application provides the methodology outputs presenting the proposed decision framework for a strategic railway project in north Greece deals with the upgrade of the existing railway corridor connecting Greece, Turkey and Bulgaria.

Keywords: decision making, system of system, cross-border, infrastructure project

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Authors: Nastaran Moosavi, Mohammad Mokhtari

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Seismic inversion is a technique which has been in use for years and its main goal is to estimate and to model physical characteristics of rocks and fluids. Generally, it is a combination of seismic and well-log data. Seismic inversion can be carried out through different methods; we have conducted and compared post-stack and pre- stack seismic inversion methods on real data in one of the fields in the Persian Gulf. Pre-stack seismic inversion can transform seismic data to rock physics such as P-impedance, S-impedance and density. While post- stack seismic inversion can just estimate P-impedance. Then these parameters can be used in reservoir identification. Based on the results of inverting seismic data, a gas reservoir was detected in one of Hydrocarbon oil fields in south of Iran (Persian Gulf). By comparing post stack and pre-stack seismic inversion it can be concluded that the pre-stack seismic inversion provides a more reliable and detailed information for identification and prediction of hydrocarbon reservoirs.

Keywords: density, p-impedance, s-impedance, post-stack seismic inversion, pre-stack seismic inversion

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Authors: Gerardo Arias, Richard Wall, Jamie Stevens

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Lucilia bufonivora Moniez, is an obligate parasite of toads and frogs widely distributed in Europe. Its sister taxon Lucilia silvarum Meigen behaves mainly as a carrion breeder in Europe, however it has been reported as a facultative parasite of amphibians. These two closely related species are morphologically almost identical, which has led to misidentification, and in fact, it has been suggested that the amphibian myiasis cases by L. silvarum reported in Europe should be attributed to L. bufonivora. Both species remain poorly studied and their taxonomic relationships are still unclear. The identification of the larval specimens involved in amphibian myiasis with molecular tools and phylogenetic analysis of these two closely related species may resolve this problem. In this work seventeen unidentified larval specimens extracted from toad myiasis cases of the UK, the Netherlands and Switzerland were obtained, their COX1 (mtDNA) and EF1-α (Nuclear DNA) gene regions were amplified and then sequenced. The 17 larval samples were identified with both molecular markers as L. bufonivora. Phylogenetic analysis was carried out with 10 other blowfly species, including L. silvarum samples from the UK and USA. Bayesian Inference trees of COX1 and a combined-gene dataset suggested that L. silvarum and L. bufonivora are separate sister species. However, the nuclear gene EF1-α does not appear to resolve their relationships, suggesting that the rates of evolution of the mtDNA are much faster than those of the nuclear DNA. This work provides the molecular evidence for successful identification of L. bufonivora and a molecular analysis of the populations of this obligate parasite from different locations across Europe. The relationships with L. silvarum are discussed.

Keywords: calliphoridae, molecular evolution, myiasis, obligate parasitism

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Authors: Jafar Ahmadi, Nafiseh Noormohammadi, Sedegeh Fabriki Ourang

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GRF, Growth regulating factor, genes encode a novel class of plant-specific transcription factors. The GRF proteins play a role in the regulation of cell numbers in young and growing tissues and may act as transcription activations in growth and development of plants. Identification of GRF genes and their expression are important in plants to performance of the growth and development of various organs. In this study, to better understanding the structural and functional differences of GRFs family, 45 GRF proteins sequences in A. thaliana, Z. mays, O. sativa, B. napus, B. rapa, H. vulgare, and S. bicolor, have been collected and analyzed through bioinformatics data mining. As a result, in secondary structure of GRFs, the number of alpha helices was more than beta sheets and in all of them QLQ domains were completely in the biggest alpha helix. In all GRFs, QLQ, and WRC domains were completely protected except in AtGRF9. These proteins have no trans-membrane domain and due to have nuclear localization signals act in nuclear and they are component of unstable proteins in the test tube.

Keywords: domain, gene family, GRF, motif

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Authors: Mehrnaz Mostafavi

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Recent advances in single-molecule protein identification (ID) and quantification techniques are poised to revolutionize proteomics, enabling researchers to delve into single-cell proteomics and identify low-abundance proteins crucial for biomedical and clinical research. This paper introduces a different approach to single-molecule protein ID and quantification using tri-color amino acid tags and a plasmonic nanopore device. A comprehensive simulator incorporating various physical phenomena was designed to predict and model the device's behavior under diverse experimental conditions, providing insights into its feasibility and limitations. The study employs a whole-proteome single-molecule identification algorithm based on convolutional neural networks, achieving high accuracies (>90%), particularly in challenging conditions (95–97%). To address potential challenges in clinical samples, where post-translational modifications affecting labeling efficiency, the paper evaluates protein identification accuracy under partial labeling conditions. Solid-state nanopores, capable of processing tens of individual proteins per second, are explored as a platform for this method. Unlike techniques relying solely on ion-current measurements, this approach enables parallel readout using high-density nanopore arrays and multi-pixel single-photon sensors. Convolutional neural networks contribute to the method's versatility and robustness, simplifying calibration procedures and potentially allowing protein ID based on partial reads. The study also discusses the efficacy of the approach in real experimental conditions, resolving functionally similar proteins. The theoretical analysis, protein labeler program, finite difference time domain calculation of plasmonic fields, and simulation of nanopore-based optical sensing are detailed in the methods section. The study anticipates further exploration of temporal distributions of protein translocation dwell-times and the impact on convolutional neural network identification accuracy. Overall, the research presents a promising avenue for advancing single-molecule protein identification and quantification with broad applications in proteomics research. The contributions made in methodology, accuracy, robustness, and technological exploration collectively position this work at the forefront of transformative developments in the field.

Keywords: nano proteomics, nanopore-based optical sensing, deep learning, artificial intelligence

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Authors: Zair Firdaous, Fourka Mohamed, Elfelsoufi Zoubir

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The arrival of e-commerce has changed the supply chain management on the operational level as well as on the organization and strategic and even tactical decisions of the companies. The optimization of resources is an issue that is needed on the tactical and operational strategic plan. This work considers the allocation of resources in the case of pure players that have launched online sales. The aim is to improve the level of customer satisfaction and maintaining the benefits of e-retailer and of its cooperators and reducing costs and risks. We first modeled the B2C chain with all operations that integrates and possible scenarios since online retailers offer a wide selection of personalized service. The personalized services that online shopping companies offer to the clients can be embodied in many aspects, such as the customizations of payment, the distribution methods, and after-sales service choices. Every aspect of customized service has several modes. At that time, we analyzed the optimization problems of supply chain resource in customized online shopping service mode. Then, we realized an optimization model and algorithm for the development based on the analysis of the of the B2C supply chain resources. It is a multi-objective optimization that considers the collaboration of resources in operations, time and costs but also the risks and the quality of services as well as dynamic and uncertain characters related to the request.

Keywords: supply chain resource, e-commerce, pure-players, optimization

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Authors: Stefanie Behncke

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This paper analyses the effects of different macroprudential policy measures that have recently been implemented in Switzerland. Among them is the activation and the increase of the countercyclical capital buffer (CCB) and a tightening of loan-to-value (LTV) requirements. These measures were introduced to limit systemic risks in the Swiss mortgage and real estate markets. They were meant to affect mortgage growth, mortgage risks, and banks’ capital buffers. Evaluation of their quantitative effects provides insights for Swiss policymakers when reassessing their policy. It is also informative for policymakers in other countries who plan to introduce macroprudential instruments. We estimate the effects of the different macroprudential measures with a Differences-in-Differences estimator. Banks differ with respect to the relative importance of mortgages in their portfolio, their riskiness, and their capital buffers. Thus, some of the banks were more affected than others by the CCB, while others were more affected by the LTV requirements. Our analysis is made possible by an unusually informative bank panel data set. It combines data on newly issued mortgage loans and quantitative risk indicators such as LTV and loan-to-income (LTI) ratios with supervisory information on banks’ capital and liquidity situation and balance sheets. Our results suggest that the LTV cap of 90% was most effective. The proportion of new mortgages with a high LTV ratio was significantly reduced. This result does not only apply to the 90% LTV, but also to other threshold values (e.g. 80%, 75%) suggesting that the entire upper part of the LTV distribution was affected. Other outcomes such as the LTI distribution, the growth rates of mortgages and other credits, however, were not significantly affected. Regarding the activation and the increase of the CCB, we do not find any significant effects: neither LTV/LTI risk parameters nor mortgage and other credit growth rates were significantly reduced. This result may reflect that the size of the CCB (1% of relevant residential real estate risk-weighted assets at activation, respectively 2% at the increase) was not sufficiently high enough to trigger a distinct reaction between the banks most likely to be affected by the CCB and those serving as controls. Still, it might be have been effective in increasing the resilience in the overall banking system. From a policy perspective, these results suggest that targeted macroprudential policy measures can contribute to financial stability. In line with findings by others, caps on LTV reduced risk taking in Switzerland. To fully assess the effectiveness of the CCB, further experience is needed.

Keywords: banks, financial stability, macroprudential policy, mortgages

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Authors: Tsega Asresa Mengistu, Getahun Tigistu

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Computer vision is an artificial intelligence subfield that allows computers and systems to retrieve meaning from digital images. It is applied in various fields of study self-driving cars, video surveillance, agriculture, Quality control, Health care, construction, military, and everyday life. Aromatic and medicinal plants are botanical raw materials used in cosmetics, medicines, health foods, and other natural health products for therapeutic and Aromatic culinary purposes. Herbal industries depend on these special plants. These plants and their products not only serve as a valuable source of income for farmers and entrepreneurs, and going to export not only industrial raw materials but also valuable foreign exchange. There is a lack of technologies for the classification and identification of Aromatic and medicinal plants in Ethiopia. The manual identification system of plants is a tedious, time-consuming, labor, and lengthy process. For farmers, industry personnel, academics, and pharmacists, it is still difficult to identify parts and usage of plants before ingredient extraction. In order to solve this problem, the researcher uses a deep learning approach for the efficient identification of aromatic and medicinal plants by using a convolutional neural network. The objective of the proposed study is to identify the aromatic and medicinal plant Parts and usages using computer vision technology. Therefore, this research initiated a model for the automatic classification of aromatic and medicinal plants by exploring computer vision technology. Morphological characteristics are still the most important tools for the identification of plants. Leaves are the most widely used parts of plants besides the root, flower and fruit, latex, and barks. The study was conducted on aromatic and medicinal plants available in the Ethiopian Institute of Agricultural Research center. An experimental research design is proposed for this study. This is conducted in Convolutional neural networks and Transfer learning. The Researcher employs sigmoid Activation as the last layer and Rectifier liner unit in the hidden layers. Finally, the researcher got a classification accuracy of 66.4 in convolutional neural networks and 67.3 in mobile networks, and 64 in the Visual Geometry Group.

Keywords: aromatic and medicinal plants, computer vision, deep convolutional neural network

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Authors: Radoslav Židek, Veronika Šidlová, Radovan Kasarda, Birgit Fuerst-Waltl

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Machine learning represents a set of topics dealing with the creation and evaluation of algorithms that facilitate pattern recognition, classification, and prediction, based on models derived from existing data. The data can present identification patterns which are used to classify into groups. The result of the analysis is the pattern which can be used for identification of data set without the need to obtain input data used for creation of this pattern. An important requirement in this process is careful data preparation validation of model used and its suitable interpretation. For breeders, it is important to know the origin of animals from the point of the genetic diversity. In case of missing pedigree information, other methods can be used for traceability of animal´s origin. Genetic diversity written in genetic data is holding relatively useful information to identify animals originated from individual countries. We can conclude that the application of data mining for molecular genetic data using supervised learning is an appropriate tool for hypothesis testing and identifying an individual.

Keywords: genetic data, Pinzgau cattle, supervised learning, machine learning

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Authors: Justin A. Udie, Subhes C. Bhatthacharyya, Leticia Ozawa-Meida

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The impact of climate change is severe in the Niger Delta and critical oil and gas infrastructures are vulnerable. This is partly due to lack of specific impact assessment framework to assess impact indices on both existing and new infrastructures. The purpose of this paper is to develop a framework for the assessment of climate change impact on critical oil and gas infrastructure in the region. Comparative and documentary methods as well as analysis of frameworks were used to develop a flexible, integrated and conceptual four dimensional framework underpinning; 1. Scoping – the theoretical identification of inherent climate burdens, review of exposure, adaptive capacities and delineation of critical infrastructure; 2. Vulnerability assessment – presents a systematic procedure for the assessment of infrastructure vulnerability. It provides real time re-scoping, practical need for data collection, analysis and review. Physical examination of systems is encouraged to complement the scoped data and ascertain the level of exposure to relevant climate risks in the area; 3. New infrastructure – consider infrastructures that are still at developmental level. It seeks to suggest the inclusion of flexible adaptive capacities in original design of infrastructures in line with climate threats and projections; 4. The Mainstreaming Climate Impact Assessment into government’s environmental decision making approach. Though this framework is designed specifically for the estimation of exposure, adaptive capacities and criticality of vulnerable oil and gas infrastructures in the Niger Delta to climate burdens; it is recommended for researchers and experts as a first-hand generic and practicable tool which can be used for the assessment of other infrastructures perceived as critical and vulnerable. The paper does not provide further tools that synch into the methodological approach but presents pointers upon which a pragmatic methodology can be developed.

Keywords: adaptation, assessment, conceptual, climate, change, framework, vulnerability

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Authors: Jin Liang, Q. Li, Yue Qi, Liying Wang, Wenhua Yu, Xun Liu

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Fertility is very important for women. The gender role of women gives them the fertility ability. Giving birth to a boy or a girl might have effect on the mother’s life in the past in China. However, with the shifting of traditional attitudes and views, the women's social status and living situation have been transformed. Although the pregnancy and childbirth can still bring them a major impact on their lives, the form and content of the impact have changed. So we investigated the rural women of Hebei province after birth to reflect their living situation changes before and after birth and the differences of their living situation from women in the past by using a self-made rural women life situation change questionnaire, the index of well-being, and the index of general effect questionnaire. It has shown that women’s living situation after babybirth in Hebei province is well in general, and their mind and body, as well as their interpersonal relationships and social status, were all enhanced. The women’s living situation after babybirth was positively related to and could anticipate subjective happiness, and specifically, the rural women’s mind and body, their interpersonal relationship and social status in rural women life situation change questionnaire are the main predicted factors to subjective happiness. Furthermore, the women’s self-identification on female roles was influenced by the children’s gender. Specifically, women with only one daughter had highest self-identification on female roles, consisting with their families' concept about children’s gender, which indicated family values have a great effect on women’s self-identification on female roles in rural. Moreover, the women’s living situation and subjective happiness are both impacted by home incomes.

Keywords: rural women, parturition, well-being, life quality

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Authors: Mustapha Achibane, Imane Allam

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Since the nineties, all Moroccan banking institutions have to respect an arsenal of prudential ratios. The respect of these prudential measures aims to ensure the financial system stability. In order to do so, regulatory authorities tried to reduce the financial and operational risks incurred by the banking entities. Meanwhile, regulatory authorities demanded a balance sheet management work from banks. They also asked them to establish a management control system to manage operational risk, as well as an effort in terms of incurred risk-based commitments. Therefore, the prudential approach has a macroeconomic nature and it is presented as a determinant of the operational, microeconomic approach. This operational approach takes the form of a strategy that each banking entity must develop to manage the different banking risks. This study seeks to analyze the problem of risk management between the prudential and the operational approaches. It was processed through a literature review followed by an analysis of the Moroccan banking sector’s performance. At first, we will reconcile the inductive logic and then, the analytical one. The first approach consists of analyzing the phenomenon from a normative and conceptual perspective, while the second one will consist of considering the Moroccan banking system and analyzing the behavior of Moroccan banking entities in terms of risk management and performance. The results identified a favorable growth in terms of performance, despite the huge provisioning effort made to meet the international standards and the harmonization of the regulations.

Keywords: banking performance, financial intermediation, operational approach, prudential standards, risk management

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Authors: Sarah A. Harris, Fleur L. McIntyre, Paola T. Chivers, Benjamin G. Piggott, Fiona H. Farringdon

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Australian Rules Football (ARF) is an invasion based, contact field sport with over one million participants. The contact nature of the game increases exposure to all injuries, including head trauma. Evidence suggests that both concussion and sub-concussive traumas such as head knocks may damage the brain, in particular the prefrontal cortex. The prefrontal cortex may not reach full maturity until a person is in their early twenties with males taking longer to mature than females. Repeated trauma to the pre-frontal cortex during maturation may lead to negative social, cognitive and emotional effects. It is also during this period that males exhibit high levels of risk taking behaviours. Risk propensity and the incidence of injury is an unexplored area of research. Little research has considered if the level of player’s (especially younger players) risk propensity in everyday life places them at an increased risk of injury. Hence the current study, investigated if a relationship exists between risk propensity and self-reported injuries including diagnosed concussion and head knocks, among male ARF players aged 18 to 31 years. Method: The study was conducted over 22 weeks with one West Australian Football League (WAFL) club during the 2015 competition. Pre-season risk propensity was measured using the 7-item self-report Risk Propensity Scale. Possible scores ranged from 9 to 63, with higher scores indicating higher risk propensity. Players reported their self-perceived injuries (concussion, head knocks, upper body and lower body injuries) fortnightly using the WAFL Injury Report Survey (WIRS). A unique ID code was used to ensure player anonymity, which also enabled linkage of survey responses and injury data tracking over the season. A General Linear Model (GLM) was used to analyse whether there was a relationship between risk propensity score and total number of injuries for each injury type. Results: Seventy one players (N=71) with an age range of 18.40 to 30.48 years and a mean age of 21.92 years (±2.96 years) participated in the study. Player’s mean risk propensity score was 32.73, SD ±8.38. Four hundred and ninety five (495) injuries were reported. The most frequently reported injury was head knocks representing 39.19% of total reported injuries. The GLM identified a significant relationship between risk propensity and head knocks (F=4.17, p=.046). No other injury types were significantly related to risk propensity. Discussion: A positive relationship between risk propensity and head trauma in contact sports (specifically WAFL) was discovered. Assessing player’s risk propensity therefore, may identify those more at risk of head injuries. Potentially leading to greater monitoring and education of these players throughout the season, regarding self-identification of head knocks and symptoms that may indicate trauma to the brain. This is important because many players involved in WAFL are in their late teens or early 20’s hence, may be at greater risk of negative outcomes if they experience repeated head trauma. Continued education and research into the risks associated with head injuries has the potential to improve player well-being.

Keywords: football, head injuries, injury identification, risk

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Authors: Schadrack Mwizerwa

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The characterization and prediction of landslides are crucial for assessing geological hazards and mitigating risks to infrastructure and communities. This research aims to develop a probabilistic framework for analyzing excavation-induced landslides, which is fundamental for assessing geological hazards and mitigating risks to infrastructure and communities. The study uses Hermite polynomial chaos, a non-stationary random process, to analyze the stability of a slope and characterize the failure probability of a real landslide induced by highway construction excavation. The correlation within the data is captured using the Karhunen-Loève (KL) expansion theory, and the finite element method is used to analyze the slope's stability. The research contributes to the field of landslide characterization by employing advanced random field approaches, providing valuable insights into the complex nature of landslide behavior and the effectiveness of advanced probabilistic models for risk assessment and management. The data collected from the Baiyuzui landslide, induced by highway construction, is used as an illustrative example. The findings highlight the importance of considering the probabilistic nature of landslides and provide valuable insights into the complex behavior of such hazards.

Keywords: Hermite polynomial chaos, Karhunen-Loeve, slope stability, probabilistic analysis

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Authors: Firdaous Zair, Zoubir Elfelsoufi, Mohammed Fourka

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The allocation of resources is an issue that is needed on the tactical and operational strategic plan. This work considers the allocation of resources in the case of pure players, manufacturers and Click & Mortars that have launched online sales. The aim is to improve the level of customer satisfaction and maintaining the benefits of e-retailer and of its cooperators and reducing costs and risks. Our contribution is a decision support system and tool for improving the allocation of resources in logistics chains e-commerce B2C context. We first modeled the B2C chain with all operations that integrates and possible scenarios since online retailers offer a wide selection of personalized service. The personalized services that online shopping companies offer to the clients can be embodied in many aspects, such as the customizations of payment, the distribution methods, and after-sales service choices. In addition, every aspect of customized service has several modes. At that time, we analyzed the optimization problems of supply chain resource allocation in customized online shopping service mode, which is different from the supply chain resource allocation under traditional manufacturing or service circumstances. Then we realized an optimization model and algorithm for the development based on the analysis of the allocation of the B2C supply chain resources. It is a multi-objective optimization that considers the collaboration of resources in operations, time and costs but also the risks and the quality of services as well as dynamic and uncertain characters related to the request.

Keywords: e-commerce, supply chain, B2C, optimisation, resource allocation

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Authors: Ronit Chakraborty, Sugata Banerji

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There has been a marked increase in the reported prevalence of Autism Spectrum Disorder (ASD) among children in the US over the past two decades. This research has analyzed the growth in state-level ASD prevalence against 45 different potentially explanatory factors, including socio-economic, demographic, healthcare, public policy, and political factors. The goal was to understand if these factors have adequate predictive power in modeling the differential growth in ASD prevalence across various states and if they do, which factors are the most influential. The key findings of this study include (1) the confirmation that the chosen feature set has considerable power in predicting the growth in ASD prevalence, (2) the identification of the most influential predictive factors, (3) given the nature of the most influential predictive variables, an indication that a considerable portion of the reported ASD prevalence differentials across states could be attributable to over and under diagnosis, and (4) identification of Florida as a key outlier state pointing to a potential under-diagnosis of ASD there.

Keywords: autism spectrum disorder, clustering, machine learning, predictive modeling

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Authors: V. Agostini, S. Gino, S. Inturri, A. Piccinini

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In cases of corpse identification or parental testing performed on exhumed alleged dead father, usually, we seek and acquire organic samples as bones and/or bone fragments, teeth, nails and muscle’s fragments. The DNA analysis of these cadaveric matrices usually leads to identifying success, but it often happens that the results of the typing are not satisfactory with highly degraded, partial or even non-interpretable genetic profiles. To aggravate the interpretative panorama deriving from the analysis of such 'classical' organic matrices, we must add a long and laborious treatment of the sample that starts from the mechanical fragmentation up to the protracted decalcification phase. These steps greatly increase the chance of sample contamination. In the present work, instead, we want to report the use of 'unusual' cadaveric matrices, demonstrating that their forensic genetics analysis can lead to better results in less time and with lower costs of reagents. We report six case reports, result of on-field experience, in which eyeswabs and cartilage were sampled and analyzed, allowing to obtain clear single genetic profiles, useful for identification purposes. In all cases we used the standard DNA tissue extraction protocols (as reported on the user manuals of the manufacturers such as QIAGEN or Invitrogen- Thermo Fisher Scientific), thus bypassing the long and difficult phases of mechanical fragmentation and decalcification of bones' samples. PCR was carried out using PowerPlex® Fusion System kit (Promega), and capillary electrophoresis was carried out on an ABI PRISM® 310 Genetic Analyzer (Applied Biosystems®), with GeneMapper ID v3.2.1 (Applied Biosystems®) software. The software Familias (version 3.1.3) was employed for kinship analysis. The genetic results achieved have proved to be much better than the analysis of bones or nails, both from the qualitative and quantitative point of view and from the point of view of costs and timing. This way, by using the standard procedure of DNA extraction from tissue, it is possible to obtain, in a shorter time and with maximum efficiency, an excellent genetic profile, which proves to be useful and can be easily decoded for later paternity tests and/or identification of human remains.

Keywords: DNA, eye swabs and cartilage, identification human remains, paternity testing

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Authors: Reza Mohammadzadeh

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The major challenges in geotechnical engineering in underground spaces arise from uncertainties and different probabilities. The collection, collation, and collaboration of existing data to incorporate them in analysis and design for given prospect evaluation would be a reliable, practical problem solving method under uncertainty. Machine learning (ML) is a subfield of artificial intelligence in statistical science which applies different techniques (e.g., Regression, neural networks, support vector machines, decision trees, random forests, genetic programming, etc.) on data to automatically learn and improve from them without being explicitly programmed and make decisions and predictions. In this paper, a conceptual database schema of geotechnical risks in underground coal mining based on a cloud system architecture has been designed. A new approach of risk assessment using a three-dimensional risk matrix supported by the level of knowledge (LoK) has been proposed in this model. Subsequently, the model workflow methodology stages have been described. In order to train data and LoK models deployment, an ML platform has been implemented. IBM Watson Studio, as a leading data science tool and data-driven cloud integration ML platform, is employed in this study. As a Use case, a data set of geotechnical hazards and risk assessment in underground coal mining were prepared to demonstrate the performance of the model, and accordingly, the results have been outlined.

Keywords: data model, geotechnical risks, machine learning, underground coal mining

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Authors: Muhammad Fezan Afzal, Imran Khan, Salma Imtiaz

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The need for human verification and identification requires from centuries for authentication. Since it is being used in big institutes like financial, government and crime departments, a continued struggle is important to make this system more efficient to prevent security breaches. Therefore, multiple devices are used to authenticate the biometric for each individual. A large number of devices are required to cover a large number of users. As the number of devices increases, cost will automatically increase. Furthermore, it is time-consuming for biometrics due to the devices being insufficient and are not available at every door. In this paper, we propose the framework and algorithm where the mobile of each individual can also perform the biometric authentication of attendance and security. Every mobile has a biometric authentication system that is used in different mobile applications for security purposes. Therefore, each individual can use the biometric system mobile without moving from one place to another. Moreover, by using the biometrics mobile, the cost of biometric systems can be removed that are mostly deployed in different organizations for the attendance of students, employees and for other security purposes.

Keywords: fingerprint, fingerprint authentication, mobile verification, mobile biometric verification, mobile fingerprint sensor

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Authors: Ruth Hegarty, Noel Connaughton

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Sustainability reporting has become a priority for many global multinational companies. This is associated with ever-increasing expectations from key stakeholders for companies to be transparent about their strategies, activities and management with regard to sustainability issues. The Global Reporting Initiative (GRI) encourages reporters to only provide information on the issues that are really critical in order to achieve the organisation’s goals for sustainability and manage its impact on environment and society. A key challenge for most reporting organisations is how to identify relevant issues for sustainability reporting and prioritise those material issues in accordance with company and stakeholder needs. A recent study indicates that most of the largest companies listed on the world’s stock exchanges are failing to provide data on key sustainability indicators such as employee turnover, energy, greenhouse gas emissions (GHGs), injury rate, pay equity, waste and water. This paper takes an indepth look at the approaches used by a select number of international sustainability leader corporates to identify key sustainability issues. The research methodology involves performing a detailed analysis of the sustainability report content of up to 50 companies listed on the 2014 Dow Jones Sustainability Indices (DJSI). The most recent sustainability report content found on the GRI Sustainability Disclosure Database is then compared with 91 GRI Specific Standard Disclosures and a small number of GRI Standard Disclosures. Preliminary research indicates significant gaps in the information disclosed in corporate sustainability reports versus the indicator content specified in the GRI Content Index. The following outlines some of the key findings to date: Most companies made a partial disclosure with regard to the Economic indicators of climate change risks and infrastructure investments, but did not focus on the associated negative impacts. The top Environmental indicators disclosed were energy consumption and reductions, GHG emissions, water withdrawals, waste and compliance. The lowest rates of indicator disclosure included biodiversity, water discharge, mitigation of environmental impacts of products and services, transport, environmental investments, screening of new suppliers and supply chain impacts. The top Social indicators disclosed were new employee hires, rates of injury, freedom of association in operations, child labour and forced labour. Lesser disclosure rates were reported for employee training, composition of governance bodies and employees, political contributions, corruption and fines for non-compliance. The reporting on most other Social indicators was found to be poor. In addition, most companies give only a brief explanation on how material issues are defined, identified and ranked. Data on the identification of key stakeholders and the degree and nature of engagement for determining issues and their weightings is also lacking. Generally, little to no data is provided on the algorithms used to score an issue. Research indicates that most companies lack a rigorous and thorough methodology to systematically determine the material issues of sustainability reporting in accordance with company and stakeholder needs.

Keywords: identification of key stakeholders, material issues, sustainability reporting, transparency

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Authors: Dina Farran, Mark Ashworth, Fiona Gaughran

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Atrial fibrillation (AF), the most prevalent cardiac arrhythmia, is associated with an increased risk of stroke, contributing to heart failure and death. In this project, we aim to improve patient safety by screening for stroke risk among people with AF and co-morbid mental illness. To do so, we started by conducting a systematic review and meta-analysis on prevalence, management, and outcomes of AF in people with Serious Mental Illness (SMI) versus the general population. We then evaluated oral anticoagulation (OAC) prescription trends in people with AF and co-morbid SMI in King’s College Hospital. We also evaluated the association between mental illness severity and OAC prescription in eligible patients in South London and Maudsley (SLaM) NHS Foundation Trust. Next, we implemented an electronic clinical decision support system (eCDSS) consisting of a visual prompt on patient electronic Personal Health Records to screen for AF-related stroke risk in three Mental Health of Older Adults wards at SLaM. Finally, we assessed the feasibility and acceptability of the eCDSS by qualitatively investigating clinicians’ perspectives of the potential usefulness of the eCDSS (pre-intervention) and their experiences and their views regarding its impact on clinicians and patients (post-intervention). The systematic review showed that people with SMI had low reported rates of AF. AF patients with SMI were less likely to receive OAC than the general population. When receiving warfarin, people with SMI, particularly bipolar disorder, experienced poor anticoagulation control compared to the general population. Meta-analysis showed that SMI was not significantly associated with an increased risk of stroke or major bleeding when adjusting for underlying risk factors. The main findings of the first observational study were that among AF patients having a high stroke risk, those with co-morbid SMI were less likely than non-SMI to be prescribed any OAC, particularly warfarin. After 2019, there was no significant difference between the two groups. In the second observational study, patients with AF and co-morbid SMI were less likely to be prescribed any OAC compared to those with dementia, substance use disorders, or common mental disorders, adjusting for age, sex, stroke, and bleeding risk scores. Among AF patients with co-morbid SMI, warfarin was less likely to be prescribed to those having alcohol or substance dependency, serious self-injury, hallucinations or delusions, and activities of daily living impairment. In the intervention, clinicians were asked to confirm the presence of AF, clinically assess stroke and bleeding risks, record risk scores in clinical notes, and refer patients at high risk of stroke to OAC clinics. Clinicians reported many potential benefits for the eCDSS, including improving clinical effectiveness, better identification of patients at risk, safer and more comprehensive care, consistency in decision making and saving time. Identified potential risks included rigidity in decision-making, overreliance, reduced critical thinking, false positive recommendations, annoyance, and increased workload. This study presents a unique opportunity to quantify AF patients with mental illness who are at high risk of severe outcomes using electronic health records. This has the potential to improve health outcomes and, therefore patients' quality of life.

Keywords: atrial fibrillation, stroke, mental health conditions, electronic clinical decision support systems

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Authors: Evelyn Marie Richmond, Andrew McBride, Chris Johnston, John Marley

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Background: Good quality patient information resources for orthognathic treatment help to reinforce information delivered during the initial consultation and help patients make informed decisions about their care. The Consultant Orthodontists and a Dental Core Trainee noted limited patient engagement with the British Orthodontic Society (BOS) 'Your Jaw Surgery' online resources and that the existing BOS patient information leaflet (PIL) could be customised and developed to meet local requirements. Aim: The quality improvement project (QIP) aimed to improve patients' understanding of orthognathic treatment by ensuring at least 90% of patients had read the new in-house patient information leaflet (PIL) and a minimum of 50% of patients had accessed the British Orthodontic Society (BOS) 'Your Jaw Surgery' online resources before attending the joint orthognathic multidisciplinary clinic by June 2023. Methods: The QIP was undertaken in the orthodontic department of the School of Dentistry, Belfast. Data was collected prospectively during a 6-month period from January 2023 to June 2023 over 3 Plan, Do, Study, Act (PDSA) cycles. Suitable patients were identified at consultant orthodontic new patient clinics. Following initial consultation for orthognathic treatment, patients were contacted to complete a patient questionnaire. Design: The change ideas were a poster with a QR code directing patients to the BOS 'Your Jaw Surgery' website in consultation areas and a new in-house PIL with a QR code directing patients to the BOS 'Your Jaw Surgery' website. Results: In PDSA cycle 1, 86.7% of patients were verbally directed to the BOS 'Your Jaw Surgery' website, and 53.3% accessed the online resources after their initial consultation. Although 100% of patients reported reading the existing PIL, only 64.3% felt it discussed the risks of orthognathic treatment in sufficient detail. By PDSA cycle 3, 100% of patients reported being directed to the BOS 'Your Jaw Surgery' website, however, only 58.3% engaged with the website. 100% of patients who read the new PIL felt that it discussed the risks of orthognathic treatment in sufficient detail. Conclusion: The slight improvement in access to the BOS 'Your Jaw Surgery' website shows that patients do not necessarily choose to access information online despite its availability. The uptake of the new PIL was greater than reported patient engagement with the BOS 'Your Jaw Surgery' website, which indicates patients still value written information despite the availability of online resources.

Keywords: orthognathic surgery, patient information resources, quality improvement project, risks

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Authors: Ezeabasili Chibuike Patrick

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The complex situation of construction industries in Nigeria and the risk of failures involved includes cost overrun, time overrun, Corruption, Government influence, Subcontractor challenges, Political influence and Instability, Cultural differences, Human resources deficiencies, cash flow Challenges, foreign exchange issues, inadequate design, Safety, low productivity, late payment, Quality control issues, project management issues, Environmental issues, Force majeure Competition amongst others has made the industry prone to risk and failures. Good project management remains effective in improving decision-making, which minimizes these risk events. This study was done to address these project risks and good decision-making to avert them. A mixed-method approach to research was used to do this study. Data collected by questionnaires and interviews on thirty-two (32) construction professionals was used in analyses to aid the knowledge and management of risks that were identified. The study revealed that there is no good risk management expertise in Nigeria. Also, that the economic/political situation and the recent COVID-19 pandemic has added to the risk and poor management strategies. The contingency theory and cost has therefore surfaced to be the most strategic management method used to reduce these risk issues and they seem to be very effective.

Keywords: strategies, risk management, contingency theory, Nigeria

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Authors: K. Khlifi, A. Haddouk, M. Hlaili, H. Mechergui

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The present paper provides a detailed analysis of prior methods and approaches for non-linear load identification in residential buildings. The main goal of this analysis is to decipher the distorted signals and to estimate the harmonics influence on power systems. We have performed an analytical study of non-linear loads behavior in the residential environment. Simulations have been performed in order to evaluate the distorted rate of the current and follow his behavior. To complete this work, an instrumental platform has been realized to carry out practical tests on single-phase non-linear loads which illustrate the current consumption of some domestic appliances supplied with single-phase sinusoidal voltage. These non-linear loads have been processed and tracked in order to limit their influence on the power grid and to reduce the Joule effect losses. As a result, the study has allowed to identify responsible circuits of harmonic pollution.

Keywords: distortion rate, harmonic analysis, harmonic pollution, non-linear load, power factor

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Authors: Chia-Chun Wu, Yu-Hsien Sung

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This study aims to examine the consistency between students’ predictions and their actual observations on the bullying prevalence rate among different types of high-risk victims, thereby clarifying the reliability of students’ reports on the identification of bullying. A total of 1,732 Taiwanese students (734 males and 998 females) participated in this study. A Rasch model was adopted for data analysis. The results showed that students with “personality or behavioral issues” are more likely to be bullied in schools, based on both students’ predictions and actual observations. Moreover, the results differed significantly between genders and between various educational levels in students’ predictions and their actual observations on the bullying prevalence rate of different types of high-risk victims. To summarize, this study not only suggests that students’ reports on the identification of bullying are accurate and could be a valuable reference in terms of recognizing a bullying incident, but it also argues that more attention should be paid to students’ gender and educational level when taking their perspectives into consideration when it comes to identifying bullying behaviors.

Keywords: school bullying, student, bullying recognition, high-risk victims

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Authors: Zoya Khan, Amina Muzaffar

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Social media based brand communities are communities that are developed around a brand. In the highly globalized world of today, Facebook is undoubtedly being regarded and has been widely recognized as a trendy and well-accepted medium of marketing. By means of a Facebook fan page, organizations can effectually create, enhance, and sustain customer-brand relationship. In this article, we explore whether brand communities based on social media (a special type of online brand communities) have positive effects on the main community elements and value creation practices in the communities as well as on brand trust and brand loyalty. A survey was conducted and 201 valid responses were used for analysis. The results of structural equation modeling show that brand communities established on social media have positive effects on value creation practices. Brand use, impression management practices and brand identification has an impact on brand trust and this brand trust then further leads to brand loyalty.

Keywords: relationship quality, impression management practices, brand identification, brand trust, brand loyalty

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Authors: Mengxin Feng, Feng Xu, Zhiyong Lai

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As a typical representative of the countryside, traditional Chinese villages are rich in cultural landscape resources and historical information, but they are still in continuous decline. The problems of people's weak protection awareness and low cultural recognition are still serious, and the protection of cultural heritage is imminent. At the same time, with the rapid development of rural tourism, its cultural value has been explored and paid attention to again. From the perspective of tourists, this study aimed to explore people's perception and identity of cultural landscape resources under the current cultural tourism development background. We selected eleven typical landscape elements of Lingshui Village, a traditional village in Beijing, as research objects and conducted a questionnaire survey with two scales of perception and identity to explore the characteristics of people's perception and identification of landscape elements. We found that there was a strong positive correlation between the perception and identity of each element and that geographical location influenced visitors' overall perception. The perception dimensions scored the highest in location, and the lowest in history and culture, and the identity dimensions scored the highest in meaning and lowest in emotion. We analyzed the impact of visitors' backgrounds on people's perception and identity characteristics and found that age and education were two important factors. The elderly had a higher degree of perceived identity, as the familiarity effect increased their attention. Highly educated tourists had more stringent criteria for perception and identification. The above findings suggest strategies for conserving and optimizing landscape elements in the traditional village to improve the acceptance and recognition of cultural information in traditional villages, which will inject new vitality into the development of traditional villages.

Keywords: traditional village, tourist perception, landscape elements, perception and identity

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Authors: Abeer M. Algeblawi

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Fifteen isolates of Agrobacterium tumefaciens were obtained from crown gall samples collected from six locations (Tripoli, Alzahra, Ain-Zara, Alzawia, Alazezia in Libya) from Grape (Vitis vinifera L.), Pear (Pyrus communis L.), Peach (Prunus persica L.) and Alexandria in Egypt from Guava (Psidium guajava L.) trees, Artichoke (Cynara cardunculus L.) and Sugar beet (Beta vulgaris L.). Total DNA was extracted from the eight isolates as well as the identification of six isolates used into Polymerase Chain Reaction (PCR) analysis and Random Amplified Polymorphic DNA (RAPD) technique were used. High similarity (55.5%) was observed among the eight A. tumefaciens isolates (Agro1, Agro2, Agro3, Agro4, Agro5, Agro6, Agro7, and Agro8). The PCR amplification products were resulting from the use of two specific primers (virD2A-virD2C). Analysis induction six isolates of A. tumefaciens obtained from different hosts. A visible band was specific to A. tumefaciens of (220 bp, 224 bp) and 338 bp produced with total DNA extracted from bacterial cells.

Keywords: Agrobacterium tumefaciens, crown gall, identification, molecular characterization, PCR, RAPD

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Authors: Yaroslav Pavlov

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In the modern world, ensuring quality has become increasingly important in various fields of human activity. One universal approach to quality management, proven effective in the food industry, is the HACCP (Hazard Analysis and Critical Control Points) concept. Based on principles of preventing potential hazards to consumers at all stages of production, from raw materials to the final product, HACCP offers a systematic approach to identifying, assessing risks, and managing critical control points (CCPs). Initially used primarily for food production, it was later effectively adapted to the food service sector. Implementing HACCP provides organizations with a reliable foundation for improving food safety, covering all links in the food chain from producer to consumer, making it an integral part of modern quality management systems. The main principles of HACCP—hazard identification, CCP determination, effective monitoring procedures, corrective actions, regular checks, and documentation—are universal and can be adapted to other areas. The adaptation of the HACCP concept is relevant for continuing professional education (CPE) with certain reservations. Specifically, it is reasonable to abandon the term ‘hazards’ as deviations in CCPs do not pose dangers, unlike in food production. However, the approach through CCP analysis and the use of HACCP's main principles for educational services are promising. This is primarily because it allows for identifying key CCPs based on the value creation model of a specific educational organization and consequently focusing efforts on specific CCPs to manage the quality of educational services. This methodology can be called the Analysis of Critical Points in Educational Services (ACPES). ACPES offers a similar approach to managing the quality of educational services, focusing on preventing and eliminating potential risks that could negatively impact the educational process, learners' achievement of set educational goals, and ultimately lead to students rejecting the organization's educational services. ACPES adapts proven HACCP principles to educational services, enhancing quality management effectiveness and student satisfaction. ACPES includes identifying potential problems at all stages of the educational process, from initial interest to graduation and career development. In ACPES, the term "hazards" is replaced with "problematic areas," reflecting the specific nature of the educational environment. Special attention is paid to determining CCPs—stages where corrective measures can most effectively prevent or minimize the risk of failing educational goals. The ACPES principles align with HACCP's principles, adjusted for the specificities of CPE. The method of the learner's journey map (variation of Customer Journey Map, CJM) can be used to overcome the complexity of formalizing the production chain in educational services. CJM provides a comprehensive understanding of the learner's experience at each stage, facilitating targeted and effective quality management. Thus, integrating the learner's journey map into ACPES represents a significant extension of the methodology's capabilities, ensuring a comprehensive understanding of the educational process and forming an effective quality management system focused on meeting learners' needs and expectations.

Keywords: quality management, continuing professional education, customer journey map, HACCP

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