Search results for: Galileo new advanced features

Authors: Baladitya Swaika, Rahul Khatry

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Computer Adaptive Tests (CATs) is one of the most efficient ways for testing the cognitive abilities of students. CATs are based on Item Response Theory (IRT) which is based on item selection and ability estimation using statistical methods of maximum information selection/selection from posterior and maximum-likelihood (ML)/maximum a posteriori (MAP) estimators respectively. This study aims at combining both classical and Bayesian approaches to IRT to create a dataset which is then fed to a neural network which automates the process of ability estimation and then comparing it to traditional CAT models designed using IRT. This study uses python as the base coding language, pymc for statistical modelling of the IRT and scikit-learn for neural network implementations. On creation of the model and on comparison, it is found that the Neural Network based model performs 7-10% worse than the IRT model for score estimations. Although performing poorly, compared to the IRT model, the neural network model can be beneficially used in back-ends for reducing time complexity as the IRT model would have to re-calculate the ability every-time it gets a request whereas the prediction from a neural network could be done in a single step for an existing trained Regressor. This study also proposes a new kind of framework whereby the neural network model could be used to incorporate feature sets, other than the normal IRT feature set and use a neural network’s capacity of learning unknown functions to give rise to better CAT models. Categorical features like test type, etc. could be learnt and incorporated in IRT functions with the help of techniques like logistic regression and can be used to learn functions and expressed as models which may not be trivial to be expressed via equations. This kind of a framework, when implemented would be highly advantageous in psychometrics and cognitive assessments. This study gives a brief overview as to how neural networks can be used in adaptive testing, not only by reducing time-complexity but also by being able to incorporate newer and better datasets which would eventually lead to higher quality testing.

Keywords: computer adaptive tests, item response theory, machine learning, neural networks

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Authors: Jonathan Turner, Julie Doyle, Laura O’Philbin, Dympna O’Sullivan

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People living with dementia should be at the centre of decision-making regarding goals for daily living. These goals include basic activities (dressing, hygiene, and mobility), advanced activities (finances, transportation, and shopping), and meaningful activities that promote well-being (pastimes and intellectual pursuits). However, there is limited involvement of people living with dementia in the design of technology to support their goals. A project is described that is co-designing intelligent computer-based support for, and with, people affected by dementia and their carers. The technology will support self-management, empower participation in shared decision-making with carers and help people living with dementia remain healthy and independent in their homes for longer. It includes information from the patient’s care plan, which documents medications, contacts, and the patient's wishes on end-of-life care. Importantly for this work, the plan can outline activities that should be maintained or worked towards, such as exercise or social contact. The authors discuss how to integrate care goal information from such a care plan with data collected from passive sensors in the patient’s home in order to deliver individualized planning and interventions for persons with dementia. A number of scientific challenges are addressed: First, to co-design with dementia patients and their carers computerized support for shared decision-making about their care while allowing the patient to share the care plan. Second, to develop a new and open monitoring framework with which to configure sensor technologies to collect data about whether goals and actions specified for a person in their care plan are being achieved. This is developed top-down by associating care quality types and metrics elicited from the co-design activities with types of data that can be collected within the home, from passive and active sensors, and from the patient’s feedback collected through a simple co-designed interface. These activities and data will be mapped to appropriate sensors and technological infrastructure with which to collect the data. Third, the application of machine learning models to analyze data collected via the sensing devices in order to investigate whether and to what extent activities outlined via the care plan are being achieved. The models will capture longitudinal data to track disease progression over time; as the disease progresses and captured data show that activities outlined in the care plan are not being achieved, the care plan may recommend alternative activities. Disease progression may also require care changes, and a data-driven approach can capture changes in a condition more quickly and allow care plans to evolve and be updated.

Keywords: care goals, decision-making, dementia, self-care, sensors

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Authors: Teng Li, Kamran Mohseni

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This paper presents an inviscid regularization technique that is capable of regularizing the shocks and sharp interfaces simultaneously in the shock-interface interaction simulations. The direct numerical simulation of flows involving shocks has been investigated for many years and a lot of numerical methods were developed to capture the shocks. However, most of these methods rely on the numerical dissipation to regularize the shocks. Moreover, in high Reynolds number flows, the nonlinear terms in hyperbolic Partial Differential Equations (PDE) dominates, constantly generating small scale features. This makes direct numerical simulation of shocks even harder. The same difficulty happens in two-phase flow with sharp interfaces where the nonlinear terms in the governing equations keep sharpening the interfaces to discontinuities. The main idea of the proposed technique is to average out the small scales that is below the resolution (observable scale) of the computational grid by filtering the convective velocity in the nonlinear terms in the governing PDE. This technique is named “observable method” and it results in a set of hyperbolic equations called observable equations, namely, observable Navier-Stokes or Euler equations. The observable method has been applied to the flow simulations involving shocks, turbulence, and two-phase flows, and the results are promising. In the current paper, the observable method is examined on the performance of regularizing shocks and interfaces at the same time in shock-interface interaction problems. Bubble-shock interactions and Richtmyer-Meshkov instability are particularly chosen to be studied. Observable Euler equations will be numerically solved with pseudo-spectral discretization in space and third order Total Variation Diminishing (TVD) Runge Kutta method in time. Results are presented and compared with existing publications. The interface acceleration and deformation and shock reflection are particularly examined.

Keywords: compressible flow simulation, inviscid regularization, Richtmyer-Meshkov instability, shock-bubble interactions.

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Authors: Malte Brettel, Niklas Friederichsen, Michael Keller, Marius Rosenberg

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The German manufacturing industry has to withstand an increasing global competition on product quality and production costs. As labor costs are high, several industries have suffered severely under the relocation of production facilities towards aspiring countries, which have managed to close the productivity and quality gap substantially. Established manufacturing companies have recognized that customers are not willing to pay large price premiums for incremental quality improvements. As a consequence, many companies from the German manufacturing industry adjust their production focusing on customized products and fast time to market. Leveraging the advantages of novel production strategies such as Agile Manufacturing and Mass Customization, manufacturing companies transform into integrated networks, in which companies unite their core competencies. Hereby, virtualization of the process- and supply-chain ensures smooth inter-company operations providing real-time access to relevant product and production information for all participating entities. Boundaries of companies deteriorate, as autonomous systems exchange data, gained by embedded systems throughout the entire value chain. By including Cyber-Physical-Systems, advanced communication between machines is tantamount to their dialogue with humans. The increasing utilization of information and communication technology allows digital engineering of products and production processes alike. Modular simulation and modeling techniques allow decentralized units to flexibly alter products and thereby enable rapid product innovation. The present article describes the developments of Industry 4.0 within the literature and reviews the associated research streams. Hereby, we analyze eight scientific journals with regards to the following research fields: Individualized production, end-to-end engineering in a virtual process chain and production networks. We employ cluster analysis to assign sub-topics into the respective research field. To assess the practical implications, we conducted face-to-face interviews with managers from the industry as well as from the consulting business using a structured interview guideline. The results reveal reasons for the adaption and refusal of Industry 4.0 practices from a managerial point of view. Our findings contribute to the upcoming research stream of Industry 4.0 and support decision-makers to assess their need for transformation towards Industry 4.0 practices.

Keywords: Industry 4.0., mass customization, production networks, virtual process-chain

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Authors: Chiara Colarusso, Michela Terlizzi, Aldo Pinto, Rosalinda Sorrentino

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Cigarette smoking is the main cause and the most common risk factor for both COPD and lung cancer. In our previous studies, we proved that caspase-11 in mice and its human analogue, caspase-4, are involved in lung carcinogenesis and that AIM2 inflammasome might play a pro-cancerous role in lung cancer. Therefore, the aim of this study was to investigate potential crosstalk between COPD and lung cancer, focusing on AIM2 and caspase-11-dependent inflammasome signaling pathway. To mimic COPD, we took advantage of an experimental first-hand smoking mouse model and, to confirm what was observed in mice, we used human samples of lung adenocarcinoma patients stratified according to the smoking and COPD status. We demonstrated that smoke exposure led to emphysema-like features, bronchial tone impairment, and release of IL-1-like cytokines (IL-1α, IL-1β, IL-33, IL-18) in a caspase-1 independent manner in C57Bl/6N. Rather, a dysfunctional caspase-11 in smoke-exposed 129Sv mice was associated to lower bronchial inflammation, collagen deposition, and IL-1-like inflammation. In addition, for the first time, we found that AIM2 inflammasome is involved in lung inflammation in smoking and COPD, in that its expression was higher in smoke-exposed C57Bl/6N compared to 129Sv smoking mice, who instead did not show any alteration of AIM2 in both macrophages and dendritic cells. Moreover, we found that AIM2 expression in the cancerous tissue, albeit higher than non-cancerous tissue, was not statistically different according to the COPD and smoking status. Instead, the higher expression of AIM2 in non-cancerous tissue of smoker COPD patients than smokers who did not have COPD was correlated to a higher hazard ratio of poor survival rate than patients who presented lower levels of AIM2. In conclusion, our data highlight that caspase-11 in mice is associated to smoke-induced lung latent inflammation which could drive the establishment of lung cancer, and that AIM2 inflammasome plays a role at the crosstalk between smoking/COPD and lung adenocarcinoma in that its higher presence is correlated to lower survival rate of smoker COPD adenocarcinoma.

Keywords: COPD, inflammasome, lung cancer, lung inflammation, smoke

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Authors: Federica Laface, Cristina Pedà, Francesco Longo, Francesca de Domenico, Riccardo Minichino, Pierpaolo Consoli, Pietro Battaglia, Silvestro Greco, Teresa Romeo

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Plastics pollution represents one of the most important threats to marine biodiversity. In the last decades, different species are investigated to evaluate the extent of the plastic ingestion phenomenon. Even if the cephalopods play an important role in the food chain, they are still poorly studied. The aim of this research was to investigate the plastic ingestion in two commercial cephalopod species from the southern Tyrrhenian Sea: the common octopus, Octopus vulgaris (n=6; mean mantle length ML 10.7 ± 1.8) and the common cuttlefish, Sepia officinalis (n=13; mean ML 13.2 ± 1.7). Plastics were extracted from the filters obtained by the chemical digestion of cephalopods gastrointestinal tracts (GITs), using 10% potassium hydroxide (KOH) solution in a 1:5 (w/v) ratio. Once isolated, particles were photographed, measured, and their size class, shape and color were recorded. A total of 81 items was isolated from 16 of the 19 examined GITs, representing a total occurrence (%O) of 84.2% with a mean value of 4.3 ± 8.6 particles per individual. In particular, 62 plastics were found in 6 specimens of O. vulgaris (%O=100) and 19 particles in 10 S. officinalis (%O=94.7). In both species, the microplastics size class was the most abundant (93.8%). Plastic items found in O. vulgaris were mainly fibers (61%) while fragments were the most frequent in S. officinalis (53%). Transparent was the most common color in both species. The analysis will be completed by Fourier transform infrared (FT-IR) spectroscopy technique in order to identify polymers nature. This study reports preliminary data on plastic ingestion events in two cephalopods species and represents the first record of plastic ingestion by the common octopus. Microplastic items detected in both common octopus and common cuttlefish could derive from secondary and/or accidental ingestion events, probably due to their behavior, feeding habits and anatomical features. Further studies will be required to assess the effect of marine litter pollution in these ecologically and commercially important species.

Keywords: cephalopods, GIT analysis, marine pollution, Mediterranean sea, microplastics

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Authors: Tianjie Zhang, Bingqian Cheng, Peng Zeng

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Engineering science and technology progress and innovation have become an important engine to promote social development. The reform exploration of "new engineering" in China has drawn extensive attention around the world, with its connotation as "to cultivate future diversified, innovative and outstanding engineering talents by taking ‘fostering character and civic virtue’ as the guide, responding to changes and shaping the future as the construction concept, and inheritance and innovation, crossover and fusion, coordination and sharing as the principal approach". In this context, Tianjin University, as a traditional Chinese university with advantages in engineering, further launched the CCII (Coherent-Collaborative-Interdisciplinary-Innovation) program, raising the cultivation idea of integrating new liberal arts education, multidisciplinary engineering education and personalized professional education. As urban planning practice in China has undergone the evolution of "physical planning -- comprehensive strategic planning -- resource management-oriented planning", planning education has also experienced the transmutation process of "building foundation -- urban scientific foundation -- multi-disciplinary integration". As a characteristic and advantageous discipline of Tianjin University, the major of Urban and Rural Planning, in accordance with the "CCII Program of Tianjin University", aims to build China's top and world-class major, and implements the following educational reform measures: 1. Adding corresponding English courses, such as advanced course on GIS Analysis, courses on comparative studies in international planning involving ecological resources and the sociology of the humanities, etc. 2. Holding "Academician Forum", inviting international academicians to give lectures or seminars to track international frontier scientific research issues. 3. Organizing "International Joint Workshop" to provide students with international exchange and design practice platform. 4. Setting up a business practice base, so that students can find problems from practice and solve them in an innovative way. Through these measures, the Urban and Rural Planning major of Tianjin University has formed a talent training system with multi-disciplinary cross integration and orienting to the future science and technology.

Keywords: China, higher education reform, innovation, new engineering education, rural and urban planning, Tianjin University

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Authors: Dacheng Li, Bo Huang, Qinjin Han, Ming Li

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Remotely sensed imagery with the high spatial and temporal characteristics, which it is hard to acquire under the current land observation satellites, has been considered as a key factor for monitoring environmental changes over both global and local scales. On a basis of the limited high spatial-resolution observations, challenged studies called spatiotemporal fusion have been developed for generating high spatiotemporal images through employing other auxiliary low spatial-resolution data while with high-frequency observations. However, a majority of spatiotemporal fusion approaches yield to satisfactory assumption, empirical but unstable parameters, low accuracy or inefficient performance. Although the spatiotemporal fusion methodology via sparse representation theory has advantage in capturing reflectance changes, stability and execution efficiency (even more efficient when overcomplete dictionaries have been pre-trained), the retrieval of high-accuracy dictionary and its response to fusion results are still pending issues. In this paper, we employ additional image pairs (here each image-pair includes a Landsat Operational Land Imager and a Moderate Resolution Imaging Spectroradiometer acquisitions covering the partial area of Baotou, China) only into the coupled dictionary training process based on K-SVD (K-means Singular Value Decomposition) algorithm, and attempt to improve the fusion results of two existing sparse representation based fusion models (respectively utilizing one and two available image-pair). The results show that more eligible image pairs are probably related to a more accurate overcomplete dictionary, which generally indicates a better image representation, and is then contribute to an effective fusion performance in case that the added image-pair has similar seasonal aspects and image spatial structure features to the original image-pair. It is, therefore, reasonable to construct multi-dictionary training pattern for generating a series of high spatial resolution images based on limited acquisitions.

Keywords: spatiotemporal fusion, sparse representation, K-SVD algorithm, dictionary learning

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Authors: Ben Khayut, Lina Fabri, Maya Avikhana

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The models of the modern Artificial Narrow Intelligence (ANI) cannot: a) independently and continuously function without of human intelligence, used for retraining and reprogramming the ANI’s models, and b) think, understand, be conscious, cognize, infer, and more in state of Uncertainty, and changes in situations, and environmental objects. To eliminate these shortcomings and build a new generation of Artificial Intelligence systems, the paper proposes a Conception, Model, and Method of Computational Psycholinguistic Cognitive Situational-Fuzzy Self-Controlled Brain and Mind System (CPCSFSCBMSUU) using a neural network as its computational memory, operating under uncertainty, and activating its functions by perception, identification of real objects, fuzzy situational control, forming images of these objects, modeling their psychological, linguistic, cognitive, and neural values of properties and features, the meanings of which are identified, interpreted, generated, and formed taking into account the identified subject area, using the data, information, knowledge, and images, accumulated in the Memory. The functioning of the CPCSFSCBMSUU is carried out by its subsystems of the: fuzzy situational control of all processes, computational perception, identifying of reactions and actions, Psycholinguistic Cognitive Fuzzy Logical Inference, Decision making, Reasoning, Systems Thinking, Planning, Awareness, Consciousness, Cognition, Intuition, Wisdom, analysis and processing of the psycholinguistic, subject, visual, signal, sound and other objects, accumulation and using the data, information and knowledge in the Memory, communication, and interaction with other computing systems, robots and humans in order of solving the joint tasks. To investigate the functional processes of the proposed system, the principles of Situational Control, Fuzzy Logic, Psycholinguistics, Informatics, and modern possibilities of Data Science were applied. The proposed self-controlled System of Brain and Mind is oriented on use as a plug-in in multilingual subject Applications.

Keywords: computational brain, mind, psycholinguistic, system, under uncertainty

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Authors: Virupakshi Hiremata, Ratnakar M. Shet, Raghavendra Gunnaiah, Prashantha A.

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Muskmelon is a health-beneficial and refreshing dessert vegetable with a low shelf life. Mangalore melon, a genetic homeologue of muskmelon, has a shelf life of more than six months and is mostly used for culinary purposes. Understanding the genetics of shelf life, yield and yield-related traits and identification of markers linked to such traits is helpful in transfer of extended shelf life from Mangalore melon to the muskmelon through intra-specific hybridization. For QTL mapping, 276 F2 mapping population derived from the cross Arka Siri × SS-17 was genotyped with 40 polymorphic markers distributed across 12 chromosomes. The same population was also phenotyped for yield, shelf life and fruit quality traits. One major QTL (R2 >10) and fourteen minor QTLs (R2 <10) localized on four linkage groups, governing different traits were mapped in F2 mapping population developed from the intraspecific cross with a LOD > 5.5. The phenotypic varience explained by each locus varied from 3.63 to 10.97 %. One QTL was linked to shelf-life (qSHL-3-1), five QTLs were linked to TSS (qTSS-1-1, qTSS-3-3, qTSS-3-1, qTSS-3-2 and qTSS-1-2), two QTLs for flesh thickness (qFT-3-1, and qFT-3-2) and seven QTLs for fruit yield per vine (qFYV-3-1, qFYV-1-1, qFYV-3-1, qFYV1-1, qFYV-1-3, qFYV2-1 and qFYV6-1). QTL flanking markers may be used for marker assisted introgression of shelf life into muskmelon. Important QTL will be further fine-mapped for identifying candidate genes by QTLseq and RNAseq analysis. Fine-mapping of Important Quantitative Trait Loci (QTL) holds immense promise in elucidating the genetic basis of complex traits. Leveraging advanced techniques like QTLseq and RNA sequencing (RNA seq) is crucial for this endeavor. QTLseq combines next-generation sequencing with traditional QTL mapping, enabling precise identification of genomic regions associated with traits of interest. Through high-throughput sequencing, QTLseq provides a detailed map of genetic variations linked to phenotypic variations, facilitating targeted investigations. Moreover, RNA seq analysis offers a comprehensive view of gene expression patterns in response to specific traits or conditions. By comparing transcriptomes between contrasting phenotypes, RNA seq aids in pinpointing candidate genes underlying QTL regions. Integrating QTLseq with RNA seq allows for a multi-dimensional approach, coupling genetic variation with gene expression dynamics.

Keywords: QTL, shelf life, TSS, muskmelon and Mangalore melon

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Authors: Pesaru Vigneshwar Reddy, Parvathaneni Pavan

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Green organic chemistry which is the latest and one of the most researched topics now-a- days has been in demand since 1990’s. Majority of the research in green organic chemistry chemicals are some of the important starting materials for greater number of major chemical industries. The production of organic chemicals has raw materials (or) reagents for other application is major sector of manufacturing polymers, pharmaceuticals, pesticides, paints, artificial fibers, food additives etc. organic synthesis on a large scale compound to the labratory scale, involves the use of energy, basic chemical ingredients from the petro chemical sectors, catalyst and after the end of the reaction, seperation, purification, storage, packing distribution etc. During these processes there are many problems of health and safety for workers in addition to the environmental problems caused there by use and deposition as waste. Green chemistry with its 12 principles would like to see changes in conventional way that were used for decades to make synthetic organic chemical and the use of less toxic starting materials. Green chemistry would like to increase the efficiency of synthetic methods, to use less toxic solvents, reduce the stage of synthetic routes and minimize waste as far as practically possible. In this way, organic synthesis will be part of the effort for sustainable development Green chemistry is also interested for research and alternatives innovations on many practical aspects of organic synthesis in the university and research labaratory of institutions. By changing the methodologies of organic synthesis, health and safety will be advanced in the small scale laboratory level but also will be extended to the industrial large scale production a process through new techniques. The three key developments in green chemistry include the use of super critical carbondioxide as green solvent, aqueous hydrogen peroxide as an oxidising agent and use of hydrogen in asymmetric synthesis. It also focuses on replacing traditional methods of heating with that of modern methods of heating like microwaves traditions, so that carbon foot print should reduces as far as possible. Another beneficiary of this green chemistry is that it will reduce environmental pollution through the use of less toxic reagents, minimizing of waste and more bio-degradable biproducts. In this present paper some of the basic principles, approaches, and early achievements of green chemistry has a branch of chemistry that studies the laws of passing of chemical reactions is also considered, with the summarization of green chemistry principles. A discussion about E-factor, old and new synthesis of ibuprofen, microwave techniques, and some of the recent advancements also considered.

Keywords: energy, e-factor, carbon foot print, micro-wave, sono-chemistry, advancement

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Authors: Usama Massoud, Abeer A. Kenawy, El-Said A. Ragab, Abbas M. Abbas, Heba M. El-Kosery

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Vertical Electrical Sounding (VES) and Transient Electro Magnetic (TEM) survey have been applied for characterizing the groundwater aquifers at El Sadat industrial area. El-Sadat city is one of the most important industrial cities in Egypt. It has been constructed more than three decades ago at about 80 km northwest of Cairo along the Cairo–Alexandria desert road. Groundwater is the main source of water supplies required for domestic, municipal, and industrial activities in this area due to the lack of surface water sources. So, it is important to maintain this vital resource in order to sustain the development plans of this city. In this study, VES and TEM data were identically measured at 24 stations along three profiles trending NE–SW with the elongation of the study area. The measuring points were arranged in a grid like pattern with both inter-station spacing and line–line distance of about 2 km. After performing the necessary processing steps, the VES and TEM data sets were inverted individually to multi-layer models, followed by a joint inversion of both data sets. Joint inversion process has succeeded to overcome the model-equivalence problem encountered in the inversion of individual data set. Then, the joint models were used for the construction of a number of cross sections and contour maps showing the lateral and vertical distribution of the geo-electrical parameters in the subsurface medium. Interpretation of the obtained results and correlation with the available geological and hydrogeological information revealed TWO aquifer systems in the area. The shallow Pleistocene aquifer consists of sand and gravel saturated with fresh water and exhibits large thickness exceeding 200 m. The deep Pliocene aquifer is composed of clay and sand and shows low resistivity values. The water bearing layer of the Pleistocene aquifer and the upper surface of Pliocene aquifer are continuous and no structural features have cut this continuity through the investigated area.

Keywords: El Sadat city, joint inversion, VES, TEM

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Authors: Aron Witkowski, Andrzej Wodecki

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Purpose: This study aims to explore the feasibility and effectiveness of utilizing Generative Artificial Intelligence (GenAI) agents as product managers within the manufacturing sector. It seeks to evaluate whether current GenAI capabilities can fulfill the complex requirements of product management and deliver comparable outcomes to human counterparts. Study Design/Methodology/Approach: This research involved the creation of a support application for product managers, utilizing high-quality sources on product management and generative AI technologies. The application was designed to assist in various aspects of product management tasks. To evaluate its effectiveness, a study was conducted involving 10 experienced product managers from the manufacturing sector. These professionals were tasked with using the application and providing feedback on the tool's responses to common questions and challenges they encounter in their daily work. The study employed a mixed-methods approach, combining quantitative assessments of the tool's performance with qualitative interviews to gather detailed insights into the user experience and perceived value of the application. Findings: The findings reveal that GenAI-based product management agents exhibit significant potential in handling routine tasks, data analysis, and predictive modeling. However, there are notable limitations in areas requiring nuanced decision-making, creativity, and complex stakeholder interactions. The case study demonstrates that while GenAI can augment human capabilities, it is not yet fully equipped to independently manage the holistic responsibilities of a product manager in the manufacturing sector. Originality/Value: This research provides an analysis of GenAI's role in product management within the manufacturing industry, contributing to the limited body of literature on the application of GenAI agents in this domain. It offers practical insights into the current capabilities and limitations of GenAI, helping organizations make informed decisions about integrating AI into their product management strategies. Implications for Academic and Practical Fields: For academia, the study suggests new avenues for research in AI-human collaboration and the development of advanced AI systems capable of higher-level managerial functions. Practically, it provides industry professionals with a nuanced understanding of how GenAI can be leveraged to enhance product management, guiding investments in AI technologies and training programs to bridge identified gaps.

Keywords: generative artificial intelligence, GenAI, NPD, new product development, product management, manufacturing

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Authors: Brian Tung, Yam Wing Siu, Tsun Se Cheong

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Purpose: This research aims to explore how personal and environmental factors, especially the socio-economic changes and behavioral changes fostered by the COVID-19 outbreak pandemic, affect the financial vulnerability of a specific segment of people in financial distress. Innovative research methodology of machine learning will be applied to data collected from over 300 local individuals in Hong Kong seeking counseling or similar services in recent years. Results: First, machine learning has found that too much exposure to digital services and information on digitized services may lead to adverse effects on respondents’ financial vulnerability. Second, the improvement in financial literacy level provides benefits to the financially vulnerable group, especially those respondents who have started with a lower level. Third, serious addiction to digital technology can lead to worsened debt servicing ability. Machine learning also has found a strong correlation between debt servicing situations and income-seeking behavior as well as spending behavior. In addition, if the vulnerable groups are able to make appropriate investments, they can reduce the probability of incurring financial distress. Finally, being too active in borrowing and repayment can result in a higher likelihood of over-indebtedness. Conclusion: Findings can be employed in formulating a better counseling strategy for professionals. Debt counseling services can be more preventive in nature. For example, according to the findings, with a low level of financial literacy, the respondents are prone to overspending and unable to react properly to the e-marketing promotion messages pop-up from digital services or even falling into financial/investment scams. In addition, people with low levels of financial knowledge will benefit from financial education. Therefore, financial education programs could include tech-savvy matters as special features.

Keywords: personal finance, digitization of the economy, COVID-19 pandemic, addiction to digital technology, financial vulnerability

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Authors: Naila Safdar, Faria Riasat, Azra Yasmin

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Lychee is an emerging fruit crop in Pakistan. Two famous cultivars of lychee, Gola and Surakhi, were collected from Khanpur Orchard, Pakistan and their whole fruit (including peel, pulp and seed) was investigated for pomological features and therapeutic activities. Both cultivars differ in shape and size with Gola having large size (3.27cm length, 2.36cm width) and more flesh to seed ratio (8.65g). FTIR spectroscopy and phytochemical tests confirmed presence of different bioactive compounds like phenol, flavonoids, quinones, anthraquinones, tannins, glycosides, and alkaloids, in both lychee fruits. Atomic absorption spectroscopy indicated an increased amount of potassium, magnesium, sodium, iron, and calcium in Gola and Surakhi fruits. Small amount of trace metals, zinc and copper, were also detected in lychee fruit, while heavy metals lead, mercury, and nickel were absent. These two lychee cultivars were also screened for antitumor activity by Potato disc assay with maximum antitumor activity shown by aqueous extract of Surakhi seed (77%) followed by aqueous extract of Gola pulp (74%). Antimicrobial activity of fruit parts was checked by agar well diffusion method against six bacterial strains Enterococcus faecium, Enterococcus faecalis, Staphylococcus aureus, Bacillus subtilis, Bacillus sp. MB083, and Bacillus sp. MB141. Highest antimicrobial activity was shown by methanolic extract of Gola pulp (27mm ± 0.70) and seed (19.5mm ± 0.712) against Enterococcus faecalis. DPPH scavenging assay revealed highest antioxidant activity by aqueous extract of Gola peel (98.10%) followed by n-hexane extract of Surakhi peel (97.73%). Results obtained by reducing power assay also corroborated with the results of DPPH scavenging activity.

Keywords: antimicrobial evaluation, antitumor assay, gola, phytoconstituents, reactive oxygen species, Surakhi

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Authors: Aamna Tufail, Kajal Kotecha, Iordanis Toursounidis, Ravinder Pabla

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Introduction/Aims: Acute Myeloid Leukaemia (AML) is a part of leukaemic group of hematopoietic disorders with a varying range of presentations, including oro-facial manifestations. Early recognition and management are essential for favourable outcomes. Materials and Methods: We present our experience, clinical presentation, and clinical photographs of a patient with previously undiagnosed AML who presented with oral symptoms to the emergency department of our hospital. An analysis of clinical characteristics, diagnostic investigations, and management modalities was performed. Results/Statistics: A 58-year-old man presented to A&E reporting an 11-day history of right sided facial swelling, acute TMJ symptoms, and oral discomfort. A dentist ruled out acute dental causes one day post onset of symptoms. Initial assessment was anatomically inconsistent and did not reveal a routine oral or maxillofacial etiology. Detailed clinical examination demonstrated fever, generalised pallor, swelling and erythema of right nasolabial region, bilateral masseteric tenderness, intraoral palatal ecchymosis, palatal ulceration, buccal and labial petechiae, cervical lymphadenopathy, and haematoma on dorsum of right hand overlying right 2nd metacarpal joint. Suspecting a systemic medical cause, we requested haematological investigations, which revealed neutropenia, thrombocytopenia, and anaemia. Flow cytometry confirmed CD34 + AML. Oral discomfort was managed symptomatically. The patient was referred to a tertiary care centre for acute haematologic care, where he was treated with IV antibiotics and continuing cycles of chemotherapy. Conclusions/Clinical Relevance: Oro-facial manifestations may be the first clinical sign of AML. Awareness of its features is vital in early diagnosis. In this context, dentists and oral medicine specialists can play an important role in detecting clinical signs of haematological disorders such as AML.

Keywords: acute myeloid leukaemia, oral symptoms, ulceration, diagnosis, management

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Authors: Wenyan Xu, Rundong Wang, Chen Li, Yonghong Hu, Zhonghua Lu

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In the field of quantitative trading, it is common to find patterns in short-term volatile trends of the market. These patterns are known as High-Frequency (HF) risk factors, serving as effective indicators of future stock price volatility. However, in the past, these risk factors were usually generated by traditional financial models, and the validity of these risk factors is heavily based on domain-specific knowledge manually added instead of extensive market data. Inspired by symbolic regression (SR), the task of inferring mathematical laws from existing data, we take the extraction of formulaic risk factors from high-frequency trading (HFT) market data as an SR task. In this paper, we challenge the procedure of manually constructing risk factors and propose an end-to-end methodology, Intraday Risk Factor Transformer (IRFT) to directly predict the full formulaic factors, constants included. Specifically, we utilize a hybrid symbolic-numeric vocabulary where symbolic tokens denote operators/stock features and numeric tokens denote constants. Then, we train a Transformer model on the HFT dataset to directly generate complete formulaic HF risk factors without relying on the skeleton, which is a parametric function using a pre-defined list of operators – typically, the math operations (+, ×, /) and functions(√x, log x, cos x). It determines the general shape of the stock volatility law up to a choice of constants, e.g., f(x) = tan(ax+b) (x is the stock price). We further refine predicted constants(a,b) using the Broyden–Fletcher–Goldfarb–Shanno algorithm (BFGS) as informed guesses to mitigate non-linear issues. Compared to the 10 approaches in SRBench, which is a living benchmark for SR, IRFT gains a 30% excess investment return on the HS300 and S&P500 datasets, with inference times orders of magnitude faster than theirs in HF risk factor mining tasks.

Keywords: transformer, factor-mining language model, highfrequency risk factor collections

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Authors: Mohamed dammak

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Great attention has been paid to the design and synthesis of novel organic-inorganic compounds in recent decades because of their structural variety and the large diversity of atomic arrangements. In this work, the structure for the novel dimethyl aminopyridine tetrachlorocobaltate (C₇H₁₁N₂)₂CoCl₄ prepared by the slow evaporation method at room temperature has been successfully discussed. The X-ray diffraction results indicate that the hybrid material has a triclinic structure with a P space group and features a 0D structure containing isolated distorted [CoCl₄]2- tetrahedra interposed between [C7H11N²⁻]+ cations forming planes perpendicular to the c axis at z = 0 and z = ½. The effect of the synthesis conditions and the reactants used, the interactions between the cationic planes, and the isolated [CoCl4]2- tetrahedra are employing N-H...Cl and C-H…Cl hydrogen bonding contacts. The inspection of the Hirshfeld surface analysis helps to discuss the strength of hydrogen bonds and to quantify the inter-contacts. A phase transition was discovered by thermal analysis at 390 K, and comprehensive dielectric research was reported, showing a good agreement with thermal data. Impedance spectroscopy measurements were used to study the electrical and dielectric characteristics over a wide range of frequencies and temperatures, 40 Hz–10 MHz and 313–483 K, respectively. The Nyquist plot (Z" versus Z') from the complex impedance spectrum revealed semicircular arcs described by a Cole-Cole model. An electrical circuit consisting of a link of grain and grain boundary elements is employed. The real and imaginary parts of dielectric permittivity, as well as tg(δ) of (C₇H₁₁N₂)₂CoCl₄ at different frequencies, reveal a distribution of relaxation times. The presence of grain and grain boundaries is confirmed by the modulus investigations. Electric and dielectric analyses highlight the good protonic conduction of this material.

Keywords: organic-inorganic, phase transitions, complex impedance, protonic conduction, dielectric analysis

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Authors: Mequanent Wale Mekonen, Edoardo Otranto, Angela Alibrandi

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Diabetic kidney disease is one of the main microvascular complications caused by diabetes. Several clinical and biochemical variables are reported to be associated with diabetic kidney disease in people with type 2 diabetes. However, their interrelations could distort the effect estimation of these variables for the disease's progression. The objective of the study is to determine how the biochemical and clinical variables in people with type 2 diabetes are interrelated with each other and their effects on kidney disease progression through advanced statistical methods. First, principal component analysis was used to explore how the biochemical and clinical variables intercorrelate with each other, which helped us reduce a set of correlated biochemical variables to a smaller number of uncorrelated variables. Then, ordered logit regression models (cumulative, stage, and adjacent) were employed to assess the effect of biochemical and clinical variables on the order-level response variable (progression of kidney function) by considering the proportionality assumption for more robust effect estimation. This retrospective cross-sectional study retrieved data from a type 2 diabetic cohort in a polyclinic hospital at the University of Messina, Italy. The principal component analysis yielded three uncorrelated components. These are principal component 1, with negative loading of glycosylated haemoglobin, glycemia, and creatinine; principal component 2, with negative loading of total cholesterol and low-density lipoprotein; and principal component 3, with negative loading of high-density lipoprotein and a positive load of triglycerides. The ordered logit models (cumulative, stage, and adjacent) showed that the first component (glycosylated haemoglobin, glycemia, and creatinine) had a significant effect on the progression of kidney disease. For instance, the cumulative odds model indicated that the first principal component (linear combination of glycosylated haemoglobin, glycemia, and creatinine) had a strong and significant effect on the progression of kidney disease, with an effect or odds ratio of 0.423 (P value = 0.000). However, this effect was inconsistent across levels of kidney disease because the first principal component did not meet the proportionality assumption. To address the proportionality problem and provide robust effect estimates, alternative ordered logit models, such as the partial cumulative odds model, the partial adjacent category model, and the partial continuation ratio model, were used. These models suggested that clinical variables such as age, sex, body mass index, medication (metformin), and biochemical variables such as glycosylated haemoglobin, glycemia, and creatinine have a significant effect on the progression of kidney disease.

Keywords: diabetic kidney disease, ordered logit model, principal component analysis, type 2 diabetes

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Authors: G. Alston Rush, Gus A. Rush III, M. F. Horstemeyer

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This study compares the shell-facemask responses of four commonly used American football helmets, under the National Operating Committee on Standards for Athletic Equipment (NOCSAE) drop impact test method, to show that the test standard would more accurately simulate in-use conditions by modification to include the facemask. In our study, the need for a more vigorous systematic approach to football helmet testing procedures is emphasized by comparing the Head Injury Criterion (HIC), the Gadd Severity Index (SI), and peak acceleration values for different helmets at different locations on the helmet under modified NOCSAE standard drop tower tests. Drop tests were performed on the Rawlings Quantum Plus, Riddell 360, Schutt Ion 4D, and Xenith X2 helmets at eight impact locations, impact velocities of 5.46 and 4.88 meters per second, and helmet configurations with and without facemasks. Analysis of NOCSAE drop test results reveal significant differences (p < 0.05) for when the facemasks were attached to helmets, as compared to the NOCSAE Standard, without facemask configuration. The boundary conditions of the facemask attachment can have up to a 50% decrease (p < 0.001) in helmet performance with respect to peak acceleration. While generally, all helmets with the facemasks gave greater HIC, SI, and acceleration values than helmets without the facemasks, significant helmet dependent variations were observed across impact locations and impact velocities. The variations between helmet responses could be attributed to the unique design features of each helmet tested, which include different liners, chin strap attachments, and faceguard attachment systems. In summary, these comparative drop test results revealed that the current NOCSAE standard test methods need improvement by attaching the facemasks to helmets during testing. The modified NOCSAE football helmet standard test gives a more accurate representation of a helmet’s performance and its ability to mitigate the on-field impact.

Keywords: football helmet testing, gadd severity index, head injury criterion, mild traumatic brain injury

Procedia PDF Downloads 437

Authors: Nuran Öze

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People always want to be aware of what is happening around them. The nature of man constantly triggers the need for gathering information because of curiosity. The media has emerged to save people the need for information. It is known that the media has changed with the technological developments over time, diversified and, people's information needs are provided in different ways. Today, the Internet has become an integral part of everyday life. The invasion of the Internet into everyday life practices at this level affects every aspect of life. These effects cause people to change their life practices. Technological developments have always influenced of people, the way they reach information. Looking at the history of the media, the breaking point about the dissemination of information is seen as the invention of the machine of the printing press. This adventure that started with written media has now become a multi-dimensional structure. Written, audio, visual media has now changed shape with new technologies. Especially emerging of the internet to everyday life, of course, has effects on media field. 'New media' has appeared which contains most of traditional media features in its'. While in the one hand this transformation enables captures a harmony between traditional and new media, on the other hand, new media and traditional media are rivaling each other. The purpose of this study is to examine the problematic relationship between traditional media and new media through the news reading practices of individuals. This study can be evaluated as a kind of media sociology. To reach this aim, two different field researches will be done besides literature review. The research will be conducted in Northern Cyprus. Northern Cyprus Northern Cyprus is located in the Mediterranean Sea. North Cyprus is a country which is not recognized by any country except Turkey. Despite this, takes its share from all technological developments take place in the world. One of the field researches will consist of the questionnaires to be applied on media readers' news reading practices. This survey will be conducted in a social media environment. The second field survey will be conducted in the form of interviews with general editorials or news directors in traditional media. In the second field survey, in-depth interview method will be applied. As a result of these investigations, supporting sides between the new media and the traditional media and directions which contrast with each other will be revealed. In addition to that, it will try to understand the attitudes and perceptions of readers about the traditional media and the new media in this study.

Keywords: new media, news, North Cyprus, traditional media

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Authors: Nareshkumar Harale, B. B. Meshram

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The continued exponential growth of successful cyber intrusions against today’s businesses has made it abundantly clear that traditional perimeter security measures are no longer adequate and effective. We evolved the network trust architecture from trust-untrust to Zero-Trust, With Zero Trust, essential security capabilities are deployed in a way that provides policy enforcement and protection for all users, devices, applications, data resources, and the communications traffic between them, regardless of their location. Information exchange over the Internet, in spite of inclusion of advanced security controls, is always under innovative, inventive and prone to cyberattacks. TCP/IP protocol stack, the adapted standard for communication over network, suffers from inherent design vulnerabilities such as communication and session management protocols, routing protocols and security protocols are the major cause of major attacks. With the explosion of cyber security threats, such as viruses, worms, rootkits, malwares, Denial of Service attacks, accomplishing efficient and effective intrusion detection and prevention is become crucial and challenging too. In this paper, we propose a design and analysis model for next generation network intrusion detection and protection system as part of layered security strategy. The proposed system design provides intrusion detection for wide range of attacks with layered architecture and framework. The proposed network intrusion classification framework deals with cyberattacks on standard TCP/IP protocol, routing protocols and security protocols. It thereby forms the basis for detection of attack classes and applies signature based matching for known cyberattacks and data mining based machine learning approaches for unknown cyberattacks. Our proposed implemented software can effectively detect attacks even when malicious connections are hidden within normal events. The unsupervised learning algorithm applied to network audit data trails results in unknown intrusion detection. Association rule mining algorithms generate new rules from collected audit trail data resulting in increased intrusion prevention though integrated firewall systems. Intrusion response mechanisms can be initiated in real-time thereby minimizing the impact of network intrusions. Finally, we have shown that our approach can be validated and how the analysis results can be used for detecting and protection from the new network anomalies.

Keywords: network intrusion detection, network intrusion prevention, association rule mining, system analysis and design

Procedia PDF Downloads 217

Authors: Sathwik Sarvadevabhatla Kasyap, Kostas Senetakis

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The mechanical behavior of geological materials is very complex, and this complexity is related to the discrete nature of soils and rocks. Characteristics of a material at the grain scale such as particle size and shape, surface roughness and morphology, and particle contact interface are critical to evaluate and better understand the behavior of discrete materials. This study investigates experimentally the micro-mechanical behavior of quartz sand grains with emphasis on the influence of the presence of microparticles in their contact region. The outputs of the study provide some fundamental insights on the contact mechanics behavior of artificially coated grains and can provide useful input parameters in the discrete element modeling (DEM) of soils. In nature, the contact interfaces between real soil grains are commonly observed with microparticles. This is usually the case of sand-silt and sand-clay mixtures, where the finer particles may create a coating on the surface of the coarser grains, altering in this way the micro-, and thus the macro-scale response of geological materials. In this study, the micro-mechanical behavior of Leighton Buzzard Sand (LBS) quartz grains, with interference of different microparticles at their contact interfaces is studied in the laboratory using an advanced custom-built inter-particle loading apparatus. Special techniques were adopted to develop the coating on the surfaces of the quartz sand grains so that to establish repeatability of the coating technique. The characterization of the microstructure of coated particles on their surfaces was based on element composition analyses, microscopic images, surface roughness measurements, and single particle crushing strength tests. The mechanical responses such as normal and tangential load – displacement behavior, tangential stiffness behavior, and normal contact behavior under cyclic loading were studied. The behavior of coated LBS particles is compared among different classes of them and with pure LBS (i.e. surface cleaned to remove any microparticles). The damage on the surface of the particles was analyzed using microscopic images. Extended displacements in both normal and tangential directions were observed for coated LBS particles due to the plastic nature of the coating material and this varied with the variation of the amount of coating. The tangential displacement required to reach steady state was delayed due to the presence of microparticles in the contact region of grains under shearing. Increased tangential loads and coefficient of friction were observed for the coated grains in comparison to the uncoated quartz grains.

Keywords: contact interface, microparticles, micro-mechanical behavior, quartz sand

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Authors: Van Trieu, Shouhuai Xu, Yusheng Feng

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Tracking attack trajectories can be difficult, with limited information about the nature of the attack. Even more difficult as attack information is collected by Intrusion Detection Systems (IDSs) due to the current IDSs having some limitations in identifying malicious and anomalous traffic. Moreover, IDSs only point out the suspicious events but do not show how the events relate to each other or which event possibly cause the other event to happen. Because of this, it is important to investigate new methods capable of performing the tracking of attack trajectories task quickly with less attack information and dependency on IDSs, in order to prioritize actions during incident responses. This paper proposes a two-level graph causality framework for tracking attack trajectories in internet networks by leveraging observable malicious behaviors to detect what is the most probable attack events that can cause another event to occur in the system. Technically, given the time series of malicious events, the framework extracts events with useful features, such as attack time and port number, to apply to the conditional independent tests to detect the relationship between attack events. Using the academic datasets collected by IDSs, experimental results show that the framework can quickly detect the causal pairs that offer meaningful insights into the nature of the internet network, given only reasonable restrictions on network size and structure. Without the framework’s guidance, these insights would not be able to discover by the existing tools, such as IDSs. It would cost expert human analysts a significant time if possible. The computational results from the proposed two-level graph network model reveal the obvious pattern and trends. In fact, more than 85% of causal pairs have the average time difference between the causal and effect events in both computed and observed data within 5 minutes. This result can be used as a preventive measure against future attacks. Although the forecast may be short, from 0.24 seconds to 5 minutes, it is long enough to be used to design a prevention protocol to block those attacks.

Keywords: causality, multilevel graph, cyber-attacks, prediction

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Authors: Mahadehe Hassan

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In most countries manufacturing, trading and distribution of gasoline and diesel fuels belongs to the most important sectors of national economy. For Bangladesh, a robust, well-functioning, secure and smartly managed national fuel distribution chain is an essential precondition for achieving Government top priorities in development and modernization of transportation infrastructure, protection of national environment and population health as well as, very importantly, securing due tax revenue for the State Budget. Bangladesh is a developing country with complex fuel supply network, high fuel taxes incidence and – till now - limited possibilities in application of modern, automated technologies for Government national fuel market control. Such environment allows dishonest physical and legal persons and organized criminals to build and profit from illegal fuel distribution schemes and fuel illicit trade. As a result, the market transparency and the country attractiveness for foreign investments, law-abiding economic operators, national consumers, State Budget and the Government ability to finance development projects, and the country at large suffer significantly. Research shows that over 50% of retail petrol stations in major agglomerations of Bangladesh sell adulterated fuels and/or cheat customers on the real volume of the fuel pumped into their vehicles. Other forms of detected fuel illicit trade practices include misdeclaration of fuel quantitative and qualitative parameters during internal transit and selling of non-declared and smuggled fuels. The aim of the study is to recommend the implementation of a National Fuel Distribution Integrity Program (FDIP) in Bangladesh to address and resolve fuel adulteration and illicit trade problems. The program should be customized according to the specific needs of the country and implemented in partnership with providers of advanced technologies. FDIP should enable and further enhance capacity of respective Bangladesh Government authorities in identification and elimination of all forms of fuel illicit trade swiftly and resolutely. FDIP high-technology, IT and automation systems and secure infrastructures should be aimed at the following areas (1) fuel adulteration, misdeclaration and non-declaration; (2) fuel quality and; (3) fuel volume manipulation at retail level. Furthermore, overall concept of FDIP delivery and its interaction with the reporting and management systems used by the Government shall be aligned with and support objectives of the Vision 2041 and Smart Bangladesh Government programs.

Keywords: fuel adulteration, octane, kerosene, diesel, petrol, pollution, carbon emissions

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Authors: Patricia Sumod

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There is a unique movement of fashion that features a trend around secondhand clothing. This is especially observed in the lifestyles of the millennials, where the concept of reusing apparel and accessories is noticeable and, therefore, slowly diminishing the high consumption of fast fashion and generating environmental awareness. This paper will focus on how this clothing trend influences and engages consumers in buying secondhand clothing and creating fashionable looks simultaneously. To further examine the millennials’ motivation towards consumption and using secondhand fashion, a concept as a trendsetter, this paper will take a closer look at their idea of concern for the environment. Considering second-hand clothing is a sustainable consumption practice, it will investigate the role of social influencers, trendsetters, and millennials in overall fashion consumption in this context. This study aims to understand how secondhand clothing and millennials differ from other consumers regarding the perception of fast-depleting natural resources, price sensitivity, vintage attachments, and psychographics. Secondly, the paper will also present the connection of emotion between millennials and secondhand clothing that may not be necessarily purchased but received. This study will reflect on the already identified influences in increased purchase behavior and an uncharted positive relationship between the consumer and the products. This behavior will further formulate into a habit by consumer segments, creating an expanded market for secondhand clothing. There is no definite indication that fast fashion will cease to exist, but slowing its rapid movement is an attempt to work toward a sustainable future. The conclusion will present possibilities for consumers to engage in C2C online interaction, thereby reinforcing a notable change in consumer behavior and attitude in contradiction to today’s extreme consumerism and willingness to be adaptable to a minimalist way of life. Fashion brands will then begin a new forecast to actively accommodate the new millennial concept of fashion that will advertise more concern than insatiability. The research will be with literature from various authors, insights provided by researchers on this new wave of consumers, and a qualitative approach with face-to-face interviews with a sample group who are in the practice of secondhand clothing consumption.

Keywords: second-hand clothing, millennials, sustainability, consumption practice, fashion environment.

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Authors: Radu Deju, Carmen Mustata

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The VVR-S nuclear research reactor owned by Horia Hubulei National Institute of Physics and Nuclear Engineering (IFIN-HH) was designed for research and radioisotope production, being permanently shut-down in 2002, after 40 years of operation. All amount of the nuclear spent fuel S-36 and EK-10 type was returned to Russian Federation (first in 2009 and last in 2012), and the radioactive waste resulted from the reprocessing of it will remain permanently in the Russian Federation. The decommissioning strategy chosen is immediate dismantling. At this moment, the radionuclides with half-life shorter than 1 year have a minor contribution to the contamination of materials and equipment used in reactor department. The decommissioning of the reactor has started in 2010 and is planned to be finalized in 2020, being the first nuclear research reactor that has started the decommissioning project from the South-East of Europe. The management system applied in the decommissioning of the VVR-S research reactor integrates all common elements of management: nuclear safety, occupational health and safety, environment, quality- compliance with the requirements for decommissioning activities, physical protection and economic elements. This paper presents the application of integrated management system in decommissioning of systems, structures, equipment and components (SSEC) from pumps room, including the management of the resulted radioactive waste. The primary cooling system of this type of reactor includes circulation pumps, heat exchangers, degasser, filter ion exchangers, piping connection, drainage system and radioactive leaks. All the decommissioning activities of primary circuit were performed in stage 2 (year 2014), and they were developed and recorded according to the applicable documents, within the requirements of the Regulatory Body Licenses. In the presentation there will be emphasized how the integrated management system provisions are applied in the dismantling of the primary cooling system, for elaboration, approval, application of necessary documentation, records keeping before, during and after the dismantling activities. Radiation protection and economics are the key factors for the selection of the proper technology. Dedicated and advanced technologies were chosen to perform specific tasks. Safety aspects have been taken into consideration. Resource constraints have also been an important issue considered in defining the decommissioning strategy. Important aspects like radiological monitoring of the personnel and areas, decontamination, waste management and final characterization of the released site are demonstrated and documented.

Keywords: decommissioning, integrated management system, nuclear reactor, waste management

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Authors: Yun-Hsiang Lee

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Cancer is the main cause of death worldwide. With advances in medical technology, immunotherapy, which is a newly developed advanced treatment, is currently a crucial cancer treatment option. For better quality cancer care, the ability to communicate and critical thinking plays a central role in clinical oncology settings. However, few studies have explored the impact of communication skills on immunotherapy-related issues and their related factors. This study was to (i) explore the current status of communication skill ability for immunotherapy-related issues, self-efficacy for immunotherapy-related care, and critical thinking ability; and (ii) identify factors related to communication skill ability. This is a cross-sectional study. Oncology nurses were recruited from the Taiwan Oncology Nursing Society, in which nurses came from different hospitals distributed across four major geographic regions (North, Center, South, East) of Taiwan. A total of 123 oncology nurses participated in this study. A set of questionnaires were used for collecting data. Communication skill ability for immunotherapy issues, self-efficacy for immunotherapy-related care, critical thinking ability, and background information were assessed in this survey. Independent T-test and one-way ANOVA were used to examine different levels of communication skill ability based on nurses having done oncology courses (yes vs. no) and education years (< 1 year, 1-3 years, and > 3 years), respectively. Spearman correlation was conducted to understand the relationships between communication skill ability and other variables. Among the 123 oncology nurses in the current study, the majority of them were female (98.4%), and most of them were employed at a hospital in the North (46.8%) of Taiwan. Most of them possessed a university degree (78.9%) and had at least 3 years of prior work experience (71.7%). Forty-three of the oncology nurses indicated in the survey that they had not received oncology nurses-related training. Those oncology nurses reported moderate to high levels of communication skill ability for immunotherapy issues (mean=4.24, SD=0.7, range 1-5). Nurses reported moderate levels of self-efficacy for immunotherapy-related care (mean=5.20, SD=1.98, range 0-10) and also had high levels of critical thinking ability (mean=4.76, SD=0.60, range 1-6). Oncology nurses who had received oncology training courses had significantly better communication skill ability than those who had not received oncology training. Oncology nurses who had higher work experience (1-3 years, or > 3 years) had significantly higher levels of communication skill ability for immunotherapy-related issues than those with lower work experience (<1 year). When those nurses reported better communication skill ability, they also had significantly better self-efficacy (r=.42, p<.01) and better critical thinking ability (r=.47, p<.01). Taken altogether, courses designed to improve communication skill ability for immunotherapy-related issues can make a significant impact in clinical settings. Communication skill ability for oncology nurses is the major factor associated with self-efficacy and critical thinking, especially for those with lower work experience (< 1 year).

Keywords: communication skills, critical thinking, immunotherapy, oncology nurses, self-efficacy

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Authors: Akbar Nawaz Khan, Abdul Ghaffar, Muhammad Naeem Riaz

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The study was conducted to investigate the phenotypic features, morphometry and production potentialities of indigenous naked neck chicken (NN) of Pakistan under intensive management condition. A total of 35 NN chicks were randomly selected, and the experiment was performed at Poultry and wildlife research section NARC Islamabad for a period of 22 weeks. The predominant plumage color was black and golden while skin color was observed white. The average shank length, leg length, thigh length, keel length, chest breadth, head width, wing space, wing length, body length, body girth, body height and pubic bone width in adult males and females were 69.19 ± 3.34mm, 117.93 ± 4.42mm, 117.93 ± 4.42mm, 90.87 ± 6.53mm, 95.03 ± 4.56mm, 49.77 ± 2.53mm, 30.63 ± 1.50cm, 27.24 ± 2.71cm, 18.88 ± 0.65cm, 17.77 ± 1.01cm, 25.96 ± 0.56cm, 47.81 ± 1.41cm and 35.69 ± 4.09mm respectively. The average age and live body weight of NN chicken at sexual maturity were recorded as 165.85 days and 1269.38 g. While hen-day egg production of NN was recorded as 45%. The present study was aimed to investigate the existence of polymorphism at IGF-I gene in indigenous naked neck chicken through PCR based Restriction Fragment Length Polymorphism. Based on restriction analysis using Hinf I restriction enzyme, three genotypes were detected designated as AA, AC, and CC. Restriction analysis of PCR amplified product showed the presence of DNA fragments of 622, 378, 244 and 191, (genotypes). The PCR-RFLP analysis is easy, cost effective method which permits the easy characterization of IGF-I gene. This showed the investigated IGF-I genes can serve as good molecular markers for marker assisted selection (MAS) concerning growth related traits in chicken.

Keywords: Desi chicken, naked neck, morphology, morphometry, production potential, egg traits, egg geometry, IGF-I, growth, PCR- RFLP, chicken

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Authors: Symbat Moldabekova

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This research explores the practice of decision-making in commercial banks in Kazakhstan. It focuses on recent technologies, such as contactless payments and QR code, and uses interviews with bank executives and industry practitioners to gain an understanding of how decisions are made and the role of financial assessment methods. The aim of the research is (1) to study the importance of financial techniques to evaluate IT investments; (2) to understand the role of different expert groups; (3) to explore how market trends and industry features affect decisions on IT; (4) to build a model that defines the real practice of decision-making on IT in commercial banks in Kazakhstan. The theoretical framework suggests that decision-making on IT is a socially constructed process, where actor groups with different background interact and negotiate with each other to develop a shared understanding of IT and to make more effective decisions. Theory and observations suggest that the more parties involved in the process of decision-making, the higher the possibility of disagreements between them. As each actor group has their views on the rational decision on an IT project, it is worth exploring how the final decision is made in practice. Initial findings show that the financial assessment methods are used as a guideline and do not play a big role in the final decision. The commercial banks of Kazakhstan tend to study experience of neighboring countries before adopting innovation. Implementing contactless payments is widely regarded as pinnacle success factor due to increasing competition in the market. First-to-market innovations are considered as priorities therefore, such decisions can be made with exemption of some certain actor groups from the process. Customers play significant role and they participate in testing demo versions of the products before bringing innovation to the market. The study will identify the viewpoints of actors in the banking sector on a rational decision, and the ways decision-makers from a variety of disciplines interact with each other in order to make a decision on IT in retail banks.

Keywords: actor groups, decision making, technology investment, retail banks

Procedia PDF Downloads 108