Search results for: clinical decision support systems

Authors: S. Valarmathi, P. B. Harathi, R. Sridhar, S. Balasubramanian

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Machine learning tools in medical diagnosis is increasing due to the improved effectiveness of classification and recognition systems to help medical experts in diagnosing breast cancer. In this study, ID3 chooses the splitting attribute with the highest gain in information, where gain is defined as the difference between before the split versus after the split. It is applied for age, location, taluk, stage, year, period, martial status, treatment, heredity, sex, and habitat against Very Serious (VS), Very Serious Moderate (VSM), Serious (S) and Not Serious (NS) to calculate the gain of information. The ranked histogram gives the gain of each field for the breast cancer data. The doctors use TNM staging which will decide the risk level of the breast cancer and play an important decision making field in fuzzy logic for perception based measurement. Spatial risk area (taluk) of the breast cancer is calculated. Result clearly states that Coimbatore (North and South) was found to be risk region to the breast cancer than other areas at 20% criteria. Weighted value of taluk was compared with criterion value and integrated with Map Object to visualize the results. ID3 algorithm shows the high breast cancer risk regions in the study area. The study has outlined, discussed and resolved the algorithms, techniques / methods adopted through soft computing methodology like ID3 algorithm for prognostic decision making in the seriousness of the breast cancer.

Keywords: ID3 algorithm, breast cancer, fuzzy logic, MATLAB

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Authors: Salisu Ibrahim

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The paper studies the commutativity associated with fractional order linear time-varying systems (LTVSs), which is an important area of study in control systems engineering. In this paper, we explore the properties of these systems and their ability to commute. We proposed the necessary and sufficient condition for commutativity for fractional order LTVSs. Through a simulation and mathematical analysis, we demonstrate that these systems exhibit commutativity under certain conditions. Our findings have implications for the design and control of fractional order systems in practical applications, science, and engineering. An example is given to show the effectiveness of the proposed method which is been computed by Mathematica and validated by the use of Matlab (Simulink).

Keywords: fractional differential equation, physical systems, equivalent circuit, and analog control

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Authors: S. Alyami, S. Mohammad

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These Risk management practices have a significant impact on construction SMEs. The effective utilisation of these practices depends on culture change in order to optimise decision making for critical activities within construction projects. Thus, successful implementation of empowerment strategies would enhance operational employees to participate in effective decision making. However, there remain many barriers to individuals and organisations within empowerment strategies that require empirical investigation before the industry can benefit from their implementation. Gaps in understanding the relationship between employee empowerment and risk management practices still exist. This research paper aims to examine the impact of the structural empowerment on risk management practices in construction SMEs. The questionnaire has been distributed to participants (162 employees) that involve projects and civil engineers within a case study from Saudi construction SMEs. Partial least squares based structural equation modeling (PLS-SEM) was utilised to perform analysis. The results reveal a positive relationship between empowerment and risk management practices. The study shows how structural empowerment contributes to operational employees in risk management practices through involving activities such as decision making, self-efficiency, and autonomy. The findings of this study will contribute to close the current gaps in the construction SMEs context.

Keywords: construction SMEs, culture, decision making, empowerment, risk management

Procedia PDF Downloads 119

Authors: Matthew Fleet, Savannah Elliott

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Background: This study investigates the use of teaching and learning to meet the needs of deaf children in the UK PE curriculum. Research has illustrated that deaf students in mainstream schools do not receive sufficient support from teachers in lessons. This research examines the impact of different types of hearing loss and its implications within Physical Education (PE) in secondary schools. Purpose: The purpose of this study is to highlight challenges PE teachers face and make recommendations for more inclusive learning environments for deaf students. The aims and objectives of this research are: to critically analyse the current situation for deaf students accessing the PE curriculum, by identifying barriers deaf students face; to identify the challenges for PE teachers in providing appropriate support for deaf students; to provide recommendations for deaf awareness training, to enhance PE teachers’ understanding and knowledge. Method: Semi-structured interviews collected data from both PE teachers and deaf students, to examine: the support available and coping mechanisms deaf students use when they do not receive support; strategies PE teachers use to provide support for deaf students; areas for improvement and potential strategies PE teachers can apply to their practice. Results & Conclusion: The findings from the study concluded that PE teachers were inconsistent in providing appropriate support for deaf students in PE lessons. Evidence illustrated that PE teachers had limited exposure to deaf awareness training. This impacted on their ability to support deaf students effectively. Communication was a frequent barrier for deaf students, affecting their ability to retain and learn information. Also, the use of assistive technology was found to be compromised in practical PE lessons.

Keywords: physical education, deaf, inclusion, education

Procedia PDF Downloads 155

Authors: Sara Assi, Berthe Hayar, Claudio Pisano, Nadine Darwiche, Walid Saad

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Nanomedicine, the application of nanotechnology to medicine, is an emerging discipline that has gained significant attention in recent years. Current breakthroughs in nanomedicine have paved the way to develop effective drug delivery systems that can be used to target cancer. The use of nanotechnology provides effective drug delivery, enhanced stability, bioavailability, and permeability, thereby minimizing drug dosage and toxicity. As such, the use of nanoparticle (NP) formulations in drug delivery has been applied in various cancer models and have shown to improve the ability of drugs to reach specific targeted sites in a controlled manner. Cancer is one of the major causes of death worldwide; in particular, colorectal cancer (CRC) is the third most common type of cancer diagnosed amongst men and women and the second leading cause of cancer related deaths, highlighting the need for novel therapies. Retinoids, consisting of natural and synthetic derivatives, are a class of chemical compounds that have shown promise in preclinical and clinical cancer settings. However, retinoids are limited by their toxicity and resistance to treatment. To overcome this resistance, various synthetic retinoids have been developed, including the adamantyl retinoid ST1926, which is a potent anti-cancer agent. However, due to its limited bioavailability, the development of ST1926 has been restricted in phase I clinical trials. We have previously investigated the preclinical efficacy of ST1926 in CRC models. ST1926 displayed potent inhibitory and apoptotic effects in CRC cell lines by inducing early DNA damage and apoptosis. ST1926 significantly reduced the tumor doubling time and tumor burden in a xenograft CRC model. Therefore, we developed ST1926-NPs and assessed their efficacy in CRC models. ST1926-NPs were produced using Flash NanoPrecipitation with the amphiphilic diblock copolymer polystyrene-b-ethylene oxide and cholesterol as a co-stabilizer. ST1926 was formulated into NPs with a drug to polymer mass ratio of 1:2, providing a stable formulation for one week. The contin ST1926-NP diameter was 100 nm, with a polydispersity index of 0.245. Using the MTT cell viability assay, ST1926-NP exhibited potent anti-growth activities as naked ST1926 in HCT116 cells, at pharmacologically achievable concentrations. Future studies will be performed to study the anti-tumor activities and mechanism of action of ST1926-NPs in a xenograft mouse model and to detect the compound and its glucuroconjugated form in the plasma of mice. Ultimately, our studies will support the use of ST1926-NP formulations in enhancing the stability and bioavailability of ST1926 in CRC.

Keywords: nanoparticles, drug delivery, colorectal cancer, retinoids

Procedia PDF Downloads 101

Authors: Martha E. Aguiar-Barrera, Humberto Gutierrez-Pulido, Veronica Vargas-Alejo

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Identifying and modeling random phenomena is a fundamental cognitive process to understand and transform reality. Recognizing situations governed by chance and giving them a scientific interpretation, without being carried away by beliefs or intuitions, is a basic training for citizens. Hence the importance of generating teaching-learning processes, supported using technology, paying attention to model creation rather than only executing mathematical calculations. In order to develop the student's knowledge about basic probability distributions and decision making; in this work a model eliciting activity (MEA) is reported. The intention was applying the Model and Modeling Perspective to design an activity related to civil engineering that would be understandable for students, while involving them in its solution. Furthermore, the activity should imply a decision-making challenge based on sample data, and the use of the computer should be considered. The activity was designed considering the six design principles for MEA proposed by Lesh and collaborators. These are model construction, reality, self-evaluation, model documentation, shareable and reusable, and prototype. The application and refinement of the activity was carried out during three school cycles in the Probability and Statistics class for Civil Engineering students at the University of Guadalajara. The analysis of the way in which the students sought to solve the activity was made using audio and video recordings, as well as with the individual and team reports of the students. The information obtained was categorized according to the activity phase (individual or team) and the category of analysis (sample, linearity, probability, distributions, mechanization, and decision-making). With the results obtained through the MEA, four obstacles have been identified to understand and apply the binomial distribution: the first one was the resistance of the student to move from the linear to the probabilistic model; the second one, the difficulty of visualizing (infering) the behavior of the population through the sample data; the third one, viewing the sample as an isolated event and not as part of a random process that must be viewed in the context of a probability distribution; and the fourth one, the difficulty of decision-making with the support of probabilistic calculations. These obstacles have also been identified in literature on the teaching of probability and statistics. Recognizing these concepts as obstacles to understanding probability distributions, and that these do not change after an intervention, allows for the modification of these interventions and the MEA. In such a way, the students may identify themselves the erroneous solutions when they carrying out the MEA. The MEA also showed to be democratic since several students who had little participation and low grades in the first units, improved their participation. Regarding the use of the computer, the RStudio software was useful in several tasks, for example in such as plotting the probability distributions and to exploring different sample sizes. In conclusion, with the models created to solve the MEA, the Civil Engineering students improved their probabilistic knowledge and understanding of fundamental concepts such as sample, population, and probability distribution.

Keywords: linear model, models and modeling, probability, randomness, sample

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Authors: Tamara Trček Pečak, Andrej Mohar, Denis Trček

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This article investigates the latest technological means, which deploy smart structures that are based on (advanced) wireless sensors technologies and ubiquitous computing in general in order to support the above mentioned decision making. Based on two years of in-field research experiences it gives their analysis for these kinds of purposes and provides appropriate architectures and architectural solutions. Moreover, the directions for future research are stated, because these technologies are currently the most promising ones to enable cost-effective preservation of cultural heritage not only in uncontrolled places, but also in general.

Keywords: smart structures, wireless sensors, sensors networks, green computing, cultural heritage preservation, monitoring, cost effectiveness

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Authors: Seon-Young Lee, Harkiran Sagoo, Katherine Whitehurst, Georgina Wellstead, Alexander Fowler, Riaz Agha, Dennis Orgill

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Introduction: Systematic reviews attempt to answer research questions by synthesising the data within primary papers. They are an increasingly important tool within evidence-based medicine, guiding clinical practice, future research and healthcare policy. We sought to determine the reporting quality of recent systematic reviews in plastic surgery. Methods: This systematic review was conducted in line with the Cochrane handbook, reported in line with the PRISMA statement and registered at the ResearchRegistry (UIN: reviewregistry18). MEDLINE and EMBASE databases were searched in 2013 and 2014 for systematic reviews by five major plastic surgery journals. Screening, identification and data extraction was performed independently by two teams. Results: From an initial set of 163 articles, 79 met the inclusion criteria. The median PRISMA score was 16 out of 27 items (59.3%; range 6-26, 95% CI 14-17). Compliance between individual PRISMA items showed high variability. It was poorest for items related to the use of review protocol (item 5; 5%) and presentation of data on risk of bias of each study (item 19; 18%), while being the highest for description of rationale (item 3; 99%) and sources of funding and other support (item 27; 95%), and for structured summary in the abstract (item 2; 95%). Conclusion: The reporting quality of systematic reviews in plastic surgery requires improvement. ‘Hard-wiring’ of compliance through journal submission systems, as well as improved education, awareness and a cohesive strategy among all stakeholders is called for.

Keywords: PRISMA, reporting quality, plastic surgery, systematic review, meta-analysis

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Authors: Grace Omowunmi Soyebi

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A computerized medical record system is a collection of medical information about a person that is stored on a computer. One principal problem of most hospitals in rural areas is using the file management system for keeping records. A lot of time is wasted when a patient visits the hospital, probably in an emergency, and the nurse or attendant has to search through voluminous files before the patient's file can be retrieved, this may cause an unexpected to happen to the patient. This Data Mining application is to be designed using a Structured System Analysis and design method which will help in a well-articulated analysis of the existing file management system, feasibility study, and proper documentation of the Design and Implementation of a Computerized medical record system. This Computerized system will replace the file management system and help to quickly retrieve a patient's record with increased data security, access clinical records for decision-making, and reduce the time range at which a patient gets attended to.

Keywords: programming, computing, data, innovation

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Authors: Guldana Zhigerbayeva, Ming Yang

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Transportation of hazardous materials (HAZMAT) is inevitable in the process industries. The statistics show a significant number of accidents has occurred during the transportation of HAZMAT. This makes risk management of HAZMAT transportation an important topic. The tree-based methods including fault-trees, event-trees and cause-consequence analysis, and Bayesian network, have been applied to risk management of HAZMAT transportation. However, there is limited work on the development of a systematic approach. The existing approaches fail to build up the linkages between the regulatory requirements and the safety measures development. The analysis of historical data from the past accidents’ report databases would limit our focus on the specific incidents and their specific causes. Thus, we may overlook some essential elements in risk management, including regulatory compliance, field expert opinions, and suggestions. A systematic approach is needed to translate the regulatory requirements of HAZMAT transportation into specified safety measures (both technical and administrative) to support the risk management process. This study aims to first adapt the House of Quality (HoQ) to House of Safety (HoS) and proposes a new approach- Safety Function Deployment (SFD). The results of SFD will be used in a multi-criteria decision-support system to develop find an optimal route for HazMats transportation. The proposed approach will be demonstrated through a hypothetical transportation case in Kazakhstan.

Keywords: hazardous materials, risk assessment, risk management, quality function deployment

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Authors: Elaheh Talebi, Fariba Yavari, Lucy Philip, Lesley Town

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The mining industry generates vast amounts of data, necessitating robust data management systems and advanced analytics tools to achieve better decision-making processes in the development of mining production and maintaining safety. This paper highlights the advantages of Power BI, a powerful intelligence tool, over traditional Excel-based approaches for effectively managing and harnessing mining data. Power BI enables professionals to connect and integrate multiple data sources, ensuring real-time access to up-to-date information. Its interactive visualizations and dashboards offer an intuitive interface for exploring and analyzing geotechnical data. Advanced analytics is a collection of data analysis techniques to improve decision-making. Leveraging some of the most complex techniques in data science, advanced analytics is used to do everything from detecting data errors and ensuring data accuracy to directing the development of future project phases. However, while Power BI is a robust tool, specific visualizations required by geotechnical engineers may have limitations. This paper studies the capability to use Python or R programming within the Power BI dashboard to enable advanced analytics, additional functionalities, and customized visualizations. This dashboard provides comprehensive tools for analyzing and visualizing key geotechnical data metrics, including spatial representation on maps, field and lab test results, and subsurface rock and soil characteristics. Advanced visualizations like borehole logs and Stereonet were implemented using Python programming within the Power BI dashboard, enhancing the understanding and communication of geotechnical information. Moreover, the dashboard's flexibility allows for the incorporation of additional data and visualizations based on the project scope and available data, such as pit design, rock fall analyses, rock mass characterization, and drone data. This further enhances the dashboard's usefulness in future projects, including operation, development, closure, and rehabilitation phases. Additionally, this helps in minimizing the necessity of utilizing multiple software programs in projects. This geotechnical dashboard in Power BI serves as a user-friendly solution for analyzing, visualizing, and communicating both new and historical geotechnical data, aiding in informed decision-making and efficient project management throughout various project stages. Its ability to generate dynamic reports and share them with clients in a collaborative manner further enhances decision-making processes and facilitates effective communication within geotechnical projects in the mining industry.

Keywords: geotechnical data analysis, power BI, visualization, decision-making, mining industry

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Authors: Tracey Estriplet-Adams

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This paper focuses on the influence of maternal-fetal bonding by examining attachment theory, psycho-social-cultural influences/adaptations, and maternal well-being. A systematic review methodology was used to synthesize research results to summarize current evidence that can contribute to evidence-based practices. It explores the relationship between attachment styles, prenatal attachment, and perceptions of maternal-infant bonding/attachment six weeks postpartum. It also examines the protective factors of maternal-fetal attachment development. The research explores Bowlby's attachment theory and its relevance to maternal-fetal bonding with a Black Feminist Theory lens. Additionally, it discusses the impact of perceived stress, social support, and ecological models on maternal-fetal attachment. The relationship between maternal well-being, maternal-fetal attachment, and early postpartum bonding is reviewed. Moreover, the paper specifically addresses black mothers and maternal-fetal bonding, exploring the intersectionality of race, ethnicity, class, geographic location, cultural identities, and immigration status. It considers the role of familial and partner support, as well as the relationship between maternal attachment style and maternal-fetal bonding, within the framework of attachment theory and black feminist theory. Therefore, it is imperative to center Black women's voices in research, policy, and healthcare practices. Black women are experts in their own experiences and advocate for their autonomy in decision-making regarding maternal-fetal health. By amplifying their voices, we can ensure that interventions are grounded in their lived experiences.

Keywords: maternal-fetal bonding, infant well-being, maternal-infant attachment, black mothers

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Authors: Ayedh Alqahtani, Andrew Whyte

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Life Cycle Cost (LCC) is one of the goals and key pillars of the construction management science because it comprises many of the functions and processes necessary, which assist organisations and agencies to achieve their goals. It has therefore become important to design and control assets during their whole life cycle, from the design and planning phase through to disposal phase. LCCA is aimed to improve the decision making system in the ownership of assets by taking into account all the cost elements including to the asset throughout its life. Current application of LCC approach is impractical during misunderstanding of the advantages of LCC. This main objective of this research is to show a different relationship between capital cost and long-term running costs. One hundred and thirty eight actual building projects in United Kingdom (UK) were used in order to achieve and measure the above-mentioned objective of the study. The result shown that LCC is one of the most significant tools should be considered on the decision making process.

Keywords: building projects, capital cost, life cycle cost, maintenance costs, operation costs

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Authors: Guoqian Ren, Haijiang Li, Jisong Zhang

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Over the past 40 years, urban development has undergone large-scale, high-speed expansion, beyond what was previously considered normal and in a manner not proportionally related to population growth or physical considerations. With more scientific and refined decision-making in the urban construction process, new urbanization approaches, aligned with public-private partnerships (PPPs) which evolved in the early 1990s, have become acceptable and, in some situations, even better solutions to outstanding urban municipal construction projects, especially in developing countries. However, as the main driving force to deal with urban public services, PPPs are still problematic regarding value for money (VFM) process in most large-scale construction projects. This paper therefore reviews recent PPP articles in popular project management journals and relevant toolkits, published in the last 10 years, to identify the indicators that influence VFM within PPPs across regions. With increasing concerns about profitability and environmental and social impacts, the current PPP structure requires a more integrated platform to manage multi-performance project life cycles. Building information modelling (BIM), a popular approach to the procurement process in AEC sectors, provides the potential to ensure VFM while also working in tandem with the semantic approach to holistically measure life cycle costs (LCC) and achieve better sustainability. This paper suggests that BIM applied to the entire PPP life cycle could support holistic decision-making regarding VFM processes and thus meet service targets.

Keywords: public-private partnership, value for money, building information modelling, semantic approach

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Authors: Mikel Alonso López

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In the first decade of the twenty-first century, advanced imaging techniques began to be applied for neuroscience research. The Functional Magnetic Resonance Imaging (fMRI) is one of the most important and most used research techniques for the investigation of emotions, because of its ease to observe the brain areas that oxygenate when performing certain tasks. In this research, we make a review about the main research carried out on the influence of the emotions in the decision-making process that is exposed by using the fMRI.

Keywords: decision making, emotions, fMRI, consumer behaviour

Procedia PDF Downloads 480

Authors: T. G. Pathrikar, A. D. Urhekar, M. P. Bansal

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To find out S. aureus from patient samples on the basis of coagulase test. We have evaluated slide coagulase (n=46 positive), tube coagulase (n=48 positive) and DNase test (n=44, positive) , We have isolated and identified MRSA from various clinical samples and specimens by disc diffusion method determined the incidence of MRSA 50% in patients. Found out the in vitro antimicrobial susceptibility pattern of MRSA isolates and also the MIC of MRSA of oxacillin by E-Test.

Keywords: cefoxitin disc diffusion MRSA detection, e – test, S. aureus devastating pathogen, tube coagulase confirmation

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Authors: Omar Alzeley, Sergey Utev

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Minimizing a constrained multivariate function is the fundamental of Machine learning, and these algorithms are at the core of data mining and data visualization techniques. The decision function that maps input points to output points is based on the result of optimization. This optimization is the central of learning theory. One approach to complex systems where the dynamics of the system is inferred by a statistical analysis of the fluctuations in time of some associated observable is time series analysis. The purpose of this paper is a mathematical transition from the autoregressive model of classical time series to the matrix formalization of quantum theory. Firstly, we have proposed a quantum time series model (QTS). Although Hamiltonian technique becomes an established tool to detect a deterministic chaos, other approaches emerge. The quantum probabilistic technique is used to motivate the construction of our QTS model. The QTS model resembles the quantum dynamic model which was applied to financial data. Secondly, various statistical methods, including machine learning algorithms such as the Kalman filter algorithm, are applied to estimate and analyses the unknown parameters of the model. Finally, simulation techniques such as Markov chain Monte Carlo have been used to support our investigations. The proposed model has been examined by using real and simulated data. We establish the relation between quantum statistical machine and quantum time series via random matrix theory. It is interesting to note that the primary focus of the application of QTS in the field of quantum chaos was to find a model that explain chaotic behaviour. Maybe this model will reveal another insight into quantum chaos.

Keywords: machine learning, simulation techniques, quantum probability, tensor product, time series

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Authors: M. Hussaina, K. Mahboobb, S. Z. Ilyasa, S. Shaheena

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Plume dispersion modeling is a computational procedure to establish a relationship between emissions, meteorology, atmospheric concentrations, deposition and other factors. The emission characteristics (stack height, stack diameter, release velocity, heat contents, chemical and physical properties of the gases/particle released etc.), terrain (surface roughness, local topography, nearby buildings) and meteorology (wind speed, stability, mixing height, etc.) are required for the modeling of the plume dispersion and estimation of ground and air concentration. During the early phase of Fukushima accident, plume dispersion modeling and decisions were taken for the implementation of protective measures. A difference in estimated results and decisions made by different countries for taking protective actions created a concern in local and international community regarding the exact identification of the safe zone. The current study is focused to highlight the importance of accurate and exact weather data availability, scientific approach for decision making for taking urgent protective actions, compatible and harmonized approach for plume dispersion modeling during a nuclear emergency. As a case study, the influence of meteorological data on plume dispersion modeling and decision-making process has been performed.

Keywords: decision making process, radiation doses, nuclear emergency, meteorological implications

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Authors: Luciano Oliveira, Elsa Vásquez-Alvarez

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The increase in rail freight transport in Brazil in recent years requires new railway lines and the maintenance of existing ones, which generates high costs for concessionaires. It is in this context that this work is inserted, whose objective is to propose a method that uses Binary Linear Programming for the choice of sleeper and rail fastening, from various options, including the way to apply these materials, with focus to minimize costs. Unit value information, the life cycle each of material type, and service expenses are considered. The model was implemented in commercial software using real data for its validation. The formulated model can be replicated to support decision-making for other railway projects in the choice of sleepers and rail fastening with lowest cost.

Keywords: linear programming, rail fastening, rail sleeper, railway

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Authors: Feride Eskin Bacaksiz, Aytolan Yildirim

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Practices voluntarily performed by organizations for their employees well-being, create an emotional imperative for employees in accordance with reciprocity norm. Changes in desired course occur in organizational outputs and attitudes towards organization among employees perceiving their organizations as virtuous and supportive. The aim of this study was to examine the effect of organizational virtuousness on performance and organizational identification levels of employees and mediating role of perceived organizational support in this relationship. The data of this descriptive and methodological study were collected from 336 nurses working in a public university hospital in 2015. Participant information form, Organizational Virtuousness, Perceived Organizational Support, Organizational Identification, and Employee Performance scales were used to collect the data. Descriptive, correlative, psychometric analyses and Structural Equation Modeling were performed for the data analysis. Most of the participants were female, under 30 years of age, graduated degrees and staff nurse. Mean scores obtained by the participants from scales were calculated as 3.43(SD=.99) for organizational virtuousness, 2.99 (SD=1.16) for perceived organizational support, 3.18 (SD=1.03) for organizational identification and 3.84 (SD=0.66) for employee performance. It was found that correlation between organizational virtuousness and employee performance regressed from r=0.64 to r=-0.01 and correlation between organizational virtuousness and organizational identification regressed from r=0.55 to r=-0.16 and became statistically non-significant (p < 0.05) via mediating role of perceived organizational support. According to the results, perceived organizational support assumes full mediation on the impact of organizational virtues of employee performance and organizational identification levels. Therefore, organizations, which intend to positively affect employees attitudes towards organization and their performance, should both extend organizational virtuous activities and affect perceptions of employees; whereas, employees should perceive that they are supported by their organization.

Keywords: employee performance, organizational identification, organizational virtuousness, perceived organizational support

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Authors: M. Macchiaroli, L. Dolores, V. Pellecchia

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With the recent Resolution n. 580/2019/R/idr, the Italian Regulatory Authority for Energy, Networks, and Environment (ARERA) for the Urban Water Management has introduced, for water managements characterized by persistent critical issues regarding the planning and organization of the service and the implementation of the necessary interventions for the improvement of infrastructures and management quality, a new mechanism for determining tariffs: the regulatory scheme of Convergence. The aim of this regulatory scheme is the overcoming of the Water Service Divided in order to improve the stability of the local institutional structures, technical quality, contractual quality, as well as in order to guarantee transparency elements for Users of the Service. Convergence scheme presupposes the identification of the cost items to be considered in the tariff in parametric terms, distinguishing three possible cases according to the type of historical data available to the Manager. The study, in particular, focuses on operations that have neither data on tariff revenues nor data on operating costs. In this case, the Manager's Constraint on Revenues (VRG) is estimated on the basis of a reference benchmark and becomes the starting point for defining the structure of the tariff classes, in compliance with the TICSI provisions (Integrated Text for tariff classes, ARERA's Resolution n. 665/2017/R/idr). The proposed model implements the recent studies on optimization models for the definition of tariff classes in compliance with the constraints dictated by TICSI in the application of the Convergence mechanism, proposing itself as a support tool for the Managers and the local water regulatory Authority in the decision-making process.

Keywords: decision-making process, economic evaluation of projects, optimizing tools, urban water management, water tariff

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Authors: Tizian Matschak, Ilja Nastjuk, Stephan Kühnel, Simon Trang

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We argue that besides well-known primary effects of information security controls (ISCs), namely confidentiality, integrity, and availability, ISCs can also have secondary effects. For example, while IT can add business value through impacts on business processes, ISCs can be a barrier and distort the relationship between IT and organizational value through the impact on business processes. By applying the Delphi method with 28 experts, we derived 27 business process influence dimensions of ISCs. Defining and understanding these mechanisms can change the common understanding of the cost-benefit valuation of IT security investments and support managers' effective and efficient decision-making.

Keywords: business process dimensions, dark side of information security, Delphi study, IT security controls

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Authors: Gulcan Sahal, Isil Seyis Bilkay

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Candida species which often exist as commensal microorganisms in healthy individuals are major causes of important infections, especially in AIDS and immunocompromised patients, by means of their biofilm formation abilities. Therefore, in this study, determination of biofilm formation in different clinical strains of Candida species, investigation of strong biofilm forming Candida strains, examination of clinical information of each strong and weak biofilm forming Candida strains and investigation of some plant substances’ effects on biofilm formation of strong biofilm forming strains were aimed. In this respect, biofilm formation of Candida strains was analyzed via crystal violet binding assay. According to our results, biofilm levels of strains belong to different Candida species were different from each other. Additionally, it is also found that some plant substances effect biofilm formation. All these results indicate that, as well as C. albicans strains, other non-albicans Candida species also emerge as causative agents of infections and have biofilm formation abilities. In addition, usage of some plant substances in different concentrations may provide a new treatment against biofilm related Candida infections.

Keywords: anti-biofilm, biofilm formation, Candida species, biosystems engineering

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Authors: Arindam Chaudhuri

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The research presents epsilon- hierarchical fuzzy twin support vector regression (epsilon-HFTSVR) based on epsilon-fuzzy twin support vector regression (epsilon-FTSVR) and epsilon-twin support vector regression (epsilon-TSVR). Epsilon-FTSVR is achieved by incorporating trapezoidal fuzzy numbers to epsilon-TSVR which takes care of uncertainty existing in forecasting problems. Epsilon-FTSVR determines a pair of epsilon-insensitive proximal functions by solving two related quadratic programming problems. The structural risk minimization principle is implemented by introducing regularization term in primal problems of epsilon-FTSVR. This yields dual stable positive definite problems which improves regression performance. Epsilon-FTSVR is then reformulated as epsilon-HFTSVR consisting of a set of hierarchical layers each containing epsilon-FTSVR. Experimental results on both synthetic and real datasets reveal that epsilon-HFTSVR has remarkable generalization performance with minimum training time.

Keywords: regression, epsilon-TSVR, epsilon-FTSVR, epsilon-HFTSVR

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Authors: Fahmi Hassan, Noorizan Abdul Aziz, Yahaya Hassan, Hazlinda Abu Hassan

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Sepsis incidence in critical care settings is a major problem in health care. Extended antibiotic infusion is thought to be superior to traditional dosing especially when treating critically ill patients with sepsis. We compared clinical outcomes of critically ill patients with sepsis receiving 30-minute meropenem infusion and three-hour meropenem infusion. A retrospective case-control study was conducted among septic patients treated with meropenem infusion in ICUs of three hospitals. Patients included in the study received either extended or standard meropenem infusion as per the practice of individual settings. Outcomes and clinical data were retrospectively collected from the electronic databases and patients’ files. A total of 108 patients received extended meropenem infusion while another 117 patients received standard meropenem infusion. Patients receiving the extended meropenem infusion were found to have a significantly lower shorter length of hospital and ICU stay. It was also found that among those receiving extended meropenem infusion, 54.7% (64/117) had a reduction of SAPS II score, while only 44% (48/108) of patients receiving standard meropenem infusion had reduced scores. This study will strengthen the evidence in using extended meropenem infusion as a standard practice in critical care settings. As this is the first study of its kind done in Malaysia, it proves that prolonged meropenem infusion may be beneficial to critically ill patients with sepsis. However, randomized clinical trials with large sample size should be carried out in local settings in order to minimize other confounders that may influence with the result of the study.

Keywords: antibiotics, beta lactams, critical care, extended infusion, meropenem

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Authors: Shuo Mu, Guangzhi Jiang, Jinsa Chen

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The analysis of Indel for RNA sequencing of clinical samples is easily affected by sequencing experiment errors and software selection. In order to improve the efficiency and accuracy of analysis, we developed an automatic reporting system for Indel recognition and annotation based on image snapshot of transcriptome reads alignment. This system includes sequence local-assembly and realignment, target point snapshot, and image-based recognition processes. We integrated high-confidence Indel dataset from several known databases as a training set to improve the accuracy of image processing and added a bioinformatical processing module to annotate and filter Indel artifacts. Subsequently, the system will automatically generate data, including data quality levels and images results report. Sanger sequencing verification of the reference Indel mutation of cell line NA12878 showed that the process can achieve 83% sensitivity and 96% specificity. Analysis of the collected clinical samples showed that the interpretation accuracy of the process was equivalent to that of manual inspection, and the processing efficiency showed a significant improvement. This work shows the feasibility of accurate Indel analysis of clinical next-generation sequencing (NGS) transcriptome. This result may be useful for RNA study for clinical samples with microsatellite instability in immunotherapy in the future.

Keywords: automatic reporting, indel, next-generation sequencing, NGS, transcriptome

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Authors: Camilo Andrés Agudelo Vélez, Lina María Martínez Sánchez, Isabel Cristina Ortiz Trujillo, Evert Armando Jiménez Cotes, Natalia Perilla Hernández, María de los Ángeles Rodríguez Gázquez, Daniel Duque Restrepo, Felipe Hernández Restrepo, Dayana Andrea Quintero Moreno, Juan José Builes Gómez, Camilo Ruiz Mejía, Ana Lucia Arango Gómez

Abstract:

Preeclampsia is a clinical complication during pregnancy with high incidence in Colombia; therefore, it is important to evaluate the influence of external conditions and medical interventions, in order to promote measures that encourage improvements in the quality of life. Objective: Determine clinical and sociodemographic variables in women with preeclampsia. Methods: This cross-sectional study enrolled 50 patients with the diagnosis of preeclampsia, from a private institution in Medellin, during 2015. We used the software SPSS ver.20 for statistical analysis. For the qualitative variables, we calculated the mean and standard deviation, while, for ordinal and nominal levels of quantitative variables, ratios were estimated. Results: The average age was 26.8±5.9 years. The predominant characteristics were socioeconomic stratum 2 (48%), students (55%), mixed race (46%) and middle school as level of education (38%). As for clinical features, 72% of the cases were mild preeclampsia, and 22% were severe forms. The most common clinical manifestations were edema (46%), headache (62%), and proteinuria (55%). As for the Gyneco-obstetric history, 8% reported previous episodes of this disease and it was the first pregnancy for 60% of the patients. Conclusions: Preeclampsia is a frequent condition in young women; on the other hand, headache and edema were the most common reasons for consultation, therefore, doctors need to be aware of these symptoms in pregnant women.

Keywords: pre-eclampsia, hypertension, pregnancy complications, pregnancy, abdominal, edema

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Authors: Chusit Apirumanekul, Chayanis Krittasudthacheewa, Ratchapat Ratanavaraha, Yanyong Inmuong

Abstract:

Rapid economic development in the Lower Mekong region is leading to changes in water quantity and quality. Changes in land- and forest-use, infrastructure development, increasing urbanization, migration patterns and climate risks are increasing demands for water, within various sectors, placing pressure on scarce water resources. Appropriate policies, strategies, and planning are urgently needed for improved water resource management. Over the last decade, Thailand has experienced more frequent and intense drought situations, affecting the level of water storage in reservoirs along with insufficient water allocation for agriculture during the dry season. The Huay Saibat River Basin, one of the well-known water-scarce areas in the northeastern region of Thailand, is experiencing ongoing water scarcity that affects both farming livelihoods and household consumption. Drought management in Thailand mainly focuses on emergency responses, rather than advance preparation and mitigation for long-term solutions. Despite many efforts from local authorities to mitigate the drought situation, there is yet no long-term comprehensive water management strategy, that integrates climate risks alongside other uncertainties. This paper assesses the application in the Huay Saibat River Basin, of the Robust Decision Support framework, to explore the feasibility of multiple drought management policies; including a shift in cropping season, in crop changes, in infrastructural operations and in the use of groundwater, under a wide range of uncertainties, including climate and land-use change. A series of consultative meetings were organized with relevant agencies and experts at the local level, to understand and explore plausible water resources strategies and identify thresholds to evaluate the performance of those strategies. Three different climate conditions were identified (dry, normal and wet). Other non-climatic factors influencing water allocation were further identified, including changes from sugarcane to rubber, delaying rice planting, increasing natural retention storage and using groundwater to supply demands for household consumption and small-scale gardening. Water allocation and water use in various sectors, such as in agriculture, domestic, industry and the environment, were estimated by utilising the Water Evaluation And Planning (WEAP) system, under various scenarios developed from the combination of climatic and non-climatic factors mentioned earlier. Water coverage (i.e. percentage of water demand being successfully supplied) was defined as a threshold for water resource strategy assessment. Thresholds for different sectors (agriculture, domestic, industry, and environment) were specified during multi-stakeholder engagements. Plausible water strategies (e.g. increasing natural retention storage, change of crop type and use of groundwater as an alternative source) were evaluated based on specified thresholds in 4 sectors (agriculture, domestic, industry, and environment) under 3 climate conditions. 'Business as usual' was evaluated for comparison. The strategies considered robust, emerge when performance is assessed as successful, under a wide range of uncertainties across the river basin. Without adopting any strategy, the water scarcity situation is likely to escalate in the future. Among the strategies identified, the use of groundwater as an alternative source was considered a potential option in combating water scarcity for the basin. Further studies are needed to explore the feasibility for groundwater use as a potential sustainable source.

Keywords: climate change, robust decision support, scenarios, water resources management

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Authors: Suzan Anwar, Utkarsh Goyal

Abstract:

Heart rate (HR) is a predictor of cardiovascular, cerebrovascular, and all-cause mortality in the general population, as well as in patients with cardio and cerebrovascular diseases. Machine learning (ML) significantly improves the accuracy of cardiovascular risk prediction, increasing the number of patients identified who could benefit from preventive treatment while avoiding unnecessary treatment of others. This research examines relationship between the individual's various heart health inputs like age, sex, cp, trestbps, thalach, oldpeaketc, and the likelihood of developing heart disease. Machine learning techniques like logistic regression and decision tree, and Python are used. The results of testing and evaluating the model using the Heart Failure Prediction Dataset show the chance of a person having a heart disease with variable accuracy. Logistic regression has yielded an accuracy of 80.48% without data handling. With data handling (normalization, standardscaler), the logistic regression resulted in improved accuracy of 87.80%, decision tree 100%, random forest 100%, and SVM 100%.

Keywords: heart rate, machine learning, SVM, decision tree, logistic regression, random forest

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Authors: Mirzashahi Babak, Mansouri Pejman, Najafi Arvin, Farzan Mahmoud

Abstract:

Introduction: There are several surgical treatment choices for cervical spondylotic myelopathy (CSM). The aim of this study is to evaluate clinical outcomes and surgical complications in patients with cervical disk degeneration (CDD) undergoing either anterior cervical discectomy with or without fusion or cervical laminectomy and fusion. Methods: This prospective case series study included 45 consecutive patients with cervical spondylotic myelopathy between January 2010 and November 2014. There were 28 males and 17 females, with a mean age of 47 (range 37-68) years. The mean clinical follow-up was 14 months (range 3-24 months). The Neck Disability Index (NDI), visual analog scale (VAS) neck and arm pain, Short Form-36 (SF-36) were used as the functional outcome measurements. All of the complications in our patients were recorded. Results: In our study group, 26 patients underwent only one or two level anterior cervical discectomy. Ten patients underwent anterior cervical discectomy and fusion (ACDF) and nine cases underwent posterior laminectomy and fusion. We have found a statistically significant improvement between mean preoperative (29, range 19-43) and postoperative (7, range 0-12) NDI scores following surgery (P < 0.05). Also, there was a statistically significant difference between pre and post-operative VAS and SF-36 score (p < 0.05). There was a 7% overall complication rate (n = 3). The only complication in our patients was surgical site cellulitis which has been managed with oral antibiotic therapy. Conclusion: Both anterior cervical discectomy with or without fusion or posterior laminectomy and fusion are safe and efficacious treatment options for the management of CSM. The clinical outcomes seem to be fairly reproducible.

Keywords: cervical, myelopathy, discectomy, fusion, laminectomy

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