Search results for: driver monitoring

Authors: R. Posia, J. Mistry, K. Kamani

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The health screening of laboratory rodents is essential for ensuring animal health and the validity of biomedical research data. Routine health monitoring is necessary to verify the effectiveness of biosecurity and the specific pathogen free (SPF) status of the colony. The present screening was performed in barrier maintained rat (Rattus norvegicus) colony. Rats were maintained under a controlled environment and strict biosecurity in the facility. The screening was performed on quarterly bases from randomly selected animals from breeding and or maintenance colonies. Selected animals were subject to blood collection under isoflurane anaesthesia. Serum was separated from the collected blood and stored samples at -60 ± 10 °C until further use. A total of 88 samples were collected quarterly bases from animals in a year. In the serological test, enzyme-linked immunosorbent assay (ELISA) was used for screening of serum samples against sialodacryoadenitis virus (SDAV), Sendai virus (SV), and Kilham’s rat virus (KRV). ELISA kits were procured from XpressBio, USA. Test serum samples were run along with positive control, negative control serum in 96 well ELISA plates as per the procedure recommended by the vendor. Test ELISA plate reading was taken in the microplate reader. This screening observed that none of the samples was observed positive for the sialodacryoadenitis virus (SDAV), Sendai virus (SV), and Kilham’s rat virus (KRV), indicating that effectiveness of biosecurity practices followed in the rodent colony. The result of serological screening helps us to declare that our rodent colony is specifically pathogen free for these pathogens.

Keywords: biosecurity, ELISA, specific pathogen free, serological screening, serum

Procedia PDF Downloads 75

Authors: Habtamu Abdisa

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Spring water is particularly valuable due to its high mineral content, which is beneficial for human health. However, anthropogenic activities usually imbalance the natural levels of its composition, which can cause adverse health effects. Regular monitoring of a naturally given environmental resource is of great concern in the world today. The spectrophotometric application is one of the best methods for qualifying and quantifying the mineral contents of environmental water samples. This research was conducted to evaluate the quality of spring water concerning its heavy metal composition. A grab sampling technique was employed to collect representative samples, including duplicates. The samples were then treated with concentrated HNO3 to a pH level below 2 and stored at 4oC. The samples were digested and analyzed for cadmium (Cd), chromium (Cr), manganese (Mn), copper (Cu), iron (Fe), and zinc (Zn) following method validation. Atomic Absorption Spectrometry (AAS) was utilized for the sample analysis. Quality control measures, including blanks, duplicates, and certified reference materials (CRMs), were implemented to ensure the accuracy and precision of the analytical results. Of the metals analyzed in the water samples, Cd and Cr were found to be below the detection limit. However, the concentrations of Mn, Cu, Fe, and Zn ranged from mean values of 0.119-0.227 mg/L, 0.142-0.166 mg/L, 0.183-0.267 mg/L, and 0.074-0.181 mg/L, respectively. Sediment analysis revealed mean concentration ranges of 348.31-429.21 mg/kg, 0.23-0.28 mg/kg, 18.73-22.84 mg/kg, 2.76-3.15 mg/kg, 941.84-1128.56 mg/kg, and 42.39-66.53 mg/kg for Mn, Cd, Cu, Cr, Fe, and Zn, respectively. The study results established that the evaluated spring water and its associated sediment met the regulatory standards and guidelines for heavy metal concentrations. Furthermore, this research can enhance the quality assurance and control processes for environmental sample analysis, ensuring the generation of reliable data.

Keywords: method validation, heavy metal, spring water, sediment, method detection limit

Procedia PDF Downloads 67

Authors: Emmanouil Papavasileiou, Nikos Bozionelos, Liza Howe-Walsh, Sarah Turnbull

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Purpose: The research focuses on women academics’ insecure identity at work and examines its link with generational identity. The aim is to enrich understanding of identities at work as a crucial attribute of managing academics in the context of the proliferation of managerialist controls of audit, accountability, monitoring, and performativity. Methodology: Positivist quantitative methodology was utilized. Data were collected from the Scientific Women's Academic Network (SWAN) Charter. Responses from 155 women academics based in the British Higher Education system were analysed. Findings: Analysis showed high prevalence of strong imposter feelings among participants, suggesting high insecurity at work among women academics in the United Kingdom. Generational identity was related to imposter feelings. In particular, Millennials scored significantly higher than the other generational groups. Research implications: The study shows that imposter feelings are variously manifested among the prevalent generations of women academics, while generational identity is a significant antecedent of such feelings. Research limitations: Caution should be exercised in generalizing the findings to national cultural contexts beyond the United Kingdom. Practical and social implications: Contrary to popular depictions of Millennials as self-centered, narcissistic, materialistic and demanding, women academics who are members of this generational group appear significantly more insecure than the preceding generations. Value: The study provides insightful understandings into women academics’ identity at work as a function of generational identity, and provides a fruitful avenue for further research within and beyond this gender group and profession.

Keywords: academics, generational diversity, imposter feelings, United Kingdom, women, work identity

Procedia PDF Downloads 145

Authors: Parisa Mansour

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Cystic fibrosis (CF) is one of the most common autosomal recessive diseases among whites. It mostly affects the lungs, causing infections and inflammation that account for 90% of deaths in CF patients. Because of this high variability in clinical presentation and organ involvement, investigating treatment responses and evaluating lung changes over time is critical to preventing CF progression. High-resolution computed tomography (HRCT) greatly facilitates the assessment of lung disease progression in CF patients. Recently, artificial intelligence was used to analyze chest CT scans of CF patients. In this paper, we propose a convolutional neural network (CNN) approach to classify CF lung patterns in HRCT images. The proposed network consists of two convolutional layers with 3 × 3 kernels and maximally connected in each layer, followed by two dense layers with 1024 and 10 neurons, respectively. The softmax layer prepares a predicted output probability distribution between classes. This layer has three exits corresponding to the categories of normal (healthy), bronchitis and inflammation. To train and evaluate the network, we constructed a patch-based dataset extracted from more than 1100 lung HRCT slices obtained from 45 CF patients. Comparative evaluation showed the effectiveness of the proposed CNN compared to its close peers. Classification accuracy, average sensitivity and specificity of 93.64%, 93.47% and 96.61% were achieved, indicating the potential of CNNs in analyzing lung CF patterns and monitoring lung health. In addition, the visual features extracted by our proposed method can be useful for automatic measurement and finally evaluation of the severity of CF patterns in lung HRCT images.

Keywords: HRCT, CF, cystic fibrosis, chest CT, artificial intelligence

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Authors: Claude Takenga, Rolf-Dietrich Berndt, Erling Si, Markus Diem, Guohui Qiao, Melanie Gau, Michael Brandstoetter, Martin Kampel, Michael Dworzak

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In patients with acute lymphoblastic leukaemia (ALL), treatment response is increasingly evaluated with minimal residual disease (MRD) analyses. Flow Cytometry (FCM) is a fast and sensitive method to detect MRD. However, the interpretation of these multi-parametric data requires intensive operator training and experience. This paper presents a pipeline-software, as a ready-to-use FCM-based MRD-assessment tool for the daily clinical practice for patients with ALL. The new tool increases accuracy in assessment of FCM-MRD in samples which are difficult to analyse by conventional operator-based gating since computer-aided analysis potentially has a superior resolution due to utilization of the whole multi-parametric FCM-data space at once instead of step-wise, two-dimensional plot-based visualization. The system developed as a telemedical network reduces the work-load and lab-costs, staff-time needed for training, continuous quality control, operator-based data interpretation. It allows dissemination of automated FCM-MRD analysis to medical centres which have no established expertise for the benefit of an even larger community of diseased children worldwide. We established a telemedical network system for analysis and clinical follow-up and treatment monitoring of Leukaemia. The system is scalable and adapted to link several centres and laboratories worldwide.

Keywords: data security, flow cytometry, leukaemia, telematics platform, telemedicine

Procedia PDF Downloads 981

Authors: Dachuan Shi, M. Hecht, Y. Ye

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With the trend of digitalization in railway freight transport, a large number of freight wagons in Germany have been equipped with telematics devices, commonly placed on the wagon body. A telematics device contains a GPS module for tracking and a 3-axis accelerometer for shock detection. Besides these basic functions, it is desired to use the integrated accelerometer for condition monitoring without any additional sensors. Wheel flats as a common type of failure on wheel tread cause large impacts on wagons and infrastructure as well as impulsive noise. A large wheel flat may even cause safety issues such as derailments. In this sense, this paper proposes a machine learning approach for wheel flat detection by using car body accelerations. Due to suspension systems, impulsive signals caused by wheel flats are damped significantly and thus could be buried in signal noise and disturbances. Therefore, it is very challenging to detect wheel flats using car body accelerations. The proposed algorithm considers the envelope spectrum of car body accelerations to eliminate the effect of noise and disturbances. Subsequently, a 1-D convolutional neural network (CNN), which is well known as a deep learning method, is constructed to automatically extract features in the envelope-frequency domain and conduct classification. The constructed CNN is trained and tested on field test data, which are measured on the underframe of a tank wagon with a wheel flat of 20 mm length in the operational condition. The test results demonstrate the good performance of the proposed algorithm for real-time fault detection.

Keywords: fault detection, wheel flat, convolutional neural network, machine learning

Procedia PDF Downloads 130

Authors: Andrew D. Henshaw, James M. Austin

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Introduction: Human trafficking is an increasingly serious transnational criminal enterprise and social security issue. Despite ongoing efforts to mitigate the phenomenon and a significant expansion of security scrutiny over past decades, it is not receding. This is true for many nations in Southeast Asia, widely recognized as the global hub for trafficked persons, including men, women, and children. Clearly, human trafficking is difficult to address because there are numerous drivers, causes, and motivators for it to persist, such as non-military and non-traditional security challenges, i.e., climate change, global warming displacement, and natural disasters. These make displaced persons and refugees particularly vulnerable. The issue is so large conservative estimates put a dollar value at around $150 billion-plus per year (Niethammer, 2020) spanning sexual slavery and exploitation, forced labor, construction, mining and in conflict roles, and forced marriages of girls and women. Coupled with corruption throughout military, police, and civil authorities around the world, and the active hands of powerful transnational criminal organizations, it is likely that such figures are grossly underestimated as human trafficking is misreported, under-detected, and deliberately obfuscated to protect those profiting from it. For example, the 2022 UN report on human trafficking shows a 56% reduction in convictions in that year alone (UNODC, 2022). Our Approach: To better understand this, our research utilizes a bespoke methodology. Applying a JAM (Juxtaposition Assessment Matrix), which we previously developed to detect flows of dark money around the globe (Henshaw, A & Austin, J, 2021), we now focus on the human trafficking paradigm. Indeed, utilizing a JAM methodology has identified key indicators of human trafficking not previously explored in depth. Being a set of structured analytical techniques that provide panoramic interpretations of the subject matter, this iteration of the JAM further incorporates behavioral and driver indicators, including the employment of Open-Source Artificial Intelligence (OS-AI) across multiple collection points. The extracted behavioral data was then applied to identify non-traditional indicators as they contribute to human trafficking. Furthermore, as the JAM OS-AI analyses data from the inverted position, i.e., the viewpoint of the traffickers, it examines the behavioral and physical traits required to succeed. This transposed examination of the requirements of success delivers potential leverage points for exploitation in the fight against human trafficking in a new and novel way. Findings: Our approach identified new innovative datasets that have previously been overlooked or, at best, undervalued. For example, the JAM OS-AI approach identified critical 'dark agent' lynchpins within human trafficking that are difficult to detect and harder to connect to actors and agents within a network. Our preliminary data suggests this is in part due to the fact that ‘dark agents’ in extant research have been difficult to detect and potentially much harder to directly connect to the actors and organizations in human trafficking networks. Our research demonstrates that using new investigative techniques such as OS-AI-aided JAM introduces a powerful toolset to increase understanding of human trafficking and transnational crime and illuminate networks that, to date, avoid global law enforcement scrutiny.

Keywords: human trafficking, open-source intelligence, transnational crime, human security, international human rights, intelligence analysis, JAM OS-AI, Dark Money

Procedia PDF Downloads 90

Authors: Terentes Printzios Dimitrios, Loanna Gourgouli, Vlachopoulos Charalambos

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Aims: Atrial fibrillation (AF) remains one of the major causes of stroke, heart failure, sudden death and cardiovascular morbidity. Ablation techniques are becoming more appealing after the latest results of randomized trials showing the overall clinical benefit. On the other hand, imaging techniques and the frontier application of 3D printing are emerging as a valuable ally for cardiac procedures. However, no randomized trial has directly assessed the impact of preprocedural imaging and especially 3D printing guidance for AF ablation. The present study is designed to investigate for the first time the effect of 3D printing of the heart on the safety and effectiveness of the ablation procedure. Methods and design: The 3D-GALA trial is a randomized, open-label, controlled, multicentre clinical trial of 2 parallel groups designed to enroll a total of 100 patients undergoing ablation using cryo-balloon for paroxysmal and persistent AF. Patients will be randomized with a patient allocation ratio of 1: 1 to preprocedural MRI scan of the heart and 3D printing of left atrium and pulmonary veins and cryoablation versus standard cryoablation without imaging. Patients will be followed up to 6 months after the index procedure. The primary outcome measure is the reduction of radiation dose and contrast amount during pulmonary veins isolation. Secondary endpoints will include the percentage of atrial fibrillation relapse at 24h-Holter electrocardiogram monitoring at 6 months after initial treatment. Discussion: To our knowledge, the 3D-GALA trial will be the first study to provide evidence about the clinical impact of preprocedural imaging and 3D printing before cryoablation.

Keywords: atrial fibrillation, cardiac MRI, cryoablation, 3-d printing

Procedia PDF Downloads 174

Authors: Mukisa Daphine Letisha

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Plea bargaining, a practice often associated with more developed legal systems, has emerged as a significant tool within Uganda's criminal justice system despite its absence in formal legal structures inherited from its colonial past. Initiated in 2013 with the aim of reducing case backlogs, expediting trials, and addressing prison congestion, plea bargaining reflects a pragmatic response to systemic challenges. While rooted in international statutes and domestic constitutional provisions, its implementation relies heavily on the Judicature (Plea Bargain) Rules of 2016, which outline procedural requirements and safeguards. Advocates argue that plea bargaining has yielded tangible benefits, including a reduction in case backlog and efficient allocation of resources, with notable support from judicial and prosecutorial authorities. Case examples demonstrate successful outcomes, with accused individuals benefitting from reduced sentences in exchange for guilty pleas. However, challenges persist, including procedural irregularities, inadequate statutory provisions, and concerns about coercion and imbalance of power between prosecutors and accused individuals. To enhance efficacy, recommendations focus on establishing monitoring mechanisms, stakeholder training, and public sensitization campaigns. In conclusion, while plea bargaining offers potential advantages in streamlining Uganda's criminal justice system, addressing its challenges requires careful consideration of procedural safeguards and stakeholder engagement to ensure fairness and integrity in the administration of justice.

Keywords: plea-bargaining, criminal-justice system, uganda, efficacy

Procedia PDF Downloads 52

Authors: Nashed Atef Nashed Farag

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Introduction: Reporting adverse events following vaccination remains a challenge. WHO has mandated pharmacovigilance centers around the world to submit Adverse Events Following Immunization (AEFI) reports from different countries to a large electronic database of adverse drug event data called Vigibase. Despite sufficient information about AEFIs on Vigibase, they are not available to the general public. However, the WHO has an alternative website called VigiAccess, an open-access website that serves as an archive for reported adverse reactions and AEFIs. The aim of the study was to establish a reporting model for a number of commonly used vaccines in the VigiAccess system. Methods: On February 5, 2018, VigiAccess comprehensively searched for ESSI reports on the measles vaccine, oral polio vaccine (OPV), yellow fever vaccine, pneumococcal vaccine, rotavirus vaccine, meningococcal vaccine, tetanus vaccine, and tuberculosis vaccine (BCG). These are reports from all pharmacovigilance centers around the world since they joined the WHO Drug Monitoring Program. Results: After an extensive search, VigiAccess found 9,062 AEFIs from the measles vaccine, 185,829 AEFIs from the OPV vaccine, 24,577 AEFIs from the yellow fever vaccine, 317,208 AEFIs from the pneumococcal vaccine, 73,513 AEFIs from the rotavirus vaccine, and 145,447 AEFIs from meningococcal cal vaccine, 22,781 EI FI vaccines against tetanus and 35,556 BCG vaccines against AEFI. Conclusion: The study found that among the eight vaccines examined, pneumococcal vaccines were associated with the highest number of AEFIs, while measles vaccines were associated with the fewest AEFIs.

Keywords: surgical approach, anatomical approach, decompression, axillary nerve, quadrangular space adverse events following immunization, cameroon, COVID-19 vaccines, nOPV, ODK vaccines, adverse reactions, VigiAccess, adverse event reporting

Procedia PDF Downloads 71

Authors: David Ryan, Martin Breugst, Turlough Downes, Peter A. Byrne, Gerard P. McGlacken

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An ambident nucleophile is a nucleophile that possesses two or more distinct nucleophilic sites that are linked through resonance and are effectively “in competition” for reaction with an electrophile. Examples include enolates, pyridone anions, and nitrite anions, among many others. Reactions of ambident nucleophiles and electrophiles are extremely prevalent at all levels of organic synthesis. The principle of hard and soft acids and bases (the “HSAB principle”) is most commonly cited in the explanation of selectivities in such reactions. Although this rationale is pervasive in any discussion on ambident reactivity, the HSAB principle has received considerable criticism. As a result, the principle’s supplantation has become an area of active interest in recent years. This project focuses on developing a model for rationalizing ambident reactivity. Presented here is an approach that incorporates computational calculations and experimental kinetic data to construct Gibbs energy profile diagrams. The preferred site of alkylation of nitrite anion with a range of ‘hard’ and ‘soft’ alkylating agents was established by ¹H NMR spectroscopy. Pseudo-first-order rate constants were measured directly by ¹H NMR reaction monitoring, and the corresponding second-order constants and Gibbs energies of activation were derived. These, in combination with computationally derived standard Gibbs energies of reaction, were sufficient to construct Gibbs energy wells. By representing the ambident system as a series of overlapping Gibbs energy wells, a more intuitive picture of ambident reactivity emerges. Here, previously unexplained switches in reactivity in reactions involving closely related electrophiles are elucidated.

Keywords: ambident, Gibbs, nucleophile, rates

Procedia PDF Downloads 81

Authors: Abdullah Al-Alaian, Ahmad Al-Enzi, Hasan Al-Herz, Ahmad Bakri, Shant Tatorian, Amr Nounou

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Kuwait is a country that has an imbalanced economy since most of its national outcome comes from the oil trade. It is so risky for a country to be dependent on a single source for income, and this increases the need to diversify its economy. In addition, according to the Public Authority for Industry, the contribution of the industrial sector to the current Gross Domestic Product (GDP) of Kuwait is low which is about 4.33%. Therefore, the development of the industrial sector can be one of the means to diversify the economy and increase the industry's contribution to the national outcome. This is in accordance with Kuwait’s vision of 2035 which aims at increasing the contribution of the industrial sector to the GDP to 12%. In order to do so, this study aims at proposing a strategic plan that will accomplish certain objectives when implemented. It is based on analyzing the industrial sectors in Kuwait taking into consideration studying the strengths, weaknesses, opportunities, and threats facing them. At the same time, it tends to gain from the experience of leading models and neighboring countries regarding the development of the industrial sector. In this study, the SWOT analysis technique will be conducted on all industrial sectors based on evaluation criteria in which it is determined whether any of them has a potential for improvement or not. In other words, it is determined whether the sectors are able to compete locally, regionally, or globally. Based on the results of the SWOT analysis, certain sectors will be chosen, assessed based on an assessment scheme, and their potentials for improvement will be aligned with the overall objectives. To ensure the achievement of the study’s objectives, an action plan will be proposed regarding recommendations for the related authorities, and for entrepreneurs. In addition, monitoring tools are going to be provided for the purpose of periodically checking the progress made in the implementation of the plan.

Keywords: industrial sector, SWOT analysis, productivity, competitiveness, GDP, Kuwait, economy

Procedia PDF Downloads 479

Authors: M. K. Wijayarathna, S. M. Buddika Harshanath

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Monitoring student engagement has become a crucial part of the educational process and a reliable indicator of the capacity to retain information. As online learning classrooms are now more common these days, students' attention levels have become increasingly important, making it more difficult to check each student's concentration level in an online classroom setting. To profile student attention to various gradients of engagement, a study is a plan to conduct using machine learning models. Using a convolutional neural network, the findings and confidence score of the high accuracy model are obtained. In this research, convolutional neural networks are using to help discover essential emotions that are critical in defining various levels of participation. Students' attention levels were shown to be influenced by emotions such as calm, enjoyment, surprise, and fear. An improved virtual learning system was created as a result of these data, which allowed teachers to focus their support and advise on those students who needed it. Student participation has formed as a crucial component of the learning technique and a consistent predictor of a student's capacity to retain material in the classroom. Convolutional neural networks have a plan to implement the platform. As a preliminary step, a video of the pupil would be taken. In the end, researchers used a convolutional neural network utilizing the Keras toolkit to take pictures of the recordings. Two convolutional neural network methods are planned to use to determine the pupils' attention level. Finally, those predicted student attention level results plan to display on the graphical user interface of the System.

Keywords: HTML5, JavaScript, Python flask framework, AI, graphical user

Procedia PDF Downloads 97

Authors: Deepanjali Gurav, Kun Qian

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In-vitro metabolic diagnosis relies on designed materials-based analytical platforms for detection of selected metabolites in biological samples, which has a key role in disease detection and therapeutic evaluation in clinics. However, the basic challenge deals with developing a simple approach for metabolic analysis in bio-samples with high sample complexity and low molecular abundance. In this work, we report a designer plasmonic nanoshells based platform for direct detection of small metabolites in clinical samples for in-vitro metabolic diagnostics. We first synthesized a series of plasmonic core-shell particles with tunable nanoshell structures. The optimized plasmonic nanoshells as new matrices allowed fast, multiplex, sensitive, and selective LDI MS (Laser desorption/ionization mass spectrometry) detection of small metabolites in 0.5 μL of bio-fluids without enrichment or purification. Furthermore, coupling with isotopic quantification of selected metabolites, we demonstrated the use of these plasmonic nanoshells for disease detection and therapeutic evaluation in clinics. For disease detection, we identified patients with postoperative brain infection through glucose quantitation and daily monitoring by cerebrospinal fluid (CSF) analysis. For therapeutic evaluation, we investigated drug distribution in blood and CSF systems and validated the function and permeability of blood-brain/CSF-barriers, during therapeutic treatment of patients with cerebral edema for pharmacokinetic study. Our work sheds light on the design of materials for high-performance metabolic analysis and precision diagnostics in real cases.

Keywords: plasmonic nanoparticles, metabolites, fingerprinting, mass spectrometry, in-vitro diagnostics

Procedia PDF Downloads 136

Authors: Rajiv Ratan Singh, Sachin Kumar Tripathi, Pradeep Kumar Yadav

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The timely evaluation, diagnosis, and treatment of people who have been exposed to toxic chemicals is a crucial component of emergency poison management in the medical field. The various substances that can poison include chemicals, medications, and naturally occurring poisons. The toxicology of the particular drug involved, as well as the symptoms and indicators of poisoning, must be thoroughly understood to handle poisoning emergencies effectively. One of the most important aspects of emergency poison management in medicine is the prompt examination, diagnosis, and treatment of persons who have been exposed to dangerous substances. To properly manage poisoning crises, one must have a good understanding of the toxicology of the particular medication concerned, as well as the signs and indicators of poisoning. Emergency management of poisoning includes not only prompt medical attention but also patient education, follow-up care, and monitoring for any long-term consequences. To achieve the greatest results for patients, the management of poisoning is a complicated and dynamic process that calls for collaboration between medical professionals, first responders, and toxicologists. All poisoned patients who present to the emergency room are assessed and diagnosed based on a collection of symptoms and a biochemical diagnosis, and they are then provided targeted, specialized treatment for the toxin identified. This article focuses on the loxodromic strategy as the primary method of treatment for poisoned patients. The authors of this article conclude that mortality and morbidity can be reduced if patients visit the emergency room promptly and receive targeted treatment.

Keywords: antidotes, blood poisoning, emergency medicine, gastric lavage, medico-legal aspects, patient care

Procedia PDF Downloads 98

Authors: A. ElZawam, D. McLean, A. Tibary

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In alpaca, age at puberty is variable and the factors regulating the pattern of puberty and sexual maturation are a subject of controversy. Plasma testosterone level is often used as an indicator of sexual maturity. Our hypothesis is that hCG treatment will cause an increase in testosterone level that is correlated with animal age. The specific aim was to investigate the testicular tissue response to a single hCG injection by monitoring the serum testosterone concentration. Eighty four (n=84) males ranging in age from 6 to 60 months were used. Alpacas were grouped based on their ages into 15 groups. Each group had three to five male animals. Blood samples were collected from the jugular vein before treatment with hCG and 2 hours after intravenous administration of 3000 IU of hCG (Chorulon®). The serum was harvested and stored at -20ºC until the analysis. The effect of age on basal testosterone level and response to hCG treatment was evaluated by Analysis of Variance. As a result, basal serum testosterone concentrations were very low (<0.1ng/ml) until 9 months of age. Although basal serum testosterone concentrations increased steadily with age there was a significant variation amongst males within the same age group. Administration of 3000 IU of hCG, resulted in an average increase of 50% (P<0.05) in serum testosterone concentration after 2 hours. The percentage increase in serum testosterone in response to hCG stimulation varied from 51 to 81%. There was no correlation between the degree of response and age. However, the response to hCG injection presented two modes of increase depending on the age of animals. The first mode occurred at ages 9 to 14 months and the second mode was observed between 22 and 36 months. In conclusion, our results suggest that testicular growth and sensitivity to LH stimulation may be bimodal in the male alpaca with a rapid increase in growth and sensitivity between 9 and 14 months of age and a second phase of increased responsiveness after 21 months of ages.

Keywords: alpaca, testosterone, hCG, animal science

Procedia PDF Downloads 569

Authors: Tri Nopiyanto, Rahardhyani Dwiannisa, Arief Ismaryanto

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One main issue for a certain region in order to achieve development is if the government that consists of the executive, legislative and judicial board are able to work together. However, there are certain conditions that these boards are the sources of conflict, especially between the executive and legislative board. One of the example of the conflict is between the Local Government and Legislative Board (DPRD) in the Province of Jakarta in 2015. The cause of this conflict is because of the occurrence of pokir (pokok pikiran or ideas of budgeting). Pokir is driven by a budgeting plan that is arranged by DPRD that is supposed to be sourced from the aspiration of the people and delivered 5 months before the legalization of Local Government Budget (APBD), but the current condition in Jakarta is that pokir is a project by DPRD members itself and delivered just 3 days before the legalization in order to facilitate the interests of the members of the legislative. This paper discusses how pokir happens and what factors caused it. This paper uses political budgeting theory by Andy Norton and Diane Elson to analyze the issue. The method used in this paper is qualitative to collect the data and solve the problem of this research. The methods involved are in depth interview, experimental questionnaire, and literature studies. Results of this research are that Pokir occurs because of the distribution of power among DPRD members, between parties, executive, and legislative board. Beside that, Pokir also occurs because of the lack of the people’s participation in budgeting process and monitoring. Other than that, this paper also found that pokir also happens because of the budgeting system that is not able to provide a clean budgeting process, so it enables the creation of certain slots to add pokir into the budgets. Pokir also affects the development of Jakarta that goes through stagnation. This research recommends the implementation of e-budgeting to prevent the occurrence of pokir itself in the Province of Jakarta.

Keywords: legislative and executive board, Jakarta, political budgeting, Pokir

Procedia PDF Downloads 270

Authors: Daofan Guo, Dong Yang

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For decades, well logging with coiled tubing has relied solely on surface data such as pump pressure, wellhead pressure, depth counter, and weight indicator readings. While this data serves the oil industry well, modern smart logging utilizes real-time downhole information, which automatically increases operational efficiency and optimizes intervention qualities. For example, downhole pressure, temperature, and depth measurement data can be transmitted through the electro-optical hybrid cable in the coiled tubing to surface operators on a real-time base. This paper mainly introduces the unique structural features and various applications of the electro-optical hybrid cables which were deployed into downhole with the help of coiled tubing technology. Fiber optic elements in the cable enable optical communications and distributed measurements, such as distributed temperature and acoustic sensing. The electrical elements provide continuous surface power for downhole tools, eliminating the limitations of traditional batteries, such as temperature, operating time, and safety concerns. The electrical elements also enable cable telemetry operation of cable tools. Both power supply and signal transmission were integrated into an electro-optical hybrid cable, and the downhole information can be captured by downhole electrical sensors and distributed optical sensing technologies, then travels up through an optical fiber to the surface, which greatly improves the accuracy of measurement data transmission.

Keywords: electro-optical hybrid cable, underground photoelectric composite cable, seismic cable, coiled tubing, real-time monitoring

Procedia PDF Downloads 141

Authors: Yoshifumi Hino

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An infinitely repeated prisoner’s dilemma is a typical model that represents teamwork situation. If both players choose costly actions and contribute to the team, then both players are better off. However, each player has an incentive to choose a selfish action. We analyze the game under costly observation. Each player can observe the action of the opponent only when he pays an observation cost in that period. In reality, teamwork situations are often costly observation. Members of some teams sometimes work in distinct rooms, areas, or countries. In those cases, they have to spend their time and money to see other team members if they want to observe it. The costly observation assumption makes the cooperation difficult substantially because the equilibrium must satisfy the incentives not only on the action but also on the observational decision. Especially, it is the most difficult to cooperate each other when the stage-game is prisoner's dilemma because players have to communicate through only two actions. We examine whether or not players can cooperate each other in prisoner’s dilemma under costly observation. Specifically, we check whether symmetric Pareto efficient payoff vectors in repeated prisoner’s dilemma can be approximated by sequential equilibria or not (efficiency result). We show the efficiency result without any randomization device under certain circumstances. It means that players can cooperate with each other without any randomization device even if the observation is costly. Next, we assume that public randomization device is available, and then we show that any feasible and individual rational payoffs in prisoner’s dilemma can be approximated by sequential equilibria under a specific situation (folk theorem). It implies that players can achieve asymmetric teamwork like leadership situation when public randomization device is available.

Keywords: cost observation, efficiency, folk theorem, prisoner's dilemma, private monitoring, repeated games.

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Authors: Sarah M. Asar, Nabeel M. Elhady

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Egypt’s current per capita water share indicates that the country suffers and has been suffering from water poverty. The abundant utilization of turfgrass in Egypt’s new urban settlements, the reliance on freshwater for irrigation, and the inadequate plant selection increase the water demand in such settlements. Decreasing the surface area of turfgrass by using alternative landscape features such as mulching, using ornamental low-maintenance plants, increasing pathways, etc., could significantly decrease the water demand of urban landscapes. The use of Ammochloa palaestina, Cenchrus crientalis (Oriental Fountain Grass), and Cistus parviflorus (with water demands of approximately 0.005m³/m²/day) as alternatives for Cynodon dactylon (0.01m³/m²/day), which is the most commonly used grass species in Egypt’s landscape, could decrease an area’s water demand by approximately 40-50%. Moreover, creating hydro-zones of similar water demanding plants would enable irrigation facilitation rather than the commonly used uniformed irrigation. Such a practice could further reduce water consumption by 15-20%. These results are based on a case-study analysis of one of Egypt’s relatively new urban settlements, Al-Rehab. Such results emphasize the importance of utilizing native, drought-tolerant vegetation in the urban landscapes of Egypt to reduce irrigation demands. Furthermore, proper implementation, monitoring, and maintenance of automated irrigation systems could be an important factor in a space’s efficient water use. As most new urban settlements in Egypt adopt sprinkler and drip irrigation systems, the lack of maintenance leads to the manual operation of such systems, and, thereby, excessive irrigation occurs.

Keywords: alternative landscape, native plants, efficient irrigation, low water demand

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Authors: John Okanda Okwaro

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Carbon (IV) oxide (CO₂) is emitted majorly from fossil fuel combustion and industrial production. The sources of interest of carbon (IV) oxide in the study area are mining activities, transport systems, and industrial processes. This study is aimed at building models that will help in monitoring the emissions within the study area. Three scenarios were discussed, namely: pessimistic scenario, business-as-usual scenario, and optimistic scenario. The result showed that there was a reduction in carbon dioxide concentration by approximately 50.5 ppm between March 2020 and January 2021 inclusive. This is majorly due to reduced human activities that led to decreased consumption of energy. Also, the CO₂ concentration trend follows the business-as-usual scenario (BAU) path. From the models, the pessimistic, business-as-usual, and optimistic scenarios give CO₂ concentration of about 545.9 ppm, 408.1 ppm, and 360.1 ppm, respectively, on December 31st, 2021. This research helps paint the picture to the policymakers of the relationship between energy sources and CO₂ emissions. Since the reduction in CO₂ emission was due to decreased use of fossil fuel as there was a decrease in economic activities, then if Kenya relies more on green energy than fossil fuel in the post-COVID-19 period, there will be more CO₂ emission reduction. That is, the CO₂ concentration trend is likely to follow the optimistic scenario path, hence a reduction in CO₂ concentration of about 48 ppm by the end of the year 2021. This research recommends investment in solar energy by energy-intensive companies, mine machinery and equipment maintenance, investment in electric vehicles, and doubling tree planting efforts to achieve the 10% cover.

Keywords: forecasting, greenhouse gas, green energy, hierarchical data format

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Authors: Mandlenkosi George Robert Mahlobo, Tumelo Seadira, Major Melusi Mabuza, Peter Apata Olubambi

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Cathodic protection (CP) has been widely considered a suitable technique for mitigating corrosion of buried metal structures. Plenty of efforts have been made in developing techniques, in particular non-destructive techniques, for monitoring and quantifying the effectiveness of CP to ensure the sustainability and performance of buried steel structures. The aim of this study was to investigate the evolution of the electrochemical processes at the steel/soil interface during the application of CP on steel in simulated soil. Carbon steel was subjected to electrochemical tests with NS4 solution used as simulated soil conditions for 4 days before applying CP for a further 11 days. A previously modified non-destructive voltammetry technique was applied before and after the application of CP to measure the corrosion rate. Electrochemical impedance spectroscopy (EIS), in combination with mathematical modeling through equivalent electric circuits, was applied to determine the electrochemical behavior at the steel/soil interface. The measured corrosion rate was found to have decreased from 410 µm/yr to 8 µm/yr between days 5 and 14 because of the applied CP. Equivalent electrical circuits were successfully constructed and used to adequately model the EIS results. The modeling of the obtained EIS results revealed the formation of corrosion products via a mixed activation-diffusion mechanism during the first 4 days, while the activation mechanism prevailed in the presence of CP, resulting in a protective film. The x-ray diffraction analysis confirmed the presence of corrosion products and the predominant protective film corresponding to the calcareous deposit.

Keywords: carbon steel, cathodic protection, NS4 solution, voltammetry, EIS

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Authors: Mitsuo Yoshida

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A significant mercury contamination of soil/sediment was unveiled by an environmental monitoring program in a wetland along La Plata River, west to Montevideo City, Uruguay. The mercury contamination was caused by industrial wastewater discharged from a chlor-alkali plant using a mercury-cell process. The contamination level is above 60 mg/kg in soil/sediment. Most of mercury (Hg) in the environment is inorganic, but some fractions are converted by bacteria to methylmercury (MeHg), a toxic organic compound. MeHg biologically accumulates through a food-chain and become serious public health risk. In order to clarify the contaminated part for countermeasure operation, an intervention value of mercury contamination of sediment/soil was defined as 15 mg/kg (total Hg) by the authority. According to the intervention value, mercury contaminated area in the La Plata site is approximately 48,280 m² and estimated total volume of contaminated sediments/soils was around 18,750 m³. The countermeasures to contaminated zone were proposed in two stages; (i) mitigation of risks for public health and (ii) site remediation. The first stage is an installation of fens and net around the contamination zone, for mitigating risks of exposure, inhalation, and intake. The food chain among wetland-river ecosystem was also interrupted by the installation of net and fens. The state of mercury contamination in La Plata site and plan of countermeasure was disclosed to local people and the public, and consensus on setting off-limit area was successfully achieved. Mass media also contribute to share the information on the contamination site. The cost for countermeasures was borne by the industry under the polluter-pay-principle.

Keywords: chlor-alkali plant, mercury contamination, polluter pay principle, Uruguay, wetland

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Authors: M. Karimpour, L. Hitihamillage, N. Elkhoury, S. Moridpour, R. Hesami

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Rail transport authorities around the world have been facing a significant challenge when predicting rail infrastructure maintenance work for a long period of time. Generally, maintenance monitoring and prediction is conducted manually. With the restrictions in economy, the rail transport authorities are in pursuit of improved modern methods, which can provide precise prediction of rail maintenance time and location. The expectation from such a method is to develop models to minimize the human error that is strongly related to manual prediction. Such models will help them in understanding how the track degradation occurs overtime under the change in different conditions (e.g. rail load, rail type, rail profile). They need a well-structured technique to identify the precise time that rail tracks fail in order to minimize the maintenance cost/time and secure the vehicles. The rail track characteristics that have been collected over the years will be used in developing rail track degradation prediction models. Since these data have been collected in large volumes and the data collection is done both electronically and manually, it is possible to have some errors. Sometimes these errors make it impossible to use them in prediction model development. This is one of the major drawbacks in rail track degradation prediction. An accurate model can play a key role in the estimation of the long-term behavior of rail tracks. Accurate models increase the track safety and decrease the cost of maintenance in long term. In this research, a short review of rail track degradation prediction models has been discussed before estimating rail track degradation for the curve sections of Melbourne tram track system using Adaptive Network-based Fuzzy Inference System (ANFIS) model.

Keywords: ANFIS, MGT, prediction modeling, rail track degradation

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Authors: Gaya Bin Noon, Thoko Hanjahanja-Phiri, Laura Xavier Fadrique, Plinio Pelegrini Morita, Hélène Vaillancourt, Jennifer Teague, Tania Donovska

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Active Assisted Living (AAL) refers to systems designed to improve the quality of life, aid in independence, and create healthier lifestyles for care recipients. As the population ages, there is a pressing need for non-intrusive, continuous, adaptable, and reliable health monitoring tools to support aging in place. AAL has great potential to support these efforts with the wide variety of solutions currently available, but insufficient efforts have been made to address concerns arising from the integration of AAL into care. The purpose of this research was to (1) explore the integration of AAL technologies and data into the clinical pathway, and (2) map data access and governance for AAL technology in order to develop standards for use by policy-makers, technology manufacturers, and developers of smart communities for seniors. This was done through four successive research phases: (1) literature search to explore existing work in this area and identify lessons learned; (2) modeling of the continuum of care; (3) adapting a framework for data governance into the AAL context; and (4) interviews with stakeholders to explore the applicability of previous work. Opportunities for standards found in these research phases included a need for greater consistency in language and technology requirements, better role definition regarding who can access and who is responsible for taking action based on the gathered data, and understanding of the privacy-utility tradeoff inherent in using AAL technologies in care settings.

Keywords: active assisted living, aging in place, internet of things, standards

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Authors: Akbar Cahyadhi Pratama Putra, Tantri Utami Widhaningtyas, M. Randy Aswin

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Indonesia as an archipelagic nation have very long coastline which have large potential marine resources, one of that is the mangrove ecosystems. Lapindo mudflow disaster in Sidoarjo, East Java requires mudflow flowed into the sea through the river Brantas and Porong. Mud material that transported by river flow is feared dangerous because they contain harmful substances such as heavy metals. This study aims to map the mangrove ecosystem seen from its density and knowing how big the impact of a disaster on the Lapindo mud to mangrove ecosystem and accompanied by efforts to address the mangrove ecosystem that maintained continuity. Mapping coastal mangrove conditions of Sidoarjo was done using remote sensing products that Landsat 7 ETM + images with dry months of recording time in 2002, 2006, 2009, and 2014. The density of mangrove detected using NDVI that uses the band 3 that is the red channel and band 4 that is near IR channel. Image processing was used to produce NDVI using ENVI 5.1 software. NDVI results were used for the detection of mangrove density is 0-1. The development of mangrove ecosystems of both area and density from year to year experienced has a significant increase. Mangrove ecosystems growths are affected by material deposition area of Lapindo mud on Porong and Brantas river estuary, where the silt is growing medium suitable mangrove ecosystem and increasingly growing. Increasing the density caused support by public awareness to prevent heavy metals in the material so that the Lapindo mud mangrove breeding done around the farm.

Keywords: archipelagic nation, mangrove, Lapindo mudflow disaster, NDVI

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Authors: Andile Mkhohlakali, Tien-Chien Jen, James Tshilongo, Happy Mabowa

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Among different parameters, oxygen is one of the most important analytes of interest, dissolved oxygen (DO) concentration is very crucial and significant for various areas of physical, chemical, and environmental monitoring. Herein we report oxygen-sensitive luminophores -based lanthanum(III) trifluoromethanesulfonate), [La]³⁺ was encapsulated into SiO₂-based xerogel matrix. The nanosensor is composed of organically modified silica nanoparticles, doped with the luminescent oxygen–sensitive lanthanum(III) trifluoromethanesulfonate complex. The precursor materials used for sensing film were triethyl ethoxy silane (TEOS) and (3-Mercaptopropyltriethoxysilane) (MPTMS- TEOS) used for SiO2-baed matrices. Brunauer–Emmett–Teller (BET), and BJH indicate that the SiO₂ transformed from microporous to mesoporous upon the addition of La³⁺ luminophore with increased surface area (SBET). The typical amorphous SiO₂ based xerogels were revealed with X-Ray diffraction (XRD) and Selected Area Electron Diffraction (SAED) analysis. Scanning electron microscope- (SEM) and transmission electron microscope (TEM) showed the porous morphology and reduced particle for SiO₂ and La-SiO₂ xerogels respectively. The existence of elements, siloxane networks, and thermal stability of xerogel was confirmed by energy dispersive spectroscopy (EDS), Fourier-transform infrared spectroscopy (FTIR), and Thermographic analysis (TGA). UV-Vis spectroscopy and photoluminescence (PL) have been used to characterize the optical properties of xerogels. La-SiO₂ demonstrates promising characteristic features of an active sensing film for dissolved oxygen in the water. Keywords: Sol-gel, ORMOSILs, encapsulation, Luminophores quenching, O₂-sensing

Keywords: sol-gel, ORMOSILs, luminophores quenching, O₂-sensing

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Authors: Rudy Bahouth, Farouk Benmeddour, Emmanuel Moulin, Jamal Assaad

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Guided ultrasonic waves are used in Non-Destructive Testing (NDT) and Structural Health Monitoring (SHM) for inspection and damage detection. Recently, wireless data transmission using ultrasonic waves in solid metallic channels has gained popularity in some industrial applications such as nuclear, aerospace and smart vehicles. The idea is to find a good substitute for electromagnetic waves since they are highly attenuated near metallic components due to Faraday shielding. The proposed solution is to use ultrasonic guided waves such as Lamb waves as an information carrier due to their capability of propagation for long distances. In addition to this, valuable information about the health of the structure could be extracted simultaneously. In this work, the reliable frequency bandwidth for communication is extracted experimentally from dispersion curves at first. Then, an experimental platform for wireless communication using Lamb waves is described and built. After this, coherent demodulation algorithm used in telecommunications is tested for Amplitude Shift Keying, On-Off Keying and Binary Phase Shift Keying modulation techniques. Signal processing parameters such as threshold choice, number of cycles per bit and Bit Rate are optimized. Experimental results are compared based on the average Bit Error Rate. Results have shown high sensitivity to threshold selection for Amplitude Shift Keying and On-Off Keying techniques resulting a Bit Rate decrease. Binary Phase Shift Keying technique shows the highest stability and data rate between all tested modulation techniques.

Keywords: lamb waves communication, wireless communication, coherent demodulation, bit error rate

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Authors: Zarabizan Zakaria, Syuhaida Ismail, Aminah Md. Yusof

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Project management process starts from the planning stage up to the stage of completion (handover of buildings, preparation of the final accounts and the closing balance). This process is not easy to implement efficiently and effectively. The issue of delays in construction is a major problem for construction projects. These delays have been blamed mainly on inefficient traditional construction practices that continue to dominate the current industry. This is due to several factors, such as environments of construction technology, sophisticated design and customer demands that are constantly changing and influencing, either directly or indirectly, the practice of management. Among the identified influences are physical environment, social environment, information environment, political and moral atmosphere. Therefore, this paper is emerged to determine the problem and issues in the final account closing in construction projects, and it establishes the need to embrace Supply Chain Management (SCM) and then elucidates the need and strategies for the development of a delay reduction framework. At the same time, this paper provides effective measures to avoid or at least reduce the delay to the optimum level. Allowing problems in the closure declaration to occur without proper monitoring and control can leave negative impact on the cost and time of delivery to the end user. Besides, it can also affect the reputation or image of the agency/department that manages the implementation of a contract and consequently may reduce customer's trust towards the agencies/departments. It is anticipated that the findings reported in this paper could address root delay contributors and apply SCM tools for their mitigation for the better development of construction project.

Keywords: final account closing, construction project, construction delay, supply chain management

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Authors: Maatouk Mohamed, Nouira Mariem

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Background and aims: Healthcare-associated infections (HAI) represent a major public health problem worldwide. They represent one of the most serious adverse events in health care. The objectives of our study were to estimate the prevalence of HAI at the Charles Nicolle Hospital (CNH) and to identify the main associated factors as well as to estimate the frequency of antibiotic use. Methods: It was a cross sectional study at the CNH with a unique passage per department (OctoberDecember 2018). All patients present at the wards for more than 48 hours were included. All patients from outpatient consultations, emergency and dialysis departments were not included. The site definitions of infections proposed by the Centers for Disease Control and Prevention (CDC) were used. Only clinically and/or microbiologically confirmed active HAIs were included. Results: A total of 318 patients were included with a mean age of 52 years and a sex ratio (Female/Male) of 1.05. A total of 41 patients had one or more active HAIs, corresponding to a prevalence of 13.1% (95% CI: 9.3%-16.9%). The most frequent sites infections were urinary tract infections and pneumonia. Multivariate analysis among adult patients (>=18 years) (n=261), revealed that infection on admission (p=0.01), alcoholism (p=0.01), high blood pressure (p=0.008), having at least one invasive device inserted (p=0.004), and history of recent surgery (p=0.03), increased significantly the risk of HAIs. More than 1 of 3 patients (35.4%) were under antibiotics on the day of the survey, of which more than half (57.4%) were under 2 or more types of antibiotics. Conclusion: The prevalence of HAIs and antibiotic prescriptions at the CNH were considerably high. An infection prevention and control committee, as well as the development of an Antibiotic stewardship program with continuous monitoring using repeated prevalence surveys must be implemented to limit the frequency of these infections effectively.

Keywords: tumors, oesophagectomy, esophagogastric junction, systematic review

Procedia PDF Downloads 81