Search results for: driving monitoring

Authors: S. Palaniyappan, P. K. Chennam, M. Trautmann, H. Ahmad, T. Mehner, T. Lampke, G. Wagner

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In structural-health monitoring of fiber reinforced plastics (FRPs), every single inorganic fiber sensor that are integrated into the bulk material requires an electrical insulation around itself, when the surrounding reinforcing fibers are electrically conductive. This results in a more accurate data acquisition only from the sensor fiber without any electrical interventions. For this purpose, thin nano-films of aluminium oxide (Al₂O₃)-based electrical-insulation coatings have been fabricated around the Silicon Carbide (SiC) single fiber sensors through reactive DC magnetron sputtering technique. The sputtered coatings were amorphous in nature and the thickness of the coatings increased with an increase in the sputter time. Microstructural characterization of the coated fibers performed using scanning electron microscopy (SEM) confirmed a homogeneous circumferential coating with no detectable defects or cracks on the surface. X-ray diffraction (XRD) analyses of the as-sputtered and 2 hours annealed coatings (825 & 1125 ˚C) revealed the amorphous and crystalline phases of Al₂O₃ respectively. Raman spectroscopic analyses produced no characteristic bands of Al₂O₃, as the thickness of the films was in the nanometer (nm) range, which is too small to overcome the actual penetration depth of the laser used. In addition, the influence of the insulation coatings on the mechanical properties of the SiC sensor fibers has been analyzed.

Keywords: Al₂O₃ thin film, electrical insulation coating, PVD process, SiC fibre, single fibre tensile test

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Authors: Salamatu Sani

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This study is an investigation of how code-mixing manifests in the language development of a Nigerian child, especially in the Hausa speaking environment. It is hinged on the fact that the environment influences the first language acquired by a child regardless of the cultural and/or linguistic background of the parents. The child under investigation has been subjected to close monitoring on her speech hitherto. It is a longitudinal study covering a period of twelve months (January 2018 to December 2018); that was when the subject was between twenty-four and thirty months of age. The speeches have been recorded by means of a tape recorder, video, and a diary. The study employs as a theoretical framework, emergentism, which is an eclectic of the behaviourist and the mentalist theories to the study of language development, for analysis. This is in agreement with the positions of Skinner and Watson. Sequel to this investigation, it was discovered the environment is a major factor that influences the exposure of a child to a language more than the other factors and that, if a child is exposed to more than one language, there is a great tendency for such a child to code-mix and code-switch in her speech production. The child under investigation, in spite of the linguistic background of her parents, speaks the Hausa Language much better than the other languages around her though with remarkable code-mixing with other languages around her such as English and Ebira languages. The study concludes that although a child is born with the innate ability to acquire a particular language, the environment plays a key role to trigger the innate ability and consequently, the child is exposed to the acquisition of the dominant language around her at a particular given time.

Keywords: bilingual, code-mixing, emergentism, environment, Hausa

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Authors: Zheng Sun, Weiwei Cui, Xiaodong Ma, Hongxin Jin, Dongpao Hong, Jinsong Yang, Jingyi Sun

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With the improvement of the performance and complexity of modern equipment, automatic test system (ATS) becomes widely used for condition monitoring and fault diagnosis. However, the conventional ATS mainly works in a serial mode, and lacks the ability of testing several equipments at the same time. That leads to low test efficiency and ATS redundancy. Especially for a large majority of equipment under test, the conventional ATS cannot meet the requirement of efficient testing. To reduce the support resource and increase test efficiency, we propose a method of design for the parallel test based on the embedded system in this paper. Firstly, we put forward the general framework of the parallel test system, and the system contains a central management system (CMS) and several distributed test subsystems (DTS). Then we give a detailed design of the system. For the hardware of the system, we use embedded architecture to design DTS. For the software of the system, we use test program set to improve the test adaption. By deploying the parallel test system, the time to test five devices is now equal to the time to test one device in the past. Compared with the conventional test system, the proposed test system reduces the size and improves testing efficiency. This is of great significance for equipment to be put into operation swiftly. Finally, we take an industrial control system as an example to verify the effectiveness of the proposed method. The result shows that the method is reasonable, and the efficiency is improved up to 500%.

Keywords: parallel test, embedded system, automatic test system, automatic test system (ATS), central management system, central management system (CMS), distributed test subsystems, distributed test subsystems (DTS)

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Authors: Luan Vardari, Dena Arapi Vardari

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The Balkan countries, known for their diverse landscapes and cultural heritage, face the dual challenge of promoting economic growth while addressing pressing environmental concerns. In recent years, the concept of green finance has emerged as a powerful tool to achieve sustainable development and mitigate the environmental impact of various sectors, including architecture. This extended abstract explores the untapped potential of green finance in architecture within the Balkan region and highlights its role in driving sustainable construction practices and fostering a greener future. The abstract begins by defining green finance and emphasizing its relevance in the context of the architectural sector in Balkan countries. It underlines the benefits of green finance, such as economic growth, environmental conservation, and social well-being. Integrating green finance into architectural projects is important as a means to achieve sustainable development goals while promoting financial viability. Also, delves into the current state of green building practices in the Balkan countries and identifies the need for financial support to further drive adoption. It explores the existing regulatory frameworks and policies that promote sustainable architecture and discusses how green finance can complement these initiatives. Unique challenges faced by Balkan countries are highlighted, along with the potential opportunities that green finance presents in overcoming these challenges. We highlight successful sustainable architectural projects in the region to showcase the practical application of green finance in the Balkans. These projects exemplify the effective utilization of green finance mechanisms, resulting in tangible economic and environmental impacts, including job creation, energy efficiency, and reduced carbon emissions. The abstract concludes by identifying replicable models and lessons learned from these projects that can serve as a blueprint for future sustainable architecture initiatives in the Balkans. The importance of collaboration and knowledge sharing among stakeholders is emphasized. Engaging architects, financial institutions, governments, and local communities is crucial to promoting green finance in architecture. The abstract suggests the establishment of knowledge exchange platforms and regional/international networks to foster collaboration and facilitate the sharing of expertise among Balkan countries.

Keywords: sustainable finance, renewable energy, Balkan region, investment opportunities, green infrastructure, ESG criteria, architecture

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Authors: Ahmed Aboforn

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Butene-1 product is consider effectively raw material in Polyethylene production, however Oxygenates impurities existing will be effected ethylene/butene-1 copolymers synthesized through titanium-magnesium-supported Ziegler-Natta catalysts. Laterally, Petrochemical industries are challenge against poor quality of Butene-1 and other C4 mix – feedstock that reflected on business impact and production losing. In addition, propylene product suffering from contamination by oxygenates components and causing for lose production and plant upset of Polypropylene process plants. However, Multidimensional gas chromatography (MDGC) innovative analytical methodology is a chromatography technique used to separate complex samples, as mixing different functional group as Hydrocarbon and oxygenates compounds and have similar retention factors, by running the eluent through two or more columns instead of the customary single column. This analytical study striving to enhance the quality of Oxygenates analytical method, as monitoring the concentration of oxygenates with accurate and precise analytical method by utilizing multidimensional GC supported by Backflush technique and Flame Ionization Detector, which have high performance separation of hydrocarbon and Oxygenates; also improving the minimum detection limits (MDL) to detect the concentration <1.0 ppm. However different types of oxygenates as (Alcohols, Aldehyde, Ketones, Ester and Ether) may be determined in other Hydrocarbon streams asC3, C4-mix, until C12 mixture, supported by liquid injection auto-sampler.

Keywords: analytical chemistry, gas chromatography, petrochemicals, oxygenates

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Authors: G. La Scalia, M. Enea, R. Micale, O. Corona, L. Settanni

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The quality and condition of perishable products delivered to the market and their subsequent selling prices are directly affected by the care taken during harvesting and handling. Mechanical injury, in fact, occurs at all stages, from pre-harvest operations through post-harvest handling, packing and transport to the market. The main implications of this damage are the reduction of the product’s quality and economical losses related to the shelf life diminution. For most perishable products, the shelf life is relatively short and it is typically dictated by microbial growth related to the application of dynamic and static loads during transportation. This paper presents the correlation between vibration levels and microbiological growth on strawberries and woodland strawberries and detects the presence of volatile organic compounds (VOC) in order to develop an intelligent logistic unit capable of monitoring VOCs using a specific sensor system. Fresh fruits were exposed to vibrations by means of a vibrating table in a temperature-controlled environment. Microbiological analyses were conducted on samples, taken at different positions along the column of the crates. The values obtained were compared with control samples not exposed to vibrations and the results show that different positions along the column influence the development of bacteria, yeasts and filamentous fungi.

Keywords: microbiological analysis, shelf life, transport damage, volatile organic compounds

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Authors: Hasan Kalyoncu, Füsun Kılçık, Hatice Gülboy Akyıldırım, Aynur Özen, Mehmet Acar, Nur Yoluk

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For evaluation of water quality of the river systems in Antalya Basin, macrozoobenthos samples were taken from 22 determined stations by a hand net and identified at family level. Water quality of Antalya Basin was determined according to Biological Monitoring Working Party (BMWP) system, by using macrozoobenthic invertebrates and physicochemical parameters. As a result of the evaluation, while Aksu Stream was determined as the most polluted stream in Antalya Basin, Isparta Stream was determined as the most polluted tributary of Aksu Stream. Pollution level of the Isparta Stream was determined as quality class V and it is the extremely polluted part of stream. Pollution loads at the sources of the streams were determined in low levels in general. Due to some parts of the streams have passed through deep canyons and take their sources from nonresidential and non-arable regions, majority of the streams that take place in Antalya Basin are at high quality level. Waste water, which comes from agricultural and residential regions, affects the lower basins of the streams. Because of the waste water, lower parts of the stream basins exposed to the pollution under anthropogenic effects. However, in Aksu Stream, which differs by being exposed to domestic and industrial wastes of Isparta City, extreme pollution was determined, particularly in the Isparta Stream part.

Keywords: Antalya basin, biomonitoring, BMWP, water quality

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Authors: Mohammad A. N. M. Shafiqul Karim

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As a developing country, Bangladesh has to face numerous challenges. Self Independence in electricity, contributing to climate change by reducing carbon emission and bringing the backward population of society to the mainstream is more challenging for them. Therefore, it is essential to ensure recycled use of local products to the maximum level in every sector. Some private organizations have already worked alongside government to bring the backward population to the mainstream by developing their financial capacities. As rice husk is the largest single category of the total energy supply in Bangladesh. As part of this strategy, rice husk can play a great as a promising renewable energy source, which is readily available, has considerable environmental benefits and can produce electricity and ensure multiple uses of byproducts in construction technology. For the first time in Bangladesh, an experimental multidimensional project depending on Rice Husk Electricity and Rice Husk Ash (RHA) concrete brick/block under Green Eco-Tech Limited has already been started. Project analysis, opportunity, sustainability, the high monitoring component, limitations and finally evaluated data reflecting the viability of establishing more projects using rice husk are discussed in this paper. The by-product of rice husk from the production of green electricity, RHA, can be used for making, in particular, RHA concrete brick/block in Bangladeshi aspects is also discussed here.

Keywords: project analysis, rice husk, rice husk ash concrete brick/block, compressive strength of rice husk ash concrete brick/block

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Authors: Yu-Lin Chen, Kimberly Koester, Marissa Raymond-Flesh, Anika Thapar, Jay Thapar

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Purpose: Effectively communicating adolescent health topics to teens and their parents is crucial. This study emphasizes critically evaluating the optimal use of artificial intelligence tools (AI), which are increasingly prevalent in disseminating health information. By fostering a deeper understanding of AI voice preference in the context of health, the research aspires to have a ripple effect, enhancing the collective health literacy and decision-making capabilities of both teenagers and their parents. This study explores AI voices' potential within health learning modules for annual well-child visits. We aim to identify preferred voice characteristics and understand factors influencing perceived trustworthiness, ultimately aiming to improve health literacy and decision-making in both demographics. Methods: A cross-sectional study assessed preferences and trust perceptions of AI voices in learning modules among teens (11-18) and their parents/guardians in Northern California. The study involved the development of four distinct learning modules covering various adolescent health-related topics, including general communication, sexual and reproductive health communication, parental monitoring, and well-child check-ups. Participants were asked to evaluate eight AI voices across the modules, considering a set of six factors such as intelligibility, naturalness, prosody, social impression, trustworthiness, and overall appeal, using Likert scales ranging from 1 to 10 (the higher, the better). They were also asked to select their preferred choice of voice for each module. Descriptive statistics summarized participant demographics. Chi-square/t-tests explored differences in voice preferences between groups. Regression models identified factors impacting the perceived trustworthiness of the top-selected voice per module. Results: Data from 104 participants (teen=63; adult guardian = 41) were included in the analysis. The mean age is 14.9 for teens (54% male) and 41.9 for the parent/guardian (12% male). At the same time, similar voice quality ratings were observed across groups, and preferences varied by topic. For instance, in general communication, teens leaned towards young female voices, while parents preferred mature female tones. Interestingly, this trend reversed for parental monitoring, with teens favoring mature male voices and parents opting for mature female ones. Both groups, however, converged on mature female voices for sexual and reproductive health topics. Beyond preferences, the study delved into factors influencing perceived trustworthiness. Interestingly, social impression and sound appeal emerged as the most significant contributors across all modules, jointly explaining 71-75% of the variance in trustworthiness ratings. Conclusion: The study emphasizes the importance of catering AI voices to specific audiences and topics. Social impression and sound appeal emerged as critical factors influencing perceived trustworthiness across all modules. These findings highlight the need to tailor AI voices by age and the specific health information being delivered. Ensuring AI voices resonate with both teens and their parents can foster their engagement and trust, ultimately leading to improved health literacy and decision-making for both groups. Limitations and future research: This study lays the groundwork for understanding AI voice preferences for teenagers and their parents in healthcare settings. However, limitations exist. The sample represents a specific geographic location, and cultural variations might influence preferences. Additionally, the modules focused on topics related to well-child visits, and preferences might differ for more sensitive health topics. Future research should explore these limitations and investigate the long-term impact of AI voice on user engagement, health outcomes, and health behaviors.

Keywords: artificial intelligence, trustworthiness, voice, adolescent

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Authors: Ian Walsh, Terry Nguyen-Khuong, Christopher H. Taron, Pauline M. Rudd

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Glycoproteins and their covalently bonded glycans play critical roles in the immune system, cell communication, disease and disease prognosis. Ultra performance liquid chromatography (UPLC) coupled with mass spectrometry is conventionally used to qualitatively and quantitatively characterise glycan structures in a given sample. Exoglycosidases are enzymes that catalyze sequential removal of monosaccharides from the non-reducing end of glycans. They naturally have specificity for a particular type of sugar, its stereochemistry (α or β anomer) and its position of attachment to an adjacent sugar on the glycan. Thus, monitoring the peak movements (both in the UPLC and MS1) after application of exoglycosidases provides a unique and effective way to annotate sugars with high detail - i.e. differentiating positional and linkage isomers. Manual annotation of an exoglycosidase experiment is difficult and time consuming. As such, with increasing sample complexity and the number of exoglycosidases, the analysis could result in manually interpreting hundreds of peak movements. Recently, we have implemented pattern recognition software for automated interpretation of UPLC-MS1 exoglycosidase digestions. In this work, we explain the software, indicate how much time it will save and provide example usage showing the annotation of positional and linkage isomers in Immunoglobulin G, apolipoprotein J, and simple glycan standards.

Keywords: bioinformatics, automated glycan assignment, liquid chromatography, mass spectrometry

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Authors: Zheni S. Stefanova, Kandethody M. Ramachandran

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With the increasing dependency on our computer devices, we face the necessity of adequate, efficient and effective mechanisms, for protecting our network. There are two main problems that Intrusion Detection Systems (IDS) attempt to solve. 1) To detect the attack, by analyzing the incoming traffic and inspect the network (intrusion detection). 2) To produce a prompt response when the attack occurs (intrusion prevention). It is critical creating an Intrusion detection model that will detect a breach in the system on time and also challenging making it provide an automatic and with an acceptable delay response at every single stage of the monitoring process. We cannot afford to adopt security measures with a high exploiting computational power, and we are not able to accept a mechanism that will react with a delay. In this paper, we will propose an intrusion response mechanism that is based on artificial intelligence, and more precisely, reinforcement learning techniques (RLT). The RLT will help us to create a decision agent, who will control the process of interacting with the undetermined environment. The goal is to find an optimal policy, which will represent the intrusion response, therefore, to solve the Reinforcement learning problem, using a Q-learning approach. Our agent will produce an optimal immediate response, in the process of evaluating the network traffic.This Q-learning approach will establish the balance between exploration and exploitation and provide a unique, self-learning and strategic artificial intelligence response mechanism for IDS.

Keywords: cyber security, intrusion prevention, optimal policy, Q-learning

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Authors: Tayyaba Bibi, Jenny Ronan, Robert Hernan, Kathleen O’Rourke, Brendan McHugh, Evin McGovern, Michelle Giltrap, Gordon Chambers, James Wilson

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Sediment contamination is a major source of ecosystem stress and has received significant attention from the scientific community. Both the Water Framework Directive (WFD) and Marine Strategy Framework Directive (MSFD) require a robust set of tools for biological and chemical monitoring. For the MSFD in particular, causal links between contaminant and effects need to be assessed. Appropriate assessment tools are required in order to make an accurate evaluation. In this study, a range of recommended sediment bioassays and chemical measurements are assessed in a number of potentially impacted and lowly impacted locations around Ireland. Previously, assessment indices have been developed on individual compartments, i.e. contaminant levels or biomarker/bioassay responses. A number of assessment indices are applied to chemical and ecotoxicological data from the Seachange project (Project code) and compared including the metal pollution index (MPI), pollution load index (PLI) and Chapman index for chemistry as well as integrated biomarker response (IBR). The benefits and drawbacks of the use of indices and aggregation techniques are discussed. In addition to this, modelling of raw data is investigated to analyse links between contaminant and effects.

Keywords: bioassays, contamination indices, ecotoxicity, marine environment, sediments

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Authors: Jeong Woo Kang, MiYoung Baek, Ki-Suk Kim, Kwang-Jick Lee, ByungJae So

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Introduction: A fast, easy and sensitive detection method was developed and validated by liquid chromatography tandem mass spectrometry for the determination of marbofloxacin in pig plasma which was further applied to study the pharmacokinetics of marbofloxacin. Materials and Methods: The plasma sample (500 μL) was mixed with 1.5 ml of 0.1% formic acid in MeCN to precipitate plasma proteins. After shaking for 20 min, The mixture was centrifuged at 5,000 × g for 30 min. It was dried under a nitrogen flow at 50℃. 500 μL aliquot of the sample was injected into the LC-MS/MS system. Chromatographic analysis was carried out mobile phase gradient consisting 0.1% formic acid in D.W. (A) and 0.1% formic acid in MeCN (B) with C18 reverse phase column. Mass spectrometry was performed using the positive ion mode and the selected ion monitoring (MRM). Results and Conclusions: The method validation was performed in the sample matrix. Good linearities (R2>0.999) were observed and the quantified average recoveries of marbofloxacin were 87 - 92% at level of 10 ng g-1 -100 ng g-1. The percent of coefficient of variation (CV) for the described method was less than 10 % over the range of concentrations studied. The limits of detection (LOD) and quantification (LOQ) were 2 and 5 ng g-1, respectively. This method has also been applied successfully to pharmacokinetic analysis of marbofloxacin after intravenous (IV), intramuscular (IM) and oral administration (PO). The mean peak plasma concentration (Cmax) was 2,597 ng g-1at 0.25 h, 2,587 ng g-1at 0.44 h and 2,355 ng g-1at 1.58 h for IV, IM and PO, respectively. The area under the plasma concentration-time curve (AUC0–t) was 24.8, 29.0 and 25.2 h μg/mL for IV, IM and PO, respectively. The elimination half-life (T1/2) was 8.6, 13.1 and 9.5 for IV, IM and PO, respectively. Bioavailability (F) of the marbofloxacin in pig was 117 and 101 % for IM and PO, respectively. Based on these result, marbofloxacin does not have any obstacles as therapeutics to develop the oral formulations such as tablets and capsules.

Keywords: marbofloxacin, LC-MS/MS, pharmacokinetics, chromatographic

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Authors: Oluwafunmibi Omotayo Fasanya, Augustine Kena Adjei

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Depression has emerged as a growing public health issue, with the limited effectiveness of current treatment methods driving the search for modifiable lifestyle factors. Physical inactivity and poor dietary habits are consistently identified as factors associated with increased depression symptoms. While the independent effects of physical activity (PA) and dietary quality (DQ) on mental health are well established, the combined influence of both factors on depression has not been thoroughly examined in a representative sample of U.S. adults. This study aims to explore the individual and joint associations of PA and DQ with depression symptoms, highlighting their combined impact on adults across the U.S. Using data from the National Health and Nutrition Examination Survey (NHANES) from 2007 to 2020, we evaluated the relationships between PA (measured through metabolic equivalent (MET) minutes per week) and DQ (assessed using the Healthy Eating Index [HEI]-2015) and depression symptoms (defined by a score of ≥10 on the 9-item Patient Health Questionnaire [PHQ-9]). Participants were classified into four lifestyle categories: (1) healthy diet and active, (2) unhealthy diet but active, (3) healthy diet but inactive, and (4) unhealthy diet and inactive. Logistic regression models adjusted for relevant covariates were used to examine associations, with age-adjusted prevalence rates for depression calculated according to NHANES guidelines. Data from 21,530 participants, representing approximately 954 million U.S. adults aged 20-80 years, were analyzed. The overall age-adjusted prevalence of depression symptoms was 7.15%. A total of 83.1% of participants met PA recommendations, and 27.3% scored above the 60th percentile in the HEI-2015 index. Higher PA levels were inversely related to depression symptoms (adjusted odds ratio [AOR]: 0.805; 95% CI: 0.724-0.920), as was better dietary quality (AOR: 0.788; 95% CI: 0.690-0.910). A combination of healthy diet and adequate PA was associated with the lowest risk of depression symptoms (AOR: 0.635; 95% CI: 0.520-0.775) compared to inactive participants with unhealthy diets. Notably, participants with either a healthy diet or adequate PA but not both did not experience the same reduction in depression risk. This study highlights that the combination of a healthy diet and regular physical activity offers a synergistic protective effect against depression symptoms in U.S. adults. Public health initiatives targeting both dietary improvements and increased physical activity may significantly reduce the burden of depression across populations. Further research should focus on understanding the mechanisms underlying these interactions.

Keywords: dietary quality, physical activity, depression, healthy eating

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Authors: G. A. Adamu, M. S. Sallau, S. O. Idris, E. B. Agbaji

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Drinking water is supplied to Danbatta, Makoda and some parts of Minjibir local government areas of Kano State from the surface water of Thomas Reservoir. The present land use in the catchment area of the reservoir indicates high agricultural activities, fishing, as well as domestic and small scale industrial activities. To study and monitor the quality of surface and drinking water of the area, water samples were collected from the reservoir, treated water at the treatment plant and potable water at the consumer end in three seasons November - February (cold season), March - June (dry season) and July - September (rainy season). The samples were analyzed for physical and chemical parameters, pH, temperature, total dissolved solids (TDS), conductivity, turbidity, total hardness, suspended solids, total solids, colour, dissolved oxygen (DO), biological oxygen demand (BOD), chloride ion (Cl^-) nitrite (NO₂^-), nitrate (NO₃^-), chemical oxygen demand (COD) and phosphate (PO₄^3-). The higher values obtained in some parameters with respect to the acceptable standard set by World Health Organization (WHO) and Nigerian Industrial Standards (NIS) indicate the pollution of both the surface and drinking water. These pollutants were observed to have a negative impact on water quality in terms of eutrophication, largely due to anthropogenic activities in the watershed.

Keywords: surface water, drinking water, water quality, pollution, Thomas reservoir, Kano

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Authors: Hossam E. Emam

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The functional textiles development history in the military field could be ascribed as a uniquely interesting research topic. Soldiers are like a high-performance athletes, where monitoring their physical and physiological capabilities is a vital requirement. Functional clothes represent a “second skin” that has a close, “intimate” relationship with the human body. For the application of textiles in military purposes, which is normally required in difficult weather and environmental conditions, several functions are required. The requirements for designing functional military textiles for soldier's protection can be categorized into three categories; i) battle field (protection from chemical warfare agents, flames, and thermal radiation), ii) environmental (water proof, air permeable, UV-protection, antibacterial), iii) physiological (minimize heat stress, low weight, insulative, durability). All of these requirements are important, but the means to fulfill these requirements are not simple and straight forward. Additionally, the combination of more than one function is reported to be very expensive and requires many complicated steps, and the final product is found to be low durability. Not only do all of these requirements are overlapping, but they are also contradicting each other at various levels. Thus, we plan to produce multi-functional textiles (e.g., anti-microbial, UV-protection, fire retardant, photoluminescent) to be applied in military clothes. The current project aims to use quite a simple and applicable technique through the modification of textiles with different coordination polymers and functionalized coordination polymers.

Keywords: functional textiles, military clothes, coordination polymers, antimicrobial, fire retardant, photolumenscent

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Authors: Mera Ababneh, Sayer Al-Azzam, Karem Alzoubi, Abeer Rababa'h

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Background: Medication errors are among the most common medical errors. Their occurrences result in patient’s mortality, morbidity, and additional healthcare costs. Continuous monitoring and detection is required. Objectives: The aim of this study was to compare medication errors in outpatient’s prescriptions in two different hospitals (paper system vs. electronic system). Methods: This was a cross sectional observational study conducted in two major hospitals; King Abdullah University Hospital (KAUH) and Princess Bassma Teaching Hospital (PBTH) over three months period. Data collection was conducted by two trained pharmacists at each site. During the study period, medication prescriptions and dispensing procedures were screened for medication errors in both participating centers by two trained pharmacist. Results: In the electronic prescription hospital, 2500 prescriptions were screened in which 631 medication errors were detected. Prescription errors were 231 (36.6%), and dispensing errors were 400 (63.4%) of all errors. On the other side, analysis of 2500 prescriptions in paper-based hospital revealed 3714 medication errors, of which 288 (7.8%) were prescription errors, and 3426 (92.2%) were dispensing errors. A significant number of 2496 (67.2%) were inadequately and/or inappropriately labeled. Conclusion: This study provides insight for healthcare policy makers, professionals, and administrators to invest in advanced technology systems, education, and epidemiological surveillance programs to minimize medication errors.

Keywords: medication errors, prescription errors, dispensing errors, electronic prescription, handwritten prescription

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Authors: Gaetano Zazzaro, Angelo Martone, Roberto V. Montaquila, Luigi Pavone

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Seizure is the main factor that affects the quality of life of epileptic patients. The diagnosis of epilepsy, and hence the identification of epileptogenic zone, is commonly made by using continuous Electroencephalogram (EEG) signal monitoring. Seizure identification on EEG signals is made manually by epileptologists and this process is usually very long and error prone. The aim of this paper is to describe an automated method able to detect seizures in EEG signals, using knowledge discovery in database process and data mining methods and algorithms, which can support physicians during the seizure detection process. Our detection method is based on Artificial Neural Network classifier, trained by applying the multilayer perceptron algorithm, and by using a software application, called Training Builder that has been developed for the massive extraction of features from EEG signals. This tool is able to cover all the data preparation steps ranging from signal processing to data analysis techniques, including the sliding window paradigm, the dimensionality reduction algorithms, information theory, and feature selection measures. The final model shows excellent performances, reaching an accuracy of over 99% during tests on data of a single patient retrieved from a publicly available EEG dataset.

Keywords: artificial neural network, data mining, electroencephalogram, epilepsy, feature extraction, seizure detection, signal processing

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Authors: Lubna Eljabu, Mohammad Etemad, Stan Matwin

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Port authorities have many challenges in congested ports to allocate their resources to provide a safe and secure loading/ unloading procedure for cargo vessels. Selecting a destination port is the decision of a vessel master based on many factors such as weather, wavelength and changes of priorities. Having access to a tool which leverages AIS messages to monitor vessel’s movements and accurately predict their next destination port promotes an effective resource allocation process for port authorities. In this research, we propose a method, namely, Reference Route of Trajectory (RRoT) to assist port authorities in predicting inflow and outflow traffic in their local environment by monitoring Automatic Identification System (AIS) messages. Our RRoT method creates a reference route based on historical AIS messages. It utilizes some of the best trajectory similarity measure to identify the destination of a vessel using their recent movement. We evaluated five different similarity measures such as Discrete Fr´echet Distance (DFD), Dynamic Time Warping (DTW), Partial Curve Mapping (PCM), Area between two curves (Area) and Curve length (CL). Our experiments show that our method identifies the destination port with an accuracy of 98.97% and an fmeasure of 99.08% using Dynamic Time Warping (DTW) similarity measure.

Keywords: spatial temporal data mining, trajectory mining, trajectory similarity, resource optimization

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Authors: Marcela de Oliveira, Guilherme Giacomini, Allan Felipe Fattori Alves, Ana Luiza Menegatti Pavan, Maria Eugenia Dela Rosa, Fernando Antonio Bacchim Neto, Diana Rodrigues de Pina

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It is estimated that each year one death every 10 seconds (about 2 million deaths) in the world is attributed to tuberculosis (TB). Even after effective treatment, TB leaves sequelae such as, for example, pulmonary fibrosis, compromising the quality of life of patients. Evaluations of the aforementioned sequel are usually performed subjectively by radiology specialists. Subjective evaluation may indicate variations inter and intra observers. The examination of x-rays is the diagnostic imaging method most accomplished in the monitoring of patients diagnosed with TB and of least cost to the institution. The application of computational algorithms is of utmost importance to make a more objective quantification of pulmonary impairment in individuals with tuberculosis. The purpose of this research is the use of computer algorithms to quantify the pulmonary impairment pre and post-treatment of patients with pulmonary TB. The x-ray images of 10 patients with TB diagnosis confirmed by examination of sputum smears were studied. Initially the segmentation of the total lung area was performed (posteroanterior and lateral views) then targeted to the compromised region by pulmonary sequel. Through morphological operators and the application of signal noise tool, it was possible to determine the compromised lung volume. The largest difference found pre- and post-treatment was 85.85% and the smallest was 54.08%.

Keywords: algorithm, radiology, tuberculosis, x-rays exam

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Authors: Volker Landersheim, Daria Manushyna, Thinh Pham, Dai-Duong Tran, Thomas Geury, Omar Hegazy, Steven Wilkins

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Air pollution is one of the emerging problems in our society. Targets of reduction of CO₂ emissions address low-carbon and resource-efficient transport. (Plug-in) hybrid electric propulsion concepts offer the possibility to reduce total cost of ownership (TCO) and emissions for public transport vehicles (e.g., bus application). In this context, typically, diesel engines are used to form the hybrid propulsion system of the vehicle. Though the technological development of diesel engines experience major advantages, some challenges such as the high amount of particle emissions remain relevant. Gaseous fuels (i.e., compressed natural gases (CNGs) or liquefied petroleum gases (LPGs) represent an attractive alternative to diesel because of their composition. In the framework of the research project 'Optimised Real-world Cost-Competitive Modular Hybrid Architecture' (ORCA), which was funded by the EU, two different hybrid-electric propulsion concepts have been investigated: one using a diesel engine as internal combustion engine and one using CNG as fuel. The aim of the current study is to analyze specific benefits for the aforementioned hybrid propulsion systems for predefined driving scenarios with regard to emissions and total cost of ownership in bus application. Engine models based on experimental data for diesel and CNG were developed. For the purpose of designing optimal energy management strategies for each propulsion system, maps-driven or quasi-static models for specific engine types are used in the simulation framework. An analogous modelling approach has been chosen to represent emissions. This paper compares the two concepts regarding their CO₂ and NOx emissions. This comparison is performed for relevant bus missions (urban, suburban, with and without zero-emission zone) and with different energy management strategies. In addition to the emissions, also the downsizing potential of the combustion engine has been analysed to minimize the powertrain TCO (pTCO) for plug-in hybrid electric buses. The results of the performed analyses show that the hybrid vehicle concept using the CNG engine shows advantages both with respect to emissions as well as to pTCO. The pTCO is 10% lower, CO₂ emissions are 13% lower, and the NOx emissions are more than 50% lower than with the diesel combustion engine. These results are consistent across all usage profiles under investigation.

Keywords: bus transport, emissions, hybrid propulsion, pTCO, CNG

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Authors: Ayodeji Oluleye

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This study used Total Ozone Mapping Spectrometer (TOMS) Aerosol Index (AI) and reanalysis dataset of thirty years (1983-2012) to investigate the influence of the atmospheric circulation on dust transport during the Harmattan period over WestAfrica using TOMS data. The Harmattan dust mobilization and atmospheric circulation pattern were evaluated using a kernel density estimate which shows the areas where most points are concentrated between the variables. The evolution of the Inter-Tropical Discontinuity (ITD), Sea surface Temperature (SST) over the Gulf of Guinea, and the North Atlantic Oscillation (NAO) index during the Harmattan period (November-March) was also analyzed and graphs of the average ITD positions, SST and the NAO were observed on daily basis. The Pearson moment correlation analysis was also employed to assess the effect of atmospheric circulation on Harmattan dust transport. The results show that the departure (increased) of TOMS AI values from the long-term mean (1.64) occurred from around 21st of December, which signifies the rich dust days during winter period. Strong TOMS AI signal were observed from January to March with the maximum occurring in the latter months (February and March). The inter-annual variability of TOMSAI revealed that the rich dust years were found between 1984-1985, 1987-1988, 1997-1998, 1999-2000, and 2002-2004. Significantly, poor dust year was found between 2005 and 2006 in all the periods. The study has found strong north-easterly (NE) trade winds were over most of the Sahelianregion of West Africa during the winter months with the maximum wind speed reaching 8.61m/s inJanuary.The strength of NE winds determines the extent of dust transport to the coast of Gulf of Guinea during winter. This study has confirmed that the presence of the Harmattan is strongly dependent on theSST over Atlantic Ocean and ITD position. The locus of the average SST and ITD positions over West Africa could be described by polynomial functions. The study concludes that the evolution of near surface wind field at 925 hpa, and the variations of SST and ITD positions are the major large scale atmospheric circulation systems driving the emission, distribution, and transport of Harmattan dust aerosols over West Africa. However, the influence of NAO was shown to have fewer significance effects on the Harmattan dust transport over the region.

Keywords: atmospheric circulation, dust aerosols, Harmattan, West Africa

Procedia PDF Downloads 310

Authors: Wenjun Zhang, Yunqing Du, Steven W. Cranford, Ming L. Wang

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The beginning of 21st century has witnessed new advancements in the design and use of new materials for biosensing applications, from nano to macro, protein to tissue. Traditional analytical methods lack a complete toolset to describe the complexities introduced by living systems, pathological relations, discrete hierarchical materials, cross-phase interactions, and structure-property dependencies. Materiomics – via systematic molecular dynamics (MD) simulation – can provide structure-process-property relations by using a materials science approach linking mechanisms across scales and enables oriented biosensor design. With this approach, DNA biosensors can be utilized to detect disease biomarkers present in individuals’ breath such as acetone for diabetes. Our wireless sensor array based on single-stranded DNA (ssDNA)-decorated single-walled carbon nanotubes (SWNT) has successfully detected trace amount of various chemicals in vapor differentiated by pattern recognition. Here, we present how MD simulation can revolutionize the way of design and screening of DNA aptamers for targeting biomarkers related to oral diseases and oral health monitoring. It demonstrates great potential to be utilized to build a library of DNDA sequences for reliable detection of several biomarkers of one specific disease, and as well provides a new methodology of creating, designing, and applying of biosensors.

Keywords: biosensor, DNA, biomarker, molecular dynamics simulation

Procedia PDF Downloads 463

Authors: Andrei Bejan, Luminita Marin, Dalila Belei

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Phenothiazine with electron-rich nitrogen and sulfur heteroatoms has a high electron-donating ability which promotes a good conjugation and therefore low band-gap with consequences upon charge carrier mobility improving and shifting of light emission in visible domain. Moreover, its non-planar butterfly conformation inhibits molecular aggregation and thus preserves quite well the fluorescence quantum yield in solid state compared to solution. Therefore phenothiazine and its derivatives are promising hole transport materials for use in organic electronic and optoelectronic devices as light emitting diodes, photovoltaic cells, integrated circuit sensors or driving circuits for large area display devices. The objective of this paper was to obtain a series of new phenothiazine derivatives by introduction of different electron withdrawing substituents as formyl, carboxyl and cyanoacryl units in order to create a push pull system which has potential to improve the electronic and optical properties. Bromine atom was used as electrono-donor moiety to extend furthermore the existing conjugation. The understudy compounds were structural characterized by FTIR and 1H-NMR spectroscopy and single crystal X-ray diffraction. Besides, the single crystal X-ray diffraction brought information regarding the supramolecular architecture of the compounds. Photophysical properties were monitored by UV-vis and photoluminescence spectroscopy, while the electrochemical behavior was established by cyclic voltammetry. The absorption maxima of the studied compounds vary in a large range (322-455 nm), reflecting the different electronic delocalization degree, depending by the substituent nature. In a similar manner, the emission spectra reveal different color of emitted light, a red shift being evident for the groups with higher electron withdrawing ability. The emitted light is pure and saturated for the compounds containing strong withdrawing formyl or cyanoacryl units and reach the highest quantum yield of 71% for the compound containing bromine and cyanoacrilic units. Electrochemical study show reversible oxidative and reduction processes for all the compounds and a close correlation of the HOMO-LUMO band gap with substituent nature. All these findings suggest the obtained compounds as promising materials for optoelectronic devices.

Keywords: electrochemical properties, phenothiazine derivatives, photoluminescence, quantum yield

Procedia PDF Downloads 329

Authors: Itamir de Morais Barroca Filho, Cephas A. S. Barreto, Ramon Malaquias, Cezar Miranda Paula de Souza, Arthur Costa Gorgônio, João C. Xavier-Júnior, Mateus Firmino, Fellipe Matheus Costa Barbosa

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Information and Communication Technologies (ICT) in healthcare are crucial for efficiently delivering medical healthcare services to patients. These ICTs are also known as e-health and comprise technologies such as electronic record systems, telemedicine systems, and personalized devices for diagnosis. The focus of e-health is to improve the quality of health information, strengthen national health systems, and ensure accessible, high-quality health care for all. All the data gathered by these technologies make it possible to help clinical staff with automated decisions using machine learning. In this context, we collected patient data, such as heart rate, oxygen saturation (SpO2), blood pressure, respiration, and others. With this data, we were able to develop machine learning models for patients’ risk of death and estimate the length of stay in ICU beds. Thus, this paper presents the methodology for applying machine learning techniques to develop these models. As a result, although we implemented these models on an IoT healthcare platform, helping clinical staff in healthcare in an ICU, it is essential to create a robust clinical validation process and monitoring of the proposed models.

Keywords: ICT, e-health, machine learning, ICU, healthcare

Procedia PDF Downloads 110

Authors: Arto Grasten

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Given the rising trend in obesity in children and youth, age-related decline in moderate- to- vigorous-intensity physical activity (MVPA) in several Western, African, and Asian countries in addition to limited evidence of behavioral, affective, cognitive outcomes in physical education, it is important to clarify the motivational processes in physical education classes behind total MVPA engagement. The present study examined the full sequence of the Hierarchical Model of Motivation in physical education including motivational climate, basic psychological needs, intrinsic motivation, contextual behavior, affect, cognition, total MVPA, and associated links to body mass index (BMI) and gender differences. A cross-sectional data comprised self-reports and objective assessments of 770 middle school students (Mage = 13.99 ± .81 years, 52% of girls) in North-East Finland. In order to test the associations between motivational climate, psychological needs, intrinsic motivation, cognition, behavior, affect, and total MVPA, a path model was implemented. Indirect effects between motivational climate and cognition, behavior, affect and total MVPA were tested by setting basic needs and intrinsic motivation as mediators into the model. The findings showed that direct and indirect paths for girls and boys associated with different contextual outcomes and girls’ indirect paths were not related with total MVPA. Precisely, task-involving climate-mediated by physical competence and intrinsic motivation related to enjoyment, importance, and graded assessments within girls, whereas task-involving climate associated with enjoyment and importance via competence and autonomy, and total MVPA via autonomy, intrinsic motivation, and importance within boys. Physical education assessments appeared to be essential in motivating students to participate in greater total MVPA. BMI was negatively linked with competence and relatedness only among girls. Although, the current and previous empirical findings supported task-involving teaching methods in physical education, in some cases, ego-involving climate should not be totally avoided. This may indicate that girls and boys perceive physical education classes in a different way. Therefore, both task- and ego-involving teaching practices can be useful ways of driving behavior in physical education classes.

Keywords: achievement goal theory, assessment, enjoyment, hierarchical model of motivation, physical activity, self-determination theory

Procedia PDF Downloads 281

Authors: Jaruwan Chutrtong

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Yoghurt is a fermented milk product. The process of making yogurt involves fermenting milk with live and active bacterial cultures by adding bacteria directly to the dairy product. It is usually made with a culture of Lactobacillus sp. (L. acidophilus or L. bulgaricus) and Streptococcus thermophilus. Many people like to eat it plain or flavored and it's also use as ingredient in many dishes. Yogurt is rich in nutrients including the microorganism which have important role in balancing the digestion and absorption of the boy.Consumers will benefit from lactic acid bacteria more or less depending on the amount of bacteria that lives in yogurt while eating. When purchasing yogurt, consumers should always check the label for live cultures. Yoghurt must keep in refrigerator at 4°C for up to ten days. After this amount of time, the cultures often become weak. This research studied freezing dry yogurt storage by monitoring on the survival of microorganisms when stored at different temperatures. At 300°C, representative room temperature of country in equator zone, number of lactic acid bacteria reduced 4 log cycles in 10 week. At 400°C, representative temperature in summer of country in equator zone, number of lactic acid bacteria also dropped 4 log cycle in 10 week, similar as storage at 300°C. But drying yogurt storage at 400°C couldn’t reformed to be good character yogurt as good as storage at 400°C only 4 week storage too. After 1 month, it couldn’t bring back the yogurt form. So if it is inevitable to keep yogurt powder at a temperature of 40°C, yoghurt is maintained only up to 4 weeks.

Keywords: dynamic, dry yoghurt, storage, temperature

Procedia PDF Downloads 325

Authors: Teklay Gebrecherkos, Mahmud Abdulkader, Tobias Rinke De Wit, Britta C. Urban, Feyissa Chala, Yazezew Kebede, Dawit Welday

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Background: C-reactive protein (CRP) levels are a reliable surrogate for interleukin-6 bioactivity that plays a pivotal role in the pathogenesis of cytokine storm associated with severe COVID-19. There is a lack of data on the role of CRP as a determinant of COVID-19 severity status in the African context. Methods: We determined the longitudinal kinetics of CRP levels on 78 RT-PCR-confirmed COVID-19 patients (49 non-severe and 29 severe cases) and 50 PCR-negative controls. Results: COVID-19 patients had overall significantly elevated CRP at baseline when compared to PCR-negative controls [median 11.1 (IQR: 2.0-127.8) mg/L vs. 0.9 (IQR: 0.5-1.9) mg/L; p=0.0004)]. Moreover, severe COVID-19 patients had significantly higher median CRP levels than non-severe cases [166.1 (IQR: 48.6-332.5) mg/L vs. 2.4 (IQR: 1.2-7.6) mg/L; p<0.00001)]. In addition, persistently elevated levels of CRP were exhibited among those with comorbidities and higher age groups. Area under receiver operating characteristic curve (AUC) analysis of CRP levels distinguished PCR-confirmed COVID-19 patients from the ones with PCR-negative non-COVID-19 individuals, with an AUC value of 0.77 (95% CI: 0.68-0.84; p=0.001). Moreover, it clearly distinguished severe from non-severe COVID-19 patients, with an AUC value of 0.83 (95% CI: 0.73-0.91). After adjusting for age and the presence of comorbidities, CRP levels above 30 mg/L were significantly associated with an increased risk of developing severe COVID-19 (adjusted relative risk 3.99 (95%CI: 1.35-11.82; p=0.013). Conclusions: Determining CRP levels in COVID-19 patients in African settings may provide a simple, prompt, and inexpensive assessment of the severity status at baseline and monitoring of treatment outcomes.

Keywords: CRP, COVID-19, SARS-CoV-2, biomarker

Procedia PDF Downloads 82

Authors: Kavita Bodke

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Structural health monitoring (SHM) is experiencing growth, necessitating the development of distinct methodologies to address its expanding scope effectively. In this study, we developed automatic structure damage identification, which incorporates three unique types of a building’s structural integrity. The first pertains to the presence of fractures within the structure, the second relates to the issue of dampness within the structure, and the third involves corrosion inside the structure. This study employs image classification techniques to discern between intact and impaired structures within structural data. The aim of this research is to find automatic damage detection with the probability of each damage class being present in one image. Based on this probability, we know which class has a higher probability or is more affected than the other classes. Utilizing photographs captured by a mobile camera serves as the input for an image classification system. Image classification was employed in our study to perform multi-class and multi-label classification. The objective was to categorize structural data based on the presence of cracks, moisture, and corrosion. In the context of multi-class image classification, our study employed three distinct methodologies: Random Forest, Multilayer Perceptron, and CNN. For the task of multi-label image classification, the models employed were Rasnet, Xceptionet, and Inception.

Keywords: SHM, CNN, deep learning, multi-class classification, multi-label classification

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Authors: Arun Kumar Singh, Rupesh M. Das, Shailendra Saini

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The effect of solar cycle and seasons on the total electron content has been investigated over high latitude region during 24th solar cycle (2010-2014). The total electron content data has been observed with the help of Global Ionospheric Scintillation and TEC monitoring (GISTM) system installed at Indian permanent scientific 'Maitri station' [70˚46’00”S 11˚43’56” E]. The dependence of TEC over a solar cycle has been examined by the performing linear regression analysis between the vertical total electron content (VTEC) and daily total sunspot numbers (SSN). It has been found that the season and level of geomagnetic activity has a considerable effect on the VTEC. It is observed that the VTEC and SSN follow better agreement during summer seasons as compared to winter and equinox seasons and extraordinary agreement during minimum phase (during the year 2010) of the solar cycle. There is a significant correlation between VTEC and SSN during quiet days of the years as compared to overall days of the years (2010-2014). Further, saturation effect has been observed during maximum phase (during the year 2014) of the 24th solar cycle. It is also found that Ap index and SSN has a linear correlation (R=0.37) and the most of the geomagnetic activity occurs during the declining phase of the solar cycle.

Keywords: high latitude ionosphere, sunspot number, correlation, vertical total electron content

Procedia PDF Downloads 193