Search results for: reliability and validity

Authors: Muhammad Shafi'u Adamu

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This study examined the effects of two Group Cognitive Behavioural Therapies (Cognitive Restructuring and Rational Emotive Behavioural Therapy) on Psychological Distress of awaiting-trial Inmates in Correctional Centres in North-West, Nigeria. The study had four specific objectives, four research questions, and four null hypotheses. The study used a quasi-experimental design that involved pre-test and post-test. The population comprised of all 7,962 awaiting-trial inmates in correctional centres in North-west, Nigeria. 131 awaiting trial inmates from three intact Correctional Centres were randomly selected using the census technique. The respondents were sampled and randomly put into 3 groups (CR, REBT and Control). Kessler Psychological Distress Scale (K10) was adapted for data collection in the study. The instrument was validated by experts and subjected to pilot study using Cronbach's Alpha with reliability co-efficient of 0.772. Each group received treatment for 8 consecutive weeks (60 minutes/week). Data collected from the field were subjected to descriptive statistics of mean, standard deviation and mean difference to answer the research questions. Inferential statistics of ANOVA and independent sample t-test were used to test the null hypotheses at P≤ 0.05 level of significance. Results in the study revealed that there was no significant difference among the pre-treatment mean scores of experimental and control groups. Statistical evidence also showed a significant difference among the mean sores of the three groups, and thus, results of the Post Hoc multiple-comparison test indicating the posttreatment reduction of psychological distress on the awaiting-trial inmates. Documented output also showed a significant difference between the post-treatment psychologically distressed mean scores of male and female awaiting-trial inmates, but there was no difference on those exposed to REBT. The research recommends that a standardized structured CBT counselling technique treatment should be designed for correctional centres across Nigeria, and CBT counselling techniques could be used in the treatment of PD in both correctional and clinical settings.

Keywords: awaiting-trial inmates, cognitive restructuring, correctional centres, group cognitive behavioural therapies, rational emotive behavioural therapy

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Authors: Valentina Marutyan

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Healthcare data mining is a rapidly developing field at the intersection of technology and medicine that has the potential to change our understanding and approach to providing healthcare. Healthcare and data mining is the process of examining huge amounts of data to extract useful information that can be applied in order to improve patient care, treatment effectiveness, and overall healthcare delivery. This field looks for patterns, trends, and correlations in a variety of healthcare datasets, such as electronic health records (EHRs), medical imaging, patient demographics, and treatment histories. To accomplish this, it uses advanced analytical approaches. Predictive analysis using historical patient data is a major area of interest in healthcare data mining. This enables doctors to get involved early to prevent problems or improve results for patients. It also assists in early disease detection and customized treatment planning for every person. Doctors can customize a patient's care by looking at their medical history, genetic profile, current and previous therapies. In this way, treatments can be more effective and have fewer negative consequences. Moreover, helping patients, it improves the efficiency of hospitals. It helps them determine the number of beds or doctors they require in regard to the number of patients they expect. In this project are used models like logistic regression, random forests, and neural networks for predicting diseases and analyzing medical images. Patients were helped by algorithms such as k-means, and connections between treatments and patient responses were identified by association rule mining. Time series techniques helped in resource management by predicting patient admissions. These methods improved healthcare decision-making and personalized treatment. Also, healthcare data mining must deal with difficulties such as bad data quality, privacy challenges, managing large and complicated datasets, ensuring the reliability of models, managing biases, limited data sharing, and regulatory compliance. Finally, secret code of data mining in healthcare helps medical professionals and hospitals make better decisions, treat patients more efficiently, and work more efficiently. It ultimately comes down to using data to improve treatment, make better choices, and simplify hospital operations for all patients.

Keywords: data mining, healthcare, big data, large amounts of data

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Authors: Saleh Alumaran, Giampaolo Bella, Feng Chen

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The study of organisations’ information security cultures has attracted scholars as well as healthcare services industry to research the topic and find appropriate tools and approaches to develop a positive culture. The vast majority of studies in Saudi national health services are on the use of technology to protect and secure health services information. On the other hand, there is a lack of research on the role and impact of an organisation’s cultural dimensions on information security. This research investigated and analysed the role and impact of cultural dimensions on information security in Saudi Arabia health service. Hypotheses were tested and two surveys were carried out in order to collect data and information from three major hospitals in Saudi Arabia (SA). The first survey identified the main cultural-dimension problems in SA health services and developed an initial information security culture framework model. The second survey evaluated and tested the developed framework model to test its usefulness, reliability and applicability. The model is based on human behaviour theory, where the individual’s attitude is the key element of the individual’s intention to behave as well as of his or her actual behaviour. The research identified six cultural dimensions: Saudi national culture, Saudi health service leadership, employees’ trust, technology, multicultural interactions and employees’ job roles. The research also identified a set of cultural sub-dimensions. These include working values and norms, tribe values and norms, attitudes towards women, power sharing, vision, social interaction, respect and understanding, hospital intra-net, hospital employees’ language(s) used, multi-national culture, communication system, employees’ job satisfaction and job security. The research identified that (a) the human behaviour towards medical information in SA is one of the main threats to information security and one of the main challenges to SA health authority, (b) The current situation of SA hospitals’ IS cultures is falling short in protecting medical information due to the current value and norms towards information security, (c) Saudi national culture and employees’ job role are the main dimensions playing major roles in the employees’ attitude, and technology is the least important dimension playing a role in the employees’ attitudes.

Keywords: cultural dimension, electronic health record, information security, privacy

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Authors: Melanie Ostermann, Eivind Birkeland, Ying Xue, Alexander Sauter, Mihaela R. Cimpan

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Background: New reliable and robust techniques to assess biological effects of nanomaterials (NMs) in vitro are needed to speed up safety analysis and to identify key physicochemical parameters of NMs, which are responsible for their acute cytotoxicity. The central aim of this study was to validate and evaluate the applicability and reliability of an impedance-based flow cytometry (IFC) technique for the high-throughput screening of NMs. Methods: Eight inorganic NMs from the European Commission Joint Research Centre Repository were used: NM-302 and NM-300k (Ag: 200 nm rods and 16.7 nm spheres, respectively), NM-200 and NM- 203 (SiO₂: 18.3 nm and 24.7 nm amorphous, respectively), NM-100 and NM-101 (TiO₂: 100 nm and 6 nm anatase, respectively), and NM-110 and NM-111 (ZnO: 147 nm and 141 nm, respectively). The aim was to assess the biological effects of these materials on human monoblastoid (U937) cells. Dispersions of NMs were prepared as described in the NANOGENOTOX dispersion protocol and cells were exposed to NMs at relevant concentrations (2, 10, 20, 50, and 100 µg/mL) for 24 hrs. The change in electrical impedance was measured at 0.5, 2, 6, and 12 MHz using the IFC AmphaZ30 (Amphasys AG, Switzerland). A traditional toxicity assay, Trypan Blue Dye Exclusion assay, and dark-field microscopy were used to validate the IFC method. Results: Spherical Ag particles (NM-300K) showed the highest toxic effect on U937 cells followed by ZnO (NM-111 ≥ NM-110) particles. Silica particles were moderate to non-toxic at all used concentrations under these conditions. A higher toxic effect was seen with smaller sized TiO2 particles (NM-101) compared to their larger analogues (NM-100). No interferences between the IFC and the used NMs were seen. Uptake and internalization of NMs were observed after 24 hours exposure, confirming actual NM-cell interactions. Conclusion: Results collected with the IFC demonstrate the applicability of this method for rapid nanotoxicity assessment, which proved to be less prone to nano-related interference issues compared to some traditional toxicity assays. Furthermore, this label-free and novel technique shows good potential for up-scaling in directions of an automated high-throughput screening and for future NM toxicity assessment. This work was supported by the EC FP7 NANoREG (Grant Agreement NMP4-LA-2013-310584), the Research Council of Norway, project NorNANoREG (239199/O70), the EuroNanoMed II 'GEMN' project (246672), and the UH-Nett Vest project.

Keywords: cytotoxicity, high-throughput, impedance, nanomaterials

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Authors: Antonio Casero Martínez, María de Lluch Rayo Llinas

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This work is part of an investigation into the relationship between romantic love and self-esteem in college students, performed by the students of matter "methods and techniques of social research", of the Master Gender at the University of Balearic Islands, during 2014-2015. In particular, we have investigated the relationships that may exist between self-esteem, gender and field of study. They are known as gender differences in self-esteem, and the relationship between gender and branch of study observed annually by the distribution of enrolment in universities. Therefore, in this part of the study, we focused the spotlight on the differences in self-esteem between the sexes through the various branches of study. The study sample consists of 726 individuals (304 men and 422 women) from 30 undergraduate degrees that the University of the Balearic Islands offers on its campus in 2014-2015, academic year. The average age of men was 21.9 years and 21.7 years for women. The sampling procedure used was random sampling stratified by degree, simple affixation, giving a sampling error of 3.6% for the whole sample, with a confidence level of 95% under the most unfavorable situation (p = q). The Spanish translation of the Rosenberg Self-Esteen Scale (RSE), by Atienza, Moreno and Balaguer was applied. The psychometric properties of translation reach a test-retest reliability of 0.80 and an internal consistency between 0.76 and 0.87. In this paper we have obtained an internal consistency of 0.82. The results confirm the expected differences in self-esteem by gender, although not in all branches of study. Mean levels of self-esteem in women are lower in all branches of study, reaching statistical significance in the field of Science, Social Sciences and Law, and Engineering and Architecture. However, analysed the variability of self-esteem by the branch of study within each gender, the results show independence in the case of men, whereas in the case of women find statistically significant differences, arising from lower self-esteem of Arts and Humanities students vs. the Social and legal Sciences students. These findings confirm the results of numerous investigations in which the levels of female self-esteem appears always below the male, suggesting that perhaps we should consider separately the two populations rather than continually emphasize the difference. The branch of study, for its part has not appeared as an explanatory factor of relevance, beyond detected the largest absolute difference between gender in the technical branch, one in which women are historically a minority, ergo, are no disciplinary or academic characteristics which would explain the differences, but the differentiated social context that occurs within it.

Keywords: study branch, gender, self-esteem, applied psychology

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Authors: Jaleh Mohammad Aliha, Rezvan Razazi, Nasim Naderi

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Introduction: Despite the progress in new effective drugs in the treatment of heart failure, the disease still accompanied with frequent hospitalization, impaired quality of life, early mortality and significant economic burden. Patients with chronic disease and consequently patients with heart failure need the knowledge and optimal health literacy to improve the quality of life and minimize the rate of rehopitalizatio. So, considering to importance of knowledge and health literacy in this patients as well as contradictory literature, this study conducted to investigate the relationship between health literacy and Knowledge of heart failure with rehospitalization in patients with heart failure admitted to heart failure clinic in Rajai Heart center in 1394. Methods: The cross-sectional method with convenience sampling method was used in this study. After obtaining the necessary permissions from the ethics committee and the Shahid Rajai Heart center, 238 patients who were older than 18 years and had ejection fraction 35% or less with the ability to read and write and lack of psychiatric, neurological and cognitive disorders and signed the informed consent were recruited. Data collection were perfomed through demographic data questionnaire, short standard health literacy questionnaire 'Short-TOFHLA-16' and Vanderwall (2005) knowledge of heart failure questionnaire. Reliability was assessed by internal consistency method and Cronbach's alpha for both questionnaires was more than 0.7. Then data were analysed by SPSS-20 with descriptive statistic and analytical statistic such as T-test, Chi-square and ANOVA. Results: The majority of patients were male (66%), married (80%) and had age between 50 to 70 years old (42%). The majority of studied men and women have good health literacy and About half of them have adequate knowledge about heart failure. Fisher's exact test showed that there was a significant statistical correlation between health literacy and knowlegh about heart failure. In other words, higher health literacy associated with more knowledge about their condition. Also findings showed that there was no significant statistical correlation between health literacy and knowledge about heart failure and frequency of CCU and emergency admissions. Conclusion: The study results showed that the higher health literacy, associated with the greater knowledge about heart failure and patients' perception about caring recommendations and disease outcomes. Therefore, the knowledge about heart failure and factors which related to severity of the disease, is the important issue to problem identification and treatment and reduction of rehospitalization.

Keywords: health literacy, heart failure, knowlegde, rehospitalization

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Authors: Hai L. Tran

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In the digital age, evidence-based reporting is touted as a best practice for seeking the truth and keeping the public well-informed. Journalists are expected to rely on evidence to demonstrate the validity of a factual statement and lend credence to an individual account. Evidence can be obtained from various sources, and due to a rich supply of evidence types available, the definition of this important concept varies semantically. To promote clarity and understanding, it is necessary to break down the various types of evidence and categorize them in a more coherent, systematic way. There is a wide array of devices that digital journalists deploy as proof to back up or refute a truth claim. Evidence can take various formats, including verbal and visual materials. Verbal evidence encompasses quotes, soundbites, talking heads, testimonies, voice recordings, anecdotes, and statistics communicated through written or spoken language. There are instances where evidence is simply non-verbal, such as when natural sounds are provided without any verbalized words. On the other hand, other language-free items exhibited in photos, video footage, data visualizations, infographics, and illustrations can serve as visual evidence. Moreover, there are different sources from which evidence can be cited. Supporting materials, such as public or leaked records and documents, data, research studies, surveys, polls, or reports compiled by governments, organizations, and other entities, are frequently included as informational evidence. Proof can also come from human sources via interviews, recorded conversations, public and private gatherings, or press conferences. Expert opinions, eye-witness insights, insider observations, and official statements are some of the common examples of testimonial evidence. Digital journalism studies tend to make broad references when comparing qualitative versus quantitative forms of evidence. Meanwhile, limited efforts are being undertaken to distinguish between sister terms, such as “data,” “statistical,” and “base-rate” on one side of the spectrum and “narrative,” “anecdotal,” and “exemplar” on the other. The present study seeks to develop the evidence taxonomy, which classifies evidence through the quantitative-qualitative juxtaposition and in a hierarchical order from broad to specific. According to this scheme, data, statistics, and base rate belong to the quantitative evidence group, whereas narrative, anecdote, and exemplar fall into the qualitative evidence group. Subsequently, the taxonomical classification arranges data versus narrative at the top of the hierarchy of types of evidence, followed by statistics versus anecdote and base rate versus exemplar. This research reiterates the central role of evidence in how journalists describe and explain social phenomena and issues. By defining the various types of evidence and delineating their logical connections it helps remove a significant degree of conceptual inconsistency, ambiguity, and confusion in digital journalism studies.

Keywords: evidence, evidence forms, evidence types, taxonomy

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Authors: Shreya Saxena

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Background: Choledocholithiasis is a common complication of gallstone disease. Risk scoring systems exist to guide the need for further imaging or endoscopy in managing choledocholithiasis. We completed an audit to review the American Society for Gastrointestinal Endoscopy (ASGE) scoring system for prediction and management of choledocholithiasis against the current practice at a tertiary hospital to assess its utility in resource optimisation. We have now conducted a cost focused sub-analysis on patients categorized high-risk for choledocholithiasis according to the guidelines to determine any associated cost benefits. Method: Data collection from our prior audit was used to retrospectively identify thirteen patients considered high-risk for choledocholithiasis. Their ongoing management was mapped against the guidelines. Individual costs for the key investigations were obtained from our hospital financial data. Total cost for the different management pathways identified in clinical practice were calculated and compared against predicted costs associated with recommendations in the guidelines. We excluded the cost of laparoscopic cholecystectomy and considered a set figure for per day hospital admission related expenses. Results: Based on our previous audit data, we identified a77% positive predictive value for the ASGE risk stratification tool to determine patients at high-risk of choledocholithiasis. 47% (6/13) had an magnetic resonance cholangiopancreatography (MRCP) prior to endoscopic retrograde cholangiopancreatography (ERCP), whilst 53% (7/13) went straight for ERCP. The average length of stay in the hospital was 7 days, with an additional day and cost of £328.00 (£117 for ERCP) for patients awaiting an MRCP prior to ERCP. Per day hospital admission was valued at £838.69. When calculating total cost, we assumed all patients had admission bloods and ultrasound done as the gold standard. In doing an MRCP prior to ERCP, there was a 130% increase in cost incurred (£580.04 vs £252.04) per patient. When also considering hospital admission and the average length of stay, it was an additional £1166.69 per patient. We then calculated the exact costs incurred by the department, over a three-month period, for all patients, for key investigations or procedures done in the management of choledocholithiasis. This was compared to an estimate cost derived from the recommended pathways in the ASGE guidelines. Overall, 81% (£2048.45) saving was associated with following the guidelines compared to clinical practice. Conclusion: MRCP is the most expensive test associated with the diagnosis and management of choledocholithiasis. The ASGE guidelines recommend endoscopy without an MRCP in patients stratified as high-risk for choledocholithiasis. Our audit that focused on assessing the utility of the ASGE risk scoring system showed it to be relatively reliable for identifying high-risk patients. Our cost analysis has shown significant cost savings per patient and when considering the average length of stay associated with direct endoscopy rather than an additional MRCP. Part of this is also because of an increased average length of stay associated with waiting for an MRCP. The above data supports the ASGE guidelines for the management of high-risk for choledocholithiasis patients from a cost perspective. The only caveat is our small data set that may impact the validity of our average length of hospital stay figures and hence total cost calculations.

Keywords: cost-analysis, choledocholithiasis, risk stratification tool, general surgery

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Authors: Breno Barrreto Silva, Agnieszka Otwinowska, Katarzyna Kutylowska

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Research comparing lexical learning following the writing of sentences and longer texts with keywords is limited and contradictory. One possibility is that the recursivity of writing may enhance processing and increase lexical learning; another possibility is that the higher cognitive load of complex-text writing (e.g., essays), at least when timed, may hinder the learning of words. In our study, we selected 2 sets of 10 academic keywords matched for part of speech, length (number of characters), frequency (SUBTLEXus), and concreteness, and we asked 90 L1-Polish advanced-level English majors to use the keywords when writing sentences, timed (60 minutes) or untimed essays. First, all participants wrote a timed Control essay (60 minutes) without keywords. Then different groups produced Timed essays (60 minutes; n=33), Untimed essays (n=24), or Sentences (n=33) using the two sets of glossed keywords (counterbalanced). The comparability of the participants in the three groups was ensured by matching them for proficiency in English (LexTALE), and for few measures derived from the control essay: VocD (assessing productive lexical diversity), normed errors (assessing productive accuracy), words per minute (assessing productive written fluency), and holistic scores (assessing overall quality of production). We measured lexical learning (depth and breadth) via an adapted Vocabulary Knowledge Scale (VKS) and a free association test. Cognitive load was measured in the three essays (Control, Timed, Untimed) using normed number of errors and holistic scores (TOEFL criteria). The number of errors and essay scores were obtained from two raters (interrater reliability Pearson’s r=.78-91). Generalized linear mixed models showed no difference in the breadth and depth of keyword knowledge after writing Sentences, Timed essays, and Untimed essays. The task-based measurements found that Control and Timed essays had similar holistic scores, but that Untimed essay had better quality than Timed essay. Also, Untimed essay was the most accurate, and Timed essay the most error prone. Concluding, using keywords in Timed, but not Untimed, essays increased cognitive load, leading to more errors and lower quality. Still, writing sentences and essays yielded similar lexical learning, and differences in the cognitive load between Timed and Untimed essays did not affect lexical acquisition.

Keywords: learning academic words, writing essays, cognitive load, english as an L2

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Authors: Byeongcheol Kang, Junyi Kim, Hyungsik Jung, Hyungjun Yang, Jaewoo An, Jonggeun Choe

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It is important to figure out reservoir properties for better production management. Due to the limited information, there are geological uncertainties on very heterogeneous or channel reservoir. One of the solutions is to generate multiple equi-probable realizations using geostatistical methods. However, some models have wrong properties, which need to be excluded for simulation efficiency and reliability. We propose a novel method of model selection scheme, based on distance-based clustering for reliable application of production optimization algorithm. Distance is defined as a degree of dissimilarity between the data. We calculate Hausdorff distance to classify the models based on their similarity. Hausdorff distance is useful for shape matching of the reservoir models. We use multi-dimensional scaling (MDS) to describe the models on two dimensional space and group them by K-means clustering. Rather than simulating all models, we choose one representative model from each cluster and find out the best model, which has the similar production rates with the true values. From the process, we can select good reservoir models near the best model with high confidence. We make 100 channel reservoir models using single normal equation simulation (SNESIM). Since oil and gas prefer to flow through the sand facies, it is critical to characterize pattern and connectivity of the channels in the reservoir. After calculating Hausdorff distances and projecting the models by MDS, we can see that the models assemble depending on their channel patterns. These channel distributions affect operation controls of each production well so that the model selection scheme improves management optimization process. We use one of useful global search algorithms, particle swarm optimization (PSO), for our production optimization. PSO is good to find global optimum of objective function, but it takes too much time due to its usage of many particles and iterations. In addition, if we use multiple reservoir models, the simulation time for PSO will be soared. By using the proposed method, we can select good and reliable models that already matches production data. Considering geological uncertainty of the reservoir, we can get well-optimized production controls for maximum net present value. The proposed method shows one of novel solutions to select good cases among the various probabilities. The model selection schemes can be applied to not only production optimization but also history matching or other ensemble-based methods for efficient simulations.

Keywords: distance-based clustering, geological uncertainty, particle swarm optimization (PSO), production optimization

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Authors: You-Kai Jhang, Yang-Cheng Lu

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Major contributions of this study are threefold: designing a new model of planar-membrane humidifier for Proton Exchange Membrane Fuel Cell (PEMFC), an index to measure the Effectiveness (εT) of that humidifier, and an air compressor system to replicate related planar-membrane humidifier experiments. PEMFC as a kind of renewable energy has become more and more important in recent years due to its reliability and durability. To maintain the efficiency of the fuel cell, the membrane of PEMFC need to be controlled in a good hydration condition. How to maintain proper membrane humidity is one of the key issues to optimize PEMFC. We developed new humidifier to recycle water vapor from cathode air outlet so as to keep the moisture content of cathode air inlet in a PEMFC. By measuring parameters such as dry side air outlet dew point temperature, dry side air inlet temperature and humidity, wet side air inlet temperature and humidity, and differential pressure between dry side and wet side, we calculated indices obtained by dew point approach temperature (DPAT), water flux (J), water recovery ratio (WRR), effectiveness (εT), and differential pressure (ΔP). We discussed six topics including sealing effect, flow rate effect, flow direction effect, channel effect, temperature effect, and humidity effect by using these indices. Gas cylinders are used as sources of air supply in many studies of humidifiers. Gas cylinder depletes quickly during experiment at 1kW air flow rate, and it causes replication difficult. In order to ensure high stable air quality and better replication of experimental data, this study designs an air supply system to overcome this difficulty. The experimental result shows that the best rate of pressure loss of humidifier is 0.133×10³ Pa(g)/min at the torque of 25 (N.m). The best humidifier performance ranges from 30-40 (LPM) of air flow rates. The counter flow configured humidifies moisturizes the dry side inlet air more effectively than the parallel flow humidifier. From the performance measurements of the channel plates various rib widths studied in this study, it is found that the narrower the rib width is, the more the performance of humidifier improves. Raising channel width in same hydraulic diameter (Dh ) will obtain higher εT and lower ΔP. Moreover, increasing the dry side air inlet temperature or humidity will lead to lower εT. In addition, when the dry side air inlet temperature exceeds 50°C, the effect becomes even more obvious.

Keywords: PEM fuel cell, water management, membrane humidifier, heat and mass transfer, humidifier performance

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Authors: V. Ziegler, F. Schneider, M. Pesch

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With the EDM264, GRIMM offers a solution for mobile short- and long-term measurements in outdoor areas and at production sites. For research as well as permanent areal observations on a near reference quality base. The model EDM264 features a powerful and robust measuring cell based on optical particle counting (OPC) principle with all the advantages that users of GRIMM's portable aerosol spectrometers are used to. The system is embedded in a compact weather-protection housing with all-weather sampling, heated inlet system, data logger, and meteorological sensor. With TSP, PM10, PM4, PM2.5, PM1, and PMcoarse, the EDM264 provides all fine dust fractions real-time, valid for outdoor applications and calculated with the proven GRIMM enviro-algorithm, as well as six additional dust mass fractions pm10, pm2.5, pm1, inhalable, thoracic and respirable for IAQ and workplace measurements. This highly versatile instrument performs real-time monitoring of particle number, particle size and provides information on particle surface distribution as well as dust mass distribution. GRIMM's EDM264 has 31 equidistant size channels, which are PSL traceable. A high-end data logger enables data acquisition and wireless communication via LTE, WLAN, or wired via Ethernet. Backup copies of the measurement data are stored in the device directly. The rinsing air function, which protects the laser and detector in the optical cell, further increases the reliability and long term stability of the EDM264 under different environmental and climatic conditions. The entire sample volume flow of 1.2 L/min is analyzed by 100% in the optical cell, which assures excellent counting efficiency at low and high concentrations and complies with the ISO 21501-1standard for OPCs. With all these features, the EDM264 is a world-leading dust monitor for precise monitoring of particulate matter and particle number concentration. This highly reliable instrument is an indispensable tool for many users who need to measure aerosol levels and air quality outdoors, on construction sites, or at production facilities.

Keywords: aerosol research, aerial observation, fence line monitoring, wild fire detection

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Authors: Rachel M. Edelstein, John D. Van Horn, Karen M. Schmidt, Sydney N. Cushing

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As a consequence of sports-related concussions, female athletes have been documented as reporting more symptoms than their male counterparts, in addition to incurring longer periods of recovery. However, the role of sex and its potential influence on symptom reporting and recovery outcomes in concussion management has not been completely explored. The present aims to investigate the relationship between female concussion symptom severity and the presence of assessment bias. The Sport Concussion Assessment Tool 3 (SCAT3), collected by the NCAA and DoD CARE Consortium, was quantified at five different time points post-concussion. N= 1,258 NCAA athletes, n= 473 female (soccer, rugby, lacrosse, ice hockey) and n=785 male athletes (football, rugby, lacrosse, ice hockey). A polytomous Item Response Theory (IRT) Graded Response Model (GRM) was used to assess the relationship between sex and symptom reporting. Differential Item Functioning (DIF) and Differential Group Functioning (DGF) were used to examine potential group-level bias. Interactions for DIF were utilized to explore the impact of sex on symptom reporting among NCAA male and female athletes throughout and after their concussion recovery. DIF was significantly detected after B-H corrections displayed in limited items; however, one symptom, “Pressure in Head” (-0.29, p=0.04 vs -0.20, p =0.04), was statistically significant at both < 6 hours and 24-48 hours. Thus, implies that at < 6 hours, males were 29% less likely to indicate “Pressure in the Head” compared to female athletes and 20% less likely at 24-48 hours. Overall, the DGF suggested significant group differences, suggesting that male athletes might be at a higher risk for returning to play prematurely (logits = -0.38, p < 0.001). However, after analyzing the SCAT 3, a clinically relevant trend was discovered. Twelve out of the twenty-two symptoms suggest higher difficulty in female athletes within three or more of the five-time points. These symptoms include Balance Problems, Blurry Vision, Confusion, Dizziness, Don’t Feel Right, Feel in Fog, Feel Slow Down, Low Energy, Neck Pain, Sensitivity to Light, Sensitivity to Noise, Trouble Falling Asleep. Despite a lack of statistical significance, this tendency is contrary to current literature stating that males may be unclear on symptoms, but females may be more honest in reporting symptoms. Further research, which includes possible modifying socioecological factors, is needed to determine whether females may consistently experience more symptoms and require longer recovery times or if, parsimoniously, males tend to present their symptoms and readiness for play differently than females. Such research will help to improve the validity of current assumptions concerning male as compared to female head injuries and optimize individualized treatments for sports-related head injuries.

Keywords: female athlete, sports-related concussion, item response theory, concussion assessment

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Authors: Paul Moses Ndegwa, Teresia Kabucho, Lucy Wanjiru, Esther Wanjiru, Brian Githaiga, Jecinta Wambui

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Health outcome has improved in the country since 2013 following the adoption of the new constitution in Kenya with devolved governance with administration and health planning functions transferred to county governments. 2018-2022 development agenda prioritized universal healthcare coverage, food security, and nutrition, however, the emergence of Covid-19 and the increase of non-communicable diseases pose a challenge and constrain in an already overwhelmed health system. A study was conducted July-November 2021 to establish key challenges in achieving universal healthcare coverage within the county and best practices for improved non-communicable disease control. 14 health workers ranging from nurses, doctors, public health officers, clinical officers, and pharmaceutical technologists were purposely engaged to provide critical information through questionnaires by a trained duo observing ethical procedures on confidentiality. Data analysis. Communicable diseases are major causes of morbidity and mortality. Non-communicable diseases contribute to approximately 39% of deaths. More than 45% of the population does not have access to safe drinking water. Study noted geographic inequality with respect to distribution and use of health resources including competing non-health priorities. 56% of health workers are nurses, 13% clinical officers, 7% doctors, 9%public health workers, 2% are pharmaceutical technologists. Poor-quality data limits the validity of disease-burdened estimates and research activities. Risk factors include unsafe water, sanitation, hand washing, unsafe sex, and malnutrition. Key challenge in achieving universal healthcare coverage is the rise in the relative contribution of non-communicable diseases. Improve targeted disease control with effective and equitable resource allocation. Develop high infectious disease control mechanisms. Improvement of quality data for decision making. Strengthen electronic data-capture systems. Increase investments in the health workforce to improve health service provision and achievement of universal health coverage. Create a favorable environment to retain health workers. Fill in staffing gaps resulting in shortages of doctors (7%). Develop a multi-sectional approach to health workforce planning and management. Need to invest in mechanisms that generate contextual evidence on current and future health workforce needs. Ensure retention of qualified, skilled, and motivated health workforce. Deliver integrated people-centered health services.

Keywords: multi-sectional approach, equity, people-centered, health workforce retention

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Authors: Martin Kittel, Alexander Roth

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The continuous integration of variable renewable energy sources (VRE) in the power sector is required for decarbonizing the European economy. Power sectors become increasingly exposed to weather variability, as the availability of VRE, i.e., mainly wind and solar photovoltaic, is not persistent. Extreme events, e.g., long-lasting periods of scarce VRE availability (‘VRE droughts’), challenge the reliability of supply. Properly accounting for the severity of VRE droughts is crucial for designing a resilient renewable European power sector. Energy system modeling is used to identify such a design. Our analysis reveals the sensitivity of the optimal design of the European power sector towards VRE droughts. We analyze how VRE droughts impact optimal power sector investments, especially in generation and flexibility capacity. We draw upon work that systematically identifies VRE drought patterns in Europe in terms of frequency, duration, and seasonality, as well as the cross-regional and cross-technological correlation of most extreme drought periods. Based on their analysis, the authors provide a selection of relevant historical weather years representing different grades of VRE drought severity. These weather years will serve as input for the capacity expansion model for the European power sector used in this analysis (DIETER). We additionally conduct robustness checks varying policy-relevant assumptions on capacity expansion limits, interconnections, and level of sector coupling. Preliminary results illustrate how an imprudent selection of weather years may cause underestimating the severity of VRE droughts, flawing modeling insights concerning the need for flexibility. Sub-optimal European power sector designs vulnerable to extreme weather can result. Using relevant weather years that appropriately represent extreme weather events, our analysis identifies a resilient design of the European power sector. Although the scope of this work is limited to the European power sector, we are confident that our insights apply to other regions of the world with similar weather patterns. Many energy system studies still rely on one or a limited number of sometimes arbitrarily chosen weather years. We argue that the deliberate selection of relevant weather years is imperative for robust modeling results.

Keywords: energy systems, numerical optimization, variable renewable energy sources, energy drought, flexibility

Procedia PDF Downloads 51

Authors: Jeff Moussodji, Dominique Drouin

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The highly complex technology requirements of today’s integrated circuits (ICs), lead to the increased use of several materials types such as metal structures, brittle and porous low-k materials which are used in both front end of line (FEOL) and back end of line (BEOL) process for wafer manufacturing. In order to singulate chip from wafer, a critical laser-grooving process, prior to blade dicing, is used to remove these layers of materials out of the dicing street. The combination of laser-grooving and blade dicing allows to reduce the potential risk of induced mechanical defects such micro-cracks, chipping, on the wafer top surface where circuitry is located. It seems, therefore, essential to have a fundamental understanding of the physics involving laser-dicing in order to maximize control of these critical process and reduce their undesirable effects on process efficiency, quality, and reliability. In this paper, the study was based on the convergence of two approaches, numerical and experimental studies which allowed us to investigate the interaction of a nanosecond pulsed laser and BEOL wafer materials. To evaluate this interaction, several laser grooved samples were compared with finite element modeling, in which three different aspects; phase change, thermo-mechanical and optic sensitive parameters were considered. The mathematical model makes it possible to highlight a groove profile (depth, width, etc.) of a single pulse or multi-pulses on BEOL wafer material. Moreover, the heat affected zone, and thermo-mechanical stress can be also predicted as a function of laser operating parameters (power, frequency, spot size, defocus, speed, etc.). After modeling validation and calibration, a satisfying correlation between experiment and modeling, results have been observed in terms of groove depth, width and heat affected zone. The study proposed in this work is a first step toward implementing a quick assessment tool for design and debug of multiple laser grooving conditions with limited experiments on hardware in industrial application. More correlations and validation tests are in progress and will be included in the full paper.

Keywords: laser-dicing, nano-second pulsed laser, wafer multi-stack, multiphysics modeling

Procedia PDF Downloads 183

Authors: Jihane Bouabid

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The urgency to transition towards sustainable energy sources has revealed itself imperative. Today, in the 21st Century, the intellectual society have imposed technological advancements and improvements, and anticipates expeditious outcomes as an integral component of its relentless pursuit of an elevated standard of living. As a part of empowering human development, driving economic growth and meeting social needs, the access to energy services has become a necessity. As a part of these improvements, we are introducing the project "Mywindturbine" - an interactive web user interface for design and analysis in the field of wind energy, with a particular adherence to the IEC (International Electrotechnical Commission) standard 61400-2 "Wind turbines – Part 2: Design requirements for small wind turbines". Wind turbines play a pivotal role in Morocco's renewable energy strategy, leveraging the nation's abundant wind resources. The IEC 61400-2 standard ensures the safety and design integrity of small wind turbines deployed in Morocco, providing guidelines for performance and safety protocols. The conformity with this standard ensures turbine reliability, facilitates standards alignment, and accelerates the integration of wind energy into Morocco's energy landscape. The aim of the GUI (Graphical User Interface) for engineers and professionals from the field of wind energy systems who would like to design a small wind turbine system following the safety requirements of the international standards IEC 61400-2. The interface provides an easy way to analyze the structure of the turbine machine under normal and extreme load conditions based on the specific inputs provided by the user. The platform introduces an overview to sustainability and renewable energy, with a focus on wind turbines. It features a cross-examination of the input parameters provided from the user for the SLM (Simple Load Model) of small wind turbines, and results in an analysis according to the IEC 61400-2 standard. The analysis of the simple load model encompasses calculations for fatigue loads on blades and rotor shaft, yaw error load on blades, etc. for the small wind turbine performance. Through its structured framework and adherence to the IEC standard, "Mywindturbine" aims to empower professionals, engineers, and intellectuals with the knowledge and tools necessary to contribute towards a sustainable energy future.

Keywords: small wind turbine, IEC 61400-2 standard, user interface., simple load model

Procedia PDF Downloads 28

Authors: Alia Alghosoun, Nabil El Moçayd, Mohammed Seaid

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Modeling dam-break flows over non-flat beds requires an accurate representation of the topography which is the main source of uncertainty in the model. Therefore, developing robust and accurate techniques for reconstructing topography in this class of problems would reduce the uncertainty in the flow system. In many hydraulic applications, experimental techniques have been widely used to measure the bed topography. In practice, experimental work in hydraulics may be very demanding in both time and cost. Meanwhile, computational hydraulics have served as an alternative for laboratory and field experiments. Unlike the forward problem, the inverse problem is used to identify the bed parameters from the given experimental data. In this case, the shallow water equations used for modeling the hydraulics need to be rearranged in a way that the model parameters can be evaluated from measured data. However, this approach is not always possible and it suffers from stability restrictions. In the present work, we propose an adaptive optimal control technique to numerically identify the underlying bed topography from a given set of free-surface observation data. In this approach, a minimization function is defined to iteratively determine the model parameters. The proposed technique can be interpreted as a fractional-stage scheme. In the first stage, the forward problem is solved to determine the measurable parameters from known data. In the second stage, the adaptive control Ensemble Kalman Filter is implemented to combine the optimality of observation data in order to obtain the accurate estimation of the topography. The main features of this method are on one hand, the ability to solve for different complex geometries with no need for any rearrangements in the original model to rewrite it in an explicit form. On the other hand, its achievement of strong stability for simulations of flows in different regimes containing shocks or discontinuities over any geometry. Numerical results are presented for a dam-break flow problem over non-flat bed using different solvers for the shallow water equations. The robustness of the proposed method is investigated using different numbers of loops, sensitivity parameters, initial samples and location of observations. The obtained results demonstrate high reliability and accuracy of the proposed techniques.

Keywords: erodible beds, finite element method, finite volume method, nonlinear elasticity, shallow water equations, stresses in soil

Procedia PDF Downloads 110

Authors: Zeinab Yazdanfar, Dilan Robert, Daniel Lester, S. Setunge

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Scour has been identified as the most common threat to bridge stability worldwide. Traditionally, scour around bridge piers is calculated using the empirical approaches that have considerable limitations and are difficult to generalize. The multi-physic nature of scouring which involves turbulent flow, soil mechanics and solid-fluid interactions cannot be captured by simple empirical equations developed based on limited laboratory data. These limitations can be overcome by direct numerical modeling of coupled hydro-mechanical scour process that provides a robust prediction of bridge scour and valuable insights into the scour process. Several numerical models have been proposed in the literature for bridge scour estimation including Eulerian flow models and coupled Euler-Lagrange models incorporating an empirical sediment transport description. However, the contact forces between particles and the flow-particle interaction haven’t been taken into consideration. Incorporating collisional and frictional forces between soil particles as well as the effect of flow-driven forces on particles will facilitate accurate modeling of the complex nature of scour. In this study, a coupled Computational Fluid Dynamics and Discrete Element Model (CFD-DEM) has been developed to simulate the scour process that directly models the hydro-mechanical interactions between the sediment particles and the flowing water. This approach obviates the need for an empirical description as the fundamental fluid-particle, and particle-particle interactions are fully resolved. The sediment bed is simulated as a dense pack of particles and the frictional and collisional forces between particles are calculated, whilst the turbulent fluid flow is modeled using a Reynolds Averaged Navier Stocks (RANS) approach. The CFD-DEM model is validated against experimental data in order to assess the reliability of the CFD-DEM model. The modeling results reveal the criticality of particle impact on the assessment of scour depth which, to the authors’ best knowledge, hasn’t been considered in previous studies. The results of this study open new perspectives to the scour depth and time assessment which is the key to manage the failure risk of bridge infrastructures.

Keywords: bridge scour, discrete element method, CFD-DEM model, multi-phase model

Procedia PDF Downloads 107

Authors: Fatima Khurshid, Noor Ul Ain, Syed Abdul Rehman Kashif, Zainab Riaz, Abdullah Usman Khan, Muhammad Imran

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As the world is moving towards extra-high voltage (EHV) and ultra-high voltage (UHV) power systems, the performance requirements of power transformers are becoming crucial to the system reliability and security. With the transformers being an essential component of a power system, low health index of transformers poses greater risks for safe and reliable operation. Therefore, to meet the rising demands of the power system and transformer performance, researchers are being prompted to provide solutions for enhanced thermal and electrical properties of transformers. This paper proposes an approach to improve the health index of a transformer by using nano-technology in conjunction with bio-degradable oils. Vegetable oils can serve as potential dielectric fluid alternatives to the conventional mineral oils, owing to their numerous inherent benefits; namely, higher fire and flashpoints, and being environment-friendly in nature. Moreover, the addition of nanoparticles in the dielectric fluid further serves to improve the dielectric strength of the insulation medium. In this research, using the finite element method (FEM) in COMSOL Multiphysics environment, and a 2D space dimension, three different oil samples have been modelled, and the electric field distribution is computed for each sample at various electric potentials, i.e., 90 kV, 100 kV, 150 kV, and 200 kV. Furthermore, each sample has been modified with the addition of nanoparticles of different radii (50 nm and 100 nm) and at different interparticle distance (5 mm and 10 mm), considering an instant of time. The nanoparticles used are non-conductive and have been modelled as alumina (Al₂O₃). The geometry has been modelled according to IEC standard 60897, with a standard electrode gap distance of 25 mm. For an input supply voltage of 100 kV, the maximum electric field stresses obtained for the samples of synthetic vegetable oil, olive oil, and mineral oil are 5.08 ×10⁶ V/m, 5.11×10⁶ V/m and 5.62×10⁶ V/m, respectively. It is observed that for the unmodified samples, vegetable oils have a greater dielectric strength as compared to the conventionally used mineral oils because of their higher flash points and higher values of relative permittivity. Also, for the modified samples, the addition of nanoparticles inhibits the streamer propagation inside the dielectric medium and hence, serves to improve the dielectric properties of the medium.

Keywords: dielectric strength, finite element method, health index, nanotechnology, streamer propagation

Procedia PDF Downloads 121

Authors: Sakshi Dhumale, Madhushree C., Amba Shetty

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The effect of station density on the geostatistical prediction of groundwater levels is of critical importance to ensure accurate and reliable predictions. Monitoring station density directly impacts the accuracy and reliability of geostatistical predictions by influencing the model's ability to capture localized variations and small-scale features in groundwater levels. This is particularly crucial in regions with complex hydrogeological conditions and significant spatial heterogeneity. Insufficient station density can result in larger prediction uncertainties, as the model may struggle to adequately represent the spatial variability and correlation patterns of the data. On the other hand, an optimal distribution of monitoring stations enables effective coverage of the study area and captures the spatial variability of groundwater levels more comprehensively. In this study, we investigate the effect of station density on the predictive performance of groundwater levels using the geostatistical technique of Ordinary Kriging. The research utilizes groundwater level data collected from 121 observation wells within the semi-arid Berambadi watershed, gathered over a six-year period (2010-2015) from the Indian Institute of Science (IISc), Bengaluru. The dataset is partitioned into seven subsets representing varying sampling densities, ranging from 15% (12 wells) to 100% (121 wells) of the total well network. The results obtained from different monitoring networks are compared against the existing groundwater monitoring network established by the Central Ground Water Board (CGWB). The findings of this study demonstrate that higher station densities significantly enhance the accuracy of geostatistical predictions for groundwater levels. The increased number of monitoring stations enables improved interpolation accuracy and captures finer-scale variations in groundwater levels. These results shed light on the relationship between station density and the geostatistical prediction of groundwater levels, emphasizing the importance of appropriate station densities to ensure accurate and reliable predictions. The insights gained from this study have practical implications for designing and optimizing monitoring networks, facilitating effective groundwater level assessments, and enabling sustainable management of groundwater resources.

Keywords: station density, geostatistical prediction, groundwater levels, monitoring networks, interpolation accuracy, spatial variability

Procedia PDF Downloads 26

Authors: Tiptunya Duangsri, Panwilai Chomchid, Natchanok Jansawang

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This research study was to investigate of education decisions must be made which a part of it should be passed on to future generations as obligatory for all members of a chemistry class for students who will prepare themselves for a special position. The descriptions of instructional design were provided and the recent criticisms are discussed. This research study to an outline of an integrative framework for the description of information and the instructional design model give structure to negotiate a semblance of conscious understanding. The aims of this study are to describe the instructional design model for comparisons between students’ genders of their effects on STEM educational learning achievement motives to their science attitudes and logical thinking abilities with a sample size of 18 students at the 11th grade level with the cluster random sampling technique in Mahawichanukul School were designed. The chemistry learning environment was administered with the STEM education method. To build up the 5-instrument lesson instructional plan issues were instructed innovations, the 30-item Logical Thinking Test (LTT) on 5 scales, namely; Inference, Recognition of Assumptions, Deduction, Interpretation and Evaluation scales was used. Students’ responses of their perceptions with the Test Of Chemistry-Related Attitude (TOCRA) were assessed of their attitude in science toward chemistry. The validity from Index Objective Congruence value (IOC) checked by five expert specialist educator in two chemistry classroom targets in STEM education, the E1/E2 process were equaled evidence of 84.05/81.42 which results based on criteria are higher than of 80/80 standard level with the IOC from the expert educators. Comparisons between students’ learning achievement motives with STEM educational model on stoichiometry issue in chemistry classes with different genders were differentiated at evidence level of .05, significantly. Associations between students’ learning achievement motives on their posttest outcomes and logical thinking abilities, the predictive efficiency (R2) values indicate that 69% and 70% of the variances in different male and female student groups of their logical thinking abilities. The predictive efficiency (R2) values indicate that 73%; and 74% of the variances in different male and female student groups of their science attitudes toward chemistry were associated. Statistically significant on students’ perceptions of their chemistry learning classroom environment and their science attitude toward chemistry when using the MCI and TOCRA, the predictive efficiency (R2) values indicated that 72% and 74% of the variances in different male and female student groups of their chemistry classroom climate, consequently. Suggestions that supporting chemistry or science teachers from science, technology, engineering and mathematics (STEM) in addressing complex teaching and learning issues related instructional design to develop, teach, and assess traditional are important strategies with a focus on STEM education instructional method.

Keywords: development, the instructional design model, students learning achievement motives, science attitudes with STEM educational model, stoichiometry issue, chemistry classes, genders

Procedia PDF Downloads 255

Authors: Muhammad Umer Mehmood, Muhammad Luqman, Muhammad Yaseen, Imtiaz Hussain

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Climate change is an arduous fact, which could not be unheeded easily. It is a phenomenon which has brought a collection of challenges for the mankind. Scientists have found many of its negative impacts on the life of human being and the resources on which the life of humanity is dependent. There are many issues which are associated with the factor of prime importance in this study, 'climate change'. Whenever changes happen in nature, they strike the whole globe. Effects of these changes vary from region to region. Climate of every region of this globe is different from the other. Even within a state, country or the province has different climatic conditions. So it is mandatory that the response in that specific region and the coping strategy of this specific region should be according to the prevailing risk. In the present study, the objective was to assess the coping strategies and vulnerability of small landholders. So that a professional suggestion could be made to cope with the vulnerability factor of small farmers. The cross-sectional research design was used with the intervention of quantitative approach. The study was conducted in the Khanewal district, of Punjab, Pakistan. 120 small farmers were interviewed after randomized sampling from the population of respective area. All respondents were above the age of 15 years. A questionnaire was developed after keen observation of facts in the respective area. Content and face validity of the instrument was assessed with SPSS and experts in the field. Data were analyzed through SPSS using descriptive statistics. From the sample of 120, 81.67% of the respondents claimed that the environment is getting warmer and not fit for their present agricultural practices. 84.17% of the sample expressed serious concern that they are disturbed due to change in rainfall pattern and vulnerability towards the climatic effects. On the other hand, they expressed that they are not good at tackling the effects of climate change. Adaptation of coping strategies like change in cropping pattern, use of resistant varieties, varieties with minimum water requirement, intercropping and tree planting was low by more than half of the sample. From the sample 63.33% small farmers said that the coping strategies they adopt are not effective enough. The present study showed that subsistence farming, lack of marketing and overall infrastructure, lack of access to social security networks, limited access to agriculture extension services, inappropriate access to agrometeorological system, unawareness and access to scientific development and low crop yield are the prominent factors which are responsible for the vulnerability of small farmers. A comprehensive study should be conducted at national level so that a national policy could be formulated to cope with the dilemma in future with relevance to climate change. Mainstreaming and collaboration among the researchers and academicians could prove beneficiary in this regard the interest of national leaders’ does matter. Proper policies to avoid the vulnerability factors should be the top priority. The world is taking up this issue with full responsibility as should we, keeping in view the local situation.

Keywords: adaptation, coping strategies, climate change, Pakistan, small farmers, vulnerability

Procedia PDF Downloads 109

Authors: M. Salvador, J. C. Martinez-Garcia, A. Moyano, M. C. Blanco-Lopez, M. Rivas

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Biosensors play a crucial role in the detection of molecules nowadays due to their advantages of user-friendliness, high selectivity, the analysis in real time and in-situ applications. Among them, Lateral Flow Immunoassays (LFIAs) are presented among technologies for point-of-care bioassays with outstanding characteristics such as affordability, portability and low-cost. They have been widely used for the detection of a vast range of biomarkers, which do not only include proteins but also nucleic acids and even whole cells. Although the LFIA has traditionally been a positive/negative test, tremendous efforts are being done to add to the method the quantifying capability based on the combination of suitable labels and a proper sensor. One of the most successful approaches involves the use of magnetic sensors for detection of magnetic labels. Bringing together the required characteristics mentioned before, our research group has developed a biosensor to detect biomolecules. Superparamagnetic nanoparticles (SPNPs) together with LFIAs play the fundamental roles. SPMNPs are detected by their interaction with a high-frequency current flowing on a printed micro track. By means of the instant and proportional variation of the impedance of this track provoked by the presence of the SPNPs, quantitative and rapid measurement of the number of particles can be obtained. This way of detection requires no external magnetic field application, which reduces the device complexity. On the other hand, the major limitations of LFIAs are that they are only qualitative or semiquantitative when traditional gold or latex nanoparticles are used as color labels. Moreover, the necessity of always-constant ambient conditions to get reproducible results, the exclusive detection of the nanoparticles on the surface of the membrane, and the short durability of the signal are drawbacks that can be advantageously overcome with the design of magnetically labeled LFIAs. The approach followed was to coat the SPIONs with a specific monoclonal antibody which targets the protein under consideration by chemical bonds. Then, a sandwich-type immunoassay was prepared by printing onto the nitrocellulose membrane strip a second antibody against a different epitope of the protein (test line) and an IgG antibody (control line). When the sample flows along the strip, the SPION-labeled proteins are immobilized at the test line, which provides magnetic signal as described before. Preliminary results using this practical combination for the detection and quantification of the Prostatic-Specific Antigen (PSA) shows the validity and consistency of the technique in the clinical range, where a PSA level of 4.0 ng/mL is the established upper normal limit. Moreover, a LOD of 0.25 ng/mL was calculated with a confident level of 3 according to the IUPAC Gold Book definition. Its versatility has also been proved with the detection of other biomolecules such as troponin I (cardiac injury biomarker) or histamine.

Keywords: biosensor, lateral flow immunoassays, point-of-care devices, superparamagnetic nanoparticles

Procedia PDF Downloads 212

Authors: Pratap Chandra Pati, Prabina Rajib, Parama Barai

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The traditional finance theory neglects the role of sentiment factor in asset pricing. However, the behavioral approach to asset-pricing based on noise trader model and limit to arbitrage includes investor sentiment as a priced risk factor in the assist pricing model. Investor sentiment affects stock more that are vulnerable to speculation, hard to value and risky to arbitrage. It includes small stocks, high volatility stocks, growth stocks, distressed stocks, young stocks and non-dividend-paying stocks. Since the introduction of Chicago Board Options Exchange (CBOE) volatility index (VIX) in 1993, it is used as a measure of future volatility in the stock market and also as a measure of investor sentiment. CBOE VIX index, in particular, is often referred to as the ‘investors’ fear gauge’ by public media and prior literature. The upward spikes in the volatility index are associated with bouts of market turmoil and uncertainty. High levels of the volatility index indicate fear, anxiety and pessimistic expectations of investors about the stock market. On the contrary, low levels of the volatility index reflect confident and optimistic attitude of investors. Based on the above discussions, we investigate whether market-wide fear levels measured volatility index is priced factor in the standard asset pricing model for the Indian stock market. First, we investigate the performance and validity of Fama and French three-factor model and Carhart four-factor model in the Indian stock market. Second, we explore whether India volatility index as a proxy for fearful market-based sentiment indicators affect the cross section of stock returns after controlling for well-established risk factors such as market excess return, size, book-to-market, and momentum. Asset pricing tests are performed using monthly data on CNX 500 index constituent stocks listed on the National stock exchange of India Limited (NSE) over the sample period that extends from January 2008 to March 2017. To examine whether India volatility index, as an indicator of fear sentiment, is a priced risk factor, changes in India VIX is included as an explanatory variable in the Fama-French three-factor model as well as Carhart four-factor model. For the empirical testing, we use three different sets of test portfolios used as the dependent variable in the in asset pricing regressions. The first portfolio set is the 4x4 sorts on the size and B/M ratio. The second portfolio set is the 4x4 sort on the size and sensitivity beta of change in IVIX. The third portfolio set is the 2x3x2 independent triple-sorting on size, B/M and sensitivity beta of change in IVIX. We find evidence that size, value and momentum factors continue to exist in Indian stock market. However, VIX index does not constitute a priced risk factor in the cross-section of returns. The inseparability of volatility and jump risk in the VIX is a possible explanation of the current findings in the study.

Keywords: India VIX, Fama-French model, Carhart four-factor model, asset pricing

Procedia PDF Downloads 227

Authors: Moustafa Osman Mohammed

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The modeling of a spatial-economic database is crucial in recitation economic network structure to social development. Sustainability within the spatial-economic model gives attention to green businesses to comply with Earth’s Systems. The natural exchange patterns of ecosystems have consistent and periodic cycles to preserve energy and materials flow in systems ecology. When network topology influences formal and informal communication to function in systems ecology, ecosystems are postulated to valence the basic level of spatial sustainable outcome (i.e., project compatibility success). These referred instrumentalities impact various aspects of the second level of spatial sustainable outcomes (i.e., participant social security satisfaction). The sustainability outcomes are modeling composite structure based on a network analysis model to calculate the prosperity of panel databases for efficiency value, from 2005 to 2025. The database is modeling spatial structure to represent state-of-the-art value-orientation impact and corresponding complexity of sustainability issues (e.g., build a consistent database necessary to approach spatial structure; construct the spatial-economic-ecological model; develop a set of sustainability indicators associated with the model; allow quantification of social, economic and environmental impact; use the value-orientation as a set of important sustainability policy measures), and demonstrate spatial structure reliability. The structure of spatial-ecological model is established for management schemes from the perspective pollutants of multiple sources through the input–output criteria. These criteria evaluate the spillover effect to conduct Monte Carlo simulations and sensitivity analysis in a unique spatial structure. The balance within “equilibrium patterns,” such as collective biosphere features, has a composite index of many distributed feedback flows. The following have a dynamic structure related to physical and chemical properties for gradual prolong to incremental patterns. While these spatial structures argue from ecological modeling of resource savings, static loads are not decisive from an artistic/architectural perspective. The model attempts to unify analytic and analogical spatial structure for the development of urban environments in a relational database setting, using optimization software to integrate spatial structure where the process is based on the engineering topology of systems ecology.

Keywords: ecological modeling, spatial structure, orientation impact, composite index, industrial ecology

Procedia PDF Downloads 30

Authors: Afshin Kadri

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Using Renewable Energy Resources (RES) as a type of DG unit is developing in distribution systems. The connection of these generation units to existing AC distribution systems changes the structure and some of the operational aspects of these grids. Most of the RES requires to power electronic-based interfaces for connection to AC systems. These interfaces consist of at least one DC/AC conversion unit. Nowadays, grid-connected inverters must have the required feature to support the grid under sag voltage conditions. There are two curves in these conditions that show the magnitude of the reactive component of current as a function of voltage drop value and the required minimum time value, which must be connected to the grid. This feature is named low voltage ride-through (LVRT). Implementing this feature causes problems in the operation of the inverter that increases the amplitude of high-frequency components of the injected current and working out of maximum power point in the photovoltaic panel connected inverters are some of them. The important phenomenon in these conditions is ripples in the DC bus voltage that affects the operation of the inverter directly and indirectly. The losses of DC bus capacitors which are electrolytic capacitors, cause increasing their temperature and decreasing its lifespan. In addition, if the inverter is connected to the photovoltaic panels directly and has the duty of maximum power point tracking, these ripples cause oscillations around the operating point and decrease the generating energy. Using a bidirectional converter in the DC bus, which works as a buck and boost converter and transfers the ripples to its DC bus, is the traditional method to eliminate these ripples. In spite of eliminating the ripples in the DC bus, this method cannot solve the problem of reliability because it uses an electrolytic capacitor in its DC bus. In this work, a control method is proposed which uses the bidirectional converter as the fourth leg of the inverter and eliminates the DC bus ripples using an injection of unbalanced currents into the grid. Moreover, the proposed method works based on constant power control. In this way, in addition, to supporting the amplitude of grid voltage, it stabilizes its frequency by injecting active power. Also, the proposed method can eliminate the DC bus ripples in deep voltage drops, which cause increasing the amplitude of the reference current more than the nominal current of the inverter. The amplitude of the injected current for the faulty phases in these conditions is kept at the nominal value and its phase, together with the phase and amplitude of the other phases, are adjusted, which at the end, the ripples in the DC bus are eliminated, however, the generated power decreases.

Keywords: renewable energy resources, voltage drop value, DC bus ripples, bidirectional converter

Procedia PDF Downloads 48

Authors: Farnaz Alborzi, Angelika Schmitz, Rainer Stamminger

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Reducing water temperatures in the wash phase of a washing programme and increasing the overall cycle durations are the latest trends in decreasing energy consumption of washing programmes. Since the implementation of the new energy efficiency classes in 2010, manufacturers seem to apply the aforementioned washing strategy with lower temperatures combined with longer programme durations extensively to realise energy-savings needed to meet the requirements of the highest energy efficiency class possible. A semi-representative on-line survey in eleven European countries (Czech Republic, Finland, France, Germany, Hungary, Italy, Poland, Romania, Spain, Sweden and the United Kingdom) was conducted by Bonn University in 2015 to shed light on consumer opinion and behaviour regarding the effects of the lower washing temperature and longer cycle duration in laundry washing on consumers’ acceptance of the programme. The risk of the long wash cycle is that consumers might not use the energy efficient Standard programmes and will think of this option as inconvenient and therefore switch to shorter, but more energy consuming programmes. Furthermore, washing in a lower temperature may lead to the problem of cross-contamination. Washing behaviour of over 5,000 households was studied in this survey to provide support and guidance for manufacturers and policy designers. Qualified households were chosen following a predefined quota: -Involvement in laundry washing: substantial, -Distribution of gender: more than 50 % female , -Selected age groups: -20–39 years, -40–59 years, -60–74 years, -Household size: 1, 2, 3, 4 and more than 4 people. Furthermore, Eurostat data for each country were used to calculate the population distribution in the respective age class and household size as quotas for the consumer survey distribution in each country. Before starting the analyses, the validity of each dataset was controlled with the aid of control questions. After excluding the outlier data, the number of the panel diminished from 5,100 to 4,843. The primary outcome of the study is European consumers are willing to save water and energy in a laundry washing but reluctant to use long programme cycles since they don’t believe that the long cycles could be energy-saving. However, the results of our survey don’t confirm that there is a relation between frequency of using Standard cotton (Eco) or Energy-saving programmes and the duration of the programmes. It might be explained by the fact that the majority of washing programmes used by consumers do not take so long, perhaps consumers just choose some additional time reduction option when selecting those programmes and this finding might be changed if the Energy-saving programmes take longer. Therefore, it may be assumed that introducing the programme duration as a new measure on a revised energy label would strongly influence the consumer at the point of sale. Furthermore, results of the survey confirm that consumers are more willing to use lower temperature programmes in order to save energy than accepting longer programme cycles and majority of them accept deviation from the nominal temperature of the programme as long as the results are good.

Keywords: duration, energy-saving, standard programmes, washing temperature

Procedia PDF Downloads 201

Authors: Md Tanvir Rahman, Mahbube Subhani, Mahmud Ashraf, Paul Kremer

Abstract:

Cross-laminated timber (CLT) is made from layers of timber boards orthogonally oriented in the thickness direction, and due to this, CLT can withstand bi-axial bending in contrast with most other engineered wood products such as laminated veneer lumber (LVL) and glued laminated timber (GLT). Wood is cylindrically anisotropic in nature and is characterized by significantly lower elastic modulus and shear modulus in the planes perpendicular to the fibre direction, and is therefore classified as orthotropic material and is thus characterized by 9 elastic constants which are three elastic modulus in longitudinal direction, tangential direction and radial direction, three shear modulus in longitudinal tangential plane, longitudinal radial plane and radial tangential plane and three Poisson’s ratio. For simplification, timber materials are generally assumed to be transversely isotropic, reducing the number of elastic properties characterizing it to 5, where the longitudinal plane and radial planes are assumed to be planes of symmetry. The validity of this assumption was investigated through numerical modelling of CLT with both orthotropic mechanical properties and transversely isotropic material properties for three softwood species, which are Norway spruce, Douglas fir, Radiata pine, and three hardwood species, namely Victorian ash, Beech wood, and Aspen subjected to uniformly distributed loading under simply supported boundary condition. It was concluded that assuming the timber to be transversely isotropic results in a negligible error in the order of 1 percent. It was also observed that along with longitudinal elastic modulus, ratio of longitudinal shear modulus (GL) and rolling shear modulus (GR) has a significant effect on a deflection for CLT panels of lower span to depth ratio. For softwoods such as Norway spruce and Radiata pine, the ratio of longitudinal shear modulus, GL to rolling shear modulus GR is reported to be in the order of 12 to 15 times in literature. This results in shear flexibility in transverse layers leading to increased deflection under out-of-plane loading. The rolling shear modulus of hardwoods has been found to be significantly higher than those of softwoods, where the ratio between longitudinal shear modulus to rolling shear modulus as low as 4. This has resulted in a significant rise in research into the manufacturing of CLT from entirely from hardwood, as well as from a combination of softwood and hardwoods. The commonly used beam theory to analyze the performance of CLT panels under out-of-plane loads are the Shear analogy method, Gamma method, and k-method. The shear analogy method has been found to be the most effective method where shear deformation is significant. The effect of the ratio of longitudinal shear modulus and rolling shear modulus of cross-layer on the deflection of CLT under uniformly distributed load with respect to its length to depth ratio was investigated using shear analogy method. It was observed that shear deflection is reduced significantly as the ratio of the shear modulus of the longitudinal layer and rolling shear modulus of cross-layer decreases. This indicates that there is significant room for improvement of the bending performance of CLT through developing hybrid CLT from a mix of softwood and hardwood.

Keywords: rolling shear modulus, shear deflection, ratio of shear modulus and rolling shear modulus, timber

Procedia PDF Downloads 99

Authors: Mohamad R. Moshtagh, Ahmad Bagheri

Abstract:

Accurate fault detection in rotating machinery is of utmost importance to ensure optimal performance and prevent costly downtime in industrial applications. This study presents a robust fault detection system based on vibration data collected from rotating gears under various operating conditions. The considered scenarios include: (1) both gears being healthy, (2) one healthy gear and one faulty gear, and (3) introducing an imbalanced condition to a healthy gear. Vibration data was acquired using a Hentek 1008 device and stored in a CSV file. Python code implemented in the Spider environment was used for data preprocessing and analysis. Winner features were extracted using the Wiener feature selection method. These features were then employed in multiple machine learning algorithms, including Convolutional Neural Networks (CNN), Multilayer Perceptron (MLP), K-Nearest Neighbors (KNN), and Random Forest, to evaluate their performance in detecting and classifying faults in both the training and validation datasets. The comparative analysis of the methods revealed the superior performance of the Wiener-CNN approach. The Wiener-CNN method achieved a remarkable accuracy of 100% for both the two-class (healthy gear and faulty gear) and three-class (healthy gear, faulty gear, and imbalanced) scenarios in the training and validation datasets. In contrast, the other methods exhibited varying levels of accuracy. The Wiener-MLP method attained 100% accuracy for the two-class training dataset and 100% for the validation dataset. For the three-class scenario, the Wiener-MLP method demonstrated 100% accuracy in the training dataset and 95.3% accuracy in the validation dataset. The Wiener-KNN method yielded 96.3% accuracy for the two-class training dataset and 94.5% for the validation dataset. In the three-class scenario, it achieved 85.3% accuracy in the training dataset and 77.2% in the validation dataset. The Wiener-Random Forest method achieved 100% accuracy for the two-class training dataset and 85% for the validation dataset, while in the three-class training dataset, it attained 100% accuracy and 90.8% accuracy for the validation dataset. The exceptional accuracy demonstrated by the Wiener-CNN method underscores its effectiveness in accurately identifying and classifying fault conditions in rotating machinery. The proposed fault detection system utilizes vibration data analysis and advanced machine learning techniques to improve operational reliability and productivity. By adopting the Wiener-CNN method, industrial systems can benefit from enhanced fault detection capabilities, facilitating proactive maintenance and reducing equipment downtime.

Keywords: fault detection, gearbox, machine learning, wiener method

Procedia PDF Downloads 53