Search results for: Random Numbers

Authors: Seungho Shin, Keunwoo Choi, Ali Akbar, Sukkee Um

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In this study, the nanoscale transport properties and catalyst utilization of vertically aligned carbon nanotube (VACNT) catalyst layers are computationally predicted by the three-dimensional lattice Boltzmann simulation based on the quasi-random nanostructural model in pursuance of fuel cell catalyst performance improvement. A series of catalyst layers are randomly generated with statistical significance at the 95% confidence level to reflect the heterogeneity of the catalyst layer nanostructures. The nanoscale gas transport phenomena inside the catalyst layers are simulated by the D3Q19 (i.e., three-dimensional, 19 velocities) lattice Boltzmann method, and the corresponding mass transport characteristics are mathematically modeled in terms of structural properties. Considering the nanoscale reactant transport phenomena, a transport-based effective catalyst utilization factor is defined and statistically analyzed to determine the structure-transport influence on catalyst utilization. The tortuosity of the reactant mass transport path of VACNT catalyst layers is directly calculated from the streaklines. Subsequently, the corresponding effective mass diffusion coefficient is statistically predicted by applying the pre-estimated tortuosity factors to the Knudsen diffusion coefficient in the VACNT catalyst layers. The statistical estimation results clearly indicate that the morphological structures of VACNT catalyst layers reduce the tortuosity of reactant mass transport path when compared to conventional catalyst layer and significantly improve consequential effective mass diffusion coefficient of VACNT catalyst layer. Furthermore, catalyst utilization of the VACNT catalyst layer is substantially improved by enhanced mass diffusion and electric current paths despite the relatively poor interconnections of the ion transport paths.

Keywords: Lattice Boltzmann method, nano transport phenomena, polymer electrolyte fuel cells, vertically aligned carbon nanotube

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Authors: B. O. Diyaolu

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The globalization of football especially among youth over the decade is uprising. Nigeria youth displaying football jerseys at every opportunity is an acceptance of football globalization. The Love for English Premier League (EPL) football jersey is very strong among Nigeria fans. Football club jerseys of the EPL are a common sports product among fans in Nigeria. This study investigates the contribution of football club jerseys towards EPL fans’ loyalty in Nigeria. Descriptive survey research design was used for the study. The population consists of EPL fans in Nigeria. Simple random sampling technique (fish bowl without replacement) was used to select two states from the six geo-political zones. Purposive sampling technique was used to pick eight viewing centres while accidental sampling technique was used to pick five vendor stands from each State. An average of 250 respondents was selected from each state. A total of 3,200 respondents participated in the research. Two research instruments were used. A self-developed structured questionnaire on Football Jersey Scale (FJS): The instrument consists of 10 items. Fans Loyalty Scale (FLS): The instrument was modified from the psychological commitment to team (PCT) scale, and consists of 20 items. The Cronbach’s Alpha reliability coefficient of 0.72 and 0.75 was obtained, respectively. The hypothesis was tested at 0.05 significant levels. Data were analysed using frequency, percentages count, pie chart and multiple regressions. The result showed that the b-value of football club jersey is 0.148 also the standard regression coefficient (Beta) is 0.089. The t = 4.759 is statistically significant at p = 0.000. This signified a relative contribution of football club jersey on EPL fans loyalty in Nigeria. Club jersey, which is the most outstanding identifier of every club, was found to significantly predict loyalty. The jersey on the body of the fan has become the site for a declaration of loyalty which becomes available for social interaction and negotiation. The Nigerian local league clubs in an attempt to keep Nigerian fans loyal must borrow a leaf from their European counterparts.

Keywords: club Jerseys, English Premier League, football fans, Nigeria youth

Procedia PDF Downloads 237

Authors: Siddarth Kannan

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Objectives: Deep Brain Stimulation (DBS) and Motor Cortex stimulation (MCS) are innovative interventions in order to treat various neuropathic pain disorders such as post-stroke pain. While each treatment has a varying degree of success in managing pain, comparative analysis has not yet been performed, and the success rates of these techniques using validated, objective pain scores have not been synthesised. The aim of this study was to compare the effect of pain relief offered by MCS and DBS on patients with post-stroke pain and to assess if either of these procedures offered better results. Methods: A systematic review and meta-analysis were conducted in accordance with PRISMA guidelines (PROSPEROID CRD42021277542). Three databases were searched, and articles published from 2000 to June 2023 were included (last search date 25 June 2023). Meta-analysis was performed using random effects models. We evaluated the performance of DBS or MCS by assessing studies that reported pain relief using the Visual Analogue Scale (VAS). Data analysis of descriptive statistics was performed using SPSS (Version 27; IBM; Armonk; NY; USA). R statistics (Rstudio Version 4.0.1) was used to perform meta-analysis. Results: Of the 478 articles identified, 27 were included in the analysis (232 patients- 117 DBS & 115 MCS). The pooled number of patients who improved after DBS was 0.68 (95% CI, 0.57-0.77, I2=36%). The pooled number of patients who improved after MCS was 0.72 (95% CI, 0.62-0.80, I2=59%). Further sensitivity analysis was done to include only studies with a minimum of 5 patients in order to assess if there was any impact on the overall results. Nine studies each for DBS and MCS met these criteria. There seemed to be no significant difference in results. Conclusions: The use of surgical interventions such as DBS and MCS is an upcoming field for the treatment of post-stroke pain, with limited studies exploring and comparing these two techniques. While our study shows that MCS might be a slightly better treatment option, further research would need to be done in order to determine the appropriate surgical intervention for post-stroke pain.

Keywords: post-stroke pain, deep brain stimulation, motor cortex stimulation, pain relief

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Authors: Marek Dosbaba

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Within the mining sector, SEM-based Automated Mineralogy (AM) has been the standard application for quickly and efficiently handling mineral processing tasks. Over the last decade, the trend has been to analyze larger numbers of samples, often with a higher level of detail. This has necessitated a shift from interactive sample analysis performed by an operator using a SEM, to an increased reliance on offline processing to analyze and report the data. In response to this trend, TESCAN TIMA Mineral Analyzer is designed to quickly create a virtual copy of the studied samples, thereby preserving all the necessary information. Depending on the selected data acquisition mode, TESCAN TIMA can perform hyperspectral mapping and save an X-ray spectrum for each pixel or segment, respectively. This approach allows the user to browse through elemental distribution maps of all elements detectable by means of energy dispersive spectroscopy. Re-evaluation of the existing data for the presence of previously unconsidered elements is possible without the need to repeat the analysis. Additional tiers of data such as a secondary electron or cathodoluminescence images can also be recorded. To take full advantage of these information-rich datasets, TIMA utilizes a new archiving tool introduced by TESCAN. The dataset size can be reduced for long-term storage and all information can be recovered on-demand in case of renewed interest. TESCAN TIMA is optimized for network storage of its datasets because of the larger data storage capacity of servers compared to local drives, which also allows multiple users to access the data remotely. This goes hand in hand with the support of remote control for the entire data acquisition process. TESCAN also brings a newly extended open-source data format that allows other applications to extract, process and report AM data. This offers the ability to link TIMA data to large databases feeding plant performance dashboards or geometallurgical models. The traditional tabular particle-by-particle or grain-by-grain export process is preserved and can be customized with scripts to include user-defined particle/grain properties.

Keywords: Tescan, electron microscopy, mineralogy, SEM, automated mineralogy, database, TESCAN TIMA, open format, archiving, big data

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Authors: Mahmoud Huleihel, George Abu-Aqil, Manal Suleiman, Klaris Riesenberg, Itshak Lapidot, Ahmad Salman

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Urinary tract infections (UTIs) are considered to be the most common bacterial infections worldwide, which are caused mainly by Escherichia (E.) coli (about 80%). Klebsiella pneumoniae (about 10%) and Pseudomonas aeruginosa (about 6%). Although antibiotics are considered as the most effective treatment for bacterial infectious diseases, unfortunately, most of the bacteria already have developed resistance to the majority of the commonly available antibiotics. Therefore, it is crucial to identify the infecting bacteria and to determine its susceptibility to antibiotics for prescribing effective treatment. Classical methods are time consuming, require ~48 hours for determining bacterial susceptibility. Thus, it is highly urgent to develop a new method that can significantly reduce the time required for determining both infecting bacterium at the species level and diagnose its susceptibility to antibiotics. Fourier-Transform Infrared (FTIR) spectroscopy is well known as a sensitive and rapid method, which can detect minor molecular changes in bacterial genome associated with the development of resistance to antibiotics. The main goal of this study is to examine the potential of FTIR spectroscopy, in tandem with machine learning algorithms, to identify the infected bacteria at the species level and to determine E. coli susceptibility to different antibiotics directly from patients' urine in about 30minutes. For this goal, 1600 different E. coli isolates were isolated for different patients' urine sample, measured by FTIR, and analyzed using different machine learning algorithm like Random Forest, XGBoost, and CNN. We achieved 98% success in isolate level identification and 89% accuracy in susceptibility determination.

Keywords: urinary tract infections (UTIs), E. coli, Klebsiella pneumonia, Pseudomonas aeruginosa, bacterial, susceptibility to antibiotics, infrared microscopy, machine learning

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Authors: Tewodros Abate Alemayehu, Abebe Getahun, Akewake Geremew, Dawit Solomon Demeke, John Recha, Dawit Solomon, Gebremedihin Ambaw, Fasil Dawit Moges

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The purpose of this study was to examine the effects of supplementation of zinc oxide (ZnO) nanoparticles and Mannan-oligosaccharide (MOS) on growth performance, feed utilization, fatty acid profiles, hematology, and intestinal morphology of Chamo strain Nile tilapia Oreochromis niloticus (L.) fry reared at optimal temperature (28.62 ± 0.11 ⁰C). Nile tilapia fry (initial weight 1.45 ± 0.01g) were fed basal diet/control diet (Diet-T1), 6 g kg-¹ MOS supplemented diet (Diet-T2), 4 mg ZnO-NPs supplemented diet (Diet-T3), 4 mg ZnO-Bulk supplemented diet (Diet-T4), a combination of 6 g kg-¹ MOS and 4 mg ZnO-Bulk supplemented diet (Diet-T5) and combination of 6 g kg-¹ MOS and 4 mg ZnO-NPs supplemented diet (Diet-T6). Randomly, duplicate aquariums for each diet were assigned and hand-fed to apparent satiation three times daily (08:00, 12:00, and 16:00) for 12 weeks. Fish fed MOS, ZnO-NPs, and a combination of MOS and ZnO-Bulk supplemented diet had higher weight gain, Daily Growth Rate (DGR), and Specific Growth Rate (SGR) than fish fed the basal diet and other feeding groups, although the effect was not significant. According to the GC analysis, Nile tilapia was supplemented with 6 g kg-¹ MOS, 4 mg ZnO-NPs, or a combination of ZnO-NPs, and MOS showed the highest content of EPA, DHA, and higher ratios of PUFA/SFA than other feeding groups. Mean villi length in the proximal and middle portion of the Nile tilapia intestine was affected significantly (p<0.05) by diet. Fish fed Diet-T2 and Diet-T3 had significantly higher villi lengths in the proximal and middle portions of the intestine compared to other feeding groups. The inclusion of additives significantly improved goblet numbers at the proximal, middle, and distal portions of the intestine. Supplementation of additives had also improved some hematological parameters compared with control groups. In conclusion, dietary supplementation of additives MOS and ZnO-NPs could confer benefits on growth performance, fatty acid profiles, hematology, and intestinal morphology of Chamo strain Nile tilapia.

Keywords: chamo strain nile tilapia, fatty acid profile, hematology, intestinal morphology, MOS, ZnO-Bulk, ZnO-NPs

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Authors: AbdelRahman A. Faragalla, Mohamed H. Alqhtani, Mohamed M. M.Ahmed

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Saudi Arabia has currently been beset by a barrage of bizarre assemblages of subterranean termite fauna, inflicting heavy catastrophic havocs on human valued properties in various homes, storage facilities, warehouses, agricultural and horticultural crops including okra, sweet pepper, tomatoes, sorghum, date palm trees, citruses and many forest domains and green lush desert oases. The most pressing urgent priority is to use modern technologies to alleviate the painstaking obstacle of taxonomic identification of these injurious noxious pests that might lead to effective pest control in both infested agricultural commodities and field crops. Our study has indicated the use of DNA fingerprinting technologies, in order to generate basic information of the genetic similarity between 3 predominant families containing the most destructive termite species. The methodologies included extraction and DNA isolation from members of the major families and the use of randomly selected primers and PCR amplifications with the nucleotide sequences. GC content and annealing temperatures for all primers, PCR amplifications and agarose gel electrophoresis were also conducted in addition to the scoring and analysis of Random Amplification Polymorphic DNA-PCR (RAPDs). A phylogenetic analysis for different species using statistical computer program on the basis of RAPD-DNA results, represented as a dendrogram based on the average of band sharing ratio between different species. Our study aims to shed more light on this intriguing subject, which may lead to an expedited display of the kinship and relatedness of species in an ambitious undertaking to arrive at correct taxonomic classification of termite species, discover sibling species, so that a logistic rational pest management strategy could be delineated.

Keywords: DNA fingerprinting, Western Saudi Arabia, DNA primers, RAPD

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Authors: Jutharat Attawet, Alex Y. Wang, Cindy M. Farquhar, Elizabeth A. Sullivan

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Background: Adverse maternal and perinatal outcomes of multiple pregnancies resulting from multiple embryo transfers (ET) has become significant concerns. This is particularly relevant for gestational carriers since they usually do not have infertility issues. Single embryo transfer (SET) therefore has been encouraged to assist reproductive technology (ART) practice in order to reduce multiple pregnancies. Objectives: This systematic review aims to investigate the pregnancy and birth outcomes of SET and multiple ET in surrogacy arrangements. Search methods: This study is a systematic review. Electronic databases were searched from CINAHL, Medline, Embase, Scopus and ProQuest for studies from 1980 to 2017. Cross-references and national ART reports were also manual searchings. Articles without restriction of English language and study types were accessed. Carrier cycles involving in SET and multiple ET were identified in database searching. The main outcome measures including clinical pregnancy, live delivery and multiple deliveries per gestational carrier cycle were compared between SET and multiple ET. Mantel-Haenzel risk ratios (RRs) with 95% confidence intervals (CIs), using the numbers of outcome events in SET and multiple ET of each study were calculated suing RevMan5.3. Outcomes: The search returned 97 articles of which 5 met the inclusion criteria. Approximately 50% of carrier cycles were transferred a single embryo and 50% were transferred more than one embryo. The clinical pregnancy rate (CPR) was 39% for SET and 53% for multiple ET, which was not significantly different with RR = 0.83 (95% CI: 0.67-1.03). The live delivery rate was 33% for SET and 57% for multiple ET which was not significantly different with RR = 0.78 (95% CI: 0.61-1.00). The multiple delivery rate per carrier was greater risks in the multiple ET carrier cycles (RR =0.4, 95% CI: 0.01-0.26). There were 104 sets of twins (including one set of twins selectively reduced from triplets to twins) and 1 set of triples in the multiple ET carrier cycle. In the SET carrier cycles, there were 2 sets of twins. Significance of the study: SET should be advocated among surrogate carriers to prevent multiple pregnancies and subsequent adverse outcomes for both carrier and baby. Surrogacy practice should be reviewed and surrogate carriers should be fully informed of the risk of adverse maternal and birth outcome of multiple pregnancies due to multiple embryo transfers.

Keywords: assisted reproduction, birth outcomes, carrier, gestational surrogacy, multiple embryo transfer, multiple pregnancy, pregnancy outcomes, single embryo transfer, surrogate mother, systematic review

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Authors: Cheng Sim Quah, Sandra Phek Lin Sim

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This study examined how individuals in their respective teams contributed to innovation performance besides defining the term of innovation in their own respective views. This study also identified factors that motivated University staff to contribute to the innovation products. In addition, it examined whether there is a significant relationship between professional training level and the length of service among university staff towards innovation and to what extent do the two variables contributed towards innovative products. The significance of this study is that it revealed the strengths and weaknesses of the university staff when contributing to innovation performance. Stratified-random sampling was employed to determine the samples representing the population of lecturers in the study, involving 123 lecturers in one of the local universities in Malaysia. The method employed to analyze the data is through categorizing into themes for the open-ended questions besides using descriptive and inferential statistics for the quantitative data. This study revealed that two types of definition for the term “innovation” exist among the university staff, namely, creation of new product or new approach to do things as well as value-added creative way to upgrade or improve existing process and service to be more efficient. This study found that the most prominent factor that propel them towards innovation is to improve the product in order to benefit users, followed by self-satisfaction and recognition. This implies that the staff in the organization viewed the creation of innovative products as a process of growth to fulfill the needs of others and also to realize their personal potential. This study also found that there was only a significant relationship between the professional training level and the length of service of 4-6 years among the university staff. The rest of the groups based on the length of service showed that there was no significant relationship with the professional training level towards innovation. Moreover, results of the study on directional measures depicted that the relationship for the length of service of 4 - 6 years with professional training level among the university staff is quite weak. This implies that good organization management lies on the shoulders of the key leaders who enlighten the path to be followed by the staff.

Keywords: innovation, length of service, performance, professional training level, motivation

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Authors: Ghazala Yasmeen, Zahid Yousaf

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Frequent social media use has significantly changed people's life and communication styles during the last two decades. Social media use has multiple dimensions, and there are nuanced relationships between it and how it affects different societal subgroups. With the increased popularity and rapid growth of social networking sites, people are experiencing potential social media addiction, which causes severe mental health problems. How social media is dramatically influencing the lives and mental health of its users, and particularly of the students, creating psychological issues, e.g., isolation, depression, and anxiety, will be the primary objective of this study. This research will address the problems confronted by many students who are regular social media users and can undergo mental distress. This study aims to explore how social media use can lead to isolation, depression, and anxiety. This research will also investigate the effects of cyber-bullying on social, emotional, and psychological wellbeing. For this purpose, the researcher will use the survey technique as a method of inquiry. Ryff's theory of Psychological wellbeing will be used as a theoretical framework to explore the association between social media addiction and psychological effects among users. For data collection, the researcher will use the quantitative research method through a survey questionnaire from three universities in Pakistan from the public and private sectors. This study will imply a two-stage random sampling technique. At first, the researcher will select 20% of students from universities. In the second stage, 20% of students using different social networking sites will be chosen, and draw a representative sample from these will be. The intended study will use questionnaires comprising two portions. The first section will consist of social media engagement by the students, following impacts on their mental health and reported attitude towards psychological wellbeing. This study will spotlight the considerations of parents, educationists, and policymakers to take measures against the devastating effects of cyber-crimes on young adults.

Keywords: anxiety, depression, isolation, social media, wellbeing

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Authors: Rakan Hassan M. Alzahrani, Ziyad Alzahrani, Bader Bashrahil, Abdulrahman Elyasi, Abdullah a Ghaddaf, Rayan Alzahrani, Mohammed Alkathlan, Nawaf Alghamdi, Dakheelallah Almutairi

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Background: Corticosteroid irrigations, which regularly involve the off-label use of budesonide mixed with normal saline in high volume Sino-nasal irrigations, have been more commonly used in the management of post-operative chronic rhinosinusitis (CRS). Objective: This article attempted to measure the efficacy of post-operative budesonide nasal irrigation compared to normal saline-alone nasal irrigation in the management of chronic rhinosinusitis (CRS) through a systematic review and meta-analysis of randomized controlled trials (RCTs). Methods: The databases PubMed, Embase, and Cochrane Central Register of Controlled Trials were searched by two independent authors. Only RCTs comparing budesonide irrigation to normal saline alone irrigation for CRS with or without polyposis after functional endoscopic sinus surgery (FESS) were eligible. A random effect analysis model of the reported CRS-related quality of life (QOL) measures and the objective endoscopic assessment scales of the disease was done. Results: Only 6 RCTs met the eligibility criteria, with a total number of participants of 356. Compared to normal saline irrigation, budesonide nasal irrigation showed statically significant improvements in both the CRS-related quality of life (QOL) and the endoscopic findings (MD= -4.22 confidence interval [CI]: -5.63, -2.82 [P < 0.00001]), (SMD= -0.50 confidence interval [CI]: -0.93, -0.06 [P < 0.03]) respectively. Conclusion: Both intervention arms showed improvements in CRS-related QOL and endoscopic findings in post-FESS chronic rhinosinusitis with or without polyposis. However, budesonide irrigation seems to have a slight edge over conventional normal saline irrigation with no reported serious side effects, including hypothalamic-pituitary-adrenal (HPA) axis suppression.

Keywords: Budesonide, chronic rhinosinusitis, corticosteroids, nasal irrigation, normal saline

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Authors: Kholood A. Baron

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While radiologist numbers specialized in spine interventional procedures are limited in Kuwait, the number of patients demanding these procedures is increasing rapidly. Due to this high demand, the workload of radiologists is increasing, which might represent a radiation exposure concern. During these procedures, the doctor’s hands are in very close proximity to the main radiation beam/ if not within it. The aim of this study is to measure the radiation dose for radiologists during several interventional procedures for the spine. Methods: Two doctors carrying different workloads were included. (DR1) was performing procedures in the morning and afternoon shifts, while (DR2) was performing procedures in the morning shift only. Comparing the radiation exposures that the hand of each doctor is receiving will assess radiation safety and help to set up workload regulations for radiologists carrying a heavy schedule of such procedures. Entrance Skin Dose (ESD) was measured via TLD (ThermoLuminescent Dosimetry) placed at the right wrist of the radiologists. DR1 was covering the morning shift in one hospital (Mubarak Al-Kabeer Hospital) and the afternoon shift in another hospital (Dar Alshifa Hospital). The TLD chip was placed in his gloves during the 2 shifts for a whole week. Since DR2 was covering the morning shift only in Al Razi Hospital, he wore the TLD during the morning shift for a week. It is worth mentioning that DR1 was performing 4-5 spine procedures/day in the morning and the same number in the afternoon and DR2 was performing 5-7 procedures/day. This procedure was repeated for 4 consecutive weeks in order to calculate the ESD value that a hand receives in a month. Results: In general, radiation doses that the hand received in a week ranged from 0.12 to 1.12 mSv. The ESD values for DR1 for the four consecutive weeks were 1.12, 0.32, 0.83, 0.22 mSv, thus for a month (4 weeks), this equals 2.49 mSv and calculated to be 27.39 per year (11 months-since each radiologist have 45 days of leave in each year). For DR2, the weekly ESD values are 0.43, 0.74, 0.12, 0.61 mSv, and thus, for a month, this equals 1.9 mSv, and for a year, this equals 20.9 mSv /year. These values are below the standard level and way below the maximum limit of 500 mSv per year (set by ICRP = International Council of Radiation Protection). However, it is worth mentioning that DR1 was a senior consultant and hence needed less fluoro-time during each procedure. This is evident from the low ESD values of the second week (0.32) and the fourth week (0.22), even though he was performing nearly 10-12 procedures in a day /5 days a week. These values were lower or in the same range as those for DR2 (who was a junior consultant). This highlighted the importance of increasing the radiologist's skills and awareness of fluoroscopy time effect. In conclusion, the radiation dose that radiologists received during spine interventional radiology in our setting was below standard dose limits.

Keywords: radiation protection, interventional radiology dosimetry, ESD measurements, radiologist radiation exposure

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Authors: Funmilayo Sarah Eguakun, Peter Oluremi Adesoye

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One of the major problems being faced by human society is that the global temperature is believed to be rising due to human activity that releases carbon IV oxide (CO2) to the atmosphere. Carbon IV oxide is the most important greenhouse gas influencing global warming and possible climate change. With climate change becoming alarming, reducing CO2 in our atmosphere has become a primary goal of international efforts. Forest landsare major sink and could absorb large quantities of carbon if the trees are judiciously managed. The study aims at estimating the carbon sequestration capacity of Pinus caribaea (pine)and Tectona grandis (Teak) under the prevailing environmental conditions and exploring tree growth variables that influencesthe carbon sequestration capacity in Omo Forest Reserve, Ogun State, Nigeria. Improving forest management by manipulating growth characteristics that influences carbon sequestration could be an adaptive strategy of forestry to climate change. Random sampling was used to select Temporary Sample Plots (TSPs) in the study area from where complete enumeration of growth variables was carried out within the plots. The data collected were subjected to descriptive and correlational analyses. The results showed that average carbon stored by Pine and Teak are 994.4±188.3 Kg and 1350.7±180.6 Kg respectively. The difference in carbon stored in the species is significant enough to consider choice of species relevant in climate change adaptation strategy. Tree growth variables influence the capacity of the tree to sequester carbon. Height, diameter, volume, wood density and age are positively correlated to carbon sequestration. These tree growth variables could be manipulated by the forest manager as an adaptive strategy for climate change while plantations of high wood density speciescould be relevant for management strategy to increase carbon storage.

Keywords: adaptation, carbon sequestration, climate change, growth variables, wood density

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Authors: Elaine Wong

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This research protocol aims to explore and justify the need for nutrition and physical activity intervention to improve health outcomes among SME (Small Medium Enterprise) employees. It was found that the worksite is an ideal and convenient setting for employees to take charge of their health thru active participation in health programmes since they spent a great deal of time at their workplace. This study will examine the impact of both general or/and targeted health interventions in both SME and non-SME companies utilizing the Workplace Health Promotion (WHP) grant over a 12 months period and assessed the improvement in chronic health disease outcomes in Singapore. Random sampling of both non-SME and SME companies will be conducted to undergo health intervention and statistical packages such as Statistical Package for Social Science (SPSS) 25 will be used to examine the impact of both general and targeted interventions on employees who participate and those who do not participate in the intervention and their effects on blood glucose (BG), blood lipid, blood pressure (BP), body mass index (BMI), and body fat percentage. Using focus groups and interviews, the data results will be transcribed to investigate enablers and barriers to workplace health intervention revealed by employees and WHP coordinators that could explain the variation in the health screening results across the organisations. Dietary habits and physical activity levels of the employees participating and not participating in the intervention will be collected before and after intervention to assess any changes in their lifestyle practices. It makes economic sense to study the impact of these interventions on health screening outcomes across various organizations that are existing grant recipients to justify the sustainability of these programmes by the local government. Healthcare policy makers and employers can then tailor appropriate and relevant programmes to manage these escalating chronic health disease conditions which is integral to the competitiveness and productivity of the nation’s workforce.

Keywords: chronic diseases, health screening, nutrition and fitness intervention , workplace health

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Authors: Sri Yusnita Irda Sari, Deni Kurniadi Sunjaya, Ardini Saptaningsih Raksanagara

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Water is one of the fundamental basic needs for human life, particularly drinking water sources. Although water quality is getting better, fecal-contamination of water is still found around the world, especially in the slum area of mid-low income countries. Drinking water source contamination in urban slum dwellers increases the risk of water borne diseases. Low level of sanitation and poor drinking water supply known as risk factors for diarrhea, moreover bacteria-contaminated drinking water source is the main cause of diarrhea in developing countries. This study aimed to assess risk infection due to Fecal Coliform contamination in various drinking water sources in urban area by applying Quantitative Microbiological Risk Assessment (QMRA). A Cross-sectional survey was conducted in a period of August to October 2015. Water samples were taken by simple random sampling from households in Cikapundung river basin which was one of urban slum area in the center of Bandung city, Indonesia. About 379 water samples from 199 households and 15 common wells were tested. Half of the households used treated drinking water from water gallon mostly refill water gallon which was produced in drinking water refill station. Others used raw water sources which need treatment before consume as drinking water such as tap water, borehole, dug well and spring water source. Annual risk to get infection due to Fecal Coliform contamination from highest to lowest risk was dug well (1127.9 x 10-5), spring water (49.7 x 10-5), borehole (1.383 x 10-5) and tap water (1.121 x 10-5). Annual risk infection of refill drinking water was 1.577 x 10-5 which is comparable to borehole and tap water. Household water treatment and storage to make raw water sources drinkable is essential to prevent risk of water borne diseases. Strong regulation and intense monitoring of refill water gallon quality should be prioritized by the government; moreover, distribution of tap water should be more accessible and affordable especially in urban slum area.

Keywords: drinking water, quantitative microbiological risk assessment, slum, urban

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Authors: Pinna Beatrice., Laini Alex, Negro Giovanni, Burgazzi Gemma, Viaroli Pierluigi, Vezza Paolo

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Habitat models rarely consider macroinvertebrates as ecological targets in rivers. Available approaches mainly focus on single macroinvertebrate species, not addressing the ecological needs and functionality of the entire community. This research aimed to provide an approach to model the habitat of the macroinvertebrate community. The approach is based on the recently developed Flow-T index, together with a Random Forest (RF) regression, which is employed to apply the Flow-T index at the meso-habitat scale. Using different datasets gathered from both field data collection and 2D hydrodynamic simulations, the model has been calibrated in the Trebbia river (2019 campaign), and then validated in the Trebbia, Taro, and Enza rivers (2020 campaign). The three rivers are characterized by a braiding morphology, gravel riverbeds, and summer low flows. The RF model selected 12 mesohabitat descriptors as important for the macroinvertebrate community. These descriptors belong to different frequency classes of water depth, flow velocity, substrate grain size, and connectivity to the main river channel. The cross-validation R² coefficient (R²𝒸ᵥ) of the training dataset is 0.71 for the Trebbia River (2019), whereas the R² coefficient for the validation datasets (Trebbia, Taro, and Enza Rivers 2020) is 0.63. The agreement between the simulated results and the experimental data shows sufficient accuracy and reliability. The outcomes of the study reveal that the model can identify the ecological response of the macroinvertebrate community to possible flow regime alterations and to possible river morphological modifications. Lastly, the proposed approach allows extending the MesoHABSIM methodology, widely used for the fish habitat assessment, to a different ecological target community. Further applications of the approach can be related to flow design in both perennial and non-perennial rivers, including river reaches in which fish fauna is absent.

Keywords: ecological flows, macroinvertebrate community, mesohabitat, river habitat modeling

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Authors: Anjaly Joseph, Elezebeth Mathews

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Transportation and urban planning is the least recognised area for physical activity promotion in India, unlike developed regions. Identifying the preferred transportation modalities and factors associated with it is essential to address these lacunae. The objective of the study was to assess the prevalence of modes of transportation to work, and its correlates among working adults in Ernakulam District, Kerala. A cross sectional study was conducted among 350 working individuals in the age group of 18-60 years, selected through multi-staged stratified random sampling in Ernakulam district of Kerala. The inclusion criteria were working individuals 18-60 years, workplace at a distance of more than 1 km from the home and who worked five or more days a week. Pregnant women/women on maternity leave and drivers (taxi drivers, autorickshaw drivers, and lorry drivers) were excluded. An interview schedule was used to capture the modes of transportation namely, public, private and active transportation, socio demographic details, travel behaviour, anthropometric measurements and health status. Nearly two-thirds (64 percent) of them used private transportation to work, while active commuters were only 6.6 percent. The correlates identified for active commuting compared to other modes were low socio-economic status (OR=0.22, CI=0.5-0.85) and presence of a driving license (OR=4.95, CI= 1.59-15.45). The correlates identified for public transportation compared to private transportation were female gender (OR= 17.79, CI= 6.26-50.31), low income (OR=0.33, CI= 0.11-0.93), being unmarried (OR=5.19, CI=1.46-8.37), presence of no or only one private vehicle in the house (OR=4.23, CI=1.24-20.54) and presence of convenient public transportation facility to workplace (OR=3.97, CI= 1.66-9.47). The association between body mass index (BMI) and public transportation were explored and found that public transport users had lesser BMI than private commuters (OR=2.30, CI=1.23-4.29). Policies that encourage active and public transportation needs to be introduced such as discouraging private vehicle through taxes, introduction of convenient and safe public transportation facility, walking/cycling paths, and paid parking facility.

Keywords: active transportation, correlates, India, public transportation, transportation modes

Procedia PDF Downloads 148

Authors: Prakash M.N, Mahesh G, Muhammed Rafi K.M, Shiju P. Nair

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Introduction: In launch vehicle missions, Reaction Control thrusters are being used for the three-axis stabilization of the vehicle during the coasting phases. A pressure-fed propulsion system is used for the operation of these thrusters due to its less complexity. In liquid stages, these thrusters are designed to draw propellant from the same tank used for the main propulsion system. So in order to regulate the propellant flow rates of these thrusters, flow control orifices are used in feed lines. These orifices are calibrated separately as per the flow rate requirement of individual thrusters for the nominal operating conditions. In some missions, it was observed that the thrusters were operated at higher thrust than nominal. This point was addressed through a series of cold flow and hot tests carried out in-ground and this paper elaborates the details of the same. Discussion: In order to find out the exact reason for this phenomenon, two flight configuration thrusters were identified and hot tested in the ground with calibrated orifices and feed lines. During these tests, the chamber pressure, which is directly proportional to the thrust, is measured. In both cases, chamber pressures higher than the nominal by 0.32bar to 0.7bar were recorded. The increase in chamber pressure is due to an increase in the oxidizer flow rate of both the thrusters. Upon further investigation, it is observed that the calibration of the feed line is done with ambient pressure downstream. But in actual flight conditions, the orifices will be subjected to operate with 10 to 11bar pressure downstream. Due to this higher downstream pressure, the flow through the orifices increases and thereby, the thrusters operate with higher chamber pressure values. Conclusion: As part of further investigatory tests, two numbers of fresh thrusters were realized. Orifice tuning of these thrusters was carried out in three different ways. In the first trial, the orifice tuning was done by simulating 1bar pressure downstream. The second trial was done with the injector assembled downstream. In the third trial, the downstream pressure equal to the flight injection pressure was simulated downstream. Using these calibrated orifices, hot tests were carried out in simulated vacuum conditions. Chamber pressure and flow rate values were exactly matching with the prediction for the second and third trials. But for the first trial, the chamber pressure values obtained in the hot test were more than the prediction. This clearly shows that the flow is detached in the 1st trial and attached for the 2nd & 3rd trials. Hence, the error in tuning the flow control orifices is pinpointed as the reason for this higher chamber pressure observed in flight.

Keywords: reaction control thruster, propellent, orifice, chamber pressure

Procedia PDF Downloads 185

Authors: Gururaj Bhajantri

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Financial sector is the backbone of any economy and it plays a crucial role in the mobilisation and allocation of resources. One of the main objectives of financial sector is inclusive growth. The constituents of the financial sector are banks, and financial Institutions, which mobilise the resources from the surplus sector and channelize the same to the different needful sectors in the economy. Micro Small and the Medium Enterprises sector in India cover a wide range of economic activities. These enterprises are divided on the basis of investment on equipment. The micro enterprises are divided into manufacturing and services sector. Micro Service enterprises have investment limit up to ten lakhs on equipment. Hairdresser is one who not only cuts and shaves but also provides different types of hair cut, hairstyles, trimming, hair-dye, massage, manicure, pedicure, nail services, colouring, facial, makeup application, waxing, tanning and other beauty treatments etc., hairdressing salons provide these services with the help of equipment. They need investment on equipment not more than ten lakhs. Hence, they can be considered as Micro service enterprises. Hairdressing salons require more than Rs 2.50,000 to start a moderate salon. Moreover, hairdressers are unable to access the organised finance. Still these individuals access finance from money lenders with high rate of interest to lead life. The socio economic conditions of hairdressers are not known properly. Hence, the present study brings a light on the role of financial institutions in promoting hairdressing salons. The study also focuses the socio-economic background of individuals in hairdressings salons, problems faced by them. The present study is based on primary and secondary data. Primary data collected among hairdressing salons in Davangere city. Samples selected with the help of simple random sampling techniques. Collected data analysed and interpreted with the help of simple statistical tools.

Keywords: micro service enterprises, financial institutions, hairdressing salons, financial sector

Procedia PDF Downloads 184

Authors: Mai Alharthy, Agnes Shiel, Hynes Sinead

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Objectives: The objectives of the study are to translate and culturally adapt the RBMT-3 to be appropriate for use within an Arabic-speaking population and to achieve maximum equivalency between the translated and original versions and to evaluate the psychometric properties of the Arabic version of the RBMT-3. Participants' numbers are 16 (10 females and 6 males). All participants are bilingual speakers of Arabic and English, above 18 years old and with no current nor past memory impairment. Methods: The study was conducted in two stages: Translation and cultural adaptation stage: Forward and backward translations were completed by professional translators. Five out of the 14 RBMT-3 subtests required cultural adaptations. Half of the faces in the face recognition subtests were replaced with Arabic faces by a professional photographer. Pictures that are irrelevant to the Arabic culture in the picture recognition subtests were replaced. Names, story and orientations subtests were also adapted to suit the Arabic culture. An expert committee was formed to compare the translated and original versions and to advise on further changes required for test materials. Validation of the Arabic RBMT-3- pilot: 16 Participants were tested on version 1 of the English version and the two versions of the Arabic RBMT-3 ( counterbalanced ). The assessment period was 6 weeks long, with two weeks gap between tests. All assessments took place in a quiet room in the National University of Ireland Galway. Two qualified occupational therapists completed the assessments. Results: Wilcox signed-rank test was used to compare between subtest scores. Significant differences were found in the story, orientation and names subtests between the English and Arabic versions. No significant differences were found in subtests from both Arabic versions except for the story subtest. Conclusion: The story and orientation subtests should be revised by the expert committee members to make further adaptations. The rest of the Arabic RBMT-3 subtests are equivalent to the subtests of the English version. The psychometric properties of the Arabic RBMT-3 will be investigated in a larger Arabic-speaking sample in Saudi Arabia. The outcome of this research is to provide clinicians and researchers with a reliable tool to assess memory problems in Arabic speaking population.

Keywords: memory impairment, neuropsychological assessment, cultural adaptation, cognitive assessment

Procedia PDF Downloads 245

Authors: James Ladzekpo

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Background: The urgent need to identify new pharmacological targets for diabetes treatment and prevention has been amplified by the disease's extensive impact on individuals and healthcare systems. A deeper insight into the biological underpinnings of diabetes is crucial for the creation of therapeutic strategies aimed at these biological processes. Current predictive models based on genetic variations fall short of accurately forecasting diabetes. Objectives: Our study aims to pinpoint key epigenetic factors that predispose individuals to diabetes. These factors will inform the development of an advanced predictive model that estimates diabetes risk from genetic profiles, utilizing state-of-the-art statistical and data mining methods. Methodology: We have implemented a recursive feature elimination with cross-validation using the support vector machine (SVM) approach for refined feature selection. Building on this, we developed six machine learning models, including logistic regression, k-Nearest Neighbors (k-NN), Naive Bayes, Random Forest, Gradient Boosting, and Multilayer Perceptron Neural Network, to evaluate their performance. Findings: The Gradient Boosting Classifier excelled, achieving a median recall of 92.17% and outstanding metrics such as area under the receiver operating characteristics curve (AUC) with a median of 68%, alongside median accuracy and precision scores of 76%. Through our machine learning analysis, we identified 31 genes significantly associated with diabetes traits, highlighting their potential as biomarkers and targets for diabetes management strategies. Conclusion: Particularly noteworthy were the Gradient Boosting Classifier and Multilayer Perceptron Neural Network, which demonstrated potential in diabetes outcome prediction. We recommend future investigations to incorporate larger cohorts and a wider array of predictive variables to enhance the models' predictive capabilities.

Keywords: diabetes, machine learning, prediction, biomarkers

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Authors: Sokkhey Phauk, Takeo Okazaki

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The challenging task in educational institutions is to maximize the high performance of students and minimize the failure rate of poor-performing students. An effective method to leverage this task is to know student learning patterns with highly influencing factors and get an early prediction of student learning outcomes at the timely stage for setting up policies for improvement. Educational data mining (EDM) is an emerging disciplinary field of data mining, statistics, and machine learning concerned with extracting useful knowledge and information for the sake of improvement and development in the education environment. The study is of this work is to propose techniques in EDM and integrate it into a web-based system for predicting poor-performing students. A comparative study of prediction models is conducted. Subsequently, high performing models are developed to get higher performance. The hybrid random forest (Hybrid RF) produces the most successful classification. For the context of intervention and improving the learning outcomes, a feature selection method MICHI, which is the combination of mutual information (MI) and chi-square (CHI) algorithms based on the ranked feature scores, is introduced to select a dominant feature set that improves the performance of prediction and uses the obtained dominant set as information for intervention. By using the proposed techniques of EDM, an academic performance prediction system (APPS) is subsequently developed for educational stockholders to get an early prediction of student learning outcomes for timely intervention. Experimental outcomes and evaluation surveys report the effectiveness and usefulness of the developed system. The system is used to help educational stakeholders and related individuals for intervening and improving student performance.

Keywords: academic performance prediction system, educational data mining, dominant factors, feature selection method, prediction model, student performance

Procedia PDF Downloads 90

Authors: Fulufhelo Amanda Doboro, Kgomotso Sebeko, Stephen Njiro, Moritz Van Vuuren

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Ovine herpesvirus 2 (OvHV-2) genome obtained from the lymphopblastoid cell line of a BJ1035 cow was recently sequenced in the United States of America (USA). Information on the sequences of OvHV-2 genes obtained from South African strains from bovine or other African countries and molecular characterization of OvHV-2 is not documented. Present investigation provides information on the nucleotide and derived amino acid sequences and genetic diversity of Ov 7, Ov 8 ex2, ORF 27 and ORF 73 genes, of these genes from OvHV-2 strains circulating in South Africa. Gene-specific primers were designed and used for PCR of DNA extracted from 42 bovine blood samples that previously tested positive for OvHV-2. The expected PCR products of 495 bp, 253 bp, 890 bp and 1632 bp respectively for Ov 7, Ov 8 ex2, ORF 27 and ORF 73 genes were sequenced and multiple sequence analysis done on the selected regions of the sequenced PCR products. Two genotypes for ORF 27 and ORF 73 gene sequences, and three genotypes for Ov 7 and Ov 8 ex2 gene sequences were identified, and similar groupings for the derived amino acid sequences were obtained for each gene. Nucleotide and amino acid sequence variations that led to the identification of the different genotypes included SNPs, deletions and insertions. Sequence analysis of Ov 7 and ORF 27 genes revealed variations that distinguished between sequences from SA and reference OvHV-2 strains. The implication of geographic origin among SA sequences was difficult to evaluate because of random distribution of genotypes in the different provinces, for each gene. However, socio-economic factors such as migration of people with animals, or transportation of animals for agricultural or business use from one province to another are most likely to be responsible for this observation. The sequence variations observed in this study have no impact on the antibody binding activities of glycoproteins encoded by Ov 7, Ov 8 ex2 and ORF 27 genes, as determined by prediction of the presence of B cell epitopes using BepiPred 1.0. The findings of this study will be used for selection of gene candidates for the development of diagnostic assays and vaccine development as well.

Keywords: amino acid, genetic diversity, genes, nucleotide

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Authors: Ebraheem Al-Jouri, Youssef Abu-Ahmad, Ramasamy Srinivasan

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The parasitoid, Diadegma semiclausum (Hymenoptera: Ichneumonidae) is one of the most effective exotic parasitoids of diamondback moth (DBM), Plutella xylostella in the lowland areas of Homs, Syria. Molecular evolution studies are useful tools to shed light on the molecular bases of insect geographical spread and adaptation to new hosts and environment and for designing better control strategies. In this study, molecular evolution analysis was performed based on the 42 nuclear internal transcribed spacer-2 (ITS2) sequences representing the D. semiclausum and eight other Diadegma spp. from Syria and worldwide. Possible recombination events were identified by RDP4 program. Four potential recombinants of the American D. insulare and D. fenestrale (Jeju) were detected. After detecting and removing recombinant sequences, the ratio of non-synonymous (dN) to synonymous (dS) substitutions per site (dN/dS=ɷ) has been used to identify codon positions involved in adaptive processes. Bayesian techniques were applied to detect selective pressures at a codon level by using five different approaches including: fixed effects likelihood (FEL), internal fixed effects likelihood (IFEL), random effects method (REL), mixed effects model of evolution (MEME) and Program analysis of maximum liklehood (PAML). Among the 40 positively selected amino acids (aa) that differed significantly between clades of Diadegma species, three aa under positive selection were only identified in D. semiclausum. Additionally, all D. semiclausum branches tree were highly found under episodic diversifying selection (EDS) at p≤0.05. Our study provide evidence that both recombination and positive selection have contributed to the molecular diversity of Diadegma spp. and highlights the significant contribution of D. semiclausum in adaptive evolution and influence the fitness in the DBM parasitoid.

Keywords: diadegma sp, DBM, ITS2, phylogeny, recombination, dN/dS, evolution, positive selection

Procedia PDF Downloads 398

Authors: Richard Ren

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Air pollution is a serious danger to international well-being and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.

Keywords: air quality prediction, air pollution, artificial intelligence, machine learning algorithms

Procedia PDF Downloads 100

Authors: Van Truong Pham

Abstract:

Background: Self-management was described as a potential strategy for blood pressure control in patients with hypertension. However, the effects of self-management interventions on blood pressure, self-efficacy, medication adherence, and body mass index (BMI) in older adults with hypertension have not been systematically evaluated. We evaluated the effects of self-management interventions on systolic blood pressure (SBP) and diastolic blood pressure (DBP), self-efficacy, medication adherence, and BMI in hypertensive older adults. Methods: We followed the recommended guidelines of preferred reporting items for systematic reviews and meta-analyses. Searches in electronic databases including CINAHL, Cochrane Library, Embase, Ovid-Medline, PubMed, Scopus, Web of Science, and other sources were performed to include all relevant studies up to April 2019. Studies selection, data extraction, and quality assessment were performed by two reviewers independently. We summarized intervention effects as Hedges' g values and 95% confidence intervals (CI) using a random-effects model. Data were analyzed using Comprehensive Meta-Analysis software 2.0. Results: Twelve randomized controlled trials met our inclusion criteria. The results revealed that self-management interventions significantly improved blood pressure control, self-efficacy, medication adherence, whereas the effect of self-management on BMI was not significant in older adult patients with hypertension. The following Hedges' g (effect size) values were obtained: SBP, -0.34 (95% CI, -0.51 to -0.17, p < 0.001); DBP, -0.18 (95% CI, -0.30 to -0.05, p < 0.001); self-efficacy, 0.93 (95%CI, 0.50 to 1.36, p < 0.001); medication adherence, 1.72 (95%CI, 0.44 to 3.00, p=0.008); and BMI, -0.57 (95%CI, -1.62 to 0.48, p = 0.286). Conclusions: Self-management interventions significantly improved blood pressure control, self-efficacy, and medication adherence. However, the effects of self-management on obesity control were not supported by the evidence. Healthcare providers should implement self-management interventions to strengthen patients' role in managing their health care.

Keywords: self-management, meta-analysis, blood pressure control, self-efficacy, medication adherence, body mass index

Procedia PDF Downloads 108

Authors: Asena Biber, Ates Gul Ergun, Seda Bulut

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Based on the literature, there are large numbers of studies investigating the relationship between culture and leadership effectiveness. Although giving effective speeches is vital characteristic for a leader to be perceived as effective, to our knowledge, there is no research study the determinants of perceived effective leader speech. The aim of this study is to find the effects of both culture and voice pitch on perceptions of leader's speech effectiveness. Our hypothesis is that people from high power distance countries will perceive leaders' speech effective when the leader's voice pitch is high, comparing with people from relatively low power distance countries. The participants of the study were 36 undergraduate students (12 Pakistanis, 12 Nigerians, and 12 Turks) who are studying in Turkey. National power distance scores of Nigerians ranked as first, Turks ranked as second and Pakistanis ranked as third. There are two independent variables in this study; three nationality groups that representing three levels of power distance and voice pitch of the leader which is manipulated as high and low levels. Researchers prepared an audio to manipulate high and low conditions of voice pitch. A professional whose native language is English read the predetermined speech in high and low voice pitch conditions. Voice pitch was measured using Hertz (Hz) and Decibel (dB). Each nationality group (Pakistan, Nigeria, and Turkey) were divided into groups of six students who listened to either the low or high pitch conditions in the cubicles of the laboratory. It was expected from participants to listen to the audio and fill in the questionnaire which was measuring the leadership effectiveness on a response scale ranging from 1 to 5. To determine the effects of nationality and voice pitch on perceived effectiveness of leader' voice pitch, 3 (Pakistani, Nigerian, and Turk) x 2 (low voice pitch and high voice pitch) two way between subjects analysis of variances was carried out. The results indicated that there was no significant main effect of voice pitch and interaction effect on perceived effectiveness of the leader’s voice pitch. However, there was a significant main effect of nationality on perceived effectiveness of the leader's voice pitch. Based on the results of Turkey’s HSD post-hoc test, only the perceived effectiveness of the leader's speech difference between Pakistanis and Nigerians was statistically significant. The results show that the hypothesis of this study was not supported. As limitations of the study, it is of importance to mention that the sample size should be bigger. Also, the language of the questionnaire and speech should be in the participant’s native language in further studies.

Keywords: culture, leadership effectiveness, power distance, voice pitch

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Authors: Leena Inamdar, David Allen, Sushma Acquilla, James Gore

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Health systems globally are facing increasingly complex challenges. Emerging health threats, changing population demographics and increasing health inequalities, globalisation, economic constraints on government spending are some of the most critical ones. These challenges demand not only innovative funding and cross-sectoral approaches, but also require a multidisciplinary public health workforce equipped with skills and expertise to meet the future challenges of the Sustainable Development Goals (SDGs). We aim to outline an approach to assessing the feasibility of establishing a competency-based public health training at a country level. Although the SDGs provide an enabling impetus for change and promote positive developments, public health training and education still lag behind. Large gaps are apparent in both the numbers of trained professionals and the options for high quality training. Public health training in most Low-Middle Income Countries is still largely characterized by a traditional and limited public health focus. There is a pressing need to review and develop core and emerging competences for a well-equipped workforce fit for the future. This includes the important role of national Health and Human Resource Ministries in determining these competences. Public health has long been recognised as a multidisciplinary field, with need for professionals from a wider range of disciplines such as management, health promotion, health economics, law. Leadership and communication skills are also critical to achieve the successes in meeting public health outcomes. Such skills and competences need to be translated into competency-based training and education, to prepare current public health professionals with the skills required in today’s competitive job market. Integration of academic and service based public-health training, flexible accredited programmes to support existing mid-career professionals, continuous professional development need to be explored. In the current global climate of austerity and increasing demands on health systems, the need for stepping up public health training and education is more important than ever. By using a case study, we demonstrate the process of assessing the in-county capacity to establish a competency based public health training programme that will help to develop a stronger, more versatile and much needed public health workforce to meet the SDGs.

Keywords: public health training, competency-based, assessment, SDGs

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Authors: Adedayo Racheal Agbonna

Abstract:

The rising level of graduate unemployment in Nigeria has brought about the introduction of entrepreneurship education as a career option for self–reliance and self-employment. Sequel to this, it is important to have an understanding of the determining factors of entrepreneurial intention. Therefore this research empirically investigated the influence of entrepreneurship education on entrepreneurial intention of undergraduate students of selected universities in Ogun State, Nigeria. The study is significant to researchers, university policy makers, and the government. Survey research design was adopted in the study. The population consisted of 17,659 final year undergraduate students universities in Ogun State. The study adopted stratified and random sampling technique. The table of sample size determination was used to determine the sample size for this study at 95% confidence level and 5% margin error to arrive at a sample size of 1877 respondents. The elements of population were 400 level students of the selected universities. A structured questionnaire titled 'Entrepreneurship Education and students’ Entrepreneurial intention' was administered. The result of the reliability test had the following values 0.716, 0.907 and 0.949 for infrastructure, perceived university support, and entrepreneurial intention respectively. In the same vein, from the construct validity test, the following values were obtained 0.711, 0.663 and 0.759 for infrastructure, perceived university support and entrepreneurial intention respectively. Findings of this study revealed that each of the entrepreneurship education variables significantly affected intention University infrastructure B= -1.200, R²=0.679, F (₁,₁₈₇₅) = 3958.345, P < 0.05) Perceived University Support B= -1.027, R²=0.502, F(₁,₁₈₇₅) = 1924.612, P < 0.05). The perception of respondents in public university and private university on entrepreneurship education have a statistically significant difference [F(₁,₁₈₇₅) = 134.614, p < 0.05) α F(₁,₁₈₇₅) = 363.439]. The study concluded that entrepreneurship education positively influenced entrepreneurial intention of undergraduate students in Ogun State, Nigeria. Also, university infrastructure and perceived university support have negative and significant effect on entrepreneurial intention. The study recommended that to promote entrepreneurial intention of university undergraduate students, infrastructures and the university support that can arouse entrepreneurial intention of students should be put in place.

Keywords: entrepreneurship education, entrepreneurial intention, perceived university support, university infrastructure

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Authors: S. Archsana, Vajira Balasuriya

Abstract:

In Trincomalee of Sri Lanka, a post-conflict area, resettlement projects and policy initiatives are taking place to improve the wealth of the rural communities through promoting economic activities by way of encouraging the rural women to opt to commence and operate Micro and Small Scale (MSS) businesses. This study attempts to identify the manner in which the institutional environment could facilitate these MSS businesses owned and operated by women in the rural environment. The respondents of this study are the beneficiaries of the Divi Neguma Development Training Program (DNDTP); a project designed to aid women owned MSS businesses, in Trincomalee district. 96 women business operators, who had obtained financing facilities from the DNDTP, are taken as the sample based on fixed interval random sampling method. The study reveals that primary challenges encountered by 82% of the women business operators are lack of initial capital followed by 71% initial market finding and 35% access to technology. The low level of education and language barriers are the constraints in accessing support agencies/service providers. Institutional support; specifically management and marketing services, have a significant relationship with wealth augmentation. Institutional support at the setting-up stage of businesses are thin whereas terms and conditions of the finance facilities are perceived as ‘too challenging’. Although diversification enhances wealth of the rural women business operators, assistance from the institutional framework to prepare financial reports that are required for business expansion is skinny. The study further reveals that institutional support is very much weak in terms of providing access to new technology and identifying new market networks. A mechanism that could facilitate the institutional framework to support the rural women business operators to access new technology and untapped market segments, and assistance in preparation of legal and financial documentation is recommended.

Keywords: business facilitation, institutional support, rural women business operators, wealth augmentation

Procedia PDF Downloads 418