Search results for: weighted%20visual%20words

Authors: Neil Singla, Derek Muse, Karen DiDonato, Pamela Palmer

Abstract:

Introduction: Pain is the most common reason people visit emergency rooms. Studies indicate however, that Emergency Department (ED) physicians often do not provide adequate analgesia to their patients as a result of gender and age bias, opiophobia and insufficient knowledge of and formal training in acute pain management. Novel classes of analgesics have recently been introduced, but many patients suffer from acute pain in settings where the availability of intravenous (IV) access may be limited, so there remains a clinical need for rapid-acting, potent analgesics that do not require an invasive route of delivery. A sublingual sufentanil tablet (SST), dispensed using a single-dose applicator, is in development for treatment of moderate-to-severe acute pain in a medically-supervised setting. Objective: The primary objective of this study was to demonstrate the repeat-dose efficacy, safety and tolerability of sufentanil 20 mcg and 30 mcg sublingual tablets compared to placebo for the management of acute pain as determined by the time-weighted sum of pain intensity differences (SPID) to baseline over the 12-hour study period (SPID12). Key secondary efficacy variables included SPID over the first hour (SPID1), Total pain relief over the 12-hour study period (TOTPAR12), time to perceived pain relief (PR) and time to meaningful PR. Safety variables consisted of adverse events (AE), vital signs, oxygen saturation and early termination. Methods: In this Phase 2, double-blind, dose-finding study, an equal number of male and female patients were randomly assigned in a 2:2:1 ratio to SST 20 mcg, SS 30 mcg or placebo, respectively, following bunionectomy. Study drug was dosed as needed, but not more frequently than hourly. Rescue medication was available as needed. The primary endpoint was the Summed Pain Intensity Difference to baseline over 12h (SPIDI2). Safety was assessed by continuous oxygen saturation monitoring and adverse event reporting. Results: 101 patients (51 Male/50 Female) were randomized, 100 received study treatment (intent-to-treat [ITT] population), and 91 completed the study. Reasons for early discontinuation were lack of efficacy (6), adverse events (2) and drug-dosing error (1). Mean age was 42.5 years. For the ITT population, SST 30 mcg was superior to placebo (p=0.003) for the SPID12. SPID12 scores in the active groups were superior for both male (ANOVA overall p-value =0.038) and female (ANOVA overall p-value=0.005) patients. Statistically significant differences in favour of sublingual sufentanil were also observed between the SST 30mcg and placebo group for SPID1(p<0.001), TOTPAR12(p=0.002), time to perceived PR (p=0.023) and time to meaningful PR (p=0.010). Nausea, vomiting and somnolence were more frequent in the sufentanil groups but there were no significant differences between treatment arms for the proportion of patients who prematurely terminated due to AE or inadequate analgesia. Conclusions: Sufentanil tablets dispensed sublingually using a single-dose applicator is in development for treatment of patients with moderate-to-severe acute pain in a medically-supervised setting where immediate IV access is limited. When administered sublingually, sufentanil’s pharmacokinetic profile and non-invasive delivery makes it a useful alternative to IM or IV dosing.

Keywords: acute pain, pain management, sublingual, sufentanil

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Authors: Rawan Hakawati, Beatrice Smyth, David Rooney, Geoffrey McCullough

Abstract:

Targets have been set in the EU to increase the share of renewable energy consumption to 20% by 2020, but developments have not occurred evenly across the member states. Northern Ireland is almost 90% dependent on imported fossil fuels. With such high energy dependency, Northern Ireland is particularly susceptible to the security of supply issues. Linked to fossil fuels are greenhouse gas emissions, and the EU plans to reduce emissions by 20% by 2020. The use of indigenously produced biomass could reduce both greenhouse gas emissions and external energy dependence. With a wide range of both crop and waste feedstock potentially available in Northern Ireland, anaerobic digestion has been put forward as a possible solution for renewable energy production, waste management, and greenhouse gas reduction. Not all feedstock, however, is the same, and an understanding of feedstock suitability is important for both plant operators and policy makers. The aim of this paper is to investigate biomass suitability for anaerobic digestion in Northern Ireland. It is also important that decisions are based on solid scientific evidence. For this reason, the methodology used is multi-criteria decision matrix analysis which takes multiple criteria into account simultaneously and ranks alternatives accordingly. The model uses the weighted sum method (which follows the Entropy Method to measure uncertainty using probability theory) to decide on weights. The Topsis method is utilized to carry out the mathematical analysis to provide the final scores. Feedstock that is currently available in Northern Ireland was classified into two categories: wastes (manure, sewage sludge and food waste) and energy crops, specifically grass silage. To select the most suitable feedstock, methane yield, feedstock availability, feedstock production cost, biogas production, calorific value, produced kilowatt-hours, dry matter content, and carbon to nitrogen ratio were assessed. The highest weight (0.249) corresponded to production cost reflecting a variation of £41 gate fee to 22£/tonne cost. The weights calculated found that grass silage was the most suitable feedstock. A sensitivity analysis was then conducted to investigate the impact of weights. The analysis used the Pugh Matrix Method which relies upon The Analytical Hierarchy Process and pairwise comparisons to determine a weighting for each criterion. The results showed that the highest weight (0.193) corresponded to biogas production indicating that grass silage and manure are the most suitable feedstock. Introducing co-digestion of two or more substrates can boost the biogas yield due to a synergistic effect induced by the feedstock to favor positive biological interactions. A further benefit of co-digesting manure is that the anaerobic digestion process also acts as a waste management strategy. From the research, it was concluded that energy from agricultural biomass is highly advantageous in Northern Ireland because it would increase the country's production of renewable energy, manage waste production, and would limit the production of greenhouse gases (current contribution from agriculture sector is 26%). Decision-making methods based on scientific evidence aid policy makers in classifying multiple criteria in a logical mathematical manner in order to reach a resolution.

Keywords: anaerobic digestion, biomass as feedstock, decision matrix, renewable energy

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Authors: Abdulaziz Alakeel, Abdulrahman Alomair, Mohammed Fouda

Abstract:

Introduction: Methotrexate (MTX) is an antimetabolite used to treat multiple conditions, including neoplastic diseases, severe psoriasis, and rheumatoid arthritis. Skin cancer is the out-of-control growth of abnormal cells in the epidermis, the outermost skin layer, caused by unrepaired DNA damage that triggers mutations. These mutations lead the skin cells to multiply rapidly and form malignant tumors. The aim of this review is to evaluate the risk of skin cancer associated with the use of methotrexate and to suggest regulatory recommendations if required. Methodology: Signal Detection team at Saudi Food and Drug Authority (SFDA) performed a safety review using National Pharmacovigilance Center (NPC) database as well as the World Health Organization (WHO) VigiBase, alongside with literature screening to retrieve related information for assessing the causality between skin cancer and methotrexate. The search conducted in July 2020. Results: Four published articles support the association seen while searching in literature, a recent randomized control trial published in 2020 revealed a statistically significant increase in skin cancer among MTX users. Another study mentioned methotrexate increases the risk of non-melanoma skin cancer when used in combination with immunosuppressant and biologic agents. In addition, the incidence of melanoma for methotrexate users was 3-fold more than the general population in a cohort study of rheumatoid arthritis patients. The last article estimated the risk of cutaneous malignant melanoma (CMM) in a cohort study shows a statistically significant risk increase for CMM was observed in MTX exposed patients. The WHO database (VigiBase) searched for individual case safety reports (ICSRs) reported for “Skin Cancer” and 'Methotrexate' use, which yielded 121 ICSRs. The initial review revealed that 106 cases are insufficiently documented for proper medical assessment. However, the remaining fifteen cases have extensively evaluated by applying the WHO criteria of causality assessment. As a result, 30 percent of the cases showed that MTX could possibly cause skin cancer; five cases provide unlikely association and five un-assessable cases due to lack of information. The Saudi NPC database searched to retrieve any reported cases for the combined terms methotrexate/skin cancer; however, no local cases reported up to date. The data mining of the observed and the expected reporting rate for drug/adverse drug reaction pair is estimated using information component (IC), a tool developed by the WHO Uppsala Monitoring Centre to measure the reporting ratio. Positive IC reflects higher statistical association, while negative values translated as a less statistical association, considering the null value equal to zero. Results showed that a combination of 'Methotrexate' and 'Skin cancer' observed more than expected when compared to other medications in the WHO database (IC value is 1.2). Conclusion: The weighted cumulative pieces of evidence identified from global cases, data mining, and published literature are sufficient to support a causal association between the risk of skin cancer and methotrexate. Therefore, health care professionals should be aware of this possible risk and may consider monitoring any signs or symptoms of skin cancer in patients treated with methotrexate.

Keywords: methotrexate, skin cancer, signal detection, pharmacovigilance

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Authors: Eleni Akritopoulou, Katerina Topouzoglou

Abstract:

The last 20 years marine debris has been identified as one of the main marine pollution sources caused by anthropogenic activities. Plastics has reached the farthest marine areas of the planet affecting all marine trophic levels including the, recently discovered, amphipoda Eurythenes plasticus inhabiting Mariana Trench to large cetaceans, marine reptiles and sea birds causing immunodeficiency disorders, deteriorating health and death overtime. For the time period 2016-20, in the framework of the national initiative ‘Keep Aegean Blue”, All for Blue team has been collecting marine debris (coastline and underwater) following a modified in situ MEDSEALITTER monitoring protocol from eight Greek islands. After collection, marine debris was weighted, sorted and categorised according to material; plastic (PL), glass (G), metal (M), wood (W), rubber (R), cloth (CL), paper (P), mixed (MX). The goal of the project included the documentation of marine debris sources, human trends, waste management and public marine environmental awareness. Waste management was focused on plastics recycling and utilisation into daily useful products. This research is focused on the island of Mykonos due to its continuous touristic activity and lack of scientific information. In overall, a field work area of 1.832.856 m2 was cleaned up yielding 5092 kg of marine debris. The preliminary results indicated PL as main source of marine debris (62,8%) followed by M (15,5%), GL (13,2%) and MX (2,8%). Main items found were fishing tools (lines, nets), disposable cutlery, cups and straws, cigarette butts, flip flops and other items like plastic boat compartments. In collaboration with a local company for plastic management and the Circular Economy and Eco Innovation Institute (Sweden), all plastic debris was recycled. Granulation process was applied transforming plastic into building materials used for refugees’ houses, litter bins bought by municipalities and schools and, other items like shower components. In terms of volunteering and attendance in public awareness seminars, there was a raise of interest by 63% from different age ranges and professions. Regardless, the research being fairly new for Mykonos island and logistics issues potentially affected systemic sampling, it appeared that plastic debris is the main littering source attributed, possibly to the intense touristic activity of the island all year around. However, marine environmental awareness activities were pointed out to be an effective tool in forming public perception against marine debris and, alter the daily habits of local society. Since the beginning of this project, three new local environmental teams were formed against marine pollution supported by the local authorities and stakeholders. The continuous need and request for the production of items made by recycled marine debris appeared to be beneficial socio-economically to the local community and actions are taken to expand the project nationally. Finally, as an ongoing project and whilst, new scientific information is collected, further funding and research is needed.

Keywords: Greece, marine debris, marine environmental awareness, Mykonos island, plastics debris, plastic granulation, recycled plastic, tourism, waste management

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Authors: Chuyuan Wang, Nayan Khare, Lily Villa, Patricia Solis, Elizabeth A. Wentz

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Maricopa County, Arizona, has a semi-arid hot desert climate that is one of the hottest regions in the United States. The exacerbated urban heat island (UHI) effect caused by rapid urbanization has made the urban area even hotter than the rural surroundings. The Phoenix metropolitan area experiences extremely high temperatures in the summer from June to September that can reach the daily highest of 120 °F (48.9 °C). Morbidity and mortality due to the environmental heat is, therefore, a significant public health issue in Maricopa County, especially because it is largely preventable. Public records from the Maricopa County Department of Public Health (MCDPH) revealed that between 2012 and 2016, there were 10,825 incidents of heat-related morbidity incidents, 267 outdoor environmental heat deaths, and 173 indoor heat-related deaths. A lot of research has examined heat-related death and its contributing factors around the world, but little has been done regarding heat-related morbidity issues, especially for regions that are naturally hot in the summer. The objective of this study is to examine the demographic, socio-economic, housing, and environmental factors that contribute to heat-related morbidity in Maricopa County. We obtained heat-related morbidity data between 2012 and 2016 at census tract level from MCDPH. Demographic, socio-economic, and housing variables were derived using 2012-2016 American Community Survey 5-year estimate from the U.S. Census. Remotely sensed Landsat 7 ETM+ and Landsat 8 OLI satellite images and Level-1 products were acquired for all the summer months (June to September) from 2012 and 2016. The National Land Cover Database (NLCD) 2016 percent tree canopy and percent developed imperviousness data were obtained from the U.S. Geological Survey (USGS). We used ordinary least squares (OLS) regression analysis to examine the empirical relationship between all the independent variables and heat-related morbidity rate. Results showed that higher morbidity rates are found in census tracts with higher values in population aged 65 and older, population under poverty, disability, no vehicle ownership, white non-Hispanic, population with less than high school degree, land surface temperature, and surface reflectance, but lower values in normalized difference vegetation index (NDVI) and housing occupancy. The regression model can be used to explain up to 59.4% of total variation of heat-related morbidity in Maricopa County. The multiscale geographically weighted regression (MGWR) technique was then used to examine the spatially varying relationships between heat-related morbidity rate and all the significant independent variables. The R-squared value of the MGWR model increased to 0.691, that shows a significant improvement in goodness-of-fit than the global OLS model, which means that spatial heterogeneity of some independent variables is another important factor that influences the relationship with heat-related morbidity in Maricopa County. Among these variables, population aged 65 and older, the Hispanic population, disability, vehicle ownership, and housing occupancy have much stronger local effects than other variables.

Keywords: census, empirical modeling, heat-related morbidity, spatial analysis

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Authors: Aishwarya Venkat, Anastasia Marshak, Ryan B. Simpson, Elena N. Naumova

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Livestock ownership is simultaneously linked to improved nutritional status through increased availability of animal-source protein, and increased risk of enteric infections through higher exposure to contaminated water sources. Agrarian and agro-pastoral households, especially those with cattle, goats, and sheep, are highly dependent on seasonally various environmental conditions, which directly impact nutrition and health. This study explores global spatiotemporally explicit evidence regarding the relationship between livestock ownership, enteric infections, and malnutrition. Seasonal and cyclical fluctuations, as well as mediating effects, are further examined to elucidate health and nutrition outcomes of individual and communal livestock ownership. The US Agency for International Development’s Demographic and Health Surveys (DHS) and the United Nations International Children's Emergency Fund’s Multi-Indicator Cluster Surveys (MICS) provide valuable sources of household-level information on anthropometry, asset ownership, and disease outcomes. These data are especially important in data-sparse regions, where surveys may only be conducted in the aftermath of emergencies. Child-level disease history, anthropometry, and household-level asset ownership information have been collected since DHS-V (2003-present) and MICS-III (2005-present). This analysis combines over 15 years of survey data from DHS and MICS to study 2,466,257 children under age five from 82 countries. Subnational (administrative level 1) measures of diarrhea prevalence, mean livestock ownership by type, mean and median anthropometric measures (height for age, weight for age, and weight for height) were investigated. Effects of several environmental, market, community, and household-level determinants were studied. Such covariates included precipitation, temperature, vegetation, the market price of staple cereals and animal source proteins, conflict events, livelihood zones, wealth indices and access to water, sanitation, hygiene, and public health services. Children aged 0 – 6 months, 6 months – 2 years, and 2 – 5 years of age were compared separately. All observations were standardized to interview day of year, and administrative units were harmonized for consistent comparisons over time. Geographically weighted regressions were constructed for each outcome and subnational unit. Preliminary results demonstrate the importance of accounting for seasonality in concurrent assessments of malnutrition and enteric infections. Household assets, including livestock, often determine the intensity of these outcomes. In many regions, livestock ownership affects seasonal fluxes in malnutrition and enteric infections, which are also directly affected by environmental and local factors. Regression analysis demonstrates the spatiotemporal variability in nutrition outcomes due to a variety of causal factors. This analysis presents a synthesis of evidence from global survey data on the interrelationship between enteric infections, malnutrition, and livestock. These results provide a starting point for locally appropriate interventions designed to address this nexus in a timely manner and simultaneously improve health, nutrition, and livelihoods.

Keywords: diarrhea, enteric infections, households, livestock, malnutrition, seasonality

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Authors: Simon J. Wilde, David M. Herold, Michael J. Bryant

Abstract:

Social media networks have become the hotbed for advertising activities due mainly to their increasing consumer/user base and, secondly, owing to the ability of marketers to accurately measure ad exposure and consumer-based insights on such networks. More than half of the world’s population (4.8 billion) now uses social media (60%), with 150 million new users having come online within the last 12 months (to June 2022). As the use of social media networks by users grows, key business strategies used for interacting with these potential customers have matured, especially social media advertising. Unlike other traditional media outlets, social media advertising is highly interactive and digital channel specific. Social media advertisements are clearly targetable, providing marketers with an extremely powerful marketing tool. Yet despite the measurable benefits afforded to businesses engaged in social media advertising, recent controversies (such as the relationship between Facebook and Cambridge Analytica in 2018) have only heightened the role trust and privacy play within these social media networks. Using a web-based quantitative survey instrument, survey participants were recruited via a reputable online panel survey site. Respondents to the survey represented social media users from all states and territories within Australia. Completed responses were received from a total of 258 social media users. Survey respondents represented all core age demographic groupings, including Gen Z/Millennials (18-45 years = 60.5% of respondents) and Gen X/Boomers (46-66+ years = 39.5% of respondents). An adapted ADTRUST scale, using a 20 item 7-point Likert scale, measured trust in social media advertising. The ADTRUST scale has been shown to be a valid measure of trust in advertising within traditional media, such as broadcast media and print media, and, more recently, the Internet (as a broader platform). The adapted scale was validated through exploratory factor analysis (EFA), resulting in a three-factor solution. These three factors were named reliability, usefulness and affect, and the willingness to rely on. Factor scores (weighted measures) were then calculated for these factors. Factor scores are estimates of the scores survey participants would have received on each of the factors had they been measured directly, with the following results recorded (Reliability = 4.68/7; Usefulness and Affect = 4.53/7; and Willingness to Rely On = 3.94/7). Further statistical analysis (independent samples t-test) determined the difference in factor scores between the factors when age (Gen Z/Millennials vs. Gen X/Boomers) was utilized as the independent, categorical variable. The results showed the difference in mean scores across all three factors to be statistically significant (p<0.05) for these two core age groupings: (1) Gen Z/Millennials Reliability = 4.90/7 vs. Gen X/Boomers Reliability = 4.34/7; (2) Gen Z/Millennials Usefulness and Affect = 4.85/7 vs Gen X/Boomers Usefulness and Affect = 4.05/7; and (3) Gen Z/Millennials Willingness to Rely On = 4.53/7 vs Gen X/Boomers Willingness to Rely On = 3.03/7. The results clearly indicate that older social media users lack trust in the quality of information conveyed in social media ads when compared to younger, more social media-savvy consumers. This is especially evident with respect to Factor 3 (Willingness to Rely On), whose underlying variables reflect one’s behavioral intent to act based on the information conveyed in advertising. These findings can be useful to marketers, advertisers, and brand managers in that the results highlight a critical need to design ‘authentic’ advertisements on social media sites to better connect with these older users in an attempt to foster positive behavioral responses from within this large demographic group – whose engagement with social media sites continues to increase year on year.

Keywords: social media advertising, trust, older consumers, internet studies

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Authors: Utkarsh A. Mishra, Ankit Bansal

Abstract:

At high temperature, radiative heat transfer is the dominant mode of heat transfer. It is governed by various phenomena such as photon emission, absorption, and scattering. The solution of the governing integrodifferential equation of radiative transfer is a complex process, more when the effect of participating medium and wavelength properties are taken into consideration. Although a generic formulation of such radiative transport problem can be modeled for a wide variety of problems with non-gray, non-diffusive surfaces, there is always a trade-off between simplicity and accuracy of the problem. Recently, solutions of complicated mathematical problems with statistical methods based on randomization of naturally occurring phenomena have gained significant importance. Photon bundles with discrete energy can be replicated with random numbers describing the emission, absorption, and scattering processes. Photon Monte Carlo (PMC) is a simple, yet powerful technique, to solve radiative transfer problems in complicated geometries with arbitrary participating medium. The method, on the one hand, increases the accuracy of estimation, and on the other hand, increases the computational cost. The participating media -generally a gas, such as CO₂, CO, and H₂O- present complex emission and absorption spectra. To model the emission/absorption accurately with random numbers requires a weighted sampling as different sections of the spectrum carries different importance. Importance sampling (IS) was implemented to sample random photon of arbitrary wavelength, and the sampled data provided unbiased training of MC estimators for better results. A better replacement to uniform random numbers is using deterministic, quasi-random sequences. Halton, Sobol, and Faure Low-Discrepancy Sequences are used in this study. They possess better space-filling performance than the uniform random number generator and gives rise to a low variance, stable Quasi-Monte Carlo (QMC) estimators with faster convergence. An optimal supervised learning scheme was further considered to reduce the computation costs of the PMC simulation. A one-dimensional plane-parallel slab problem with participating media was formulated. The history of some randomly sampled photon bundles is recorded to train an Artificial Neural Network (ANN), back-propagation model. The flux was calculated using the standard quasi PMC and was considered to be the training target. Results obtained with the proposed model for the one-dimensional problem are compared with the exact analytical and PMC model with the Line by Line (LBL) spectral model. The approximate variance obtained was around 3.14%. Results were analyzed with respect to time and the total flux in both cases. A significant reduction in variance as well a faster rate of convergence was observed in the case of the QMC method over the standard PMC method. However, the results obtained with the ANN method resulted in greater variance (around 25-28%) as compared to the other cases. There is a great scope of machine learning models to help in further reduction of computation cost once trained successfully. Multiple ways of selecting the input data as well as various architectures will be tried such that the concerned environment can be fully addressed to the ANN model. Better results can be achieved in this unexplored domain.

Keywords: radiative heat transfer, Monte Carlo Method, pseudo-random numbers, low discrepancy sequences, artificial neural networks

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Authors: Danyi Wang, Andrew Schriefer, Dennis O'Rourke, Brajendra Kumar, Yang Liu, Fei Zhong, Juergen Scheuenpflug, Zheng Feng

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Purpose: It has been recognized that the microbiome plays critical roles in disease pathogenesis, including cancer, autoimmune disease, and multiple sclerosis. To develop a clinical-grade assay for exploring microbiome-derived clinical biomarkers across disease areas, a two-phase approach is implemented. 1) Identification of the optimal sample preparation reagents using pre-mixed bacteria and healthy donor stool samples coupled with proprietary Sigma-Aldrich® bioinformatics solution. 2) Exploratory analysis of patient samples for enabling precision medicine. Study Procedure: In phase 1 study, we first compared the 16S sequencing results of two ATCC® microbiome standards (MSA 2002 and MSA 2003) across five different extraction kits (Kit A, B, C, D & E). Both microbiome standards samples were extracted in triplicate across all extraction kits. Following isolation, DNA quantity was determined by Qubit assay. DNA quality was assessed to determine purity and to confirm extracted DNA is of high molecular weight. Bacterial 16S ribosomal ribonucleic acid (rRNA) amplicons were generated via amplification of the V3/V4 hypervariable region of the 16S rRNA. Sequencing was performed using a 2x300 bp paired-end configuration on the Illumina MiSeq. Fastq files were analyzed using the Sigma-Aldrich® Microbiome Platform. The Microbiome Platform is a cloud-based service that offers best-in-class 16S-seq and WGS analysis pipelines and databases. The Platform and its methods have been extensively benchmarked using microbiome standards generated internally by MilliporeSigma and other external providers. Data Summary: The DNA yield using the extraction kit D and E is below the limit of detection (100 pg/µl) of Qubit assay as both extraction kits are intended for samples with low bacterial counts. The pre-mixed bacterial pellets at high concentrations with an input of 2 x106 cells for MSA-2002 and 1 x106 cells from MSA-2003 were not compatible with the kits. Among the remaining 3 extraction kits, kit A produced the greatest yield whereas kit B provided the least yield (Kit-A/MSA-2002: 174.25 ± 34.98; Kit-A/MSA-2003: 179.89 ± 30.18; Kit-B/MSA-2002: 27.86 ± 9.35; Kit-B/MSA-2003: 23.14 ± 6.39; Kit-C/MSA-2002: 55.19 ± 10.18; Kit-C/MSA-2003: 35.80 ± 11.41 (Mean ± SD)). Also, kit A produced the greatest yield, whereas kit B provided the least yield. The PCoA 3D visualization of the Weighted Unifrac beta diversity shows that kits A and C cluster closely together while kit B appears as an outlier. The kit A sequencing samples cluster more closely together than both the other kits. The taxonomic profiles of kit B have lower recall when compared to the known mixture profiles indicating that kit B was inefficient at detecting some of the bacteria. Conclusion: Our data demonstrated that the DNA extraction method impacts DNA concentration, purity, and microbial communities detected by next-generation sequencing analysis. Further microbiome analysis performance comparison of using healthy stool samples is underway; also, colorectal cancer patients' samples will be acquired for further explore the clinical utilities. Collectively, our comprehensive qualification approach, including the evaluation of optimal DNA extraction conditions, the inclusion of positive controls, and the implementation of a robust qualified bioinformatics pipeline, assures accurate characterization of the microbiota in a complex matrix for deciphering the deep biology and enabling precision medicine.

Keywords: 16S rRNA sequencing, analytical validation, bioinformatics pipeline, metagenomics

Procedia PDF Downloads 142

Authors: Simon J. Wilde, David M. Herold, Michael J. Bryant

Abstract:

Social media networks have become the hotbed for advertising activities, due mainly to their increasing consumer/user base, and secondly, owing to the ability of marketers to accurately measure ad exposure and consumer-based insights on such networks. More than half of the world’s population (4.8 billion) now uses social media (60%), with 150 million new users having come online within the last 12 months (to June 2022). As the use of social media networks by users grows, key business strategies used for interacting with these potential customers have matured, especially social media advertising. Unlike other traditional media outlets, social media advertising is highly interactive and digital channel-specific. Social media advertisements are clearly targetable, providing marketers with an extremely powerful marketing tool. Yet despite the measurable benefits afforded to businesses engaged in social media advertising, recent controversies (such as the relationship between Facebook and Cambridge Analytica in 2018) have only heightened the role trust and privacy play within these social media networks. The purpose of this exploratory paper is to investigate the extent to which social media users trust social media advertising. Understanding this relationship will fundamentally assist marketers in better understanding social media interactions and their implications for society. Using a web-based quantitative survey instrument, survey participants were recruited via a reputable online panel survey site. Respondents to the survey represented social media users from all states and territories within Australia. Completed responses were received from a total of 258 social media users. Survey respondents represented all core age demographic groupings, including Gen Z/Millennials (18-45 years = 60.5% of respondents) and Gen X/Boomers (46-66+ years = 39.5% of respondents). An adapted ADTRUST scale, using a 20 item 7-point Likert scale, measured trust in social media advertising. The ADTRUST scale has been shown to be a valid measure of trust in advertising within traditional different media, such as broadcast media and print media, and more recently, the Internet (as a broader platform). The adapted scale was validated through exploratory factor analysis (EFA), resulting in a three-factor solution. These three factors were named reliability, usefulness and affect, and the willingness to rely on. Factor scores (weighted measures) were then calculated for these factors. Factor scores are estimates of the scores survey participants would have received on each of the factors had they been measured directly, with the following results recorded (Reliability = 4.68/7; Usefulness and Affect = 4.53/7; and Willingness to Rely On = 3.94/7). Further statistical analysis (independent samples t-test) determined the difference in factor scores between the factors when age (Gen Z/Millennials vs. Gen X/Boomers) was utilised as the independent, categorical variable. The results showed the difference in mean scores across all three factors to be statistically significant (p<0.05) for these two core age groupings: Gen Z/Millennials Reliability = 4.90/7 vs Gen X/Boomers Reliability = 4.34/7; Gen Z/Millennials Usefulness and Affect = 4.85/7 vs Gen X/Boomers Usefulness and Affect = 4.05/7; and Gen Z/Millennials Willingness to Rely On = 4.53/7 vs Gen X/Boomers Willingness to Rely On = 3.03/7. The results clearly indicate that older social media users lack trust in the quality of information conveyed in social media ads, when compared to younger, more social media-savvy consumers. This is especially evident with respect to Factor 3 (Willingness to Rely On), whose underlying variables reflect one’s behavioural intent to act based on the information conveyed in advertising. These findings can be useful to marketers, advertisers, and brand managers in that the results highlight a critical need to design ‘authentic’ advertisements on social media sites to better connect with these older users, in an attempt to foster positive behavioural responses from within this large demographic group – whose engagement with social media sites continues to increase year on year.

Keywords: social media advertising, trust, older consumers, online

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Authors: Murat Arıbaş, Uğur Özcan

Abstract:

Due to the increasing number of universities and academics, the fund of the universities for research activities and grants/supports given by government institutions have increased number and quality of academic research projects. Although every academic research project has a specific purpose and importance, limited resources (money, time, manpower etc.) require choosing the best ones from all (Amiri, 2010). It is a pretty hard process to compare and determine which project is better such that the projects serve different purposes. In addition, the evaluation process has become complicated since there are more than one evaluator and multiple criteria for the evaluation (Dodangeh, Mojahed and Yusuff, 2009). Mehrez and Sinuany-Stern (1983) determined project selection problem as a Multi Criteria Decision Making (MCDM) problem. If a decision problem involves multiple criteria and objectives, it is called as a Multi Attribute Decision Making problem (Ömürbek & Kınay, 2013). There are many MCDM methods in the literature for the solution of such problems. These methods are AHP (Analytic Hierarchy Process), ANP (Analytic Network Process), TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluation), UTADIS (Utilities Additives Discriminantes), ELECTRE (Elimination et Choix Traduisant la Realite), MAUT (Multiattribute Utility Theory), GRA (Grey Relational Analysis) etc. Teach method has some advantages compared with others (Ömürbek, Blacksmith & Akalın, 2013). Hence, to decide which MCDM method will be used for solution of the problem, factors like the nature of the problem, types of choices, measurement scales, type of uncertainty, dependency among the attributes, expectations of decision maker, and quantity and quality of the data should be considered (Tavana & Hatami-Marbini, 2011). By this study, it is aimed to develop a systematic decision process for the grant support applications that are expected to be evaluated according to their scientific adequacy by multiple evaluators under certain criteria. In this context, project evaluation process applied by The Scientific and Technological Research Council of Turkey (TÜBİTAK) the leading institutions in our country, was investigated. Firstly in the study, criteria that will be used on the project evaluation were decided. The main criteria were selected among TÜBİTAK evaluation criteria. These criteria were originality of project, methodology, project management/team and research opportunities and extensive impact of project. Moreover, for each main criteria, 2-4 sub criteria were defined, hence it was decided to evaluate projects over 13 sub-criterion in total. Due to superiority of determination criteria weights AHP method and provided opportunity ranking great number of alternatives TOPSIS method, they are used together. AHP method, developed by Saaty (1977), is based on selection by pairwise comparisons. Because of its simple structure and being easy to understand, AHP is the very popular method in the literature for determining criteria weights in MCDM problems. Besides, the TOPSIS method developed by Hwang and Yoon (1981) as a MCDM technique is an alternative to ELECTRE method and it is used in many areas. In the method, distance from each decision point to ideal and to negative ideal solution point was calculated by using Euclidian Distance Approach. In the study, main criteria and sub-criteria were compared on their own merits by using questionnaires that were developed based on an importance scale by four relative groups of people (i.e. TUBITAK specialists, TUBITAK managers, academics and individuals from business world ) After these pairwise comparisons, weight of the each main criteria and sub-criteria were calculated by using AHP method. Then these calculated criteria’ weights used as an input in TOPSİS method, a sample consisting 200 projects were ranked on their own merits. This new system supported to opportunity to get views of the people that take part of project process including preparation, evaluation and implementation on the evaluation of academic research projects. Moreover, instead of using four main criteria in equal weight to evaluate projects, by using weighted 13 sub-criteria and decision point’s distance from the ideal solution, systematic decision making process was developed. By this evaluation process, new approach was created to determine importance of academic research projects.

Keywords: Academic projects, Ahp method, Research projects evaluation, Topsis method.

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