Search results for: statistical literacy

Authors: Pongthep Bunrueng

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This action research accentuates the outcome of a development in English pronunciation, using principles of phonetics for English major students at Loei Rajabhat University. The research is split into 5 separate modules: 1) Organs of Speech and How to Produce Sounds, 2) Monopthongs, 3) Diphthongs, 4) Consonant sounds, and 5) Suprasegmental Features. Each module followed a 4 step action research process, 1) Planning, 2) Acting, 3) Observing, and 4) Reflecting. The research targeted 2nd year students who were majoring in English Education at Loei Rajabhat University during the academic year of 2011. A mixed methodology employing both quantitative and qualitative research was used, which put theory into action, taking segmental features up to suprasegmental features. Multiple tools were employed which included the following documents: pre-test and post-test papers, evaluation and assessment papers, group work assessment forms, a presentation grading form, an observation of participants form and a participant self-reflection form. All 5 modules for the target group showed that results from the post-tests were higher than those of the pre-tests, with 0.01 statistical significance. All target groups attained results ranging from low to moderate and from moderate to high performance. The participants who attained low to moderate results had to re-sit the second round. During the first development stage, participants attended classes with group participation, in which they addressed planning through mutual co-operation and sharing of responsibility. Analytic induction of strong points for this operation illustrated that learner cognition, comprehension, application, and group practices were all present whereas the participants with weak results could be attributed to biological differences, differences in life and learning, or individual differences in responsiveness and self-discipline. Participants who were required to be re-treated in Spiral 2 received the same treatment again. Results of tests from the 5 modules after the 2nd treatment were that the participants attained higher scores than those attained in the pre-test. Their assessment and development stages also showed improved results. They showed greater confidence at participating in activities, produced higher quality work, and correctly followed instructions for each activity. Analytic induction of strong and weak points for this operation remains the same as for Spiral 1, though there were improvements to problems which existed prior to undertaking the second treatment.

Keywords: action research, English pronunciation, phonetics, segmental features, suprasegmental features

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Authors: Laura Rodriguez Amaya

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Advances in science, technology, engineering, and mathematics (STEM) are viewed as important to countries’ national economies and their capacities to be competitive in the global economy. However, many countries experience low numbers of students entering these disciplines. To strengthen the professional STEM pipelines, it is important that students are retained in these disciplines at universities. Scholars agree that to retain students in universities’ STEM degrees, it is necessary that STEM course content shows the relevance of these academic fields to their daily lives. By increasing students’ understanding on the importance of these degrees and careers, students’ motivation to remain in these academic programs can also increase. An effective way to make STEM content relevant to students’ lives is the use of geospatial technologies and geovisualization in the classroom. The Geospatial Revolution, and the science and technology associated with it, has provided scientists and engineers with an incredible amount of data about Earth and Earth systems. This data can be used in the classroom to support instruction and make content relevant to all students. The purpose of this study was to find out the prevalence use of geospatial technologies and geovisualization as teaching practices in a USA university. The Teaching Practices Inventory survey, which is a modified version of the Carl Wieman Science Education Initiative Teaching Practices Inventory, was selected for the study. Faculty in the STEM disciplines that participated in a summer learning institute at a 4-year university in the USA constituted the population selected for the study. One of the summer learning institute’s main purpose was to have an impact on the teaching of STEM courses, particularly the teaching of gateway courses taken by many STEM majors. The sample population for the study is 97.5 of the total number of summer learning institute participants. Basic descriptive statistics through the Statistical Package for the Social Sciences (SPSS) were performed to find out: 1) The percentage of faculty using geospatial technologies and geovisualization; 2) Did the faculty associated department impact their use of geospatial tools?; and 3) Did the number of years in a teaching capacity impact their use of geospatial tools? Findings indicate that only 10 percent of respondents had used geospatial technologies, and 18 percent had used geospatial visualization. In addition, the use of geovisualization among faculty of different disciplines was broader than the use of geospatial technologies. The use of geospatial technologies concentrated in the engineering departments. Data seems to indicate the lack of incorporation of geospatial tools in STEM education. The use of geospatial tools is an effective way to engage students in deep STEM learning. Future research should look at the effect on student learning and retention in science and engineering programs when geospatial tools are used.

Keywords: engineering education, geospatial technology, geovisualization, STEM

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Authors: Mequanent Wale Mekonen, Edoardo Otranto, Angela Alibrandi

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Diabetic kidney disease is one of the main microvascular complications caused by diabetes. Several clinical and biochemical variables are reported to be associated with diabetic kidney disease in people with type 2 diabetes. However, their interrelations could distort the effect estimation of these variables for the disease's progression. The objective of the study is to determine how the biochemical and clinical variables in people with type 2 diabetes are interrelated with each other and their effects on kidney disease progression through advanced statistical methods. First, principal component analysis was used to explore how the biochemical and clinical variables intercorrelate with each other, which helped us reduce a set of correlated biochemical variables to a smaller number of uncorrelated variables. Then, ordered logit regression models (cumulative, stage, and adjacent) were employed to assess the effect of biochemical and clinical variables on the order-level response variable (progression of kidney function) by considering the proportionality assumption for more robust effect estimation. This retrospective cross-sectional study retrieved data from a type 2 diabetic cohort in a polyclinic hospital at the University of Messina, Italy. The principal component analysis yielded three uncorrelated components. These are principal component 1, with negative loading of glycosylated haemoglobin, glycemia, and creatinine; principal component 2, with negative loading of total cholesterol and low-density lipoprotein; and principal component 3, with negative loading of high-density lipoprotein and a positive load of triglycerides. The ordered logit models (cumulative, stage, and adjacent) showed that the first component (glycosylated haemoglobin, glycemia, and creatinine) had a significant effect on the progression of kidney disease. For instance, the cumulative odds model indicated that the first principal component (linear combination of glycosylated haemoglobin, glycemia, and creatinine) had a strong and significant effect on the progression of kidney disease, with an effect or odds ratio of 0.423 (P value = 0.000). However, this effect was inconsistent across levels of kidney disease because the first principal component did not meet the proportionality assumption. To address the proportionality problem and provide robust effect estimates, alternative ordered logit models, such as the partial cumulative odds model, the partial adjacent category model, and the partial continuation ratio model, were used. These models suggested that clinical variables such as age, sex, body mass index, medication (metformin), and biochemical variables such as glycosylated haemoglobin, glycemia, and creatinine have a significant effect on the progression of kidney disease.

Keywords: diabetic kidney disease, ordered logit model, principal component analysis, type 2 diabetes

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Authors: Salma A. Mahmoud

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Epigenetic, or alteration in gene expression influenced by extragenetic factors, has emerged as one of the most promising areas that will address some of the gaps in our current knowledge in understanding patterns of human variation. In the last decade, the research investigating epigenetic mechanisms in many fields has flourished and witnessed significant progress. It paved the way for a new era of integrated research especially between anthropology/archeology and life sciences. Skeletal remains are considered the most significant source of information for studying human variations across history, and by utilizing these valuable remains, we can interpret the past events, cultures and populations. In addition to archeological, historical and anthropological importance, studying bones has great implications in other fields such as medicine and science. Bones also can hold within them the secrets of the future as they can act as predictive tools for health, society characteristics and dietary requirements. Bones in their basic forms are composed of cells (osteocytes) that are affected by both genetic and environmental factors, which can only explain a small part of their variability. The primary objective of this project is to examine the epigenetic landscape/signature within bones of archeological remains as a novel marker that could reveal new ways to conceptualize chronological events, gender differences, social status and ecological variations. We attempted here to address discrepancies in common variants such as methylome as well as novel epigenetic regulators such as chromatin remodelers, which to our best knowledge have not yet been investigated by anthropologists/ paleoepigenetists using plethora of techniques (biological, computational, and statistical). Moreover, extracting epigenetic information from bones will highlight the importance of osseous material as a vector to study human beings in several contexts (social, cultural and environmental), and strengthen their essential role as model systems that can be used to investigate and construct various cultural, political and economic events. We also address all steps required to plan and conduct an epigenetic analysis from bone materials (modern and ancient) as well as discussing the key challenges facing researchers aiming to investigate this field. In conclusion, this project will serve as a primer for bioarcheologists/anthropologists and human biologists interested in incorporating epigenetic data into their research programs. Understanding the roles of epigenetic mechanisms in bone structure and function will be very helpful for a better comprehension of their biology and highlighting their essentiality as interdisciplinary vectors and a key material in archeological research.

Keywords: epigenetics, archeology, bones, chromatin, methylome

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Authors: Andreea Molnar, Amalia Ardeljan, Lexi Frankel, Marissa Dallara, Brittany Nagel, Omar Rashid

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Background: Escherichia coli is a gram-negative, facultative anaerobic bacteria that belongs to the family Enterobacteriaceae and resides in the intestinal tracts of individuals. E.Coli has numerous strains grouped into serogroups and serotypes based on differences in antigens in their cell walls (somatic, or “O” antigens) and flagella (“H” antigens). More than 700 serotypes of E. coli have been identified. Although most strains of E. coli are harmless, a few strains, such as E. coli O157:H7 which produces Shiga toxin, can cause intestinal infection with symptoms of severe abdominal cramps, bloody diarrhea, and vomiting. Infection with E. Coli can lead to the development of systemic inflammation as the toxin exerts its effects. Chronic inflammation is now known to contribute to cancer development in several organs, including the prostate. The purpose of this study was to evaluate the correlation between E. Coli and the incidence of prostate cancer. Methods: Data collected in this cohort study was provided by a Health Insurance Portability and Accountability Act (HIPAA) compliant national database to evaluate patients infected with E.Coli infection and prostate cancer using the International Classification of Disease (ICD-10 and ICD-9 codes). Permission to use the database was granted by Holy Cross Health, Fort Lauderdale for the purpose of academic research. Data analysis was conducted through the use of standard statistical methods. Results: Between January 2010 and December 2019, the query was analyzed and resulted in 81, 037 patients after matching in both infected and control groups, respectively. The two groups were matched by Age Range and CCI score. The incidence of prostate cancer was 2.07% and 1,680 patients in the E. Coli group compared to 5.19% and 4,206 patients in the control group. The difference was statistically significant by a p-value p<2.2x10-16 with an Odds Ratio of 0.53 and a 95% CI. Based on the specific treatment for E.Coli, the infected group vs control group were matched again with a result of 31,696 patients in each group. 827 out of 31,696 (2.60%) patients with a prior E.coli infection and treated with antibiotics were compared to 1634 out of 31,696 (5.15%) patients with no history of E.coli infection (control) and received antibiotic treatment. Both populations subsequently developed prostate carcinoma. Results remained statistically significant (p<2.2x10-16), Odds Ratio=0.55 (95% CI 0.51-0.59). Conclusion: This retrospective study shows a statistically significant correlation between E.Coli infection and a decreased incidence of prostate cancer. Further evaluation is needed in order to identify the impact of E.Coli infection and prostate cancer development.

Keywords: E. Coli, prostate cancer, protective, microbiology

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Authors: Triveni Gogoi, Rima Chatterjee

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Shear wave velocity (Vs) estimation is an important approach in the seismic exploration and characterization of a hydrocarbon reservoir. There are varying methods for prediction of S-wave velocity, if recorded S-wave log is not available. But all the available methods for Vs prediction are empirical mathematical models. Shear wave velocity can be estimated using P-wave velocity by applying Castagna’s equation, which is the most common approach. The constants used in Castagna’s equation vary for different lithologies and geological set-ups. In this study, multiple regression analysis has been used for estimation of S-wave velocity. The EMERGE module from Hampson-Russel software has been used here for generation of S-wave log. Both single attribute and multi attributes analysis have been carried out for generation of synthetic S-wave log in Upper Assam basin. Upper Assam basin situated in North Eastern India is one of the most important petroleum provinces of India. The present study was carried out using four wells of the study area. Out of these wells, S-wave velocity was available for three wells. The main objective of the present study is a prediction of shear wave velocities for wells where S-wave velocity information is not available. The three wells having S-wave velocity were first used to test the reliability of the method and the generated S-wave log was compared with actual S-wave log. Single attribute analysis has been carried out for these three wells within the depth range 1700-2100m, which corresponds to Barail group of Oligocene age. The Barail Group is the main target zone in this study, which is the primary producing reservoir of the basin. A system generated list of attributes with varying degrees of correlation appeared and the attribute with the highest correlation was concerned for the single attribute analysis. Crossplot between the attributes shows the variation of points from line of best fit. The final result of the analysis was compared with the available S-wave log, which shows a good visual fit with a correlation of 72%. Next multi-attribute analysis has been carried out for the same data using all the wells within the same analysis window. A high correlation of 85% has been observed between the output log from the analysis and the recorded S-wave. The almost perfect fit between the synthetic S-wave and the recorded S-wave log validates the reliability of the method. For further authentication, the generated S-wave data from the wells have been tied to the seismic and correlated them. Synthetic share wave log has been generated for the well M2 where S-wave is not available and it shows a good correlation with the seismic. Neutron porosity, density, AI and P-wave velocity are proved to be the most significant variables in this statistical method for S-wave generation. Multilinear regression method thus can be considered as a reliable technique for generation of shear wave velocity log in this study.

Keywords: Castagna's equation, multi linear regression, multi attribute analysis, shear wave logs

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Authors: Oseyemi Omowunmi Olubomehin, Olufemi Michael Denton

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Diabetes mellitus is a disease that is related to the digestion of carbohydrates, proteins and fats and how this affects the blood glucose levels. Various synthetic drugs employed in the management of the disease work through different mechanisms. Keeping postprandial blood glucose levels within acceptable range is a major factor in the management of type 2 diabetes and its complications. Thus, the inhibition of carbohydrate-hydrolyzing enzymes such as α-amylase is an important strategy in lowering postprandial blood glucose levels, but synthetic inhibitors have undesirable side effects like flatulence, diarrhea, gastrointestinal disorders to mention a few. Therefore, it is necessary to identify and explore the α-amylase inhibitors from plants due to their availability, safety, and low costs. In the present study, extracts from the leaves of Rauvolfia vomitoria and seeds of Picralima nitida which are used in the Nigeria traditional system of medicine to treat diabetes were tested for their α-amylase inhibitory effect. The powdered plant samples were subjected to phytochemical screening using standard procedures. The leaves and seeds macerated successively using n-hexane, ethyl acetate and methanol resulted in the crude extracts which at different concentrations (0.1, 0.5 and 1 mg/mL) alongside the standard drug acarbose, were subjected to α-amylase inhibitory assay using the Benfield and Miller methods, with slight modification. Statistical analysis was done using ANOVA, SPSS version 2.0. The phytochemical screening results of the leaves of Rauvolfia vomitoria and the seeds of Picralima nitida showed the presence of alkaloids, tannins, saponins and cardiac glycosides while in addition Rauvolfia vomitoria had phenols and Picralima nitida had terpenoids. The α-amylase assay results revealed that at 1 mg/mL the methanol, hexane, and ethyl acetate extracts of the leaves of Rauvolfia vomitoria gave (15.74, 23.13 and 26.36 %) α-amylase inhibitions respectively, the seeds of Picralima nitida gave (15.50, 30.68, 36.72 %) inhibitions which were not significantly different from the control at p < 0.05, while acarbose gave a significant 56 % inhibition at p < 0.05. The presence of alkaloids, phenols, tannins, steroids, saponins, cardiac glycosides and terpenoids in these plants are responsible for the observed anti-diabetic activity. However, the low percentages of α-amylase inhibition by these plant samples shows that α-amylase inhibition is not the major way by which both plants exhibit their anti-diabetic effect.

Keywords: alpha-amylase, Picralima nitida, postprandial hyperglycemia, Rauvolfia vomitoria

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Authors: Lorenza Sganzetta, Nunzia Borrelli

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The research intends to reflect on the current mapping of the Food Strategies, on the reasons why in the planning objectives panorama, such sustainability priorities are located in those geographic areas and on the evolutions of these priorities of the Mediterranean planning dispositions. The whirling population growth that is affecting global cities is causing an enormous challenge to conventional resource-intensive food production and supply and the urgent need to face food safety, food security and sustainability concerns. Urban or Territorial Food Strategies can provide an interesting path for the development of this new agenda within the imperative principle of sustainability. In the specific, it is relevant to explore what ‘sustainability’ means within these policies. Most of these plans include actions related to four main components and interpretations of sustainability that are food security and safety, food equity, environmental sustainability itself and cultural identity and, at the designing phase, they differ slightly from each other according to the degree of approximation to one of these dimensions. Moving from these assumptions, the article would analyze some practices and policies representatives of different Food Strategies of the world and focus on the Mediterranean ones, on the problems and negative externalities from which they start, on the first interventions that are implementing and on their main objectives. We will mainly use qualitative data from primary and secondary collections. So far, an essential observation could have been made about the relationship between these sustainability dimensions and geography. In statistical terms, the US and Canadian policies tended to devote a large research space to health issues and access to food; those northern European showed a special attention to the environmental issues and the shortening of the chain; and finally the policies that, even in limited numbers, were being developed in the Mediterranean basin, were characterized by a strong territorial and cultural imprint and their major aim was to preserve local production and the contact between the productive land and the end consumer. Recently, though, Mediterranean food planning strategies are focusing more on health related and food accessibility issues and analyzing our diets not just as a matter of culture and territorial branding but as tools for reducing public health costs and accessibility to fresh food for everyone. The article would reflect then on how Food Safety, Food Security and Health are entering the new agenda of the Mediterranean Food Strategies. The research hypothesis suggests that the economic crisis that in the last years invested both producers and consumers had a significant impact on the nutrition habits and on the redefinition of food poverty, even in the fatherland of the healthy Mediterranean diet. This trend and other variables influenced the orientation and the objectives of the food strategies.

Keywords: food security, food strategy, health, sustainability

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Authors: Rosni Lakandri

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With the development of science and technology, there has been a complete transformation in the domain of information technology. Particularly after the Second World War and Cold War period, the role of media and communication technology in shaping the political, economic, socio-cultural proceedings across the world has been tremendous. It performs as a channel between the governing bodies of the state and the general masses. As we have seen the international community constantly talking about the onset of Asian Century, India and China happens to be the major player in this. Both have the civilization history, both are neighboring countries, both are witnessing a huge economic growth and, important of all, both are considered the rising powers of Asia. Not negating the fact that both countries have gone to war with each other in 1962 and the common people and even the policy makers of both the sides view each other till now from this prism. A huge contribution to this perception of people goes to the media coverage of both sides, even if there are spaces of cooperation which they share, the negative impacts of media has tended to influence the people’s opinion and government’s perception about each other. Therefore, analysis of media’s impression in both the countries becomes important in order to know their effect on the larger implications of foreign policy towards each other. It is usually said that media not only acts as the information provider but also acts as ombudsman to the government. They provide a kind of check and balance to the governments in taking proper decisions for the people of the country but in attempting to answer this hypothesis we have to analyze does the media really helps in shaping the political landscape of any country? Therefore, this study rests on the following questions; 1.How do China and India depict each other through their respective News media? 2.How much and what influences they make on the policy making process of each country? How do they shape the public opinion in both the countries? In order to address these enquiries, the study employs both primary and secondary sources available, and in generating data and other statistical information, primary sources like reports, government documents, and cartography, agreements between the governments have been used. Secondary sources like books, articles and other writings collected from various sources and opinion from visual media sources like news clippings, videos in this topic are also included as a source of on ground information as this study is not based on field study. As the findings suggest in case of China and India, media has certainly affected people’s knowledge about the political and diplomatic issues at the same time has affected the foreign policy making of both the countries. They have considerable impact on the foreign policy formulation and we can say there is some mediatization happening in foreign policy issues in both the countries.

Keywords: China, foreign policy, India, media, public opinion

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Authors: Danna Jia, Bin Li

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Background: Atopic dermatitis (AD) is a chronic and refractory inflammatory skin disease characterized by relapsing eczematous and pruritic skin lesions. The global prevalence of AD ranges from 1~ 20%, and its incidence rates are increasing. It affects individuals from infancy to adulthood, significantly impacting their daily lives and social activities. Despite its major health burden, the precise mechanisms underlying AD remain unknown. Understanding the genetic differences associated with AD is crucial for advancing diagnosis and targeted treatment development. This study aims to identify candidate genes of AD by using bioinformatics analysis. Methods: We conducted a comprehensive analysis of four pooled transcriptomic datasets (GSE16161, GSE32924, GSE130588, and GSE120721) obtained from the Gene Expression Omnibus (GEO) database. Differential gene expression analysis was performed using the R statistical language. The differentially expressed genes (DEGs) between AD patients and normal individuals were functionally analyzed using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. Furthermore, a protein-protein interaction (PPI) network was constructed to identify candidate genes. Results: Among the patient-level gene expression datasets, we identified 114 shared DEGs, consisting of 53 upregulated genes and 61 downregulated genes. Functional analysis using GO and KEGG revealed that the DEGs were mainly associated with the negative regulation of transcription from RNA polymerase II promoter, membrane-related functions, protein binding, and the Human papillomavirus infection pathway. Through the PPI network analysis, we identified eight core genes: CD44, STAT1, HMMR, AURKA, MKI67, and SMARCA4. Conclusion: This study elucidates key genes associated with AD, providing potential targets for diagnosis and treatment. The identified genes have the potential to contribute to the understanding and management of AD. The bioinformatics analysis conducted in this study offers new insights and directions for further research on AD. Future studies can focus on validating the functional roles of these genes and exploring their therapeutic potential in AD. While these findings will require further verification as achieved with experiments involving in vivo and in vitro models, these results provided some initial insights into dysfunctional inflammatory and immune responses associated with AD. Such information offers the potential to develop novel therapeutic targets for use in preventing and treating AD.

Keywords: atopic dermatitis, bioinformatics, biomarkers, genes

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Authors: Cedillo Ortiz Cesar Isaac, Marañón-Ruiz Virginia-Francisca, Lozano-Alvarez Juan Antonio, Jáuregui-Rincón Juan, Roger Chiu Zarate

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Introduction: The contamination of water with the azo-dye is a problem worldwide as although wastewater contaminate is treated in a municipal sewage system, still contain a considerable amount of dyes. In the present, there are different processes denominated tertiary method in which it is possible to lower the concentration of the dye. One of these methods is by adsorption onto various materials which can be organic or inorganic materials. The xanthan is a biomaterial as removal agents to decrease the dye content in aqueous solution. The Zimm-Bragg model described the experimental isotherms obtained when this biopolymer was used in the removal of textile dyes. Nevertheless, it was not established if a possible correlation between dye structure and removal efficiency exists. In this sense, the principal objective of this report is to propose a qualitative relationship between the structure of three azo-dyes (Congo Red (CR), Methyl Red (MR) and Methyl Orange (MO)) and their removal efficiency from aqueous environment when xanthan are used as dye sequestering agents. Methods: The dyes were subjected to different pH and ionic strength values to obtain the conditions of maximum dye removal. Afterward, these conditions were used to perform the adsorption isotherm as was reported in the previous study in our group. The Zimm-Bragg model was used to describe the experimental data and the parameters of nucleation (Ku) and cooperativity (U) were obtained by optimization using the R statistical software. The spectra from UV-Visible (aqueous solution), Infrared absorption and Raman spectroscopies (dry samples) were obtained from the biopolymer-dye complex. Results: The removal percent with xanthan in each dye are as follows: with CR had 99.98 % when the pH is 12 and ionic strength is 10.12, with MR had 84.79 % when the pH is 9.5 and ionic strength is 43 and finally the MO had 30 % in pH 4 and 72. It can be seen that when xanthan is used to remove the dyes, exists a lower dependence between structure and removal efficiency. This may be due to the different tendency to form aggregates of each dye. This aggregation capacity and the charge of each dye resulting from the pH and ionic strength values of aqueous solutions are key factors in the dye removal. The experimental isotherm of MR was only that adequately described by Zimm-Bragg model. Because with the CR had the 100 % of remove thus is very difficult obtain de experimental isotherm and finally MO had results fluctuating and therefore was impossible get the accurate data. Conclusions: The study of the removal of three dyes with xanthan as dye sequestering agents suggests that aggregation capacity of dyes and the charge resulting from structural characteristics such as molecular weight and functional groups have a relationship with the removal efficiency. Acknowledgements: We are gratefully acknowledged support for this project by Consejo Nacional de Ciencia y Tecnología, México (CONACyT, Grant No. 632694.)

Keywords: adsorption, azo dyes, xanthan gum, Zimm Bragg theory

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Authors: El Khaddam Safaa, Soulaymani Abdelmajid, Mokhtari Abdelghani, Ouammi Lahcen, Rachida Soulaymani-Beincheikh

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The poisonings represent a problem of health in the world and Morocco, The exact dimensions of this phenomenon are still poorly recorded that we see the lack of exhaustive statistical data. The objective of this retrospective study of a series of cases of the poisonings declared at the level of the region of Tadla-Azilal and collected by the Moroccan Poison Control and Pharmacovigilance Center. An epidemiological profile of the poisonings was to raise, to determine the risk factors influencing the vital preview of the poisoned And to follow the evolution of the incidence, the lethality, and the mortality. During the period of study, we collected and analyzed 9303 cases of poisonings by different incriminated toxic products with the exception of the scorpion poisonings. These poisonings drove to 99 deaths. The epidemiological profile which we raised, showed that the poisoned were of any age with an average of 24.62±16.61 years, The sex-ratio (woman/man) was 1.36 in favor of the women. The difference between both sexes is highly significant (χ2 = 210.5; p<0,001). Most of the poisoned which declared to be of urban origin (60.5 %) (χ2=210.5; p<0,001). Carbon monoxide was the most incriminated among the cases of poisonings (24.15 %), them putting in head, followed by some pesticides and farm produces (21.44 %) and food (19.95 %). The analysis of the risk factors showed that the grown-up patients whose age is between 20 and 74 years have twice more risk of evolving towards the death (RR=1,57; IC95 % = 1,03-2,38) than the other age brackets, so the male genital organ was the most exposed (explained) to the death that the female genital organ (RR=1,59; IC95 % = 1,07-2,38) The patients of rural origin had presented 5 times more risk (RR=4,713; IC95 % = 2,543-8,742). Poisoned by the mineral products had presented the maximum of risk on the vital preview death (RR=23,19, IC95 % = 2,39-224,1). The poisonings by pesticides produce a risk of 9 (RR=9,31; IC95 % = 6,10-14,18). The incidence was 3,3 cases of 10000 inhabitants, and the mortality was 0,004 cases of 1000 inhabitants (that is 4 cases by 1000 000 inhabitants). The rate of lethality registered annually was 10.6 %. The evolution of the indicators of health according to the years showed that the rate of statement measured by the incidence increased by a significant way. We also noted an improvement in the coverage which (who) ended up with a decrease in the rate of the lethality and the mortality during last years. The fight anti-toxic is a work of length time. He asks for a lot of work various levels. It is necessary to attack the delay accumulated by our country on the various legal, institutional and technical aspects. The ideal solution is to develop and to set up a national strategy.

Keywords: epidemiology, poisoning, risk factors, indicators of health, Tadla-Azilal grated by anti-toxic fight

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Authors: Susan Mwai, Mary Muchane, Peter Wachira, Sheila Okoth, Muchai Muchane, Halima Saado

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Tropical forests harbor a wide range of biodiversity and rich macro-fungi diversity compared to the temperate regions in the World. However, biodiversity is facing the threat of extinction following the rate of forest loss taking place before proper study and documentation of macrofungi is achieved. The present study was undertaken to determine the effect of converting indigenous habitat to plantation forest on macrofungi diversity. To achieve the objective of this study, an inventory focusing on macro-fungi diversity was conducted within Kereita block in Kikuyu Escarpment forest which is on the southern side of Aberdare mountain range. The macrofungi diversity was conducted in the indigenous forest and in more than 15 year old Patula plantation forest , during the wet (long rain season, December 2014) and dry (Short rain season, May, 2015). In each forest type, 15 permanent (20m x 20m) sampling plots distributed across three (3) forest blocks were used. Both field and laboratory methods involved recording abundance of fruiting bodies, taxonomic identity of species and analysis of diversity indices and measures in terms of species richness, density and diversity. R statistical program was used to analyze for species diversity and Canoco 4.5 software for species composition. A total number of 76 genera in 28 families and 224 species were encountered in both forest types. The most represented taxa belonged to the Agaricaceae (16%), Polyporaceae (12%), Marasmiaceae, Mycenaceae (7%) families respectively. Most of the recorded macro-fungi were saprophytic, mostly colonizing the litter 38% and wood 34% based substrates, which was followed by soil organic dwelling species (17%). Ecto-mycorrhiza fungi (5%) and parasitic fungi (2%) were the least encountered. The data established that indigenous forests (native ecosystems) hosts a wide range of macrofungi assemblage in terms of density (2.6 individual fruit bodies / m2), species richness (8.3 species / plot) and species diversity (1.49/ plot level) compared to the plantation forest. The Conversion of native forest to plantation forest also interfered with species composition though did not alter species diversity. Seasonality was also shown to significantly affect the diversity of macro-fungi and 61% of the total species being present during the wet season. Based on the present findings, forested ecosystems in Kenya hold diverse macro-fungi community which warrants conservation measures.

Keywords: diversity, Indigenous forest, macro-fungi, plantation forest, season

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Authors: Mohammad Arabi

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The development of advanced technologies in the field of signal processing and vibration analysis has enabled more accurate analysis and fault detection in electrical systems. This research investigates the application of temporal and frequency features in detecting faults in electric motor bearings, aiming to enhance fault detection accuracy and prevent unexpected failures. The use of methods such as deep learning algorithms and neural networks in this process can yield better results. The main objective of this research is to evaluate the efficiency and accuracy of methods based on temporal and frequency features in identifying faults in electric motor bearings to prevent sudden breakdowns and operational issues. Additionally, the feasibility of using techniques such as machine learning and optimization algorithms to improve the fault detection process is also considered. This research employed an experimental method and random sampling. Vibration signals were collected from electric motors under normal and faulty conditions. After standardizing the data, temporal and frequency features were extracted. These features were then analyzed using statistical methods such as analysis of variance (ANOVA) and t-tests, as well as machine learning algorithms like artificial neural networks and support vector machines (SVM). The results showed that using temporal and frequency features significantly improves the accuracy of fault detection in electric motor bearings. ANOVA indicated significant differences between normal and faulty signals. Additionally, t-tests confirmed statistically significant differences between the features extracted from normal and faulty signals. Machine learning algorithms such as neural networks and SVM also significantly increased detection accuracy, demonstrating high effectiveness in timely and accurate fault detection. This study demonstrates that using temporal and frequency features combined with machine learning algorithms can serve as an effective tool for detecting faults in electric motor bearings. This approach not only enhances fault detection accuracy but also simplifies and streamlines the detection process. However, challenges such as data standardization and the cost of implementing advanced monitoring systems must also be considered. Utilizing temporal and frequency features in fault detection of electric motor bearings, along with advanced machine learning methods, offers an effective solution for preventing failures and ensuring the operational health of electric motors. Given the promising results of this research, it is recommended that this technology be more widely adopted in industrial maintenance processes.

Keywords: electric motor, fault detection, frequency features, temporal features

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Authors: Rafael Andres Rincon Barrera

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Safety in global aviation plays a preponderant role in organizations that seek to avoid accidents in an attempt to preserve their most precious assets (the people and the machines). Human factors-based programs have shown to be effective in managing human-generated risks. The importance of training on human factors in maintenance has not been indifferent to the Colombian Air Force (COLAF). This research, which has a mixed quantitative, qualitative and descriptive approach, deals with its absence of structuring an instruction program in Human Factors in Aeronautical Maintenance, which serves as a tool to improve Operational Safety in the military air units of the COLAF. Research shows the trends and evolution of human factors programs in aeronautical maintenance through the analysis of a data matrix with 33 sources taken from different databases that are about the incorporation of these types of programs in the aeronautical industry in the last 20 years; as well as the improvements in the operational safety process that are presented after the implementation of these ones. Likewise, it compiles different normative guides in force from world aeronautical authorities for training in these programs, establishing a matrix of methodologies that may be applicable to develop a training program in human factors in maintenance. Subsequently, it illustrates the design, validation, and development of a human factors knowledge measurement instrument for maintenance at the COLAF that includes topics on Human Factors (HF), Safety Management System (SMS), and aeronautical maintenance regulations at the COLAF. With the information obtained, it performs the statistical analysis showing the aspects of knowledge and strengthening the staff for the preparation of the instruction program. Performing data triangulation based on the applicable methods and the weakest aspects found in the maintenance people shows a variable crossing from color coding, thus indicating the contents according to a training program for human factors in aeronautical maintenance, which are adjusted according to the competencies that are expected to be developed with the staff in a curricular format established by the COLAF. Among the most important findings are the determination that different authors are dealing with human factors in maintenance agrees that there is no standard model for its instruction and implementation, but that it must be adapted to the needs of the organization, that the Safety Culture in the Companies which incorporated programs on human factors in maintenance increased, that from the data obtained with the instrument for knowledge measurement of human factors in maintenance, the level of knowledge is MEDIUM-LOW with a score of 61.79%. And finally that there is an opportunity to improve Operational Safety for the COLAF through the implementation of the training program of human factors in maintenance for the technicians working in this area.

Keywords: Colombian air force, human factors, safety culture, safety management system, triangulation

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Authors: Eva Laryea, Clement Yeboah Authors

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A pretest-posttest within subjects, experimental design was employed to examine the effects of a computerized basic statistics learning game on achievement and statistics-related anxiety of students enrolled in introductory graduate statistics course. Participants (N = 34) were graduate students in a variety of programs at state-funded research university in the Southeast United States. We analyzed pre-test posttest differences using paired samples t-tests for achievement and for statistics anxiety. The results of the t-test for knowledge in statistics were found to be statistically significant indicating significant mean gains for statistical knowledge as a function of the game-based intervention. Likewise, the results of the t-test for statistics-related anxiety were also statistically significant indicating a decrease in anxiety from pretest to posttest. The implications of the present study are significant for both teachers and students. For teachers, using computer games developed by the researchers can help to create a more dynamic and engaging classroom environment, as well as improve student learning outcomes. For students, playing these educational games can help to develop important skills such as problem solving, critical thinking, and collaboration. Students can develop interest in the subject matter and spend quality time to learn the course as they play the game without knowing that they are even learning the presupposed hard course. The future directions of the present study are promising, as technology continues to advance and become more widely available. Some potential future developments include the integration of virtual and augmented reality into educational games, the use of machine learning and artificial intelligence to create personalized learning experiences, and the development of new and innovative game-based assessment tools. It is also important to consider the ethical implications of computer game-based pedagogy, such as the potential for games to perpetuate harmful stereotypes and biases. As the field continues to evolve, it will be crucial to address these issues and work towards creating inclusive and equitable learning experiences for all students. This study has the potential to revolutionize the way basic statistics graduate students learn and offers exciting opportunities for future development and research. It is an important area of inquiry for educators, researchers, and policymakers, and will continue to be a dynamic and rapidly evolving field for years to come.

Keywords: pretest-posttest within subjects, experimental design, achievement, statistics-related anxiety

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Authors: Hira Jabbar, Tanzeel-Ur Rehman

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Urban parks and open spaces play a significant role in improving physical and mental health of the citizens, strengthen the societies and make the cities more attractive places to live and work. As the world’s cities continue to grow, continuing to value green space in cities is vital but is also a challenge, particularly in developing countries where there is pressure for space, resources, and development. Offering equal opportunity of accessibility to parks is one of the important issues of park distribution. The distribution of parks should allow all inhabitants to have close proximity to their residence. Remote sensing and Geographic information systems (GIS) can provide decision makers with enormous opportunities to improve the planning and management of Park facilities. This study exhibits the capability of GIS and RS techniques to provide baseline knowledge about the distribution of parks, level of accessibility and to help in identification of potential areas for such facilities. For this purpose Landsat OLI imagery for year 2016 was acquired from USGS Earth Explorer. Preprocessing models were applied using Erdas Imagine 2014v for the atmospheric correction and NDVI model was developed and applied to quantify the land use/land cover classes including built up, barren land, water, and vegetation. The parks amongst total public green spaces were selected based on their signature in remote sensing image and distribution. Percentages of total green and parks green were calculated for each town of Lahore City and results were then synchronized with the recommended standards. ANGSt model was applied to calculate the accessibility from parks. Service area analysis was performed using Network Analyst tool. Serviceability of these parks has been evaluated by employing statistical indices like service area, service population and park area per capita. Findings of the study may contribute in helping the town planners for understanding the distribution of parks, demands for new parks and potential areas which are deprived of parks. The purpose of present study is to provide necessary information to planners, policy makers and scientific researchers in the process of decision making for the management and improvement of urban parks.

Keywords: accessible natural green space standards (ANGSt), geographic information systems (GIS), remote sensing (RS), United States geological survey (USGS)

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Authors: Jun Won Kim

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Objective: Theta-phase gamma-amplitude coupling (TGC) was used as a novel evidence-based tool to reflect the dysfunctional cortico-thalamic interaction in patients with schizophrenia. However, to our best knowledge, no studies have reported the diagnostic utility of the TGC in the resting-state electroencephalographic (EEG) of neuroleptic-naive patients with schizophrenia compared to healthy controls. Thus, the purpose of this EEG study was to understand the underlying mechanisms in patients with schizophrenia by comparing the TGC at rest between two groups and to evaluate the diagnostic utility of TGC. Method: The subjects included 90 patients with schizophrenia and 90 healthy controls. All patients were diagnosed with schizophrenia according to the criteria of Diagnostic and Statistical Manual of Mental Disorders, 4th edition (DSM-IV) by two independent psychiatrists using semi-structured clinical interviews. Because patients were either drug-naïve (first episode) or had not been taking psychoactive drugs for one month before the study, we could exclude the influence of medications. Five frequency bands were defined for spectral analyses: delta (1–4 Hz), theta (4–8 Hz), slow alpha (8–10 Hz), fast alpha (10–13.5 Hz), beta (13.5–30 Hz), and gamma (30-80 Hz). The spectral power of the EEG data was calculated with fast Fourier Transformation using the 'spectrogram.m' function of the signal processing toolbox in Matlab. An analysis of covariance (ANCOVA) was performed to compare the TGC results between the groups, which were adjusted using a Bonferroni correction (P < 0.05/19 = 0.0026). Receiver operator characteristic (ROC) analysis was conducted to examine the discriminating ability of the TGC data for schizophrenia diagnosis. Results: The patients with schizophrenia showed a significant increase in the resting-state TGC at all electrodes. The delta, theta, slow alpha, fast alpha, and beta powers showed low accuracies of 62.2%, 58.4%, 56.9%, 60.9%, and 59.0%, respectively, in discriminating the patients with schizophrenia from the healthy controls. The ROC analysis performed on the TGC data generated the most accurate result among the EEG measures, displaying an overall classification accuracy of 92.5%. Conclusion: As TGC includes phase, which contains information about neuronal interactions from the EEG recording, TGC is expected to be useful for understanding the mechanisms the dysfunctional cortico-thalamic interaction in patients with schizophrenia. The resting-state TGC value was increased in the patients with schizophrenia compared to that in the healthy controls and had a higher discriminating ability than the other parameters. These findings may be related to the compensatory hyper-arousal patterns of the dysfunctional default-mode network (DMN) in schizophrenia. Further research exploring the association between TGC and medical or psychiatric conditions that may confound EEG signals will help clarify the potential utility of TGC.

Keywords: quantitative electroencephalography (QEEG), theta-phase gamma-amplitude coupling (TGC), schizophrenia, diagnostic utility

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Authors: Xiao Wang, Qinge Zhang

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Background: This randomized, open-label study examined the therapeutic effects of computerized cognitive training (CCT) combined with selective serotonin reuptake inhibitors (SSRIs) on cognitive impairment among patients with late-life depression (LLD). Method: Study data were collected from May 5, 2021, to April 21, 2023. Outpatients who met diagnostic criteria for major depressive disorder according to the fifth revision of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) criteria (i.e., a total score on the 17-item Hamilton Depression Rating Scale (HAMD-17) ≥ 18 and a total score on the Montreal Cognitive Assessment scale (MOCA) <26) were randomly assigned to receive up to 12 weeks of CCT and SSRIs treatment (n=57) or SSRIs and Control treatment (n=61). The primary outcome was the change in Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-Cog) scores from baseline to week 12 between the two groups. The secondary outcomes included changes in the HAMD-17 score, Hamilton Anxiety Scale (HAMA) score and Neuropsychiatric Inventory (NPI) score. Mixed model repeated measures (MMRM) analysis was performed on modified intention-to-treat (mITT) and completer populations. Results: The full analysis set (FAS) included 118 patients (CCT and SSRIs group, n=57; SSRIs and Control group, n =61). Over the 12-week study period, the reduction in the ADAS-cog total score was significant (P < 0.001) in both groups, while MMRM analysis revealed a significantly greater reduction in cognitive function (ADAS-cog total scores) from baseline to posttreatment in the CCT and SSRIs group than in the SSRI and Control group [(F (1,115) =13.65, least-squares mean difference [95% CI]: −2.77 [−3.73, −1.81], p<0.001)]. There were significantly greater improvements in depression symptoms (measured by the HAMD-17) in the CCT and SSRIs group than in the control group [MMRM, estimated mean difference (SE) between groups −3.59 [−5.02, −2.15], p < 0.001]. The least-squares mean changes in the HAMA scores and NPI scores between baseline and week 8 were greater in the CCT and SSRIs group than in the control group (all P < 0.05). There was no significant difference between groups on response rates and remission rates by using the last-observation-carried-forward (LOCF) method (all P > 0.05). The most frequent adverse events (AEs) in both groups were dry mouth, somnolence, and constipation. There was no significant difference in the incidence of adverse events between the two groups. Conclusions: CCT combined with SSRIs was efficacious and well tolerated in LLD patients with cognitive impairment.

Keywords: late-life depression, cognitive function, computerized cognitive training, SSRIs

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Authors: Ibrahim Umar, Ashiru Rajab, Sumayya Chindo, Emmanuel Olashore

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INTRODUCTION: Kano is the most populous state in Nigeria and one of the two states with the highest TB burden in the country. The state notifies an average of 8,000+ TB cases quarterly and has the highest yearly notification of all the states in Nigeria from 2020 to 2022. The contribution of the state TB program to the National TB notification varies from 9% to 10% quarterly between the first quarter of 2022 and second quarter of 2023. The Kano State TB Situation Room is an innovative platform for timely data collection, collation and analysis for informed decision in health system. During the 2023 second National TB Testing week (NTBTW) Kano TB program aimed at early TB detection, prevention and treatment. The state TB Situation room provided avenue to the state for coordination and surveillance through real time data reporting, review, analysis and use during the NTBTW. OBJECTIVES: To assess the role of innovative information and communication technology platform for real-time TB reporting during second National TB Testing week in Nigeria 2023. To showcase the NTBTW data cascade analysis using TSR as innovative ICT platform. METHODOLOGY: The State TB deployed a real-time virtual dashboard for NTBTW reporting, analysis and feedback. A data room team was set up who received realtime data using google link. Data received was analyzed using power BI analytic tool with statistical alpha level of significance of <0.05. RESULTS: At the end of the week-long activity and using the real-time dashboard with onsite mentorship of the field workers, the state TB program was able to screen a total of 52,054 people were screened for TB from 72,112 individuals eligible for screening (72% screening rate). A total of 9,910 presumptive TB clients were identified and evaluated for TB leading to diagnosis of 445 TB patients with TB (5% yield from presumptives) and placement of 435 TB patients on treatment (98% percentage enrolment). CONCLUSION: The TB Situation Room (TBSR) has been a great asset to Kano State TB Control Program in meeting up with the growing demand for timely data reporting in TB and other global health responses. The use of real time surveillance data during the 2023 NTBTW has in no small measure improved the TB response and feedback in Kano State. Scaling up this intervention to other disease areas, states and nations is a positive step in the right direction towards global TB eradication.

Keywords: tuberculosis (tb), national tb testing week (ntbtw), tb situation rom (tsr), information communication technology (ict)

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Authors: Ophir Segal, Daniel Weltsch, Shay Tenenbaum, Ran Thein

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Purpose: Patients with lateral patellar dislocation (LPD) are not always referred to perform an MRI. This might be the case in first time LPD patients without surgical indications or in patients with recurrent LPD who had MRI in previous episodes. Unfortunately, in some cases, there are additional knee pathological findings, which include tearing of the collateral or cruciate ligaments and injury to the tendons or menisci. These findings might be overlooked during the physical examination or masked by nonspecific clinical findings like knee pain, effusion, or hemarthrosis. The prevalence of these findings, which can be revealed by MRI, is misreported in literature and is considered rare. In our practice, all patients with LPD are sent for MRI after LPD. Therefore, we have designed a retrospective comparative study to evaluate the prevalence of additional pathological findings in patients with acute traumatic LPD that had performed MRI, comparing different groups of patients according to age, sex, and Tibial Tuberosity-Trochlear Groove(TT-TG) distance. Methods: MRI of the knee in patients after traumatic LPD were evaluated for the presence of additional pathological findings such as injuries to ligaments: Anterior/Posterior cruciate ligament(ACL, PCL), Medial/Lateral collateral ligament(MCL, LCL), injuries to tendons(QUADICEPS, PATELLAR), menisci(Medial/Lateral meniscus(MM, LM)) and tibial plateau, by a fellowship-trained, senior musculoskeletal radiologist. A comparison between different groups of patients was performed according to age (age group < 25 years, age group > 25 years), sex (Male/Female group), and TT-TG distance (TT-TG<15 groups, TT-TG>15 groups). A descriptive and comparative statistical analysis was performed. Results: 150 patients were included in this study. All suffered from LPD between the years 2012-2017 (mean age 21.3( ± SD 8.9), 86 males). ACL, PCL, MCL, and LCL complete or partial tears were found in 17(11.3%), 3(2%), 22(14.6%), and 4(2.7%) of the patients, respectively. MM and LM tears were found in 10(6.7%) and 3(2%) of the patients, respectively. A higher prevalence of PCL injury, MM tear, and LM tear were found in the older age group compared to the younger group of patients (10.5% vs. 1.8%, 18.4% vs. 2.7%, and 7.9% vs. 0%, respectively, p<0.05). A higher prevalence of non-displaced MM tear and LCL injury was found in the male group compared to the female group (8.1% vs. 0% and 8.1% vs. 0% respectively, p<0.05). A higher prevalence of ACL injury was found in the normal TT-TG group compared to the pathologic TT-TG group (17.5% vs. 2.3%, p= 0.0184). Conclusions: Overall, 43 out of 150 (28.7%) of the patient's MRI’s were positive for additional pathological radiological findings. Interestingly, a higher prevalence of additional pathologies was found in the groups of patients with a lower risk for recurrent LPD, including males, patients older than 25, and patients with TT-TG lower than 15mm, and therefore might not be referred for an MRI scan. Thus, we recommend a strict physical examination, awareness to the high prevalence of additional pathological findings, and to consider performing an MRI in all patients after LPD.

Keywords: additional findings, lateral patellar dislocation (LPD), MRI scan, traumatic patellar dislocation, cruciate ligaments injuries, menisci injuries, collateral ligaments injuries

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Authors: Arlene López-Sampson, Tony Page, Betsy Jackes

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Aquilaria genus produces a highly valuable fragrant oleoresin known as agarwood. Agarwood forms in a few trees in the wild as a response to injure or pathogen attack. The resin is used in perfume and incense industry and medicine. Cultivation of Aquilaria species as a sustainable source of the resin is now a common strategy. Physiological traits are frequently used as a proxy of crop and tree productivity. Aquilaria species growing in Queensland, Australia were studied to investigate relationship between leaf-productivity traits with tree growth. Specifically, 28 trees, representing 12 plus trees and 16 trees from yield plots, were selected to conduct carbon isotope analysis (δ13C) and monitor six leaf attributes. Trees were grouped on four diametric classes (diameter at 150 mm above ground level) ensuring the variability in growth of the whole population was sampled. Model averaging technique based on the Akaike’s information criterion (AIC) was computed to identify whether leaf traits could assist in diameter prediction. Carbon isotope values were correlated with height classes and leaf traits to determine any relationship. In average four leaves per shoot were recorded. Approximately one new leaf per week is produced by a shoot. Rate of leaf expansion was estimated in 1.45 mm day-1. There were no statistical differences between diametric classes and leaf expansion rate and number of new leaves per week (p > 0.05). Range of δ13C values in leaves of Aquilaria species was from -25.5 ‰ to -31 ‰ with an average of -28.4 ‰ (± 1.5 ‰). Only 39% of the variability in height can be explained by δ13C in leaf. Leaf δ13C and nitrogen content values were positively correlated. This relationship implies that leaves with higher photosynthetic capacities also had lower intercellular carbon dioxide concentrations (ci/ca) and less depleted values of 13C. Most of the predictor variables have a weak correlation with diameter (D). However, analysis of the 95% confidence of best-ranked regression models indicated that the predictors that could likely explain growth in Aquilaria species are petiole length (PeLen), values of δ13C (true13C) and δ15N (true15N), leaf area (LA), specific leaf area (SLA) and number of new leaf produced per week (NL.week). The model constructed with PeLen, true13C, true15N, LA, SLA and NL.week could explain 45% (R2 0.4573) of the variability in D. The leaf traits studied gave a better understanding of the leaf attributes that could assist in the selection of high-productivity trees in Aquilaria.

Keywords: 13C, petiole length, specific leaf area, tree growth

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Authors: Irene Kretchy, Frances Owusu-Daaku, Samuel Danquah

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Hypertension is the leading risk factor for cardiovascular diseases, and a major cause of death and disability worldwide. This study examined whether psychosocial variables influenced patients’ perception and experience of side effects of their medicines, how they coped with these experiences and the impact on mental health and medication adherence to conventional hypertension therapies. Methods: A hospital-based mixed methods study, using quantitative and qualitative approaches was conducted on hypertensive patients. Participants were asked about side effects, medication adherence, common psychological symptoms, and coping mechanisms with the aid of standard questionnaires. Information from the quantitative phase was analyzed with the Statistical Package for Social Sciences (SPSS) version 20. The interviews from the qualitative study were audio-taped with a digital audio recorder, manually transcribed and analyzed using thematic content analysis. The themes originated from participant interviews a posteriori. Results: The experiences of side effects – such as palpitations, frequent urination, recurrent bouts of hunger, erectile dysfunction, dizziness, cough, physical exhaustion - were categorized as no/low (39.75%), moderate (53.0%) and high (7.25%). Significant relationships between depression (x 2 = 24.21, P < 0.0001), anxiety (x 2 = 42.33, P < 0.0001), stress (x 2 = 39.73, P < 0.0001) and side effects were observed. A logistic regression model using the adjusted results for this association are reported – depression [OR = 1.9 (1.03 – 3.57), p = 0.04], anxiety [OR = 1.5 (1.22 – 1.77), p = < 0.001], and stress [OR = 1.3 (1.02 – 1.71), p = 0.04]. Side effects significantly increased the probability of individuals to be non-adherent [OR = 4.84 (95% CI 1.07 – 1.85), p = 0.04] with social factors, media influences and attitudes of primary caregivers further explaining this relationship. The personal adoption of medication modifying strategies, espousing the use of complementary and alternative treatments, and interventions made by clinicians were the main forms of coping with side effects. Conclusions: Results from this study show that contrary to a biomedical approach, the experience of side effects has biological, social and psychological interrelations. The result offers more support for the need for a multi-disciplinary approach to healthcare where all forms of expertise are incorporated into health provision and patient care. Additionally, medication side effects should be considered as a possible cause of non-adherence among hypertensive patients, thus addressing this problem from a Biopsychosocial perspective in any intervention may improve adherence and invariably control blood pressure.

Keywords: biopsychosocial, hypertension, medication adherence, psychological disorders

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Authors: Despoina Mouratidis, Katia Lida Kermanidis

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Machine translation (MT) is a very important task in Natural Language Processing (NLP). MT evaluation is crucial in MT development, as it constitutes the means to assess the success of an MT system, and also helps improve its performance. Several methods have been proposed for the evaluation of (MT) systems. Some of the most popular ones in automatic MT evaluation are score-based, such as the BLEU score, and others are based on lexical similarity or syntactic similarity between the MT outputs and the reference involving higher-level information like part of speech tagging (POS). This paper presents a language-independent machine learning framework for classifying pairwise translations. This framework uses vector representations of two machine-produced translations, one from a statistical machine translation model (SMT) and one from a neural machine translation model (NMT). The vector representations consist of automatically extracted word embeddings and string-like language-independent features. These vector representations used as an input to a multi-layer neural network (NN) that models the similarity between each MT output and the reference, as well as between the two MT outputs. To evaluate the proposed approach, a professional translation and a "ground-truth" annotation are used. The parallel corpora used are English-Greek (EN-GR) and English-Italian (EN-IT), in the educational domain and of informal genres (video lecture subtitles, course forum text, etc.) that are difficult to be reliably translated. They have tested three basic deep learning (DL) architectures to this schema: (i) fully-connected dense, (ii) Convolutional Neural Network (CNN), and (iii) Long Short-Term Memory (LSTM). Experiments show that all tested architectures achieved better results when compared against those of some of the well-known basic approaches, such as Random Forest (RF) and Support Vector Machine (SVM). Better accuracy results are obtained when LSTM layers are used in our schema. In terms of a balance between the results, better accuracy results are obtained when dense layers are used. The reason for this is that the model correctly classifies more sentences of the minority class (SMT). For a more integrated analysis of the accuracy results, a qualitative linguistic analysis is carried out. In this context, problems have been identified about some figures of speech, as the metaphors, or about certain linguistic phenomena, such as per etymology: paronyms. It is quite interesting to find out why all the classifiers led to worse accuracy results in Italian as compared to Greek, taking into account that the linguistic features employed are language independent.

Keywords: machine learning, machine translation evaluation, neural network architecture, pairwise classification

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Authors: Reemiah Alotaibi, Muthu Ramachandran, Ah-Lian Kor, Amin Hosseinian-Far

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In the past decade, developers of Web 2.0 technologies have shown increasing interest in the topic of e-government. There has been a rapid growth in social media technology because of its significant role in backing up some essential social needs. Its importance and power is derived from its capacity to support two-way communication. Governments are curious to get engaged in these websites, hoping to benefit from the new forms of communication and interaction offered by such technology. Greater participation by the public can be viewed as a chief indicator of effective government communication. Yet, the level of public participation in government 2.0 is not quite satisfactory. In general, it is still at the early stage in most developing countries, including Saudi Arabia. Although it is a fact that Saudi people are among the most active in using social media, the number of people who use social media to communicate with the public institutions is not high. Furthermore, most of the governmental organisations are not using social media tools to communicate with the public. They use these platforms to disseminate information. Our study focuses on the factors affecting citizens’ adoption of social media in Saudi Arabia. Our research question is: what are the factors affecting Saudi citizens’ use of social media to communicate with the government? To answer this research question, the research aims to validate the UTAUT model for examining social media tools from the citizen perspective. An amendment will be proposed to fit the adoption of social media platforms as a communication channel in government by using a developed conceptual model which integrates constructs from the UTAUT model and others external variables based on the literature review. The set of potential factors that affect these citizens' decisions to adopt social media to communicate with their government has been identified as perceived encouragement, trust and cultural influence. The connection between the above-mentioned constructs from the basis for the research hypothesis will be examined in the light of a quantitative methodology. Data collection will be performed through a survey targeting a number of Saudi citizens who are social media users. The data collected from the primary survey will later be analysed by using statistical methods. The outcomes of this research project are argued to have potential contributions to the fields of social media and e-Government adoption, both on the theoretical and practical levels. It is believed that this research project is the first of its type that attempts to identify the factors that affect citizens’ adoption of social media to communicate with the government. The importance of identifying these factors stems from the potential use of them to enhance the government’s implementation of social media and help in making more accurate decisions and strategies based on comprehending the most important factors that affect citizens’ decisions.

Keywords: social media, adoption, citizen, UTAUT model

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Authors: Boutheina Ben Abdelmoumen Mardassi, Salim Chibani, Safa Boujemaa, Amaury Vaysse, Julien Guglielmini, Elhem Yacoub

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Background and aim: Mycoplasma hominis (MH) is a pathogenic bacterium belonging to the Mollicutes class. It causes a wide range of gynecological infections and infertility among adults. Recently, we have explored for the first time the phylodistribution of Tunisian M. hominis clinical strains using an expanded MLST. We have demonstrated their distinction into two pure lineages, which each corresponding to a specific pathotype: genital infections and infertility. The aim of this project is to gain further insight into the evolutionary dynamics and the specific genetic factors that distinguish MH pathotypes Methods: Whole genome sequencing of Mycoplasma hominis clinical strains was performed using illumina Miseq. Denovo assembly was performed using a publicly available in-house pipeline. We used prokka to annotate the genomes, panaroo to generate the gene presence matrix and Jolytree to establish the phylogenetic tree. We used treeWAS to identify genetic loci associated with the pathothype of interest from the presence matrix and phylogenetic tree. Results: Our results revealed a clear categorization of the 62 MH clinical strains into two distinct genetic lineages, with each corresponding to a specific pathotype.; gynecological infections and infertility[AV1] . Genome annotation showed that GC content is ranging between 26 and 27%, which is a known characteristic of Mycoplasma genome. Housekeeping genes belonging to the core genome are highly conserved among our strains. TreeWas identified 4 virulence genes associated with the pathotype gynecological infection. encoding for asparagine--tRNA ligase, restriction endonuclease subunit S, Eco47II restriction endonuclease, and transcription regulator XRE (involved in tolerance to oxidative stress). Five genes have been identified that have a statistical association with infertility, tow lipoprotein, one hypothetical protein, a glycosyl transferase involved in capsule synthesis, and pyruvate kinase involved in biofilm formation. All strains harbored an efflux pomp that belongs to the family of multidrug resistance ABC transporter, which confers resistance to a wide range of antibiotics. Indeed many adhesion factors and lipoproteins (p120, p120', p60, p80, Vaa) have been checked and confirmed in our strains with a relatively 99 % to 96 % conserved domain and hypervariable domain that represent 1 to 4 % of the reference sequence extracted from gene bank. Conclusion: In summary, this study led to the identification of specific genetic loci associated with distinct pathotypes in M hominis.

Keywords: mycoplasma hominis, infertility, gynecological infections, virulence genes, antibiotic resistance

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Authors: Xiangtuo Chen, Paul-Henry Cournéde

Abstract:

Crop yield prediction is a paramount issue in agriculture. The main idea of this paper is to find out efficient way to predict the yield of corn based meteorological records. The prediction models used in this paper can be classified into model-driven approaches and data-driven approaches, according to the different modeling methodologies. The model-driven approaches are based on crop mechanistic modeling. They describe crop growth in interaction with their environment as dynamical systems. But the calibration process of the dynamic system comes up with much difficulty, because it turns out to be a multidimensional non-convex optimization problem. An original contribution of this paper is to propose a statistical methodology, Multi-Scenarios Parameters Estimation (MSPE), for the parametrization of potentially complex mechanistic models from a new type of datasets (climatic data, final yield in many situations). It is tested with CORNFLO, a crop model for maize growth. On the other hand, the data-driven approach for yield prediction is free of the complex biophysical process. But it has some strict requirements about the dataset. A second contribution of the paper is the comparison of these model-driven methods with classical data-driven methods. For this purpose, we consider two classes of regression methods, methods derived from linear regression (Ridge and Lasso Regression, Principal Components Regression or Partial Least Squares Regression) and machine learning methods (Random Forest, k-Nearest Neighbor, Artificial Neural Network and SVM regression). The dataset consists of 720 records of corn yield at county scale provided by the United States Department of Agriculture (USDA) and the associated climatic data. A 5-folds cross-validation process and two accuracy metrics: root mean square error of prediction(RMSEP), mean absolute error of prediction(MAEP) were used to evaluate the crop prediction capacity. The results show that among the data-driven approaches, Random Forest is the most robust and generally achieves the best prediction error (MAEP 4.27%). It also outperforms our model-driven approach (MAEP 6.11%). However, the method to calibrate the mechanistic model from dataset easy to access offers several side-perspectives. The mechanistic model can potentially help to underline the stresses suffered by the crop or to identify the biological parameters of interest for breeding purposes. For this reason, an interesting perspective is to combine these two types of approaches.

Keywords: crop yield prediction, crop model, sensitivity analysis, paramater estimation, particle swarm optimization, random forest

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Authors: Abdul-Ganiyu Fuseini, Bernice Redley, Helen Rawson, Lenore Lay, Debra Kerr

Abstract:

Aim: The study aimed to develop and validate a culturally appropriate patient-reported outcome measure for measuring dignity for older adults during acute hospital admissions. Design: A three-phased mixed-method sequential exploratory design was used. Methods: Concept elicitation and generation of items for the scale was informed by older adults’ perspectives about dignity during acute hospitalization and a literature review. Content validity evaluation and pre-testing were undertaken using standard instrument development techniques. A cross-sectional survey design was conducted involving 270 hospitalized older adults for evaluation of construct and convergent validity, internal consistency reliability, and test–retest reliability of the scale. Analysis was performed using Statistical Package for the Social Sciences, version 25. Reporting of the study was guided by the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist. Results: We established the 15-item Hospitalized Older Adults’ Dignity Scale that has a 5-factor structure: Shared Decision-Making (3 items); Healthcare Professional-Patient Communication (3 items); Patient Autonomy (4 items); Patient Privacy (2 items); and Respectful Care (3 items). Excellent content validity, adequate construct and convergent validity, acceptable internal consistency reliability, and good test-retest reliability were demonstrated. Conclusion: We established the Hospitalized Older Adults Dignity Scale as a valid and reliable scale to measure dignity for older adults during acute hospital admissions. Future studies using confirmatory factor analysis are needed to corroborate the dimensionality of the factor structure and external validity of the scale. Routine use of the scale may provide information that informs the development of strategies to improve dignity-related care in the future. Impact: The development and validation of the Hospitalized Older Adults Dignity Scale will provide healthcare professionals with a feasible and reliable scale for measuring older adults’ dignity during acute hospitalization. Routine use of the scale may enable the capturing and incorporation of older patients’ perspectives about their healthcare experience and provide information that informs the development of strategies to improve dignity-related care in the future.

Keywords: dignity, older adults, hospitalisation, scale, patients, dignified care, acute care

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Authors: Silas Webb, Joseph Hartland

Abstract:

Background: Long-term retention of patients on ART has become a major health challenge in Sub-Saharan Africa (SSA). In 2010 a systematic review of 39 papers found that 30% of patients were no longer taking their ARTs two years after starting treatment. In the same review, it was noted that there was a paucity of data as to why patients become lost to follow-up (LTFU) in SSA. This project was performed in Mulanje Mission Hospital in Malawi as part of Swindon Academy’s Global Health eSSC. The HIV prevalence for Malawi is 10.3%, one of the highest rates in the world, however prevalence soars to 18% in the Mulanje. Therefore it is essential that patients at risk of being LTFU are identified early and managed appropriately to help them continue to participate in the service. Methodology: All patients on adult antiretroviral formulations at MMH, who were classified as ‘defaulters’ (patients missing a scheduled follow up visit by more than two months) over the last 12 months were included in the study. Demographic varibales were collected from Mastercards for data analysis. A comparison group of patients currently not lost to follow up was created by using all of the patients who attended the HIV clinic between 18th-22nd July 2016 who had never defaulted from ART. Data was analysed using the chi squared (χ²) test, as data collected was categorical, with alpha levels set at 0.05. Results: Overall, 136 patients had defaulted from ART over the past 12 months at MMH. Of these, 43 patients had missing Mastercards, so 93 defaulter datasets were analysed. In the comparison group 93 datasets were also analysed and statistical analysis done using Chi-Squared testing. A higher proportion of men in the defaulting group was noted (χ²=0.034) and defaulters tended to be younger (χ²=0.052). 94.6% of patients who defaulted were taking Tenofovir, Lamivudine and Efavirenz, the standard first line ART therapy in Malawi. The mean length of time on ART was 39.0 months (RR: -22.4-100.4) in the defaulters group and 47.3 months (RR: -19.71-114.23) in the control group, with a mean difference of 8.3 less months in the defaulters group (χ ²=0.056). Discussion: The findings in this study echo the literature, however this review expands on that and shows the demographic for the patient at most risk of defaulting and being LTFU would be: a young male who has missed more than 4 doses of ART and is within his first year of treatment. For the hospital, this data is important at it identifies significant areas for public health focus. For instance, fear of disclosure and stigma may be disproportionately affecting younger men, so interventions can be aimed specifically at them to improve their health outcomes. The mean length of time on medication was 8.3 months less in the defaulters group, with a p-value of 0.056, emphasising the need for more intensive follow-up in the early stages of treatment, when patients are at the highest risk of defaulting.

Keywords: anti-retroviral therapy, ART, HIV, lost to follow up, Malawi

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Authors: Razvan Mercut, Mihaela Ionescu, Vlad Parvanescu, Razvan Ghita, Tudor-Gabriel Caragea, Cristina Simionescu, Marius-Eugen Ciurea

Abstract:

Introduction: Over the past years, the incidence of non-melanoma skin cancer (NMSC) has continuously increased, being one of the most commonly diagnosed carcinomasofthe cephalic extremity. NMSC regroups basal cell carcinoma (BCC), squamous cell carcinoma (SCC), Merkel cell carcinoma, cutaneous lymphoma, and sarcoma. The most common forms are BCC and SCC, both still implying a significant level of morbidity due to local invasion (especially BCC), even if the overall death rates are declining. The objective of our study was the evaluation of clinical and histological aspects of NMSC for a group of patients with BCC and SCC, from Craiova, a south-western major city in Romania. Materialand method: Our study lot comprised 65 patients, with an almost equal distribution of sexes, and ages between 23-91 years old (mean value±standard deviation62.61±16.67), all treated within the Clinic of Plastic Surgery and Reconstructive Microsurgery, Clinical Emergency County Hospital Craiova, Romania, between 2019-2020. In order to determine the main morphological characteristics of both studied cancers, we used paraffin embedding techniques, with various staining methods:hematoxylin-eosin, Masson's trichrome stain with aniline blue, and Periodic acid-schiffAlcian Blue. The statistical study was completed using Microsoft Excel (Microsoft Corp., Redmond, WA, USA), with XLSTAT (Addinsoft SARL, Paris, France). Results: The overall results of our study indicate that BCC accounts for 67.69% of all NMSC forms; SCC covers 27.69%, while 4.62% are representedby other forms. The most frequent site is the nose for BCC (27.69%, 18 patients), being followed by preauricular regions, forehead, and periorbital areas. For patients with SCC, tumors were mainly located at lips level (66.67%, 12 patients). The analysis of NMSC histological forms indicated that nodular BCC is predominant (45.45%, 20 patients), as well as ulcero-vegetant SCC (38.89%, 7 patients). We have not identified any topographic characteristics or NMSC forms significantly related to age or sex. Conclusions: The most frequent NMSC form identified for our study lot was BCC. The preferred location was the nose for BCC. For SCC, the oral cavity is the most frequent anatomical site, especially the lips level. Nodular BCC and ulcero-vegetant SCC were the most commonly identified histological types. Our findings emphasize the need for periodic screening, in order to improve prevention and early treatment for these malignancies.

Keywords: non-melanoma skin cancer, basal cell carcinoma, squamous cell carcinoma, histological

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