Search results for: variable

Authors: Marie-Helena Docherty, Sion Edryd Williams

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The prevalence of diabetes mellitus is increasing worldwide. In Sub-Saharan Africa, type 2 diabetes represents over 90% of all types of diabetes with the number of diabetic patients expected to rise. This represents a huge economic burden in an area already contending with high rates of other significant diseases, including the highest worldwide prevalence of HIV. Diabetic complications considerably impact on morbidity and mortality. The epidemiological data for the region quotes high rates of retinopathy (7-63%), neuropathy (27-66%) and microalbuminuria (10-83%). It is therefore imperative that diabetic screening programmes are established. It is recognised that in many parts of the developing world the implementation and management of such programmes is limited by a lack of available resources. The International Diabetes Federation produced guidelines in 2012 taking these limitations into account suggesting that all diabetic patients should have access to basic screening. These guidelines are consistent with the national diabetic guidelines produced by the Lesotho Medical Council. However, diabetic care in Lesotho is delivered at the local level, with variable levels of quality. A cross sectional study was performed in the outpatient department of Maluti Hospital in Mapoteng, Lesotho, a busy rural hospital in the Berea district. Demographic data on gender, age and modality of treatment were collected over a six-week time period. Information regarding 3 basic screening parameters was obtained. These parameters included eye screening (defined as a documented ophthalmology review within the last 12 months), foot screening (defined as a documented foot health assessment by any health care professional within the last 12 months) and secondary prevention (defined as a documented blood pressure and lipid profile reading within the last 12 months). These parameters were selected on the basis of the absolute minimum level of resources in Maluti Hospital. Renal screening was excluded, as the hospital does not have access to reliable renal profile checks or urinalysis. There is however a fully functioning on-site ophthalmology department run by a senior ophthalmologist with the ability to provide retinal photography, retinal surgery and photocoagulation therapy. Data was collected on 183 type 2 diabetics. 112 patients were male and 71 were female. The average age was 43 years. 4 patients were diet controlled, 140 patients were on oral hypoglycaemic agents (metformin and/or glibenclamide), and 39 patients were on a combination of insulin and oral hypoglycaemics. In the preceding 12 months, 5 patients had undergone eye screening (3%), 24 patients had undergone foot screening (13%), and 31 patients had lipid profile testing (17%). All patients had a documented blood pressure reading (100%). Our results show that screening is poorly performed in the basic indicators suggested by the IDF and the Lesotho Medical Council. On the basis of these results, a screening programme was developed using the mnemonic SaFE; secondary prevention, foot and eye care. This is simple, memorable and transferable between healthcare professionals. In the future, the expectation would be to expand upon this current programme to include renal screening, and to further develop screening pertaining to secondary prevention.

Keywords: Africa, complications, rural, screening

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Authors: Diana Reckien

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Vulnerability assessments are increasingly used to support policy-making in complex environments, like urban areas. Usually, vulnerability studies include the construction of aggregate (sub-) indices and the subsequent mapping of indices across an area of interest. Vulnerability studies show a couple of advantages: they are great communication tools, can inform a wider general debate about environmental issues, and can help allocating and efficiently targeting scarce resources for adaptation policy and planning. However, they also have a number of challenges: Vulnerability assessments are constructed on the basis of a wide range of methodologies and there is no single framework or methodology that has proven to serve best in certain environments, indicators vary highly according to the spatial scale used, different variables and metrics produce different results, and aggregate or composite vulnerability indicators that are mapped easily distort or bias the picture of vulnerability as they hide the underlying causes of vulnerability and level out conflicting reasons of vulnerability in space. So, there is urgent need to further develop the methodology of vulnerability studies towards a common framework, which is one reason of the paper. We introduce a social vulnerability approach, which is compared with other approaches of bio-physical or sectoral vulnerability studies relatively developed in terms of a common methodology for index construction, guidelines for mapping, assessment of sensitivity, and verification of variables. Two approaches are commonly pursued in the literature. The first one is an additive approach, in which all potentially influential variables are weighted according to their importance for the vulnerability aspect, and then added to form a composite vulnerability index per unit area. The second approach includes variable reduction, mostly Principal Component Analysis (PCA) that reduces the number of variables that are interrelated into a smaller number of less correlating components, which are also added to form a composite index. We test these two approaches of constructing indices on the area of New York City as well as two different metrics of variables used as input and compare the outcome for the 5 boroughs of NY. Our analysis yields that the mapping exercise yields particularly different results in the outer regions and parts of the boroughs, such as Outer Queens and Staten Island. However, some of these parts, particularly the coastal areas receive the highest attention in the current adaptation policy. We imply from this that the current adaptation policy and practice in NY might need to be discussed, as these outer urban areas show relatively low social vulnerability as compared with the more central parts, i.e. the high dense areas of Manhattan, Central Brooklyn, Central Queens and the Southern Bronx. The inner urban parts receive lesser adaptation attention, but bear a higher risk of damage in case of hazards in those areas. This is conceivable, e.g., during large heatwaves, which would more affect more the inner and poorer parts of the city as compared with the outer urban areas. In light of the recent planning practice of NY one needs to question and discuss who in NY makes adaptation policy for whom, but the presented analyses points towards an under representation of the needs of the socially vulnerable population, such as the poor, the elderly, and ethnic minorities, in the current adaptation practice in New York City.

Keywords: vulnerability mapping, social vulnerability, additive approach, Principal Component Analysis (PCA), New York City, United States, adaptation, social sensitivity

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Authors: N. K. Ambujam, V. Sudha

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Reservoirs are being contaminated all around the world with point source and Non-Point Source (NPS) pollution. The most common NPS pollutants are sediments and nutrients. Krishnagiri Reservoir (KR) has been chosen for the present case study, which is located in the tropical semi-arid climatic zone of Tamil Nadu, South India. It is the main source of surface water in Krishnagiri district to meet the freshwater demands. The reservoir has lost about 40% of its water holding capacity due to sedimentation over the period of 50 years. Hence, from the research and management perspective, there is a need for a sound knowledge on the spatial and seasonal variations of KR water quality. The present study encompasses the specific objectives as (i) to investigate the longitudinal heterogeneity and seasonal variations of physicochemical parameters, nutrients and biological characteristics of KR water and (ii) to examine the extent of degradation of water quality in KR. 15 sampling points were identified by uniform stratified method and a systematic monthly sampling strategy was selected due to high dynamic nature in its hydrological characteristics. The physicochemical parameters, major ions, nutrients and Chlorophyll a (Chl a) were analysed. Trophic status of KR was classified by using Carlson's Trophic State Index (TSI). All statistical analyses were performed by using Statistical Package for Social Sciences programme, version-16.0. Spatial maps were prepared for Chl a using Arc GIS. Observations in KR pointed out that electrical conductivity and major ions are highly variable factors as it receives inflow from the catchment with different land use activities. The study of major ions in KR exhibited different trends in their values and it could be concluded that as the monsoon progresses the major ions in the water decreases or water quality stabilizes. The inflow point of KR showed comparatively higher concentration of nutrients including nitrate, soluble reactive phosphorus (SRP), total phosphors (TP), total suspended phosphorus (TSP) and total dissolved phosphorus (TDP) during monsoon seasons. This evidently showed the input of significant amount of nutrients from the catchment side through agricultural runoff. High concentration of TDP and TSP at the lacustrine zone of the reservoir during summer season evidently revealed that there was a significant release of phosphorus from the bottom sediments. Carlson’s TSI of KR ranged between 81 and 92 during northeast monsoon and summer seasons. High and permanent Cyanobacterial bloom in KR could be mainly due to the internal loading of phosphorus from the bottom sediments. According to Carlson’s TSI classification Krishnagiri reservoir was ranked in the hyper-eutrophic category. This study provides necessary basic data on the spatio-temporal variations of water quality in KR and also proves the impact of point and NPS pollution from the catchment area. High TSI warrants a greater threat for the recovery of internal P loading and hyper-eutrophic condition of KR. Several expensive internal measures for the reduction of internal loading of P were introduced by many scientists. However, the outcome of the present research suggests for the innovative algae harvesting technique for the removal of sediment nutrients.

Keywords: NPS pollution, nutrients, hyper-eutrophication, krishnagiri reservoir

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Authors: Juliana A. B. Silva, Caio H. T. L. Albuquerque, Leonardo L. dos Santos, Cristiane K. Oliveira, Ivani Malvestiti, Fernando Hallwass, Ricardo L. Longo

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Complexes with lanthanide ions have been extensively studied due to their applications as luminescent, magnetic and catalytic materials as molecular or extended crystals, thin films, glasses, polymeric matrices, ionic liquids, and in solution. NMR chemical shift data in solution have been reported and suggest fluxional structures in a wide range of coordination compounds with rare earth ions. However, the fluxional mechanisms for these compounds are still not established. This structural fluxionality may affect the photophysical, catalytic and magnetic properties in solution. Thus, understanding the structural interconversion mechanisms may aid the design of coordination compounds with, for instance, improved (electro)luminescence, catalytic and magnetic behaviors. The [Eu(btfa)₃bipy] complex, where btfa= 4,4,4-trifluoro-1-phenyl-1,3-butanedionate and bipy= 2,2’-bipiridyl, has a well-defined X-ray crystallographic structure and preliminary 1H NMR data suggested a structural fluxionality. Thus, we have investigated a series of coordination compounds with lanthanide ions [Ln(btfa)₃L], where Ln = La, Eu, Gd or Yb and L= bipy or phen (phen=1,10-phenanthroline) using a combined theoretical-experimental approach. These complexes were synthesized and fully characterized, and detailed NMR measurements were obtained. They were also studied by quantum chemical computational methods (DFT-PBE0). The aim was to determine the relevant factors in the structure of these compounds that favor or not the fluxional behavior. Measurements of the 1H NMR signals at variable temperature in CD₂Cl₂ of the [Eu(btfa)₃L] complexes suggest that these compounds have a fluxional structure, because the crystal structure has non-equivalent btfa ligands that should lead to non-equivalent hydrogen atoms and thus to more signals in the NMR spectra than those obtained at room temperature, where all hydrogen atoms of the btfa ligands are equivalent, and phen ligand has an effective vertical symmetry plane. For the [Eu(btfa)₃bipy] complex, the broadening of the signals at –70°C provides a lower bound for the coalescence temperature, which indicates the energy barriers involved in the structural interconversion mechanisms are quite small. These barriers and, consequently, the coalescence temperature are dependent upon the radii of the lanthanide ion as well as to their paramagnetic effects. The PBE0 calculated structures are in very good agreement with the crystallographic data and, for the [Eu(btfa)₃bipy] complex, this method provided several distinct structures with almost the same energy. However, the energy barrier for structural interconversion via dissociative pathways were found to be quite high and could not explain the experimental observations. Whereas the pseudo-rotation pathways, involving the btfa and bipy ligands, have very small activation barriers, in excellent agreement with the NMR data. The results also showed an increase in the activation barrier along the lanthanide series due to the decrease of the ionic radii and consequent increase of the steric effects. TD-DFT calculations showed a dependence of the ligand donor state energy with different structures of the complex [Eu(btfa)₃phen], which can affect the energy transfer rates and the luminescence. The energy required to promote the structural fluxionality may also enhance the luminescence quenching in solution. These results can aid in the design of more luminescent compounds and more efficient devices.

Keywords: computational chemistry, lanthanide-based compounds, NMR, structural fluxionality

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Authors: Nitin Bhagat

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Drought is a global phenomenon. It has a huge impact on agriculture and allied sector activities. Agriculture plays a substantial role in the economy of developing countries, which mainly depends on rainfall. The present study illustrates the drought conditions in Masurdi village of Latur district in the Marathwada region, Maharashtra. This paper is based on both primary as well as secondary data sources. The multistage sample method was used for primary data collection. The 100 households sample survey data has been collected from the village through a semi-structured questionnaire. The crop production data is collected from the Department of Agriculture, Government of Maharashtra. The rainfall data is obtained from the Department of Revenue, Office of Divisional Commissioner, Aurangabad for the period from 1988 to 2018. This paper examines the severity of drought consequences of the 2015 drought on domestic water supply, crop production, and the effect on children's schooling, livestock assets, bank credit, and migration. The study also analyzed climate variables' impact on the Latur district's total food grain production for 19 years from 2000 to 2018. This study applied multiple regression analysis to check the relationship between climatic variables and the Latur district's total food grain production. The climate variables are annual rainfall, maximum temperature and minimum temperature. The study considered that climatic variables are independent variables and total food grain as the dependent variable. It shows there is a significant relationship between rainfall and maximum temperature. The study also calculated rainfall deviations to find out the drought and normal years. According to drought manual 2016, the rainfall deviation calculated using the following formula. RF dev = {(RFi – RFn) / RFn}*100.Approximately 27.43 % of the workforce migrated from rural to urban areas for searching jobs, and crop production decreased tremendously due to inadequate rainfall in the drought year 2015. Many farm and non-farm labor, some marginal and small cultivators, migrated from rural to urban areas (like Pune, Mumbai, and Western Maharashtra).About 48 % of the households' children faced education difficulties; in the drought period, children were not going to school. They left their school and joined to bring water with their mother and fathers, sometimes they fetched water on their head or using a bicycle, near about 2 km from the village. In their school-going days, drinking water was not available in their schools, so the government declared holidays early in the academic education year 2015-16 compared to another academic year. Some college and 10th class students left their education due to financial problems. Many households benefited from state government schemes, like drought subsidies, crop insurance, and bank loans. Out of 100 households, about 50 (50 %) have obtained financial support from the state government’s subsidy scheme, 58 ( 58 %) have got crop insurance, and 41(41 %) irrigated households have got bank loans from national banks; besides that, only two families have obtained loans from their relatives and moneylenders.

Keywords: agriculture, drought, household, rainfall

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Authors: Monica Arnaudo, Monika Topel, Bjorn Laumert

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Within the Swedish context, the current trend of relatively low electricity prices promotes the electrification of the energy infrastructure. The residential heating sector takes part in this transition by proposing a switch from a centralized district heating system towards a distributed heat pumps-based setting. When it comes to urban environments, two issues arise. The first, seen from an electricity-sector perspective, is related to the fact that existing networks are limited with regards to their installed capacities. Additional electric loads, such as heat pumps, can cause severe overloads on crucial network elements. The second, seen from a heating-sector perspective, has to do with the fact that the indoor comfort conditions can become difficult to handle when the operation of the heat pumps is limited by a risk of overloading on the distribution grid. Furthermore, the uncertainty of the electricity market prices in the future introduces an additional variable. This study aims at assessing the extent to which distributed heat pumps can penetrate an existing heat energy network while respecting the technical limitations of the electricity grid and the thermal comfort levels in the buildings. In order to account for the multi-disciplinary nature of this research question, a cosimulation modeling approach was adopted. In this way, each energy technology is modeled in its customized simulation environment. As part of the cosimulation methodology: a steady-state power flow analysis in pandapower was used for modeling the electrical distribution grid, a thermal balance model of a reference building was implemented in EnergyPlus to account for space heating and a fluid-cycle model of a heat pump was implemented in JModelica to account for the actual heating technology. With the models set in place, different scenarios based on forecasted electricity market prices were developed both for present and future conditions of Hammarby Sjöstad, a neighborhood located in the south-east of Stockholm (Sweden). For each scenario, the technical and the comfort conditions were assessed. Additionally, the average cost of heat generation was estimated in terms of levelized cost of heat. This indicator enables a techno-economic comparison study among the different scenarios. In order to evaluate the levelized cost of heat, a yearly performance simulation of the energy infrastructure was implemented. The scenarios related to the current electricity prices show that distributed heat pumps can replace the district heating system by covering up to 30% of the heating demand. By lowering of 2°C, the minimum accepted indoor temperature of the apartments, this level of penetration can increase up to 40%. Within the future scenarios, if the electricity prices will increase, as most likely expected within the next decade, the penetration of distributed heat pumps can be limited to 15%. In terms of levelized cost of heat, a residential heat pump technology becomes competitive only within a scenario of decreasing electricity prices. In this case, a district heating system is characterized by an average cost of heat generation 7% higher compared to a distributed heat pumps option.

Keywords: cosimulation, distributed heat pumps, district heating, electrical distribution grid, integrated energy systems

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Authors: Catherine S. Fichten, Tali Heiman, Mary Jorgensen, Mai Nhu Nguyen, Rhonda Amsel, Dorit Olenik-Shemesh

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The study examined Canadian and Israeli students' perceptions related to their intention to graduate from their program of studies. Canada and Israel are dissimilar in many ways that affect education, including language and alphabet. In addition, the postsecondary education systems differ. For example, in some parts of Canada (e.g., in Quebec, Canada’s 2nd largest province), students matriculate after 11 years of high school; in Israel, this typically occurs after 12 years. In addition, Quebec students attend two compulsory years of junior college before enrolling in a three-year university Bachelor program; in Israel students enroll in a three-year Bachelor program directly after matriculation. In addition, Israeli students typically enroll in the army shortly after high school graduation; in Canada, this is not the case. What the two countries do have in common is concern about the success of postsecondary students with disabilities. The present study was based on Ajzen’s Theory of Planned Behavior (TPB); the model suggests that behavior is influenced by Intention to carry it out. This, in turn, is predicted by the following correlated variables: Perceived Behavioral Control (i.e., ease or difficulty enacting the behavior - in this case graduation), Subjective Norms (i.e., perceived social/peer pressure from individuals important in the student’s life), and Attitude (i.e., positive or negative evaluation of graduation). A questionnaire was developed to test the TPB in previous Canadian studies and administered to 845 Canadian college students (755 nondisabled, 90 with LD/ADHD) who had completed at least one semester of studies) and to 660 Israeli university students enrolled in a Bachelor’s program (537 nondisabled, 123 with LD/ADHD). Because Israeli students were older than Canadian students we covaried age in SPSS-based ANOVA comparisons and included it in regression equations. Because females typically have better academic outcomes than males, gender was included in all analyses. ANOVA results indicate only a significant gender effect for Intention to graduate, with females having higher scores. Four stepwise regressions were conducted, with Intention to graduate as the predicted variable, and Gender and the three TPB predictors as independent variables (separate analyses for Israeli and Canadian samples with and without LD/ADHD). Results show that for samples with LD/ADHD, although Gender and Age were not significant predictors, the TPB predictors were, with all three TPB predictors being significant for the Canadian sample (i.e., Perceived Behavioral Control, Subjective Norms, Attitude, R2=.595), and two of the three (i.e., Perceived Behavioral Control, Subjective Norms) for the Israeli sample (R2=.528). For nondisabled students, the results for both countries show that all three TPB predictors were significant along with Gender: R2=.443 for Canada and R2=.332 for Israel; age was not significant. Our findings show that despite vast differences between our Canadian and Israeli samples, Intention to graduate was related to the three TPB predictors. This suggests that our TPB measure is valid for diverse samples and countries that it can be used as a quick, inexpensive way to predict graduation rates, and that strengthening the three predictor variables may result in higher graduation rates.

Keywords: disability, higher education, students, theory of planned behavior

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Authors: Nahla Elsherbiny, Ahmed Ahmed, Hamada Mohammed, Mohamed Ali

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Background: The enterococci may be considered as opportunistic agents particularly in immunocompromised patients. It is one of the top three pathogens causing many healthcare associated infections (HAIs). Resistance to several commonly used antimicrobial agents is a remarkable characteristic of most species which may carry various genes contributing to virulence. Objectives: to determine the prevalence of enterococci species in different intensive care units (ICUs) causing health care-associated infections (HAIs), intestinal carriage and environmental contamination. Also, to study the antimicrobial susceptibility pattern of the isolates with special reference to vancomycin resistance. In addition to phenotypic and genotypic detection of gelatinase, cytolysin and biofilm formation among isolates. Patients and Methods: This study was carried out in the infection control laboratory at Assiut University Hospitals over a period of one year. Clinical samples were collected from 285 patients with various (HAIs) acquired after admission to different ICUs. Rectal swabs were taken from 14 cases for detection of enterococci carriage. In addition, 1377 environmental samples were collected from the surroundings of the patients. Identification was done by conventional bacteriological methods and confirmed by analytical profile index (API). Antimicrobial sensitivity testing was performed by Kirby Bauer disc diffusion method and detection of vancomycin resistance was done by agar screen method. For the isolates, phenotypic detection of cytolysin, gelatinase production and detection of biofilm by tube method, Congo red method and microtiter plate. We performed polymerase chain reaction (PCR) for detection of some virulence genes (gelE, cylA, vanA, vanB and esp). Results: Enterococci caused 10.5% of the HAIs. Respiratory tract infection was the predominant type (86.7%). The commonest species were E.gallinarum (36.7%), E.casseliflavus (30%), E.faecalis (30%), and E.durans (3.4 %). Vancomycin resistance was detected in a total of 40% (12/30) of those isolates. The risk factors associated with acquiring vancomycin resistant enterococci (VRE) were immune suppression (P= 0.031) and artificial feeding (P= 0.008). For the rectal swabs, enterococci species were detected in 71.4% of samples with the predominance of E. casseliflavus (50%). Most of the isolates were vancomycin resistant (70%). Out of a total 1377 environmental samples, 577 (42%) samples were contaminated with different microorganisms. Enterococci were detected in 1.7% (10/577) of total contaminated samples, 50% of which were vancomycin resistant. All isolates were resistant to penicillin, ampicillin, oxacillin, ciprofloxacin, amikacin, erythromycin, clindamycin and trimethoprim-sulfamethaxazole. For the remaining antibiotics, variable percentages of resistance were reported. Cytolysin and gelatinase were detected phenotypically in 16% and 48 % of the isolates respectively. The microtiter plate method showed the highest percentages of detection of biofilm among all isolated species (100%). The studied virulence genes gelE, esp, vanA and vanB were detected in 62%, 12%, 2% and 12% respectively, while cylA gene was not detected in any isolates. Conclusions: A significant percentage of enterococci was isolated from patients and environments in the ICUs. Many virulence factors were detected phenotypically and genotypically among isolates. The high percentage of resistance, coupled with the risk of cross transmission to other patients make enterococci infections a significant infection control issue in hospitals.

Keywords: antimicrobial resistance, enterococci, ICUs, virulence factors

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Authors: Alex J. Summers, Jasmine P. Devadhasan, Douglas Montgomery, Brittany Fischer, Jian Gu, Frederic Zenhausern

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Immunoassays have been utilized for several applications, including the detection of pathogens. Our laboratory is in the development of a tier 1 biothreat panel utilizing Vertical Flow Assay (VFA) technology for simultaneous detection of pathogens and toxins. One method of manufacturing VFA membranes is with non-contact piezoelectric dispensing, which provides advantages, such as low-volume and rapid dispensing without compromising the structural integrity of antibody or substrate. Challenges of this processinclude premature discontinuation of dispensing and misaligned spotting. Preliminary data revealed the Yp 11C7 mAb (11C7)reagent to exhibit a large angle of failure during printing which may have contributed to variable printing outputs. A Design of Experiment (DOE) was executed using this reagent to investigate the effects of hydrostatic pressure and reagent concentration on microarray printing outputs. A Nano-plotter 2.1 (GeSIM, Germany) was used for printing antibody reagents ontonitrocellulose membrane sheets in a clean room environment. A spotting plan was executed using Spot-Front-End software to dispense volumes of 11C7 reagent (20-50 droplets; 1.5-5 mg/mL) in a 6-test spot array at 50 target membrane locations. Hydrostatic pressure was controlled by raising the Pressure Compensation Vessel (PCV) above or lowering it below our current working level. It was hypothesized that raising or lowering the PCV 6 inches would be sufficient to cause either liquid accumulation at the tip or discontinue droplet formation. After aspirating 11C7 reagent, we tested this hypothesis under stroboscope.75% of the effective raised PCV height and of our hypothesized lowered PCV height were used. Humidity (55%) was maintained using an Airwin BO-CT1 humidifier. The number and quality of membranes was assessed after staining printed membranes with dye. The droplet angle of failure was recorded before and after printing to determine a “stroboscope score” for each run. The DOE set was analyzed using JMP software. Hydrostatic pressure and reagent concentration had a significant effect on the number of membranes output. As hydrostatic pressure was increased by raising the PCV 3.75 inches or decreased by lowering the PCV -4.5 inches, membrane output decreased. However, with the hydrostatic pressure closest to equilibrium, our current working level, membrane output, reached the 50-membrane target. As the reagent concentration increased from 1.5 to 5 mg/mL, the membrane output also increased. Reagent concentration likely effected the number of membrane output due to the associated dispensing volume needed to saturate the membranes. However, only hydrostatic pressure had a significant effect on stroboscope score, which could be due to discontinuation of dispensing, and thus the stroboscope check could not find a droplet to record. Our JMP predictive model had a high degree of agreement with our observed results. The JMP model predicted that dispensing the highest concentration of 11C7 at our current PCV working level would yield the highest number of quality membranes, which correlated with our results. Acknowledgements: This work was supported by the Chemical Biological Technologies Directorate (Contract # HDTRA1-16-C-0026) and the Advanced Technology International (Contract # MCDC-18-04-09-002) from the Department of Defense Chemical and Biological Defense program through the Defense Threat Reduction Agency (DTRA).

Keywords: immunoassay, microarray, design of experiment, piezoelectric dispensing

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Authors: Juan A. Arzate, Funda C. Ertem, M. Nicolas Cruz-Bournazou, Peter Neubauer, Stefan Junne

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— One of the biggest challenges the world faces today is global warming that is caused by greenhouse gases (GHGs) coming from the combustion of fossil fuels for energy generation. In order to mitigate climate change, the European Union has committed to reducing GHG emissions to 80–95% below the level of the 1990s by the year 2050. Renewable technologies are vital to diminish energy-related GHG emissions. Since water and biomass are limited resources, the largest contributions to renewable energy (RE) systems will have to come from wind and solar power. Nevertheless, high proportions of fluctuating RE will present a number of challenges, especially regarding the need to balance the variable energy demand with the weather dependent fluctuation of energy supply. Therefore, biogas plants in this content would play an important role, since they are easily adaptable. Feedstock availability varies locally or seasonally; however there is a lack of knowledge in how biogas plants should be operated in a stable manner by local feedstock. This problem may be prevented through suitable control strategies. Such strategies require the development of convenient mathematical models, which fairly describe the main processes. Modelling allows us to predict the system behavior of biogas plants when different feedstocks are used with different loading rates. Life cycle assessment (LCA) is a technique for analyzing several sides from evolution of a product till its disposal in an environmental point of view. It is highly recommend to use as a decision making tool. In order to achieve suitable strategies, the combination of a flexible energy generation provided by biogas plants, a secure production process and the maximization of the environmental benefits can be obtained by the combination of process modelling and LCA approaches. For this reason, this study focuses on the biogas plant which flexibly generates required energy from the co-digestion of maize, grass and cattle manure, while emitting the lowest amount of GHG´s. To achieve this goal AMOCO model was combined with LCA. The program was structured in Matlab to simulate any biogas process based on the AMOCO model and combined with the equations necessary to obtain climate change, acidification and eutrophication potentials of the whole production system based on ReCiPe midpoint v.1.06 methodology. Developed simulation was optimized based on real data from operating biogas plants and existing literature research. The results prove that AMOCO model can successfully imitate the system behavior of biogas plants and the necessary time required for the process to adapt in order to generate demanded energy from available feedstock. Combination with LCA approach provided opportunity to keep the resulting emissions from operation at the lowest possible level. This would allow for a prediction of the process, when the feedstock utilization supports the establishment of closed material circles within a smart bio-production grid – under the constraint of minimal drawbacks for the environment and maximal sustainability.

Keywords: AMOCO model, GHG emissions, life cycle assessment, modelling

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Authors: Yagmur Soylu, Emir Ozeren, Erol Esen, Digdem M. Siyez, Ozlem Belkis, Ezgi Burc, Gülce Demirgurz

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The aim of the study is to determine the predictive power of personal growth initiative, socio-demographic variables (such as sex, grade, and working condition) on career adaptability and optimism of bachelor students in Dokuz Eylul University in Turkey. According to career construction theory, career adaptability is viewed as a psychosocial construct, which refers to an individual’s resources for dealing with current and expected tasks, transitions and traumas in their occupational roles. Career optimism is defined as positive results for future career development of individuals in the expectation that it will achieve or to put the emphasis on the positive aspects of the event and feel comfortable about the career planning process. Personal Growth Initiative (PGI) is defined as being proactive about one’s personal development. Additionally, personal growth is defined as the active and intentional engagement in the process of personal. A study conducted on college students revealed that individuals with high self-development orientation make more effort to discover the requirements of the profession and workspaces than individuals with low levels of personal development orientation. University life is a period that social relations and the importance of academic activities are increased, the students make efforts to progress through their career paths and it is also an environment that offers opportunities to students for their self-realization. For these reasons, personal growth initiative is potentially an important variable which has a key role for an individual during the transition phase from university to the working life. Based on the review of the literature, it is expected that individual’s personal growth initiative, sex, grade, and working condition would significantly predict one’s career adaptability. In the relevant literature, it can be seen that there are relatively few studies available on the career adaptability and optimism of university students. Most of the existing studies have been carried out with limited respondents. In this study, the authors aim to conduct a comprehensive research with a large representative sample of bachelor students in Dokuz Eylul University, Izmir, Turkey. By now, personal growth initiative and career development constructs have been predominantly discussed in western contexts where individualistic tendencies are likely to be seen. Thus, the examination of the same relationship within the context of Turkey where collectivistic cultural characteristics can be more observed is expected to offer valuable insights and provide an important contribution to the literature. The participants in this study were comprised of 1500 undergraduate students being included from thirteen faculties in Dokuz Eylul University. Stratified and random sampling methods were adopted for the selection of the participants. The Personal Growth Initiative Scale-II and Career Futures Inventory were used as the major measurement tools. In data analysis stage, several statistical analysis concerning the regression analysis, one-way ANOVA and t-test will be conducted to reveal the relationships of the constructs under investigation. At the end of this project, we will be able to determine the level of career adaptability and optimism of university students at varying degrees so that a fertile ground is likely to be created to carry out several intervention techniques to make a contribution to an emergence of a healthier and more productive youth generation in psycho-social sense.

Keywords: career optimism, career adaptability, personal growth initiative, university students

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Authors: Winnie Kung, Xinhua Liu, Debbie Huang, Patricia Kim, Keon Kim, Xiaoran Wang, Lawrence Yang

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Considerable Asian Americans were exposed to the World Trade Center attack due to the proximity of the site to Chinatown and a sizeable number of South Asians working in the collapsed and damaged buildings nearby. Few studies focused on Asians in examining the disaster’s mental health impact, and even less longitudinal studies were reported beyond the first couple of years after the event. Based on the World Trade Center Health Registry, this study examined the trajectory of PTSD of individuals directly exposed to the attack from 2-3 to 5-6 years after the attack, comparing Asians against the non-Hispanic White group. Participants included 2,431 Asians and 31,455 Whites. Trajectories were delineated into the resilient, chronic, delayed-onset and remitted groups using PTSD checklist cut-off score at 44 at the 2 waves. Logistic regression analyses were conducted to compare the poorer trajectories against the resilient as a reference group, using predictors of baseline sociodemographic, exposure to the disaster, lower respiratory symptoms and previous depression/anxiety disorder diagnosis, and recruitment source as the control variable. Asians had significant lower socioeconomic status in terms of income, education and employment status compared to Whites. Over 3/4 of participants from both races were resilient, though slightly less for Asians than Whites (76.5% vs 79.8%). Asians had a higher proportion with chronic PTSD (8.6% vs 7.4%) and remission (5.9% vs 3.4%) than Whites. A considerable proportion of participants had delayed-onset in both races (9.1% Asians vs 9.4% Whites). The distribution of trajectories differed significantly by race (p<0.0001) with Asians faring poorer. For Asians, in the chronic vs resilient group, significant protective factors included age >65, annual household income >$50,000, and never married vs married/cohabiting; risk factors were direct disaster exposure, job loss due to 9/11, lost someone, and tangible loss; lower respiratory symptoms and previous mental disorder diagnoses. Similar protective and risk factors were noted for the delayed-onset group, except education being protective; and being an immigrant a risk. Between the 2 comparisons, the chronic group was more vulnerable than the delayed-onset as expected. It should also be noted that in both comparisons, Asians’ current employment status had no significant impact on their PTSD trajectory. Comparing between Asians against Whites, the direction of the relationships between the predictors and the PTSD trajectories were mostly the same, although more factors were significant for Whites than for Asians. A few factors showed significant racial difference: Higher risk for lower respiratory symptoms for Whites than Asians, higher risk for pre-9/11 mental disorder diagnosis for Asians than Whites, and immigrant a risk factor for the remitted vs resilient groups for Whites but not for Asians. Over 17% Asians still suffered from PTSD 5-6 years after the WTC attack signified its persistent impact which incurred substantial human, social and economic costs. The more disadvantaged socioeconomic status of Asians rendered them more vulnerable in their mental health trajectories relative to Whites. Together with their well-documented low tendency to seek mental health help, outreach effort to this population is needed to ensure follow-up treatment and prevention.

Keywords: PTSD, Asian Americans, World Trade Center Attack, racial differences

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Authors: Turky Al-Qahtani, Roustem Miftahof

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Introduction: Under common assumptions of excitabi-lity, morphological (cellular) homogeneity, and spatial structural anomalies added as required, it has been shown that biological systems are able to display travelling wave dynamics. Being not self-sustainable, existence depends on the electrophysiological state of transmembrane ion channels and it requires an extrinsic/intrinsic periodic source. However, organs in the body are highly multicellular, heterogeneous, and their functionality is the outcome of electro-mechanical conjugation, rather than excitability only. Thus, peristalsis in the gut relies on spatiotemporal myoelectrical pattern formations between the mechanical, represented by smooth muscle cells (SM), and the control, comprised of a chain of primary sensory and motor neurones, components. Synaptically linked through the afferent and efferent pathways, they form a functional unit (FU) of the gut. Aims: These are: i) to study numerically the complex dynamics, and ii) to investigate the possibility of self-sustained myoelectrical activity in the FU. Methods: The FU recreates the following sequence of physiological events: deformation of mechanoreceptors of located in SM; generation and propagation of electrical waves of depolarisation - spikes - along the axon to the soma of the primary neurone; discharge of the primary neurone and spike propagation towards the motor neurone; burst of the motor neurone and transduction of spikes to SM, subsequently producing forces of contraction. These are governed by a system of nonlinear partial and ordinary differential equations being a modified version of the Hodgkin-Huxley model and SM fibre mechanics. In numerical experiments; the source of excitation is mechanical stretches of SM at a fixed amplitude and variable frequencies. Results: Low frequency (0.5 < v < 2 Hz) stimuli cause the propagation of spikes in the neuronal chain and, finally, the generation of active forces by SM. However, induced contractions are not sufficient to initiate travelling wave dynamics in the control system. At frequencies, 2 < v < 4 Hz, multiple low amplitude and short-lasting contractions are observed in SM after the termination of stretching. For frequencies (0.5 < v < 4 Hz), primary and sensory neurones demonstrate strong connectivity and coherent electrical activity. Significant qualitative and quantitative changes in dynamics of myoelectical patterns with a transition to a self-organised mode are recorded with the high degree of stretches at v = 4.5 Hz. Increased rates of deformation lead to the production of high amplitude signals at the mechanoreceptors with subsequent self-sustained excitation within the neuronal chain. Remarkably, the connection between neurones weakens resulting in incoherent firing. Further increase in a frequency of stimulation (v > 4.5 Hz) has a detrimental effect on the system. The mechanical and control systems become disconnected and exhibit uncoordinated electromechanical activity. Conclusion: To our knowledge, the existence of periodic activity in a multicellular, functionally heterogeneous biological system with mechano-electrical dynamics, such as the FU, has been demonstrated for the first time. These findings support the notion of possible peristalsis in the gut even in the absence of intrinsic sources - pacemaker cells. Results could be implicated in the pathogenesis of intestinal dysrythmia, a medical condition associated with motor dysfunction.

Keywords: complex dynamics, functional unit, the gut, dysrythmia

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Authors: Denise De Fátima Fernandes Barbosa, Tyane Mayara Ferreira Oliveira, Diego Jorge Maia Lima, Paula Renata Amorim Lessa, Ana Karina Bezerra Pinheiro, Cintia Gondim Pereira Calou, Glauberto Da Silva Quirino, Hellen Lívia Oliveira Catunda, Tatiana Gomes Guedes, Nicolau Da Costa

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The aim of this study is to evaluate the use of Digital Cervicography (DC) in the diagnosis of precancerous lesions related to Human Papillomavirus (HPV). Cross-sectional study with a quantitative approach, of evaluative type, held in a health unit linked to the Pro Dean of Extension of the Federal University of Ceará, in the period of July to August 2015 with a sample of 33 women. Data collecting was conducted through interviews with enforcement tool. Franco (2005) standardized the technique used for DC. Polymerase Chain Reaction (PCR) was performed to identify high-risk HPV genotypes. DC were evaluated and classified by 3 judges. The results of DC and PCR were classified as positive, negative or inconclusive. The data of the collecting instruments were compiled and analyzed by the software Statistical Package for Social Sciences (SPSS) with descriptive statistics and cross-references. Sociodemographic, sexual and reproductive variables were analyzed through absolute frequencies (N) and their respective percentage (%). Kappa coefficient (κ) was applied to determine the existence of agreement between the DC of reports among evaluators with PCR and also among the judges about the DC results. The Pearson's chi-square test was used for analysis of sociodemographic, sexual and reproductive variables with the PCR reports. It was considered statistically significant (p<0.05). Ethical aspects of research involving human beings were respected, according to 466/2012 Resolution. Regarding the socio-demographic profile, the most prevalent ages and equally were those belonging to the groups 21-30 and 41-50 years old (24.2%). The brown color was reported in excess (84.8%) and 96.9% out of them had completed primary and secondary school or studying. 51.5% were married, 72.7% Catholic, 54.5% employed and 48.5% with income between one and two minimum wages. As for the sexual and reproductive characteristics, prevailed heterosexual (93.9%) who did not use condoms during sexual intercourse (72.7%). 51.5% had a previous history of Sexually Transmitted Infection (STI), and HPV the most prevalent STI (76.5%). 57.6% did not use contraception, 78.8% underwent examination Cancer Prevention Uterus (PCCU) with shorter time interval or equal to one year, 72.7% had no cases of Cervical Cancer in the family, 63.6% were multiparous and 97% were not vaccinated against HPV. DC identified good level of agreement between raters (κ=0.542), had a specificity of 77.8% and sensitivity of 25% when compared their results with PCR. Only the variable race showed a statistically significant association with CRP (p=0.042). DC had 100% acceptance amongst women in the sample, revealing the possibility of other experiments in using this method so that it proves as a viable technique. The DC positivity criteria were developed by nurses and these professionals also perform PCCU in Brazil, which means that DC can be an important complementary diagnostic method for the appreciation of these professional’s quality of examinations.

Keywords: gynecological examination, human papillomavirus, nursing, papillomavirus infections, uterine lasmsneop

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Authors: Kyriaki Hatziagapiou, Konstantinos Bethanis, Olti Nikola, Elias Christoforides, Eleni Koniari, Eleni Kakouri, George Lambrou, Christina Kanaka-Gantenbein

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Glioblastoma multiforme (GBM) remains a serious health challenge, as current therapeutic modalities continue to yield unsatisfactory results, with the average survival rarely exceeding 1-2 years. Natural compounds still provide some of the most promising approaches for discovering new drugs. The non-psychotropic cannabidiol (CBD) deriving from Cannabis sativa L. provides such promise. CBD is endowed with anticancer, antioxidant, and genoprotective properties as established in vitro and in in vivo experiments. CBD’s selectivity towards cancer cells and its safe profile suggest its usage in cancer therapies. However, the bioavailability of oral CBD is low due to poor aqueous solubility, erratic gastrointestinal absorption, and significant first-pass metabolism, hampering its therapeutic potential and resulting in a variable pharmacokinetic profile. In this context, CBD can take great advantage of nanomedicine-based formulation strategies. Cyclodextrins (CDs) are cyclic oligosaccharides used in the pharmaceutical industry to incorporate apolar molecules inside their hydrophobic cavity, increasing their stability, water solubility, and bioavailability or decreasing their side effects. CBD-inclusion complexes with CDs could be a good strategy to improve its properties, like solubility and stability to harness its full therapeutic potential. The current research aims to study the potential cytotoxic effect of CBD and CBD-CDs complexes CBD-RMβCD (randomly methylated β-cyclodextrin) and CBD-HPβCD (hydroxypropyl-b-CD) on the A172 glioblastoma cell line. CBD is diluted in 10% DMSO, and CBD/CDs solutions are prepared by mixing solid CBD, solid CDs, and dH2O. For the biological assays, A172 cells are incubated at a range of concentrations of CBD, CBD-RMβCD and CBD-HPβCD, RMβCD, and HPβCD (0,03125-4 mg/ml) at 24, 48, and 72 hours. Analysis of cell viability after incubation with the compounds is performed with Alamar Blue viability assay. CBD’s dilution to DMSO 10% was inadequate, as crystals are observed; thus cytotoxicity experiments are not assessed. CBD’s solubility is enhanced in the presence of both CDs. CBD/CDs exert significant cytotoxicity in a dose and time-dependent manner (p < 0.005 for exposed cells to any concentration at 48, 72, and 96 hours versus cells not exposed); as their concentration and time of exposure increases, the reduction of resazurin to resofurin decreases, indicating a reduction in cell viability. The cytotoxic effect is more pronounced in cells exposed to CBD-HPβCD for all concentrations and time-points. RMβCD and HPβCD at the highest concentration of 4 mg/ml also exerted antitumor action per se since manifesting cell growth inhibition. The results of our study could afford the basis of research regarding the use of natural products and their inclusion complexes as anticancer agents and the shift to targeted therapy with higher efficacy and limited toxicity. Acknowledgments: The research is partly funded by ΙΚΥ (State Scholarships Foundation) – Post-doc Scholarships-Partnership Agreement 2014-2020.

Keywords: cannabidiol, cyclodextrins, glioblastoma, hydroxypropyl-b-Cyclodextrin, randomly-methylated-β-cyclodextrin

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Authors: Zachary Blanks, Solomon Sonya

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Poaching presents a serious threat to endangered animal species, environment conservations, and human life. Additionally, some poaching activity has even been linked to supplying funds to support terrorist networks elsewhere around the world. Consequently, agencies dedicated to protecting wildlife habitats have a near intractable task of adequately patrolling an entire area (spanning several thousand kilometers) given limited resources, funds, and personnel at their disposal. Thus, agencies need predictive tools that are both high-performing and easily implementable by the user to help in learning how the significant features (e.g. animal population densities, topography, behavior patterns of the criminals within the area, etc) interact with each other in hopes of abating poaching. This research develops a classification model using machine learning algorithms to aid in forecasting future attacks that is both easy to train and performs well when compared to other models. In this research, we demonstrate how data imputation methods (specifically predictive mean matching, gradient boosting, and random forest multiple imputation) can be applied to analyze data and create significant predictions across a varied data set. Specifically, we apply these methods to improve the accuracy of adopted prediction models (Logistic Regression, Support Vector Machine, etc). Finally, we assess the performance of the model and the accuracy of our data imputation methods by learning on a real-world data set constituting four years of imputed data and testing on one year of non-imputed data. This paper provides three main contributions. First, we extend work done by the Teamcore and CREATE (Center for Risk and Economic Analysis of Terrorism Events) research group at the University of Southern California (USC) working in conjunction with the Department of Homeland Security to apply game theory and machine learning algorithms to develop more efficient ways of reducing poaching. This research introduces ensemble methods (Random Forests and Stochastic Gradient Boosting) and applies it to real-world poaching data gathered from the Ugandan rain forest park rangers. Next, we consider the effect of data imputation on both the performance of various algorithms and the general accuracy of the method itself when applied to a dependent variable where a large number of observations are missing. Third, we provide an alternate approach to predict the probability of observing poaching both by season and by month. The results from this research are very promising. We conclude that by using Stochastic Gradient Boosting to predict observations for non-commercial poaching by season, we are able to produce statistically equivalent results while being orders of magnitude faster in computation time and complexity. Additionally, when predicting potential poaching incidents by individual month vice entire seasons, boosting techniques produce a mean area under the curve increase of approximately 3% relative to previous prediction schedules by entire seasons.

Keywords: ensemble methods, imputation, machine learning, random forests, statistical analysis, stochastic gradient boosting, wildlife protection

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Authors: Samantha Ramachandra, Avanthi Rupasinghe

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Demographic transition from lower to higher percentage of elderly population eventually coupled with epidemiological transition from communicable to non-communicable diseases (NCD). Higher percentage of NCD overload the health system as NCD survivors claims continuous health care. The demands are challenging to a resource constrained setting but reorganizing the system may find solutions. The study focused on the facilities available and their utilization at outpatient department (OPD) setting of the public hospitals of Sri Lanka for continuous medical care. This will help in identifying steps of reorganizing the system to provide better care with the maximum utilization of available facilities. The study was conducted as a situation analysis with secondary data at hospital planning units. Variable were identified according to the world health organization (WHO) recommendation on continuous health care for elders in “age-friendly primary health care toolkit”. Data were collected from secondary and tertiary care hospitals of Sri Lanka where most of the continuous care services are available. Out of 58 secondary and tertiary care hospitals, 16 were included in the study to represent each hospital categories. Average number of patient attending for episodic treatment at OPD and Clinical follow-up of chronic conditions shows vast disparity according to the category of the hospital ranging from 3750 – 800 per day at OPD and 1250 – 200 per clinic session. Average time spent per person at OPD session is low, range from 1.54 - 2.28 minutes, the time was increasing as the hospital category goes down. 93.7% hospitals had special arrangements for providing acute care on chronic conditions such as catheter, feeding tube and wound care. 25% hospitals had special clinics for elders, 81.2% hospitals had healthy lifestyle clinics (HLC), 75% hospitals had physical rehabilitation facilities and 68.8% hospitals had facilities for counselling. Elderly clinics and HLC were mostly available at lower grade hospitals where as rehabilitation and counselling facilities were mostly available at bigger hospitals. HLC are providing health education for both patients and their family members, refer patients for screening of complication but not provide medical examinations, investigations or treatments even though they operate in the hospital setting. Physical rehabilitation is basically offered for patients with rheumatological conditions but utilization of centers for injury rehabilitation and rehabilitation of survivors following major illness such as myocardial infarctions, stroke, cancer is not satisfactory (12.5%). Human Resource distribution within hospital shows vast disparity and there are 103 physiotherapists in the biggest hospital where only 36 physiotherapists available at the next level hospital. Counselling facilities also provided mainly for the patient with psychological conditions (100%) but they were not providing counselling for newly diagnosed patients with major illnesses (0%). According to results, most of the public-sector hospitals in Sri Lanka have basic facilities required in providing continuous care but the utilization of services need more focus. Hospital administration or the government need to have initial steps in proper utilization of them in improving continuous health care incorporating team approach of rehabilitation. The author wishes to acknowledge that this paper was made possible by the support and guidance given by the “Australia Awards Fellowships Program for Sri Lanka – 2017,” which was funded by the Department of Foreign Affairs and Trade, Australia, and co-hosted by Monash University, Australia and the Sri Lanka Institute of Development Administration.

Keywords: continuous care, outpatient department, non communicable diseases, rehabilitation

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Authors: Ana Paula Almeida Castaldelli Maciel, Gabriela Medeiros, Amanda de Souza Machado, Maria Clara Pilatti, Ralpho Rinaldo dos Reis, Silvio Cesar Sampaio

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Sustainable agricultural systems are crucial to ensuring global food security and the long-term production of nutritious food. Comprehensive soil and water management practices, including nutrient management, balanced fertilizer use, and appropriate waste management, are essential for sustainable agriculture. Swine wastewater (SWW) treatment has become a significant focus due to environmental concerns related to heavy metals, antibiotics, resistant pathogens, and nutrients. In South America, small farms use soil to dispose of animal waste, a practice that is expected to increase with global pork production. The potential of SWW as a nutrient source is promising, contributing to global food security, nutrient cycling, and mineral fertilizer reduction. Short- and long-term studies evaluated the effects of SWW on soil and plant parameters, such as nutrients, heavy metals, organic matter (OM), cation exchange capacity (CEC), and pH. Although promising results have been observed in short- and medium-term applications, long-term applications require more attention due to heavy metal concentrations. Organic soil amendment strategies, due to their economic and ecological benefits, are commonly used to reduce the bioavailability of heavy metals. However, the rate of degradation and initial levels of OM must be monitored to avoid changes in soil pH and release of metals. The study aimed to evaluate the long-term effects of SWW application on soil fertility parameters, focusing on calcium (Ca), magnesium (Mg), and potassium (K), in addition to CEC and OM. Experiments were conducted at the Universidade Estadual do Oeste do Paraná, Brazil, using 24 drainage lysimeters for nine years, with different application rates of SWW and mineral fertilization. Principal Component Analysis (PCA) was then conducted to summarize the composite variables, known as principal components (PC), and limit the dimensionality to be evaluated. The retained PCs were then correlated with the original variables to identify the level of association between each variable and each PC. Data were interpreted using Analysis of Variance - ANOVA for general linear models (GLM). As OM was not measured in the 2007 soybean experiment, it was assessed separately from PCA to avoid loss of information. PCA and ANOVA indicated that crop type, SWW, and mineral fertilization significantly influenced soil nutrient levels. Soybeans presented higher concentrations of Ca, Mg, and CEC. The application of SWW influenced K levels, with higher concentrations observed in SWW from biodigesters and higher doses of swine manure. Variability in nutrient concentrations in SWW due to factors such as animal age and feed composition makes standard recommendations challenging. OM levels increased in SWW-treated soils, improving soil fertility and structure. In conclusion, the application of SWW can increase soil fertility and crop productivity, reducing environmental risks. However, careful management and long-term monitoring are essential to optimize benefits and minimize adverse effects.

Keywords: contamination, water research, biodigester, nutrients

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Authors: Karen L. Lindsay, Sonja Entringer, Claudia Buss, Pathik D. Wadhwa

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Maternal nutrition and stress are independently recognized as among the most important factors that influence prenatal biology, with implications for fetal development and poor pregnancy outcomes. While there is substantial evidence from non-pregnancy human and animal studies that a complex, bi-directional relationship exists between nutrition and stress, to the author’s best knowledge, their interaction in the context of pregnancy has been significantly understudied. The aim of this study is to assess the interaction between maternal psychological stress and diet quality across pregnancy and its effects on biomarkers of prenatal insulin resistance and inflammation. This is a prospective longitudinal study of N=235 women carrying a healthy, singleton pregnancy, recruited from prenatal clinics of the University of California, Irvine Medical Center. Participants completed a 4-day ambulatory assessment in early, middle and late pregnancy, which included multiple daily electronic diary entries using Ecological Momentary Assessment (EMA) technology on a dedicated study smartphone. The EMA diaries gathered moment-level data on maternal perceived stress, negative mood, positive mood and quality of social interactions. The numerical scores for these variables were averaged across each study time-point and converted to Z-scores. A single composite variable for 'STRESS' was computed as follows: (Negative mood+Perceived stress)–(Positive mood+Social interaction quality). Dietary intakes were assessed by three 24-hour dietary recalls conducted within two weeks of each 4-day assessment. Daily nutrient and food group intakes were averaged across each study time-point. The Alternative Healthy Eating Index adapted for pregnancy (AHEI-P) was computed for early, middle and late pregnancy as a validated summary measure of diet quality. At the end of each 4-day ambulatory assessment, women provided a fasting blood sample, which was assayed for levels of glucose, insulin, Interleukin (IL)-6 and Tumor Necrosis Factor (TNF)-α. Homeostasis Model Assessment of Insulin Resistance (HOMA-IR) was computed. Pearson’s correlation was used to explore the relationship between maternal STRESS and AHEI-P within and between each study time-point. Linear regression was employed to test the association of the stress-diet interaction (STRESS*AHEI-P) with the biological markers HOMA-IR, IL-6 and TNF-α at each study time-point, adjusting for key covariates (pre-pregnancy body mass index, maternal education level, race/ethnicity). Maternal STRESS and AHEI-P were significantly inversely correlated in early (r=-0.164, p=0.018) and mid-pregnancy (-0.160, p=0.019), and AHEI-P from earlier gestational time-points correlated with later STRESS (early AHEI-P x mid STRESS: r=-0.168, p=0.017; mid AHEI-P x late STRESS: r=-0.142, p=0.041). In regression models, the interaction term was not associated with HOMA-IR or IL-6 at any gestational time-point. The stress-diet interaction term was significantly associated with TNF-α according to the following patterns: early AHEI-P*early STRESS vs early TNF-α (p=0.005); early AHEI-P*early STRESS vs mid TNF-α (p=0.002); early AHEI-P*mid STRESS vs mid TNF-α (p=0.005); mid AHEI-P*mid STRESS vs mid TNF-α (p=0.070); mid AHEI-P*late STRESS vs late TNF-α (p=0.011). Poor diet quality is significantly related to higher psychosocial stress levels in pregnant women across gestation, which may promote inflammation via TNF-α. Future prenatal studies should consider the combined effects of maternal stress and diet when evaluating either one of these factors on pregnancy or infant outcomes.

Keywords: diet quality, inflammation, insulin resistance, nutrition, pregnancy, stress, tumor necrosis factor-alpha

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Authors: V. Saccà, A. Sarica, F. Novellino, S. Barone, T. Tallarico, E. Filippelli, A. Granata, P. Valentino, A. Quattrone

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The work aim was to evaluate how well Random Forest (RF) and Support Vector Machine (SVM) algorithms could support the early diagnosis of Multiple Sclerosis (MS) from resting-state functional connectivity data. In particular, we wanted to explore the ability in distinguishing between controls and patients of mean signals extracted from ICA components corresponding to 15 well-known networks. Eighteen patients with early-MS (mean-age 37.42±8.11, 9 females) were recruited according to McDonald and Polman, and matched for demographic variables with 19 healthy controls (mean-age 37.55±14.76, 10 females). MRI was acquired by a 3T scanner with 8-channel head coil: (a)whole-brain T1-weighted; (b)conventional T2-weighted; (c)resting-state functional MRI (rsFMRI), 200 volumes. Estimated total lesion load (ml) and number of lesions were calculated using LST-toolbox from the corrected T1 and FLAIR. All rsFMRIs were pre-processed using tools from the FMRIB's Software Library as follows: (1) discarding of the first 5 volumes to remove T1 equilibrium effects, (2) skull-stripping of images, (3) motion and slice-time correction, (4) denoising with high-pass temporal filter (128s), (5) spatial smoothing with a Gaussian kernel of FWHM 8mm. No statistical significant differences (t-test, p < 0.05) were found between the two groups in the mean Euclidian distance and the mean Euler angle. WM and CSF signal together with 6 motion parameters were regressed out from the time series. We applied an independent component analysis (ICA) with the GIFT-toolbox using the Infomax approach with number of components=21. Fifteen mean components were visually identified by two experts. The resulting z-score maps were thresholded and binarized to extract the mean signal of the 15 networks for each subject. Statistical and machine learning analysis were then conducted on this dataset composed of 37 rows (subjects) and 15 features (mean signal in the network) with R language. The dataset was randomly splitted into training (75%) and test sets and two different classifiers were trained: RF and RBF-SVM. We used the intrinsic feature selection of RF, based on the Gini index, and recursive feature elimination (rfe) for the SVM, to obtain a rank of the most predictive variables. Thus, we built two new classifiers only on the most important features and we evaluated the accuracies (with and without feature selection) on test-set. The classifiers, trained on all the features, showed very poor accuracies on training (RF:58.62%, SVM:65.52%) and test sets (RF:62.5%, SVM:50%). Interestingly, when feature selection by RF and rfe-SVM were performed, the most important variable was the sensori-motor network I in both cases. Indeed, with only this network, RF and SVM classifiers reached an accuracy of 87.5% on test-set. More interestingly, the only misclassified patient resulted to have the lowest value of lesion volume. We showed that, with two different classification algorithms and feature selection approaches, the best discriminant network between controls and early MS, was the sensori-motor I. Similar importance values were obtained for the sensori-motor II, cerebellum and working memory networks. These findings, in according to the early manifestation of motor/sensorial deficits in MS, could represent an encouraging step toward the translation to the clinical diagnosis and prognosis.

Keywords: feature selection, machine learning, multiple sclerosis, random forest, support vector machine

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Authors: Pablo Chico De Guzman, Cesar Sanchez

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Microservice architectures are increasingly in distributed cloud applications due to the advantages on the software composition, development speed, release cycle frequency and the business logic time to market. On the other hand, these architectures also introduce some challenges on the testing and release phases of applications. Container technology solves some of these issues by providing reproducible environments, easy of software distribution and isolation of processes. However, there are other issues that remain unsolved in current container technology when dealing with multiple machines, such as networking for multi-host communication, service discovery, load balancing or data persistency (even though some of these challenges are already solved by traditional cloud vendors in a very mature and widespread manner). Container cluster management tools, such as Kubernetes, Mesos or Docker Swarm, attempt to solve these problems by introducing a new control layer where the unit of deployment is the container (or the pod — a set of strongly related containers that must be deployed on the same machine). These tools are complex to configure and manage and they do not follow a pure immutable infrastructure approach since servers are reused between deployments. Indeed, these tools introduce dependencies at execution time for solving networking or service discovery problems. If an error on the control layer occurs, which would affect running applications, specific expertise is required to perform ad-hoc troubleshooting. As a consequence, it is not surprising that container cluster support is becoming a source of revenue for consulting services. This paper presents i2kit, a deployment tool based on the immutable infrastructure pattern, where the virtual machine is the unit of deployment. The input for i2kit is a declarative definition of a set of microservices, where each microservice is defined as a pod of containers. Microservices are built into machine images using linuxkit —- a tool for creating minimal linux distributions specialized in running containers. These machine images are then deployed to one or more virtual machines, which are exposed through a cloud vendor load balancer. Finally, the load balancer endpoint is set into other microservices using an environment variable, providing service discovery. The toolkit i2kit reuses the best ideas from container technology to solve problems like reproducible environments, process isolation, and software distribution, and at the same time relies on mature, proven cloud vendor technology for networking, load balancing and persistency. The result is a more robust system with no learning curve for troubleshooting running applications. We have implemented an open source prototype that transforms i2kit definitions into AWS cloud formation templates, where each microservice AMI (Amazon Machine Image) is created on the fly using linuxkit. Even though container cluster management tools have more flexibility for resource allocation optimization, we defend that adding a new control layer implies more important disadvantages. Resource allocation is greatly improved by using linuxkit, which introduces a very small footprint (around 35MB). Also, the system is more secure since linuxkit installs the minimum set of dependencies to run containers. The toolkit i2kit is currently under development at the IMDEA Software Institute.

Keywords: container, deployment, immutable infrastructure, microservice

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Authors: Emilio Galdeano-Gómez, Juan C. Pérez-Mesa, Laura Piedra-Muñoz, María C. García-Barranco, Jesús Hernández-Rubio

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The situation in which firms engage in simultaneous cooperation and competition with each other is a phenomenon known as co-opetition. This scenario has received increasing attention in business economics and management analyses. In the domain of supply chain networks and for small and medium-sized enterprises, SMEs, these strategies are of greater relevance given the complex environment of globalization and competition in open markets. These firms face greater challenges regarding technology and access to specific resources due to their limited capabilities and limited market presence. Consequently, alliances and collaborations with both buyers and suppliers prove to be key elements in overcoming these constraints. However, rivalry and competition are also regarded as major factors in successful internationalization processes, as they are drivers for firms to attain a greater degree of specialization and to improve efficiency, for example enabling them to allocate scarce resources optimally and providing incentives for innovation and entrepreneurship. The present work aims to contribute to the literature on SMEs’ internationalization strategies. The sample is constituted by a panel data of marketing firms from the Andalusian food sector and a multivariate regression analysis is developed, measuring variables of co-opetition and international activity. The hierarchical regression equations method has been followed, thus resulting in three estimated models: the first one excluding the variables indicative of channel type, while the latter two include the international retailer chain and wholesaler variable. The findings show that the combination of several factors leads to a complex scenario of inter-organizational relationships of cooperation and competition. In supply chain management analyses, these relationships tend to be classified as either buyer-supplier (vertical level) or supplier-supplier relationships (horizontal level). Several buyers and suppliers tend to participate in supply chain networks, and in which the form of governance (hierarchical and non-hierarchical) influences cooperation and competition strategies. For instance, due to their market power and/or their closeness to the end consumer, some buyers (e.g. large retailers in food markets) can exert an influence on the selection and interaction of several of their intermediate suppliers, thus endowing certain networks in the supply chain with greater stability. This hierarchical influence may in turn allow these suppliers to develop their capabilities (e.g. specialization) to a greater extent. On the other hand, for those suppliers that are outside these networks, this environment of hierarchy, characterized by a “hub firm” or “channel master”, may provide an incentive for developing their co-opetition relationships. These results prove that the analyzed firms have experienced considerable growth in sales to new foreign markets, mainly in Europe, dealing with large retail chains and wholesalers as main buyers. This supply industry is predominantly made up of numerous SMEs, which has implied a certain disadvantage when dealing with the buyers, as negotiations have traditionally been held on an individual basis and in the face of high competition among suppliers. Over recent years, however, cooperation among these marketing firms has become more common, for example regarding R&D, promotion, scheduling of production and sales.

Keywords: co-petition networks, international supply chain, maketing agrifood firms, SMEs strategies

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Authors: Layla Haidar, Shari Esquenazi-Karonika

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Introduction: Mental health includes one’s emotional, psychological, and interpersonal well-being; it ranges from “good” to “poor” on a continuum. At the individual-level, it affects how a person thinks, feels, and acts. Moreover, it determines how they cope with stress, relate to others, and interface with their surroundings. Research has yielded that mental health is directly related with short- and long-term physical health (including chronic disease), health risk behaviors, education-level, employment, and social relationships. As is the case with physical conditions like diabetes, heart disease, and cancer, mitigating the behavioral and genetic risks of debilitating mental health conditions like anxiety and depression can nurture a healthier quality of mental health throughout one’s life. In order to maximize the benefits of prevention, it is important to identify modifiable risks and develop protective habits earlier in life. Methods: The Adolescent Behaviors and Experiences Survey (ABES) dataset was used for this study. The ABES survey was administered to high school students (9th-12th grade) during January 2021- June 2021 by the Centers for Disease Control and Prevention (CDC). The data was analyzed to identify any associations between feelings of sadness, hopelessness, or increased suicidality among high school students with relation to their participation on one or more sports teams and their average daily consumed screen time. Data was analyzed using descriptive and multivariable analytic techniques. A multinomial logistic regression of each variable was conducted to examine if there was an association, while controlling for grade-level, sex, and race. Results: The findings from this study are insightful for administrators and policymakers who wish to address mounting concerns related to student mental health. The study revealed that compared to a student who participated on zero sports teams, students who participated in 1 or more sports teams showed a significantly increased risk of depression (p<0.05). Conversely, the rate of depression in students was significantly less in those who consumed 5 or more hours of screen time per day, compared to those who consumed less than 1 hour per day of screen time (p<0.05). Conclusion: These findings are informative and highlight the importance of understanding the nuances of student participation on sports teams (e.g., physical exertion, social dynamics of team, and the level of competitiveness within the sport). Likewise, the context of an individual’s screen time (e.g., social media, engaging in team-based video games, or watching television) can inform parental or school-based policies about screen time activity. Although physical activity has been proven to be important for emotional and physical well-being of youth, playing on multiple teams could have negative consequences on the emotional state of high school students potentially due to fatigue, overtraining, and injuries. Existing literature has highlighted the negative effects of screen time; however, further research needs to consider the type of screen-based consumption to better understand its effects on mental health.

Keywords: behavioral science, mental health, adolescents, prevention

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Authors: Mario Tauzene Afonso Matangue, Ivan Andres Sanchez Ortiz

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The Metropolitan area of Maputo (Mozambique Capital City) is located in semi-arid zone (800 mm annual rainfall) with 1101170 million inhabitants. On the west side, there are the flatlands of Infulene where the Mulauze River flows towards to the Indian Ocean, receiving at this site, the storm water contaminated with sanitary sewage from Maputo, transported through a concrete open channel. In Infulene, local communities grow salads crops such as tomato, onion, garlic, lettuce, and cabbage, which are then commercialized and consumed in several markets in Maputo City. Lettuce is the most daily consumed salad crop in different meals, generally in fast-foods, breakfasts, lunches, and dinners. However, the risk of infection by several pathogens due to the consumption of lettuce, using the Quantitative Microbial Risk Assessment (QMRA) tools, is still unknown since there are few studies or publications concerning to this matter in Mozambique. This work is aimed at determining the annual risk arising from the consumption of lettuce grown in Infulene valley, in Maputo, using QMRA tools. The exposure model was constructed upon the volume of contaminated water remaining in the lettuce leaves, the empirical relations between the number of pathogens and the indicator of microorganisms (E. coli), the consumption of lettuce (g) and reduction of pathogens (days). The reference pathogens were Vibrio cholerae, Cryptosporidium, norovirus, and Ascaris. The water quality samples (E. coli) were collected in the storm water channel from January 2016 to December 2018, comprising 65 samples, and the urban lettuce consumption data were collected through inquiry in Maputo Metropolis covering 350 persons. A non-parametric bootstrap was performed involving 10,000 iterations over the collected dataset, namely, water quality (E. coli) and lettuce consumption. The dose-response models were: Exponential for Cryptosporidium, Kummer Confluent hypergeomtric function (1F1) for Vibrio and Ascaris Gaussian hypergeometric function (2F1-(a,b;c;z) for norovirus. The annual infection risk estimates were performed using R 3.6.0 (CoreTeam) software by Monte Carlo (Latin hypercubes), a sampling technique involving 10,000 iterations. The annual infection risks values expressed by Median and the 95th percentile, per person per year (pppy) arising from the consumption of lettuce are as follows: Vibrio cholerae (1.00, 1.00), Cryptosporidium (3.91x10⁻³, 9.72x 10⁻³), nororvirus (5.22x10⁻¹, 9.99x10⁻¹) and Ascaris (2.59x10⁻¹, 9.65x10⁻¹). Thus, the consumption of the lettuce would result in greater risks than the tolerable levels ( < 10⁻³ pppy or 10⁻⁶ DALY) for all pathogens, and the Vibrio cholerae is the most virulent pathogens, according to the hit-single models followed by the Ascaris lumbricoides and norovirus. The sensitivity analysis carried out in this work pointed out that in the whole QMRA, the most important input variable was the reduction of pathogens (Spearman rank value was 0.69) between harvest and consumption followed by water quality (Spearman rank value was 0.69). The decision-makers (Mozambique Government) must strengthen the prevention measures related to pathogens reduction in lettuce (i.e., washing) and engage in wastewater treatment engineering.

Keywords: annual infections risk, lettuce, non-parametric bootstrapping, quantitative microbial risk assessment tools

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Authors: Jose A. Alvarez Aldegunde, Adrian Fernandez Sanchez, Matthew D. Menden, Bernardo Vila Rodriguez

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Up to five statistical pre-processings have been carried out considering the pollutant records of the stations present in Cartagena de Indias, Colombia, also taking into account the childhood asthma incidence surveys conducted in hospitals in the city by the Health Ministry of Colombia for this study. These pre-processings have consisted of different techniques such as the determination of the quality of data collection, determination of the quality of the registration network, identification and debugging of errors in data collection, completion of missing data and purified data, as well as the improvement of the time scale of records. The characterization of the quality of the data has been conducted by means of density analysis of the pollutant registration stations using ArcGis Software and through mass balance techniques, making it possible to determine inconsistencies in the records relating the registration data between stations following the linear regression. The results obtained in this process have highlighted the positive quality in the pollutant registration process. Consequently, debugging of errors has allowed us to identify certain data as statistically non-significant in the incidence and series of contamination. This data, together with certain missing records in the series recorded by the measuring stations, have been completed by statistical imputation equations. Following the application of these prior processes, the basic series of incidence data for respiratory disease and pollutant records have allowed the characterization of the influence of pollutants on respiratory diseases such as, for example, childhood asthma. This characterization has been carried out using statistical correlation methods, including visual correlation, simple linear regression correlation and spectral analysis with PAST Software which identifies maximum periodicity cycles and minimums under the formula of the Lomb periodgram. In relation to part of the results obtained, up to eleven maximums and minimums considered contemporary between the incidence records and the particles have been identified taking into account the visual comparison. The spectral analyses that have been performed on the incidence and the PM2.5 have returned a series of similar maximum periods in both registers, which are at a maximum during a period of one year and another every 25 days (0.9 and 0.07 years). The bivariate analysis has managed to characterize the variable "Daily Vehicular Flow" in the ninth position of importance of a total of 55 variables. However, the statistical correlation has not obtained a favorable result, having obtained a low value of the R2 coefficient. The series of analyses conducted has demonstrated the importance of the influence of pollutants such as PM2.5 in the development of childhood asthma in Cartagena. The quantification of the influence of the variables has been able to determine that there is a 56% probability of dependence between PM2.5 and childhood respiratory asthma in Cartagena. Considering this justification, the study could be completed through the application of the BenMap Software, throwing a series of spatial results of interpolated values of the pollutant contamination records that exceeded the established legal limits (represented by homogeneous units up to the neighborhood level) and results of the impact on the exacerbation of pediatric asthma. As a final result, an economic estimate (in Colombian Pesos) of the monthly and individual savings derived from the percentage reduction of the influence of pollutants in relation to visits to the Hospital Emergency Room due to asthma exacerbation in pediatric patients has been granted.

Keywords: Asthma Incidence, BenMap, PM2.5, Statistical Analysis

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Authors: Chau-Kuang Chen, Juanita Buford, Colette Davis, Raisha Allen, John Hughes, James Tyus, Dexter Samuels

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During the post-Civil War era, the city of Nashville, Tennessee, had the highest mortality rate in the country. The elevated death and disease among ex-slaves were attributable to the unavailability of healthcare. To address the paucity of healthcare services, the College, an institution with the mission of educating minority professionals and serving the under served population, was established in 1876. This study was designed to assess if the College has accomplished its mission of serving under served communities and contributed to the elimination of health disparities in the United States. The study objective was to quantify the impact of socioeconomic status and adverse health outcomes on primary care professionals serving disadvantaged communities, which, in turn, was significantly associated with a health professional shortage score partly designated by the U.S. Department of Health and Human Services. Various statistical methods were used to analyze the alumni data in years 1975 – 2013. K-means cluster analysis was utilized to identify individual medical and dental graduates into the cluster groups of the practice communities (Disadvantaged or Non-disadvantaged Communities). Discriminant analysis was implemented to verify the classification accuracy of cluster analysis. The independent t test was performed to detect the significant mean differences for clustering and criterion variables between Disadvantaged and Non-disadvantaged Communities, which confirms the “content” validity of cluster analysis model. Chi-square test was used to assess if the proportion of cluster groups (Disadvantaged vs Non-disadvantaged Communities) were consistent with that of practicing specialties (primary care vs. non-primary care). Finally, the partial least squares (PLS) path model was constructed to explore the “construct” validity of analytics model by providing the magnitude effects of socioeconomic status and adverse health outcome on primary care professionals serving disadvantaged community. The social ecological theory along with statistical models mentioned was used to establish the relationship between medical and dental graduates (primary care professionals serving disadvantaged communities) and their social environments (socioeconomic status, adverse health outcome, health professional shortage score). Based on social ecological framework, it was hypothesized that the impact of socioeconomic status and adverse health outcomes on primary care professionals serving disadvantaged communities could be quantified. Also, primary care professionals serving disadvantaged communities related to a health professional shortage score can be measured. Adverse health outcome (adult obesity rate, age-adjusted premature mortality rate, and percent of people diagnosed with diabetes) could be affected by the latent variable, namely socioeconomic status (unemployment rate, poverty rate, percent of children who were in free lunch programs, and percent of uninsured adults). The study results indicated that approximately 83% (3,192/3,864) of the College’s medical and dental graduates from 1975 to 2013 were practicing in disadvantaged communities. In addition, the PLS path modeling demonstrated that primary care professionals serving disadvantaged community was significantly associated with socioeconomic status and adverse health outcome (p < .001). In summary, the majority of medical and dental graduates from the College provide primary care services to disadvantaged communities with low socioeconomic status and high adverse health outcomes, which demonstrate that the College has fulfilled its mission.

Keywords: disadvantaged community, K-means cluster analysis, PLS path modeling, primary care

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Authors: Mohammad R. Aghakashkooli, Milutin G. Jovanovic

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The brushless doubly-fed reluctance generator (BDFRG) is an emerging, medium-speed alternative to a conventional wound rotor slip-ring doubly-fed induction generator (DFIG) in wind energy conversion systems (WECS). It can provide competitive overall performance and similar low failure rates of a typically 30% rated back-to-back power electronics converter in 2:1 speed ranges but with the following important reliability and cost advantages over DFIG: the maintenance-free operation afforded by its brushless structure, 50% synchronous speed with the same number of rotor poles (allowing the use of a more compact, and more efficient two-stage gearbox instead of a vulnerable three-stage one), and superior grid integration properties including simpler protection for the low voltage ride through compliance of the fractional converter due to the comparatively higher leakage inductances and lower fault currents. Vector controlled pulse-width-modulated converters generally feature a much lower total harmonic distortion relative to hysteresis counterparts with variable switching rates and as such have been a predominant choice for BDFRG (and DFIG) wind turbines. Eliminating a shaft position sensor, which is often required for control implementation in this case, would be desirable to address the associated reliability issues. This fact has largely motivated the recent growing research of sensorless methods and developments of various rotor position and/or speed estimation techniques for this purpose. The main limitation of all the observer-based control approaches for grid-connected wind power applications of the BDFRG reported in the open literature is the requirement for pre-commissioning procedures and prior knowledge of the machine inductances, which are usually difficult to accurately identify by off-line testing. A model reference adaptive system (MRAS) based sensor-less vector control scheme to be presented will overcome this shortcoming. The true machine parameter independence of the proposed field-oriented algorithm, offering robust, inherently decoupled real and reactive power control of the grid-connected winding, is achieved by on-line estimation of the inductance ratio, the underlying rotor angular velocity and position MRAS observer being reliant upon. Such an observer configuration will be more practical to implement and clearly preferable to the existing machine parameter dependent solutions, and especially bearing in mind that with very little modifications it can be adapted for commercial DFIGs with immediately obvious further industrial benefits and prospects of this work. The excellent encoder-less controller performance with maximum power point tracking in the base speed region will be demonstrated by realistic simulation studies using large-scale BDFRG design data and verified by experimental results on a small laboratory prototype of the WECS emulation facility.

Keywords: brushless doubly fed reluctance generator, model reference adaptive system, sensorless vector control, wind energy conversion

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Authors: Ainura Tursunalieva, Irene Hudson

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Continuous improvement of both the quality and safety of health care is an important goal in Australia and internationally. The intensive care unit (ICU) receives patients with a wide variety of and severity of illnesses. Accurately identifying patients at risk of developing complications or dying is crucial to increasing healthcare efficiency. Thus, it is essential for clinicians and researchers to have a robust framework capable of evaluating the risk profile of a patient. ICU scoring systems provide such a framework. The Acute Physiology and Chronic Health Evaluation III and the Simplified Acute Physiology Score II are ICU scoring systems frequently used for assessing the severity of acute illness. These scoring systems collect multiple risk factors for each patient including physiological measurements then render the assessment outcomes of individual risk factors into a single numerical value. A higher score is related to a more severe patient condition. Furthermore, the Mortality Probability Model II uses logistic regression based on independent risk factors to predict a patient’s probability of mortality. An important overlooked limitation of SAPS II and MPM II is that they do not, to date, include interaction terms between a patient’s vital signs. This is a prominent oversight as it is likely there is an interplay among vital signs. The co-existence of certain conditions may pose a greater health risk than when these conditions exist independently. One barrier to including such interaction terms in predictive models is the dimensionality issue as it becomes difficult to use variable selection. We propose an innovative scoring system which takes into account a dependence structure among patient’s vital signs, such as systolic and diastolic blood pressures, heart rate, pulse interval, and peripheral oxygen saturation. Copulas will capture the dependence among normally distributed and skewed variables as some of the vital sign distributions are skewed. The estimated dependence parameter will then be incorporated into the traditional scoring systems to adjust the points allocated for the individual vital sign measurements. The same dependence parameter will also be used to create an alternative copula-based model for predicting a patient’s probability of mortality. The new copula-based approach will accommodate not only a patient’s trajectories of vital signs but also the joint dependence probabilities among the vital signs. We hypothesise that this approach will produce more stable assessments and lead to more time efficient and accurate predictions. We will use two data sets: (1) 250 ICU patients admitted once to the Chui Regional Hospital (Kyrgyzstan) and (2) 37 ICU patients’ agitation-sedation profiles collected by the Hunter Medical Research Institute (Australia). Both the traditional scoring approach and our copula-based approach will be evaluated using the Brier score to indicate overall model performance, the concordance (or c) statistic to indicate the discriminative ability (or area under the receiver operating characteristic (ROC) curve), and goodness-of-fit statistics for calibration. We will also report discrimination and calibration values and establish visualization of the copulas and high dimensional regions of risk interrelating two or three vital signs in so-called higher dimensional ROCs.

Keywords: copula, intensive unit scoring system, ROC curves, vital sign dependence

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Authors: Anushka Naidoo, Veron Ramsuran, Maxwell Chirehwa, Paolo Denti, Kogieleum Naidoo, Helen McIlleron, Nonhlanhla Yende-Zuma, Ravesh Singh, Sinaye Ngcapu, Nesri Padayatachi

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Background: Despite efforts to introduce new drugs and shorter drug regimens for drug-susceptible tuberculosis (TB), the standard first-line treatment has not changed in over 50 years. Rifampicin, isoniazid, and pyrazinamide are critical components of the current standard treatment regimens. Some studies suggest that microbiologic failure and acquired drug resistance are primarily driven by low drug concentrations that result from pharmacokinetic (PK) variability independent of adherence to treatment. Wide between-patient pharmacokinetic variability for rifampin, isoniazid, and pyrazinamide has been reported in prior studies. There may be several reasons for this variability. However, genetic variability in genes coding for drug metabolizing and transporter enzymes have been shown to be a contributing factor for variable tuberculosis drug exposures. Objective: We describe the pharmacokinetics of first-line TB drugs rifampicin, isoniazid, and pyrazinamide and assess the effect of genetic variability in relevant selected drug metabolizing and transporter enzymes on pharmacokinetic parameters of isoniazid and rifampicin. Methods: We conducted the randomized-controlled Improving retreatment success TB trial in Durban, South Africa. The drug regimen included rifampicin, isoniazid, and pyrazinamide. Drug concentrations were measured in plasma, and concentration-time data were analysed using nonlinear-mixed-effects models to quantify the effects of relevant covariates and single nucleotide polymorphisms (SNP’s) of drug metabolizing and transporter genes on rifampicin, isoniazid and pyrazinamide exposure. A total of 25 SNP’s: four NAT2 (used to determine acetylator status), four SLCO1B1, three Pregnane X receptor (NR1), six ABCB1 and eight UGT1A, were selected for analysis in this study. Genotypes were determined for each of the SNP’s using a TaqMan® Genotyping OpenArray™. Results: Among fifty-eight patients studied; 41 (70.7%) were male, 97% black African, 42 (72.4%) HIV co-infected and 40 (95%) on efavirenz-based ART. Median weight, fat-free mass (FFM), and age at baseline were 56.9 kg (interquartile range, IQR: 51.1-65.2), 46.8 kg (IQR: 42.5-50.3) and 37 years (IQR: 31-42), respectively. The pharmacokinetics of rifampicin and pyrazinamide was best described using one-compartment models with first-order absorption and elimination, while for isoniazid two-compartment disposition was used. The median (interquartile range: IQR) AUC (h·mg/L) and Cmax (mg/L) for rifampicin, isoniazid, and pyrazinamide were; 25.62 (23.01-28.53) and 4.85 (4.36-5.40), 10.62 (9.20-12.25) and 2.79 (2.61-2.97), 345.74 (312.03-383.10) and 28.06 (25.01-31.52), respectively. Eighteen percent of patients were classified as rapid acetylators, and 34% and 43% as slow and intermediate acetylators, respectively. Rapid and intermediate acetylator status based on NAT 2 genotype resulted in 2.3 and 1.6 times higher isoniazid clearance than slow acetylators. We found no effects of the SLCO1B1 genotypes on rifampicin pharmacokinetics. Conclusion: Plasma concentrations of rifampicin, isoniazid, and pyrazinamide were low overall in our patients. Isoniazid clearance was high overall and as expected higher in rapid and intermediate acetylators resulting in lower drug exposures. In contrast to reports from previous South African or Ugandan studies, we did not find any effects of the SLCO1B1 or other genotypes tested on rifampicin PK. However, our findings are in keeping with more recent studies from Malawi and India emphasizing the need for geographically diverse and adequately powered studies. The clinical relevance of the low tuberculosis drug concentrations warrants further investigation.

Keywords: rifampicin, isoniazid pharmacokinetics, genetics, NAT2, SLCO1B1, tuberculosis

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Authors: Sylvie Michel, François Cocula

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Digital agriculture is an approach that exploits information and communication technologies. These encompass data acquisition tools like mobile applications, satellites, sensors, connected devices, and smartphones. Additionally, it involves transfer and storage technologies such as 3G/4G coverage, low-bandwidth terrestrial or satellite networks, and cloud-based systems. Furthermore, embedded or remote processing technologies, including drones and robots for process automation, along with high-speed communication networks accessible through supercomputers, are integral components of this approach. While farm-level adoption studies regarding digital agricultural technologies have emerged in recent years, they remain relatively limited in comparison to other agricultural practices. To bridge this gap, this study delves into understanding farmers' intention to adopt digital tools, employing the technology, organization, environment framework. A qualitative research design encompassed semi-structured interviews, totaling fifteen in number, conducted with key stakeholders both prior to and following the 2020-2021 COVID-19 lockdowns in France. Subsequently, the interview transcripts underwent thorough thematic content analysis, and the data and verbatim were triangulated for validation. A coding process aimed to systematically organize the data, ensuring an orderly and structured classification. Our research extends its contribution by delineating sub-dimensions within each primary dimension. A total of nine sub-dimensions were identified, categorized as follows: perceived usefulness for communication, perceived usefulness for productivity, and perceived ease of use constitute the first dimension; technological resources, financial resources, and human capabilities constitute the second dimension, while market pressure, institutional pressure, and the COVID-19 situation constitute the third dimension. Furthermore, this analysis enriches the TOE framework by incorporating entrepreneurial orientation as a moderating variable. Managerial orientation emerges as a pivotal factor influencing adoption intention, with producers acknowledging the significance of utilizing digital sales support tools to combat "greenwashing" and elevate their overall brand image. Specifically, it illustrates that producers recognize the potential of digital tools in time-saving and streamlining sales processes, leading to heightened productivity. Moreover, it highlights that the intent to adopt digital sales support tools is influenced by a market mimicry effect. Additionally, it demonstrates a negative association between the intent to adopt these tools and the pressure exerted by institutional partners. Finally, this research establishes a positive link between the intent to adopt digital sales support tools and economic fluctuations, notably during the COVID-19 pandemic. The adoption of sales support tools in agriculture is a multifaceted challenge encompassing three dimensions and nine sub-dimensions. The research delves into the adoption of digital farming technologies at the farm level through the TOE framework. This analysis provides significant insights beneficial for policymakers, stakeholders, and farmers. These insights are instrumental in making informed decisions to facilitate a successful digital transition in agriculture, effectively addressing sector-specific challenges.

Keywords: adoption, digital agriculture, e-commerce, TOE framework

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