Specialty Coffee Farmers' Climate Change Concern and Perceived Ability to Adapt

Climate change studies predict that rising temperatures and water shortages will negatively impact coffee production suitability at lower elevations (Rivera et al., 2015). As climate change becomes increasingly severe, an assessment of coffee producers’ ability and willingness to adapt would be especially valuable to those hoping to create adaptation strategies and policies. This had led to a significant growth of research surrounding the livelihood of farmers, as well as their perceptions of climate change and adaptation. However, research focused specifically on specialty coffee is still lacking. With higher quality considerations, different value chains, and lower price volatility, specialty coffee farmers are an especially interesting area of study (Vellucci, 2015). This study aims to fill this knowledge gap. To do this, a survey was conducted among Costa Rican specialty coffee producers in order to identify whether their concern about climate change and their perceived ability to adapt are affected by perceptions of climate change risk, financing, farmer demographics, coffee management practices, biophysical factors, access to information, or perceived adaptation methods. Survey responses were coded, quantified, and analyzed through statistical software using analysis of variance and linear regressions. Previous studies show more concern about coffee price volatility than climate change (Tucker et al., 2009; Eakin et al., 2006; Gay et al. 2006). However, this study found greater concern about climate change than falling coffee prices among surveyed farmers, reinforcing that specialty coffee farmers may be better positioned than nonspeciality growers to handle market volatility. Nevertheless, respondents felt less prepared to face the impacts of climate change. This study hypothesized that farmers with higher levels of climate change concern would have the lowest levels of perceived ability to adapt. However, it was found that farmer’s concern about climate change did not correlate with their feelings of preparedness to address it. These few results among others detailed in the report signal a need to address the climate change concerns and adaptation capacity of speciality coffee growers. As Costa Rican policy makers, development organizations, and coffee importers and exporters build multistakeholder strategies to support this key segment of farmers, they should prioritize the implementation of tools that build adaptive capacity in addition to traditional market based mechanisms like promotion and trade policies. These results encourage the development of future studies to explore which specific tools at the farm, household, landscape, or political level would most enhance adaptive capacity of speciality coffee growers.Master of ScienceNatural Resources and EnvironmentUniversity of Michiganhttp://deepblue.lib.umich.edu/bitstream/2027.42/117595/1/Final Paper - Coffee Team.pd

Structural Sustainable Recycled Aggregate Concrete Production Under Environmental Conditions

The use of recycled aggregates (RA) in the concrete industry has become increasingly popular due to the reduction in natural aggregate (NA) consumption and the ability to reuse demolition waste. This research focuses on analyzing the performance of recycled aggregate concrete (RAC) cured with sodium sulfate (Na2SO4). Five different mixtures were created, varying from 0% RA without supplementary cementitious material (SCM), to 0%, 15%, 30%, and 45% substitution of NA with RA and SCM. The slump test was performed on all fresh RAC mixtures, which showed a decrease in slump with an increase in RA content. Both 5% Na2SO4 solution curing at 91 days and standard curing at 7, 28, and 91 days resulted in a reduction in compressive strength and ultrasonic pulse velocity (UPV) as the proportion of RA increased. Compared to standard curing, the compressive strength of specimens cured with 5% Na2SO4 solution at 91 days showed a decrease of approximately 5-7%. The UPV of SCM-based mixes showed 14-28% improvement with respect to normal aggregate concrete (NAC) in normal water curing. Furthermore, the SCM-included specimens have produced less deterioration in Na2SO4 immersion as SCM particles resist the severity of the dominant sulfate environment

Structural Sustainable Recycled Aggregate Concrete Production Under Environmental Conditions

The use of recycled aggregates (RA) in the concrete industry has become increasingly popular due to the reduction in natural aggregate (NA) consumption and the ability to reuse demolition waste. This research focuses on analyzing the performance of recycled aggregate concrete (RAC) cured with sodium sulfate (Na2SO4). Five different mixtures were created, varying from 0% RA without supplementary cementitious material (SCM), to 0%, 15%, 30%, and 45% substitution of NA with RA and SCM. The slump test was performed on all fresh RAC mixtures, which showed a decrease in slump with an increase in RA content. Both 5% Na2SO4 solution curing at 91 days and standard curing at 7, 28, and 91 days resulted in a reduction in compressive strength and ultrasonic pulse velocity (UPV) as the proportion of RA increased. Compared to standard curing, the compressive strength of specimens cured with 5% Na2SO4 solution at 91 days showed a decrease of approximately 5-7%. The UPV of SCM-based mixes showed 14-28% improvement with respect to normal aggregate concrete (NAC) in normal water curing. Furthermore, the SCM-included specimens have produced less deterioration in Na2SO4 immersion as SCM particles resist the severity of the dominant sulfate environment

Travel Time Estimation using Multivariate Regression Model

As it is known from the current research and studies that travel time of vehicles is the most reliable parameters to measure the cost of a link. Cost modeling of routes has many useful applications in dynamic route selection strategies e.g. route selection for emergency vehicles. Travel time of an individual vehicle passing a road segment is a function of many parameters which includes of road geometry, traffic flow characteristics, driver"s behaviors and region-specific rules and regulations, length of the segment, number of lanes, lane width, traffic flow, traffic volume and density, average speed of vehicles, vehicles composition and the ratio of turn movements on ramps. Moreover, the average travel time of vehicles on freeways is also dependent on some parameters that vary from country to country e.g. traffic regulations, driving rules, driver"s behavior and the construction of roads. Current mathematical models and simulation software"s lack the implementation of all these parameters and hence the results of these models are mostly different from the actual. The calibration of simulation software is always required to reduce this difference. The estimation of travel time using some numerical computation or simulation software"s is not reliable. This paper describes the modeling of travel time as a cost/metric of segments on a freeway. In it, regression models are used to evaluation the travel time for a throughway segment using traffic statistics acquired from field surveys. The validity of the models is explained with their statistical significance. Regression models are equally beneficial for any region if the data sets are quite large and enough parameters are included in the model. In regression analysis, the relationships among different variables are estimated. In it, different modeling techniques are used to find the relationship between dependent and independent variables. More precisely, the analysis helps to realize how the dependent variable changes with the variation of any of the independent variables keeping other variables fixed. In this work, statistical techniques i.e. regression modeling and analysis of variance (ANOVA) has been used to evaluate the impact of each independent variable (parameters) on the travel time. Finally, a multivariate regression model is used to approximate the time of travel. The estimated time is related to the actual travel time from the real field data and the model fitness is evaluated. Our dataset constitutes of four independent parameters and one dependent parameters. Independent variable (Inputs): 1 Length of the segment 2 No of lanes in the segment 3 Flow of traffic on the segment 4 Average Speed of vehicles on the segment Dependent variable (Response) 1 Travel Time Regression analysis has been used as a statistical technique to find the response variable (travel time). In this paper it is proposed to find the travel time for a particular connection using regression models applied to actual traffic data sets collected from field surveys. Real traffic data for several segments from different freeways has acquired and analyzed them using regression models. The probable travel time was compared with actual travel time for each segment of the highway and it was found that the estimation using regression models reveals the significant level of accuracy. R-Studio is being used in the statistical analysis of the data. We computed the regression equation for the estimation of travel time for all the given four parameters (distance, lanes, flow, speed) using coefficients, ?0, ?1, ?2, ?3 and ?4. Figure1 shows the actual travel time of the vehicle and the estimated travel time which is obtained by the regression analysis.qscienc

Clinical presentation of ulcerative colitis among Bangladeshi population twenty years experience from a tertiary care hospital in Bangladesh

Background: The prevalence of Ulcerative colitis has been increasingly reported from Western countries as well as other Asian countries. Our personal experience shows that Ulcerative colitis is not uncommon in our country and is being diagnosed more commonly. So, there is need to study the disease pattern in our country. Objective: To find out the clinical presentation, among Bangladeshi population. Methods: A hospital (Department of Gastroenterology, Bang­abandhu Sheikh Mujib Medical University) based study registering previously diagnosed and newly diagnosed cases of Ulcerative colitis, was carried out from January 1990 to June 2010. Data that were obtained are: age and sex of the patients, clinical presentations like bloody diarrhoea, per rectal bleeding, diarrhoea without per rectal bleeding, urgency, tenesmus, abdominal pain, fever, anorexia, weakness, weight loss. Data regarding physical findings and extra intestinal manifestations were also recorded. Results: Out of 164 patients 65.24% (107) were male and 34.76% (57) were female. The male- female ratio was 1.88 : 1. Mean age of male patients was 36.14(±11.66) years and mean age for female patients was 33.15(±11.12) years. Maximum number of male patients were in 21-40 years age group (65.42%, 70). Maximum number of female patients were in 21-30 years age group (42.10%, 24). Maximum number of both male and female patients were in 21-30 years age group (35.97%, 59). Clinical features of 164 patients showed that 87.28% (143) had bloody diarrhoea, 20.12% (33) had per-rectal bleeding, 4.26% (7) had diarrhoea without per rectal bleeding, 1.21% (2) had urgency, 5.48% (9) had tenesmus, 33.53% (55) had abdominal pain, 17.66% (29) had fever, 18.29% (30) had anorexia, weakness and 17.68% (29) had weight loss at their initial presentation. Physical examination of 164 patients revealed that 81(49.39%) patients had normal findings, 7 (4.27%) patients had oedema and 83 (50.61%) patients had anaemia. Extra intestinal features were absent in 143 (87.20%) patients out of 164 patients. The rest 21 (12.80%) patients had joint involvement and 2 ( 1.21 % ) patients had ocular involvement. There was no patient with skin involvement. Conclusion: The clinical presentation of Ulcerative colitis in our country is mostly similar compared to other Asian' and Western countries except higher male-female ratio, presence of oedema and wide variability of extra intestinal involve­ment. These differences are probably due to social and cultural reasons, poor nutritional status, incomplete workup or records and influence of various enviornmental factors. To validate these results further prospective studies are needed

Efficacy of probiotics in irritable bowel syndrome: A randomized, double blind placebo-controlled study

Background: Gut flora have important trophic effects on intestinal epithelia and on immune structure and fonction.They also protect colonized host against invasion by alien microbes.Recent research suggests that an imbalance of the intestinal microbiota and a dysfunctional intestinal barrier might trigger irritable bowel syndrome (lBS). As probiotics have been reported to restore the intestinal microbiota and the gut barrier, the therapeutic potential of probiotics within IBS became of strong interest. Objectives: To assess the efficacy of probiotics in lBS. Methods: Patients of 15 to 60 years old and both sexes were included f om the out patient department (OPD) of gastroenterology, Bangabandhu Sheikh Mujib Medi­cal University (BSMMU). A validated lBS-QOL instmment consisted of 34 questions used to assess improvement of quality of Iife before and after treatment. A total of 65 diarrhoea predominant LBS patients were randomised to receive either probiotics(n-33) or placebo(n-32) twice daily frir 6 weeks.Results: At the end of 6 weeks therapy, improvement in various symptoms(abclominal pain, stool frequency, consistency and 11atulence) in probiotics group was statistically significant. Mean QOL score before treatment was 103 in probiotics group and I 06 in placebo group. After 6 weeks of treatment mean QOL score was 82 in probiotics group and I 02.58 in placebo group. No side effects of the therapeutic agents were observed in any patient during the trial. Conclusions: Probiotics effectively alleviates global IBS and improves TBS symptoms simultaneously with an improvement of quality of life

Invariant Scattering Transform for Medical Imaging

Invariant scattering transform introduces new area of research that merges the signal processing with deep learning for computer vision. Nowadays, Deep Learning algorithms are able to solve a variety of problems in medical sector. Medical images are used to detect diseases brain cancer or tumor, Alzheimer's disease, breast cancer, Parkinson's disease and many others. During pandemic back in 2020, machine learning and deep learning has played a critical role to detect COVID-19 which included mutation analysis, prediction, diagnosis and decision making. Medical images like X-ray, MRI known as magnetic resonance imaging, CT scans are used for detecting diseases. There is another method in deep learning for medical imaging which is scattering transform. It builds useful signal representation for image classification. It is a wavelet technique; which is impactful for medical image classification problems. This research article discusses scattering transform as the efficient system for medical image analysis where it's figured by scattering the signal information implemented in a deep convolutional network. A step by step case study is manifested at this research work.Comment: 11 pages, 8 figures and 1 tabl

Significance of Agricultural Finance in Agricultural and Rural Development of Pakistan “A Case Study of Qambar Shahdadkot District”

The purpose of this study is to investigate the significance of agricultural finance on agricultural and rural development of Pakistan. The study was based on primary data; the data was collected from Borrowers and Non Borrowers of agricultural finance from district Qambar shahdadkot, Sindh Province of Pakistan. Borrowers of agricultural finance include formal and non formal sources of finance. The results shows that the total revenue of Agricultural Finance borrowers was 76000 rupees while the non borrowers agricultural revenue was 61750 rupees and the variable cost for agricultural finance borrowers was a little bit high then non borrowers as 41652 and 34342 rupees respectively, it was because of availability of capital, the farmers who borrowing agricultural finance and providing inputs on time and in proper were getting better production. Most of the farmers agreed that agricultural finance was helpfull for improving living standard useful for household and rural development; it facilitates farmers in use of agricultural inputs on time and getting best agricultural production. Keywords: Agricultural Finance, rural development, Borrowers and Non Borrowers, total revenue, total cost, Variable costs, capital