<div style="text-align:justify;"> <span style="line-height:1.5;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">Pathologies transm...<div style="text-align:justify;"> <span style="line-height:1.5;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">Pathologies transmissible by hand such as gastrointestinal pathologies constitute a real public health problem, especially in sub-Saharan Africa where hygienic conditions are precarious. This study took place at Félix Houphou</span><span style="white-space:nowrap;font-family:Verdana;">ë</span><span style="font-family:Verdana;"></span></span><span style="font-family:Verdana;">t-Boigny</span></span><span "="" style="line-height:1.5;"><span style="font-family:Verdana;"> University from April to August 2018. The samples were taken from toilet surfaces such as doorknobs, tap heads, flush push buttons and seats WC. A total of three hundred and sixty-eight (368) samples were obtained, including 170 from the staff toilets and 198 from the student toilets. The results revealed the presence of total coliforms, </span><i><span style="font-family:Verdana;">Escherichia</span></i><span style="font-family:Verdana;"> spp and </span><i><span style="font-family:Verdana;">Salmonella</span></i><span style="font-family:Verdana;"><span style="font-family:Verdana;"> spp. The surfaces of student toilets were the most contaminated surfaces. The presence of entero-bacteria on the contact surfaces of the toilets of the Félix Houphou</span><span style="white-space:nowrap;font-family:Verdana;">ë</span><span style="font-family:Verdana;"></span></span><span style="font-family:Verdana;">t-Boigny university represents a health risk for the university population.</span></span> </div>展开更多
BACKGROUND Type 1 diabetes is an autoimmune disease leading to insulin deficiency,and it is mainly diagnosed in young adults.One of the major acute complications of type 1 diabetes is diabetic ketoacidosis(DKA),which ...BACKGROUND Type 1 diabetes is an autoimmune disease leading to insulin deficiency,and it is mainly diagnosed in young adults.One of the major acute complications of type 1 diabetes is diabetic ketoacidosis(DKA),which is a metabolic emergency that can be triggered by stress,infection,or poor blood glucose control.The association of DKA with conditions such as acute pancreatitis and malaria is rare and therefore represents a major diagnostic and therapeutic challenge.CASE SUMMARY A 20-year-old female was admitted to the emergency room for abdominal pelvic pain,fever,asthenia,polyuria,and polydipsia with a progressive deterioration of her state of consciousness.At admission,she was in a mild coma(Glasgow score:9),had a fever of 38.5°C,and had hyperglycemia(6 g/dL).The tests revealed severe DKA,hypertriglyceridemia,hyperamylasemia,and hyperlipasemia as well as malaria parasite density.The computed tomography scan confirmed acute stage E pancreatitis.The diagnosis was that of inaugural ketoacidosis of type 1 diabetes unbalanced by pancreatitis and malaria.Treatment included insulin therapy,rehydration,and antimalarial and analgesic treatment.After 10 days,the outcome was favorable with a normalization of the blood sugar,and an endocrine follow-up was recommend.CONCLUSION Rapid and multidisciplinary management of DKA,pancreatitis,and malaria led to a favorable and stable prognosis.展开更多
In the context of climate change,countries in West Africa are faced with recurrent flooding with catastrophic consequences,that makes it imperative to have access to rainfall information on fine spatial and temporal s...In the context of climate change,countries in West Africa are faced with recurrent flooding with catastrophic consequences,that makes it imperative to have access to rainfall information on fine spatial and temporal scales for better monitoring and prediction of these phenomena,as could be provided by weather radars.Based on an extensive archive of data from the X-band polarimetric radar and rain gauges observations gathered during the intensive AMMA campaigns in 2006–2007 and the Megha-Tropiques satellite measurement validation programme in 2010 in West Africa,we(i)simulated jointly realistic data for polarimetric radar variables and rain intensity using copula,and(ii)assessed rain rate estimation methods based on neural network(NN)inversion techniques and non-linearly calibrated parametric algorithms.The assessment of rainfall rate retrieval by these estimators is carried out using the part of the observations database not employed for calibration steps.The multiparametric algorithms R(ZH,K_(DP))and R(Z_(DR),K_(DP))perform better than R(ZH,Z_(DR))and R(ZH,Z_(DR),K_(DP)),especially since they are calibrated using copulas with upper tail dependencies,with KGE ranging in 0.68–0.75 and 0.79–0.82,respectively versus ranges of 0.40–0.64 and 0.20–0.51,for the two latter estimators.The neural network-based estimators RNN(Z_(DR),K_(DP))and RNN(ZH,K_(DP)),show KGE score characteristics comparable to those obtained from the best parametric relations,specifically optimized for the synthetic copula-based dataset.However,the neural network-based estimators were shown to be more robust when applied to a specific rainfall event.More specifically,neural network-based estimators trained on synthetic data are sensitive to the copulas’ability to capture the dependence between the variables of interest over the entire distribution of joint values.This leads to a near-cancellation of sensitivity to variability in the raindrop size distribution,as shown the coefficients of correlation near 1,especially for RNN(Z_(DR),K_(DP)),and for less extent RNN(Z_(H),K_(DP)).展开更多
About 44%of the world’s cocoa is produced in one single country,Côte d’Ivoire.Providing this important raw material,most Ivorian cocoa farmers live in severe poverty,which,despite a multitude of sector interven...About 44%of the world’s cocoa is produced in one single country,Côte d’Ivoire.Providing this important raw material,most Ivorian cocoa farmers live in severe poverty,which,despite a multitude of sector interventions,is still widespread,affecting social and environmental sustainability in cocoa production.In this context,cocoa farmers are still often treated as a homogeneous group of small-scale producers(mainly males),resulting in interventions being conceptualized as one-size-fits-all approaches and failing to deliver support schemes that take farmers’specific conditions appropriately into account.Applying a broader typology approach that combines farm characteristics with farmers’characteristics,this study aims to delineate Ivorian cocoa farmers and their farms into specific types in order to improve advice for targeted sustainability interventions and living income(LI)potentials.Principal component analysis and hierarchical clustering analysis of a household dataset collected in 2022 in five cocoa-growing regions of Côte d’Ivoire were chosen to identify types of male-headed farms.To assure gender sensitive analysis,a female-headed farm type was created artificially.The specific characteristics of the identified types were captured using descriptive analysis.Descriptive statistics and non-parametric tests were then applied to examine the relationships between these farm types and various outcomes.Additionally,a binary logistic model was used to estimate the probability of these links in relation to variables relevant for achieving a LI.Finally,Spearman non-parametric correlation was used to identify eventual differences in the strength of relationships between key variables per farm type.Three different types of male-headed farms are identified:type 1(the most productive and diversified farms with larger size),type 2(middle-sized farms with strong focus on cash crops),and type 3(small-sized farms with a good level of diversification for self-consumption).The artificially created type 4 represents female-headed farms with the smallest size.On average,none of these farm types achieves a LI.However,type 1 shows the smallest LI gap,while type 4 is by far the worst.Our analyses reveal underlying socio-economic factors systematically disadvantaging female-headed cocoa farms,most notably limited access to land and other material assets.The key contribution of this study lies in the empirical identification of the different characteristics of farms in a given farming system,thereby identifying the need for targeted support interventions.Type-specific recommendations are made,showing pathways to provide tailored programs to farmers of different types in order to reduce their LI gaps.展开更多
Pollution of transboundary rivers can result from anthropogenic activities in their watersheds.In this study,sediment traps were deployed to determine the fluxes,concentrations,and health risks associated with arsenic...Pollution of transboundary rivers can result from anthropogenic activities in their watersheds.In this study,sediment traps were deployed to determine the fluxes,concentrations,and health risks associated with arsenic,cadmium,mercury,lead,and iron in the estuaries of three transboundary rivers(Comoé,Bia,and Tanoé)in West Africa.Thus,the analysis of metal-associated sedimentation particle samples collected in rainy,flood,and dry seasons was required.Sediment traps were used to calculate the metal fluxes associated with sedimentation particles towards the Atlantic Ocean.Finally,the carcinogenic and non-carcinogenic risks of ingestion and dermal contact associated with sedimentation particles were assessed.The results showed that the total concentrations of trace metals in particulate matter were higher than in the UCC(Upper Crust Continental),with the exception of lead.The highest fluxes of lead,mercury,iron and arsenic associated with sedimented particles were observed during flood periods in the estuary of the Comoé,Bia and Tanoérivers.Cadmium fluxes associated with sedimentation particles were highest in the rainy season in the Bia and Comoéestuaries and in the flood season in the Tanoéestuary.Pearson’s correlation analysis and the enrichment factor showed that the trace metals were derived from anthropogenic activities such as mining and farming.In addition,contamination indices showed that sediment particles in the estuaries of the three rivers were severely contaminated with mercury.However,the results of potential human health risks associated with trace metals show that there is no probability of exposure of the community to harmful and carcinogenic effects through ingestion and dermal absorption of sediment particles.It is essential to integrate the information from this study into policy-and decision-making processes for better management of transboundary river water resources in coastal countries,particularly the Côte d’Ivoire.展开更多
The Pressure-Volume-Temperature(PVT)properties of crude oil are typically determined through laboratory analysis during the early phases of exploration and fielddevelopment.However,due to extensive data required,time-...The Pressure-Volume-Temperature(PVT)properties of crude oil are typically determined through laboratory analysis during the early phases of exploration and fielddevelopment.However,due to extensive data required,time-consuming nature,and high costs,laboratory methods are often not preferred.Machine learning,with its efficiencyand rapid convergence,has emerged as a promising alternative for PVT properties estimation.This study employs the modified particle swarm optimization-based group method of data handling(PSO-GMDH)to develop predictive models for estimating both the oil formation volume factor(OFVF)and bubble point pressure(P_(b)).Data from the Mpyo oil fieldin Uganda were used to create the models.The input parameters included solution gas-oil ratio(R_(s)),oil American Petroleum Institute gravity(API),specificgravity(SG),and reservoir temperature(T).The results demonstrated that PSO-GMDH outperformed backpropagation neural networks(BPNN)and radial basis function neural networks(RBFNN),achieving higher correlation coefficientsand lower prediction errors during training and testing.For OFVF prediction,PSO-GMDH yielded a correlation coefficient(R)of 0.9979(training)and 0.9876(testing),with corresponding root mean square error(RMSE)values of 0.0021 and 0.0099,and mean absolute error(MAE)values of 0.00055 and 0.00256,respectively.For P_(b)prediction,R was 0.9994(training)and 0.9876(testing),with RMSE values of 6.08 and 8.26,and MAE values of 1.35 and 2.63.The study also revealed that R_(s)significantlyimpacts OFVF and P_(b)predictions compared to other input parameters.The models followed physical laws and remained stable,demonstrating that PSO-GMDH is a robust and efficientmethod for predicting OFVF and P_(b),offering a time and cost-effective alternative.展开更多
还原型谷胱甘肽是一种重要的生物活性化合物,广泛应用于食品、医药和化妆品等领域,具有重要的实际应用价值和产业前景。通过5种树脂(LX-18,732,SP,HD-8,XDA-1)对谷胱甘肽进行静态吸附研究,筛选出在酸性条件下具有较高吸附量的732阳离子...还原型谷胱甘肽是一种重要的生物活性化合物,广泛应用于食品、医药和化妆品等领域,具有重要的实际应用价值和产业前景。通过5种树脂(LX-18,732,SP,HD-8,XDA-1)对谷胱甘肽进行静态吸附研究,筛选出在酸性条件下具有较高吸附量的732阳离子树脂。确定732树脂的动态吸附工艺:吸附流速为0.5 m L/min,最佳洗脱液为氯化钠溶液,且最佳洗脱浓度为2%,洗脱流速为0.8 m L/min,在最优条件下谷胱甘肽的回收率可以达到65.08%。展开更多
文摘<div style="text-align:justify;"> <span style="line-height:1.5;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">Pathologies transmissible by hand such as gastrointestinal pathologies constitute a real public health problem, especially in sub-Saharan Africa where hygienic conditions are precarious. This study took place at Félix Houphou</span><span style="white-space:nowrap;font-family:Verdana;">ë</span><span style="font-family:Verdana;"></span></span><span style="font-family:Verdana;">t-Boigny</span></span><span "="" style="line-height:1.5;"><span style="font-family:Verdana;"> University from April to August 2018. The samples were taken from toilet surfaces such as doorknobs, tap heads, flush push buttons and seats WC. A total of three hundred and sixty-eight (368) samples were obtained, including 170 from the staff toilets and 198 from the student toilets. The results revealed the presence of total coliforms, </span><i><span style="font-family:Verdana;">Escherichia</span></i><span style="font-family:Verdana;"> spp and </span><i><span style="font-family:Verdana;">Salmonella</span></i><span style="font-family:Verdana;"><span style="font-family:Verdana;"> spp. The surfaces of student toilets were the most contaminated surfaces. The presence of entero-bacteria on the contact surfaces of the toilets of the Félix Houphou</span><span style="white-space:nowrap;font-family:Verdana;">ë</span><span style="font-family:Verdana;"></span></span><span style="font-family:Verdana;">t-Boigny university represents a health risk for the university population.</span></span> </div>
文摘BACKGROUND Type 1 diabetes is an autoimmune disease leading to insulin deficiency,and it is mainly diagnosed in young adults.One of the major acute complications of type 1 diabetes is diabetic ketoacidosis(DKA),which is a metabolic emergency that can be triggered by stress,infection,or poor blood glucose control.The association of DKA with conditions such as acute pancreatitis and malaria is rare and therefore represents a major diagnostic and therapeutic challenge.CASE SUMMARY A 20-year-old female was admitted to the emergency room for abdominal pelvic pain,fever,asthenia,polyuria,and polydipsia with a progressive deterioration of her state of consciousness.At admission,she was in a mild coma(Glasgow score:9),had a fever of 38.5°C,and had hyperglycemia(6 g/dL).The tests revealed severe DKA,hypertriglyceridemia,hyperamylasemia,and hyperlipasemia as well as malaria parasite density.The computed tomography scan confirmed acute stage E pancreatitis.The diagnosis was that of inaugural ketoacidosis of type 1 diabetes unbalanced by pancreatitis and malaria.Treatment included insulin therapy,rehydration,and antimalarial and analgesic treatment.After 10 days,the outcome was favorable with a normalization of the blood sugar,and an endocrine follow-up was recommend.CONCLUSION Rapid and multidisciplinary management of DKA,pancreatitis,and malaria led to a favorable and stable prognosis.
文摘In the context of climate change,countries in West Africa are faced with recurrent flooding with catastrophic consequences,that makes it imperative to have access to rainfall information on fine spatial and temporal scales for better monitoring and prediction of these phenomena,as could be provided by weather radars.Based on an extensive archive of data from the X-band polarimetric radar and rain gauges observations gathered during the intensive AMMA campaigns in 2006–2007 and the Megha-Tropiques satellite measurement validation programme in 2010 in West Africa,we(i)simulated jointly realistic data for polarimetric radar variables and rain intensity using copula,and(ii)assessed rain rate estimation methods based on neural network(NN)inversion techniques and non-linearly calibrated parametric algorithms.The assessment of rainfall rate retrieval by these estimators is carried out using the part of the observations database not employed for calibration steps.The multiparametric algorithms R(ZH,K_(DP))and R(Z_(DR),K_(DP))perform better than R(ZH,Z_(DR))and R(ZH,Z_(DR),K_(DP)),especially since they are calibrated using copulas with upper tail dependencies,with KGE ranging in 0.68–0.75 and 0.79–0.82,respectively versus ranges of 0.40–0.64 and 0.20–0.51,for the two latter estimators.The neural network-based estimators RNN(Z_(DR),K_(DP))and RNN(ZH,K_(DP)),show KGE score characteristics comparable to those obtained from the best parametric relations,specifically optimized for the synthetic copula-based dataset.However,the neural network-based estimators were shown to be more robust when applied to a specific rainfall event.More specifically,neural network-based estimators trained on synthetic data are sensitive to the copulas’ability to capture the dependence between the variables of interest over the entire distribution of joint values.This leads to a near-cancellation of sensitivity to variability in the raindrop size distribution,as shown the coefficients of correlation near 1,especially for RNN(Z_(DR),K_(DP)),and for less extent RNN(Z_(H),K_(DP)).
基金This work was conducted in the frame of the accompanying research on strategies for improving farmer families’incomes and sustainable cocoa production funded by the German Federal Ministry for Economic Cooperation and Development(BMZ).
文摘About 44%of the world’s cocoa is produced in one single country,Côte d’Ivoire.Providing this important raw material,most Ivorian cocoa farmers live in severe poverty,which,despite a multitude of sector interventions,is still widespread,affecting social and environmental sustainability in cocoa production.In this context,cocoa farmers are still often treated as a homogeneous group of small-scale producers(mainly males),resulting in interventions being conceptualized as one-size-fits-all approaches and failing to deliver support schemes that take farmers’specific conditions appropriately into account.Applying a broader typology approach that combines farm characteristics with farmers’characteristics,this study aims to delineate Ivorian cocoa farmers and their farms into specific types in order to improve advice for targeted sustainability interventions and living income(LI)potentials.Principal component analysis and hierarchical clustering analysis of a household dataset collected in 2022 in five cocoa-growing regions of Côte d’Ivoire were chosen to identify types of male-headed farms.To assure gender sensitive analysis,a female-headed farm type was created artificially.The specific characteristics of the identified types were captured using descriptive analysis.Descriptive statistics and non-parametric tests were then applied to examine the relationships between these farm types and various outcomes.Additionally,a binary logistic model was used to estimate the probability of these links in relation to variables relevant for achieving a LI.Finally,Spearman non-parametric correlation was used to identify eventual differences in the strength of relationships between key variables per farm type.Three different types of male-headed farms are identified:type 1(the most productive and diversified farms with larger size),type 2(middle-sized farms with strong focus on cash crops),and type 3(small-sized farms with a good level of diversification for self-consumption).The artificially created type 4 represents female-headed farms with the smallest size.On average,none of these farm types achieves a LI.However,type 1 shows the smallest LI gap,while type 4 is by far the worst.Our analyses reveal underlying socio-economic factors systematically disadvantaging female-headed cocoa farms,most notably limited access to land and other material assets.The key contribution of this study lies in the empirical identification of the different characteristics of farms in a given farming system,thereby identifying the need for targeted support interventions.Type-specific recommendations are made,showing pathways to provide tailored programs to farmers of different types in order to reduce their LI gaps.
文摘Pollution of transboundary rivers can result from anthropogenic activities in their watersheds.In this study,sediment traps were deployed to determine the fluxes,concentrations,and health risks associated with arsenic,cadmium,mercury,lead,and iron in the estuaries of three transboundary rivers(Comoé,Bia,and Tanoé)in West Africa.Thus,the analysis of metal-associated sedimentation particle samples collected in rainy,flood,and dry seasons was required.Sediment traps were used to calculate the metal fluxes associated with sedimentation particles towards the Atlantic Ocean.Finally,the carcinogenic and non-carcinogenic risks of ingestion and dermal contact associated with sedimentation particles were assessed.The results showed that the total concentrations of trace metals in particulate matter were higher than in the UCC(Upper Crust Continental),with the exception of lead.The highest fluxes of lead,mercury,iron and arsenic associated with sedimented particles were observed during flood periods in the estuary of the Comoé,Bia and Tanoérivers.Cadmium fluxes associated with sedimentation particles were highest in the rainy season in the Bia and Comoéestuaries and in the flood season in the Tanoéestuary.Pearson’s correlation analysis and the enrichment factor showed that the trace metals were derived from anthropogenic activities such as mining and farming.In addition,contamination indices showed that sediment particles in the estuaries of the three rivers were severely contaminated with mercury.However,the results of potential human health risks associated with trace metals show that there is no probability of exposure of the community to harmful and carcinogenic effects through ingestion and dermal absorption of sediment particles.It is essential to integrate the information from this study into policy-and decision-making processes for better management of transboundary river water resources in coastal countries,particularly the Côte d’Ivoire.
基金support from the Chinese Scholarship Council(Grant No.2022GXZ005733)。
文摘The Pressure-Volume-Temperature(PVT)properties of crude oil are typically determined through laboratory analysis during the early phases of exploration and fielddevelopment.However,due to extensive data required,time-consuming nature,and high costs,laboratory methods are often not preferred.Machine learning,with its efficiencyand rapid convergence,has emerged as a promising alternative for PVT properties estimation.This study employs the modified particle swarm optimization-based group method of data handling(PSO-GMDH)to develop predictive models for estimating both the oil formation volume factor(OFVF)and bubble point pressure(P_(b)).Data from the Mpyo oil fieldin Uganda were used to create the models.The input parameters included solution gas-oil ratio(R_(s)),oil American Petroleum Institute gravity(API),specificgravity(SG),and reservoir temperature(T).The results demonstrated that PSO-GMDH outperformed backpropagation neural networks(BPNN)and radial basis function neural networks(RBFNN),achieving higher correlation coefficientsand lower prediction errors during training and testing.For OFVF prediction,PSO-GMDH yielded a correlation coefficient(R)of 0.9979(training)and 0.9876(testing),with corresponding root mean square error(RMSE)values of 0.0021 and 0.0099,and mean absolute error(MAE)values of 0.00055 and 0.00256,respectively.For P_(b)prediction,R was 0.9994(training)and 0.9876(testing),with RMSE values of 6.08 and 8.26,and MAE values of 1.35 and 2.63.The study also revealed that R_(s)significantlyimpacts OFVF and P_(b)predictions compared to other input parameters.The models followed physical laws and remained stable,demonstrating that PSO-GMDH is a robust and efficientmethod for predicting OFVF and P_(b),offering a time and cost-effective alternative.
文摘还原型谷胱甘肽是一种重要的生物活性化合物,广泛应用于食品、医药和化妆品等领域,具有重要的实际应用价值和产业前景。通过5种树脂(LX-18,732,SP,HD-8,XDA-1)对谷胱甘肽进行静态吸附研究,筛选出在酸性条件下具有较高吸附量的732阳离子树脂。确定732树脂的动态吸附工艺:吸附流速为0.5 m L/min,最佳洗脱液为氯化钠溶液,且最佳洗脱浓度为2%,洗脱流速为0.8 m L/min,在最优条件下谷胱甘肽的回收率可以达到65.08%。
