COMPARACIÓN TEÓRICO – EXPERIMENTAL DEL COMPORTAMIENTO A FLEXIÓN DE VIGAS DE HORMIGÓN ARMADO MEDIANTE GRÁFICAS MOMENTO-CURVATURA

  Para vigas de hormigón armado el confinamiento mediante el refuerzo transversal mejora su desempeño a flexión (acción simultánea de tracción y compresión), permitiendo mayor resistencia y como consecuencia mayores deformaciones, a la vez que incrementa la ductilidad del elemento, misma propiedad que relaciona la capacidad estructural en el rango elástico y plástico en función de los desplazamientos, todo esto resumido en la gráfica momento-curvatura (M-Φ). El presente trabajo muestra la comparación teórico-experimental del comportamiento a flexión de vigas de hormigón armado mediante la gráfica momento-curvatura, partiendo de una viga base con geometría estándar preestablecida, que se ensaya con una configuración de simple apoyo sometida a una fuerza puntual creciente en el centro de la luz que delimita su deformación. A partir de resultados de ensayos experimentales realizados en la Universidad Técnica de Manabí se genera la gráfica momento curvatura (M-Φ), misma que es confrontada con la obtenida a partir de softwares de elementos finitos y puesta en consideración en base a las teorías clásicas de la flexión del hormigón. En virtud de los resultados obtenidos a partir de la calibración de un modelo de elementos finitos con un porcentaje de error del 2,89% en función de los puntos de cedencia de la gráfica momento-curvatura entre el modelo experimental y el modelo de elementos finitos, se llega a la conclusión de que el elemento puesto en estudio sufre los mismos efectos de fallas (falla primaria: dúctil, falla secundaria: frágil) las cuales están determinadas por el comportamiento que adquiere la gráfica momento curvatura (M-Φ) en dependencia de las deformaciones de los materiales.   Palabras claves: Deformaciones, desplazamientos, gráfica momento curvatura, ensayos experimentales, elementos finitos, teorías clásicas.   Abstract— For reinforced concrete beams, confinement through transverse reinforcement improves their flexural performance (simultaneous action of tension and compression), allowing greater resistance and consequently greater deformations, while increasing the ductility of the element, the same property that relates to capacity. Structural in the elastic and plastic range as a function of the displacements, all this summarized in the moment-curvature graph (M-Φ). The present work shows the theoretical-experimental comparison of the bending behavior of reinforced concrete beams through the moment-curvature graph, starting from a base beam with pre-established standard geometry, which is tested with a simple support configuration subjected to an increasing point force in the center of the light that defines its deformation. From the results of experimental tests carried out at the Universidad Técnica de Manabí, the curvature moment graph (M-Φ) is generated, which is compared with that obtained from finite element software and taken into consideration based on classical theories. of concrete flexure. By virtue of the results obtained from the calibration of a finite element model with an error percentage of 2.89% as a function of the yield points of the moment-curvature graph between the experimental model and the finite element model , it is concluded that the element under study suffers the same failure effects (primary failure: ductile, secondary failure: brittle) which are determined by the behavior acquired by the curve moment graph (M-Φ) in dependence of the deformations of the materials. Index Terms: Strains, displacement, moment curvature graph, experimental essays, finite elements, classical theories

Probabilistic dietary based estimation of the burden of aflatoxin-induced hepatocellular carcinoma among adult Malawians

This research article published by Wageningen Academic Publishers, 2019The risk of aflatoxin-induced hepatocellular carcinoma (HCC) among adults (average body weight of 60 kg) in Malawi was assessed based on aflatoxin B1 (AFB1) exposure through groundnut and maize consumption, by Monte Carlo simulation. The risk (cases per year per 100,000 people) of aflatoxin-induced HCC was estimated based on the AFB1 exposures estimated by this study and hepatitis B virus infection prevalence published for Malawi. AFB1 exposures were estimated by probabilistically combining data of AFB1 contamination in 338 groundnut and 604 maize samples with data of per capita groundnut and maize consumption in 274 households. Aflatoxins in the samples were analysed using validated LC-MS/MS, HPLC and VICAM based methods. The groundnut and maize consumption survey was based on household expenditure technique. The simulated mean AFB1 exposures through consumption of groundnuts, maize, and combination thereof were 28±65, 42±174, and 71±211 ng/kg. body weight (bw)/day, respectively. The estimated HCC risks were 1.26±2.72, 1.86±6.66 and 3.10±6.85 cases per 100,000 persons per year, respectively. Further, hypothetical eradication of hepatitis B virus (HBV) reduced the risk of HCC by 78%. This reaffirms the need for integrating HBV vaccination in the fight of aflatoxin induced HCC

Comparative study for the performance of pure artificial intelligence software sensor and self-organizing map assisted software sensor in predicting 5-day biochemical oxygen demand for Kauma Sewage Treatment Plant effluent in Malawi

Introduction: Modeling plays a crucial role in understanding wastewater treatment processes, yet conventional deterministic models face challenges due to complexity and uncertainty. Artificial intelligence offers an alternative, requiring no prior system knowledge. This study tested the reliability of the Adaptive Fuzzy Inference System (ANFIS), an artificial intelligence algorithm that integrates both neural networks and fuzzy logic principles, to predict effluent Biochemical Oxygen Demand. An important indicator of organic pollution in wastewater.Materials and Methods: The ANFIS models were developed and validated with historical wastewater quality data for the Kauma Sewage Treatment Plant located in Lilongwe City, Malawi. A Self Organizing Map (SOM) was applied to extract features of the raw data to enhance the performance of ANFIS. Cost-effective, quicker, and easier-to-measure variables were selected as possible predictors while using their respective correlations with effluent. Influents’ temperature, pH, dissolved oxygen, and effluent chemical oxygen demand were among the model predictors.Results and Discussions: The comparative results demonstrated that for the same model structure, the ANFIS model achieved correlation coefficients (R) of 0.92, 0.90, and 0.81 during training, testing, and validation respectively, whereas the SOM-assisted ANFIS Model achieved R Values of 0.99, 0.87 and 0.94. Overall, despite the slight decrease in R-value during the testing stage, the SOM- assisted ANFIS model outperformed the traditional ANFIS model in terms of predictive capability. A graphic user interface was developed to improve user interaction and friendliness of the developed model. Integration of the developed model with supervisory control and data acquisition system is recommended. The study also recommends widening the application of the developed model, by retraining it with data from other wastewater treatment facilities and rivers in Malawi

Odor Identification Impairment and Change with Cholinesterase Inhibitor Treatment in Mild Cognitive Impairment

Background: Anticholinergic challenge can induce odor identification impairment that indicates Alzheimer’s disease (AD) pathology, and short-term change in odor identification impairment with cholinesterase inhibitor (CheI) treatment may predict longer term cognitive outcomes. Objective: In patients with mild cognitive impairment (MCI) treated prospectively with donepezil, a CheI, for 52 weeks, to determine if 1) acute decline in odor identification ability with anticholinergic challenge can predict cognitive improvement, and 2) change in odor identification over 8 weeks can predict cognitive improvement. Methods: MCI was diagnosed clinically without AD biomarkers. At baseline, the University of Pennsylvania Smell identification Test (UPSIT) was administered before and after an anticholinergic atropine nasal spray challenge. Donepezil was started at 5 mg daily, increased to 10 mg daily if tolerated, and this dose was maintained for 52 weeks. Main outcomes were ADAS-Cog total score and Selective Reminding Test (SRT) total immediate recall score measured at baseline, 26 and 52 weeks. Results: In 100 study participants, mean age 70.14 (SD 9.35) years, atropine-induced decrease in UPSIT score at baseline was not associated with change in ADAS-Cog or SRT scores over 52 weeks. Change in UPSIT score from 0 to 8 weeks did not show a significant association with change in the ADAS-Cog or SRT measures over 52 weeks. Conclusion: These negative findings in a relatively large sample of patients with MCI did not replicate results in much smaller samples. Change in odor identification with anticholinergic challenge, and over 8 weeks, may not be useful predictors of cognitive improvement with CheI in patients with MCI

Adopt or Adapt: Sanitation Technology Choices in Urbanizing Malawi.

This paper presents the results of a mixed-methods study examining adaptation strategies that property owners in low-income, rapidly urbanizing areas in Malawi adopt to address the limitations of pit latrines, the most common method of disposing human excreta. A particular challenge is lack of space for constructing new latrines as population density increases: traditional practice has been to cap full pits and simply move to a new site, but increasing demands on space require new approaches to extend the service life of latrines. In this context, we collected data on sanitation technology choices from January to September 2013 through 48 in-depth interviews and a stated preference survey targeting 1,300 property owners from 27 low-income urban areas. Results showed that property owners with concern about space for replacing pit latrines were 1.8 times more likely to select pit emptying service over the construction of new pit latrines with a slab floor (p = 0.02) but there was no significant association between concern about space for replacing pit latrines and intention to adopt locally promoted, novel sanitation technology known as ecological sanitation (ecosan). Property owners preferred to adapt existing, known technology by constructing replacement pit latrines on old pit latrine locations, reducing the frequency of replacing pit latrines, or via emptying pit latrines when full. This study highlights potential challenges to adoption of wholly new sanitation technologies, even when they present clear advantages to end users. To scale, alternative sanitation technologies for rapidly urbanising cities should offer clear advantages, be affordable, be easy to use when shared among multiple households, and their design should be informed by existing adaptation strategies and local knowledge

Evaluating barriers to effective rural stakeholder engagement in catchment management in Malawi

Water quality and quantity are heavily influenced by catchment management, yet without participation by local communities, opportunities for enhanced protection and conservation in rural areas is limited. This paper explores the factors hindering local participation in catchment management, analysing stakeholder engagement by conducting in-depth interviews, focus group discussions and evidence syntheses in three contrasting catchments in Malawi. Our findings reveal omission of key actors in the catchment management process. Rural communities were least involved in catchment management. Barriers limiting participation were found to be interlinked and complex including weak regulatory frameworks, inadequate resources, lack of commitment, corruption, resistance to change, poor coordination, and cultural factors. Analysis of the interlinkages highlighted areas for intervention in promoting stakeholder participation which would, in turn, improve water security at catchment level. A comprehensive theory of change-based engagement framework that considers specific socio-cultural, economic, and political contexts to overcome the identified barriers is proposed

Water allocation using system dynamic modelling in the aquaculture integrated with small-scale irrigation systems in Malawi

The agricultural sector is faced with numerous challenges including climate change and water scarcity in many developing countries. In order to address scarcity and improve water use efficiency for rural farmers, fish farming is being integrated with small-scale irrigation. However, there are challenges in how to allocate water between the two farming enterprises. This study explored the capabilities of system dynamics to allocate water between a fish pond and a crop field in Chingale, Malawi using a system dynamic software, Vensim™ PLE. For soil water and pond water, a simple water balance structure was built and connected to the crop growth structure. Simulations run for 125 days corresponding to the maize growth period. Model results are similar to the actual yield (about 3.5 ton/ha for hybrid) and biomass production (about 7 ton/ha) in the area. Results also show it was possible to maintain pond water depth at recommended depths for raising fish: fish stocking (1 m), operation of the pond (1.5–2.0 m) and harvesting of the fish (less than 1.2 m) throughout the maize growing period. While the study did not comprehensively build and simulate fish growth, the use of such simple tools would benefit rural farmers with few resources. Based on the promising capabilities and the results of the tool it is recommended that further comprehensive analysis to fully incorporate all key sub-components affecting crop and fish growth be carried out

Infilling missing data and outliers for a conventional sewage treatment plant using a self-organizing map: a case study of Kauma Sewage Treatment Plant in Lilongwe, Malawi

Data availability is key for modeling of wastewater treatment processes. However, process data are characterized by missing values and outliers. This study applied a self-organizing map (SOM) to fill in missing values and replace outliers in wastewater treatment data from Kauma Sewage Treatment Plant in Lilongwe, Malawi. We used primary and secondary wastewater data and executed the SOM algorithm to fill missing values and replace outliers in effluent pH, biochemical oxygen demand, and dissolved oxygen. The results suggest that the SOM algorithm is reliable in filling gaps in wastewater time series data with less than 50% missing values with correlation coefficient (R) values of >0.90. The SOM algorithm failed to reliably fill gaps and replace outliers in time series data with >50% missing values. For instance, high mean square error (MSE) values of 3,655.57, 10.62, and 2,153.34 for pH, DO, and BOD, respectively, were registered in datasets with more than 50% missing values, while very small MSE values (MSE ≈ 0) were associated with effluent pH, BOD, and DO data with missing values of >50%. Practitioners can use this approach to improve the planning and management of wastewater treatment facilities where available data records are riddled with missing observations. HIGHLIGHTS Missing data impinge on wastewater treatment plant processes efficiency.; The advancement of information technology and artificial intelligence enables the infilling of missing data.; We proposed to infill missing data and outliers using a Multivariate model called the Self-Organizing Map.; Missing data and outliers are replaced with reasonable estimates.; The approach has provided long series data for modelling the behavior of the wastewater treatment process.

The retina as a window to the basal ganglia: Systematic review of the potential link between retinopathy and hyperkinetic disorders in diabetes

There is evidence that glycemic fluctuations trigger vascular-mediated dysfunction in both the retina and the striatopallidal regions in patients with diabetes. The latter is associated with a variety of hyperkinetic disorders that are rare but disabling and potentially preventable. We conducted a systematic review of the potential association between diabetic retinopathy and the risk and prognosis of hyperkinetic disorders in patients with diabetes. We identified a total of 461 articles and 147 were eligible for review. Nine out of 147 articles (6.12%) reported 13 patients with information on diabetic retinopathy. Glycemic fluctuations were present at onset in 10 patients (77%) and retinopathy was present in nine of them (69.23%). The degree of retinopathy was reported in four patients. Two had severe, bilateral proliferative retinopathy, one had moderate-to-severe non-proliferative retinopathy and one had non-proliferative retinopathy. In the nine patients with retinopathy, hyperkinesia persisted, required higher doses of dopamine receptor antagonists or deep brain stimulation. Retinopathy was absent in four cases (30.77%). In these patients, hyperkinesia resolved spontaneously or with lower doses of dopamine receptor antagonists. Diabetic retinopathy could be an indirect marker of striatopallidal microangiopathy in patients with diabetes. The severity of retinopathy may be associated with increased risk or worse prognosis for patients who develop hyperkinetic disorders of the diabetic striatopathy spectrum. Early detection of retinopathy could identify patients in which avoiding glycemic fluctuations may prevent the development of striatopathy and hyperkinetic disorders. •In diabetes, vascular dysfunction occurs in the retina and striatopallidal regions.•Glycemic fluctuations often precede deterioration in retinopathy and striatopathy.•Diabetic retinopathy could be an indirect marker of striatopallidal microangiopathy

Likelihood of selecting ecological sanitation over pit latrines when there is concern about space for pit latrines (n = 1198).

<p>Likelihood of selecting ecological sanitation over pit latrines when there is concern about space for pit latrines (n = 1198).</p