Solar Irrigation Pump (SIP) sizing tool: user manual (Beta version)

Santosh Mali Paresh Shirsath (2022, [Libro])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA SOLAR POWERED IRRIGATION SYSTEMS PUMPS IRRIGATION WATER MANUALS

The input reduction principle of agroecology is wrong when it comes to mineral fertilizer use in sub-Saharan Africa

Gatien Falconnier Marc Corbeels Frédéric Baudron Antoine Couëdel leonard rusinamhodzi bernard vanlauwe Ken Giller (2023, [Artículo])

Can farmers in sub-Saharan Africa (SSA) boost crop yields and improve food availability without using more mineral fertilizer? This question has been at the center of lively debates among the civil society, policy-makers, and in academic editorials. Proponents of the “yes” answer have put forward the “input reduction” principle of agroecology, i.e. by relying on agrobiodiversity, recycling and better efficiency, agroecological practices such as the use of legumes and manure can increase crop productivity without the need for more mineral fertilizer. We reviewed decades of scientific literature on nutrient balances in SSA, biological nitrogen fixation of tropical legumes, manure production and use in smallholder farming systems, and the environmental impact of mineral fertilizer. Our analyses show that more mineral fertilizer is needed in SSA for five reasons: (i) the starting point in SSA is that agricultural production is “agroecological” by default, that is, very low mineral fertilizer use, widespread mixed crop-livestock systems and large crop diversity including legumes, but leading to poor soil fertility as a result of widespread soil nutrient mining, (ii) the nitrogen needs of crops cannot be adequately met solely through biological nitrogen fixation by legumes and recycling of animal manure, (iii) other nutrients like phosphorus and potassium need to be replaced continuously, (iv) mineral fertilizers, if used appropriately, cause little harm to the environment, and (v) reducing the use of mineral fertilizers would hamper productivity gains and contribute indirectly to agricultural expansion and to deforestation. Yet, the agroecological principles directly related to soil fertility—recycling, efficiency, diversity—remain key in improving soil health and nutrient-use efficiency, and are critical to sustaining crop productivity in the long run. We argue for a nuanced position that acknowledges the critical need for more mineral fertilizers in SSA, in combination with the use of agroecological practices and adequate policy support.

Manure Crop Yields Smallholder Farming Systems Environmental Hazards CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA BIOLOGICAL NITROGEN FIXATION LEGUMES NUTRIENT BALANCE SOIL FERTILITY AGROECOLOGY YIELD INCREASES LITERATURE REVIEWS

Closing the yield gap of soybean (Glycine max (L.) Merril) in Southern Africa: a case of Malawi, Zambia, and Mozambique

Siyabusa Mkuhlani Isaiah Nyagumbo (2023, [Artículo])

Introduction: Smallholder farmers in Sub-Saharan Africa (SSA) are increasingly producing soybean for food, feed, cash, and soil fertility improvement. Yet, the difference between the smallholder farmers’ yield and either the attainable in research fields or the potential from crop models is wide. Reasons for the yield gap include low to nonapplication of appropriate fertilizers and inoculants, late planting, low plant populations, recycling seeds, etc. Methods: Here, we reviewed the literature on the yield gap and the technologies for narrowing it and modelled yields through the right sowing dates and suitable high-yielding varieties in APSIM. Results and Discussion: Results highlighted that between 2010 and 2020 in SSA, soybean production increased; however, it was through an expansion in the cropped area rather than a yield increase per hectare. Also, the actual smallholder farmers’ yield was 3.8, 2.2, and 2.3 times lower than the attainable yield in Malawi, Zambia, and Mozambique, respectively. Through inoculants, soybean yield increased by 23.8%. Coupling this with either 40 kg ha−1 of P or 60 kg ha−1 of K boosted the yields by 89.1% and 26.0%, respectively. Overall, application of 21–30 kg ha-1 of P to soybean in SSA could increase yields by about 48.2%. Furthermore, sowing at the right time increased soybean yield by 300%. Although these technologies enhance soybean yields, they are not fully embraced by smallholder farmers. Hence, refining and bundling them in a digital advisory tool will enhance the availability of the correct information to smallholder farmers at the right time and improve soybean yields per unit area.

Decision Support Tools Digital Tools Site-Specific Recommendations CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA DECISION SUPPORT SYSTEMS LEGUMES YIELDS SOYBEANS

Seasonal climate forecasts (SCFs) based risk management strategies: A case study of rainfed rice cultivation in India

Nand Lal Kushwaha Paresh Shirsath Dipaka Ranjan Sena (2022, [Artículo])

FResampler1 Seasonal Climate Forecasts Decision Support System for Agrotechnology Transfer CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CLIMATE CHANGE DECISION SUPPORT SYSTEMS YIELDS RICE RISK MANAGEMENT

How a holobiome perspective could promote intensification, biosecurity and eco-efficiency in the shrimp aquaculture industry

Eric Daniel Gutiérrez Pérez RICARDO VAZQUEZ JUAREZ FRANCISCO JAVIER MAGALLON BARAJAS MIGUEL ANGEL MARTINEZ MERCADO GRISEL ALEJANDRA ESCOBAR ZEPEDA Paola Magallón Servín (2022, [Artículo])

"The aquaculture industry faces many challenges regarding the intensification of shrimp rearing systems. One of these challenges is the release of excessive amounts of nitrogen and phosphorus into coastal areas, causing disruption in nutrient cycling and microbial equilibrium, which are important for coastal productivity. Biosecurity within the shrimp rearing systems can also be compromised by disruption to the nutrient fluxes, and as consequence the microbiome of the system. In certain conditions, these changes could lead to the blooming of potentially pathogenic bacteria. These changes in the external microbiome of the system and the constant fluctuations of nutrients can affect the intestinal microbiome of shrimp, which is involved in the growth and development of the host, affecting nutrient absorption, regulating metabolic processes, synthesising vitamins, modulating the immune response and preventing growth of pathogenic bacteria. It has been suggested that specific changes in the intestinal microbiome of Litopenaeus vannamei may be an avenue through which to overcome some of the problems that this industry faces, in terms of health, growth and waste. Recent research, however, has focussed mainly on changes in the intestinal microbiome. Researchers have overlooked the relevance of other aspects of the system, such as the microbiome from the benthic biofilms; zooplankton, plankton and bacterioplankton; and other sources of microorganisms that can directly affect the microbial status of the intestinal and epiphytic communities, especially in rearing systems that are based on intensification and microbial maturation processes, such as a biofloc system. It is therefore necessary to place holobiome studies into context, including the ‘holobiome of the aquaculture system’ (microbiomes that make up the culture system and their interactions) and not only the intestinal microbiome. Thus, we describe factors that affect the shrimp microbiome, the methodology of study, from sampling to bioinformatic workflows, and introduce the concept of the ‘holobiome of the aquaculture system’ and how this enables us to promote the intensification, biosafety and eco-efficiency of shrimp farming. The holobiome perspective implies a greater investment of resources and time for research, but it will accelerate the development of technology that will benefit the development and sustainability of the aquaculture industry."

litopenaeus vannamei, microbiome, intensification, biofloc, holobiome of aquaculture systems CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CIENCIAS AGRARIAS PRODUCCIÓN ANIMAL NUTRICIÓN NUTRICIÓN

Evaluación de la cinética de liberación de compuestos hidrofílicos y lipofílicos a partir de nanopartículas híbridas polímero-lípido

Evaluation of the release kinetics of hydrophilic and lipophilic compounds from polymer-lipid hybrid nanoparticles

Juan Pablo Carmona Almazán (2023, [Tesis de maestría])

En el tratamiento de enfermedades, la administración de dosis múltiples es una estrategia común para mantener la concentración de los fármacos dentro de un margen terapéutico. Sin embargo, la adherencia de los pacientes a este tipo de tratamiento puede ser un desafío, llevando a una administración irregular de dosis. Una alternativa utilizada para abordar este reto son las nanopartículas híbridas polímero/lípido(NPPLs), las cuales, con menos administraciones, tienen el potencial de alcanzar la dosis necesaria en el tratamiento, posibilitando entonces el incremento del apego al tratamiento. En nuestro proyecto, se llevó a cabo la síntesis de nanopartículas de ácido poli láctico-co-glicólico (PLGA) recubiertas de lecitina de soya, por medio de técnicas de nanoprecipitación y autoensamblaje. Además, integramos estas nanopartículas en una matriz polimérica a base de aerogeles de gelatina de manera que estuvieran distribuidas de manera homogénea y concentrada. Nuestro enfoque central radica en entender la cinética de liberación de un compuesto hidrofílico (ácido gálico) y uno lipofílico (quercetina) a partir de este sistema. Logramos sintetizar nanopartículas con un diámetro hidrodinámico de 100 ± 15 nm, 153 ± 33 y149±21 nm, en el caso de las nanopartículas vacías y cargadas con ácido gálico y cargadas con quercetina, respectivamente. La eficiencia de encapsulación del ácido gálico fue del 90 ± 5 % y de la quercetina fue del 70 ± 10 %. Los resultados que obtuvimos muestran que el ácido gálico sigue una cinética del modelo de Korsmeyer-Peppas, con un valor de n = 1.01 y la quercetina una cinética de primer orden. Dado que los compuestos encapsulados tuvieron una liberación más lenta con respecto a los compuestos libres en los aerogeles de gelatina, nuestro trabajo indica que el encapsulamiento en NPPLs de un compuesto bioactivo, independientemente de su naturaleza química, puede ayudar a retrasar su liberación y reducir el número de dosis administradas, en consecuencia, esto pudiera contribuir a incrementar el apego de un paciente al tratamiento.

In the treatment of diseases, the administration of multiple doses is a common strategy to maintain drug concentrations within a therapeutic range. However, patient adherence to this type of treatment can be challenging, resulting in irregular dosing. An alternative approach used to address this challenge involves polymer/lipid hybrid nanoparticles (NPPLs), which have the potential to achieve the necessary drug dose with fewer administrations, thereby increasing treatment adherence. In our project, we synthesized poly(lactic-co-glycolic acid) (PLGA) nanoparticles coated with soy lecithin using nanoprecipitation and self-assembly techniques. These nanoparticles were then integrated into a polymer matrix based on gelatin aerogels to ensure homogeneous and concentrated distribution. Our main focus was to understand the release kinetics of a hydrophilic compound (gallic acid) and a lipophilic one (quercetin) from this system. We successfully synthesized nanoparticles with a hydrodynamic diameter of 100 ± 15 nm, 153 ± 33 nm, and 149 ± 21 nm for empty nanoparticles, gallic acid-loaded, and quercetin-loaded nanoparticles, respectively. The encapsulation efficiency was 90 ± 5 % for gallic acid and 70 ± 10 % for quercetin. The results we obtained indicate that gallic acid follows Korsmeyer-Peppas kinetics with a value of n = 1.01, while quercetin exhibits first-order kinetics. Since the encapsulated compounds showed slower release compared to free compounds in gelatin aerogels, our work suggests that encapsulation in NPPLs with a bioactive compound, regardless of its chemical nature, can help delay its release and reduce the number of doses administered. Consequently, this could contribute to improve patient treatment adherence.

nanopartículas híbridas, cinética de liberación, sistemas poliméricos, PLGA/lecitina, compuestos hidrofílicos y lipofílicos hybrid nanoparticles, release kinetics, polymeric systems, PLGA/lecithin, hydrophilic and lipophilic compounds INGENIERÍA Y TECNOLOGÍA CIENCIAS TECNOLÓGICAS INGENIERÍA Y TECNOLOGÍA QUÍMICAS ANÁLISIS DE POLÍMEROS ANÁLISIS DE POLÍMEROS

Usando la descomposición de un grafo Halin para el diseño de algoritmos autoestabilizantes

Using Halin graph decomposition for the design of self-stabilizing algorithm

Daniel Uriel Orozco Lomelí (2023, [Tesis de maestría])

Sea G = (V, E) un grafo no dirigido. El problema de encontrar un conjunto independiente fuerte en G, es identificar un conjunto S ⊆ V , tal que dados dos vértices arbitrarios de S, éstos estén separados entre sí por el menos tres aristas. Encontrar un conjunto S de tamaño máximo pertenece a la clase NP-Difícil. Por otro lado, el problema de encontrar un conjunto dominante total en G es identificar un conjunto D ⊆ V , tal que cualquier vértice en V tenga al menos un vecino que pertenezca a D. Encontrar un conjunto D de tamaño mínimo también pertenece a la clase NP-Difícil. En este trabajo de tesis se diseñaron dos algoritmos, uno que resuelve el problema de encontrar un conjunto independiente fuerte maximal y otro que resuelve el problema de encontrar un conjunto dominante total minimal. Estos dos problemas son menos restrictivos que las versiones de optimización descritas al principio de este texto y se sabe que pertenecen a la clase P. Los algoritmos diseñados corren en un sistema distribuido, son autoestabilizantes, son tolerantes a fallas transitorias y funcionan para grafos Halin. Los grafos Halin pertenecen a la clase de grafos 2-outerplanares y tienen la propiedad de que se pueden partir en dos subgrafos muy conocidos, un árbol y un ciclo. Los algoritmos propuestos aprovechan la propiedad anterior para disminuir la complejidad de los mismos. Hasta donde tenemos conocimiento, los algoritmos propuestos, que corren en tiempo lineal en el número de vértices, son los algoritmos más rápidos existentes para los problemas del conjunto independiente fuerte maximal y el conjunto dominante total minimal.

Let G = (V, E) be an undirected graph. The problem of finding a strong stable set in G, is to identify a set S ⊆ V , such that given two arbitrary vertices of S, they are separated from each other by at least three edges. Finding a set S of maximum size belongs to the class NP-Hard. On the other hand, the problem of finding a total dominanting set in G is to identify a set D ⊆ V , such that any vertex in V has at least one neighbor belonging to D. Finding a set D of minimum size also belongs to the class NP-Hard. In this thesis work, two algorithms were designed, one that solves the problem of finding a maximal strong stable set and one that solves the problem of finding a minimal total dominanting set. These two problems are less restrictive than the optimization versions described at the beginning of this text and are known to belong to the P class. The designed algorithms run on a distributed system, are self-stabilizing, are transient fault tolerant, and work for Halin graphs. Halin graphs belong to the 2-outerplanar class of graphs and have the property that they can be split into two well-known subgraphs, a tree and a cycle. The proposed algorithms take advantage of the above property to decrease the complexity of the algorithms. To the best of our knowledge, the proposed algorithms, which run in linear time in the number of vertices, are the fastest existing algorithms for the maximal strong stable set and minimal total dominating set problems.

Grafo Halin, Sistemas Distribuidos, Autoestabilización, Conjunto Independiente Fuerte, Conjunto Dominante Total Halin Graph, Distributed Systems, Self-stabilizing, Strong Stable Set, Total Dominating Set INGENIERÍA Y TECNOLOGÍA CIENCIAS TECNOLÓGICAS TECNOLOGÍA DE LOS ORDENADORES LENGUAJES ALGORÍTMICOS LENGUAJES ALGORÍTMICOS

Control de sistemas usando aprendizaje de máquina

Systems control using machine learning

Jesús Martín Miguel Martínez (2023, [Tesis de maestría])

El aprendizaje por refuerzo es un paradigma del aprendizaje de máquina con un amplio desarrollo y una creciente demanda en aplicaciones que involucran toma de decisiones y control. Es un paradigma que permite el diseño de controladores que no dependen directamente del modelo que describe la dinámica del sistema. Esto es importante ya que en aplicaciones reales es frecuente que no se disponga de dichos modelos de manera precisa. Esta tesis tiene como objetivo implementar un controlador óptimo en tiempo discreto libre de modelo. La metodología elegida se basa en algoritmos de aprendizaje por refuerzo, enfocados en sistemas con espacios de estado y acción continuos a través de modelos discretos. Se utiliza el concepto de función de valor (Q-función y función V ) y la ecuación de Bellman para resolver el problema del regulador cuadrático lineal para un sistema mecánico masa-resorte-amortiguador, en casos donde se tiene conocimiento parcial y desconocimiento total del modelo. Para ambos casos las funciones de valor son definidas explícitamente por la estructura de un aproximador paramétrico, donde el vector de pesos del aproximador es sintonizado a través de un proceso iterativo de estimación de parámetros. Cuando se tiene conocimiento parcial de la dinámica se usa el método de aprendizaje por diferencias temporales en un entrenamiento episódico, que utiliza el esquema de mínimos cuadrados con mínimos cuadrados recursivos en la sintonización del crítico y descenso del gradiente en la sintonización del actor, el mejor resultado para este esquema es usando el algoritmo de iteración de valor para la solución de la ecuación de Bellman, con un resultado significativo en términos de precisión en comparación a los valores óptimos (función DLQR). Cuando se tiene desconocimiento de la dinámica se usa el algoritmo Q-learning en entrenamiento continuo, con el esquema de mínimos cuadrados con mínimos cuadrados recursivos y el esquema de mínimos cuadrados con descenso del gradiente. Ambos esquemas usan el algoritmo de iteración de política para la solución de la ecuación de Bellman, y se obtienen resultados de aproximadamente 0.001 en la medición del error cuadrático medio. Se realiza una prueba de adaptabilidad considerando variaciones que puedan suceder en los parámetros de la planta, siendo el esquema de mínimos cuadrados con mínimos cuadrados recursivos el que tiene los mejores resultados, reduciendo significativamente ...

Reinforcement learning is a machine learning paradigm with extensive development and growing demand in decision-making and control applications. This technique allows the design of controllers that do not directly depend on the model describing the system dynamics. It is useful in real-world applications, where accurate models are often unavailable. The objective of this work is to implement a modelfree discrete-time optimal controller. Through discrete models, we implemented reinforcement learning algorithms focused on systems with continuous state and action spaces. The concepts of value-function, Q-function, V -function, and the Bellman equation are employed to solve the linear quadratic regulator problem for a mass-spring-damper system in a partially known and utterly unknown model. For both cases, the value functions are explicitly defined by a parametric approximator’s structure, where the weight vector is tuned through an iterative parameter estimation process. When partial knowledge of the dynamics is available, the temporal difference learning method is used under episodic training, utilizing the least squares with a recursive least squares scheme for tuning the critic and gradient descent for the actor´s tuning. The best result for this scheme is achieved using the value iteration algorithm for solving the Bellman equation, yielding significant improvements in approximating the optimal values (DLQR function). When the dynamics are entirely unknown, the Q-learning algorithm is employed in continuous training, employing the least squares with recursive least squares and the gradient descent schemes. Both schemes use the policy iteration algorithm to solve the Bellman equation, and the system’s response using the obtained values was compared to the one using the theoretical optimal values, yielding approximately zero mean squared error between them. An adaptability test is conducted considering variations that may occur in plant parameters, with the least squares with recursive least squares scheme yielding the best results, significantly reducing the number of iterations required for convergence to optimal values.

aprendizaje por refuerzo, control óptimo, control adaptativo, sistemas mecánicos, libre de modelo, dinámica totalmente desconocida, aproximación paramétrica, Q-learning, iteración de política reinforcement learning, optimal control, adaptive control, mechanical systems, modelfree, utterly unknown dynamics, parametric approximation, Q-learning, policy iteration INGENIERÍA Y TECNOLOGÍA CIENCIAS TECNOLÓGICAS TECNOLOGÍA DE LOS ORDENADORES INTELIGENCIA ARTIFICIAL INTELIGENCIA ARTIFICIAL