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Ontogenic changes in soybean radiation-use efficiency (RUE) have been attributed to variation in specific leaf nitrogen (SLN) based only on data collected during seed filling. We evaluated this hypothesis using data on leaf area, absorbed radiation (ARAD), aboveground dry matter (ADM), and plant nitrogen (N) concentration collected during the entire crop season from seven field experiments conducted in a stress-free environment. Each experiment included a full N treatment that received ample N fertilizer and a zero N treatment that relied on N fixation and soil N mineralization. We estimated RUE based on changes in ADM between sampling times and associated ARAD, accounting for changes in biomass composition. The RUE and SLN exhibited different seasonal patterns: a bell-shaped pattern with a peak around the beginning of seed filling, and a convex pattern followed by an abrupt decline during late seed filling, respectively. Changes in SLN explained the decline in RUE during seed filling but failed to predict changes in RUE in earlier stages and underestimated the maximum RUE observed during pod setting. Comparison between observed and simulated RUE using a process-based crop simulation model revealed similar discrepancies. The decoupling between RUE and SLN during early crop stages suggests that leaf N is above that needed to maximize crop growth but may play a role in storing N that can be used in later reproductive stages to meet the large seed N demand associated with high-yielding crops.

Oil palm production in Indonesia illustrates the intense pressure that exists worldwide to convert natural ecosystems to agricultural production. Oil palm production has increased because of expansion of cultivated area rather than due to average-yield increases. We used a data-rich modelling approach to investigate how intensification on existing plantations could help Indonesia meet palm oil demand while preserving fragile ecosystems. We found that average current yield represents 62% and 53% of the attainable yield in large and smallholder plantations, respectively. Narrowing yield gaps via improved agronomic management, together with a limited expansion that excludes fragile ecosystems, would save 2.6 million hectares of forests and peatlands and avoid 732 MtCO2e compared with following historical trends in yield and land use. Fine-tuning policy to promote intensification, along with investments in agricultural research and development, can help reconcile economic and environmental goals. Oil palm production in Indonesia has expanded by converting more natural ecosystems to agricultural ones. This study finds large yield gaps among large and smallholder farms there, suggesting improved management could increase production while sparing fragile ecosystems.

This article presents an approach for the participation of datacenters and supercomputing facilities in smart electricity markets. This is a relevant problem in modern smart grid systems to implement demand response strategies for a better use of resources to guarantee energy efficiency. The proposed approach includes a datacenter model based on empirical information to determine the power consumption of CPU-intensive and memory-intensive tasks. A negotiation approach between the datacenter and its tenants and a heuristic planning method for energy reduction optimization are proposed. The experimental evaluation is performed over realistic problem instances modeling the operation of the National Supercomputing Center in Uruguay. The obtained results indicate that the proposed approach is effective to provide appropriate demand response actions according to monetary incentives. Accurate results are reported for realistic problem instances and different types of tenants.

The Amazon basin includes 550 M ha covered with rainforests, with 60% of this area being in Brazil. Conversion of rainforest for soybean production raises concerns about the degree to which Brazil can reconcile production and environmental goals. Here we investigated the degree to which intensification could help Brazil produce more soybean without further encroachment of the Amazon Forest. Our analysis shows that continuation of current trends in soybean yield and area would lead to conversion of additional 5.7 M ha of forests and savannas during the next 15 years, with an associated 2550 Mt of CO2eq released into the atmosphere. In contrast, acceleration of yield improvement, coupled with expansion of soybean area only in areas currently used for livestock production, would allow Brazil to achieve similar economic benefits without deforestation and with substantially lower global climate warming.

Ontogenic changes in soybean radiation-use efficiency (RUE) have been attributed to variation in specific leaf nitrogen (SLN) based only on data collected during seed filling. We evaluated this hypothesis using data on leaf area, absorbed photosynthetically active radiation (APAR), aboveground dry matter (ADM), and plant nitrogen (N) concentration collected during the entire crop season from seven field experiments conducted in a stress-free environment. Each experiment included a full N treatment that received ample N fertilizer and a zero N treatment that relied on N fixation and soil N mineralization. We estimated RUE based on changes in ADM between sampling times and associated APAR, accounting for changes in biomass composition. The SLN and RUE exhibited different seasonal patterns: a bell-shaped pattern with a peak around the beginning of seed filling, and a convex pattern followed by an abrupt decline during late seed filling, respectively. The level of N supply influenced SLN more than RUE via changes in leaf N concentration, with small changes in specific leaf weight. Changes in SLN explained the decline in RUE during seed filling but failed to predict changes in RUE in earlier stages. A simple approach based on phenological stages may give more realistic estimates of RUE before seed filling, improving crop growth and yield prediction via crop models and remote sensing.HighlightChanges in radiation-use efficiency during soybean vegetative and early reproductive stages are not related to specific leaf nitrogen.

Significance After accounting for the effect of climate and improvements in agronomic management, we found the contribution of genetic technologies to increasing maize yield potential in favorable environments was substantially smaller than reported in previous studies. If genetic progress in yield potential is slowing in other environments and for other crops as well, future production gains will increasingly rely on yield gains from improved agronomic practices and/or increasing crop intensity where possible., Quantitative understanding of factors driving yield increases of major food crops is essential for effective prioritization of research and development. Yet previous estimates had limitations in distinguishing among contributing factors such as changing climate and new agronomic and genetic technologies. Here, we distinguished the separate contribution of these factors to yield advance using an extensive database collected from the largest irrigated maize-production domain in the world located in Nebraska (United States) during the 2005-to-2018 period. We found that 48% of the yield gain was associated with a decadal climate trend, 39% with agronomic improvements, and, by difference, only 13% with improvement in genetic yield potential. The fact that these findings were so different from most previous studies, which gave much-greater weight to genetic yield potential improvement, gives urgency to the need to reevaluate contributions to yield advances for all major food crops to help guide future investments in research and development to achieve sustainable global food security. If genetic progress in yield potential is also slowing in other environments and crops, future crop-yield gains will increasingly rely on improved agronomic practices.

Recent reviews about soybean nitrogen (N) requirement have speculated about a possible N limitation in high-yield environments (>4.5 Mg ha−1). However, these studies did not provide definitive experimental data to test that hypothesis and results from the literature are conflicting. To fill this knowledge gap, we evaluated N limitation across 13 high-yield soybean environments in Argentina and USA. Each experiment included a ‘zero-N’ treatment, which forced the crop to rely on biological N2 fixation and indigenous soil N, and a ‘full-N’ treatment, which provided an ample fertilizer N supply during the entire crop cycle based on site-specific yield potential. Accumulated N in aboveground dry matter (ADM) measured in a N-omission maize plot grown adjacent to the soybean experiments was used to determine indigenous soil N supply. Soybean seed yield, protein and oil concentration, ADM, harvest index (HI), accumulated N in ADM, N harvest index (NHI), and seed N were measured in both treatments at physiological maturity. A simple conceptual framework relating ADM with accumulated N was used to assess treatment differences in ADM, accumulated N, and N-use efficiency (NUE). To account for treatment differences in seed biomass composition, mass-based ADM was expressed in glucose equivalents (ADMe). Seed yield ranged from 4.6 to 6.7 Mg ha−1 (full-N) and 4 to 5.8 Mg ha−1 (zero-N), with the full-N treatment averaging 12% (0.6 Mg ha−1) and 3% (9 g kg−1) higher seed yield and protein concentration, respectively. The full-N treatment exhibited 18% (70 kg N ha−1) and 14% (1.6 Mg ha−1) greater accumulated N and ADM, respectively, compared with the zero N treatment, without changes in HI and NHI, but slightly lower NUE (29 versus 30 kg ADM kg−1 N in full and zero-N, respectively). However, NUE differences between treatments became indistinguishable when ADM was expressed as ADMe (45 kg glucose kg−1 N). The (full-N minus zero-N) seed yield difference and the indigenous soil N supply were negatively associated. This research documented (i) the existence of N limitation in high-yield soybean, (ii) that seed yield and protein concentration increases were physiologically associated with changes in accumulated N (but not in NUE and/or NHI), and (iii) that the degree of N limitation is modulated by indigenous soil N supply. Findings from this study can serve as a basis to identify environments with the largest N limitation and thus guide N management in soybean.

A few decades ago, Y. Kuramoto introduced a mathematical model of weakly coupled oscillators that gave a formal framework to some of the works of A.T. Winfree on biological clocks [Kuramoto (1975), Kuramoto (1984), Winfree (1980)]. The model proposes the idea that several oscillators can interact in a way such that the individual oscillation properties change in order to achieve a global behavior for the interconnected system. The Kuramoto model serves as a good representation of many systems in several contexts: biology, engineering, physics, mechanics, etc. [Ermentrout (1985), York (1993), Strogatz (1994), Dussopt et al. (1999), Strogatz (2000), Jadbabaie et a. (2003), Rogge et al. (2004), Marshall et al. (2004), Moshtagh et al. (2005)]. Recently, many works on the control community have focused on the analysis of the Kuramoto model, specially the one with sinusoidal coupling. The consensus or collective synchronization of the individuals is particularly important in many applications representing coordination, cooperation, emerging behavior, etc. Local stability properties of the consensus have been initially explored in [Jadbabaie et al. (2004)]. It must be noted that little attention has been devoted to the influence of the underlying interconnection graph on the stability properties of the system. The reason could be the fact that the local stability does not depend on the interconnection [van Hemmen et al. (1993)]. Global or almost global dynamical properties were studied in [Monzon et al. (2005), Monzon (2006), Monzon et al. (2006)]. In these works, the relevance of the interconnection graph of the system was hinted. In the present chapter, we go deeper on the analysis of the relationships between the dynamical properties of the system and the algebraic properties of the interconnection graph, exploiting the strong algebraic structure that every graph has. We step forward into a classification of the interconnection graphs that ensure almost global attraction of the set of synchronized states. In Section 2 we present the Kuramoto model for sinusoidally coupled oscillators, its general properties and the notion of almost global synchronization; in Section 3 we review some basic facts on algebraic graph theory; the symmetric Kuramoto model and the block analysis are presented in Sections 4 and 5; Section 6 gives some examples and applications of the main results; Section 7 presents the problem of classification of almost global synchronizing topologies.

We address the problem of scheduling water resources in a power system via approximate dynamic programming. To this goal, we model a finite horizon economic dispatch problem with convex stage cost and affine dynamics, and consider a quadratic approximation of the value functions. Evaluating the achieved policy entails solving a quadratic program at each time step, while value function fitting can be cast as a semidefinite program. We test our proposed algorithm on a simplified version of the Uruguayan power system, achieving a four percent cost reduction with respect to the myopic policy. Agencia Nacional de Investigación e Innovación

Apoptosis has been extensively characterized by both experimental approaches and model simulations. However, it is still not fully understood how the regulation occurs, especially in the intrinsic pathway, which can be activated by a great variety of signals. In addition, the conditions in which a point of no return could be reached remain elusive. In this work, we use differential equations models to approach these issues. Our starting point was the model for caspase activation of Legewie et al. (Legewie S, et al., PLoS Computational Biology 2006, 2(9): e120), which exhibits irreversible bistability. We added an activation module to this model, with the main events related to mitochondrial outer membrane permeabilization, which includes cytochrome C release by the mitochondria and its effects on caspase activation and respiratory chain disruption. This “Extended Legewie Model” (ELM) uses BAK as the apoptotic stimulus and active caspase 3 as a measure of apoptosis activation. Unexpectedly, in the extended model, BAK cannot trigger apoptosis activation using physiologically sound initial values of the variables, due to limitations in apoptosome concentration increase. Therefore, the next step was to find a regulatory mechanism, allowing apoptosis activation in the ELM, starting from physiological initial concentrations. For this aim, we performed a sensitivity analysis on the 61 parameters of the system, finding that those producing the most relevant changes in the qualitative behaviour were the rates of synthesis of caspase 3, caspase 9 and XIAP. Based on these results, the transcription factor E2F was included in the ELM because it directly regulates the rate of synthesis of caspase 3 and 9. Depending on the concentration of E2F, the ELM shows different qualitative behaviours. On one hand, for low E2F apoptosis is impossible and for high E2F apoptosis is inevitable. Therefore, if E2F is sufficiently increased, the point of no return is crossed. On the other hand, for intermediate values of E2F there is a bistable region where the fate of the system also depends on the concentration of BAK and other signalling species.

In the nervous system, neurons are organized in networks by way of connections constituted by chemical and electrical synapses. We use biological and mathematical models to study electrical synaptic communication and its determinants. In particular, we show how non-synaptic components of a neural circuit generate a band-pass filter behavior and shape action potential transmission between neurons of the mesencephalic trigeminal (MesV) nucleus of rodents. The dynamic modulation of these properties could be used as an inspiration for artificial neural networks with electrical synapses.

In this article, we studied a negotiation approach for the participation of datacenters and super-computing facilities in smart electricity markets providing ancillary services, an important problem in modern smart grid systems. Different demand response strategy were studied for colocation datacenters to commit power reductions during a sustained period, according to offers proposed to tenants. The negotiation algorithm and a heuristic planning method for energy reduction optimization were experimentally validated over realistic problem instances that model different problem dimensions and flexibility of the datacenter clients. The obtained results indicate that the proposed approach is effective to provide appropriate frequency reserves control according to monetary incentives.

In this article, we provide a proof of concept realization of a demand response scheme modelling an EV-aggregator offering smart charging 1 coordination services to several Electric Vehicles (EV). The aggregator model promotes a distributed smart charge coordination of the EVs optimizing energy costs and energy charging profiles. This proposal considers EV’s battery health constraints and mobility constraints and promotes spars day-ahead charging profiles. We use a distributed scheme with the main objective of preserving the integrity of the private information of the active agents and scalability issue. The sparsity solution is identified using the alternating direction method of multipliers. The model proposed alternates between promoting sparsity of the charging profile accomplishing EV’s constraints and minimizing energy cost. We assume a decentralized communication between the participants of the optimization problem, exchanging adequate signal prices and power profiles keeping the integrity of the private information of each active agent.

The advancement of technology makes remote management and monitoring of environmental systems increasingly close, accessible and necessary. For several applications, it is important to have an equipment to gather data and information in a friendly, remotely, and easy-to-access platform. The system that was developed consists of modular telemetry equipment and a server. Its fundamental characteristics are flexible architecture, energy autonomy and remote communication. It is designed and constructed by independent modules, which provide versatility allowing the reuse of the hardware on multiple applications. It enables to rapidly develop a prototype to test an idea. The Arduino platform was used to develop the modules because it is an open software and hardware platform, its philosophy is aligned with the purpose of this project. The server, developed using open software, has databases for storage and a web service for data display and control. The versatility of the equipment was tested in two particular applications: monitoring of beehives sound for environmental pollution control, and determination of the amount of phosphorus and nitrogen present in the water of river courses.

In this work, a social welfare maximization problem is solved to determine the optimal scheduling of end-user controllable loads, smart appliances, and energy storage. The framework considers multiple retail energy suppliers as well as the AC power flow constraints of the distribution system. The demand side management program is focus on residential and commercial end-users. We have formulated a day-ahead residential bidding/buyback scheme modeled as an optimal power flow problem. This demand side program schedules end-user’s controllable loads or smart appliances and takes advantage of the flexibility of an energy storage system. The demand side management scheme minimizes retail company’s operating costs in the wholesale market, and it also considers distribution network constraints, assuring the appropriate quality of service. We have used a dual decomposition method to decouple some constraints while maximizing social welfare. We have also introduced a demand response call event with the main objective to take into consideration the system operational constraints. Through the coordination via local marginal prices, we have obtained a decentralized and distributed bidding/buyback scheme proposing a demand side management program that preserves the integrity of the private information of the different participants.

Precision agriculture has under delivered partially because it has been based on technologies focused on increasing the resolution of spatial variation in soil and yield and more recently automation, with less effort in incorporating the physiological principles of crop responses to environmental variation. Here we show how a whole-farm precision agriculture approach accounting for the physiological processes underlying the relationship between environment and crop development, growth and yield (“zone management”), bridge yield gaps, increased farmer profit and reduced risk, on San Lorenzo, a 5000 ha dryland farm in the southern Pampas. The farm grows wheat and barley in winter, and soybean, maize, and sunflower in summer; winter grain cereal/double-cropped soybean is a main activity. Four management zones were defined: i) Zone 1, shallow soils (< 0.8 m) with low frost risk and deep water table (> 3 m below surface); ii) Zone 2, intermediate soil depth (0.8 to 1.8 m) with low frost risk and deep water table; iii) Zone 3, deep soils (> 1.8 m) with low frost risk and deep water table; and iv) Zone 4, deep soils (> 1.8 m) with high frost risk and water table < 3 m from surface. Crop choice and practices were tailored to each zone based on ecophysiological principles including the relative sensitivity of crop growth and yield to soil depth, frost and water supply during the species-specific critical window for yield determination; for example, maize is the most sensitive crop to stress during its critical window, therefore it was excluded from Zone 1 and 2, with a substantial reduction of risk and improvement of farm output (amount of grains that can be produced in a hectare) and profit. In comparison with neighboring farms, San Lorenzo had a 54% higher farm output, and 46% higher gross margin (or 112 US$ ha−1 year−1); this was driven by a higher net income (244 US$ ha−1) despite increased total costs (132 US$ ha−1). Fil: Monzon, Juan Pablo. Universidad Nacional de Mar del Plata; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata; Argentina Fil: Calviño, P. A.. Asociación Argentina de Consorcios Regionales de Experimentación Agrícola; Argentina Fil: Sadras, Victor Oscar. Universidad Nacional de Mar del Plata; Argentina. South Australian Research And Development Institute; Australia Fil: Zubiaurre, J. B.. San Lorenzo Farmer; Argentina Fil: Andrade, Fernando Héctor. Unidad Integrada Balcarce; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata; Argentina. Universidad Nacional de Mar del Plata; Argentina

As soybean yield continues to increase, it seems critical to know if there is a yield level at which potential contribution of indigenous nitrogen (N) sources (N fixation and soil mineralization) becomes insufficient to meet crop N requirements for high yields, while still maintaining or increasing protein and oil concentration. We have hypothesized that, in absence of other limiting factors, degree of N limitation increases with increasing yield potential (Yp) of the production environment. To test this hypothesis, we developed a novel protocol to ensure an ample N supply during the entire crop season (full-N treatment). That protocol was applied to field-grown irrigated soybean in Balcarce (Argentina) and Nebraska (USA), where measured full-N seed yields were ±15% of their simulated Yp in 92% of the cases. The combination of locations, years, sowing dates, and N treatments resulted in a wide range of seed yields, from 2.5 to 6.5 Mg ha−1. Overall, full-N seed yield averaged 11% higher than seed yield without N addition (zero-N). However, magnitude of yield difference between full-N and zero-N depended upon Yp, ranging from no detectable yield difference in low-Yp (ca. 2.5 Mg ha−1) to up to 900 kg ha−1 in high-Yp environments (ca. 6 Mg ha−1). Seed yield differences were associated with higher aboveground dry matter, seed number, and seed weight in the full-N versus zero-N treatments. Seed protein (but not oil) concentration was higher in the full-N treatment, and both protein and oil yields were higher in the full-N versus zero-N treatments. Findings from this study indicate that (i) N limits soybean seed yield (as well as protein yield, and oil yield) in environments with high Yp, where indigenous N sources seem insufficient to fully satisfy crop N requirements, and (ii) yield response to N fertilizer can occur above a 2.5 Mg ha−1 Yp threshold and has an upper limit of 250 kg seed per Mg increase in Yp. Fil: Cafaro la Menza, Nicolás. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. University of Nebraska; Estados Unidos Fil: Monzon, Juan Pablo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires Sur. Estación Experimental Agropecuaria Balcarce; Argentina Fil: Specht, James E.. University of Nebraska; Estados Unidos Fil: Grassini, Patricio. University of Nebraska; Estados Unidos

The challenge to increase agricultural production with a minimum environmental impact requires to reach the maximum efficiency in the capture and use of resources such as photosynthetically active radiation (PAR), water, and nitrogen (N). Such requisites are encompassed in the ecological intensification (EI) concept. The aims of this work were to evaluate at a crop sequence level: i) crops yields, ii) water and radiation productivity and its components, i.e. resource capture and resource use efficiency, and iii) partial factor productivity of applied N (PFPN), partial nutrient balance for N (PNB), N uptake and N utilization efficiency of a two-year, three-crop sequence (wheat [Triticum aestivum L.]/soybean [Glycine max (L.) Merr.] double crop – maize [Zea mays L.]) carried-out under EI principles in comparison with the same crop sequence under current farmer practices (FP) in two contrasting locations of the Argentinean Pampas, i.e. Paraná (-31°50′; -60°31′) at the northern Pampas and Balcarce (-37°45′ -58°18′) at the southern Pampas. Experiments were carried-out during four consecutive years, covering two complete cycles of the crop sequence. For the accumulated grain production of the crop sequence, EI management outyielded FP from 13 to 42%, depending on environmental conditions. Maize yield accounted for most of the variation (41–64%) of the accumulated grain yield of crop sequence, whether in EI as in FP. Average grain yield differences between EI and FP treatments were 274 g m −2 for maize, 69 g m −2 for wheat and -2 g m −2 for soybean. Water and radiation productivities of the sequence were higher in EI than in FP (26% for water and 17% for radiation; P < 0.0001), mainly because of increases in resource use efficiencies. EI reduced partial factor productivity of applied N, but improved partial nutrient balance for N as compared with FP. These reductions in partial factor productivity of applied N were less than proportional than the increases in N rate. Moreover, in spite of the higher N rate in EI respect to FP, N utilization efficiency (N ut E), i.e. grain per unit N uptake, was higher across all situations in EI. Our results showed that the challenge to obtain high grain yields by increasing N rate in a medium-input system could be achieved even with an increase in N ut E. Grain yields improvements, and increases in radiation and water productivity were reached by applying a set of agronomic practices that included improved genetics, crop and fertilizer N management englobed under EI concept. Fil: Caviglia, Octavio Pedro. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires; Argentina. Universidad Nacional de Entre Ríos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Rizzalli, Roberto Héctor. Universidad Nacional de Mar del Plata; Argentina Fil: Monzon, Juan Pablo. Universidad Nacional de Mar del Plata; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Garcia, Fernando Oscar. Universidad Nacional de Mar del Plata; Argentina. International Plant Nutrition Institute Latinoamérica; Argentina Fil: Melchiori, Ricardo José Miguel. Instituto Nacional de Tecnología Agropecuaria; Argentina Fil: Martinez, J.J.. Instituto Nacional de Tecnología Agropecuaria; Argentina Fil: Cerrudo, Anibal Alejandro. Instituto Nacional de Tecnología Agropecuaria; Argentina. Universidad Nacional de Mar del Plata; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Irigoyen, Andrea Inés. Universidad Nacional de Mar del Plata; Argentina Fil: Barbieri, Pablo Andres. Universidad Nacional de Mar del Plata; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Van Opstal, Natalia. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires; Argentina Fil: Andrade, Fernando Héctor. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Mar del Plata; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires; Argentina

This article describes a proposal for the participation of supercomputing platforms and datacenters in the electric market, by implementing demand response techniques and ancillary services. Supercomputing and datacenters are appropriate candidates to adjust their power consumption in order to help the electric network to fulfill specific goals, either by consuming available surplus of energy to execute complex tasks, or by deferring activities when energy is more expensive or generation is lower than normal. Their thermal/cooling infrastructures demand about half of the energy consumption and provide a large inertia that can be carefully used to interact with the power grid. These strategies allow implementing a smart management of the electric grid, achieving a rational utilization of renewable energy sources, and the correct utilization of information technologies to improve decision-making processes. A specific case study is presented: The National Supercomputing Center in Uruguay (Cluster-UY), for which strategies for optimal planning of the execution of tasks and energy utilization are proposed, taking into account the energy consumption, the Quality of Service provided to the users, and the thermal/cooling demands of the infrastructure. In addition, the business opportunities and business models for supercomputing and datacenters in the electric market are revisited. Results suggest the effectiveness of the proposed strategies to implement demand response techniques and provide ancillary services under the smart grid paradigm.

Seed number (SN) is positively associated with aboveground dry matter (ADM) accumulation in most crop species. In soybean, there are discrepancies among studies relative to the start and end of the critical period for seed number determination. The objective of this study was to more precisely identify those two stages. To do so, we followed two approaches: (i) analyses of experimental data where differences in SN occurred as a result of variation in crop growth due to weather and management practices and (ii) review of published experiments where soybean was subjected to artificial stresses during specific crop phases. Following the first approach, we analyzed the relationships between SN versus ADM accumulation and its components, crop growth rate (CGR) and duration, for different reproductive phases using data from experiments that portrayed a wide range of environments and management practices. In the second approach, we compared SN values in stressed versus non-stressed treatments. Accumulated ADM during the R3 to R6 phase explained ca. 70 % of the variation in SN across experiments. The CGR during R3-R6 was also a good predictor of SN, but it had lower explanatory power compared with accumulated ADM, because CGR did not account for changes in duration of critical period across experiments. Review of published data, wherein soybean crops were subjected to artificial stresses during different reproductive phases, confirmed that the R3-R6 phase is a critical phase for SN determination in soybean. Key findings of this study were: (i) critical period for SN determination in soybean occurs during the R3-R6 phase and (ii) accumulated ADM during the critical period is a better predictor of SN compared with CGR because it accounts for differences in the duration of the critical period as a result of weather and management.

Favorable weather conditions prevailing on most South American Pampas allows to grow more than one crop per year. Indeed, increasing crop intensity per unit area has been highlighted as an opportunity to increase crop production in a high food demanding world scenario. Previous studies have analyzed cropping-system yield gap by aggregating crop yields either as total amount of grain or as unit of energy. However, few cropping-system yield gap analysis have made a distinction between single (i.e., soybean sown as a single crop per year) and double-cropped soybean (i.e., soybean sown immediately after harvest of a winter cereal crop), and none of them at a country level. This article focuses on the estimation of cropping system-imposed yield gap (CSIYg), which is defined as the difference of seed yield between single soybean and double-cropped soybean. The aims of the present study were: (i) to analyze yield potential (Yp), water-limited (Yw) and yield gap (Yg) spatial and interannual variability; (ii) to investigate the concept of CSIYg for soybean using cropping systems in Uruguay as a proof of concept; and (iii) to assess differences on yield variability between single and double-cropped soybean. Yp and Yw were estimated for single and double-cropped soybean in specific locations within the major soybean crop producing areas using CROPGROW model coupled with long-term good quality weather data, soil types and dominant management practices. Estimations were scaled up following the protocols of the Global Yield Gap Atlas project. We applied a boundary function analysis to assess the differences on Yw variability between single and double-cropped soybean. At country level Yp was estimated on 6.6 and 5.7 Mg ha−1 for single and double-cropped soybean, respectively. However, we found lower differences on Yw between single and double-cropped soybean (3.6 and 3.4 Mg ha−1, respectively). We estimated CSIYg due to combined effect of weather condition and water regime on 3.2 Mg ha−1. The CSIYg representing the combined effect of weather condition, water regime and management was estimated on 1.6 Mg ha−1. Double-cropped and single soybean showed the same Yw response to precipitations and a similar Yw variability (t-test P = 0.55). Our results highlight double-cropped soybean cropping systems as an alternative for increasing grain production in this main agricultural region of the world.

The massive use of pesticides and herbicides to increment the agriculture production can produce severe environmental impacts. This implies the need of new methods to monitor and control the use of chemical agents. An alternative to traditional sampling methods is the use of insects to act as a biological distributed sensor in order to monitor the presence of pesticides in the neighbourhood. Specifically, several authors have proposed the use of the beehive as a distributed sensor. To evaluate critical changes in the beehive behaviour, the sound patterns are analysed. In this work the guidelines used to develop a remote monitoring system in order to detect abnormal changes in the sound patterns in hives are presented. The evolution of the frequency spectrum sampled in four temporal windows is proposed to monitor the beehive health. Experiments to determinate the frequency band and the frequency resolution are presented for the case of Apis mellifera . Using these guidelines a complete monitor system was developed and constructed.

Favorable climate and soils for rainfed crop production, together with a relatively low population density, results in 70–90% of Argentina grain production being exported. No assessment to date has tried to estimate the potential for extra grain production for soybean, wheat and maize, which account for 78% of total harvested area, by yield gap closure on existing cropland area and its impact at a global scale. The objectives of this paper are (i) to estimate how much additional grain could be produced without expanding crop area by closing yield gaps in Argentina, (ii) to investigate how this production and yield gaps varies across regions and years, and (iii) to analyze how these inter-annual variations are related to El Niño—Southern Oscillation phenomenon (ENSO). Production increase on existing crop area was assessed for soybean, wheat and maize by quantifying the yield gap (Yg), that is, the difference between water-limited yield potential (Yw) and actual yield (Ya). A bottom-up approach was followed to estimate Yw and Yg, in which these parameters were first estimated for specific locations in major crop producing areas and subsequently up-scaled to country level based on spatial distribution of crop area and climate zones. Locally-calibrated crop simulation models were used to estimate Yw at each selected location based on long-term weather data and dominant soil types and management practices. For the analyzed period, the national level Yg represented 41% of Yw for both wheat and maize and 32% of the Yw for soybean. If farmers had closed Yg from these levels to 20% of Yw, Argentina could have increased soybean, wheat and maize production by a respective 7.4, 5.2, and 9.2 Mt, without expanding cropland area. This additional production would have represented an increase of 9%, 4%, and 9% of soybean, wheat, and maize global exports. This potential grain surplus was, however, highly variable because of the ENSO phenomenon: attainable soybean production was 12 Mt higher in favorable “El Niño” years compared with unfavorable “La Niña” years. Interestingly, Yg tended to be higher in wet years, suggesting that farmers do not take full advantage of years with favorable conditions for rainfed crop production. Regional variation in Yg was found in Argentina highlighting the usefulness of this work as a framework to target research and, ultimately, reduce gaps in areas where current yields are well below their potential. EEA Balcarce Fil: Aramburu Merlos, Fernando. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce. Unidad Integrada. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias; Argentina Fil: Monzon, Juan Pablo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias; Argentina Fil: Mercau, Jorge Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Luis. Instituto de Matemática Aplicada de San Luis "Prof. Ezio Marchi". Universidad Nacional de San Luis. Facultad de Ciencias Físico, Matemáticas y Naturales. Instituto de Matemática Aplicada de San Luis "Prof. Ezio Marchi"; Argentina. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria San Luis; Argentina Fil: Taboada, Miguel Angel. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Suelos; Argentina Fil: Andrade, Fernando Hector. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce. Unidad Integrada. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias; Argentina Fil: Hall, Antonio Juan. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Agronomía; Argentina Fil: Jobbagy Gampel, Esteban Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Luis. Instituto de Matemática Aplicada de San Luis "Prof. Ezio Marchi". Universidad Nacional de San Luis. Facultad de Ciencias Físico, Matemáticas y Naturales. Instituto de Matemática Aplicada de San Luis "Prof. Ezio Marchi"; Argentina Fil: Cassman, Kenneth G. Universidad de Nebraska - Lincoln. Department of Agronomy and Horticulture; Estados Unidos Fil: Grassini, Patricio. Universidad de Nebraska - Lincoln. Department of Agronomy and Horticulture; Estados Unidos

After canopy closure and in the absence of limitations by water or nutrient availability, crop growth rate (CGR) of maize (Zea mays L.) is ultimately constrained by the daily incident radiation and temperature of the environment. Sustaining maximal canopy photosynthetic capacity after-flowering is, then, a necessary but not a sufficient condition to increase maize dry-matter production. The aim of the present study was to determine the extent of the photo-thermal environment limitation to CGR during the post-flowering period in current maize crops. Dynamic of CGR was studied in two well-irrigated and nourished maize field experiments (Exp. 1 and Exp. 2 for 2010−11 and 2011−12 cropping seasons, respectively) on conventional crops (i.e. full-season hybrid planted early in the season) at Balcarce, Argentina (37° 45’ S, 58° 18’ W; 130 m a.s.l.). Two independent methods were performed to benchmark the CGR of these conventional crops during the post-flowering period: i) empirical CGR values obtained under the same weather conditions from younger maize crops, and ii) theoretically estimated potential CGR, obtained as a function of daily incident radiation and potential radiation use-efficiency (RUE). Conventional crops reached the maximal CGR near flowering in mid-January, being 51.2 g m−2 d−1 and 58.8 g m−2 d−1 in Exp. 1 and Exp. 2, respectively. Afterwards, CGR decreased progressively towards crops maturity late in March. Estimates, from either the empirical or the theoretical method, indicated that although attainable-CGR decreases progressively towards the end of the cropping season, it sustains higher values than those achieved by conventional crops after flowering. Differences in attainable vs. actual-CGR was almost exclusively attributable to RUE, which, in turn, could not be explained solely by the post-flowering foliar nitrogen withdrawal. Differences between actual (1987 g m−2 in Exp. 1 and 1614 g m−2 in Exp. 2) and potential post-flowering dry-matter production defined gaps that were in the range 18.2%–47.8%. From these results, it can be concluded that the photo-thermal environment is not, at least so far, the limiting factor to the post-flowering maize growth. Further research is needed, however, to analyze the viability of increasing potential yield of maize through the closure of these estimated gaps.

We study the differentiability properties of the topological equivalence between a uniformly asymptotically stable linear nonautonomous system and a perturbed system with suitable nonlinearities. For this purpose, we construct a homeomorphism inspired in the Palmer's one restricted to the positive half line, studying additional continuity properties and providing sufficient conditions ensuring its Cr–smoothness.

This paper proposes an online method to integrate the trajectories of differential-algebraic equations in the context of networked power systems. We predict these trajectories from a real-time data stream generated by phasor measurement units, combining newly incoming data with past information. For this purpose, we propose a stochastic optimization technique that incorporates new data as they become available, trading-off measurement errors for modeling uncertainty. The method is tested on a benchmark system of 39 buses and 10 generators being able to anticipate the system recovery from a three-phase-to-ground short-circuit.

Increasing the production of overproducing strains represents a great challenge. Here, we develop a modular modulation method to determine the key steps for genetic manipulation to increase metabolite production. The method consists of three steps: (i) modularization of the metabolic network into two modules connected by linking metabolites, (ii) change in the activity of the modules using auxiliary rates producing or consuming the linking metabolites in appropriate proportions and (iii) determination of the key modules and steps to increase production. The mathematical formulation of the method in matrix form shows that it may be applied to metabolic networks of any structure and size, with reactions showing any kind of rate laws. The results are valid for any type of conservation relationships in the metabolite concentrations or interactions between modules. The activity of the module may, in principle, be changed by any large factor. The method may be applied recursively or combined with other methods devised to perform fine searches in smaller regions. In practice, it is implemented by integrating to the producer strain heterologous reactions or synthetic pathways producing or consuming the linking metabolites. The new procedure may contribute to develop metabolic engineering into a more systematic practice. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 31:656–667, 2015

This paper studies the stability and control of networked systems from the perspective of the new field of signal processing over graphs. Specifically, we reformulate the linear quadratic optimal controller as a graph filter by demonstrating that it becomes separable when applying the graph Fourier transform. Accordingly, the graph-frequency components of the input signal are processed independently by a set of parallel controllers which are given in closed form by solving their Riccati equations. Additionally, we prove that the joint graph-and-temporal-frequency transfer function of the controlled system satisfies the condition for stability, that is, that the complement of its region of convergence fits inside a cylinder of unit radius. The results are universal in the sense that they hold true for any graph-frequency and do not depend on the specific eigenvalues of the network shift operator. Numerical tests in an directed circulant graph show that the unstable poles corresponding to graph-frequencies larger than one are shrunk towards the origin.

The acoustic wave propagation in solid structures has a specific impulse response pattern, that allows to identify the impact location over a structure. By using piezoelectric transducers, the vibration on the surface is translated into a voltage signal which is later analyzed to determine the position of the impact. This technique has the potential to transform any solid object into an interactive interface. However further studies are yet to be done, in particular, position detection algorithms have to be developed, analysis of the signal and the relation with the position, the space resolution of this technique, and more. In this letter, the development of a lab instrument for the study of the mentioned technique is described and the results of several experiments are shown. Furthermore, in order to show how the technique could be used, an application of it is presented.

This paper is concerned with the benefits of a price responsive scheme as a demand response program focus on residential end-users. We consider several retail companies operating in the retail market and the Distribution System Operator optimizing the physical resources of the distribution networks. The price responsive scheme is modeled as an OPF problem. We use a decomposition model to formulate the problem as a dynamic program that maximizes social welfare. A dual decomposition method is used to decouple the original problem, preserving the integrity of the private information of each participant and capturing its preferences and comfort policies.

The exploration problem is a fundamental subject in autonomous mobile robotics that deals with achieving the complete coverage of a previously unknown environment. There are several scenarios where completing exploration of a zone is a main part of the mission. Due to the efficiency and robustness brought by multi-robot systems, exploration is usually done cooperatively. Wireless communication plays an important role in collaborative multi-robot strategies. Unfortunately, the assumption of stable communication and end-to-end connectivity may be easily compromised in real scenarios. In this paper, a novel auto-adaptive multi-objective strategy is followed to support the selection of tasks regarding both exploration performance and connectivity level. Compared with others, the proposed approach shows effectiveness and flexibility to tackle the multi-robot exploration problem, being capable of decreasing the last of disconnection periods without noticeable degradation of the completion exploration time.

Delaying maize (Zea mays L.) sowing date can diminish grain yields through reductions in the number, size and activity of growing grains (sink strength) and/or reductions in the assimilate supply (source capacity) to grains during the grain filling period. Whether the source capacity or the sink strength is the limiting factor for grain yield in late sown maize still remains unclear. Understanding source-sink relationships is relevant to optimize crop management practices, to identify critical processes for crop modelling and to develop breeding strategies. The objective of this work was to assess the effect of delays in maize sowing date on grain yield components and on the source-sink relationship during the grain filling period. Three well irrigated and fertilized maize field experiments were conducted at Balcarce, Argentina (37° 45′ S, 58° 18′ W; 130 m a.s.l.) during 2009–10; 2010–11 and 2011–12 cropping seasons. Sowing dates ranged from October to January covering a broad range of the seasonal photo-thermal variation. Grain yield was affected by sowing date and varied from 1680 g m−2 (early sowings) to 203 g m−2 (late sowings). Grain number per unit area was reduced proportionally less than weight per grain as sowing date was delayed. Variations in grain yield were related to the harvest index, and were closely associated with dry matter accumulation during the post-silking period. The variation of source capacity was higher than that of sink strength during the grain filling period and the source/sink ratio decreased from early to late sowing dates. Results indicate that crop growth during the grain filling period was limited by the sink strength in early sowing dates and by the photosynthetic source capacity in the late ones. Fil: Bonelli, Lucas Emmanuel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias; Argentina Fil: Monzon, Juan Pablo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Cerrudo, Anibal Alejandro. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias; Argentina. Instituto Nacional de Tecnología Agropecuaria; Argentina Fil: Rizzalli, Roberto H.. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias; Argentina Fil: Andrade, Fernando Héctor. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias; Argentina. Instituto Nacional de Tecnología Agropecuaria; Argentina

In this brief article, we prove the dominant role of the 1-twisted equilibrium point on the dynamical properties of the Kuramoto model with an interconnection topology given by a Harary graph. This is a very regular topology and helps to understand the complexity of the dynamic, associated to a very simple mathematical model.

This paper is concerned with the promising benefits of the incorporation of demand response (DR) scheme in residential end-users, but considering the AC distribution network's constraints and several retail companies or Local Service Entities (LSEs) participating in the retail market. This residential DR is modeled as an OPF problem run by the Operator of the distribution network, with the aggregated information collected by each retail company from their clients. We use a simple model and formulate the problem as a dynamic program that maximizes social welfare. The primal-dual method used to decouple some constraints and optimize the system, preserves the integrity of the private information of each participant and captures its preferences and constraints.

Postprint Objeto de conferencia In the present document, the authors introduce the Cooperative Exploration problem as well as the most relevant approaches in order to show the most common drawbacks and opportunities to improve the state of art solutions. Subsequently, a preliminary version of a multi-robot exploration proposal is described. The first results obtained in simulated scenarios support the underlying ideas are feasible and promising. They show that is possible to cope with real communication constraints (always present in practice), being more fault tolerant and still having good performance regarding the total exploration time. Next steps to fully implement a more reliable and robust system are discussed.

Kuramoto model of coupled oscillators represents situations where several individual agents interact and reach a collective behavior. The interaction is naturally described by a interconnection graph. Frequently, the desired performance is the synchronization of all the agents. Almost global synchronization means that the desire objective is reached for every initial conditions, with the possible exception of a zero Lebesgue measure set. This is a useful concept, specially when global synchronization can not be stated, due, for example, to the existence of multiple equilibria. In this survey article, we give an analysis of the influence of the interconnection graph on this dynamical property. We present in a ordered way several known and new results that help on the characterization of what we have called synchronizing topologies.

We prove that for autonomous differential equations with the origin as a fixed point, and with at least one eigenvalue with negative real part, we have that the existence of a density function implies local asymptotical stability. We present examples of a system admitting a density function for which the origin is not locally asymptotically stable and an almost globally stable system for which no function is a density function.

Favourable prices and new technologies have recently stimulated the adoption of wheat–soybean double crops in the south-eastern Pampas. To assess the largely unknown long-term performance of this strategy, we used CERES-Wheat and CROPGRO-Soybean with slight adaptations to account for double cropping. Models and climate records were combined to analyse management practices allowing for earlier soybean sowing, which was assumed to be the key for high soybean yield and whole-system performance. Practices investigated were: (i) short-season wheat cultivars; (ii) non-selective herbicides for faster drying of wheat before harvest; (iii) relay double cropping, where soybean is sown on standing wheat before crop maturity in contrast to sequential cropping where soybean is sown after wheat harvest. Models reproduced phenology and yield of crops in double cropping systems to the level required for our investigation. Advancing wheat harvest with herbicides and using current early wheat varieties had little impact on soybean yield. A hypothetical frost-resistant wheat allowing for earlier wheat sowing and harvest highlighted the potential to increase the yield of sequential soybean by 23%. Average soybean yield increased from 1738 kg ha −1 in sequential to 2099 kg ha −1 in relay cropping, whereas wheat yield was similar in both cropping variants. Seasonal variability in rainfall and simulated yield was partially accounted by the Southern Oscillation Index (SOI), indicating the potential for this signal to be used in risk management. The amount of rainfall during the period of yield generation in wheat and the remaining soil water at the end of the wheat growing season were higher during consistently negative SOI phase, and lower during consistently positive phase in September. In the period between 1971 and 2003 average October–December temperature increased at 0.038 °C year −1 . Higher temperature accelerated simulated wheat development and advanced harvest (0.15 day year −1 ) with no impact on yield; this allowed for earlier sowing of double cropped soybean, which together with more favourable temperature increased simulated soybean yield at a rate of 26.2 kg ha −1 year −1 . Hence, our modelling study indicated that: (i) wheat–soybean relay double cropping outperformed its sequential counterpart, (ii) seasonal variability in rainfall and yield could be partially accounted by Southern Oscillation Index (SOI) and (iii) long-term trends in crop phenology and yield could be associated with increased mean temperature.

In this work, we analyze the almost global synchronization property of sinusoidally coupled oscillators. In contrast with previous works, we introduce an approach that uses the strong basic facts of algebraic graph theory to prove dynamical properties of the standard symmetric Kuramoto model. We show how we can interconnect two (or several) systems via bridges, keeping the almost global synchronization. These ideas can be used to explore other kinds of interconnections.

The global use of agrochemicals and pesticides has increased due to the development of agricultural technologies. Evidence of the toxicity of these chemicals has been detected in beehives. In order to find the relationship between the ecosystem's contamination and the behavior of bees, we developed a device that samples audio and temperature in hives. This correlation would allow the use of apiaries as remote monitors of contamination. This paper presents the design and implementation of the system, including both hardware and software specifications. The appliance takes samples on 14 channels: six to measure temperature and eight for audio, being the latter of up to 1 kHz. It calculates the Fast Fourier transform and keeps its module to represent the energy in each frequency band. All the information is locally stored in a flash memory card and is later sent to a remote server using GPRS. The device is based on a Texas Instruments development board that uses the Stellaris LM4F232H5QD microcontroller. The system can be remotely configured and it is energetically autonomous since its battery is solar-charged.

This paper advances a new method to predict trajectories of rotor angles and bus voltages in dynamic power systems, with data collected by phasor measurement units. The predictor incorporates real time data adaptively, leveraging the algebraic differential equations describing the system, while being able to accommodate model inaccuracies. Numerical tests on a one machine infinite bus system are carried out to illustrate the predictor properties. Then, further results are presented on a classical networked testbed of nine buses and three generators.