Decision Analysis Linguistic Framework

Everyday human beings are faced with situations they should choose among different alternatives by means of reasoning and mental processes when solving a problem. Many of these decision problems are under uncertain environments including vague, imprecise and subjective information that is usually modeled by linguistic information due to the use of natural language and its relation to mental reasoning processes of the experts when expressing their judgments. In a decision process multiple criteria can be evaluated which involving multiple experts with different degrees of knowledge. Such process can be modeled by using Multi-granular Linguistic Information (MGLI) and Computing with Words (CW) processes to solve the related decision problems. Different methodologies and approaches have been proposed to accomplish this process in an accurate and interpretable way. In this paper we propose a useful Decision Analysis Framework to manage this kind of problems by using the Extended Linguistic Hierarchy (ELH), 2-tuples linguistic representation model and its computational method. The developed Framework has many advantages when dealing with a complex problem in a simple way and its capability of having easy and useful reasonably results.Sociedad Argentina de Informática e Investigación Operativ

Editorial: Advances in Power-to-X: Processes, Systems, and Deployment

[No abstract available

Partial Differential Equation-Constrained Diffeomorphic Registration from Sum of Squared Differences to Normalized Cross-Correlation, Normalized Gradient Fields, and Mutual Information: A Unifying Framework; 35632143

This work proposes a unifying framework for extending PDE-constrained Large Deformation Diffeomorphic Metric Mapping (PDE-LDDMM) with the sum of squared differences (SSD) to PDE-LDDMM with different image similarity metrics. We focused on the two best-performing variants of PDE-LDDMM with the spatial and band-limited parameterizations of diffeomorphisms. We derived the equations for gradient-descent and Gauss-Newton-Krylov (GNK) optimization with Normalized Cross-Correlation (NCC), its local version (lNCC), Normalized Gradient Fields (NGFs), and Mutual Information (MI). PDE-LDDMM with GNK was successfully implemented for NCC and lNCC, substantially improving the registration results of SSD. For these metrics, GNK optimization outperformed gradient-descent. However, for NGFs, GNK optimization was not able to overpass the performance of gradient-descent. For MI, GNK optimization involved the product of huge dense matrices, requesting an unaffordable memory load. The extensive evaluation reported the band-limited version of PDE-LDDMM based on the deformation state equation with NCC and lNCC image similarities among the best performing PDE-LDDMM methods. In comparison with benchmark deep learning-based methods, our proposal reached or surpassed the accuracy of the best-performing models. In NIREP16, several configurations of PDE-LDDMM outperformed ANTS-lNCC, the best benchmark method. Although NGFs and MI usually underperformed the other metrics in our evaluation, these metrics showed potentially competitive results in a multimodal deformable experiment. We believe that our proposed image similarity extension over PDE-LDDMM will promote the use of physically meaningful diffeomorphisms in a wide variety of clinical applications depending on deformable image registration

MapReduce-based Solutions for Scalable SPARQL Querying

The use of RDF to expose semantic data on the Web has seen a dramatic increase over the last few years. Nowadays, RDF datasets are so big and rconnected that, in fact, classical mono-node solutions present significant scalability problems when trying to manage big semantic data. MapReduce, a standard framework for distributed processing of great quantities of data, is earning a place among the distributed solutions facing RDF scalability issues. In this article, we survey the most important works addressing RDF management and querying through diverse MapReduce approaches, with a focus on their main strategies, optimizations and results

M–SURGE: new software specifically designed for multistate capture–recapture models

M–SURGE, al igual que su compañero, el programa U–CARE, se ha escrito con el propósito específico de manejar modelos multiestado de captura–recaptura, lo que a su vez permite mitigar las dificultades inherentes a los mismos (especificación de los modelos, calidad de la convergencia, flexibilidad de parametrización, evaluación del ajuste). En su terreno, M–SURGE abarca una gama de modelos más extensa que un programa general, como el MARK (White & Burnham, 1999), al tiempo que resulta más accesible para el usuario que el MS–SURVIV (Hines, 1994). De entre las principales características del M–SURGE, cabe destacar una amplia gama de modelos y varias parametrizaciones: (1) M–SURGE abarca los modelos condicionales con probabilidad de recaptura según el estado actual (modelos tipo Arnason–Schwarz), y según el estado actual y previo (modelos tipo Jolly–movement). En ambos casos, es posible examinar los efectos dependientes de la edad y/o del tiempo, así como grupos múltiples. (2) Las probabilidades combinadas de supervivencia–transición pueden representarse como tales, o descomponerse en probabilidades de transición y supervivencia. (3) Por lo que respecta a las probabilidades de transición con el mismo estado de partida, el usuario puede elegir libremente la probabilidad que deberá calcularse por sustracción. Además de ser un programa muy accesible para el usuario, también debe subrayarse la facilidad con que permite construir modelos constreñidos utilizando un lenguaje interpretado denominado GEMACO. En este estudio desarrollamos y presentamos varios tipos de modelos multiestado.M–SURGE (along with its companion program U–CARE) has been written specifically to handle multistate capture–recapture models and to alleviate their inherent difficulties (model specification, quality of convergence, flexibility of parameterization, assessment of fit). In its domain, M–SURGE covers a broader range of models than a general program like MARK (White & Burnham, 1999), while being more user–friendly than MS–SURVIV (Hines, 1994). Among the main features of M–SURGE is a wide class of models and a variety of parameterizations: (1) M–SURGE covers conditional models with probability of recapture depending on the current state (Arnason–Schwarz type models) as well as on the current and previous state (Jolly–movement type models). In both cases, age and/or time–dependence and multiple groups can be considered. (2) Combined survival–transition probabilities can be represented as such or decomposed into transition and survival probabilities. (3) Among the transition probabilities with the same state of departure, the one to be computed by subtraction can be freely picked by the user. User–friendliness is enhanced by the easiness with which constrained models are built, using an interpreted language called GEMACO. Examples of various types of multistate models are developed and presented

A cool starspot or a second transiting planet in the TrES-1 system?

We investigate the origin of a flux increase found during a transit of TrES-1, observed with the HST. This feature in the HST light curve cannot be attributed to noise and is supposedly a dark area on the stellar surface of the host star eclipsed by TrES-1 during its transit. We investigate the likeliness of two possible hypothesis for its origin: A starspot or a second transiting planet. We made use of several transit observations of TrES-1 from space with the HST and from ground with the IAC-80 telescope. On the basis of these observations we did a statistical study of flux variations in each of the observed events, to investigate if similar flux increases are present in other parts of the data set. The HST observation presents a single clear flux rise during a transit whereas the ground observations led to the detection of two such events but with low significance. In the case of having observed a starspot in the HST data, assuming a central impact between the spot and TrES-1, we would obtain a lower limit for the spot radius of 42000 km. For this radius the spot temperature would be 4690 K, 560 K lower then the stellar surface of 5250 K. For a putative second transiting planet we can set a lower limit for its radius at 0.37 R$_J$ and for periods of less than 10.5 days, we can set an upper limit at 0.72 R$_J$. Assuming a conventional interpretation, then this HST observation constitutes the detection of a starspot. Alternatively, this flux rise might also be caused by an additional transiting planet. The true nature of the origin can be revealed if a wavelength dependency of the flux rise can be shown or discarded with a higher certainty. Additionally, the presence of a second planet can also be detected by radial velocity measurements.Comment: 8 pages, 6 figures, accepted for publication in A&

Adaptive Rotational Grazing and the Story of the Regrazed Grass Plant

Livestock stocking rates and decisions about how to move animals in time and space impact plant responses to livestock grazing. We report on a ranch-scale collaborative experiment comparing adaptive rotational grazing management to season-long continuous grazing during a 4.5-month grazing period during the growing season. As part of this project, stakeholders and scientists worked together to articulate their hypotheses about the mechanisms linking rotational grazing with expected vegetation outcomes. Several stakeholders expected rotational grazing to enhance the production and diversity of grazing-sensitive perennial grass species. The main hypothesized mechanism underlying this expectation was that rotation grazing should reduce regrazing of these grass plants. To test this hypothesis, we monitored patterns of grazing and regrazing on individual tillers (ramets) of a grazing-sensitive grass species, Pascopyrum smithii (western wheatgrass) for three consecutive years. We measured regrazing rates in paddocks managed using moderate stocking and adaptive rotational grazing as well as paddocks grazed continuously, season-long at light, moderate, or heavy stocking rates. Tillers in heavily grazed paddocks were regrazed more than three times as frequently as tillers in moderately grazed pastures, reinforcing the importance of stocking rate as a driver of vegetation impact. At the ranch-scale, tillers were regrazed equally often under adaptive rotational and season-long continuous grazing management, and this result did not vary across years. Adaptive rotational grazing greatly increased heterogeneity among paddocks in patterns of regrazing, with some paddocks experiencing high utilization and others experiencing low utilization. In this semi-arid rangeland, tiller defoliation data do not support the hypothesis that adaptive rotational grazing leads to less regrazing at the ranch-scale. In line with these mechanistic results, the production and diversity of grazing-sensitive perennial grasses also failed to respond to adaptive rotational grazing after five years. However, adaptive rotational grazing may enhance management flexibility and provide opportunities to work towards other objectives, such as wildlife habitat

Pion decay constant for the Kogut-Susskind quark action in quenched lattice QCD

We present a study for the pion decay constant $f_\pi$ in the quenched approximation to lattice QCD with the Kogut-Susskind (KS) quark action, with the emphasis given to the renormalization problems. Numerical simulations are carried out at the couplings $\beta = 6.0$ and 6.2 on $32^3\times 64$ and $48^3\times 64$ lattices, respectively. The pion decay constant is evaluated for all KS flavors via gauge invariant and non-invariant axial vector currents with the renormalization constants calculated by both non-perturbative method and perturbation theory. We obtain $f_\pi = 89(6)$ MeV in the continuum limit as the best value using the partially conserved axial vector current, which requires no renormalization. From a study for the other KS flavors we find that the results obtained with the non-perturbative renormalization constants are well convergent among the KS flavors in the continuum limit, confirming restoration of $\rm SU(4)_A$ flavor symmetry, while perturbative renormalization still leaves an apparent flavor breaking effect even in the continuum limit.Comment: LaTex, 27 pages, 35 eps figures, uses revtex and eps

Decision Analysis Linguistic Framework

Everyday human beings are faced with situations they should choose among different alternatives by means of reasoning and mental processes when solving a problem. Many of these decision problems are under uncertain environments including vague, imprecise and subjective information that is usually modeled by linguistic information due to the use of natural language and its relation to mental reasoning processes of the experts when expressing their judgments. In a decision process multiple criteria can be evaluated which involving multiple experts with different degrees of knowledge. Such process can be modeled by using Multi-granular Linguistic Information (MGLI) and Computing with Words (CW) processes to solve the related decision problems. Different methodologies and approaches have been proposed to accomplish this process in an accurate and interpretable way. In this paper we propose a useful Decision Analysis Framework to manage this kind of problems by using the Extended Linguistic Hierarchy (ELH), 2-tuples linguistic representation model and its computational method. The developed Framework has many advantages when dealing with a complex problem in a simple way and its capability of having easy and useful reasonably results.Sociedad Argentina de Informática e Investigación Operativ

Adaptive, Multi-Paddock, Rotational Grazing Management: An Experimental, Ranch-Scale Assessment of Effects on Multiple Ecosystem Services

Decisions on how to move livestock in space and time are central to rangeland management. Despite decades of small-scale research, substantial uncertainty exists regarding the relative importance of cattle stocking rates per se, versus the movement of cattle in both space and time, in achieving desired vegetation and livestock outcomes at scales relevant to livestock producers. We report on a ranch-scale experiment comparing effects of collaborative, adaptive, multi-paddock, rotational management (CARM) versus more traditional, season-long, continuous rangeland management (TRM) on perennial grass density and production, cattle performance, and wildlife habitat, while holding the annual stocking rate the same in both systems. We collaborated with stakeholders to develop an adaptive grazing management plan, collected pre-treatment data in 2013, and implemented treatments during 2014 – 2020. Results for 2014 – 2018 were reported by Augustine et al. (2020); here we report on two additional years of results, covering a 7-year period of treatments from 2014 – 2020. With two additional years of measurements, we found no significant difference in total forage production in CARM vs. TRM treatments, averaged across all soil types in the experiment. In one year, we found that CARM increased forage production on loamy soils and decreased forage production on alkaline soils, but these differences were minor and in opposite directions, resulting in no net overall effect. Furthermore, we found that adaptive, rotational grazing management substantially reduced livestock weight gains in each of the first 6 years of the experiment, when cattle were managed as a single, large herd occupying each paddock sequentially. Across the 6 years, cattle weight gain averaged 15% lower in CARM vs. TRM. In the 7th year, stocking density in CARM was reduced 50% by giving cattle access to two paddocks at a time. This year also coincided with a drought. Under these conditions, cattle weight gains were identical in both treatments. Results emphasize the importance of replicated controls in assessing grazing management effects. Even in heterogeneous landscapes where livestock are moved adaptively among paddocks to match seasonal patterns of forage growth, such management may not lead to desired outcomes for vegetation and livestock