Sampling Based On Natural Image Statistics Improves Local Surrogate Explainers

Many problems in computer vision have recently been tackled using models whose predictions cannot be easily interpreted, most commonly deep neural networks. Surrogate explainers are a popular post-hoc interpretability method to further understand how a model arrives at a particular prediction. By training a simple, more interpretable model to locally approximate the decision boundary of a non-interpretable system, we can estimate the relative importance of the input features on the prediction. Focusing on images, surrogate explainers, e.g., LIME, generate a local neighbourhood around a query image by sampling in an interpretable domain. However, these interpretable domains have traditionally been derived exclusively from the intrinsic features of the query image, not taking into consideration the manifold of the data the non-interpretable model has been exposed to in training (or more generally, the manifold of real images). This leads to suboptimal surrogates trained on potentially low probability images. We address this limitation by aligning the local neighbourhood on which the surrogate is trained with the original training data distribution, even when this distribution is not accessible. We propose two approaches to do so, namely (1) altering the method for sampling the local neighbourhood and (2) using perceptual metrics to convey some of the properties of the distribution of natural images.Comment: 12 pages, 7 figure

Electrochemical sensors modified with combinations of sulfur containing phthalocyanines and capped gold nanoparticles: A study of the influence of the nature of the interaction between sensing materials

Producción CientíficaVoltametric sensors formed by the combination of a sulfur-substituted zinc phthalocyanine (ZnPcRS) and gold nanoparticles capped with tetraoctylammonium bromide (AuNPtOcBr) have been developed. The influence of the nature of the interaction between both components in the response towards catechol has been evaluated. Electrodes modified with a mixture of nanoparticles and phthalocyanine (AuNPtOcBr/ZnPcRS) show an increase in the intensity of the peak associated with the reduction of catechol. Electrodes modified with a covalent adduct-both component are linked through a thioether bond-(AuNPtOcBr-S-ZnPcR), show an increase in the intensity of the oxidation peak. Voltammograms registered at increasing scan rates show that charge transfer coefficients are different in both types of electrodes confirming that the kinetics of the electrochemical reaction is influenced by the nature of the interaction between both electrocatalytic materials. The limits of detection attained are 0.9 × 10−6 mol∙L−1 for the electrode modified with the mixture AuNPtOcBr/ZnPcRS and 1.3 × 10−7 mol∙L−1 for the electrode modified with the covalent adduct AuNPtOcBr-S-ZnPcR. These results indicate that the establishment of covalent bonds between nanoparticles and phthalocyanines can be a good strategy to obtain sensors with enhanced performance, improving the charge transfer rate and the detection limits of voltammetric sensors.Ministerio de Economía, Industria y Competitividad - Fondo Europeo de Desarrollo Regional (projects RTI2018-097990-B-I00 / CTQ2017-87102-R)Junta de Castilla y Leon - Fondo Europeo de Desarrollo Regional (project VA275P18

Analysis of survival for lung cancer resections cases with fuzzy and soft set theory in surgical decision making [Dataset]

DatasetThis initial database was developed in a study of 403 patients who underwent major pulmonary resections in the Salamanca University Hospital from 1994 to 2016. We have taken patients with known survival status and a surgical procedure other than pneumonectomy. The variables used in our study are: (1) Age of patient; (2) Body mass index (abbr. BMI, expressed in kg/m^2); (3) Existence of chronic obstructive pulmonary disease (abbr. COPD); (4) Forced vital capacity calculated percentage (abbr. FEV1%); (5) Approach of the surgery (thoracotomy or video-assisted thoracoscopic surgery, VATS); and (6) Presence of complications in the surgery. The variable of mortality allows us to establish the survival of the patient. Age is obtained from the date of birth and the date of surgery. Body mass index is calculated based on the weight and size of the patient.The variables used in our study are: (1) Age of patient; (2) Body mass index (abbr. BMI, expressed in kg/m^2); (3) Existence of chronic obstructive pulmonary disease (abbr. COPD); (4) Forced vital capacity calculated percentage (abbr. FEV1%); (5) Approach of the surgery (thoracotomy or video-assisted thoracoscopic surgery, VATS); (6) Presence of complications in the surgery

Cross‐talk between two global regulators in Streptomyces: PhoP and AfsR interact in the control of afsS, pstS and phoRP transcription

[EN] The regulatory proteins AfsR and PhoP control expression of the biosynthesis of actinorhodin and undecylprodigiosin in Streptomyces coelicolor. Electrophoretic mobility shift assays showed that PhoPDBD does not bind directly to the actII-ORF4, redD and atrA promoters, but it binds to the afsS promoter, in a region overlapping with the AfsR operator. DNase I footprinting studies revealed a PhoP protected region of 26 nt (PHO box; two direct repeats of 11 nt) that overlaps with the AfsR binding sequence. Binding experiments indicated a competition between AfsR and PhoP; increasing concentrations of PhoPDBD resulted in the disappearance of the AfsR-DNA complex. Expression studies using the reporter luxAB gene coupled to afsS promoter showed that PhoP downregulates afsS expression probably by a competition with the AfsR activator. Interestingly, AfsR binds to other PhoP-regulated promoters including those of pstS (a component of the phosphate transport system) and phoRP (encoding the two component system itself). Analysis of the AfsR-protected sequences in each of these promoters allowed us to distinguish the AfsR binding sequence from the overlapping PHO box. The reciprocal regulation of the phoRP promoter by AfsR and of afsS by PhoP suggests a fine interplay of these regulators on the control of secondary metabolismSIThis project was supported by grants of the ‘Comisión Interministerial de Ciencia y Tecnología’ (BIO2003-01489, BIO2006-14853-C02-01); Ministry of Education, Science and Technology, Madrid (GEN2003-20245-C09-01); the ERA-NET SySMO Project (GEN2006-27745-E/SYS) and the European Union (ACTINOGEN LSHM-CT-2004-005224). F. Santos-Beneit received a fellowship of the FPI programme (Ministry of Education, Spain). We thank S. Horinouchi for the plasmids containing the afsR gene, M. Bibb for strain S. coelicolor M513 (ΔafsR) and B. Martín, J. Merino, A. Casenave and B. Aguado for excellent technical assistanc

Predictive modeling of Enterococcus sp. removal with limited data from different advanced oxidation processes: a machine learning approach

The removal of contaminants through Advanced Oxidation Processes (AOPs) is a complex task that demands the simultaneous consideration of multiple operating parameters, such as type and concentration of oxidant and catalyst, type and intensity of radiation, composition of aqueous matrix, etc. Designing efficient AOPs often requires expensive and time-consuming laboratory experiments. To improve this process, this study proposes a Machine Learning approach based on a Random Forest (RF) model, to predict Enterococcus sp. concentration in wastewater treated with various AOPs, even when dealing with limited data. To assess our approach under diverse conditions, a data partitioning methodology is used to categorize the different AOPs into three distinct study cases of increasing complexity, from Case I to Case III. The evaluation of the RF model’s performance, combined with the data partitioning methodology, demonstrated its usefulness in predicting missing or additional disinfection values at any instant during the AOPs. Specifically, in Case I, the model excels at generalizing predictions across various AOP treatments, followed by Case II and III, which achieve Root Mean Squared Error (RMSE) values below or comparable to the average RMSE of Case I (0.72) in 8 out of 15 and 2 out of 4 treatments, respectively. Moreover, the effects of imbalanced data on model performance are discussed. This highlights the potential of our approach to assess AOPs performance and facilitate the design of new experiments of the same treatment type without the need for additional laboratory trials, even in challenging conditions.The publication is part of Projects TED2021-129969A-C32 and TED2021-129969B-C33 funded by MCIN/AEI/ 10.13039/501100011033 and by “European Union NextGenerationEU/PRTR”. Sonia Guerra-Rodríguez acknowledges the Universidad Politécnica de Madrid (UPM) for the financial support provided through the predoctoral contract granted within the “Programa Propio”. Jorge Rodríguez-Chueca acknowledges Comunidad de Madrid by the pluriannual agreement with the Polytechnic University of Madrid in the line of action Programme of Excellence for University Teaching Staff (M190020074BJJRC). This work was also funded by the Spanish Ministry of Economy and Competitiveness through the “Severo Ochoa Programme for Centres of Excellence in R&D” (CEX2018-000797-S) and the Generalitat de Catalonia through the CERCA Program.Peer ReviewedPostprint (published version

Shrub diversity in Mediterranean shrublands: Rescuer or victim of productivity?

[ENG]Aims: Unravelling the most prevalent causal direction between diversity and function in naturally recovered plant assemblages can greatly improve our understanding of the functional significance of diversity and its applications under the ongoing envi- ronmental changes. In this study, we apply a structural equation model framework to unravel the most plausible causal direction in the diversity–productivity relationship in subseral Mediterranean shrub-dominated communities. Methods: Total shrub cover (as a proxy of productivity when controlled by the time since land use cessation or the last wildfire), the number of species, and the number of functional types based on the dominant life forms (phanerophytes vs. chamaephytes), and the dominant foliar syndromes (deciduous vs. evergreen, needled vs. broad- leaved), were sampled in 195 circular plots distributed along an elevation gradient ranging from 400 to 1400 m a.s.l. in the Central Iberian Peninsula. We first explored the distribution of functional types along the elevation gradient using a non-metric multidimensional scaling (NMDS). Secondly, a structural equation model (SEM) frame- work using mixed-effects models was defined to unveil the prevalent causal direction between diversity (species and functional types) and productivity at the landscape scale. Results: Model selection using the Fisher's C information criterion supported a causal direction from total shrub cover to diversity in this landscape. Interestingly, the best supported model also supported a positive relationship between species richness and the number of functional types, which in turn is driven by the total shrub cover along the elevation gradient. Conclusions: Our results suggest that more species might not necessarily boost pro- ductivity. On the contrary, ongoing warming temperatures and aridity, which are characteristic of low elevations compared to highlands, might significantly reduce the number of species (victim rather than rescuer) through deleterious effects on productivity

Enhanced satellite analytics for mussel platform census using a machine-learning based approach

Mussel platforms are big floating structures made of wood (normally about 20 m × 20 m or even a bit larger) that are used for aquaculture. They are used for supporting the growth of mussels in suitable marine waters. These structures are very common near the Galician coastline. For their maintenance and tracking, it is quite convenient to be able to produce a periodic census of these structures, including their current count and position. Images from Earth observation satellites are, a priori, a convenient choice for this purpose. This paper describes an application capable of automatically supporting such a census using optical images taken at different wavelength intervals. The images are captured by the two Sentinel 2 satellites (Sentinel 2A and Sentinel 2B, both from the Copernicus Project). The Copernicus satellites are run by the European Space Agency, and the produced images are freely distributed on the Internet. Sentinel 2 images include thirteen frequency bands and are updated every five days. In our proposal, remote-sensing normalized (differential) indexes are used, and machine-learning techniques are applied to multiband data. Different methods are described and tested. The results obtained in this paper are satisfactory and prove the approach is suitable for the intended purpose. In conclusion, it is worth noting that artificial neural networks turn out to be particularly good for this problem, even with a moderate level of complexity in their design. The developed methodology can be easily re-used and adapted for similar marine environments

Approaches and methods for ecosystem services assessment in the North of Portugal: from supply modeling to land management optimization

In the last decades, ecosystems services (ES) in the North of Portugal have been assessed typically for sets of ES addressed individually based on indicators (e.g., LULC) but also through mechanistic and non-mechanistic modeling (e.g., hydrological modeling, InVEST). Economic evaluation has been applied based mostly on the combination of ES supply in biophysical units with market prices or value attributed by other techniques (e.g., avoided cost, unit value transfer). Such studies, and the approaches and methods involved, have been helpful in demonstrating the magnitude and dynamics of the supply of a series of ES in the region, both in biophysical and monetary units, and to inform regional planning and management of natural resources, such as forests. These studies have been changing the perception of stakeholders regarding forest systems and their management. Despite the importance of ES research conducted so far, there is an ongoing effort to further develop ES assessment in the region, conceptually and methodologically, namely by overcoming some of the intrinsic constraints of the approaches and methods used. Improvements intend to better integrate different ecosystem functions and services, to eliminate double counting, and to address the interactions between supply and demand of ES at several scales. The incorporation of capabilities of land-use and management optimization based on the supply and value of ES is also currently a research goal in the region. Recent developments have been based on operational research tools developed for the forest sector in the region of Bragan ça addressing ecosystem services from heuristics, multi-criteria and linear programming perspectives, expecting to solve complex spatially explicit management alternatives problems based on ES. In this presentation we will introduce these tools and their adjustment and applications in the assessment of ES in the region.info:eu-repo/semantics/publishedVersio

Social auditing in the organizations of the cooperative sector: precedent of remarkable governance scenario

Las organizaciones cooperativas forman un sector cada vez más visible y relevante, cuyo fin afianza la política de ofrecer respuesta a necesidades concretas de bienestar de las personas, colectividades y de la sociedad en general. El presente trabajo tiene por objeto resaltar la importancia que representa la auditoría social en las organizaciones del sector cooperativo, como respuesta derivada de diligentes prácticas de gobernabilidad y prácticas de buen gobierno; para ello, se tomaron 7 cooperativas especializadas de ahorro y crédito definidas por la legislación colombiana como una asociación autónoma de personas que se han unido voluntariamente para hacer frente a sus insuficiencias y aspiraciones económicas, sociales y culturales. Los hallazgos enseñan que la auditoría, cuando es administrada cabalmente, forja el cumplimiento de los objetivos estratégicos en materia social, esto es, utilizar los recursos de los fondos de destino específico en actividades propias de los mismos, tales como educación formal, salud, auxilios funerarios y otras actividades para el bienestar del asociado; actividades debidamente aprobadas por el órgano competente, reveladas en sus informes de gestión e información financiera. Como conclusión, la gobernabilidad de las cooperativas estudiadas sustenta su andamiaje en el acierto de la elección de los miembros de los comités de auditoría, quienes ejercen un efectivo control sobre los recursos con asignación específica.Cooperative organizations form an increasingly visible and relevant sector, whose purpose strengthens the policy of providing a response to specific welfare needs of individuals, communities and society in general. The purpose of this paper is to highlight the importance of social auditing in cooperative sector organizations, as a response derived from diligent governance practices; to this end, seven specialized saving and credit cooperatives defined by Colombian legislation as an autonomous association of persons who have voluntarily joined together to address their economic, social and cultural insufficiencies and aspirations were taken. The findings show that auditing when fully administered, forges the fulfilment of strategic social objectives, i.e. to use the resources of the specific earmarked funds in their own activities, such as formal education, health, funeral aid and other partner welfare activities; duly approved by the competent body, disclosed in its management reports and financial information. As a conclusion, the governance of the cooperatives studied underpins their scaffolding on the success of the choice of the members of the audit committees, who exercise effective control over the resources with specific allocation.Escuela de Estudios CooperativosFac. de Ciencias Económicas y EmpresarialesTRUEpu

High-quality region-based foreground segmentation using a spatial grid of SVM classifiers

This paper presents a novel background modeling system that uses a spatial grid of Support Vector Machines classifiers for segmenting moving objects, which is a key step in many video-based consumer applications. The system is able to adapt to a large range of dynamic background situations since no parametric model or statistical distribution are assumed. This is achieved by using a different classifier per image region that learns the specific appearance of that scene region and its variations (illumination changes, dynamic backgrounds, etc.). The proposed system has been tested with a recent public database, outperforming other state-of-the-art algorithms