Suchergebnisse

From Huhugam to Hohokam: Heritage and Archaeology in the American Southwest is an historical comparison of archaeologists' views of the ancient Hohokam with Native O'odham concepts about themselves and their relationships with their neighbors and ancestors.

Probabilistic planners have improved recently to the point that they can solve difficult tasks with complex and expressive models. In contrast, learners cannot tackle yet the expressive models that planners do, which forces complex models to be mostly handcrafted. We propose a new learning approach that can learn relational probabilistic models with both action effects and exogenous effects. The proposed learning approach combines a multivalued variant of inductive logic programming for the generation of candidate models, with an optimization method to select the best set of planning operators to model a problem. We also show how to combine this learner with reinforcement learning algorithms to solve complete problems. Finally, experimental validation is provided that shows improvements over previous work in both simulation and a robotic task. The robotic task involves a dynamic scenario with several agents where a manipulator robot has to clear the tableware on a table. We show that the exogenous effects learned by our approach allowed the robot to clear the table in a more efficient way. ; This work has been supported by the MINECO project RobInstruct TIN2014-58178-R and the European Union's Horizon 2020 research and innovation programme under grant agreement H2020-ICT-2016-1-731761 IMAGINE. D. Martínez is also supported by the Spanish Ministry of Education, Culture and Sport via a FPU doctoral grant (FPU12-04173). ; Peer Reviewed

We present a problem motivated by discussions with Colombian e-commerce platforms for agri-food products. In regular time intervals (periods), the platforms collect groceries from local farmers and stores them at a warehouse to distribute them to local customers. The supply quantities and prices per farmer and the cumulated customer demand can change from period to period. Thus, there is value in purchasing more than needed in one period to exploit cheap prices and consolidation opportunities, to hedge against future uncertainty, and to save routing cost in future periods. A careful balance between too much and not enough inventory needs to be found, especially, since inventory perishes over time. The resulting optimization problem is a stochastic dynamic multi-period routing problem with inventory and purchasing decisions. The decision space of the problem is vast as it combines purchasing, inventory, and routing decisions. Further, the value of a decisions is unknown since it depends on future developments and decisions. We propose solving the problem with a stochastic lookahead method. In every state, the method samples a set of future realizations and solves the resulting two-stage stochastic program. To cope with the complex decision space in first and second stage, we propose a "soft" decomposition where the inventory and purchasing decision are fully considered, but the routing decisions are simplified and their cost is approximated via a cost function approximation. As the routing cost also depends on future decisions, the approximated cost are learned iteratively via repeated simulation and adaption of the lookahead. We show that our method outperforms a large number of benchmark policies for a variety of instances. We further analyze the functionality of our method and investigate variation in the problem dimensions in a comprehensive analysis.

Abstract. Estimating flood damage, although crucial for assessing flood risk and for designing mitigation policies, continues to face numerous challenges, notably the assessment of indirect damage. It is widely accepted that damage other than direct damage can account for a significant proportion of total damage. Yet due to scarcer data sources and lack of knowledge on links within and between economic activities, indirect impacts have received less attention than direct impacts. Furthermore, attempts to grasp indirect damage through economic models have not gone below regional levels. Even though local communities can be devastated by flood events without this being reflected in regional accounts, few studies have been conducted from a microeconomic perspective at local level. What is more, the standard practices applied at this level of analysis tackle entities but ignore how they may be linked. This paper addresses these two challenges by building a novel agent-based model of a local agricultural production chain (a French cooperative wine-making system), utilized as a virtual laboratory for the ex ante estimation of flood impacts. We show how overlooking existing interactions between economic entities in production chains can result in either overestimation (double counting) or underestimation (wrong estimation of the consequences for the activity) of flood damage. Our results also reveal that considering interactions requires thorough characterization of their spatial configuration. Based on both the application of our method and the results obtained, we propose balanced recommendations for flood damage estimation at local level.

International audience ; Estimating flood damage, although crucial for assessing flood risk and for designing mitigation policies, continues to face numerous challenges, notably the assessment of indirect damage. It is widely accepted that damage other than direct damage can account for a significant proportion of total damage. Yet due to scarcer data sources and lack of knowledge on links within and between economic activities, indirect impacts have received less attention than direct impacts. Furthermore, attempts to grasp indirect damage through economic models have not gone below regional levels. Even though local communities can be devastated by flood events without this being reflected in regional accounts, few studies have been conducted from a microeconomic perspective at local level. What is more, the standard practices applied at this level of analysis tackle entities but ignore how they may be linked. This paper addresses these two challenges by building a novel agent-based model of a local agricultural production chain (a French cooperative wine-making system), utilized as a virtual laboratory for the ex ante estimation of flood impacts. We show how overlooking existing interactions between economic entities in production chains can result in either overestimation (double counting) or underestimation (wrong estimation of the consequences for the activity) of flood damage. Our results also reveal that considering interactions requires thorough characterization of their spatial configuration. Based on both the application of our method and the results obtained, we propose balanced recommendations for flood damage estimation at local level.

International audience ; Estimating flood damage, although crucial for assessing flood risk and for designing mitigation policies, continues to face numerous challenges, notably the assessment of indirect damage. It is widely accepted that damage other than direct damage can account for a significant proportion of total damage. Yet due to scarcer data sources and lack of knowledge on links within and between economic activities, indirect impacts have received less attention than direct impacts. Furthermore, attempts to grasp indirect damage through economic models have not gone below regional levels. Even though local communities can be devastated by flood events without this being reflected in regional accounts, few studies have been conducted from a microeconomic perspective at local level. What is more, the standard practices applied at this level of analysis tackle entities but ignore how they may be linked. This paper addresses these two challenges by building a novel agent-based model of a local agricultural production chain (a French cooperative wine-making system), utilized as a virtual laboratory for the ex ante estimation of flood impacts. We show how overlooking existing interactions between economic entities in production chains can result in either overestimation (double counting) or underestimation (wrong estimation of the consequences for the activity) of flood damage. Our results also reveal that considering interactions requires thorough characterization of their spatial configuration. Based on both the application of our method and the results obtained, we propose balanced recommendations for flood damage estimation at local level.

International audience ; Estimating flood damage, although crucial for assessing flood risk and for designing mitigation policies, continues to face numerous challenges, notably the assessment of indirect damage. It is widely accepted that damage other than direct damage can account for a significant proportion of total damage. Yet due to scarcer data sources and lack of knowledge on links within and between economic activities, indirect impacts have received less attention than direct impacts. Furthermore, attempts to grasp indirect damage through economic models have not gone below regional levels. Even though local communities can be devastated by flood events without this being reflected in regional accounts, few studies have been conducted from a microeconomic perspective at local level. What is more, the standard practices applied at this level of analysis tackle entities but ignore how they may be linked. This paper addresses these two challenges by building a novel agent-based model of a local agricultural production chain (a French cooperative wine-making system), utilized as a virtual laboratory for the ex ante estimation of flood impacts. We show how overlooking existing interactions between economic entities in production chains can result in either overestimation (double counting) or underestimation (wrong estimation of the consequences for the activity) of flood damage. Our results also reveal that considering interactions requires thorough characterization of their spatial configuration. Based on both the application of our method and the results obtained, we propose balanced recommendations for flood damage estimation at local level.

International audience ; Estimating flood damage, although crucial for assessing flood risk and for designing mitigation policies, continues to face numerous challenges, notably the assessment of indirect damage. It is widely accepted that damage other than direct damage can account for a significant proportion of total damage. Yet due to scarcer data sources and lack of knowledge on links within and between economic activities, indirect impacts have received less attention than direct impacts. Furthermore, attempts to grasp indirect damage through economic models have not gone below regional levels. Even though local communities can be devastated by flood events without this being reflected in regional accounts, few studies have been conducted from a microeconomic perspective at local level. What is more, the standard practices applied at this level of analysis tackle entities but ignore how they may be linked. This paper addresses these two challenges by building a novel agent-based model of a local agricultural production chain (a French cooperative wine-making system), utilized as a virtual laboratory for the ex ante estimation of flood impacts. We show how overlooking existing interactions between economic entities in production chains can result in either overestimation (double counting) or underestimation (wrong estimation of the consequences for the activity) of flood damage. Our results also reveal that considering interactions requires thorough characterization of their spatial configuration. Based on both the application of our method and the results obtained, we propose balanced recommendations for flood damage estimation at local level.

International audience ; Estimating flood damage, although crucial for assessing flood risk and for designing mitigation policies, continues to face numerous challenges, notably the assessment of indirect damage. It is widely accepted that damage other than direct damage can account for a significant proportion of total damage. Yet due to scarcer data sources and lack of knowledge on links within and between economic activities, indirect impacts have received less attention than direct impacts. Furthermore, attempts to grasp indirect damage through economic models have not gone below regional levels. Even though local communities can be devastated by flood events without this being reflected in regional accounts, few studies have been conducted from a microeconomic perspective at local level. What is more, the standard practices applied at this level of analysis tackle entities but ignore how they may be linked. This paper addresses these two challenges by building a novel agent-based model of a local agricultural production chain (a French cooperative wine-making system), utilized as a virtual laboratory for the ex ante estimation of flood impacts. We show how overlooking existing interactions between economic entities in production chains can result in either overestimation (double counting) or underestimation (wrong estimation of the consequences for the activity) of flood damage. Our results also reveal that considering interactions requires thorough characterization of their spatial configuration. Based on both the application of our method and the results obtained, we propose balanced recommendations for flood damage estimation at local level.

Changes in the optical properties of graphene quantum dots (GQD) during electrochemical reduction and oxidation were investigated by photoluminescence (PL) spectroelectrochemistry, which provided direct in situ evidence of the dependence of GQD luminescence on their redox state. We demonstrated that GQD PL intensity was enhanced upon reduction (quantum yield increased from 0.44 to 0.55) and substantially bleached during oxidation (quantum yield ∼0.12). Moreover, PL emission blue/red-shifted upon GQD reduction/oxidation, rendering information about electronic transitions involved in the redox processes, namely, the π → π* and the n → π* transitions between energy levels of the aromatic sp2 domains and the functional groups, respectively. PL intensity changes during GQD reduction/oxidation resulted from a variation in structural changes in GQD as a result of charge injection, as corroborated by in situ Raman spectroelectrochemistry. ; Ministerio de Economía y Competitividad (CTQ2014-55583-R, CTQ2014-61914-EXP, CTQ2015- 71955-REDT), Junta de Castilla y León (BU033-U16) and Basque Government under the ELKARTEK Program (ACTIMAT project, grant number KK-2015/00094 and KK-2016/ 00097)

El liderazgo democrático, en el transcurso del tiempo, ha evolucionado de manera radical, se ha tornado en el eje principal de influencia social, institucional e interpersonal, pues la mayoría de las empresas no pueden exceptuarse de un liderazgo con conducción democrática. Investigadores han tratado de acercarse a una conceptualización de liderazgo democrático que catalice toda experien- cia bajo este tipo de liderazgo. Generalmente, toda empresa no tiene ningún problema de adoptar este liderazgo en su sistema de administración, sin embargo, depende del líder, si el ritmo de trabajo se realiza bajo los principios que proporciona el liderazgo democrático. Investigaciones confirman que, entre los años 2000 al 2012, las empresas han ido cambiando su manera de trabajar, es decir, cambiaron su manera de liderar, requiriendo personal eficiente en su desempeño laboral, pues era lo que principalmente le importaba a la empresa. Sin embargo un nuevo escenario en el que se trabaja en equipo, conduce a las instituciones de manera positiva al cambio, promoviendo el incremento de ganancias basado en la calidad de los productos y servicios. Esta nueva forma de administrar tiene como sustento el trabajo en equipo que fue involucrando el concepto de liderazgo democrático. Pero al trabajar en equipo no es de pronto se requiere de experiencia traducido en paciencia y habilidad para obtener resultados esperados.

The lipid components of pathogen cell membranes have been considered as a poor pharmacological target, due to their universal distribution and apparent homogeneity throughout living organisms. Among the rare exceptions to this view one could mention polyene antibiotics such as amphotericin, or peptide antibiotics such as the polymyxins and the gramicidins. In the last two decades, however, the above notion has been challenged by two main lines of discovery; first, natural antimicrobial peptides (AMPs) that kill pathogens by interaction with phospholipids and membrane permeabilization, and secondly, cell-penetrating peptides (CPPs), capable of introducing into cells a variety of cargoes in the absence of specific receptors, again by interaction at some point with membrane phospholipids. For both AMPs and CPPs, the pharmacological proof-of-concept has been successfully demonstrated, and promising applications as nanobiotechnological tools have been envisaged though not hitherto materialized in clinical settings. In this review we briefly examine the pros and cons of these two classes of therapeutic agents, as well as strategies aimed at rationalizing and expanding their potentiality ; Work supported by the European Union (HEALTH-2007-223414, Leishdrug, to L.R. and D.A.), the Fondo de Investigaciones Sanitarias (PI061125, PS09/01928 and RETICS-FEDER RD 06/0021/0006 to L.R.), the regional governments of Madrid (S-BIO-0260/2006 to L.R) and Catalonia (2009 SGR 492 to D.A.), and the Spanish Ministry of Science and Innovation (PET2006-0139 to L.R. and D.A.).

Data de publicació electrònica: 28-02-2021 ; Proteolytic instability is a critical limitation for peptide-based products. Although significant efforts are devoted to stabilize sequences against proteases/peptidases in plasma/serum, such approaches tend to be rather empirical, unspecific, time-consuming, and frequently not cost-effective. A more rational and potentially rewarding alternative is to identify the chemical grounds of susceptibility to enzymatic degradation of peptides so that proteolytic resistance can be tuned by manipulation of key chemical properties. In this regard, we conducted a meta-analysis of literature published over the last decade reporting experimental data on the lifetimes of peptides exposed to proteolytic conditions. Our initial database contained 579 entries and was curated with regard to amino acid sequence, chemical modification, terminal half-life (t1/2 ) or other stability readouts, type of stability assay, and biological application of the study. Although the majority of entries in the database corresponded to (slightly or substantially) modified peptides, we chose to focus on unmodified ones, as we aimed to decipher intrinsic characteristics of peptide proteolytic susceptibility. Specifically, we developed a multivariable regression model to unravel those peptide properties with most impact on proteolytic stability and thus potential t1/2 predicting ability. Model validation was done by two different approaches. First, a library of peptides spanning a large interval of properties that modulate stability was synthesized and their t1/2 in human serum were experimentally determined. Second, the t1/2 of 21 selected peptides approved for clinical use or in clinical trials were recorded and matched with the model-estimated values. With both approaches, good correlation between experimental and predicted t1/2 data was observed. ; This research was supported by the Portuguese Fundação para a Ciência e a Tecnologia (FCT; grants PD/BD/128281/2017, PTDC/BBB‐NAN/1578/2014, PTDC/BIA‐VIR/29495/2017, UID/Multi/04349/2019, and PTDC/QUI‐NUC/30147/2017), the Spanish Ministry of Economy and Innovation (MINECO, grants AGL2014‐52395‐C2‐2‐R and AGL2017‐84097‐C2‐2‐R, and Maria de Maeztu Program for Centers of Excellence); the European Union H2020‐MSCA‐RISE‐2014 program (grant no. 828774), and the "La Caixa" Banking Foundation (grant HR17‐00409).

Background: Social withdrawal behaviour is a major health problem that is becoming increasingly important, being necessary studies that investigate its psychopathology and existence in different cultures. Aims: To describe the clinical and socio-demographic characteristics of hikikomori individuals in Spain. Method: Participants were 200 subjects referred to the Crisis Resolution Home Treatment (CRHT) because of social isolation. The definition of hikikomori was the state of avoiding social engagement with generally persistent withdrawal into one's residence for at least 6 months. Socio-demographic and clinical data were analysed, including Severity of Psychiatric Illness (SPI), Global Assessment of Functioning (GAF), Clinical Global Impression (CGI) and World Health Organization Disability Assessment (WHODAS) scales. Results: A total of 164 cases were evaluated. Hikikomori were predominantly young male, with the mean age at onset of hikikomori of 40 years old and a mean socially withdrawn period of 3 years. Only three people had no symptoms suggestive of mental disorder. Psychotic and anxiety were the most common comorbid disorders. The scales administered describe the presence of serious symptoms and impairment in social functioning, with a high prevalence of poor collaboration with treatment. Conclusion: This study shows the existence of hikikomori in Spain. Its difficult detection and treatment highlights the need for specialized domiciliary teams. The high comorbidity leads us to conclude that it may not be a new diagnosis, but rather a severe syndrome associated with multiple mental illnesses. Primary hikikomori also exist, but less commonly. Future cross-national studies are needed in order to describe its definition and psychopathology.