Residential socio-economic segregation in Costa Rica had an overall decreasing trend between 1973 and 2011 because of a sustained reduction in the amount of lower income households. However, in 1986, ...the national housing program was reformed, including a ten-fold increase in housing supply (292 thousand subsidies allocated in 1987-2011, in a country with 1.36 million housing units). The pattern of these subsidies was hypothesized to increase residential segregation in Costa Rica. Segregation indices were estimated per municipality for lower and higher income groups. The impact of social housing subsidies on segregation levels was quantified using a fixed effects model with standard errors corrected for spatial dependence. Social housing supply was found to have historically reduced residential segregation; however, the 1986 reforms created a system that followed the patterns of real estate markets, in turn reducing much of the system’s mitigation effect on residential segregation.
One should expect real estate sales, and properties listed as for sale, to be concentrated on market hotspots. Using data of real estate listings from San José, Costa Rica, this expected clustering ...is examined using point pattern processes of detached housing, apartments, and vacant lots. Non-stationary G and J functions describe the patterns and their interactions. Potential determinants of the point pattern were selected based on previous studies and theory. Their effect on the point pattern was estimated using an inhomogeneous Poisson model, with its intensity a lognormal function of the determinants. Results show detached houses, apartments, and lots are all clustered point patterns. The cross density (joint G function) of houses with apartments and with lots exhibits clustering, suggesting the patterns are related; however, the cross density of apartments and lots is no different from a Poisson distribution (they are not related). The inhomogeneous Poisson model with Euclidean distance to the central business district (CBD), nearest municipal center, and nearest main road, as well as elevation and slope, proved better than homogeneous Poisson models in explaining the point patterns of houses, apartments, and lots.
The fact that patents are documents highly constrained by law and structured by international treaties make them a unique body of publications for tracing the history and evolution of technology. The ...distinctiveness of prior art patent citations compared to bibliographic references in the nonpatent literature is discussed. Starting from these observations and using the patent classification scheme as a framework of reference, we have identified a data structure, the “technology footprint,” derived from the patents cited as prior art for a selected set of patents. This data structure will provide us with dynamic information about the technological components of the selected set of patents, which represents a technology, company, or inventor. Two case studies are presented in order to illustrate the visualization of the technology footprint: one concerning an inventor—Mr. Engelbart, the inventor of the “computer mouse”—and another concerning the early years of a technology—computerized tomography.
This paper scrutinizes the act of patent classification as it is performed by specialists, namely patent examiners, and currently supported by automated systems in patent offices for assigning ...classification codes to patent application documents. It collectively discusses aspects of the patent classification operation, some of them not very visible, which are not commonly encountered in other document and text classification tasks. The advent of Deep Learning (DL) and, especially, Large Language Models (LLMs) offer a new perspective on the development of automated systems addressing these inherent aspects of patent classification. Towards this direction, the paper analyses how these technologies can address the patent classification problems and concludes with a discussion of potential challenges and benefits that the application of Artificial Intelligence (AI) technologies may bring to the task of patent classification.
In the central nervous system, oligodendrocytes synthesize the myelin, a specialized membrane to wrap axons in a discontinuous way allowing a rapid saltatory nerve impulse conduction. ...Oligodendrocytes express a number of growth factors and neurotransmitters receptors that allow them to sense the environment and interact with neurons and other glial cells. Depending on the cell cycle stage, oligodendrocytes may respond to these signals by regulating their survival, proliferation, migration, and differentiation. Among these signals are the endocannabinoids, lipidic molecules synthesized from phospholipids in the plasma membrane in response to cell activation. Here, we discuss the evidence showing that oligodendrocytes express a full endocannabinoid signaling machinery involved in physiological oligodendrocyte functions that can be therapeutically exploited to promote remyelination in central nervous system pathologies.
Main Points
In oligodendroglial cells there is an operational endocannabinoid signaling network.
2‐AG contributes to the proliferation, directional migration and maturation of OPCs.
Manipulation of the endocannabinoid system exert beneficial therapeutic effects.
A multilevel model of the housing market for San José Metropolitan Region (Costa Rica) was developed, including spatial effects. The model is used to explore two main questions: the extent to which ...contextual (of the surroundings) and compositional (of the property itself) effects explain variation of housing prices and how does the relation between price and key covariates change with the introduction of multilevel effects. Hierarchical relations (lower level units nested into higher level) were modeled by specifying multilevel models with random intercepts and a conditional autoregressive term to include spatial effects from neighboring units at the higher level (districts). The random intercepts and conditional autoregressive models presented the best fit to the data. Variation at the higher level accounted for 16% of variance in the random intercepts model and 28% in the conditional autoregressive model. The sign and magnitude of regression coefficients proved remarkably stable across model specifications. Travel time to the city center, which presented a non-linear relation to price, was found to be the most important determinant. Multilevel and conditional autoregressive models constituted important improvements in modeling housing price, despite most of the variation still occurring at the lower level, by improving the overall model fit. They were capable of representing the regional structure and of reducing sampling bias in the data. However, the conditional autoregressive specification only represented a limited advance over the random intercepts formulation.
For years, there have been studies based on the use of natural compounds plant-derived as potential therapeutic agents for various diseases in humans. Curcumin is a phenolic compound extracted from ...Curcuma longa rhizome commonly used in Asia as a spice, pigment and additive. In traditional medicine of India and China, curcumin is considered as a therapeutic agent used in several foods. Numerous studies have shown that curcumin has broad biological functions particularly antioxidant and antiinflammatory. In fact, it has been established that curcumin is a bifunctional antioxidant; it exerts antioxidant activity in a direct and an indirect way by scavenging reactive oxygen species and inducing an antioxidant response, respectively. The renoprotective effect of curcumin has been evaluated in several experimental models including diabetic nephropathy, chronic renal failure, ischemia and reperfusion and nephrotoxicity induced by compounds such as gentamicin, adriamycin, chloroquine, iron nitrilotriacetate, sodium fluoride, hexavalent chromium and cisplatin. It has been shown recently in a model of chronic renal failure that curcumin exerts a therapeutic effect; in fact it reverts not only systemic alterations but also glomerular hemodynamic changes. Another recent finding shows that the renoprotective effect of curcumin is associated to preservation of function and redox balance of mitochondria. Taking together, these studies attribute the protective effect of curcumin in the kidney to the induction of the master regulator of antioxidant response nuclear factor erythroid-derived 2 (Nrf2), inhibition of mitochondrial dysfunction, attenuation of inflammatory response, preservation of antioxidant enzymes and prevention of oxidative stress. The information presented in this paper identifies curcumin as a promising renoprotective molecule against renal injury.
Urban growth may intensify local flooding problems. Understanding the spatially explicit flood consequences of possible future land cover patterns contributes to inform policy for mitigating these ...impacts. A cellular automata model has been coupled with the openLISEM integrated flood modeling tool to simulate scenarios of urban growth and their consequent flood; the urban growth model makes use of a continuous response variable (the percentage of built-up area) and a spatially explicit simulation of supply for urban development. The models were calibrated for Upper Lubigi (Kampala, Uganda), a sub-catchment that experienced rapid urban growth during 2004–2010; this data scarce environment was chosen in part to test the model's performance with data inputs that introduced important uncertainty. The cellular automata model was validated in Nalukolongo (Kampala, Uganda). The calibrated modeling ensemble was then used to simulate urban growth scenarios of Upper Lubigi for 2020. Two scenarios, trend conditions and a policy of strict protection of existing wetlands, were simulated. The results of simulated scenarios for Upper Lubigi show how a policy of only protecting wetlands is ineffective; further, a substantial increase of flood impacts, attributable to urban growth, should be expected by 2020. The coupled models are operational with regard to the simulation of dynamic feedbacks between flood and suitability for urban growth. The tool proved useful in generating meaningful scenarios of land cover change and comparing their policy drivers as flood mitigation measures in a data scarce environment.
•We coupled cellular automata and flood models to simulate the impact of urban growth.•The tool generates scenarios to study drivers of growth as flood mitigation measures.•The urban growth model features a continuous response variable.•Calibration/validation was done in two similar catchments, to overcome lack of data.
Lentiviral vectors (LVs) have gained value over recent years as gene carriers in gene therapy. These viral vectors are safer than what was previously being used for gene transfer and are capable of ...infecting both dividing and nondividing cells with a long-term expression. This characteristic makes LVs ideal for clinical research, as has been demonstrated with the approval of lentivirus-based gene therapies from the Food and Drug Administration and the European Agency for Medicine. A large number of functional lentiviral particles are required for clinical trials, and large-scale production has been challenging. Therefore, efforts are focused on solving the drawbacks associated with the production and purification of LVsunder current good manufacturing practice. In recent years, we have witnessed the development and optimization of new protocols, packaging cell lines, and culture devices that are very close to reaching the target production level. Here, we review the most recent, efficient, and promising methods for the clinical-scale production ofLVs.
We analyze class structures in Latin America from a sociological perspective, defining social classes as labor market positions. We propose an adaptation of the Erikson-Goldthorpe-Portocarero (EGP) ...class schema, which has become a standard in advanced industrialized countries but presents some limitations in accounting for labor relations in Latin America. Then, we use recent survey data for nine Latin American countries to delineate a map of current class structures and explore the association between social class and social/economic conditions. Our results indicate that class structures differ significantly not only between Latin America and advanced industrialized nations but also among Latin American countries. There is also a close association between class membership and socioeconomic conditions, including social protection and the risk of poverty. These results suggest that a sociological approach to social class is still pertinent to understanding the relationships among productive structures, labor markets, and living conditions in Latin America.
En este trabajo analizamos las estructuras de clase en América Latina (AL) desde una perspectiva sociológica, que define las clases sociales como posiciones en el mercado de trabajo. Proponemos adaptar el esquema de Erikson-Goldthorpe-Portocarero (EGP), que es de uso generalizado en países de industrialización temprana, pero tiene algunas limitaciones para dar cuenta de las relaciones de trabajo en AL. Luego, usamos datos recientes de encuestas de nueve países de AL para delinear un mapa de las estructuras de clase y explorar la asociación entre la pertenencia de clase y las condiciones sociales y económicas. Nuestros resultados indican que las estructuras de clase no sólo difieren significativamente entre AL y los países de industrialización temprana, sino también entre países latinoamericanos. Existe además una asociación estrecha entre la pertenencia de clase y las condiciones sociales y económicas, entre ellas la protección social y el riesgo de pobreza. Esto sugiere que una mirada sociológica a las clases sociales es todavía pertinente para entender las relaciones entre las estructuras productivas, los mercados de trabajo y las condiciones de vida en AL.
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