Estado, étnias y espacio urbano. La Habana 1878

En una reciente comunicación presentada en la Universidad de Río Piedras, Puerto Ric01, realizábamos una aproximación al problema étnico y social cubano desde una perspectiva espacial. Nuestra hipótesis era la de que fue en la década de los cuarenta, del siglo XIX, cuando tomó cuerpo en la Isla de Cuba una segregación espacial fundameintal. Por una parte la ciudad de La Habana, sede del poder político y comercial; de c)tra, el resto del territorio principalmente los campos de caña y las vegas tabaqueras. Esta dualidad espacial se manifestó de una forma muy evidente: La Habana era'la ciudad de los blancos. Si hasta la década de los cuarenta el proletariado de la c:apital era el hombre de color, esclavo o liberto, con posterioridad a dicha década la situación iba a invertirse; no nos caben muchas dudas acerca de este hecho. En primer lugar la mayor parte de las referencias, con anterioridad a 1846, nos ponel1 de manifiesto la existencia de ese proletariado de color. Baste recordar a este res'pecto el famoso ensayo de José Antonio Saco sobre la vagancia en la Isla de Cuba, 'en el cual atribuía a la sociedad esclavista rechazar el ejercicio de cualquier oficio dejando todas las artes e industrias en manos de los negros

Topography and self-gravitation interaction in elastic-gravitational modeling

Changes in gravity due to volcanic loading of the crust are influenced by topography. We investigate the relative importance of topography and self-gravitation in the interpretation of gravity changes. It is shown that modeling of gravity changes can be more precise with the introduction of topographic relief, although it is neglected self-gravitation of the medium. This paper exploits this result by suggesting a mathematical simplification that could be useful in the future development of a numerical technique to accurately include topographic effects in the modeling of deformation and gravity changes. Finally, we perform an inversion of the gravity changes observed at Mayon volcano (Philippines) between December 1992 and December 1996 including topographic effects by varying the depth of the source. Failure to account for topographic influences can bias estimates of source parameters particularly when the lateral extension of the relief is of the same order of magnitude as the source depth.Peer reviewe

Can we infer the presence of Differential Privacy in Deep Learning models' weights? Towards more secure Deep Learning

Differential Privacy (DP) is a key property to protect data and models from integrity attacks. In the Deep Learning (DL) field, it is commonly implemented through the Differentially Private Stochastic Gradient Descent (DP-SGD). However, when a model is shared or released, there is no way to check whether it is differentially private, that is, it required to trust the model provider. This situation poses a problem when data privacy is mandatory, specially with current data regulations, as the presence of DP can not be certificated consistently by any third party. Thus, we face the challenge of determining whether a DL model has been trained with DP, according to the title question: Can we infer the presence of Differential Privacy in Deep Learning models' weights? Since the DP-SGD significantly changes the training process of a DL model, we hypothesize that DP leaves an imprint in the weights of a DL model, which can be used to predict whether a model has been trained with DP regardless of its architecture and the training dataset. In this paper, we propose to employ the imprint in model weights of using DP to infer the presence of DP training in a DL model. To substantiate our hypothesis, we developed an experimental methodology based on two datasets of weights of DL models, each with models with and without DP training and a meta-classifier to infer whether DP was used in the training process of a DL model, by accessing its weights. We accomplish both, the removal of the requirement of a trusted model provider and a strong foundation for this interesting line of research. Thus, our contribution is an additional layer of security on top of the strict private requirements of DP training in DL models, towards to DL models

Structure of Alluvial Valleys from 3-D Gravity Inversion: The Low Andarax Valley (Almería, Spain) Test Case

This paper presents a gravimetric study (based on 382 gravimetric stations in an area about 32 km2) of a nearly flat basin: the Low Andarax valley. This alluvial basin, close to its river mouth, is located in the extreme south of the province of Almería and coincides with one of the existing depressions in the Betic Cordillera. The paper presents new methodological work to adapt a published inversion approach (GROWTH method) to the case of an alluvial valley (sedimentary stratification, with density increase downward). The adjusted 3D density model reveals several features in the topography of the discontinuity layers between the calcareous basement (2,700 kg/m3) and two sedimentary layers (2,400 and 2,250 kg/m3). We interpret several low density alignments as corresponding to SE faults striking about N140?145°E. Some detected basement elevations (such as the one, previously known by boreholes, in Viator village) are apparently connected with the fault pattern. The outcomes of this work are: (1) new gravimetric data, (2) new methodological options, and (3) the resulting structural conclusions

Synthesis and Characterization of Environmentally Friendly Chitosan–Arabic Gum Nanoparticles for Encapsulation of Oregano Essential Oil in Pickering Emulsion

The encapsulation of bioactive agents through the utilization of biodegradable nanoparticles is a topic of considerable scientific interest. In this study, microcapsules composed of chitosan (CS) and Arabic gum (GA) nanoparticles were synthesized, encapsulating oregano essential oil (OEO) through Pickering emulsions and subsequent spray drying. The optimization of hybrid chitosan and Arabic gum (CS–GA) nanoparticle formation was carried out via complex coacervation, followed by an assessment of their behavior during the formation of the emulsion. Measurements of the size, contact angle, and interfacial tension of the formed complexes were conducted to facilitate the development of Pickering emulsions for encapsulating the oil under the most favorable conditions. The chitosan–Arabic gum capsules were physically characterized using scanning electron microscopy and fitted to the Beerkan estimation of soil transfer (BEST) model to determine their size distribution. Finally, the OEO encapsulation efficiency was also determined. The optimum scenario was achieved with the CS–GA 1–2 capsules at a concentration of 2% wt, featuring a contact angle of 89.1 degrees, which is ideal for the formation of oil/water (O/W) emulsions. Capsules of approximately 2.5 m were obtained, accompanied by an encapsulation efficiency of approximately 60%. In addition, the hybrid nanoparticles that were obtained showed high biodegradability. The data within our study will contribute fundamental insights into CS–GA nanoparticles, and the quantitatively analyzed outcomes presented in this study will hold utility for forthcoming applications in environmentallySpanish Ministry of Science, grant number FPU17-0335

Dynamic Defense Against Byzantine Poisoning Attacks in Federated Learning

Federated learning, as a distributed learning that conducts the training on the local devices without accessing to the training data, is vulnerable to Byzatine poisoning adversarial attacks. We argue that the federated learning model has to avoid those kind of adversarial attacks through filtering out the adversarial clients by means of the federated aggregation operator. We propose a dynamic federated aggregation operator that dynamically discards those adversarial clients and allows to prevent the corruption of the global learning model. We assess it as a defense against adversarial attacks deploying a deep learning classification model in a federated learning setting on the Fed-EMNIST Digits, Fashion MNIST and CIFAR-10 image datasets. The results show that the dynamic selection of the clients to aggregate enhances the performance of the global learning model and discards the adversarial and poor (with low quality models) clients.R&D&I grants - MCIN/AEI, Spain PID-2020-119478GB-I00 PID2020-116118GA-I00 EQC2018-005-084-PERDF A way of making EuropeMCIN/AEI FPU18/04475 IJC2018-036092-

The inversion of spectral ratio H/V in a layered system using the Diffuse Field Assumption (DFA)

In order to evaluate the site effects on seismic ground motion and establish preventive measures to mitigate these effects, the dynamic characterization of sites is mandatory. Among the various geophysical tools aimed to this end, the horizontal to vertical spectral ratio (H/V) is a simple way to assess the dominant frequency of a site from seismic ambient noise. The aim of this communication is contributing to enhance the potential of this measurement with a novel method that allows extracting from the H/V the elastic properties of the subsoil, assumed here as a multilayer medium. For that purpose, we adopt the Diffuse Field Assumption from both the experimental and the modeling perspectives. At the experimental end, the idea is to define general criteria that make the data processing closely supported by theory. On the modeling front, the challenge is to compute efficiently the imaginary part of Green’s function. The Cauchy’s residue theory in the horizontal wavenumber complex plane is the selected approach. This method allows both identifying the contributions of body and surface waves and computing them separately. This permits exploring the theoretical properties of the H/V under different compositions of the seismic ambient noise. This answers some questions that historically aroused and gives new insights into the H/V method. The efficient forward calculation is the prime ingredient of an inversion scheme based on both gradient and heuristic searches. The availability of efficient forward calculation of H/V allows exploring some relevant relationships between the H/V curves and the parameters. This allows generating useful criteria to speed up inversion. As in many inverse problems, the non-uniqueness issues also emerge here. A joint inversion method that considers also the dispersion curves of surface waves extracted from seismic ambient noise is presented and applied to experimental data. This joint scheme mitigates effectively the non-uniqueness