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Compacted Graphite Iron (CGI), is a unique casting material characterized by its graphite form and extensive matrix contact surface. This type of cast iron has a tendency towards direct ferritization and possesses a complex set of intriguing properties. The use of data mining methods in modern foundry material development facilitates the achievement of improved product quality parameters. When designing a new product, it is always necessary to have a comprehensive understanding of the influence of alloying elements on the microstructure and consequently on the properties of the analyzed material. Empirical studies allow for a qualitative assessment of the above-mentioned relationships, but it is the use of intelligent computational techniques that allows for the construction of an approximate model of the microstructure and, consequently, precise predictions. The formulated prognostic model supports technological decisions during the casting design phase and is considered as the first step in the selection of the appropriate material type.

En este artículo me propongo poner en diálogo al “riesgo ambiental”, como categoría ordenadora de las relocalizaciones en el marco de la política de saneamiento de la cuenca Matanza-Riachuelo, con las experiencias del habitar de los vecinos/as que vivían junto a los arroyos en el partido de Almirante Brown y que han sido recientemente relocalizados. En principio, las experiencias del habitar junto al arroyo coinciden con lo que la Autoridad de la Cuenca Matanza Riachuelo define como “riesgo ambiental”, a la vez que desbordan esta definición. La vida junto al arroyo involucra padecimiento y disfrute, el deseo de relocalizarse para no inundarse más y el reconocimiento de habitar un territorio autoproducido que se deja con tristeza. La información y los relatos que aquí presento surgen de un trabajo de campo que vengo desarrollando en dicho municipio desde el año 2019, que consiste en la observación participante en instancias de intervención territorial y en la realización de entrevistas.

Niniejszy artykuł omawia stan polskich badań nad kobietami wiejskimi z okresu od 1990 r. do dziś. Przedstawiono tu nie tylko tematykę publikowanych opracowań, ale także zwrócono uwagę na trendy metodologiczne w naukowych eksploracjach zagadnienia. Głównym celem pracy jest dostrzeżenie niedostatków i luk w literaturze przedmiotu oraz zaprezentowanie możliwych perspektyw i narzędzi badawczych, których wprowadzenie umożliwi dokładniejsze zbadanie zagadnienia codzienności kobiet ze wsi.

Hot deformation of metals is a widely used process to produce end products with the desired geometry and required mechanical properties. To properly design the hot forming process, it is necessary to examine how the tested material behaves during hot deformation. Model studies carried out to characterize the behaviour of materials in the hot deformation process can be roughly divided into physical and mathematical simulation techniques. The methodology proposed in this study highlights the possibility of creating rheological models for selected materials using methods of artificial intelligence, such as neuro-fuzzy systems. The main goal of the study is to examine the selected method of artificial intelligence to know how far it is possible to use this method in the development of a predictive model describing the flow of metals in the process of hot deformation. The test material was Inconel 718 alloy, which belongs to the family of austenitic nickel-based superalloys characterized by exceptionally high mechanical properties, physicochemical properties and creep resistance. This alloy is hardly deformable and requires proper understanding of the constitutive behaviour of the material under process conditions to directly enable the optimization of deformability and, indirectly, the development of effective shaping technologies that can guarantee obtaining products with the required microstructure and desired final mechanical properties. To be able to predict the behaviour of the material under non-experimentally tested conditions, a rheological model was developed using the selected method of artificial intelligence, i.e. the Adaptive Neuro-Fuzzy Inference System (ANFIS). The source data used in these studies comes from a material experiment involving compression of the tested alloy on a Gleeble 3800 thermo-mechanical simulator at temperatures of 900, 1000, 1050, 1100, 1150oC with the strain rates of 0.01 - 100 s-1 to a constant true strain value of 0.9. To assess the ability of the developed model to describe the behaviour of the examined alloy during hot deformation, the values of yield stress determined by the developed model (ANFIS) were compared with the results obtained experimentally. The obtained results may also support the numerical modelling of stress-strain curves.

Neurophysiological signal analysis is crucial for understanding the complex dynamics of brain function and its deviations in various pathological conditions. Traditional linear methods, while insightful, often fail to capture the full spectrum of inherently non-linear brain dynamics. This review explores the efficacy and applicability of the Higuchi fractal dimension (HFD) in interpreting neurophysiological signals such as scalp electroencephalography (EEG) and stereotactic intracranial encephalography (sEEG). We focus on three case studies: i) distinguishing between Alzheimer's disease (AD) and healthy controls; ii) classifying neurodynamics across diverse brain parcels looking for a signature of that cortical parcel; and iii) differentiating states of consciousness. Our study highlights the potential of non-linear analysis for deeper insights into brain dynamics and its potential for improving clinical diagnostics. [ABSTRACT FROM AUTHOR]

Abstract As the brain is a complex system with occurrence of self-similarity at different levels, a dedicated analysis of the complexity of brain signals is of interest to elucidate the functional role of various brain regions across the various stages of vigilance. We exploited intracranial electroencephalogram data from 38 cortical regions using the Higuchi fractal dimension (HFD) as measure to assess brain complexity, on a dataset of 1772 electrode locations. HFD values depended on sleep stage and topography. HFD increased with higher levels of vigilance, being highest during wakefulness in the frontal lobe. HFD did not change from wake to stage N2 in temporo-occipital regions. The transverse temporal gyrus was the only area in which the HFD did not differ between any two vigilance stages. Interestingly, HFD of wakefulness and stage R were different mainly in the precentral gyrus, possibly reflecting motor inhibition in stage R. The fusiform and parahippocampal gyri were the only areas showing no difference between wakefulness and N2. Stages R and N2 were similar only for the postcentral gyrus. Topographical analysis of brain complexity revealed that sleep stages are clearly differentiated in fronto-central brain regions, but that temporo-occipital regions sleep differently.

This study aims to develop a detection method based on morphological features of spike–wave (SW) patterns in the EEG of epilepsy patients and evaluate the effect of cathodal transcranial direct current stimulation (ctDCS) treatment. The proposed method is based on several simple features describing the shape of SW patterns and their synchronous occurrence on at least two EEG channels. High sensitivity, specificity and selectivity values were achieved for each patient and condition. ctDCS resulted in a significant reduction in the number of detected patterns, a decrease in spike duration and amplitude, and an increased spike mobility. The proposed method allows efficient identification of SW patterns regardless of brain condition, although the recruitment of patterns may be modified by ctDCS. This method can be useful in the clinical evaluation of ctDCS effects. [ABSTRACT FROM AUTHOR]

This article discusses the results of studies using the developed artificial neural networks in the analysis of the occurrence of the four main mechanisms destroying the selected forging tools subjected to five different surface treatment variants (nitrided layer, pad welded layer and three hybrid layers, i.e. AlCrTiSiN, Cr/CrN and Cr/AlCrTiN). Knowledge of the forging tool durability, needed in the process of artificial neural network training, was included in the set of training data (about 800 records) derived from long-term comprehensive research carried out under industrial conditions. Based on this set, neural networks with different architectures were developed and the results concerning the intensity of the occurrence of thermal-mechanical fatigue, abrasive wear, mechanical fatigue and plastic deformation were generated for each type of the applied treatment relative to the number of forgings, pressure, friction path and temperature.

En este artículo reflexiono sobre el riesgo ambiental como categoría oficial que fundamenta y orienta los procesos de relocalización de población de la cuenca Matanza-Riachuelo. Esta categoría, con sus singulares definiciones, ha sido utilizada para crear diversos indicadores, los que han permitido recolectar datos territoriales e incluso producir mapas oficiales. Pero el riesgo ambiental también es la categoría que, por excelencia, fundamenta a la intervención estatal en esta política pública. A su vez, también opera como una categoría nativa presente en el discurso de los actores de esta política pública, tanto en la voz de los decisores como en la de los habitantes de los arroyos. Me propongo, entonces, dar cuenta de esa multiplicidad de sentidos producidos en torno a la noción de riesgo ambiental en las trincheras de esta política pública, desde una perspectiva etnográfica.

This proof-of-concept (PoC) study presents a pipeline made by two blocks: 1. the identification of the network that generates interictal epileptic activity; and 2. the study of the time course of the electrical activity that it generates, called neurodynamics, and the study of its functional connectivity to the other parts of the brain. Network identification is achieved with the Functional Source Separation (FSS) algorithm applied to electroencephalographic (EEG) recordings, the neurodynamics quantified through signal complexity with the Higuchi Fractal Dimension (HFD), and functional connectivity with the Directed Transfer Function (DTF). This PoC is enhanced by the data collected before and after neuromodulation via transcranial Direct Current Stimulation (tDCS, both Real and Sham) in a single drug-resistant epileptic person. We observed that the signal complexity of the epileptogenic network, reduced in the pre-Real, pre-Sham, and post-Sham, reached the level of the rest of the brain post-Real tDCS. DTF changes post-Real tDCS were maintained after one month. The proposed approach can represent a valuable tool to enhance understanding of the relationship between brain neurodynamics characteristics, the effects of non-invasive brain stimulation, and epileptic symptoms.

En este artículo reflexiono sobre los conflictos que se suscitan en las relocalizaciones de la cuenca Matanza-Riachuelo. La categoría de conflicto –que ha sido ampliamente desarrollada en el campo de las ciencias sociales– opera, a su vez, como un término nativo utilizado, principalmente, por los decisores y ejecutores de esta política pública. Por un lado, esta categoría nativa hace referencia al “gran conflicto” inaugural de la causa: la problemática ambiental en Villa Inflamable. Por otro lado, es utilizada para realizar una distinción entre “territorios conflictivos” o “territorios ausentes de conflictos” con los que, en consecuencia, es posible articular (o no) las acciones de esta política. Presentaré los avances de un incipiente trabajo de campo de corte cualitativo en el municipio de Almirante Brown para dar cuenta de la multiplicidad de conflictos que transcurren en las trincheras de esta política pública.

AimThe objective of this work was to demonstrate the usefulness of a novel statistical method to study the impact of transcranial magnetic stimulation (TMS) on brain connectivity in patients with depression using different stimulation protocols, i.e., 1 Hz repetitive TMS over the right dorsolateral prefrontal cortex (DLPFC) (protocol G1), 10 Hz repetitive TMS over the left DLPFC (G2), and intermittent theta burst stimulation (iTBS) consisting of three 50 Hz burst bundle repeated at 5 Hz frequency (G3).MethodsElectroencephalography (EEG) connectivity analysis was performed using Directed Transfer Function (DTF) and a set of 21 indices based on graph theory. The statistical analysis of graph-theoretic indices consisted of a combination of the k-NN rule, the leave-one-out method, and a statistical test using a 2 × 2 contingency table.ResultsOur new statistical approach allowed for selection of the best set of graph-based indices derived from DTF, and for differentiation between conditions (i.e., before and after TMS) and between TMS protocols. The effects of TMS was found to differ based on frequency band.ConclusionA set of four brain asymmetry measures were particularly useful to study protocol- and frequency-dependent effects of TMS on brain connectivity.SignificanceThe new approach would allow for better evaluation of the therapeutic effects of TMS and choice of the most appropriate stimulation protocol.