Nonlinear digital signal processing in mental health: characterization of major depression using instantaneous entropy measures of heartbeat dynamics

Nonlinear digital signal processing methods that address system complexity have provided useful computational tools for helping in the diagnosis and treatment of a wide range of pathologies. More specifically, nonlinear measures have been successful in characterizing patients with mental disorders such as Major Depression (MD). In this study, we propose the use of instantaneous measures of entropy, namely the inhomogeneous point-process approximate entropy (ipApEn) and the inhomogeneous point-process sample entropy (ipSampEn), to describe a novel characterization of MD patients undergoing affective elicitation. Because these measures are built within a nonlinear point-process model, they allow for the assessment of complexity in cardiovascular dynamics at each moment in time. Heartbeat dynamics were characterized from 48 healthy controls and 48 patients with MD while emotionally elicited through either neutral or arousing audiovisual stimuli. Experimental results coming from the arousing tasks show that ipApEn measures are able to instantaneously track heartbeat complexity as well as discern between healthy subjects and MD patients. Conversely, standard heart rate variability (HRV) analysis performed in both time and frequency domains did not show any statistical significance. We conclude that measures of entropy based on nonlinear point-process models might contribute to devising useful computational tools for care in mental health

Effects of calcium-treatment of a plastic injection mold steel on the tool wear and power consumption in slot milling

Dies and molds steels are essential materials in the manufacturing industry of engineering products. These materials are usually machined in the hardened condition and therefore, can be problematic to transform them in chips. Calcium treatment can be a viable alternative to increase machinability without compromising the main properties of the steel. The present work investigates the machinability of the calcium treated mold steel, AISI P20 UF, and compares it to the non-treated version of the same material, AISI P20, in slot milling tests with triple coated (TiN, TiCN and Al2O3) cemented carbide tools. A consolidated method that minimizes the number of tests needed for the determination of the extended Taylor's equation coefficients was used and the power consumption was measured during the machining experiments. SEM was used for the exploration of the wear of the used tool and its mechanism. The results showed that the calcium treated steel presented a considerably higher tool life, and although the treatment did not affect the power consumption directly, indirectly it reduced it because of the positive reduction of the tool wear rate allowing the power to be kept at lower levels for more extended periods. Attrition (adhesion) and abrasion were the primary tool wear mechanisms observed when machining the non-treated steel and attrition for the calcium treated material. In this latter case, because of the longer tool lives, chippings of the cutting edge were also present