Machine learning approach to investigate EV battery characteristics

The main factor influencing an electric vehicle’s range is its battery. Battery electric vehicles experience driving range reduction in low temperatures. This range reduction results from the heating demand for the cabin and recuperation limits by the braking system. Due to the lack of an internal combustion engine-style heat source, electric vehicles\u27 heating system demands a significant amount of energy. This energy is supplied by the battery and results in driving range reduction. Moreover, Due to the battery\u27s low temperature in cold weather, the charging process through recuperation is limited. This limitation of recuperation is caused by the low reaction rate in low temperatures. Technology developments for battery electric vehicles are mostly focused on maintaining the vehicle battery package temperature and state of charge. For battery management systems, state of charge and battery temperature estimations are important since they prevent over charge, over discharge, and thermal runaway. Estimation and controlling battery temperature and the state of charge guarantees safety, it will also increase the vehicle\u27s life cycle. This study analyzes the effects of ambient and battery temperature on heating system energy demand and regenerative braking parameters. Moreover, different machine learning methods for estimating the battery temperature and its state of charge are compared and presented. The analysis is based on the BMW i3 winter trips dataset which includes data for 38 different drive cycles. Results show that every 3 degrees of ambient temperature drop results in a 1% increase in the heating energy share. Furthermore, the ability of machine learning methods such as LSTM and GRU has been demonstrated to successfully forecast battery temperature and state of charge

The Role of Traumatic Experiences and Cognitive Emotion Regulation Strategies in Predicting High-risk Behaviors among Adolescents

Introduction: The goal of the present study was to investigate adolescents’ tendency to engage in high-risk behaviors based on traumatic life experiences and adaptive and maladaptive emotion regulation strategies. Method: A descriptive/correlational design was used. The participants included 220 adolescents (154 girls and 66 boys) who were selected among high-school students in Shiraz, using a convenience sampling method. The Traumatic Experiences Checklist (TEC), the Iranian Adolescents Risk-taking Scale (IARS), and the Cognitive Emotion Regulation Strategies Questionnaire (CERQ) were used collect data. The data were analyzed using descriptive statistics, Pearson correlation coefficient, and regression analysis. Results: According to the results, among traumatic experiences, only emotional abuse (P<0. 001), and among maladaptive cognitive emotion regulation strategies, only rumination (P<0. 001) had a significant effect on high-risk behaviors. In addition, no significant relationship was found between adaptive cognitive emotion regulation strategies and tendency to engage in high-risk behaviors. Conclusion: The results suggest that providing training on emotion regulation can help students select adaptive emotion regulation strategies in coping with high-risk situations. Declaration of Interest: None.

Industrial Park Role as a Catalyst for Regional Development: Zooming on Middle East Countries

The development of the industrial park has been one of the priorities of the plans of different countries and has created a magnitude challenge concerning regional disparities. Globally, the Middle Eastern countries have demonstrated a more remarkable dedication to industrial park development, given its general importance since the 1970s. Due to this importance, this paper is divided into three sections due to the critical role of industrial park development in the case of Middle Eastern countries. First, this study highlighted the relevant literature using Scinotometric analysis. In the second step, following the investigation of the relationship between selected critical variables and the development of industrial parks towards regional development in the Middle Eastern countries from 2000 to 2018. In this regard, panel data were used to determine the association between the selected variables and industrial park performance. According to the findings, the author suggests policy implementation for industrial park development in three categories: economic growth, environmental issues, and reduction in regional disparities. Finally, this study can serve as a foundation for future research, such as comparing the first batch of industrial parks with their upgraded counterparts in the Middle East and studying the competitive advantages issues

Near-infrared excitation of nitrogen-doped ultrananocrystalline diamond photoelectrodes in saline solution

Nitrogen-doped ultrananocrystalline diamond (N-UNCD) is a promising material for a variety of neural interfacing applications, due to its unique combination of high conductivity, bioinertness, and durability. One emerging application for N-UNCD is as a photoelectrode material for high-precision optical neural stimulation. This may be used for the treatment of neurological disorders and for implantable bionic devices such as cochlear ear implants and retinal prostheses. N-UNCD is a well-suited material for stimulation photoelectrodes, exhibiting a photocurrent response to light at visible wavelengths with a high charge injection density [A. Ahnood, A. N. Simonov, J. S. Laird, M. I. Maturana, K. Ganesan, A. Stacey, M. R. Ibbotson, L. Spiccia, and S. Prawer, Appl. Phys. Lett. 108, 104,103 (2016)]. In this study, the photoresponse of N-UNCD to near-infrared (NIR) irradiation is measured. NIR light has greater optical penetration through tissue than visible wavelengths, opening the possibility to stimulate previously inaccessible target cells. It is found that N-UNCD exhibits a photoresponsivity which diminishes rapidly with increasing wavelength and is attributed to transitions between mid-gap states associated with the graphitic phase present at the grain boundaries and the conduction band tail. Oxygen surface termination on the diamond films provides further enhancement of the injected charge per photon, compared to as-grown or hydrogen terminated surfaces. Based on the measured injected charge density, we estimate that the generated photocurrent of oxygen terminated N-UNCD is sufficient to achieve extracellular stimulation of brain tissue within the safe optical exposure limit

Hybrid diamond/ carbon fiber microelectrodes enable multimodal electrical/chemical neural interfacing

Implantable medical devices are now in regular use to treat or ameliorate medical conditions, including movement disorders, chronic pain, cardiac arrhythmias, and hearing or vision loss. Aside from offering alternatives to pharmaceuticals, one major advantage of device therapy is the potential to monitor treatment efficacy, disease progression, and perhaps begin to uncover elusive mechanisms of diseases pathology. In an ideal system, neural stimulation, neural recording, and electrochemical sensing would be conducted by the same electrode in the same anatomical region. Carbon fiber (CF) microelectrodes are the appropriate size to achieve this goal and have shown excellent performance, in vivo. Their electrochemical properties, however, are not suitable for neural stimulation and electrochemical sensing. Here, we present a method to deposit high surface area conducting diamond on CF microelectrodes. This unique hybrid microelectrode is capable of recording single-neuron action potentials, delivering effective electrical stimulation pulses, and exhibits excellent electrochemical dopamine detection. Such electrodes are needed for the next generation of miniaturized, closed-loop implants that can self-tune therapies by monitoring both electrophysiological and biochemical biomarkers