Future brain–computer interfaces will require local and highly individualized signal processing of fully integrated electronic circuits within the nervous system and other living tissue. New devices will need to be developed that can receive data from a sensor array, process these data into meaningful information, and translate that information into a format that can be interpreted by living systems. Here, the first example of interfacing a hardware‐based pattern classifier with a biological nerve is reported. The classifier implements the Widrow–Hoff learning algorithm on an array of evolvable organic electrochemical transistors (EOECTs). The EOECTs’ channel conductance is modulated in situ by electropolymerizing the semiconductor material within the channel, allowing for low voltage operation, high reproducibility, and an improvement in state retention by two orders of magnitude over state‐of‐the‐art OECT devices. The organic classifier is interfaced with a biological nerve using an organic electrochemical spiking neuron to translate the classifier's output to a simulated action potential. The latter is then used to stimulate muscle contraction selectively based on the input pattern, thus paving the way for the development of adaptive neural interfaces for closed‐loop therapeutic systems.

Background The rapid outbreak of COVID‐19 at the beginning of 2020 in the world has put severe physical and psychological pressure on the medical staff of hospitals involved in the care of patients with COVID‐19 to the point of risk of PTSD. There was. The aim of this study was to investigate the relationship between the prevalence of COVID‐19 and nurses' anxiety disorder. Methods This review study was conducted by library method. Results As is well known and mentioned everywhere in cyberspace, nurses have lost their mental health and become very anxious during the COVID‐19. Serious spread of traumatic psychiatric symptoms in the current situation can lead to damage to the health system. Conclusions The need to care for nurses to relieve fatigue for several months and inject hope and motivation into this group should be understood, But due to the economic situation of the country, unfortunately, the fulfillment of the promises has been delayed, which we hope will be fulfilled soon; Although the delay will certainly not prevent nurses from properly caring for patients, but resolving nurses ‘livelihood problems should also be a priority on the authorities’ agenda.

Introduction: The aim of this study was the effectiveness of positive psychology skills training on increasing the life expectancy of addicts referred to addiction treatment centers in Tehran. Methods: The research method was quasiexperimental with pretest, post-test, and follow-up design with a control group. In this study, 60 addicts were selected who were randomly assigned to experimental (n=30) and control (n=30) groups. Group therapy sessions consisted of 10 sessions, twice a week for 90 minutes each time. The research tool was Snyder Hope Questionnaire. Analysis of variance with repeated measures was used to analyze the data. Results: The results showed that there was a statistically significant difference in the mean score of hope in the experimental and control groups (P<0.001). The results showed that teaching positive psychology skills as a group can significantly increase hope in addicts. Conclusions: Therefore, positive psychology with a strong theoretical and research background is an appropriate strategy to increase life expectancy and can be used as an effective intervention method to increase life expectancy in addicts.