Modulation of polyaniline memristive device switching voltage by nucleotide-free analogue of vitamin B12.

Memristive devices offer essential properties to become a part of the next-generation computing systems based on neuromorphic principles. Organic memristive devices exhibit a unique set of properties which makes them an indispensable choice for specific applications, such as interfacing with biological systems. While the switching rate of organic devices can be easily adjusted over a wide range through various methods, controlling the switching potential is often more challenging, as this parameter is intricately tied to the materials used. Given the limited options in the selection conductive polymers and the complexity of polymer chemical engineering, the most straightforward and accessible approach to modulate switching potentials is by introducing specific molecules into the electrolyte solution. In our study, we show polyaniline (PANI)-based device switching potential control by adding nucleotide-free analogue of vitamin B12, aquacyanocobinamide, to the electrolyte solution. The employed concentrations of this molecule, ranging from 0.2 to 2 mM, enabled organic memristive devices to achieve switching potential decrease for up to 100 mV, thus providing a way to control device properties. This effect is attributed to strong aromatic interactions between PANI phenyl groups and corrin macrocycle of the aquacyanocobinamide molecule, which was supported by ultraviolet-visible spectra analysis.

Theoretical and Experimental Studies of the Shock-Compressed Gas Parameters in the Welding Gap.

This work is devoted to the study of the processes that take place in the welding gap during explosive welding (EW). In the welding gap, when plates collide, a shock-compressed gas (SCG) region is formed, which moves at supersonic speed and has a high temperature that can affect the quality of the weld joint. Therefore, this work focuses on a detailed study of the parameters of the SCG. A complex method of determining the SCG parameters included: determination of the detonation velocity using electrical contact probes, ceramic probes, and an oscilloscope; calculation of the SCG parameters; high-speed photography of the SCG region; measurement of the SCG temperature using optical pyrometry. As a result, it was found that the head front of the SCG region moved ahead of the collision point at a velocity of 3000 ± 100 m/s, while the collision point moved with a velocity of 2500 m/s. The calculation of the SCG temperature showed that the gas was heated up to 2832 K by the shock compression, while the measured temperature was in the range of 4100-4400 K. This is presumably due to the fact that small metal particles that broke off from the welded surfaces transferred their heat to the SCG region. Thus, the results of this study can be used to optimize the EW parameters and improve the weld joint quality.

Adapted MLP-Mixer network based on crossbar arrays of fast and multilevel switching (Co-Fe-B)x(LiNbO3)100-x nanocomposite memristors.

MLP-Mixer based on multilayer perceptrons (MLPs) is a novel architecture of a neuromorphic computing system (NCS) introduced for image classification tasks without convolutional layers. Its software realization demonstrates high classification accuracy, although the number of trainable weights is relatively low. One more promising way of improving the NCS performance, especially in terms of power consumption, is its hardware realization using memristors. Therefore, in this work, we proposed an NCS with an adapted MLP-Mixer architecture and memristive weights. For this purpose, we used a passive crossbar array of (Co-Fe-B)x(LiNbO3)100-x memristors. Firstly, we studied the characteristics of such memristors, including their minimal resistive switching time, which was extrapolated to be in the picosecond range. Secondly, we created a fully hardware NCS with memristive weights that are capable of classification of simple 4-bit vectors. The system was shown to be robust to noise introduction in the input patterns. Finally, we used experimental memristive characteristics to simulate an adapted MLP-Mixer architecture that demonstrated a classification accuracy of (94.7 ± 0.3)% on the Modified National Institute of Standards and Technology (MNIST) dataset. The obtained results are the first steps toward the realization of memristive NCS with a promising MLP-Mixer architecture.

Reliable Memristive Synapses Based on Parylene-MoOx Nanocomposites for Neuromorphic Applications.

Memristive devices, known for their nonvolatile resistive switching, are promising components for next-generation neuromorphic computing systems, which mimic the brain's neural architecture. Specifically, these devices are well-suited for functioning as artificial synapses due to their analogue tunability and low energy consumption. However, the improvement of their performance and reliability remains a pressing challenge. In this study, we report the development and comprehensive characterization of memristive devices based on a parylene-MoOx (PPX-Mo) nanocomposite layer, which exhibit improved characteristics over their parylene-based counterparts: lower switching voltage and energy, smaller dispersion, and better resistive plasticity. A robust statistical analysis identified the optimal synthesis parameters for these devices, providing valuable insights for future device optimization. The most probable resistive switching mechanism of the devices is proposed. By successfully integrating these memristors into a neuromorphic computing model and showcasing their scalability in crossbar geometry, we demonstrate their potential as functional artificial synapses. The results obtained from this study can be useful for the development of hardware-brain-inspired computational systems.

Multi-Terminal Nonwoven Stochastic Memristive Devices Based on Polyamide-6 and Polyaniline for Neuromorphic Computing.

Reservoir computing systems are promising for application in bio-inspired neuromorphic networks as they allow the considerable reduction of training energy and time costs as well as an overall system complexity. Conductive three-dimensional structures with the ability of reversible resistive switching are intensively developed to be applied in such systems. Nonwoven conductive materials, due to their stochasticity, flexibility and possibility of large-scale production, seem promising for this task. In this work, fabrication of a conductive 3D material by polyaniline synthesis on a polyamide-6 nonwoven matrix was shown. An organic stochastic device with a prospective to be used in reservoir computing systems with multiple inputs was created based on this material. The device demonstrates different responses (output current) when different combinations of voltage pulses are applied to the inputs. The approach is tested in handwritten digit image classification task in simulation with the overall accuracy exceeding 96%. This approach is beneficial for processing multiple data flows within a single reservoir device.

Memristive circuit-based model of central pattern generator to reproduce spinal neuronal activity in walking pattern.

Existing methods of neurorehabilitation include invasive or non-invasive stimulators that are usually simple digital generators with manually set parameters like pulse width, period, burst duration, and frequency of stimulation series. An obvious lack of adaptation capability of stimulators, as well as poor biocompatibility and high power consumption of prosthetic devices, highlights the need for medical usage of neuromorphic systems including memristive devices. The latter are electrical devices providing a wide range of complex synaptic functionality within a single element. In this study, we propose the memristive schematic capable of self-learning according to bio-plausible spike-timing-dependant plasticity to organize the electrical activity of the walking pattern generated by the central pattern generator.

New classification for septic arthritis of the hand.

The severity of septic arthritis of the hand and the prospects for restoration of joint function are determined by a complex of factors. Among them, the leading role belongs to local changes in tissue structures. This includes the destruction of articular cartilage and bone tissue with the development of osteomyelitis, the involvement of paraarticular soft tissues in the purulent process, and the destruction of the flexor/extensor tendons of the fingers. The currently missing specialized classification of septic arthritis could help in systematizing the diseases, determining treatment tactics, and predicting the results of treatment. The classification of septic arthritis of the hand proposed for discussion is based on the following principle: Joint-Wound-Tendon (JxWxTx); Jx characterizes damage to the osteochondral structures of the joint, Wx is the presence of paraarticular purulent wounds or fistulas, and Tx is destruction of the flexor/extensor tendons of the finger. The classification of the diagnosis makes it possible to assess the nature and severity of damage to the structures of the joint and may also be useful when comparing the results of treatment of septic arthritis of the hand.

Septic arthritis of the hand: From etiopathogenesis to surgical treatment.

BACKGROUND: Septic arthritis of the hand, which is the second most common after damage of the knee joint, remains one of the leading causes of temporary disability. An inflammation can cause dysfunction of the joint, and in the most severe cases, the need for amputation of the finger may arise. The results of their treatment today, especially from a functional point of view, cannot be considered satisfactory. Urgent surgical treatment is extremely important in septic arthritis of the hand, as it helps to prevent cartilage destruction and the development of osteomyelitis. AIM: To explore the features of the course of septic arthritis of the hand as well as approaches to surgical treatment and its results, depending on the nature of the damage to the articular structures. METHODS: The results of the treatment of 170 patients with septic arthritis of the hand, which were treated in the period of 2020-2021, were analyzed. Inflammation of the interphalangeal and metacarpophalangeal joints (MCP) of fingers 1, 2, and 3 was more often noted in 147 (81.6%) joints. The most common cause of arthritis was a penetrating injury as a result of household trauma (101, 59.4%), animal bite (30, 17.6%), and clenched fist injury (15, 8.8%). Septic arthritis with contiguous osteomyelitis was observed in 98 (54.4%) cases. Surgical treatment was completed with drainage and irrigation of the joint. Early mobilization was used to restore function. In patients with osteomyelitis, it was aimed at the formation of neoarthrosis. Arthrodesis was not applied. Long-term results of treatment were assessed in 142 (83.5%) patients within 1 mo to 12 mo after discharge from the hospital [the median was 7 mo (IQR: 4-9)]. RESULTS: The most commonly isolated organism was Staphylococcus aureus (35.3%). The median treatment delay in patients without osteomyelitis was 5 d (IQR: 4-7); for septic arthritis with contiguous osteomyelitis, it was 14 d (IQR: 5-21). Radiography for osteomyelitis within 2 wk was uninformative: 41.2% of diagnoses. A single surgical treatment was required in 138 (81.2%) patients, two treatments in 22 (12.9%), and three or more in 10 (5.9%). Total elimination of the infection was achieved in 163 (95.9%) patients. The best functional results of treatment were noted in patients without osteomyelitis. After septic arthritis, Total Active Motion (TAM) for the MCP was 96.2% (IQR: 85.1-98.0), for the proximal interphalangeal joint (PIP) 82.4% (IQR: 54.5-98.5), and for the distal interphalangeal joint (DIP) 69.4% (IQR: 65.4-74.1). In cases with osteomyelitis, it was possible to achieve the formation of neoarthrosis with TAM for MCP-64.2% (IQR: 45.3-90.1), for PIP-62.5% (IQR: 41.8-68.9), and for DIP-59.4% (IQR: 50-62.1). Additionally, the severity of pain during movements did not exceed 1 point. CONCLUSION: The delay in treatment of patients with septic arthritis of the hand was accompanied by a high incidence of osteomyelitis, especially in the presence of diabetes mellitus. Urgent surgical treatment, along with continued irrigation of the joint and antibiotic therapy, made it possible to eliminate the infection, and early rehabilitation restored the range of motion. The best results were noted in patients without osteomyelitis. With the development of osteomyelitis, a complex of early rehabilitation measures also made it possible to partially restore the range of motion due to the formation of neoarthrosis, without resorting to arthrodesis.

Convolutional Neural Network Based on Crossbar Arrays of (Co-Fe-B)x(LiNbO3)100-x Nanocomposite Memristors.

Convolutional neural networks (CNNs) have been widely used in image recognition and processing tasks. Memristor-based CNNs accumulate the advantages of emerging memristive devices, such as nanometer critical dimensions, low power consumption, and functional similarity to biological synapses. Most studies on memristor-based CNNs use either software models of memristors for simulation analysis or full hardware CNN realization. Here, we propose a hybrid CNN, consisting of a hardware fixed pre-trained and explainable feature extractor and a trainable software classifier. The hardware part was realized on passive crossbar arrays of memristors based on nanocomposite (Co-Fe-B)x(LiNbO3)100-x structures. The constructed 2-kernel CNN was able to classify the binarized Fashion-MNIST dataset with ~ 84% accuracy. The performance of the hybrid CNN is comparable to the other reported memristor-based systems, while the number of trainable parameters for the hybrid CNN is substantially lower. Moreover, the hybrid CNN is robust to the variations in the memristive characteristics: dispersion of 20% leads to only a 3% accuracy decrease. The obtained results pave the way for the efficient and reliable realization of neural networks based on partially unreliable analog elements.

Parylene-based memristive crossbar structures with multilevel resistive switching for neuromorphic computing.

Currently, there is growing interest in wearable and biocompatible smart computing and information processing systems that are safe for the human body. Memristive devices are promising for solving such problems due to a number of their attractive properties, such as low power consumption, scalability, and the multilevel nature of resistive switching (plasticity). The multilevel plasticity allows memristors to emulate synapses in hardware neuromorphic computing systems (NCSs). The aim of this work was to study Cu/poly-p-xylylene(PPX)/Au memristive elements fabricated in the crossbar geometry. In developing the technology for manufacturing such samples, we took into account their characteristics, in particular stable and multilevel resistive switching (at least 10 different states) and low operating voltage (<2 V), suitable for NCSs. Experiments on cycle to cycle (C2C) switching of a single memristor and device to device (D2D) switching of several memristors have shown high reproducibility of resistive switching (RS) voltages. Based on the obtained memristors, a formal hardware neuromorphic network was created that can be trained to classify simple patterns.

[The efficacy of outpatient monitoring of children and adolescents with type 1 diabetes with regular use of professional continuous glucose monitoring].

BACKGROUND: According to research, only 38% of patients reach glycated hemoglobin targets. It is possible to improve the effectiveness of medical care for children with T1D using modern technologies, including continuous glucose monitoring (CGM). AIMS: To evaluate the effectiveness of outpatient monitoring of children and adolescents with T1D with regular use of professional continuous glucose monitoring. METHODS: The inclusion criteria: age 8−12 years; T1D at least 1 year; insulin therapy by multiple injections of insulin; inadequate glycemic control of T1D: НbА1с level of 7.5% and higher and / or children and adolescents with frequent episodes of hypoglycemia (usually 4 times a week) or with a history of severe hypoglycemia; signed informed consent. All patients initially and 12 weeks after inclusion in the study conducted a study of the level of НbА1с, and also performed CGM for 6 days. Based on the results of CGM, glycemia indicators and daily doses of insulin were recorded, treatment was evaluated and corrected, and recommendations for self-monitoring were made. Glucose monitoring was carried 120−144 hours using the blind method iPro2 (Medtronic, USA). RESULTS: In all, 99 children aged 8−18 years were included in the study in all centers. The decrease in the level of НbА1с by the end of the study was 0.72%, while the proportion of patients who reached the target level of НbА1с (defined as <7.5%) was statistically significantly higher at the end of the study (15.5% and 2%, respectively; p<0.05). During the study, patients showed a trend towards a decrease in the average level and variability of glycemia by the end of the study, however, statistical significance was achieved only in relation to the average level of glycemia (p=0.04). Conducted insulin therapy, determined by the average daily doses of long-acting and short-acting insulin, did not statistically significantly change at the end of the study. The frequency of DKA episodes and severe hypoglycemia did not statistically significantly differ from the initial level. CONCLUSIONS: For children with poor glycemic control of T1D, the use of professional CGM is effective in terms of glycemic control and a safe method.

[Remote monitoring and treatment of children and adolescents with type 1 diabetes].

RATIONALE: Continuous subcutaneous insulin infusion (CSII) is an effective method for optimizing glycemic control in children with type 1 diabetes mellitus (DM1). However, the use of CSII does not always result in adequate glycemic control. Telehealth can be applied as one of the methods to improve the effectiveness of treatment. AIMS: To evaluate the use of remote medical support of children and adolescents with DM1 and its influence on glycemic control, quality of life, and incidence of acute complications of DM1. MATERIALS AND METHODS: We conducted a 24-week multi-institutional prospective open-label controlled clinical trial. 180 children and adolescents were included in this study and divided into the following categories: 1) age 8-18 years; 2) DM1 at least 1 year; 3) pump insulin therapy Medtronic Paradigm (Medtronic MiniMed, USA) at least 6 months; 4) self-monitoring of glycemia at least 4 times a day and replacement of the insulin pump infusion system at least once every 3 days; 5) inadequate glycemic control of DM1: the level of glycated hemoglobin (HbA1c) 7.5% or higher. Patients were assigned to a remote consultation group (RC; n=100) or a traditional control group (TC; n=80). All patients were trained on the basic principles of DM1 and CSII, and we measured initial HbA1c, then after 12 and 24 weeks, also registered and analyzed glycemic indicators and daily doses of insulin, evaluated and corrected the treatment. Patients or their parents in the RC group sent pump data via the Internet to the pump insulin therapy center at least once every 2 weeks at home and received treatment recommendations in response. RESULTS: The total number of patients included in the study in all institutions was 180 children at 8-18 years. Patients in both groups did not differ in age, gender, duration of DM1 and CSII, and HbA1c level. The total amount of remote consultations for all institutions was 949. The decrease in the level of HbA1c by the end of the study against the initial one was statistically significantly greater in the RC group: 1.17% compared to 0.59% in the TC group (p<0.05). The proportion of patients who reached the target level of HbA1c (<7.5%) was significantly higher in the RC group (32%) compared to the TC group (12.5%, p<0.05). During the study, the incidence of DKA and severe hypoglycemia in the RC group was statistically significantly lower. CONCLUSIONS: Remote monitoring in children with DM1 resulted in significant improvements in glycemic control (HbA1c, glycemic variability, and hypoglycemic frequency). The accumulation of evidence on the effectiveness and safety of telehealth in DM should contribute to implementing this approach in practical health care.

Parylene Based Memristive Devices with Multilevel Resistive Switching for Neuromorphic Applications.

In this paper, the resistive switching and neuromorphic behaviour of memristive devices based on parylene, a polymer both low-cost and safe for the human body, is comprehensively studied. The Metal/Parylene/ITO sandwich structures were prepared by means of the standard gas phase surface polymerization method with different top active metal electrodes (Ag, Al, Cu or Ti of ~500 nm thickness). These organic memristive devices exhibit excellent performance: low switching voltage (down to 1 V), large OFF/ON resistance ratio (up to 104), retention (≥104 s) and high multilevel resistance switching (at least 16 stable resistive states in the case of Cu electrodes). We have experimentally shown that parylene-based memristive elements can be trained by a biologically inspired spike-timing-dependent plasticity (STDP) mechanism. The obtained results have been used to implement a simple neuromorphic network model of classical conditioning. The described advantages allow considering parylene-based organic memristors as prospective devices for hardware realization of spiking artificial neuron networks capable of supervised and unsupervised learning and suitable for biomedical applications.

A glucokinase gene mutation in a young boy with diabetes mellitus, hyperinsulinemia, and insulin resistance.

We report the case of a 12-year-old boy with a glucokinase (GCK) mutation, and diabetes with hyperinsulinemia and insulin resistance. For 4 years, the patient intermittently received insulin medications Actrapid HM and Protaphane HM (total dose 5 U/day), with glycated hemoglobin (HbA1c) levels of 6.6%-7.0%. After extensive screening the patient was found to carry a heterozygous mutation (p.E256K) in GCK (MIM #138079, reference sequence NM_000162.3). Insulin therapy was replaced by metformin at 1,700 mg/day. One year later, his HbA1c level was 6.9%, postprandial glycemia at 120 min of oral glucose tolerance test was 15.4 mmol/L, hyperinsulinemia had increased to 508.9 mU/L, homeostasis model assessment index was 114.2 and the Matsuda index was 0.15. Insulin resistance was confirmed by a hyperinsulinemic euglycemic clamp test - M-index was 2.85 mg/kg/min. This observation is a rare case of one of the clinical variants of diabetes, which should be taken into account by a vigilant endocrinologist due to the need for nonstandard diagnostic and therapeutic approaches.