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The spectrum of localized hole states (traps) in amorphous silicon nitride, a-Si3N4, is experimentally studied using the method of thermally stimulated depolarization. The experiment is compared with theoretical calculations using three models of the energy spectrum of traps: discrete spectrum (monoenergetic trap), continuous spectrum, and Gaussian trap distribution. The experiment is quantitatively described by a model of a discrete spectrum of traps with an energy of 1.15 eV and a width of no more than 0.01 eV. In the case of a continuous and Gaussian spectrum of traps, the contribution to depolarization is made by the deepest traps. The blurring of the trap energy level in a-Si3N4 due to the absence of long-range order (fluctuations in the Si–N bond length and fluctuations in the N–Si–N and Si–N–Si angles) does not exceed 0.01 eV. [ABSTRACT FROM AUTHOR]

A series of laboratory and numerical experiments have been performed to study the process of the surface water cooling. The process of the submergence of an ensemble of jets (a thermal-like structure) or a negative buoyancy flux was recorded using digital cameras (∼2 and 10 Hz). Quantitative estimates of the structure and dynamical features of the initial phase of the submergence of a density front of the ensemble of jets were obtained. These estimates were compared with the previous results of the study of individual thermals. It was found that the deepening velocity is characterized by the nonlinear dependence from the submergence depth in time of both the thermals and the density front of the ensemble. The numerical calculations also showed nonlinearity in this dependence. The process of submergence of the density front was divided into three stages, which were described for the first time. The deepening velocity of the density front of the ensemble of jets was ∼0.15 cm/s. The results are qualitatively consistent with the theoretical estimates of the evolution of the free convection. The observed laboratory flows have the laminar nature of convective movements (Reynolds numbers ranging from 3 to 60). A geometric model was proposed to describe linear quantity of both the thermal and jet. It was shown that the effects of turbulence on the seawater measurements were caused externally and not related to the process of the surface water cooling. Thus, it is assumed that either thermal or saline turbulence dominates over free convection conditions. This conclusion has an important role in the study of the heat exchange process in ocean models. [ABSTRACT FROM AUTHOR]

Amorphous aluminum oxide a-Al2O3 deposited by atomic layer deposition (ALD) is widely used in nonvolatile memory devices. In this paper, the leakage current dependence on the ALD synthesis temperature is investigated by six charge transport models: Schottky effect, thermally assisted tunneling at a contact, Frenkel effect, Hill-Adachi model of overlapping Coulomb potentials, Makram-Ebeid and Lannoo multiphonon isolated trap ionization model, and Nasyrov–Gritsenko model of phonon-assisted tunneling between neighboring traps. It is shown that the leakage current exponentially increases with the ALD synthesis temperature, which is related to the increase in trap concentration. [ABSTRACT FROM AUTHOR]

Recently ferroelectric properties have been found in hafnia-based nanosized films. Such films are of the utmost interest for development of a universal memory, which combines the advantages of random access memory and flash memory. The paper studies optical properties of hafnia-zirconium oxide films H-fxZryO2 and lanthanum-alloyed hafnia-zirconium oxide films La:HfxZryO2. Fluctuations of thickness in HfxZryO2 do not exceed 3.5%, fluctuations of thickness in La:HfxZryO2 films—3.2%. Optical properties are analyzed based on effective-medium theory. According to effective-medium theory data, HfxZryO2 films contain 46% HfO2, 54% ZrO2, La:HfxZryO2 films contain 47.5% HfO2, 52.4% ZrO2, 2.5% La2O3. [ABSTRACT FROM AUTHOR]

Silicon oxynitride films of various compositions were grown by the plasma-enhanced chemical deposition method using a setup with remote plasma and an inductive excitation from a gas mixture of 10% monosilane (diluted with argon) and nitrogen in the presence of residual oxygen in working gas mixtures. The high-frequency generator power (13.56 MHz) was varied in the range of 50–150 W. The samples composition was studied using x-ray photoelectron spectroscopy. A comparison of the experimental Si 2p photoelectron spectrum with the calculation showed that, at a low generator power (50 W), the short-range order in silicon oxynitride films is better described by the "random mixture" model. As the generator power is increased (100 W and higher), the excess silicon content in a silicon oxynitride film is decreased, and the short-range order is better described by the "random bonding" model. On metal–insulator–semiconductor-structures based on the silicon oxynitride films obtained, measurements of current–voltage characteristics were carried out, and the resistive switching of the obtained structures is studied in the present contribution. It is found that, in films in which the short-range order is described by the random bonding model, a stable switching in the bipolar regime is observed. [ABSTRACT FROM AUTHOR]

Currently, a new generation of high-speed, information-intensive resistive memory based on nonstoichiometric dielectrics is being developed. The electron structure of nonstoichiometric silicon oxide SiOx is set by the value of parameter x. It is found that the treatment of thermal SiO2 in hydrogen plasma electron cyclotron resonance leads to the enrichment of silicon oxide with excess silicon, which in turn leads to the appearance of electron and hole traps in SiOx. SiOx conductivity is bipolar: electrons are injected from negatively biased silicon and holes are injected from positively biased silicon. Cathodoluminescence (CL) experiments confirm the assumption that the traps in SiOx are due to the excess silicon. p++-Si(100)/SiOx/Ni memristor metal-dielectric-semiconductor (MDS) structures are fabricated based on the developed procedure for the preparation of nonstoichiometric oxide in hydrogen plasma of electron cyclotron resonance. Such structures have the properties of resistive switching of SiOx that do not require a forming operation. [ABSTRACT FROM AUTHOR]

Movement analysis is a critical tool in understanding and addressing various disabilities associated with movement deficits. By analyzing movement patterns, healthcare professionals can identify the root causes of these alterations, which is essential for preventing, diagnosing, and rehabilitating a broad spectrum of medical conditions, disabilities, and injuries. With the advent of affordable motion capture technologies, quantitative data on patient movement is more accessible to clinicians, enhancing the quality of care. Nonetheless, it is crucial that these technologies undergo rigorous validation to ensure their accuracy in collecting and monitoring patient movements, particularly for remote healthcare services where direct patient observation is not possible. In this study, motion capture technology was used to track upper extremity movements during a reaching task presented in virtual reality. Kinematic data was then calculated for each participant using a scaled dynamic inertial model. The goal was to evaluate the accuracy of joint angle calculations using inverse kinematics from motion capture relative to the typical movement redundancy. Shoulder, elbow, radioulnar, and wrist joint angles were calculated with models scaled using either direct measurements of each individual's arm segment lengths or those lengths were calculated from individual height using published average proportions. The errors in joint angle trajectories calculated using the two methods of model scaling were compared to the inter-trial variability of those trajectories. The variance of this error was primarily within the normal range of variability between repetitions of the same movements. This suggests that arm joint angles can be inferred with good enough accuracy from motion capture data and individual height to be useful for the clinical assessment of motor deficits., Competing Interests: Competing Interests The authors declare no competing interests.

Neural control of movement has to overcome the problem of redundancy in the multidimensional musculoskeletal system. The problem can be solved by reducing the dimensionality of the control space of motor commands, i.e., through muscle synergies or motor primitives. Evidence for this solution exists, multiple studies have obtained muscle synergies using decomposition methods. These synergies vary across different workspaces and are present in both dominant and non-dominant limbs. Here we explore the dimensionality of control space by examining muscle activity patterns across reaching movements in different directions starting from different postures performed bilaterally by healthy individuals. We further explore the effect of biomechanical constraints on the dimensionality of control space. We are building on top of prior work showing that muscle activity profiles can be explained by applied moments about the limb joints that reflect the biomechanical constraints. These muscle torques derived from motion capture represent the combined actions of muscle contractions that are under the control of the nervous system. Here we test the generalizability of the relationship between muscle torques and muscle activity profiles across different starting positions and between limbs. We also test a hypothesis that the dimensionality of control space is shaped by biomechanical constraints. We used principal component analysis to evaluate the contribution of individual muscles to producing muscle torques across different workspaces and in both dominant and non-dominant limbs. Results generalize and support the hypothesis. We show that the muscle torques that support the limb against gravity are produced by more consistent combinations of muscle co-contraction than those that produce propulsion. This effect was the strongest in the non-dominant arm moving in the lateral workspace on one side of the body., Competing Interests: Competing Interests The authors declare no competing interests.

This paper presents a novel method for solving the inverse kinematic problem of capturing human reaching movements using a dynamic biomechanical model. The model consists of rigid segments connected by joints and actuated by markers. The method was validated against a rotation matrix-based method using motion capture data recorded during reaching movements performed by healthy human volunteers. The results showed that the proposed method achieved low errors in joint angles and compensated for noise in motion capture data. The angles were comparable to those calculated using the standard marker-based method. The proposed bioinspired method can be used in real-time medical applications for processing noisy marker data with occlusions.

Neural circuits embed limb dynamics for motor control and sensorimotor integration. The somatotopic organization of motoneuron pools in the spinal cord may support these computations. Here, we tested if the spatial organization of motoneurons is related to the musculoskeletal anatomy. We created a 3D model of motoneuron locations within macaque spinal cord and compared the spatial distribution of motoneurons to the anatomical organization of the muscles they innervate. We demonstrated that the spatial distribution of motoneuron pools innervating the upper limb and the anatomical relationships between the muscles they innervate were similar between macaque and human species. Using comparative analysis, we found that the distances between motoneuron pools innervating synergistic muscles were the shortest, followed by those innervating antagonistic muscles. Such spatial organization can support the co-activation of synergistic muscles and reciprocal inhibition of antagonistic muscles. The spatial distribution of motoneurons may play an important role in embedding musculoskeletal dynamics., (© 2024. The Author(s).)

The ability to move allows us to interact with the world. When this ability is impaired, it can significantly reduce one's quality of life and independence and may lead to complications. The importance of remote patient evaluation and rehabilitation has recently grown due to limited access to in-person services. For example, the COVID-19 pandemic unexpectedly resulted in strict regulations, reducing access to non-emergent healthcare services. Additionally, remote care offers an opportunity to address healthcare disparities in rural, underserved, and low-income areas where access to services remains limited. Improving accessibility through remote care options would limit the number of hospital or specialist visits and render routine care more affordable. Finally, the use of readily available commercial consumer electronics for at-home care can enhance patient outcomes due to improved quantitative observation of symptoms, treatment efficacy, and therapy dosage. While remote care is a promising means to address these issues, there is a crucial need to quantitatively characterize motor impairment for such applications. The following protocol seeks to address this knowledge gap to enable clinicians and researchers to obtain high-resolution data on complex movement and underlying muscle activity. The ultimate goal is to develop a protocol for remote administration of functional clinical tests. Here, participants were instructed to perform a medically-inspired Box and Block task (BBT), which is frequently used to assess hand function. This task requires subjects to transport standardized cubes between two compartments separated by a barrier. We implemented a modified BBT in virtual reality to demonstrate the potential of developing remote assessment protocols. Muscle activation was captured for each subject using surface electromyography. This protocol allowed for the acquisition of high-quality data to better characterize movement impairment in a detailed and quantitative manner. Ultimately, these data have the potential to be used to develop protocols for virtual rehabilitation and remote patient monitoring.

The nervous system predicts and executes complex motion of body segments actuated by the coordinated action of muscles. When a stroke or other traumatic injury disrupts neural processing, the impeded behavior has not only kinematic but also kinetic attributes that require interpretation. Biomechanical models could allow medical specialists to observe these dynamic variables and instantaneously diagnose mobility issues that may otherwise remain unnoticed. However, the real-time and subject-specific dynamic computations necessitate the optimization these simulations. In this study, we explored the effects of intrinsic viscoelasticity, choice of numerical integration method, and decrease in sampling frequency on the accuracy and stability of the simulation. The bipedal model with 17 rotational degrees of freedom (DOF)-describing hip, knee, ankle, and standing foot contact-was instrumented with viscoelastic elements with a resting length in the middle of the DOF range of motion. The accumulation of numerical errors was evaluated in dynamic simulations using swing-phase experimental kinematics. The relationship between viscoelasticity, sampling rates, and the integrator type was evaluated. The optimal selection of these three factors resulted in an accurate reconstruction of joint kinematics (err < 1%) and kinetics (err < 5%) with increased simulation time steps. Notably, joint viscoelasticity reduced the integration errors of explicit methods and had minimal to no additional benefit for implicit methods. Gained insights have the potential to improve diagnostic tools and accurize real-time feedback simulations used in the functional recovery of neuromuscular diseases and intuitive control of modern prosthetic solutions., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Bahdasariants et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

A major goal in neuroscience is to elucidate the principles by which memories are stored in a neural network. Here, we have systematically studied how four types of associative memories (short- and long-term memories, each as positive and negative associations) are encoded within the compact neural network of Caenorhabditis elegans worms. Interestingly, sensory neurons were primarily involved in coding short-term, but not long-term, memories, and individual sensory neurons could be assigned to coding either the conditioned stimulus or the experience valence (or both). Moreover, when considering the collective activity of the sensory neurons, the specific training experiences could be decoded. Interneurons integrated the modulated sensory inputs and a simple linear combination model identified the experience-specific modulated communication routes. The widely distributed memory suggests that integrated network plasticity, rather than changes to individual neurons, underlies the fine behavioral plasticity. This comprehensive study reveals basic memory-coding principles and highlights the central roles of sensory neurons in memory formation., Competing Interests: CP, EI, EB, RR, VG, TN, MM, AA, AZ No competing interests declared, (© 2023, Pritz et al.)

The neural control of posture and movement is interdependent. During voluntary movement, the neural motor command is executed by the motor cortex through the corticospinal tract and its collaterals and subcortical targets. Here we address the question of whether the control mechanism for the postural adjustments at nonmoving joints is also involved in overcoming gravity at the moving joints. We used single-pulse transcranial magnetic stimulation to measure the corticospinal excitability in humans during postural and reaching tasks. We hypothesized that the corticospinal excitability is proportional to background muscle activity and the gravity-related joint moments during both static postures and reaching movements. To test this hypothesis, we used visual targets in virtual reality to instruct five postures and three movements with or against gravity. We then measured the amplitude and gain of motor evoked potentials in multiple arm and hand muscles at several phases of the reaching motion and during static postures. The stimulation caused motor evoked potentials in all muscles that were proportional to the muscle activity. During both static postures and reaching movements, the muscle activity and the corticospinal contribution to these muscles changed in proportion with the postural moments needed to support the arm against gravity, supporting the hypothesis. Notably, these changes happened not only in antigravity muscles. Altogether, these results provide evidence that the changes in corticospinal excitability cause muscle cocontraction that modulates limb stiffness. This suggests that the motor cortex is involved in producing postural adjustments that support the arm against gravity during posture maintenance and reaching. NEW & NOTEWORTHY Animal studies suggest that the corticospinal tract and its collaterals are crucial for producing postural adjustments that accompany movement in limbs other than the moving limb. Here we provide evidence for a similar control schema for both arm posture maintenance and gravity compensation during movement of the same limb. The observed interplay between the postural and movement control signals within the corticospinal tract may help explain the underlying neural motor deficits after stroke.

The human motor system has evolved to perform efficient motor control in Earth's gravity. Altered gravity environments, such as microgravity and hypergravity, pose unique challenges for performing fine motor tasks with object manipulation. Altered gravity has been shown to reduce the speed and accuracy of complex manual tasks. This study aims to leverage electromyography (EMG) and virtual reality (VR) technologies to provide insights into the neuromuscular mechanism of object weight compensation. Seven healthy subjects were recruited to perform arm and hand movements, including a customized Box and Block Test with three different block weights, 0 (VR), 0.02, and 0.1 kg. EMG was recorded from 15 muscles of arm and hand while manipulating objects instrumented with force sensors to collect contact forces. Muscle co-contraction extracted from EMGs of antagonistic muscles was used as a measure of joint stiffness for each task. Results show that the co-contraction levels increased in the task with the heavy object and decreased in the VR task. This relationship suggests that the internal expectations of the object weight and the proprioceptive and haptic feedback from the contact with the object are driving the co-contraction of antagonistic muscles.

High-performance p-type thin-film transistors (pTFTs) are crucial for realizing low-power display-on-panel and monolithic three-dimensional integrated circuits. Unfortunately, it is difficult to achieve a high hole mobility of greater than 10 cm 2 /V·s, even for SnO TFTs with a unique single-hole band and a small hole effective mass. In this paper, we demonstrate a high-performance GeSn pTFT with a high field-effect hole mobility (μ FE ), of 41.8 cm 2 /V·s; a sharp turn-on subthreshold slope ( SS ), of 311 mV/dec, for low-voltage operation; and a large on-current/off-current (I ON /I OFF ) value, of 8.9 × 10 6 . This remarkably high I ON /I OFF is achieved using an ultra-thin nanosheet GeSn, with a thickness of only 7 nm. Although an even higher hole mobility (103.8 cm 2 /V·s) was obtained with a thicker GeSn channel, the I OFF increased rapidly and the poor I ON /I OFF (75) was unsuitable for transistor applications. The high mobility is due to the small hole effective mass of GeSn, which is supported by first-principles electronic structure calculations.