Structure and energy of a DNA dodecamer under tensile load

In the last decade, methods to study single DNA molecules under tensile load have been developed. These experiments measure the force required to stretch and melt the double helix and provide insights into the structural stability of DNA. However, it is not easy to directly relate the shape of the force curve to the structural changes that occur in the double helix under tensile load. Here, state-of-the-art computer simulations of short DNA sequences are preformed to provide an atomistic description of the stretching of the DNA double helix. These calculations show that for extensions larger that ~25% the DNA undergoes a structural transformation and a few base pairs are lost from both the terminal and central part of the helix. This locally melted DNA duplex is stable and can be extended up to ~50-60% of the equilibrium length at a constant force. It is concluded that melting under tension cannot be modeled as a simple two-state process. Finally, the important role of the cantilever stiffness in determining the shape of the force- extension curve and the most probable rupture force is discussed

Three-dimensional kinetic Monte Carlo simulation of crystal growth from solution

The growth of urea crystals from water and methanol solutions has been studied with kinetic Monte Carlo simulations. Parameters for the simulations were derived from atomistic molecular dynamics simulations of the growth and dissolution of urea from water and methanol solutions. This approach allows the effect of solvation on the growth and dissolution kinetics to be fully included while extending the size of the simulation to the micrometre length scale and millisecond timescale

User Localization with HRIS and Backscatter Modulation for Next-Generation Networks

Hybrid reflective intelligent surfaces (HRISs) can support localization in sixth-generation (6G) networks thanks to their ability to generate narrow beams and at the same time receive and process locally the impinging signals. In this paper, we propose a novel protocol for user localization in a network with an HRIS. The protocol includes two steps. In the first step, the HRIS operates in full absorption mode and the user equipment (UE) transmits a signal that is locally processed at the HRIS to estimate the angle of arrival (AoA). In the second step, the base station transmits a downlink reference signal to the UE, and the HRIS superimposes a message by a backscatter modulation. The message contains information on the previously estimated AoA. Lastly, the UE, knowing the position of the HRIS, estimates the time of flight (ToF) from the signal of the second step and demodulates the information on the AoA to obtain an estimate of its location. Numerical results confirm the effectiveness of the proposed solution, also in comparison with the Cram\'er Rao lower bound on the estimated quantities.nd on the estimated quantities

Aspartic acid as a crystal growth catalyst

Ion desolvation is an important kinetic step in the growth of divalent ionic crystals - a category that encompasses numerous materials relevant to biomineralization. It has recently been shown for one such divalent ionic crystal that the rate-limiting desolvation of the cation can be assisted by the anion and that this process can be surface specific. Here we show that even a simple biological molecule, such as aspartic acid, can have a measurable catalytic effect on barite crystal growth and that this effect is related to the lowering of the activation barrier for cation desolvation. We therefore suggest that growth rate enhancement on specific faces through catalysis of the cation desolvation step may be a viable mechanism for the positive control of biomineralization

Developing a molecular dynamics force field for both folded and disordered protein states

Molecular dynamics (MD) simulation is a valuable tool for characterizing the structural dynamics of folded proteins and should be similarly applicable to disordered proteins and proteins with both folded and disordered regions. It has been unclear, however, whether any physical model (force field) used in MD simulations accurately describes both folded and disordered proteins. Here, we select a benchmark set of 21 systems, including folded and disordered proteins, simulate these systems with six state-of-the-art force fields, and compare the results to over 9,000 available experimental data points. We find that none of the tested force fields simultaneously provided accurate descriptions of folded proteins, of the dimensions of disordered proteins, and of the secondary structure propensities of disordered proteins. Guided by simulation results on a subset of our benchmark, however, we modified parameters of one force field, achieving excellent agreement with experiment for disordered proteins, while maintaining state-of-the-art accuracy for folded proteins. The resulting force field, a99SB-disp, should thus greatly expand the range of biological systems amenable to MD simulation. A similar approach could be taken to improve other force fields

Adaptive Body Gesture Representation for Automatic Emotion Recognition

We present a computational model and a system for the automated recognition of emotions starting from full-body movement. Three-dimensional motion data of full-body movements are obtained either from professional optical motion-capture systems (Qualisys) or from low-cost RGB-D sensors (Kinect and Kinect2). A number of features are then automatically extracted at different levels, from kinematics of a single joint to more global expressive features inspired by psychology and humanistic theories (e.g., contraction index, fluidity, and impulsiveness). An abstraction layer based on dictionary learning further processes these movement features to increase the model generality and to deal with intraclass variability, noise, and incomplete information characterizing emotion expression in human movement. The resulting feature vector is the input for a classifier performing real-time automatic emotion recognition based on linear support vector machines. The recognition performance of the proposed model is presented and discussed, including the tradeoff between precision of the tracking measures (we compare the Kinect RGB-D sensor and the Qualisys motion-capture system) versus dimension of the training dataset. The resulting model and system have been successfully applied in the development of serious games for helping autistic children learn to recognize and express emotions by means of their full-body movement

Effects of Computerized Emotional Training on Children with High Functioning Autism

An evaluation study of a serious game and a system for the automatic emotion recognition designed for helping autistic children to learn to recognize and express emotions by means of their full-body movement is presented. Three-dimensional motion data of full-body movements are obtained from RGB-D sensors and used to recognize emotions by means of linear SVMs. Ten children diagnosed with High Functioning Autism or Asperger Syndrome were involved in the evaluation phase, consisting of repeated sessions to play a specifically designed serious game. Results from the evaluation study show an increase of tasks accuracy from the beginning to the end of training sessions in the trained group. In particular, while the increase of recognition accuracy was concentrated in the first sessions of the game, the increase for expression accuracy is more gradual throughout all sessions. Moreover, the training seems to produce a transfer effect on facial expression recognition