Quantum Annealing in the NISQ Era: Railway Conflict Management.

We are in the noisy intermediate-scale quantum (NISQ) devices' era, in which quantum hardware has become available for application in real-world problems. However, demonstrations of the usefulness of such NISQ devices are still rare. In this work, we consider a practical railway dispatching problem: delay and conflict management on single-track railway lines. We examine the train dispatching consequences of the arrival of an already delayed train to a given network segment. This problem is computationally hard and needs to be solved almost in real time. We introduce a quadratic unconstrained binary optimization (QUBO) model of this problem, which is compatible with the emerging quantum annealing technology. The model's instances can be executed on present-day quantum annealers. As a proof-of-concept, we solve selected real-life problems from the Polish railway network using D-Wave quantum annealers. As a reference, we also provide solutions calculated with classical methods, including the conventional solution of a linear integer version of the model as well as the solution of the QUBO model using a tensor network-based algorithm. Our preliminary results illustrate the degree of difficulty of real-life railway instances for the current quantum annealing technology. Moreover, our analysis shows that the new generation of quantum annealers (the advantage system) does not perform well on those instances, either.

Effect of Ion and Binding Site on the Conformation of Chosen Glycosaminoglycans at the Albumin Surface.

Albumin is one of the major components of synovial fluid. Due to its negative surface charge, it plays an essential role in many physiological processes, including the ability to form molecular complexes. In addition, glycosaminoglycans such as hyaluronic acid and chondroitin sulfate are crucial components of synovial fluid involved in the boundary lubrication regime. This study presents the influence of Na+, Mg2+ and Ca2+ ions on human serum albumin-hyaluronan/chondroitin-6-sulfate interactions examined using molecular docking followed by molecular dynamics simulations. We analyze chosen glycosaminoglycans binding by employing a conformational entropy approach. In addition, several protein-polymer complexes have been studied to check how the binding site and presence of ions influence affinity. The presence of divalent cations contributes to the decrease of conformational entropy near carboxyl and sulfate groups. This observation can indicate the higher affinity between glycosaminoglycans and albumin. Moreover, domains IIIA and IIIB of albumin have the highest affinity as those are two domains that show a positive net charge that allows for binding with negatively charged glycosaminoglycans. Finally, in discussion, we suggest some research path to find particular features that would carry information about the dynamics of the particular type of polymers or ions.

Changes of Conformation in Albumin with Temperature by Molecular Dynamics Simulations.

This work presents the analysis of the conformation of albumin in the temperature range of 300 K - 312 K , i.e., in the physiological range. Using molecular dynamics simulations, we calculate values of the backbone and dihedral angles for this molecule. We analyze the global dynamic properties of albumin treated as a chain. In this range of temperature, we study parameters of the molecule and the conformational entropy derived from two angles that reflect global dynamics in the conformational space. A thorough rationalization, based on the scaling theory, for the subdiffusion Flory-De Gennes type exponent of 0 . 4 unfolds in conjunction with picking up the most appreciable fluctuations of the corresponding statistical-test parameter. These fluctuations coincide adequately with entropy fluctuations, namely the oscillations out of thermodynamic equilibrium. Using Fisher's test, we investigate the conformational entropy over time and suggest its oscillatory properties in the corresponding time domain. Using the Kruscal-Wallis test, we also analyze differences between the root mean square displacement of a molecule at various temperatures. Here we show that its values in the range of 306 K - 309 K are different than in another temperature. Using the Kullback-Leibler theory, we investigate differences between the distribution of the root mean square displacement for each temperature and time window.

Interactions between Beta-2-Glycoprotein-1 and Phospholipid Bilayer-A Molecular Dynamic Study.

This study aims to investigate the interactions appearing when the beta-2-glycoprotein-1 binds to a lipid bilayer. The inter- and intra-molecular forces acting between the two macromolecular systems have been investigated using a molecular dynamics simulation method. The importance of water bridges has also been addressed. Additionally, the viscoelastic response of the bilayer has been studied. In detail, the (saturated-chain) 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC) and (unsaturated-chain) 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphoethanolamine (POPE) bilayers have been chosen to test their behavior near the protein. Both of the lipids have a polar head but different chemical structures and are similar to the main phospholipids present in the synovial fluid. This study is meaningful for further explaining the worsening friction properties in articular cartilage, as the inactivation of phospholipid bilayers by beta-2-glycoprotein-1 is believed to be a cause of the destruction of cartilage in most rheumatic diseases and osteoarthritis. It was found that the protein binds stronger to the DPPC bilayer than to the POPE, but in both cases, it has the potential to change the local bilayer stability. Nevertheless, the binding forces are placed within a small area (only a few lipids contribute to the binding, creating many interactions). However, together, they are not stronger than the covalent bonds between C-O, thus, potentially, it is possible to push the lipids into the bilayer but detaching the lipids' heads from the tail is not possible. Additionally, the protein causes water displacement from the vicinity of the bilayer, and this may be a contributor to the instability of the bilayer (disrupting the water bridges needed for the stabilization of the bilayer, especially in the case of DPPC where the heads are not so well stabilized by H-bonds as they are in POPE). Moreover, it was found that the diffusivity of lipids in the DPPC bilayer bound to the protein is significantly different from the diffusivity of the ones which are not in contact with the protein. The POPE bilayer is stiffer due to intramolecular interactions, which are stronger than in the DPPC; thus, the viscous to elastic effects in the POPE case are more significant than in the case of the DPPC. It is, therefore, harder to destabilize the POPE bilayer than the DPPC one.

Computational multivariate modelling of electrical activity of the porcine uterus during spontaneous and hormone-induced oestrus.

NEW FINDINGS: What is the central question of this study? Does oestrous cycle synchronization influence myoelectrical activity of porcine myometrium? What is the main finding and its importance? Exogenous hormones used to synchronize oestrus in pigs altered myoelectrical activity, which was effectively modelled. Higher-order multivariate statistic modelling provided evidence of similar activity in both types of oestrus, but a larger order of EMG signals during induced oestrus. Higher-order statistical analysis of the probabilistic model suggests the beginning of the early follicular phase and the mid-luteal phase to be most important in evaluation of the natural patterns of myoelectrical activity. Higher-order multivariate cumulants are more informative than classical statistics in characterization of myoelectrical activity changes in porcine myometrium. ABSTRACT: In pig production units, control of the oestrous cycle and synchronization of ovulation have become routine herd management procedures. During the oestrous cycle, in both induced and spontaneous conditions, the ovaries and the uterus undergo hormone-dominated physiological changes, which are consistent with the hypothesis that there is a functional role of uterine contractions in promoting fertilization. We have used electromyography to determine whether the use of exogenous hormones, such as equine chorionic gonadotrophin and human chorionic gonadotrophin, which have the potential to control the timing of ovulation in female pigs, changes the multivariate relationships between parameters of electrical bursts and modulates the patterns of myoelectrical activity. We used the mathematical approach of higher-order multivariate cumulants in complex modelling of the myometrial electrical activity. The experiment was conducted on 12 mature Polish Landrace sows, and uterine activity was recorded during both spontaneous and induced oestrous cycles. The burst parameters were determined using six features in the time domain and, after Fast Fourier transformation, in the frequency domain. Evaluation of myoelectrical activity patterns was conducted based on classical univariate statistical methods and multivariate probabilistic modelling. The classical statistical approach indicated weaker myoelectrical activity after hormonal stimulation, whereas the higher-order multivariate statistical model showed evidence of similar status of activity and a larger order of signals during induced oestrus. Routine oestrous cycle synchronization affects the multivariate probabilistic model of myometrial electrical activity.

An application of higher order multivariate cumulants in modelling of myoelectrical activity of porcine uterus during early pregnancy.

The analysis of the uterine contraction have become a general practice in an effort to improve the clinical management of uterine contractions during pregnancy and labour in human beings. The fluctuations in uterine activity may occur without affecting progress of gestation, however the painful and fashion contractions may be the first threat of miscarriage. While pigs were considered as an referential preclinical model, the computational modelling of spontaneous myoelectrical activity of complex systems of porcine myometrium in peri-fertilization period has been proposed. The higher order statistic, multivariate cumulants and Joint Skewness Band Selection method, have been applied to study the dependence structure of electromyographic (EMG) signal with an effective EMG feature. Than the model of recognition of multivariate, myoelectricaly changes according to crucial stages for successful fertilization and early pregnancy maintenance has been estimated. We found that considering together time and frequency features of EMG signal was extremely non-Gaussian distributed and the higher order multivariate statistics such as cumulants, have to be used to determine the pattern of myoelectrical activity in reproductive tract. We confirmed the expectance that the probabilistic model changes on a daily base. We demonstrated the changes in proposed model at the crucial time points of in peri-fertilization period. We speculate the activity of the middle of uterine horn and the power (minimum and maximum) and pauses between myoelectrical burst features are essential for the functional role of uterine contractility in peri-fertilization period.

Application of hyperspectral imaging and machine learning methods for the detection of gunshot residue patterns.

Advanced image processing algorithms can support the forensic analyst to make tasks like detection, pattern comparison or identification more objective. In the case of the gunshot residue (GSR) analysis, the automatic detection of potential GSR samples can support the task of evidence collection or analysis of residue needed e.g. for a muzzle-to-target firing distance estimation. In this paper we investigate the application of a hyperspectral camera and two well-known Machine Learning algorithms to automatically indicate the potential presence of GSR samples in a scene containing cloth fabrics. For this study we have created and annotated a hyperspectral image dataset consisting of GSR samples present on multiple fabric types. The GSR samples were obtained using two types of ammunition, discharged from two shooting distances. We have investigated two detection scenarios: an unsupervised anomaly detection (with the RX detector) and a supervised pixel classification (with the SVM classifier). Our results show that an accurate detection is possible in both cases. We also note that in this setting the anomaly detection approach usually requires an image normalisation, while the classifier does not require a fabric-specific information. As an addition, we show that the hyperspectral imaging generally outperforms the RGB imaging in terms of GSR detection accuracy. While the actual verification on presence of GSR on the scene requires an analyst and secondary identification methods, the hyperspectral camera with image processing algorithms can be a valuable tool supporting the evidence collection and analysis.