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A plethora of jailbreaking attacks have been proposed to obtain harmful responses from safety-tuned LLMs. In their original settings, these methods all largely succeed in coercing the target output, but their attacks vary substantially in fluency and computational effort. In this work, we propose a unified threat model for the principled comparison of these methods. Our threat model combines constraints in perplexity, measuring how far a jailbreak deviates from natural text, and computational budget, in total FLOPs. For the former, we build an N-gram model on 1T tokens, which, in contrast to model-based perplexity, allows for an LLM-agnostic and inherently interpretable evaluation. We adapt popular attacks to this new, realistic threat model, with which we, for the first time, benchmark these attacks on equal footing. After a rigorous comparison, we not only find attack success rates against safety-tuned modern models to be lower than previously presented but also find that attacks based on discrete optimization significantly outperform recent LLM-based attacks. Being inherently interpretable, our threat model allows for a comprehensive analysis and comparison of jailbreak attacks. We find that effective attacks exploit and abuse infrequent N-grams, either selecting N-grams absent from real-world text or rare ones, e.g. specific to code datasets.

Osteoarthritis (OA) is the most common musculoskeletal disease, which has no cure. Knee OA (KOA) is one of the highest causes of disability worldwide, and it costs billions of United States dollars to the global community. Prediction of KOA progression has been of high interest to the community for years, as it can advance treatment development through more efficient clinical trials and improve patient outcomes through more efficient healthcare utilization. Existing approaches for predicting KOA, however, are predominantly static, i.e. consider data from a single time point to predict progression many years into the future, and knee level, i.e. consider progression in a single joint only. Due to these and related reasons, these methods fail to deliver the level of predictive performance, which is sufficient to result in cost savings and better patient outcomes. Collecting extensive data from all patients on a regular basis could address the issue, but it is limited by the high cost at a population level. In this work, we propose to go beyond static prediction models in OA, and bring a novel Active Sensing (AS) approach, designed to dynamically follow up patients with the objective of maximizing the number of informative data acquisitions, while minimizing their total cost over a period of time. Our approach is based on Reinforcement Learning (RL), and it leverages a novel reward function designed specifically for AS of disease progression in more than one part of a human body. Our method is end-to-end, relies on multi-modal Deep Learning, and requires no human input at inference time. Throughout an exhaustive experimental evaluation, we show that using RL can provide a higher monetary benefit when compared to state-of-the-art baselines.

Superconducting qubits based on Al/AlOx/Al Josephson junction are one of the most promising candidates for the physical implementation of universal quantum computers. Due to scalability and compatibility with the state-of-the-art nanoelectronic processes one can fabricate hundreds of qubits on a single silicon chip. However, decoherence in these systems caused by two-level-systems in amorphous dielectrics, including a tunneling barrier AlOx, is one of the major problems. We report on a Josephson junction thermal annealing process development to crystallize an amorphous barrier oxide (AlOx). The dependences of the thermal annealing parameters on the room temperature resistance are obtained. The developed method allows not only to increase the Josephson junction resistance by 175%, but also to decrease by 60% with precisions of 10% in Rn. Finally, theoretical assumptions about the structure modification in tunnel barrier are proposed. The suggested thermal annealing approach can be used to form a stable and reproducible tunneling barriers and scalable frequency trimming for a widely used fixed-frequency transmon qubits.

One of the practical limitations of solid-state superconducting quantum processors technology is frequency crowding due to low qubits fabrication reproducibility. Josephson junction 100 nm-scale nonlinear inductance of the qubits still suffers from Dolan-bridge shadow evaporation process. Here, we report on a robust wafer-scale Al/AlOx/Al Dolan-bridge Josephson junction (JJ) process using preliminary shadow evaporation bias resist mask correction and comprehensive oxidation optimization. We introduce topology correction model for two-layer resist mask biasing at a wafer-scale, which takes into account an evaporation source geometry. It results in Josephson junction area variation coefficient improvement down to 1.1% for the critical dimensions from 130x170 nm2 to 130x670 nm2 over 70x70 mm2 (49 cm2) wafer working area. Next, we investigate JJ oxidation process (oxidation method, pressure and time) and its impact on a room temperature resistance reproducibility. Finally, we combine both shadow evaporation bias correction and oxidation best practices for 4-inch wafers improving room temperature resistance variation coefficient down to 6.0/5.2/4.1% for 0.025 {\mu}m2 JJ area and 4.0/3.4/2.3% for 0.090 {\mu}m2 JJ area for 49/25/16 cm2 wafer working area correspondingly. The proposed model and oxidation method can be useful for robust wafer-scale superconducting quantum processors fabrication.

Learning representations that generalize to novel compositions of known concepts is crucial for bridging the gap between human and machine perception. One prominent effort is learning object-centric representations, which are widely conjectured to enable compositional generalization. Yet, it remains unclear when this conjecture will be true, as a principled theoretical or empirical understanding of compositional generalization is lacking. In this work, we investigate when compositional generalization is guaranteed for object-centric representations through the lens of identifiability theory. We show that autoencoders that satisfy structural assumptions on the decoder and enforce encoder-decoder consistency will learn object-centric representations that provably generalize compositionally. We validate our theoretical result and highlight the practical relevance of our assumptions through experiments on synthetic image data., Comment: The first four authors contributed equally

Knee Osteoarthritis (KOA) is a highly prevalent chronic musculoskeletal condition with no currently available treatment. The manifestation of KOA is heterogeneous and prediction of its progression is challenging. Current literature suggests that the use of multi-modal data and advanced modeling methods, such as the ones based on Deep Learning, has promise in tackling this challenge. To date, however, the evidence on the efficacy of this approach is limited. In this study, we leveraged recent advances in Deep Learning and, using a Transformer approach, developed a unified framework for the multi-modal fusion of knee imaging data. Subsequently, we analyzed its performance across a range of scenarios by investigating multiple progression horizons -- from short-term to long-term. We report our findings using a large cohort (n=2421-3967) derived from the Osteoarthritis Initiative dataset. We show that structural knee MRI allows identifying radiographic KOA progressors on par with multi-modal fusion approaches, achieving an area under the ROC curve (ROC AUC) of 0.70-0.76 and Average Precision (AP) of 0.15-0.54 in 2-8 year horizons. Progression within 1 year was better predicted with a multi-modal method using X-ray, structural, and compositional MR images -- ROC AUC of 0.76(0.04), AP of 0.13(0.04) -- or via clinical data. Our follow-up analysis generally shows that prediction from the imaging data is more accurate for post-traumatic subjects, and we further investigate which subject subgroups may benefit the most. The present study provides novel insights into multi-modal imaging of KOA and brings a unified data-driven framework for studying its progression in an end-to-end manner, providing new tools for the design of more efficient clinical trials. The source code of our framework and the pre-trained models are made publicly available.

Excitable media are ubiquitous in nature, and in such systems the local excitation tends to self-organize in traveling waves, or in rotating spiral-shaped patterns in two or three spatial dimensions. Examples include waves during a pandemic or electrical scroll waves in the heart. Here we show that such phenomena can be extended to a space of four or more dimensions and propose that connections of excitable elements in a network setting can be regarded as additional spatial dimensions. Numerical simulations are performed in four dimensions using the FitzHugh-Nagumo model, showing that the vortices rotate around a two-dimensional surface which we define as the superfilament. Evolution equations are derived for general superfilaments of co-dimension two in an N -dimensional space and their equilibrium configurations are proven to be minimal surfaces. We suggest that biological excitable systems, such as the heart or brain which have non-local connections can be regarded, at least partially, as multidimensional excitable media and discuss further possible studies in this direction.

Adversarial examples are transferable between different models. In our paper, we propose to use this property for multi-step domain adaptation. In unsupervised domain adaptation settings, we demonstrate that replacing the source domain with adversarial examples to $\mathcal{H} \Delta \mathcal{H}$-divergence can improve source classifier accuracy on the target domain. Our method can be connected to most domain adaptation techniques. We conducted a range of experiments and achieved improvement in accuracy on Digits and Office-Home datasets.

It was shown that adversarial examples improve object recognition. But what about their opposite side, easy examples? Easy examples are samples that the machine learning model classifies correctly with high confidence. In our paper, we are making the first step toward exploring the potential benefits of using easy examples in the training procedure of neural networks. We propose to use an auxiliary batch normalization for easy examples for the standard and robust accuracy improvement.

Many physical, chemical and biological processes rely on intrinsic oscillations to employ resonance responses to external stimuli of certain frequency. Such resonance phenomena in biological systems are typically explained by one of two mechanisms: either a classical linear resonance of harmonic oscillator, or entrainment and phase locking of nonlinear limit cycle oscillators subjected to periodic forcing. Here, we discover a nonlinear mechanism, which does not require intrinsic oscillations. Instead, the resonant frequency dependence arises from coupling between an excitable and a monostable region of the medium. This composite system is endowed with emergent bistability between a stable steady state and stable spatiotemporal oscillations. The resonant transition from stable state to oscillatory state is induced by waves of particular frequency travelling through the medium. This transition to the spatiotemporal oscillatory state requires accumulation of multiple waves, resulting in the exclusion of lower frequencies. The cutting off of high frequencies is realized by damping of wave amplitude in the monostable zone and then by activating amplitude sensitive dynamics in the monostable units. We demonstrate this new resonance mechanism in a simplistic reaction-diffusion model. Also, we reveal this collective resonance mechanism in in-vitro experiments and detailed biophysical simulations representing a major type of arrhythmia. We further demonstrate, both experimentally and theoretically, that the ongoing spatiotemporal oscillations, such as ectopic activity in cardiac tissue, can be stopped by travelling waves of high frequency. Overall, we claim the universality of this resonance mechanism in a broad class of nonlinear biophysical systems. Specifically, we hypothesize that such phenomena could be found in neuronal systems as an alternative to traditional resonant processes.

We present a novel algorithm for domain adaptation using optimal transport. In domain adaptation, the goal is to adapt a classifier trained on the source domain samples to the target domain. In our method, we use optimal transport to map target samples to the domain named source fiction. This domain differs from the source but is accurately classified by the source domain classifier. Our main idea is to generate a source fiction by c-cyclically monotone transformation over the target domain. If samples with the same labels in two domains are c-cyclically monotone, the optimal transport map between these domains preserves the class-wise structure, which is the main goal of domain adaptation. To generate a source fiction domain, we propose an algorithm that is based on our finding that adversarial attacks are a c-cyclically monotone transformation of the dataset. We conduct experiments on Digits and Modern Office-31 datasets and achieve improvement in performance for simple discrete optimal transport solvers for all adaptation tasks.

Accurate prediction of knee osteoarthritis (KOA) progression from structural MRI has a potential to enhance disease understanding and support clinical trials. Prior art focused on manually designed imaging biomarkers, which may not fully exploit all disease-related information present in MRI scan. In contrast, our method learns relevant representations from raw data end-to-end using Deep Learning, and uses them for progression prediction. The method employs a 2D CNN to process the data slice-wise and aggregate the extracted features using a Transformer. Evaluated on a large cohort (n=4,866), the proposed method outperforms conventional 2D and 3D CNN-based models and achieves average precision of $0.58\pm0.03$ and ROC AUC of $0.78\pm0.01$. This paper sets a baseline on end-to-end KOA progression prediction from structural MRI. Our code is publicly available at https://github.com/MIPT-Oulu/OAProgressionMR., Comment: $\copyright$ 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works

We report on the fabrication of fractal dendrites by laser induced melting of aluminum alloys. We target boron carbide (B4C) that is one of the most effective radiation-absorbing materials which is characterised by a low coefficient of thermal expansion. Due to the high fragility of B4C crystals we were able to introduce its nanoparticles into a stabilization aluminum matrix of AA385.0. The high intensity laser field action led to the formation of composite dendrite structures under the effect of local surface melting. The modelling of the dendrite cluster growth confirms its fractal nature and sheds light on the pattern behavior of the resulting quasicrystal structure., Comment: 8 pages, 3 figures

Uncertainty quantification (UQ) is a vital step in using mathematical models and simulations to take decisions. The field of cardiac simulation has begun to explore and adopt UQ methods to characterise uncertainty in model inputs and how that propagates through to outputs or predictions. In this perspective piece we draw attention to an important and under-addressed source of uncertainty in our predictions -- that of uncertainty in the model structure or the equations themselves. The difference between imperfect models and reality is termed model discrepancy, and we are often uncertain as to the size and consequences of this discrepancy. Here we provide two examples of the consequences of discrepancy when calibrating models at the ion channel and action potential scales. Furthermore, we attempt to account for this discrepancy when calibrating and validating an ion channel model using different methods, based on modelling the discrepancy using Gaussian processes (GPs) and autoregressive-moving-average (ARMA) models, then highlight the advantages and shortcomings of each approach. Finally, suggestions and lines of enquiry for future work are provided., Comment: This version is published in Philosophical Transactions of the Royal Society A; Updated in response to reviewer comments, including: added details to the introduction, fixed mathematical notations for clarity, and moved the original Table 3 to the supplement to avoid confusion

The quality of the incoming experimental data has a significant importance for both analysis and running the experiment. The main point of the Baikal-GVD DQM system is to monitor the status of the detector and obtained data on the run-by-run based analysis. It should be fast enough to be able to provide analysis results to detector shifter and for participation in the global multi-messaging system., Comment: Contribution from the Baikal-GVD Collaboration presented at the 36th International Cosmic Ray Conference, Madison, Wisconsin, USA, 24 July - 1 August 2019. Proceeding: PoS-ICRC2019-0874

We present data on the luminescence of the Baikal water medium collected with the Baikal-GVD neutrino telescope. This three-dimensional array of light sensors allows the observation of time and spatial variations of the ambient light field. We report on observation of an increase of luminescence activity in 2016 and 2018. On the contrary, we observed practically constant optical noise in 2017. An agreement has been found between two independent optical noise data sets. These are data collected with online monitoring system and the trigger system of the cluster., Comment: Contribution from the Baikal-GVD Collaboration presented at the 36th International Cosmic Ray Conference, Madison, Wisconsin, USA, 24 July - 1 August 2019. Proceeding: PoS-ICRC2019-0875

Currently in Lake Baikal, a new generation neutrino telescope is being deployed: the deep underwater Cherenkov detector of a cubic-kilometer scale Baikal-GVD. Completion of the first stage of the telescope construction is planned for 2021 with the implementation of 9 clusters. Each cluster is a completely independent unit in all the aspects: triggering, calibration, data transfer, etc. A high-energy particle might leave its trace in more than a single cluster. To be able to merge events caused by such a particle in more clusters, the appropriate inter-cluster time synchronization is vital., Comment: Contribution from the Baikal-GVD Collaboration presented at the 36th International Cosmic Ray Conference, Madison, Wisconsin, USA, 24 July - 1 August 2019. Proceeding: PoS-ICRC2019-0877

A cubic kilometer scale neutrino telescope Baikal-GVD is currently under construction in Lake Baikal. Baikal-GVD is designed to detect Cerenkov radiation from products of astrophysical neutrino interactions with Baikal water by a lattice of photodetectors submerged between the depths of 1275 and 730 m. The detector components are mounted on flexible strings and can drift from their initial positions upwards to tens of meters. This introduces positioning uncertainty which translates into a timing error for Cerenkov signal registration. A spatial positioning system has been developed to resolve this issue. In this contribution, we present the status of this system, results of acoustic measurements and an estimate of positioning error for an individual component., Comment: Contribution from the Baikal-GVD Collaboration presented at the 36th International Cosmic Ray Conference, Madison, Wisconsin, USA, 24 July - 1 August 2019. Proceeding: PoS-ICRC2019-1012

In April 2019, the Baikal-GVD collaboration finished the installation of the fourth and fifth clusters of the neutrino telescope Baikal-GVD. Momentarily, 1440 Optical Modules (OM) are installed in the largest and deepest freshwater lake in the world, Lake Baikal, instrumenting 0.25 cubic km of sensitive volume. The Baikal-GVD is thus the largest neutrino telescope on the Northern Hemisphere. The first phase of the detector construction is going to be finished in 2021 with 9 clusters, 2592 OMs in total, however the already installed clusters are stand-alone units which are independently operational and taking data from their commissioning. Huge number of channels as well as strict requirements for the precision of the time and charge calibration (ns, p.e.) make calibration procedures vital and very complex tasks. The inter cluster time calibration is performed with numerous calibration systems. The charge calibration is carried out with a Single Photo-Electron peak. The various data acquired during the last three years in regular and special calibration runs validate successful performance of the calibration systems and of the developed calibration techniques. The precision of the charge calibration has been improved and the time dependence of the obtained calibration parameters have been cross-checked. The multiple calibration sources verified a 1.5 - 2.0 ns precision of the in-situ time calibrations. The time walk effect has been studied in detail with in situ specialized calibration runs., Comment: Contribution from the Baikal-GVD Collaboration presented at the 36th International Cosmic Ray Conference, Madison, Wisconsin, USA, 24 July - 1 August 2019. Proceeding: PoS-ICRC2019-0878

Multi-messenger astronomy is a powerful tool to study the physical processes driving the non-thermal Universe. A combination of observations in cosmic rays, neutrinos, photons of all wavelengths and gravitational waves is expected. The alert system of the Baikal-GVD detector under construction will allow for a fast, on-line reconstruction of neutrino events recorded by the Baikal-GVD telescope and - if predefined conditions are satisfied - for the formation of an alert message to other communities. The preliminary results of searches for high-energy neutrinos in coincidence with GW170817/GRB170817A using the cascade mode of neutrino detection are discussed. Two Baikal-GVD clusters were operating during 2017. The zenith angle of NGC 4993 at the detection time of the GW170817 was 93.3 degrees. No events spatially coincident with GRB170817A were found. Given the non-detection of neutrino events associated with GW170817, upper limits on the neutrino fluence were established., Comment: Contribution from the Baikal-GVD Collaboration presented at the 36th International Cosmic Ray Conference, Madison, Wisconsin, USA, 24 July - 1 August 2019. Proceeding: PoS-ICRC2019-1013

Baikal-GVD is a next generation, kilometer-scale neutrino telescope currently under construction in Lake Baikal. GVD is formed by multi-megaton sub-arrays (clusters) and is designed for the detection of astrophysical neutrino fluxes at energies from a few TeV up to 100 PeV. The design of the Baikal-GVD allows one to search for astrophysical neutrinos with flux values measured by IceCube already at early phases of the array construction. We present here preliminary results of the search for high-energy neutrinos via the cascade mode with the Baikal-GVD neutrino telescope., Comment: Contribution from the Baikal-GVD Collaboration presented at the 36th International Cosmic Ray Conference, Madison, Wisconsin, USA, 24 July - 1 August 2019. Proceeding: PoS-ICRC2019-0873

A significant progress in the construction and operation of the Baikal Gigaton Volume Detector in Lake Baikal, the largest and deepest freshwater lake in the world, is reported. The effective volume of the detector for neutrino initiated cascades of relativistic particles with energy above 100 TeV has been increased up to about 0.25 cubic kilometer. This unique scientific facility, the largest operating neutrino telescope in Northern Hemisphere, allows already to register two to three events per year from astrophysical neutrinos with energies exceeding 100 TeV. Preliminary results obtained with data recorded in 2016-2018 are announced. Multimessenger approach is used to relate finding of cosmic neutrinos with those of classical astronomers, with X-ray or gamma-ray observations and the gravitational wave events., Comment: Contribution from the Baikal-GVD Collaboration presented at the 36th International Cosmic Ray Conference, Madison, Wisconsin, USA, 24 July - 1 August 2019. Proceeding: PoS-ICRC2019-1011

In a computational study we reveal a novel dynamical instability of excitation waves in the heartmuscle. The instability manifests itself as gradual local increase in the duration of the actionpotential which causes formation and hypermeandering of spiral waves. The mechanism is causedby stretch-activated currents that cause wave front-tail collisions and beat to beat elongation of theaction potential duration due to biexcitability. We discuss the importance of the instability for theonset and dynamics of cardiac arrhythmias.

Degeneration of articular cartilage (AC) is actively studied in knee osteoarthritis (OA) research via magnetic resonance imaging (MRI). Segmentation of AC tissues from MRI data is an essential step in quantification of their damage. Deep learning (DL) based methods have shown potential in this realm and are the current state-of-the-art, however, their robustness to heterogeneity of MRI acquisition settings remains an open problem. In this study, we investigated two modern regularization techniques -- mixup and adversarial unsupervised domain adaptation (UDA) -- to improve the robustness of DL-based knee cartilage segmentation to new MRI acquisition settings. Our validation setup included two datasets produced by different MRI scanners and using distinct data acquisition protocols. We assessed the robustness of automatic segmentation by comparing mixup and UDA approaches to a strong baseline method at different OA severity stages and, additionally, in relation to anatomical locations. Our results showed that for moderate changes in knee MRI data acquisition settings both approaches may provide notable improvements in the robustness, which are consistent for all stages of the disease and affect the clinically important areas of the knee joint. However, mixup may be considered as a recommended approach, since it is more computationally efficient and does not require additional data from the target acquisition setup.

In many oscillatory or excitable systems, dynamical patterns emerge which are stationary or periodic up in a moving frame of reference. Examples include traveling waves or spiral waves in chemical systems or cardiac tissue. We present a unified theoretical framework for the drift of such patterns under small external perturbations, in terms of overlap integrals between the perturbation and the adjoint critical eigenfunctions of the linearised operator (i.e. `response functions'). For spiral waves, the finite radius of the spiral tip trajectory as well as spiral wave meander are taken into account. Different coordinates systems can be chosen, depending on whether one wants to predict the motion of the spiral wave tip, the time-averaged tip path, or the center of the meander flower. The framework is applied to analyse the drift of a meandering spiral wave in a constant external field in different regimes.

The Advanced LIGO and Advanced Virgo observatories recently discovered gravitational waves from a binary neutron star inspiral. A short gamma-ray burst (GRB) that followed the merger of this binary was also recorded by Fermi-GBM and INTEGRAL, indicating particle acceleration by the source. The precise location of the event was determined by optical detections of emission following the merger. We searched for high-energy neutrinos from the merger in the TeV - 100 PeV energy range using Baikal-GVD. No neutrinos directionally coincident with the source were detected within $\pm$500 s around the merger time, as well as during a 14-day period after the GW detection. We derived 90% confidence level upper limits on the neutrino fluence from GW170817 during a $\pm$500 s window centered on the GW trigger time, and a 14-day window following the GW signal under the assumption of an $E^{-2}$ neutrino energy spectrum., Comment: 4 pages, 4 figures

Baikal-GVD is a next generation, kilometer-scale neutrino telescope under construction in Lake Baikal. It is designed to detect astrophysical neutrino fluxes at energies from a few TeV up to 100 PeV. GVD is formed by multi-megaton subarrays (clusters). The array construction started in 2015 by deployment of a reduced-size demonstration cluster named "Dubna". The first cluster in its baseline configuration was deployed in 2016, the second in 2017 and the third in 2018. The full scale GVD will be an array of ~10000 light sensors with an instrumented volume of about 2 cubic km. The first phase (GVD-1) is planned to be completed by 2020-2021. It will comprise 8 clusters with 2304 light sensors in total. We describe the design of Baikal-GVD and present selected results obtained in 2015-2017., Comment: 9 pages, 8 figures. Conference proceedings for QUARKS2018

Rotors are functional reentry sources identified in clinically relevant cardiac arrhythmias, such as ventricular and atrial fibrillation. Ablation targeting rotor sites has resulted in arrhythmia termination. Recent clinical, experimental and modelling studies demonstrate that rotors are often anchored around fibrotic scars or regions with increased fibrosis. However the mechanisms leading to abundance of rotors at these locations are not clear. The current study explores the hypothesis whether fibrotic scars just serve as anchoring sites for the rotors or whether there are other active processes which drive the rotors to these fibrotic regions. Rotors were induced at different distances from fibrotic scars of various sizes and degree of fibrosis. Simulations were performed in a 2D model of human ventricular tissue and in a patient-specific model of the left ventricle of a patient with remote myocardial infarction. In both the 2D and the patient-specific model we found that without fibrotic scars, the rotors were stable at the site of their initiation. However, in the presence of a scar, rotors were eventually dynamically anchored from large distances by the fibrotic scar via a process of dynamical reorganization of the excitation pattern. This process coalesces with a change from polymorphic to monomorphic ventricular tachycardia., Comment: 16 pages, 7 figures

We have investigated the temperature dependence of the magnetic susceptibility $\chi(T)$ of rare-earth cobaltites RCoO$_3$ (R= La, Pr, Nd, Sm, Eu) in the temperature range $4.2-300$ K and also the influence of hydrostatic pressure up to 2 kbar on their susceptibility at fixed temperatures $T=78 $ and 300 K. The specific dependence $\chi(T)$ observed in LaCoO$_3$ and the anomalously large pressure effect (d ln $\chi$/d$P\sim -100$ Mbar$^{-1}$ for $T = 78$ K) are analyzed in the framework of a two-level model with energy levels difference $\Delta$. The ground state of the system is assumed to be nonmagnetic with the zero spin of Co$^{3+}$ ions, and magnetism at a finite temperature is determined by the excited magnetic spin state. The results of the analysis, supplemented by theoretical calculations of the electronic structure of LaCoO$_3$, indicate a significant increase in $\Delta$ with a decrease in the unit cell volume under the hydrostatic pressure. In the series of RCoO$_3$ (R= Pr, Nd, Sm, Eu) compounds, the volume of crystal cell decreases monotonically due to a decrease in the radius of R$^{3+}$ ions. This leads to an increase in the relative energy $\Delta$ of the excited state (the chemical pressure effect), which manifests itself in a decrease in the contribution of cobalt ions to the magnetic susceptibility at a fixed temperature, and also in a decrease in the hydrostatic pressure effect on the susceptibility of RCoO$_3$ compounds, which we have observed at $T=300$ K.

Here I introduce basic methods of qualitative analysis of differential equations used in mathematical biology for people with minimal mathematical background.

The effect of pressure on magnetic properties of LaCoO$_3$ is studied experimentally and theoretically. The pressure dependence of magnetic susceptibility $\chi$ of LaCoO$_3$ is obtained by precise measurements of $\chi$ as a function of the hydrostatic pressure $P$ up to 2 kbar in the temperature range from 78 K to 300 K. A pronounced magnitude of the pressure effect is found to be negative in sign and strongly temperature dependent. The obtained experimental data are analysed by using a two-level model and DFT+U calculations of the electronic structure of LaCoO$_3$. In particular, the fixed spin moment method was employed to obtain a volume dependence of the total energy difference $\Delta$ between the low spin and the intermediate spin states of LaCoO$_3$. Analysis of the obtained experimental $\chi(P)$ dependence within the two-level model, as well as our DFT+U calculations, have revealed the anomalous large decrease in the energy difference $\Delta$ with increasing of the unit cell volume. This effect, taking into account a thermal expansion, can be responsible for the temperatures dependence of $\Delta$, predicting its vanishing near room temperature., Comment: 7 pages, 9 figures

Disorganized electrical activity in the heart leads to sudden cardiac death. To what extent can this electrical turbulence be viewed as classical fluid turbulence,which is an important central problem in modern physics? We investigate,for the first time,via extensive DNSs,the statistical properties of spiral-and scroll-wave turbulence in two- and three-dimensional excitable media by using approaches employed in studies of classical turbulence. We use the Panfilov and the Aliev-Panfilov mathematical models for cardiac tissue. We show that once electrical-wave turbulence has been initiated,there is a forward cascade,in which spirals or scrolls form,interact,and break to yield a turbulent state that is statistically steady and,far away from boundaries,is statistically homogeneous and isotropic. For the transmembrane potential $V$ and the slow recovery variable $g$,which define our models,we define $E_V(k)$ and $E_g(k)$,the electrical-wave analogs of the fluid energy spectrum $E(k)$ in fluid turbulence. We show that $E_V(k)$ and $E_g(k)$ are spread out over several decades in $k$. Thus spiral- and scroll-wave turbulence involves a wide range of spatial scales. $E_V(k)$ and $E_g(k)$ show approximate power laws,in some range of $k$, however,their exponents cannot be determined as accurately as their fluid-turbulence counterparts. The dimensionless ratio $L/\lambda$ is a convenient control parameter like the Reynolds number for fluid turbulence,where $L$ is the linear size of the domain and $\lambda$ the wavelength of a plane wave in the medium. By comparing several other statistical properties for spiral- and scroll-wave turbulence with their fluid-turbulence counterparts,we show that,although spiral- and scroll-wave turbulence have some statistical properties like those of fluid turbulence,overall these types of turbulence are special and differ in important ways from fluid turbulence., Comment: 16 pages, 24 figures, One table

The structure and physical properties of superconducting compounds Y(La)-Ba(Sr)-Cu-O are studied, the compounds being prepared by the method of cryogenic dispersion of a charge consisting of premix oxides and carbonates. Electrical conductivity and critical current density of the superconductors are measured over a wide temperature range of 10~$mK$ to 300~$K$. Degradation of the superconductor critical parameters in time and structural characteristics, magnetic susceptibility, heat capacity and acoustic properties are studied, and current-voltage characteristics are determined., Comment: 9 pages, 11 figures

In present analysis we complete search for a dark matter signal with the Baikal neutrino telescope NT200 from potential sources in the sky. We use five years of data and look for neutrinos from dark matter annihilations in the dwarfs spheroidal galaxies in the Southern hemisphere and the Large Magellanic Cloud known as the largest and close satellite galaxy of the Milky Way. We do not find any excess in observed data over expected background from the atmospheric neutrinos towards the LMC or any of tested 22 dwarfs. We perform a joint likelihood analysis on the sample of five selected dwarfs and found a concordance of the data with null hypothesis of the background-only observation. We derive 90% CL upper limits on the cross section of annihilating dark matter particles of mass between 30 GeV and 10 TeV into several channels both in our combined analysis of the dwarfs and in a particular analysis towards the LMC., Comment: 15 pages, 11 figures

Nonlinear waves of the reaction-diffusion (RD) type occur in many biophysical systems, including the heart, where they initiate cardiac contraction. Such waves can form vortices called scroll waves, which result in the onset of life-threatening cardiac arrhythmias. The dynamics of scroll waves is affected by the presence of inhomogeneities, which, in a very general way, can be of \textit{(i)} ionic type, i.e., they affect the reaction part, or \textit{(ii)} conduction type, i.e., they affect the diffusion part of an RD equation. We demostrate, for the first time, by using a state-of-the-art, anatomically realistic model of the pig heart, how differences in the geometrical and biophysical nature of such inhomogeneities can influence scroll-wave dynamics in different ways. Our study reveals that conduction-type inhomogeneities become increasingly important at small length scales, i.e., in the case of multiple, randomly distributed, obstacles in space at the cellular scale ($0.2-0.4{\rm mm}$). Such configurations can lead to scroll-wave break up. In contrast, ionic inhomogeneities, affect scroll-wave dynamics significantly at large length scales, when these inhomogeneities are localized in space at the tissue level ($5-10$ mm). In such configurations, these inhomogeneities can (a) attract scroll waves, by pinning them to the heterogeneity, or (b) lead to scroll-wave breakup.

Rotating scroll waves are self-organising patterns which are found in many oscillating or excitable systems. Here we show that quasi-periodic (meandering) scroll waves, which include the rotors that organise cardiac arrhythmias, exhibit filament tension when averaged over the meander cycle. With strong filament curvature or medium thickness gradients, however, scroll wave dynamics are governed by phase-locked drift instead of filament tension. Our results are validated in computational models of cycloidal meander and a cardiac tissue model with linear core., Comment: accepted for publication in Physical Review Letters (December 2017)

Magnetic susceptibility $\chi$ of the polycrystalline sample of samarium monosulfide was measured as a function of the hydrostatic pressure $P$ up to 2 kbar at liquid nitrogen and room temperatures using a pendulum-type magnetometer. A pronounced magnitude of the pressure effect is found to be positive in sign and strongly temperature dependent: the pressure derivatives of $\chi$, d\,ln$\chi$/d$P$, are $6.3\pm0.5$ and $14.2\pm1$ Mbar$^{-1}$ at 300 and 78 K, respectively. The obtained experimental results are discussed within phenomenological approaches., Comment: 5 pages, 4 figures

We present a mapping of a two-dimensional system of interacting bosons in a strong perpendicular magnetic field to an equivalent system of interacting bosons on the square lattice in the absence of the field. The mapping utilizes a magnetic Bloch and the corresponding magnetic Wannier single-particle basis in the lowest Landau level. By construction, the ground states of the resulting model of interacting bosons on the square lattice are gapped fractionalized liquids or gapless Bose metal states with broken time reversal symmetry at specific rational filling fractions., Comment: 6+ pages, 2 figures, added references, published version

We reanalyze the dataset collected during the years 1998--2003 by the deep underwater neutrino telescope NT200 in the lake Baikal with the low energy threshold (10 GeV) in searches for neutrino signal from dark matter annihilations near the center of the Milky Way. Two different approaches are used in the present analysis: counting events in the cones around the direction towards the Galactic Center and the maximum likelihood method. We assume that the dark matter particles annihilate dominantly over one of the annihilation channels $b\bar{b}$, $W^+W^-$, $\tau^+\tau^-$, $\mu^+\mu^-$ or $\nu\bar{\nu}$. No significant excess of events towards the Galactic Center over expected neutrino background of atmospheric origin is found and we derive 90% CL upper limits on the annihilation cross section of dark matter., Comment: 15 pages, 14 figures, published version

In April 2015 the demonstration cluster "Dubna" was deployed and started to take data in Lake Baikal. This array is the first cluster of the cubic kilometer scale Gigaton Volume Detector (Baikal-GVD), which is constructed in Lake Baikal. In this contribution we will review the design and status of the array., Comment: 6 pages, 8 figures, EPS-HEP 2015 conference

The electronic energy structures and magnetic properties of iron-based compounds with group VI elements (FeTe, BiFeO$_3$, SrFe$_{12}$O$_{19}$ and SrCoTiFe$_{10}$O$_{19}$) are studied using the density functional theory (DFT) methods. Manifestations of different types of chemical bonds in magnetism of these compounds are studied theoretically. Calculations of electronic structures of these systems were performed using the generalized gradient approximation (GGA) for description of the exchange and correlation effects within DFT. For SrFe$_{12}$O$_{19}$ and SrCoTiFe$_{10}$O$_{19}$ hexaferrites the GGA+$U$ method was also employed to deal with strongly correlated 3$d$-electrons. The calculations have revealed distinctive features of electronic structure of the investigated iron-based compounds with strongly correlated 3$d$-electrons, which can be responsible for their peculiar structural and magnetic properties., Comment: 7 pages, 8 figures

Magnetic susceptibility $\chi$ of Bi$_{2-x}$Mn$_{x}$Se$_3$ ($x = 0.01-0.2$) was measured in the temperature range $4.2-300$ K. For all the samples, a Curie-Weiss behaviour of $\chi(T)$ was revealed with effective magnetic moments of Mn ions corresponding to the spin value S=5/2, which couple antiferromagnetically with the paramagnetic Curie temperature $\Theta\sim -50$ K. In addition, for the samples of nominal composition $x$ = 0.1 and 0.2 the effect of a hydrostatic pressure $P$ up to 2 kbar on $\chi$ has been measured at fixed temperatures 78 and 300 K that allowed to estimate the pressure derivative of $\Theta$ to be d$\Theta$/d$P\sim-0.8$ K/kbar. Based on the observed behaviour of $\Theta$ with varied Mn concentration and pressure, a possible mechanism of interaction between localized Mn moments is discussed., Comment: 7 pages, 6 figures

We analyse sensitivity of the gigaton volume telescope Baikal-GVD for detection of neutrino signal from dark matter annihilations or decays in the Galactic Center. Expected bounds on dark matter annihilation cross section and its lifetime are found for several annihilation/decay channels., Comment: 5 pages, 8 figures

We have analyzed a data set taken over 2.76 years live time with the Baikal neutrino telescope NT200. The goal of the analysis is to search for neutrinos from dark matter annihilation in the center of the Sun. Apart from the conventional annihilation channels $b\bar{b}$, $W^+W^-$ and $\tau^+\tau^-$ we consider also the annihilation of dark matter particles into monochromatic neutrinos. From the absence of any excess of events from the direction of the Sun over the expected background, we derive 90% upper limits on the fluxes of muons and muon neutrinos from the Sun, as well as on the elastic cross sections of dark matter scattering on protons., Comment: 14 pages, 8 figures

We report on a study of the density response in doped Weyl semimetals or Weyl metals in the presence of an external magnetic field. We show that the applied field leads to a contribution to the density response, which is topological in nature and is closely related to the phenomenon of chiral anomaly. This contribution manifests in a nonanalytic nonclassical correction to the electronic compressibility and the plasmon frequency, proportional to the magnitude of the magnetic field. Such a nonanalytic correction to the electronic compressibility is a smoking-gun feature of Weyl metals, which clearly distinguishes them from ordinary ferromagnetic metals., Comment: 7+ pages, 1 figure, published version

Chirality is one of the most fundamental properties of many physical, chemical and biological systems. However, the mechanisms underlying the onset and control of chiral symmetry are largely understudied. We investigate possibility of chirality control in a chemical excitable system (the BZ reaction) by application of a chiral (rotating) electric field using the Oregonator model. We find that unlike previous findings, we can achieve the chirality control not only in the field rotation direction, but also opposite to it, depending on the field rotation frequency. To unravel the mechanism, we further develop a comprehensive theory of frequency synchronization based on the response function approach. We find that this problem can be described by the Adler equation and show phase-locking phenomena, known as the Arnold tongue. Our theoretical predictions are in good quantitative agreement with the numerical simulations and provide a solid basis for chirality control in excitable media., Comment: 21 pages with 9 figures; update references; to appear in J. Chem. Phys

Possible influence of spatially inhomogeneous distribution of strontium impurities on the temperature of antiferromagnetic (AFM) ordering in ceramic samples La2-xSrxCuO4 has been revealed., Comment: 6 pages, 3 figures 16-th International Meeting "Ordering in Minerals and Alloys", 12-17 September 2013, Rostov-on Don, Tuapse, Russia V 1, pp 124-127

The influence of uniform pressures $P$ up to 5 kbar on the superconducting transition temperature $T_c$ was studied for the FeSe$_{1-x}$Te$_x$ ($x=0$, 0.85, 0.88 and 0.9) system. For the first time, we observed a change in sign of the pressure effect on $T_c$ when going from FeSe to tellurium rich alloys. This has allowed to specify the pressure derivative d$T_c$/d$P$ for the system as a function of composition. The observed dependence was compared with results of the {\em ab initio} calculations of electronic structure and magnetism of FeSe, FeTe and FeSe$_{0.5}$Te$_{0.5}$, and also with our recent experimental data on pressure effects on magnetic susceptibilities of FeSe and FeTe compounds in the normal state. This comparison demonstrates a competing interplay between superconductivity and magnetism in tellurium rich FeSe$_{1-x}$Te$_x$ compounds, Comment: 7 pages, 6 figures

The Prototyping phase of the BAIKAL-GVD project has been started in April 2011 with the deployment of a three string engineering array which comprises all basic elements and systems of the Gigaton Volume Detector (GVD) in Lake Baikal. In April 2012 the version of engineering array which comprises the first full-scale string of the GVD demonstration cluster has been deployed and operated during 2012. The first stage of the GVD demonstration cluster which consists of three strings is deployed in April 2013. We review the Prototyping phase of the BAIKAL-GVD project and describe the configuration and design of the 2013 engineering array., Comment: Proceedings of the RICAP 2013 Conference, Rome, Italy, May 22-24, 2013, 7 pages, 12 figures

Rotating spiral waves organize spatial patterns in chemical, physical and biological excitable systems. Factors affecting their dynamics such as spatiotemporal drift are of great interest for par- ticular applications. Here, we propose a quantitative description for spiral wave dynamics on curved surfaces which shows that for a wide class of systems, including the BZ reaction and anisotropic cardiac tissue, the Ricci curvature scalar of the surface is the main determinant of spiral wave drift. The theory provides explicit equations for spiral wave drift direction, drift velocity and the period of rotation. Depending on the parameters, the drift can be directed to the regions of either maximal or minimal Ricci scalar curvature, which was verified by direct numerical simulations., Comment: preprint before submission to Physical Review E