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Abridged: We present the first observation of the HCO+(1-0) and HCN(1-0) emission in the northern filaments of Centaurus A with ALMA. HCO+(1-0) is detected in 9 clumps of the Horseshoe complex, with similar velocities as the CO(1-0) emission. Conversely, the HCN(1-0) is not detected and we derive upper limits on the flux. At a resolution of ~40 pc, the line ratio of the velocity-integrated intensities I_HCO+/I_CO varies between 0.03 and 0.08, while I_HCO+/I_HCN is higher than unity with an average lower limit of 1.51. These ratios are significantly higher than what is observed in nearby star-forming galaxies. Moreover, the ratio I_HCO+/I_CO decreases with increasing CO integrated intensity, contrary to what is observed in the star-forming galaxies. This indicates that the HCO+ emission is enhanced and may not arise from dense gas within the Horseshoe complex. This hypothesis is strengthened by the average line ratio I_HCN/I_CO<0.03 which suggests that the gas density is rather low. Using non-LTE, large velocity gradient modelling with RADEX, we explored two possible phases of the gas, that we call "diffuse" and "dense", and are characterised by a significant difference in the HCO+ relative abundance to CO, respectively N_HCO+/N_CO=10^-3 and 3x10^-5. The average CO(1-0) and HCO+(1-0) integrated intensities and the upper limit on HCN(1-0) are compatible with both "diffuse" and "dense" gas. The spectral setup of the present observations also covers the SiO(2-1). While undetected, the upper limit on SiO(2-1) is not compatible with the RADEX predictions for the "dense" gas. We conclude that the 9 molecular clouds detected in HCO+(1-0) are likely dominated by diffuse molecular gas. While the exact origin of the HCO+(1-0) emission remains to be investigated, it is likely related to the energy injection within the molecular gas that prevents gravitational collapse and star formation., Comment: Accepted for publication in A&A, 6 pages+appendices

In order to solve problems of practical importance, quantum computers will likely need to incorporate quantum error correction, where a logical qubit is redundantly encoded in many noisy physical qubits. The large physical-qubit overhead typically associated with error correction motivates the search for more hardware-efficient approaches. Here, using a microfabricated superconducting quantum circuit, we realize a logical qubit memory formed from the concatenation of encoded bosonic cat qubits with an outer repetition code of distance $d=5$. The bosonic cat qubits are passively protected against bit flips using a stabilizing circuit. Cat-qubit phase-flip errors are corrected by the repetition code which uses ancilla transmons for syndrome measurement. We realize a noise-biased CX gate which ensures bit-flip error suppression is maintained during error correction. We study the performance and scaling of the logical qubit memory, finding that the phase-flip correcting repetition code operates below threshold, with logical phase-flip error decreasing with code distance from $d=3$ to $d=5$. Concurrently, the logical bit-flip error is suppressed with increasing cat-qubit mean photon number. The minimum measured logical error per cycle is on average $1.75(2)\%$ for the distance-3 code sections, and $1.65(3)\%$ for the longer distance-5 code, demonstrating the effectiveness of bit-flip error suppression throughout the error correction cycle. These results, where the intrinsic error suppression of the bosonic encodings allows us to use a hardware-efficient outer error correcting code, indicate that concatenated bosonic codes are a compelling paradigm for reaching fault-tolerant quantum computation., Comment: Comments on the manuscript welcome!

Ionic liquids have been suggested as new engineering fluids, namely in the area of heat transfer, as alternatives to current biphenyl and diphenyl oxide, alkylated aromatics and dimethyl polysiloxane oils, which degrade above 200 {\deg}C and pose some environmental problems. Recently, we have proposed 1-ethyl-3-methylimidazolium methanesulfonate, [$C_{2}mim$][$CH_{3}SO_{3}$], as a new heat transfer fluid, because of its thermophysical and toxicological properties. However, there are some interesting points raised in this work, namely the possibility of the existence of liquid metastability below the melting point (303 K) or second order-disorder transitions ($\lambda$-type) before reaching the calorimetric freezing point. This paper analyses in more detail this zone of the phase diagram of the pure fluid, by reporting accurate thermal-conductivity measurements between 278 and 355 K with an estimated uncertainty of 2% at a 95% confidence level. A new value of the melting temperature is also reported, $T_{melt}$ = 307.8 $\pm$ 1 K. Results obtained support liquid metastability behaviour in the solid-phase region and permit the use of this ionic liquid at a heat transfer fluid at temperatures below its melting point. Thermal conductivity models based on Bridgman theory and estimation formulas were also used in this work, failing to predict the experimental data within its uncertainty.

Iterative Bleaching Extends multipleXity (IBEX) is a versatile method for highly multiplexed imaging of diverse tissues. Based on open science principles, we created the IBEX Knowledge-Base, a resource for reagents, protocols and more, to empower innovation., Comment: 8 pages, 1 figure, 9 references

Tensor networks and quantum computation are two of the most powerful tools for the simulation of quantum many-body systems. Rather than viewing them as competing approaches, here we consider how these two methods can work in tandem. We introduce a novel algorithm that combines tensor networks and quantum computation to produce results that are more accurate than what could be achieved by either method used in isolation. Our algorithm is based on multiproduct formulas (MPF) - a technique that linearly combines Trotter product formulas to reduce algorithmic error. Our algorithm uses a quantum computer to calculate the expectation values and tensor networks to calculate the coefficients used in the linear combination. We present a detailed error analysis of the algorithm and demonstrate the full workflow on a one-dimensional quantum simulation problem on $50$ qubits using two IBM quantum computers: $ibm\_torino$ and $ibm\_kyiv$.

Purpose: Phosphorus Magnetic Resonance Spectroscopy (31P MRS) enables non-invasive assessment of energy metabolism, yet its application is hindered by sensitivity limitations. To overcome this, often high magnetic fields are used, leading to challenges such as spatial B_1^+ inhomogeneity and therefore the need for accurate flip angle determination in accelerated acquisitions with short repetition times (T_R). In response to these challenges, we propose a novel short T_R and look-up table-based Double-Angle Method for fast 3D 31P B_1^+ mapping (fDAM). Methods: Our method incorporates 3D weighted stack of spiral gradient echo acquisitions and a frequency-selective pulse to enable efficient B_1^+ mapping based on the phosphocreatine signal at 7T. Protocols were optimised using simulations and validated through phantom experiments. The method was validated in phantom experiments and skeletal muscle applications using a birdcage 1H/31P volume coil. Results: The results of fDAM were compared to the classical DAM (cDAM). A good correlation (r=0.94) was obtained between the two B_1^+ maps. A 3D 31P B_1^+ mapping in the human calf muscle was achieved in about 10 min using a birdcage volume coil, with a 20% extended coverage relative to that of the cDAM (24 min). fDAM also enabled the first full brain coverage 31P 3D B_1^+ mapping in approx. 10 min using a 1 Tx/ 32 Rx coil. Conclusion: fDAM is an efficient method for 31P 3D B_1^+ mapping, showing promise for future applications in rapid 31P MRSI.

The Faraday rotation effect, quantified by the Rotation Measure (RM), is a powerful probe of the large-scale magnetization of the Universe - tracing magnetic fields not only on galaxy and galaxy cluster scales but also in the intergalactic Medium (IGM; referred to as $\mathrm{RM}_{\text{IGM}}$). The redshift dependence of the latter has extensively been explored with observations. It has also been shown that this relation can help to distinguish between different large-scale magnetization scenarios. We study the evolution of this $\mathrm{RM}_{\text{IGM}}$ for different primordial magnetogenesis scenarios to search for the imprints of primordial magnetic fields (PMFs; magnetic fields originating in the early Universe) on the redshift-dependence of $\mathrm{RM}_{\text{IGM}}$. We use cosmological magnetohydrodynamic (MHD) simulations for evolving PMFs during large-scale structure formation, coupled to the light cone analysis to produce a realistic statistical sample of mock $\mathrm{RM}_{\text{IGM}}$ images. We study the predicted behavior for the cosmic evolution of $\mathrm{RM}_{\text{IGM}}$ for different correlation lengths of PMFs, and provide fitting functions for their dependence on redshifts. We compare these mock RM trends with the recent analysis of the the LOw-Frequency ARray (LOFAR) RM Grid and find that large-scale-correlated PMFs should have (comoving) strengths $\lesssim 0.75$ nanoGauss, if originated during inflation with the scale invariant spectrum and (comoving) correlation length $\sim 19$ cMpc/h or $ \lesssim 30$ nanoGauss if they originated during phase-transition epochs with the comoving correlation length $\sim 1$ cMpc/h. Our findings agree with previous observations and confirm the results of semi-analytical studies, showing that upper limits on the PMF strength decrease as their coherence scales increase., Comment: 16 pages, 9 figures, comments welcome!

This study introduces a novel knowledge enhanced tokenisation mechanism, K-Tokeniser, for clinical text processing. Technically, at initialisation stage, K-Tokeniser populates global representations of tokens based on semantic types of domain concepts (such as drugs or diseases) from either a domain ontology like Unified Medical Language System or the training data of the task related corpus. At training or inference stage, sentence level localised context will be utilised for choosing the optimal global token representation to realise the semantic-based tokenisation. To avoid pretraining using the new tokeniser, an embedding initialisation approach is proposed to generate representations for new tokens. Using three transformer-based language models, a comprehensive set of experiments are conducted on four real-world datasets for evaluating K-Tokeniser in a wide range of clinical text analytics tasks including clinical concept and relation extraction, automated clinical coding, clinical phenotype identification, and clinical research article classification. Overall, our models demonstrate consistent improvements over their counterparts in all tasks. In particular, substantial improvements are observed in the automated clinical coding task with 13\% increase on Micro $F_1$ score. Furthermore, K-Tokeniser also shows significant capacities in facilitating quicker converge of language models. Specifically, using K-Tokeniser, the language models would only require 50\% of the training data to achieve the best performance of the baseline tokeniser using all training data in the concept extraction task and less than 20\% of the data for the automated coding task. It is worth mentioning that all these improvements require no pre-training process, making the approach generalisable., Comment: 18 pages, 6 figures

PLATO (PLAnetary Transits and Oscillations of stars) is ESA's M3 mission designed to detect and characterise extrasolar planets and perform asteroseismic monitoring of a large number of stars. PLATO will detect small planets (down to <2 R_(Earth)) around bright stars (<11 mag), including terrestrial planets in the habitable zone of solar-like stars. With the complement of radial velocity observations from the ground, planets will be characterised for their radius, mass, and age with high accuracy (5 %, 10 %, 10 % for an Earth-Sun combination respectively). PLATO will provide us with a large-scale catalogue of well-characterised small planets up to intermediate orbital periods, relevant for a meaningful comparison to planet formation theories and to better understand planet evolution. It will make possible comparative exoplanetology to place our Solar System planets in a broader context. In parallel, PLATO will study (host) stars using asteroseismology, allowing us to determine the stellar properties with high accuracy, substantially enhancing our knowledge of stellar structure and evolution. The payload instrument consists of 26 cameras with 12cm aperture each. For at least four years, the mission will perform high-precision photometric measurements. Here we review the science objectives, present PLATO's target samples and fields, provide an overview of expected core science performance as well as a description of the instrument and the mission profile at the beginning of the serial production of the flight cameras. PLATO is scheduled for a launch date end 2026. This overview therefore provides a summary of the mission to the community in preparation of the upcoming operational phases.

Public policy decision making has become more complex and complicated in recent times. Some authors have attributed this to the fact that public policy decision makers now have more variables to consider in every decision more than ever before. Others have argued that the rate of civilization, globalization and information technology has made the public to be more enlightened and abreast with the activities of government and so can oppose government decisions if they are unfavourable. This tends to increase government need for more and better information in order to satisfy the public. Consequently, this paper examined the issue of fuel subsidy removal in Nigeria, the impact of the policy on the public as well as the country and the role marketing principles would have played if the Nigerian government had taken some time to investigate what should be done, how it should be done and when it should be done. It also proposed a roadmap for future policies that have direct implications for the general public., Comment: 9 Pages

This paper looks at predictability problems, i.e., wherein an agent must choose its strategy in order to optimize the predictions that an external observer could make. We address these problems while taking into account uncertainties on the environment dynamics and on the observed agent's policy. To that end, we assume that the observer 1. seeks to predict the agent's future action or state at each time step, and 2. models the agent using a stochastic policy computed from a known underlying problem, and we leverage on the framework of observer-aware Markov decision processes (OAMDPs). We propose action and state predictability performance criteria through reward functions built on the observer's belief about the agent policy; show that these induced predictable OAMDPs can be represented by goal-oriented or discounted MDPs; and analyze the properties of the proposed reward functions both theoretically and empirically on two types of grid-world problems., Comment: 10 pages, 7 figures, 2 tables

In hematology, computational models offer significant potential to improve diagnostic accuracy, streamline workflows, and reduce the tedious work of analyzing single cells in peripheral blood or bone marrow smears. However, clinical adoption of computational models has been hampered by the lack of generalization due to large batch effects, small dataset sizes, and poor performance in transfer learning from natural images. To address these challenges, we introduce DinoBloom, the first foundation model for single cell images in hematology, utilizing a tailored DINOv2 pipeline. Our model is built upon an extensive collection of 13 diverse, publicly available datasets of peripheral blood and bone marrow smears, the most substantial open-source cohort in hematology so far, comprising over 380,000 white blood cell images. To assess its generalization capability, we evaluate it on an external dataset with a challenging domain shift. We show that our model outperforms existing medical and non-medical vision models in (i) linear probing and k-nearest neighbor evaluations for cell-type classification on blood and bone marrow smears and (ii) weakly supervised multiple instance learning for acute myeloid leukemia subtyping by a large margin. A family of four DinoBloom models (small, base, large, and giant) can be adapted for a wide range of downstream applications, be a strong baseline for classification problems, and facilitate the assessment of batch effects in new datasets. All models are available at github.com/marrlab/DinoBloom.

Intraventricular vector flow mapping (iVFM) seeks to enhance and quantify color Doppler in cardiac imaging. In this study, we propose novel alternatives to the traditional iVFM optimization scheme by utilizing physics-informed neural networks (PINNs) and a physics-guided nnU-Net-based supervised approach. When evaluated on simulated color Doppler images derived from a patient-specific computational fluid dynamics model and in vivo Doppler acquisitions, both approaches demonstrate comparable reconstruction performance to the original iVFM algorithm. The efficiency of PINNs is boosted through dual-stage optimization and pre-optimized weights. On the other hand, the nnU-Net method excels in generalizability and real-time capabilities. Notably, nnU-Net shows superior robustness on sparse and truncated Doppler data while maintaining independence from explicit boundary conditions. Overall, our results highlight the effectiveness of these methods in reconstructing intraventricular vector blood flow. The study also suggests potential applications of PINNs in ultrafast color Doppler imaging and the incorporation of fluid dynamics equations to derive biomarkers for cardiovascular diseases based on blood flow., Comment: 12 pages, accepted for publication in IEEE TUFFC; camera ready corrections, corrected acknowledgments

We present the CheckMate tool for automated verification of game-theoretic security properties, with application to blockchain protocols. CheckMate applies automated reasoning techniques to determine whether a game-theoretic protocol model is game-theoretically secure, that is, Byzantine fault tolerant and incentive compatible. We describe CheckMate's input format and its various components, modes, and output. CheckMate is evaluated on 15 benchmarks, including models of decentralized protocols, board games, and game-theoretic examples.

Automated disease diagnosis using medical image analysis relies on deep learning, often requiring large labeled datasets for supervised model training. Diseases like Acute Myeloid Leukemia (AML) pose challenges due to scarce and costly annotations on a single-cell level. Multiple Instance Learning (MIL) addresses weakly labeled scenarios but necessitates powerful encoders typically trained with labeled data. In this study, we explore Self-Supervised Learning (SSL) as a pre-training approach for MIL-based AML subtype classification from blood smears, removing the need for labeled data during encoder training. We investigate the three state-of-the-art SSL methods SimCLR, SwAV, and DINO, and compare their performance against supervised pre-training. Our findings show that SSL-pretrained encoders achieve comparable performance, showcasing the potential of SSL in MIL. This breakthrough offers a cost-effective and data-efficient solution, propelling the field of AI-based disease diagnosis.

We present new ALMA observations of CO, CN, CS, HCN and HCO$^{+}$ absorption seen against the bright and compact radio continuum sources of eight massive galaxies. Combined with archival observations, they reveal two distinct populations of molecular clouds, which we identify by combining CO emission and absorption profiles to unambiguously reveal each cloud's direction of motion and likely location. In galaxy disks, we see clouds with low velocity dispersions, low line of sight velocities and a lack of any systemic inflow or outflow. In galactic cores, we find high velocity dispersion clouds inflowing at up to 550 km/s. This provides observational evidence in favour of cold accretion onto galactic centres, which likely contributes to the fuelling of active galactic nuclei. We also see a wide range in the CO(2-1)/CO(1-0) ratios of the absorption lines. This is likely the combined effect of hierarchical substructure within the molecular clouds and continuum sources which vary in size with frequency., Comment: Submitted to MNRAS

The upcoming Square Kilometer Array (SKA) will set a new standard regarding data volume generated by an astronomical instrument, which is likely to challenge widely adopted data-analysis tools that scale inadequately with the data size. The aim of this study is to develop a new source detection and characterization method for massive radio astronomical datasets based on modern deep-learning object detection techniques. For this, we seek to identify the specific strengths and weaknesses of this type of approach when applied to astronomical data. We introduce YOLO-CIANNA, a highly customized deep-learning object detector designed specifically for astronomical datasets. In this paper, we present the method and describe all the elements introduced to address the specific challenges of radio astronomical images. We then demonstrate the capabilities of this method by applying it to simulated 2D continuum images from the SKA observatory Science Data Challenge 1 (SDC1) dataset. Using the SDC1 metric, we improve the challenge-winning score by +139% and the score of the only other post-challenge participation by +61%. Our catalog has a detection purity of 94% while detecting 40 to 60% more sources than previous top-score results, and exhibits strong characterization accuracy. The trained model can also be forced to reach 99% purity in post-process and still detect 10 to 30% more sources than the other top-score methods. It is also computationally efficient, with a peak prediction speed of 500 images of 512x512 pixels per second on a single GPU. YOLO-CIANNA achieves state-of-the-art detection and characterization results on the simulated SDC1 dataset and is expected to transfer well to observational data from SKA precursors., Comment: 42 pages. Custom layout edit of the corresponding in press A&A paper

The growth of a population is often modeled as branching process where each individual at the end of its life is replaced by a certain number of offspring. An example of these branching models is the Bellman-Harris process, where the lifetime of individuals is assumed to be independent and identically distributed. Here, we are interested in the estimation of the parameters of the Bellman-Harris model, motivated by the estimation of cell division time. Lifetimes are distributed according a Gamma distribution and we follow a population that starts from a small number of individuals by performing time-resolved measurements of the population size. The exponential growth of the population size at the beginning offers an easy estimation of the mean of the lifetime. Going farther and describing lifetime variability is a challenging task however, due to the complexity of the fluctuations of non-Markovian branching processes. Using fine and recent results on these fluctuations, we describe two time-asymptotic regimes and explain how to estimate the parameters. Then, we both consider simulations and biological data to validate and discuss our method. The results described here provide a method to determine single-cell parameters from time-resolved measurements of populations without the need to track each individual or to know the details of the initial condition.

We apply the inverse Gertsenshtein effect, i.e., the graviton-photon conversion in the presence of a magnetic field, to constrain high-frequency gravitational waves (HFGWs). Using existing astrophysical measurements, we compute upper limits on the GW energy densities $\Omega_{\rm GW}$ at 16 different frequency bands. Given the observed magnetisation of galaxy clusters with field strength $B\sim\mu{\rm G}$ correlated on $\mathcal{O}(10)\,{\rm kpc}$ scales, we estimate HFGW constraints in the $\mathcal{O}(10^2)\,{\rm GHz}$ regime to be $\Omega_{\rm GW}\lesssim10^{16}$ with the temperature measurements of the Atacama Cosmology Telescope (ACT). Similarly, we conservatively obtain $\Omega_{\rm GW}\lesssim10^{13} (10^{11})$ in the $\mathcal{O}(10^2)\,{\rm MHz}$ ($\mathcal{O}(10)\,{\rm GHz}$) regime by assuming uniform magnetic field with strength $B\sim0.1\,{\rm nG}$ and saturating the excess signal over the Cosmic Microwave Background (CMB) reported by radio telescopes such as the Experiment to Detect the Global EoR Signature (EDGES), LOw Frequency ARray (LOFAR), and Murchison Widefield Array (MWA), and the balloon-borne second generation Absolute Radiometer for Cosmology, Astrophysics, and Diffuse Emission (ARCADE2) with graviton-induced photons. The upcoming Square Kilometer Array (SKA) can tighten these constraints by roughly 10 orders of magnitude, which will be a step closer to reaching the critical value of $\Omega_{\rm GW} = 1$ or the Big Bang Nucleosynthesis (BBN) bound of $\Omega_{\rm GW}\simeq1.2\times10^{-6}$. We point to future improvement of the SKA forecast and estimate that proposed CMB measurement at the level of $\mathcal{O}(10^{0-2})\,{\rm nK}$, such as Primordial Inflation Explorer (PIXIE) and Voyage 2050, are needed to viably detect stochastic backgrounds of HFGWs., Comment: 31 pages, 4 figures, 3 tables

We perform the first broadband study of Mrk421 from radio to TeV gamma rays with simultaneous measurements of the X-ray polarization from IXPE. The data were collected within an extensive multiwavelength campaign organized between May and June 2022 using MAGIC, Fermi-LAT, NuSTAR, XMM-Newton, Swift, and several optical and radio telescopes to complement IXPE. During the IXPE exposures, the measured 0.2-1 TeV flux is close to the quiescent state and ranges from 25% to 50% of the Crab Nebula without intra-night variability. Throughout the campaign, the VHE and X-ray emission are positively correlated at a $4\sigma$ significance level. The IXPE measurements unveil a X-ray polarization degree that is a factor of 2-5 higher than in the optical/radio bands; that implies an energy-stratified jet in which the VHE photons are emitted co-spatially with the X-rays, in the vicinity of a shock front. The June 2022 observations exhibit a rotation of the X-ray polarization angle. Despite no simultaneous VHE coverage being available during a large fraction of the swing, the Swift-XRT monitoring unveils an X-ray flux increase with a clear spectral hardening. It suggests that flares in high synchrotron peaked blazars can be accompanied by a polarization angle rotation, as observed in some flat spectrum radio quasars. Finally, during the polarization angle rotation, NuSTAR data reveal two contiguous spectral hysteresis loops in opposite directions (clockwise and counter-clockwise), implying important changes in the particle acceleration efficiency on $\sim$hour timescales., Comment: Accepted for publication in Astronomy & Astrophysics. 29 pages, 22 figures. Corresponding authors: Axel Arbet Engels, Felix Schmuckermaier, David Paneque

We present new ALMA CO(2-1) observations tracing $2.2 \times 10^{10}$ solar masses of molecular gas in Abell 2390's brightest cluster galaxy, where half the gas is located in a one-sided plume extending 15 kpc out from the galaxy centre. This molecular gas has a smooth and positive velocity gradient, and is receding 250 km/s faster at its farthest point than at the galaxy centre. To constrain the plume's origin, we analyse our new observations alongside existing X-ray, optical and radio data. We consider the possibility that the plume is a jet-driven outflow with lifting aided by jet inflated X-ray bubbles, is a trail of gas stripped from the main galaxy by ram pressure, or is formed of more recently cooled and infalling gas. The galaxy's star formation and gas cooling rate suggest the lifespan of its molecular gas may be low compared with the plume's age -- which would favour a recently cooled plume. Molecular gas in close proximity to the active galactic nucleus is also indicated by 250 km/s wide CO(2-1) absorption against the radio core, as well as previously detected CO(1-0) and HI absorption. This absorption is optically thick and has a line of sight velocity towards the galaxy centre of 200 km/s. We discuss simple models to explain its origin., Comment: Accepted for publication in MNRAS

The low sliding friction of articular cartilage in the major joints , which is crucial for its homeostasis and for joint health, has been attributed to lipid bilayers forming lubricious boundary layers at its surface. The robustness of such layers, and thus their lubrication efficiency at joint pressures, depends on the lipids forming them, including cholesterol, which may act to strengthen of weaken the bilayer. A systematic study using an Atomic Force Microscope (AFM) was carried out to understand the effect of cholesterol on the nanomechanical stability of two saturated phospholipids, DSPC (1,2-distearoyl-sn-glycero-3-phosphatidlycholine) and DPPC (1,2-dipalmitoyl-sn-glycero-phosphatidylcholine), that differ in acyl chain lengths. Measurements were carried out both in water and in phosphate buffer solution (PBS). The nanomechanical stability of the lipid bilayers was quantitatively evaluated by measuring the breakthrough force needed to puncture the bilayer by the AFM tip. The molar fractions of cholesterol incorporated in the bilayers were 10% and 40%. We found that for both DSPC and DPPC, cholesterol significantly decreases the mechanical stability of the bilayers in solid ordered (SO) phase. In accordance with the literature, the strengthening effect of salt on the lipid bilayers was also observed. For DPPC with 10 mol % cholesterol, the effect of tip properties and the experimental procedure parameters on the breakthrough forces were also studied. Tip radius (2 - 42 nm), material (Si, Si3N4, Au) and loading rate (40 - 1000 nm/s) were varied systematically. The values of the breakthrough forces measured were not significantly affected by any of these parameters, showing that the weakening effect of cholesterol does not result from such changes in experimental conditions. This study helps to shed light on the mechanism of physiological lubrication.