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Collective behaviors such as swarming, chemical signaling, and clustering are fundamental to biological microorganisms, enabling hierarchical colony formation, coordinated motion, and enhanced nutrient accessibility crucial for their survival. Over the past few decades, extensive research has been dedicated to unraveling the mechanisms underlying these diverse collective patterns through experimental model systems. Among these, active droplets have emerged as valuable synthetic analogs, effectively replicating key biological attributes and serving as ideal platforms for investigating collective phenomena. This research explores the collective behavior of 4-Cyano-4-pentyl-biphenyl (5CB) oil droplets across varying P\'eclet ($Pe$) numbers. At high $Pe$, droplets exhibit a pusher mode of propulsion and form dynamic chain-like patterns. Decreasing $Pe$ enhances repulsive interactions among droplets, resulting in the inhibition of clustering. In the low $Pe$ regime, their repulsive interactions predominated by chemical field lead to the emergence of an ordered structure. Furthermore, we illustrate how active droplets efficiently navigate within a soft structured environment. These findings contribute to our comprehension of self-organized phenomena in active matter systems and provide insights for designing strategies for controlled locomotion in intricate fluidic environments., Comment: 16 pages (12 main, 4 supporting), 12 figures (7 main, 5 supporting)

The LHCb experiment at CERN has been upgraded for the Run 3 operation of the Large Hadron Collider (LHC). A new concept of tracking detector based on Scintillating Fibres (SciFi) read out with multichannel silicon photomultipliers (SiPMs) was installed during its upgrade. One of the main challenges the SciFi tracker will face during the Run 4 operation of the LHC is the higher radiation environment due to fast neutrons, where the SiPMs are located. To cope with the increase in radiation, cryogenic cooling with liquid nitrogen is being investigated as a possible solution to mitigate the performance degradation of the SiPMs induced by radiation damage. Thus, a detailed performance study of different layouts of SiPM arrays produced by Fondazione Bruno Kessler (FBK) and Hamamatsu Photonics K.K. is being carried out. These SiPMs have been designed to operate at cryogenic temperatures. Several SiPMs have been tested in a dedicated cryogenic setup down to 100 K. Key performance parameters such as breakdown voltage, dark count rate, photon detection efficiency, gain and direct cross-talk are characterized as a function of the temperature. The main results of this study are going to be presented here., Comment: Prepared for submission to JINST Proceedings 6th International Workshop on New Photon-Detector

A novel concept to enhance the photo-detection efficiency (PDE) of silicon photomultipliers (SiPMs) has been applied and remarkable positive results can be reported. This concept uses arrays of microlenses to cover every second SiPM pixel in a checkerboard arrangement and aims to deflect the light from the dead region of the pixelised structure towards the active region in the center of the pixel. The PDE is improved up to 24%, external cross-talk is reduced by 40% compared to a flat epoxy layer, and single photon time resolution is improved. This detector development is conducted in the context of the next generation LHCb scintillating fibre tracker located in a high radiation environment with a total of 700'000 detector channels. The simulation and measurement results are in good agreement and will be discussed in this work., Comment: 8 pages, 11 figures

We present a knowledge augmentation strategy for assessing the diagnostic groups and gait impairment from monocular gait videos. Based on a large-scale pre-trained Vision Language Model (VLM), our model learns and improves visual, textual, and numerical representations of patient gait videos, through a collective learning across three distinct modalities: gait videos, class-specific descriptions, and numerical gait parameters. Our specific contributions are two-fold: First, we adopt a knowledge-aware prompt tuning strategy to utilize the class-specific medical description in guiding the text prompt learning. Second, we integrate the paired gait parameters in the form of numerical texts to enhance the numeracy of the textual representation. Results demonstrate that our model not only significantly outperforms state-of-the-art methods in video-based classification tasks but also adeptly decodes the learned class-specific text features into natural language descriptions using the vocabulary of quantitative gait parameters. The code and the model will be made available at our project page: https://lisqzqng.github.io/GaitAnalysisVLM/., Comment: MICCAI 2024

Dense non-Brownian suspensions exhibit a spectacular and abrupt drop in viscosity under change of shear direction, as revealed by shear inversions (reversals) or orthogonal superposition. Here, we introduce an experimental setup to systematically explore their response to shear rotations, where one suddenly rotates the principal axes of shear by an angle $\theta$, and measure the shear stresses with a bi-axial force sensor. Our measurements confirm the genericness of the transient decrease of the resistance to shear under unsteady conditions. Moreover, the orthogonal shear stress, which vanishes in steady state, takes non-negligible values with a rich $\theta$-dependence, changing qualitatively with solid volume fraction $\phi$, and resulting in a force that tends to reduce or enhance the direction of flow for small or large $\phi$. These experimental findings are confirmed and rationalized by particle-based numerical simulations and a recently proposed constitutive model. We show that the rotation angle dependence of the orthogonal stress results from a $\phi$-dependent interplay between hydrodynamic and contact stresses., Comment: Accepted in Phys. Rev. Lett

Deep learning (DL) methods have in recent years yielded impressive results in medical imaging, with the potential to function as clinical aid to radiologists. However, DL models in medical imaging are often trained on public research cohorts with images acquired with a single scanner or with strict protocol harmonization, which is not representative of a clinical setting. The aim of this study was to investigate how well a DL model performs in unseen clinical data sets---collected with different scanners, protocols and disease populations---and whether more heterogeneous training data improves generalization. In total, 3117 MRI scans of brains from multiple dementia research cohorts and memory clinics, that had been visually rated by a neuroradiologist according to Scheltens' scale of medial temporal atrophy (MTA), were included in this study. By training multiple versions of a convolutional neural network on different subsets of this data to predict MTA ratings, we assessed the impact of including images from a wider distribution during training had on performance in external memory clinic data. Our results showed that our model generalized well to data sets acquired with similar protocols as the training data, but substantially worse in clinical cohorts with visibly different tissue contrasts in the images. This implies that future DL studies investigating performance in out-of-distribution (OOD) MRI data need to assess multiple external cohorts for reliable results. Further, by including data from a wider range of scanners and protocols the performance improved in OOD data, which suggests that more heterogeneous training data makes the model generalize better. To conclude, this is the most comprehensive study to date investigating the domain shift in deep learning on MRI data, and we advocate rigorous evaluation of DL models on clinical data prior to being certified for deployment., Comment: 11 pages, 3 figures

We perform local measurements of both the shear rate and the particle fraction to study viscous resuspension in non-Brownian suspensions. A suspension of PMMA spherical particles dispersed in a lighter Newtonian fluid (Triton X100) is sheared in a vertical Couette cell. The vertical profiles of the particle volume fraction are measured for Shields numbers ranging from 10 --3 to 1, and the variation in the particle normal stress in the vorticity direction of the particle fraction is deduced.

A method is proposed to measure the photon polarisation parameter $\lambda_\gamma$ in $b\to s\gamma$ transitions using an amplitude analysis of $B\to K\pi\pi\gamma$ decays. Simplified models of the $K\pi\pi$ i system are used to simulate $B^+ \to K^+\pi^-\pi^+\gamma$ and $B^0\to K^+\pi^-\pi^0$ decays, validate the amplitude analysis method, and demonstrate the feasibility of a measurement of the $\lambda_\gamma$ parameter irrespective of the model parameters. Similar sensitivities to $\lambda_\gamma$ are obtained with both the charged and neutral hadronic systems. In the absence of any background and distortion due to experimental effects, the statistical uncertainty expected from an analysis of $B^+ \to K^+\pi^-\pi^+\gamma$ decays in an LHCb data set corresponding to an integrated luminosity of $9\,$fb$^{-1}$ is estimated to be $0.009$. A similar measurement using $B^0\to K^+\pi^-\pi^0$ decays in a Belle II data sample corresponding to an integrated luminosity of $5\,$ab$^{-1}$ would lead to a statistical uncertainty of $0.018$

IntroductionThe free and cued selective reminding test is used to identify memory deficits in mild cognitive impairment and demented patients. It allows assessing three processes: encoding, storage, and recollection of verbal episodic memory.MethodsWe investigated the neural correlates of these three memory processes in a large cohort study. The Memento cohort enrolled 2323 outpatients presenting either with subjective cognitive decline or mild cognitive impairment who underwent cognitive, structural MRI and, for a subset, fluorodeoxyglucose--positron emission tomography evaluations.ResultsEncoding was associated with a network including parietal and temporal cortices; storage was mainly associated with entorhinal and parahippocampal regions, bilaterally; retrieval was associated with a widespread network encompassing frontal regions.DiscussionThe neural correlates of episodic memory processes can be assessed in large and standardized cohorts of patients at risk for Alzheimer's disease. Their relation to pathophysiological markers of Alzheimer's disease remains to be studied.

This paper reports experiments on the shear transient response of concentrated non-Brownian suspensions. The shear viscosity of the suspensions is measured using a wide-gap Couette rheometer equipped with a Particle Image Velocimetry (PIV) device that allows measuring the velocity field. The suspensions made of PMMA particles (31$\mu$m in diameter) suspended in a Newtonian index- and density-matched liquid are transparent enough to allow an accurate measurement of the local velocity for particle concentrations as high as 50%. In the wide-gap Couette cell, the shear induced particle migration is evidenced by the measurement of the time evolution of the flow profile. A peculiar radial zone in the gap is identified where the viscosity remains constant. At this special location, the local particle volume fraction is taken to be the mean particle concentration. The local shear transient response of the suspensions when the shear flow is reversed is measured at this point where the particle volume fraction is well defined. The local rheological measurements presented here confirm the macroscopic measurements of Gadala-Maria and Acrivos (1980). After shear reversal, the viscosity undergoes a step-like reduction, decreases slower and passes through a minimum before increasing again to reach a plateau. Upon varying the particle concentration, we have been able to show that the minimum and the plateau viscosities do not obey the same scaling law with respect to the particle volume fraction. These experimental results are consistent with the scaling predicted by Mills and Snabre (2009) and with the results of numerical simulation performed on random suspensions [Sierou and Brady (2001)]. The minimum seems to be associated with the viscosity of an isotropic suspension, or at least of a suspension whose particles do not interact through non-hydrodynamic forces, while the plateau value would correspond to the viscosity of a suspension structured by the shear where the non-hydrodynamic forces play a crucial role.