On-site residence time in a driven diffusive system: violation and recovery of mean-field

We investigate simple one-dimensional driven diffusive systems with open boundaries. We are interested in the average on-site residence time defined as the time a particle spends on a given site before moving on to the next site. Using mean-field theory, we obtain an analytical expression for the on-site residence times. By comparing the analytic predictions with numerics, we demonstrate that the mean-field significantly underestimates the residence time due to the neglect of time correlations in the local density of particles. The temporal correlations are particularly long-lived near the average shock position, where the density changes abruptly from low to high. By using Domain wall theory (DWT), we obtain highly accurate estimates of the residence time for different boundary conditions. We apply our analytical approach to residence times in a totally asymmetric exclusion process (TASEP), TASEP coupled to Langmuir kinetics (TASEP + LK), and TASEP coupled to mutually interactive LK (TASEP + MILK). The high accuracy of our predictions is verified by comparing these with detailed Monte Carlo simulations

Exact solutions of a particle in a box with a delta function potential: The factorization method

We use the factorization method to find the exact eigenvalues and eigenfunctions for a particle in a box with the delta function potential $V(x)=\lambda\delta(x-x_{0})$. We show that the presence of the potential results in the discontinuity of the corresponding ladder operators. The presence of the delta function potential allows us to obtain the full spectrum in the first step of the factorization procedure even in the weak coupling limit $\lambda\to 0$.Comment: 8 pages, 2 figures, to appear in American Journal of Physic

Expression and localization of aquaporin water channels in adult pig urinary bladder

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Strain-driven criticality underlies nonlinear mechanics of fibrous networks

Networks with only central force interactions are floppy when their average connectivity is below an isostatic threshold. Although such networks are mechanically unstable, they can become rigid when strained. It was recently shown that the transition from floppy to rigid states as a function of simple shear strain is continuous, with hallmark signatures of criticality [Sharma et al., Nature Phys. 12, 584 (2016)]. The nonlinear mechanical response of collagen networks was shown to be quantitatively described within the framework of such mechanical critical phenomenon. Here, we provide a more quantitative characterization of critical behavior in subisostatic networks. Using finite-size scaling we demonstrate the divergence of strain fluctuations in the network at well-defined critical strain. We show that the characteristic strain corresponding to the onset of strain stiffening is distinct from but related to this critical strain in a way that depends on critical exponents. We confirm this prediction experimentally for collagen networks. Moreover, we find that the apparent critical exponents are largely independent of the spatial dimensionality. With subisostaticity as the only required condition, strain-driven criticality is expected to be a general feature of biologically relevant fibrous networks

Predictive models for Alzheimer's disease diagnosis and MCI identification: The use of cognitive scores and artificial intelligence algorithms

The paper presents a comprehensive study on predictive models for Alzheimer's disease (AD) and mild cognitive impairment (MCI) diagnosis, implementing a combination of cognitive scores and artificial intelligence algorithms. The research includes detailed analyses of clinical and demographic variables such as age, education, and various cognitive and functional scores, investigating their distributions and correlations with AD and MCI. The study utilizes several machine-learning classifiers, comparing their performance through metrics like accuracy, precision, and area under the ROC curve (AUC). Key findings include the influence of gender on AD prevalence, the potential protective effect of education, and the significance of functional decline and cognitive performance scores in the models. The results demonstrate the effectiveness of ensemble methods and the robustness of the models across different data subsets, highlighting the potential of artificial intelligence in enhancing diagnostic accuracy for Alzheimer's disease and mild cognitive impairment

How does the lower urinary tract contribute to bladder sensation? ICI-RS 2023

Aim: Bladder sensation is critical for coordinating voluntary micturition to maintain healthy bladder function. Sensations are initiated by the activation of sensory afferents that innervate throughout the bladder wall. However, the physiological complexity that underlies the initiation of bladder sensory signaling in health and disease remains poorly understood. This review summarises the latest knowledge of the mechanisms underlying the generation of bladder sensation and identifies key areas for future research. Methods: Experts in bladder sensory signaling reviewed the literature on how the lower urinary tract contributes to bladder sensation and identified key research areas for discussion at the 10th International Consultation on Incontinence—Research Society. Results: The importance of bladder sensory signals in maintaining healthy bladder function is well established. However, better therapeutic management of bladder disorders with exaggerated bladder sensation, including overactive bladder syndrome (OAB) and interstitial cystitis/bladder pain syndrome (IC/BPS) is limited by a lack of knowledge in a number of key research areas including; the contribution of different nerves (pudendal, pelvic, hypogastric) to filling sensations in health and disease; the relative contribution of stretch sensitive (muscular) and stretch-insensitive (mucosal) afferents to bladder sensation in health and disease; the direct and indirect contributions of the muscularis mucosae to bladder contraction and sensation; and the impact of manipulating urothelial release factors on bladder sensation. Conclusion: Disturbances in bladder sensory signaling can have severe consequences for bladder sensation and function including the development of OAB and IC/BPS. Advancing therapeutic treatments for OAB and IC/BPS requires a deeper understanding of the mechanisms underlying the generation of bladder sensation, and key areas for future research have been identified

Multiview classification and dimensionality reduction of scalp and intracranial EEG data through tensor factorisation

Electroencephalography (EEG) signals arise as a mixture of various neural processes that occur in different spatial, frequency and temporal locations. In classification paradigms, algorithms are developed that can distinguish between these processes. In this work, we apply tensor factorisation to a set of EEG data from a group of epileptic patients and factorise the data into three modes; space, time and frequency with each mode containing a number of components or signatures. We train separate classifiers on various feature sets corresponding to complementary combinations of those modes and components and test the classification accuracy of each set. The relative influence on the classification accuracy of the respective spatial, temporal or frequency signatures can then be analysed and useful interpretations can be made. Additionaly, we show that through tensor factorisation we can perform dimensionality reduction by evaluating the classification performance with regards to the number mode components and by rejecting components with insignificant contribution to the classification accuracy

Motivations and reasons for women attending a Breast Self-Examination training program: A qualitative study

<p>Abstract</p> <p>Background</p> <p>Breast cancer is a major threat to Taiwanese women's health. Despite the controversy surrounding the effectiveness of breast self-examination (BSE) in reducing mortality, BSE is still advocated by some health departments. The aim of the study is to provide information about how women decide to practice BSE and their experiences through the training process. Sixty-six women aged 27-50 were recruited.</p> <p>Methods</p> <p>A descriptive study was conducted using small group and individual in-depth interviews to collect data, and using thematic analysis and constant comparison techniques for data analysis.</p> <p>Results</p> <p>It was found that a sense of self-security became an important motivator for entering BSE training. The satisfaction in obtaining a sense of self-security emerged as the central theme. Furthermore, a ladder motivation model was developed to explain the participants' motivations for entering BSE training. The patterns of motivation include opportunity taking, clarifying confusion, maintaining health, and illness monitoring, which were connected with the risk perception for breast cancer.</p> <p>Conclusions</p> <p>We recognize that the way women decide to attend BSE training is influenced by personal and social factors. Understanding the different risk assessments women rely on in making their health decisions is essential. This study will assist researchers and health professionals to gain a better understanding of alternative ways to deal with breast health, and not to be limited by the recommendations of the health authorities.</p