The Asymptotic Behaviours of a Class of Neutral Delay Fractional-Order Pantograph Differential Equations

By using fractional calculus and the summation by parts formula in this paper, the asymptotic behaviours of solutions of nonlinear neutral fractional delay pantograph equations with continuous arguments are investigated. The asymptotic estimates of solutions for the equation are obtained, which may imply asymptotic stability of solutions. In the end, a particular case is provided to illustrate the main result and the speed of the convergence of the obtained solutions

Review on the methods of automatic liver segmentation from abdominal images

Automatic liver segmentation from abdominal images is challenging on the aspects of segmentation accuracy, automation and robustness. There exist many methods of liver segmentation and ways of categorisingthem. In this paper, we present a new way of summarizing the latest achievements in automatic liver segmentation.We categorise a segmentation method according to the image feature it works on, therefore better summarising the performance of each category and leading to finding an optimal solution for a particular segmentation task. All the methods of liver segmentation are categorized into three main classes including gray level based method, structure based method and texture based method. In each class, the latest advance is reviewed with summary comments on the advantages and drawbacks of each discussed approach. Performance comparisons among the classes are given along with the remarks on the problems existed and possible solutions. In conclusion, we point out that liver segmentation is still an open issue and the tendency is that multiple methods will be employed to-gether to achieve better segmentation performance

Urea Transporter Physiology Studied in Knockout Mice

In mammals, there are two types of urea transporters; urea transporter (UT)-A and UT-B. The UT-A transporters are mainly expressed in kidney epithelial cells while UT-B demonstrates a broader distribution in kidney, heart, brain, testis, urinary tract, and other tissues. Over the past few years, multiple urea transporter knockout mouse models have been generated enabling us to explore the physiological roles of the different urea transporters. In the kidney, deletion of UT-A1/UT-A3 results in polyuria and a severe urine concentrating defect, indicating that intrarenal recycling of urea plays a crucial role in the overall capacity to concentrate urine. Since UT-B has a wide tissue distribution, multiple phenotypic abnormalities have been found in UT-B null mice, such as defective urine concentration, exacerbated heart blockage with aging, depression-like behavior, and earlier male sexual maturation. This review summarizes the new insights of urea transporter functions in different organs, gleaned from studies of urea transporter knockout mice, and explores some of the potential pharmacological prospects of urea transporters

A Novel Method for the Absolute Pose Problem with Pairwise Constraints

Absolute pose estimation is a fundamental problem in computer vision, and it is a typical parameter estimation problem, meaning that efforts to solve it will always suffer from outlier-contaminated data. Conventionally, for a fixed dimensionality d and the number of measurements N, a robust estimation problem cannot be solved faster than O(N^d). Furthermore, it is almost impossible to remove d from the exponent of the runtime of a globally optimal algorithm. However, absolute pose estimation is a geometric parameter estimation problem, and thus has special constraints. In this paper, we consider pairwise constraints and propose a globally optimal algorithm for solving the absolute pose estimation problem. The proposed algorithm has a linear complexity in the number of correspondences at a given outlier ratio. Concretely, we first decouple the rotation and the translation subproblems by utilizing the pairwise constraints, and then we solve the rotation subproblem using the branch-and-bound algorithm. Lastly, we estimate the translation based on the known rotation by using another branch-and-bound algorithm. The advantages of our method are demonstrated via thorough testing on both synthetic and real-world dataComment: 10 pages, 7figure

PREVALENCE AND RISK FACTORS OF E-CIGARETTES AND NRT USE AMONG HIV-INFECTED AND UNINFECTED MEN WHO HAVE SEX WITH MEN

Background: The prevalence of e-cigarettes and NRT use is increasing among general population in recent years. With the shifting in HIV-infection paradigm, describing the prevalence and pattern among men with high risk of HIV infection is important in chronic disease prevention and improving their life expectancy and quality. Objective: The aims of this study were 1) to provide a profile of current smoking, e-cigarettes use and NRT use; 2) to identify risk factors associated with initiation of e-cigarettes and NRT use among men with high risk of HIV infection. Design: A longitudinal study based on The Multicenter AIDS Cohort Study (MACS). A total of 2285 men were included with follow-ups starting from June 2015. Results: The prevalence of current smokers was constant from 2015 to 2017. Men without HIV had a similar prevalence as the general US adult men (16.7%-17.5%), at between 13.5% and 16.1%. Men with HIV had a higher prevalence at between 23.0% and 26.1%. The prevalence of e-cigarettes (ranged between 5.2% to 9.3% for HIV infected men and between 3.1% and 5.7% for uninfected men) and NRT use (ranged between 5.0% and 8.2% for infected men and between 3.5% and 4.6% for uninfected men.) did not differ by HIV status. The prevalence of e-cigarettes use was about 20% in current smokers, 4% in former smokers, and 0.3% for non-smokers. The prevalence of NRT use was about 12% in current smokers and about 3% in former smokers. Ever e-cigarettes and NRT users had a higher cumulative pack-year compared to never users. After adjusting for age, race, Hispanic ethnicity, education level, serostatus, detectable viral load, CD4 count and cumulative pack-years, the cumulative incidence risk (RR) ratio of e-cigarettes use was 0.98 (95% CI, 0.97-0.99) for one year increase in age; 1.46 (95% CI, 1.01-2.10) for high school level education compared to 4 years’ college and above, 1.55 (95% CI, 1.03-2.35) for less than high school education compared to 4 years’ college and above, 1.09 (95% CI, 0.98-1.23) for HIV infection, and 1.02 (95% CI, 0.99-1.04) for 50% increase in cumulative pack-years. The cumulative incidence risk ratio of NRT use is 0.95(95% CI, 0.95-0.97) for one-year increase in age, 1.32 (95%CI, 1.00-1.73) for being back, 1.48 (95% CI, 1.02-2.15) for high school level education compared to 4 years’ college and above, 1.31(95% CI, 0.99-1.72) and 1.10 (95% CI, 1.07-1.14) for 50% increase in cumulative pack-years. Conclusion: The prevalence of current smoking was higher for men with HIV than men without. E-cigarettes and NRT use was mostly common among current smokers, the prevalence did not differ by HIV status. E-cigarettes and NRT users had a longer cumulative pack-years compared to never users. Risk factors associated with e-cigarettes and NRT use included younger age, lower education level, HIV infection and longer cumulative pack-years. Black race is associated with NRT use

The PostModer Hermits

Metropolitan cities to grow at unfathomable rates, forming a new scale of geography know as Megaregions. And as these settlements continue to develop with the principal focus on the consequences of economy and environment, the psychological, mental health of the inhabitants becomes neglected. Japan, the archetypal example of a highly developed country, despite its economic and technological advantages, has been plagued by social isolation, suicides, and mental health issues among its people. With 541,000 young Japanese labeled as hikikomori, a term describing young people who isolate themselves in their rooms for months or years at a time, their memories of the city begs stimulation and their stories needs attention. The Post-modern Hermits is the project that seeks to redefine the relationship between people, architecture and time within the context of Japan. Using openness as a conceptual design strategy to form a memorial park which rejects the absolute completion. I intend to develop my project to share similar characteristics and features of Hejduk’s work adapted through the chosen site of Aokigahara forest. Within the Aokigahara forest, follies will take shape according to the existing morphologies. With hybrid as the principal design formula, proposed follies seek to combine basic tectonics of found urban fabrics, collective memory fragments of Tokyo and the stories of Hikikomori to present facts as a way to call attention to the stories of the victims and to rethink how such social issues are dealt with

Margin Maximization in Attention Mechanism

Attention mechanism is a central component of the transformer architecture which led to the phenomenal success of large language models. However, the theoretical principles underlying the attention mechanism are poorly understood, especially its nonconvex optimization dynamics. In this work, we explore the seminal softmax-attention model $f(\boldsymbol{X})=\langle \boldsymbol{Xv}, \texttt{softmax}(\boldsymbol{XWp})\rangle$, where, $\boldsymbol{X}$ is the token sequence and $(\boldsymbol{v},\boldsymbol{W},\boldsymbol{p})$ are tunable parameters. We prove that running gradient descent on $\boldsymbol{p}$, or equivalently $\boldsymbol{W}$, converges in direction to a max-margin solution that separates $\textit{locally-optimal}$ tokens from non-optimal ones. This clearly formalizes attention as a token separation mechanism. Remarkably, our results are applicable to general data and precisely characterize $\textit{optimality}$ of tokens in terms of the value embeddings $\boldsymbol{Xv}$ and problem geometry. We also provide a broader regularization path analysis that establishes the margin maximizing nature of attention even for nonlinear prediction heads. When optimizing $\boldsymbol{v}$ and $\boldsymbol{p}$ simultaneously with logistic loss, we identify conditions under which the regularization paths directionally converge to their respective hard-margin SVM solutions where $\boldsymbol{v}$ separates the input features based on their labels. Interestingly, the SVM formulation of $\boldsymbol{p}$ is influenced by the support vector geometry of $\boldsymbol{v}$. Finally, we verify our theoretical findings via numerical experiments and provide insights