Computational Protein Design Using AND/OR Branch-and-Bound Search

The computation of the global minimum energy conformation (GMEC) is an important and challenging topic in structure-based computational protein design. In this paper, we propose a new protein design algorithm based on the AND/OR branch-and-bound (AOBB) search, which is a variant of the traditional branch-and-bound search algorithm, to solve this combinatorial optimization problem. By integrating with a powerful heuristic function, AOBB is able to fully exploit the graph structure of the underlying residue interaction network of a backbone template to significantly accelerate the design process. Tests on real protein data show that our new protein design algorithm is able to solve many prob- lems that were previously unsolvable by the traditional exact search algorithms, and for the problems that can be solved with traditional provable algorithms, our new method can provide a large speedup by several orders of magnitude while still guaranteeing to find the global minimum energy conformation (GMEC) solution.Comment: RECOMB 201

On the composition conjecture for a class of rigid systems

In this paper, we prove that for a class of rigid systems the Composition Conjecture is correct. We show that the Moments Condition is the sufficient and necessary conditions for these rigid systems to have a center at origin point. By the obtained conclusions we can derive all the focal values of these higher order polynomial differential systems and their expressions are more succinct and beautiful

Iron line spectroscopy of black holes in asymptotically safe gravity

We study the iron line shape expected in the reflection spectrum of accretion disks around black holes in asymptotically safe gravity. We compare the results of our simulations with the iron line shapes expected in the reflection spectrum of accretion disks around Kerr black holes to see if the technique of iron line spectroscopy can be used as a tool to test asymptotically safe gravity. Our analysis shows that current X-ray facilities are surely unable to distinguish black holes in asymptotically safe gravity from black holes in Einstein's gravity. In the case of the next generation of X-ray missions, which promise to provide unprecedented high quality data, the question remains open because it cannot be addressed within our simplified model.Comment: 9 pages, 6 figures. v2: refereed versio

Strong variational sufficiency of nonsmooth optimization problems on Riemannian manifolds

The Riemannian augmented Lagrangian method (RALM) is proposed to solve the nonsmooth optimization problems on Riemannian manifolds. However, the local convergence rate of this algorithm still remains unknown without imposing any constraint qualifications. In this paper, we introduce the manifold variational sufficient condition and show that its strong version is equivalent to the manifold strong second-order sufficient condition (M-SSOSC) in some cases. More importantly, we formulate a local dual problem based on this condition, consequently establishing the R-linear convergence rate of RALM. Furthermore, the validity of the semismooth Newton method for solving the RALM subproblem is demonstrated under the M-SSOSC

On the composition conjecture for a class of rigid systems

In this paper, we prove that for a class of rigid systems the Composition Conjecture is correct. We show that the Moments Condition is the sufficient and necessary conditions for these rigid systems to have a center at origin point. By the obtained conclusions we can derive all the focal values of these higher order polynomial differential systems and their expressions are more succinct and beautiful

The association between neuroendocrine/glucose metabolism and clinical outcomes and disease course in different clinical states of bipolar disorders

ObjectiveThe treatment of bipolar disorder (BD) remains challenging. The study evaluated the impact of the hypothalamic–pituitary–adrenal (HPA) axis/hypothalamic–pituitary-thyroid (HPT) axis and glucose metabolism on the clinical outcomes in patients with bipolar depression (BD-D) and manic bipolar (BD-M) disorders.MethodsThe research design involved a longitudinal prospective study. A total of 500 BD patients aged between 18 and 65 years treated in 15 hospitals located in Western China were enrolled in the study. The Young Mania Rating Scale (YMRS) and Montgomery and Asberg Depression Rating Scale (MADRS) were used to assess the BD symptoms. An effective treatment response was defined as a reduction in the symptom score of more than 25% after 12 weeks of treatment. The score of symptoms was correlated with the homeostatic model assessment of insulin resistance (HOMA-IR) index, the HPA axis hormone levels (adrenocorticotropic hormone (ACTH) and cortisol), and the HPT axis hormone levels (thyroid stimulating hormone (TSH), triiodothyronine (T3), thyroxine (T4), free triiodothyronine (fT3), and free thyroxine (fT4)).ResultsIn the BD-M group, the YMRS was positively correlated with baseline T4 (r = 0.349, p = 0.010) and fT4 (r = 0.335, p = 0.013) and negatively correlated with fasting insulin (r = −0.289, p = 0.013). The pre-treatment HOMA-IR was significantly correlated with adverse course (p = 0.045, OR = 0.728). In the BD-D group, the baseline MADRS was significantly positively correlated with baseline fT3 (r = 0.223, p = 0.032) and fT4 (r = 0.315, p = 0.002), while baseline T3 (p = 0.032, OR = 5.071) was significantly positively related to treatment response.ConclusionThe HPT axis and glucose metabolism were closely associated with clinical outcomes at 12 weeks in both BD-D and BD-M groups. If confirmed in further longitudinal studies, monitoring T3 in BD-D patients and HOMA-IR for BD-M could be used as potential treatment response biomarkers

ParticleNet and its application on CEPC Jet Flavor Tagging

Identification of quark flavor is essential for collider experiments in high-energy physics, relying on the flavor tagging algorithm. In this study, using a full simulation of the Circular Electron Positron Collider (CEPC), we investigated the flavor tagging performance of two different algorithms: ParticleNet, originally developed at CMS, and LCFIPlus, the current flavor tagging algorithm employed at CEPC. Compared to LCFIPlus, ParticleNet significantly enhances flavor tagging performance, resulting in a significant improvement in benchmark measurement accuracy, i.e., a 36% improvement for $\nu\bar{\nu}H\to c\bar{c}$ measurement and a 75% improvement for $|V_{cb}|$ measurement via W boson decay when CEPC operates as a Higgs factory at the center-of-mass energy of 240 GeV and integrated luminosity of 5.6 $ab^{-1}$. We compared the performance of ParticleNet and LCFIPlus at different vertex detector configurations, observing that the inner radius is the most sensitive parameter, followed by material budget and spatial resolution

An Analysis of the Cause of Privacy Paradox among SNS Users: take Chinese College Students as an Example

It has been proved that the privacy paradox does exist, yet the cause of the phenomenon remains vague. This article tries to analyze the [Inserted: s]cause of privacy paradox phenomenon on SNS (WeChat) among Chinese college students based on Privacy Calculus Theory and the TPB model and introduces two new factors: the credibility of SNS and the cost of protecting privacy. Through a questionnaire and interview survey,[Inserted: a ] our result shows that there is no significant correlation between users’ privacy concerns and the intention of privacy disclosure. While the more users trust the SNS platform, the more possibility they tend to disclose their private information[Inserted: te], and the cost of privacy protection can somehow weaken the relationship between the intention and the actual behavior. Therefore, [Inserted: ship]by increasing SNS\u27s credibility, users tend to disclose more personal information to SNS providers, which may improve the competitiveness of SNSs and contribute to their sustainable development

Jet origin identification and measurement of rare hadronic decays of Higgs boson at e+e−e^+e^- collider

We propose to identify the jet origin using deep learning tools for experiments at the high energy frontier, where jet origins are categorized into 5 species of quarks, i.e., $b,c,s,u,d$, 5 species of anti-quarks, i.e., $\bar{b},\bar{c},\bar{s},\bar{u},\bar{d}$, and gluons. Using simulated physics events at the Circular Electron Positron Collider and the ParticleNet algorithm, we quantify the performance of jet origin identification using an 11-dimensional confusion matrix. This matrix exhibits flavor tagging efficiencies of 91% for $b$ and $\bar{b}$, 80% for $c$ and $\bar{c}$, and 64% for $s$ and $\bar{s}$ quarks, as well as jet charge misidentification rates of 18% for $b$ and $\bar{b}$, 7% for $c$ and $\bar{c}$, and 16% for $s$ and $\bar{s}$ quarks, respectively. We use this method to determine the upper limits on branching ratios of Higgs rare hadronic decays, specifically for $s\bar{s}$, $u\bar{u}$, and $d\bar{d}$, as well as for decays via flavor-changing neutral current, such as $sb$, $sd$, $db$, $cu$. We conclude that these Higgs decay branching ratios could be measured with typical upper limits of 0.02%-0.1% at 95% confidence level at CEPC nominal parameters. For the $H\rightarrow s \bar{s}$ decay, this upper limit corresponds to three times the standard model prediction