Weakly Supervised Audio Source Separation via Spectrum Energy Preserved Wasserstein Learning

Separating audio mixtures into individual instrument tracks has been a long standing challenging task. We introduce a novel weakly supervised audio source separation approach based on deep adversarial learning. Specifically, our loss function adopts the Wasserstein distance which directly measures the distribution distance between the separated sources and the real sources for each individual source. Moreover, a global regularization term is added to fulfill the spectrum energy preservation property regardless separation. Unlike state-of-the-art weakly supervised models which often involve deliberately devised constraints or careful model selection, our approach need little prior model specification on the data, and can be straightforwardly learned in an end-to-end fashion. We show that the proposed method performs competitively on public benchmark against state-of-the-art weakly supervised methods

Deacetylation of topoisomerase I is an important physiological function of E. coli CobB

Escherichia coli topoisomerase I (TopA), a regulator of global and local DNA supercoiling, is modified by Nε-Lysine acetylation. The NAD+-dependent protein deacetylase CobB can reverse both enzymatic and non-enzymatic lysine acetylation modification in E. coli. Here, we show that the absence of CobB in a ΔcobB mutant reduces intracellular TopA catalytic activity and increases negative DNA supercoiling. TopA expression level is elevated as topA transcription responds to the increased negative supercoiling. The slow growth phenotype of the ΔcobB mutant can be partially compensated by further increase of intracellular TopA level via overexpression of recombinant TopA. The relaxation activity of purified TopA is decreased by in vitro non-enzymatic acetyl phosphate mediated lysine acetylation, and the presence of purified CobB protects TopA from inactivation by such non-enzymatic acetylation. The specific activity of TopA expressed from His-tagged fusion construct in the chromosome is inversely proportional to the degree of in vivo lysine acetylation during growth transition and growth arrest. These findings demonstrate that E. coli TopA catalytic activity can be modulated by lysine acetylation-deacetylation, and prevention of TopA inactivation from excess lysine acetylation and consequent increase in negative DNA supercoiling is an important physiological function of the CobB protein deacetylase

Effects of relative orientation of the molecules on electron transport in molecular devices

Effects of relative orientation of the molecules on electron transport in molecular devices are studied by non-equilibrium Green's function method based on density functional theory. In particular, two molecular devices, with the planer Au$_{7}$ and Ag$_{3}$ clusters sandwiched between the Al(100) electrodes are studied. In each device, two typical configurations with the clusters parallel and vertical to the electrodes are considered. It is found that the relative orientation affects the transport properties of these two devices completely differently. In the Al(100)-Au$_7$-Al(100) device, the conductance and the current of the parallel configuration are much larger than those in the vertical configuration, while in the Al(100)-Ag$_{3}$-Al(100) device, an opposite conclusion is obtained

Clinical evaluation on the coaxial microincision cataract surgery in hard nuclear cataracts

AIM: To assess and compare the results of 2.2mm microincision coaxial cataract surgery(MCCS)phacoemulsification with the conventional 3.0mm MCCS in hard nuclear cataracts. METHODS: Totally 132 eyes with hard cataract(Ⅳ level and above)were randomized to two groups: 2.2mm MCCS(group 1:60 eyes)and 3.0mm MCCS(group 2:72 eyes). All patients underwent standard phacoemulsification and intraocular lens implantation surgery by one experienced surgeon. The average ultrasound power(AVE)was recorded during the operation. The incidences of capsule rupture and postoperative corneal edema were compared.Visual acuity, surgically induced astigmatism(SIA)and the descent rate of endothelial cell density were compared at intervals of 1 day, 1 month and 3 months after surgery. Statistic analysis was taken by Student's t test and Chi square test. RESULTS: There was no significant difference on the incidences of capsule rupture, postoperative corneal edema and AVE(P> 0.05)between the two groups(3.3%, 10.0%, 65.09±20.15)and(4.2%, 11.1%, 69.13±15.44). One day after the surgery, the 2.2mm MCCS group showed better uncorrected visual acuity as compared to the 3.0mm MCCS group(P < 0.05). There were no significant differences on best-corrected visual acuity on 1 month and 3 months after the surgery. There was no significant difference on the descent rate of endothelial cell density(16.54%±10.20%, 17.69%±10.65%)3 months after the surgery. One day, 1 month and 3 months after the surgery, SIA was 0.77±0.31,0.66±0.29, 0.52±0.25D in the 2.2mm MCCS group, and 1.41±0.73,0.98±0.61D,0.82±0.35D in the 3.0mm MCCS group, respectively. The differences were statistically significant. CONCLUSION: The operative safety of the 2.2mm MCCS group were the same as 3.0mm MCCS group with the hard nuclear cataracts. The 2.2mm MCCS phacoemulsification could significantly reduce SIA and get better earlier visual rehabilitation

Towards Safe Reinforcement Learning via Constraining Conditional Value-at-Risk

Though deep reinforcement learning (DRL) has obtained substantial success, it may encounter catastrophic failures due to the intrinsic uncertainty of both transition and observation. Most of the existing methods for safe reinforcement learning can only handle transition disturbance or observation disturbance since these two kinds of disturbance affect different parts of the agent; besides, the popular worst-case return may lead to overly pessimistic policies. To address these issues, we first theoretically prove that the performance degradation under transition disturbance and observation disturbance depends on a novel metric of Value Function Range (VFR), which corresponds to the gap in the value function between the best state and the worst state. Based on the analysis, we adopt conditional value-at-risk (CVaR) as an assessment of risk and propose a novel reinforcement learning algorithm of CVaR-Proximal-Policy-Optimization (CPPO) which formalizes the risk-sensitive constrained optimization problem by keeping its CVaR under a given threshold. Experimental results show that CPPO achieves a higher cumulative reward and is more robust against both observation and transition disturbances on a series of continuous control tasks in MuJoCo