Improving Denoising Diffusion Models via Simultaneous Estimation of Image and Noise

This paper introduces two key contributions aimed at improving the speed and quality of images generated through inverse diffusion processes. The first contribution involves reparameterizing the diffusion process in terms of the angle on a quarter-circular arc between the image and noise, specifically setting the conventional $\displaystyle \sqrt{\bar{\alpha}}=\cos(\eta)$. This reparameterization eliminates two singularities and allows for the expression of diffusion evolution as a well-behaved ordinary differential equation (ODE). In turn, this allows higher order ODE solvers such as Runge-Kutta methods to be used effectively. The second contribution is to directly estimate both the image ($\mathbf{x}_0$) and noise ($\mathbf{\epsilon}$) using our network, which enables more stable calculations of the update step in the inverse diffusion steps, as accurate estimation of both the image and noise are crucial at different stages of the process. Together with these changes, our model achieves faster generation, with the ability to converge on high-quality images more quickly, and higher quality of the generated images, as measured by metrics such as Frechet Inception Distance (FID), spatial Frechet Inception Distance (sFID), precision, and recall

Reliability based optimization for semi-actively controlled seismic structures

A stochastic semi-active control strategy for the MR damping controlled structure is provided in this paper. The integrated optimization of the weighting matrices pertaining to the active optimal control and the MR parameters pertaining to the semi-active optimal control is implemented. In order to reveal the advantages of this strategy, comparative studies on two aspects are involved, i.e. optimization schemes and probabilistic criteria. The comparison between the integrated and the separated schemes based on the probabilistic criteria in terms of statistical moments shows that the integrated scheme exhibits a better control effectiveness. While the comparison between the probabilistic criteria in terms of statistical moments and the reliability used for the integrated scheme shows that the probabilistic criteria in terms of reliability attains a more safe structure

Multiscale Representation for Real-Time Anti-Aliasing Neural Rendering

The rendering scheme in neural radiance field (NeRF) is effective in rendering a pixel by casting a ray into the scene. However, NeRF yields blurred rendering results when the training images are captured at non-uniform scales, and produces aliasing artifacts if the test images are taken in distant views. To address this issue, Mip-NeRF proposes a multiscale representation as a conical frustum to encode scale information. Nevertheless, this approach is only suitable for offline rendering since it relies on integrated positional encoding (IPE) to query a multilayer perceptron (MLP). To overcome this limitation, we propose mip voxel grids (Mip-VoG), an explicit multiscale representation with a deferred architecture for real-time anti-aliasing rendering. Our approach includes a density Mip-VoG for scene geometry and a feature Mip-VoG with a small MLP for view-dependent color. Mip-VoG encodes scene scale using the level of detail (LOD) derived from ray differentials and uses quadrilinear interpolation to map a queried 3D location to its features and density from two neighboring downsampled voxel grids. To our knowledge, our approach is the first to offer multiscale training and real-time anti-aliasing rendering simultaneously. We conducted experiments on multiscale datasets, and the results show that our approach outperforms state-of-the-art real-time rendering baselines

Secured green communication scheme for interference alignment based networks

In this paper, a new security and green communication scheme is proposed to the Interference-Alignment (IA) based networks. To achieve a secured communication, full-duplex receivers are utilized to transmit artificial noise (AN). Both the signals and the ANs are used to harvest energy to realize green communication. For these reasons, the feasible conditions of this scheme are analyzed first. Secondly, the average transmission rate, the secrecy performance and the harvested energy are investigated. Thirdly, an optimization scheme of simultaneous wireless information and power transfer (SWIPT) is given to optimize the information transmission and the energy harvesting efficiency. Meanwhile, an improved IA iteration algorithm is designed to eliminate both the AN and the interference. Furthermore, relay cooperation is considered and its system performance is analyzed. The simulations show that the target average transmission rate is not affected by AN, while the secrecy performance can be greatly improved. The energy harvesting efficiency is also better than the traditional schemes. As expected, the average transmission rate further is improved with the relay cooperation

Identifying and analyzing pointer misuses for sophisticated memory-corruption exploit diagnosis

Software exploits are one of the major threats to internet security. To quickly respond to these attacks, it is critical to automatically diagnose such exploits and find out how they circumvent existing defense mechanisms

Engineered pine endophytic Bacillus toyonensis with nematocidal and colonization abilities for pine wilt disease control

IntroductionThe pinewood nematode (PWN) is responsible for causing pine wilt disease (PWD), which has led to the significant decline of conifer species in Eurasian forests and has become a globally invasive quarantine pest. Manipulating plant-associated microbes to control nematodes is an important strategy for sustainable pest management. However, it has proven difficult to find pine-associated bacteria that possess both nematocidal activity and the ability to colonize pine tissues.MethodsThe stress experiments with turpentine and pine tissue extract were carried out to screen for the desired target strain that could adapt to the internal environment of pine trees. This strain was used to construct an engineered nematocidal strain. Additionally, a fluorescent strain was constructed to determine its dispersal ability in Pinus massoniana seedlings through plate separation, PCR detection, and fluorescence microscopy observations. The engineered nematocidal strain was tested in the greenhouse experiment to assess its ability to effectively protect P. massoniana seedlings from nematode infection.ResultsThis study isolated a Bacillus toyonensis strain Bxy19 from the healthy pine stem, which showed exceptional tolerance in stress experiments. An engineered nematocidal strain Bxy19P3C6 was constructed, which expressed the Cry6Aa crystal protein and exhibited nematocidal activity. The fluorescent strain Bxy19GFP was also constructed and used to test its dispersal ability. It was observed to enter the needles of the seedlings through the stomata and colonize the vascular bundle after being sprayed on the seedlings. The strain was observed to colonize and spread in the tracheid after being injected into the stems. The strain could colonize the seedlings and persist for at least 50 days. Furthermore, the greenhouse experiments indicated that both spraying and injecting the engineered strain Bxy19P3C6 had considerable efficacy against nematode infection.DiscussionThe evidence of the colonization ability and persistence of the strain in pine advances our understanding of the control and prediction of the colonization of exogenously delivered bacteria in pines. This study provides a promising approach for manipulating plant-associated bacteria and using Bt protein to control nematodes

Pushing the Limits of Valiant\u27s Universal Circuits: Simpler, Tighter and More Compact

A universal circuit (UC) is a general-purpose circuit that can simulate arbitrary circuits (up to a certain size $n$). Valiant provides a $k$-way recursive construction of universal circuits (STOC 1976), where $k$ tunes the complexity of the recursion. More concretely, Valiant gives theoretical constructions of 2-way and 4-way UCs of asymptotic (multiplicative) sizes $5n\log n$ and $4.75 n\log n$ respectively, which matches the asymptotic lower bound $\Omega(n\log n)$ up to some constant factor. Motivated by various privacy-preserving cryptographic applications, Kiss et al. (Eurocrypt 2016) validated the practicality of 2-way universal circuits by giving example implementations for private function evaluation. G{ü}nther et al. (Asiacrypt 2017) and Alhassan et al. (J. Cryptology 2020) implemented the 2-way/4-way hybrid UCs with various optimizations in place towards making universal circuits more practical. Zhao et al. (Asiacrypt 2019) optimized Valiant\u27s 4-way UC to asymptotic size $4.5 n\log n$ and proved a lower bound $3.64 n\log n$ for UCs under Valiant framework. As the scale of computation goes beyond 10-million-gate ($n=10^7$) or even billion-gate level ($n=10^9$), the constant factor in circuit size plays an increasingly important role in application performance. In this work, we investigate Valiant\u27s universal circuits and present an improved framework for constructing universal circuits with the following advantages. [*Simplicity*] Parameterization is no longer needed. In contrast to that previous implementations resort to a hybrid construction combining $k=2$ and $k=4$ for a tradeoff between fine granularity and asymptotic size-efficiency, our construction gets the best of both worlds when configured at the lowest complexity (i.e., $k=2$). [*Compactness*] Our universal circuits have asymptotic size $3n\log n$, improving upon the best previously known $4.5n\log n$ by 33\% and beating the $3.64n\log n$ lower bound for UCs constructed under Valiant\u27s framework (Zhao et al., Asiacrypt 2019). [*Tightness*] We show that under our new framework the universal circuit size is lower bounded by $2.95 n\log n$, which almost matches the $3n\log n$ circuit size of our 2-way construction. We implement the 2-way universal circuits and evaluate its performance with other implementations, which confirms our theoretical analysis

Effects of the gastric juice injection pattern and contraction frequency on the digestibility of casein powder suspensions in an in vitro dynamic rat stomach made with a 3D printed model

Previously, we have prepared a version of the dynamic in vitro rat stomach system (DIVRS-II or Biomimic Rat II). It was constructed and tested by showing similar digestive behaviors with those occurred in vivo. In the present work, a 3D-printed plastic mold was employed to create highly repeatable silicone rat stomach model. It has been seen to have shortened the time to handcraft a model like that used in DIVRS-II. The maximum mechanical force of the current stomach model generated by rolling extrusion is found to be more stable probably due to the more uniform wall thickness of the new model. Then the effects of the simulated gastric secretion patterns and contraction frequency of the system on the in vitro digestibility of casein powder suspensions were investigated. The results have shown that the location of the gastric secretion injection has an impact on experimental digestibility. The position of rolling-extrusion area, established at the central part of glandular portion (stomach B), displayed the highest digestibility compared to that at the other locations. Furthermore, the extent of digestion was positively correlated with the contraction frequency of the model stomach system, with the maximum frequency of 12cpm giving the highest digestibility. This highest digestibility is almost the same as the average value found in vivo. The better digestive performance produced by optimizing the gastric secretion pattern and contraction frequency may be both resulted from the improved mixing efficiency of the food matrix with digestive juice. This study shows that it is possible to achieve what in vivo in a simulated digestion device, which may be used for future food and nutrition studies in vitro