Winner's Curse Free Robust Mendelian Randomization with Summary Data

In the past decade, the increased availability of genome-wide association studies summary data has popularized Mendelian Randomization (MR) for conducting causal inference. MR analyses, incorporating genetic variants as instrumental variables, are known for their robustness against reverse causation bias and unmeasured confounders. Nevertheless, classical MR analyses utilizing summary data may still produce biased causal effect estimates due to the winner's curse and pleiotropic issues. To address these two issues and establish valid causal conclusions, we propose a unified robust Mendelian Randomization framework with summary data, which systematically removes the winner's curse and screens out invalid genetic instruments with pleiotropic effects. Different from existing robust MR literature, our framework delivers valid statistical inference on the causal effect neither requiring the genetic pleiotropy effects to follow any parametric distribution nor relying on perfect instrument screening property. Under appropriate conditions, we show that our proposed estimator converges to a normal distribution and its variance can be well estimated. We demonstrate the performance of our proposed estimator through Monte Carlo simulations and two case studies. The codes implementing the procedures are available at https://github.com/ChongWuLab/CARE/

Outer characteristic simulation and performance analysis of variable shock absorber

In this study, a variable shock absorber (VSA) for semi-active suspension is developed, the structure and operation principle of the VSA is illustrated. Based on the theory of hydraulics and elasticity, the ways of calculating for the embranchment flow rate and the throttle pressure difference on the series-parallel complex pipe line (SPCPL) are deduced and employed, and the detailed mathematical model of the VSA is established by using the differential equation for annular laminar deformation under uniform load (ALDUUL). The MATLAB/Simulink software is used to simulate the detailed model, and the calculated results agree well with the experimental results. In particular, the influence rules of the bypass groove diameter of the VSA on its damping is analyzed through this model, and the results obtained can technically support the design and performance prediction of the VSA to a certain degree

Impossible Differential Cryptanalysis of FOX

Block ciphers are the very foundation of computer and information security. FOX, also known as IDEA NXT, is a family of block ciphers published in 2004 and is famous for its provable security to cryptanalysis. In this paper, we apply impossible differential cryptanalysis on FOX cipher. We find a 4-round impossible difference, by using which adversaries can attack 5, 6 and 7-round FOX64 with $2^{71}$, $2^{135}$ and $2^{199}$ one-round encryptions respectively. Compared to the previous best attack with $2^{109.4}$, $2^{173.4}$ and $2^{237.4}$ full-round encryptions to 5, 6 and 7-round FOX64, the method in this paper is the best attack to FOX cipher. This attack can also be applied to 5-round FOX128 with $2^{135}$ one-round encryptions

A Unified Method for Finding Impossible Differentials of Block Cipher Structures

In this paper, we propose a systematic method for finding impossible differentials for block cipher structures, better than the $\mathcal{U}$-method introduced by Kim \textit{et al}~\cite{Kim03}. It is referred as a unified impossible differential finding method (UID-method). We apply the UID-method to some popular block ciphers such as {\sf Gen-Skipjack}, {\sf Gen-CAST256}, {\sf Gen-MARS}, {\sf Gen-RC6}, {\sf Four-Cell}, {\sf SMS4} and give the detailed impossible differentials. By the UID-method, we find a 16-round impossible differential on {\sf Gen-Skipjack} and a 19-round impossible differential on {\sf Gen-CAST256}. Thus we disprove the \textsl{Conjecture 2} proposed in \textsl{Asiacrypt\u2700}~\cite{Sung00} and the theorem in \textsl{FSE\u2709} rump session presentation~\cite{Pudovkina09}. On {\sf Gen-MARS} and {\sf SMS4}, the impossible differentials find by the UID-method are much longer than that found by the $\mathcal{U}$-method. On the {\sf Four-Cell} block cipher, our result is the same as the best result previously obtained by case-by-case treatment

Pseudorandomness Analysis of the Lai-Massey Scheme

At Asiacrypt’99, Vaudenay modified the structure in the IDEA cipher to a new scheme, which they called as the Lai-Massey scheme. It is proved that 3-round Lai-Massey scheme is sufficient for pseudorandomness and 4-round Lai-Massey scheme is sufficient for strong pseudorandomness. But the author didn’t point out whether three rounds and four rounds are necessary for the pseudorandomness and strong pseudorandomness of the Lai-Massey Scheme. In this paper we find a two round pseudorandomness distinguisher and a three-round strong pseudorandomness distinguisher, thus prove that three rounds is necessary for the pseudorandomness and four rounds is necessary for the strong pseudorandomness

One Neuron Saved Is One Neuron Earned: On Parametric Efficiency of Quadratic Networks

Inspired by neuronal diversity in the biological neural system, a plethora of studies proposed to design novel types of artificial neurons and introduce neuronal diversity into artificial neural networks. Recently proposed quadratic neuron, which replaces the inner-product operation in conventional neurons with a quadratic one, have achieved great success in many essential tasks. Despite the promising results of quadratic neurons, there is still an unresolved issue: \textit{Is the superior performance of quadratic networks simply due to the increased parameters or due to the intrinsic expressive capability?} Without clarifying this issue, the performance of quadratic networks is always suspicious. Additionally, resolving this issue is reduced to finding killer applications of quadratic networks. In this paper, with theoretical and empirical studies, we show that quadratic networks enjoy parametric efficiency, thereby confirming that the superior performance of quadratic networks is due to the intrinsic expressive capability. This intrinsic expressive ability comes from that quadratic neurons can easily represent nonlinear interaction, while it is hard for conventional neurons. Theoretically, we derive the approximation efficiency of the quadratic network over conventional ones in terms of real space and manifolds. Moreover, from the perspective of the Barron space, we demonstrate that there exists a functional space whose functions can be approximated by quadratic networks in a dimension-free error, but the approximation error of conventional networks is dependent on dimensions. Empirically, experimental results on synthetic data, classic benchmarks, and real-world applications show that quadratic models broadly enjoy parametric efficiency, and the gain of efficiency depends on the task.Comment: We have shared our code in https://github.com/asdvfghg/quadratic_efficienc

Moderate mutation rate in the SARS coronavirus genome and its implications

BACKGROUND: The outbreak of severe acute respiratory syndrome (SARS) caused a severe global epidemic in 2003 which led to hundreds of deaths and many thousands of hospitalizations. The virus causing SARS was identified as a novel coronavirus (SARS-CoV) and multiple genomic sequences have been revealed since mid-April, 2003. After a quiet summer and fall in 2003, the newly emerged SARS cases in Asia, particularly the latest cases in China, are reinforcing a wide-spread belief that the SARS epidemic would strike back. With the understanding that SARS-CoV might be with humans for years to come, knowledge of the evolutionary mechanism of the SARS-CoV, including its mutation rate and emergence time, is fundamental to battle this deadly pathogen. To date, the speed at which the deadly virus evolved in nature and the elapsed time before it was transmitted to humans remains poorly understood. RESULTS: Sixteen complete genomic sequences with available clinical histories during the SARS outbreak were analyzed. After careful examination of multiple-sequence alignment, 114 single nucleotide variations were identified. To minimize the effects of sequencing errors and additional mutations during the cell culture, three strategies were applied to estimate the mutation rate by 1) using the closely related sequences as background controls; 2) adjusting the divergence time for cell culture; or 3) using the common variants only. The mutation rate in the SARS-CoV genome was estimated to be 0.80 – 2.38 × 10(-3 )nucleotide substitution per site per year which is in the same order of magnitude as other RNA viruses. The non-synonymous and synonymous substitution rates were estimated to be 1.16 – 3.30 × 10(-3 )and 1.67 – 4.67 × 10(-3 )per site per year, respectively. The most recent common ancestor of the 16 sequences was inferred to be present as early as the spring of 2002. CONCLUSIONS: The estimated mutation rates in the SARS-CoV using multiple strategies were not unusual among coronaviruses and moderate compared to those in other RNA viruses. All estimates of mutation rates led to the inference that the SARS-CoV could have been with humans in the spring of 2002 without causing a severe epidemic