Improved Decoding of Expander Codes

We study the classical expander codes, introduced by Sipser and Spielman [M. Sipser and D. A. Spielman, 1996]. Given any constants 0 < ?, ? < 1/2, and an arbitrary bipartite graph with N vertices on the left, M < N vertices on the right, and left degree D such that any left subset S of size at most ? N has at least (1-?)|S|D neighbors, we show that the corresponding linear code given by parity checks on the right has distance at least roughly {? N}/{2 ?}. This is strictly better than the best known previous result of 2(1-?) ? N [Madhu Sudan, 2000; Viderman, 2013] whenever ? < 1/2, and improves the previous result significantly when ? is small. Furthermore, we show that this distance is tight in general, thus providing a complete characterization of the distance of general expander codes. Next, we provide several efficient decoding algorithms, which vastly improve previous results in terms of the fraction of errors corrected, whenever ? < 1/4. Finally, we also give a bound on the list-decoding radius of general expander codes, which beats the classical Johnson bound in certain situations (e.g., when the graph is almost regular and the code has a high rate). Our techniques exploit novel combinatorial properties of bipartite expander graphs. In particular, we establish a new size-expansion tradeoff, which may be of independent interests

MISA: Unveiling the Vulnerabilities in Split Federated Learning

\textit{Federated learning} (FL) and \textit{split learning} (SL) are prevailing distributed paradigms in recent years. They both enable shared global model training while keeping data localized on users' devices. The former excels in parallel execution capabilities, while the latter enjoys low dependence on edge computing resources and strong privacy protection. \textit{Split federated learning} (SFL) combines the strengths of both FL and SL, making it one of the most popular distributed architectures. Furthermore, a recent study has claimed that SFL exhibits robustness against poisoning attacks, with a fivefold improvement compared to FL in terms of robustness. In this paper, we present a novel poisoning attack known as MISA. It poisons both the top and bottom models, causing a \textbf{\underline{misa}}lignment in the global model, ultimately leading to a drastic accuracy collapse. This attack unveils the vulnerabilities in SFL, challenging the conventional belief that SFL is robust against poisoning attacks. Extensive experiments demonstrate that our proposed MISA poses a significant threat to the availability of SFL, underscoring the imperative for academia and industry to accord this matter due attention.Comment: This paper has been accepted by the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2024

Research progress on the relationship between axonal transport dysfunction in neuronal cells and Alzheimer’s disease

Alzheimer’s disease is known as one of the “top ten killers in the world”. Due to lack of effective therapy at present， early pathological changes have captivated widespread attention. Axonal transport dysfunction has been reported as an early pathological feature of many neurodegenerative diseases. However， multiple factors can cause axonal transport dysfunction. In this article， the relationship between axonal transport dysfunction caused by kinesins， microtubules and mitochondria and Alzheimer’s disease was discussed， aiming to provide new ideas for the prevention and treatment of Alzheimer’s disease by in-depth study on axonal transport mechanism of neure

The circadian rhythms regulated by Cx43-signaling in the pathogenesis of Neuromyelitis Optica

IntroductionNeuromyelitis Optica (NMO) is an inflammatory demyelinating disease of the central nervous system (CNS). NMO manifests as selective and severe attacks on axons and myelin of the optic nerve and spinal cord, resulting in necrotic cavities. The circadian rhythms are well demonstrated to profoundly impact cellular function, behavior, and disease. This study is aimed to explore the role and molecular basis of circadian rhythms in NMO.MethodsWe used an Aquaporin 4(AQP4) IgG-induced NMO cell model in isolated astrocytes. The expression of Cx43 and Bmal1 were detected by real-time PCR and Western Blot. TAT-Gap19 and DQP-1105 were used to inhibit Cx43 and glutamate receptor respectively. The knockdown of Bmal1 were performed with the shRNA containing adenovirus. The levels of glutamate, anterior visual pathway (AVP), and vasoactive intestinal peptide (VIP) were quantified by ELISA kits.ResultsWe found that Bmal1 and Clock, two essential components of the circadian clock, were significantly decreased in NMO astrocytes, which were reversed by Cx43 activation (linoleic acid) or glutamate. Moreover, the expression levels of Bmal1 and Clock were also decreased by Cx43 blockade (TAT-Gap19) or glutamate receptor inhibition (DQP-1105). Furthermore, adenovirus-mediated Bmal1 knockdown by shRNA (Ad-sh-Bmal1) dramatically decreased the levels of glutamate, AVP, and VIP from neurons, and significantly down-regulated the protein level of Cx43 in NMO astrocytes with Cx43 activation (linoleic acid) or glutamate treatment. However, Bmal1 knockdown did not alter these levels in normal astrocytes with Cx43 blockade (TAT-Gap19) or glutamate receptor inhibition (DQP-1105).DiscussionCollectively, these results suggest that Cx43-glutamate signaling would be a critical upstream regulator that contributes to the NMO-induced rhythmic damage in SCN astrocytes

Reducing the gap between streaming and non-streaming Transducer-based ASR by adaptive two-stage knowledge distillation

Transducer is one of the mainstream frameworks for streaming speech recognition. There is a performance gap between the streaming and non-streaming transducer models due to limited context. To reduce this gap, an effective way is to ensure that their hidden and output distributions are consistent, which can be achieved by hierarchical knowledge distillation. However, it is difficult to ensure the distribution consistency simultaneously because the learning of the output distribution depends on the hidden one. In this paper, we propose an adaptive two-stage knowledge distillation method consisting of hidden layer learning and output layer learning. In the former stage, we learn hidden representation with full context by applying mean square error loss function. In the latter stage, we design a power transformation based adaptive smoothness method to learn stable output distribution. It achieved 19\% relative reduction in word error rate, and a faster response for the first token compared with the original streaming model in LibriSpeech corpus

Synthesis and Anticancer Activity Evaluation of Novel Phenanthridine Derivatives

Based on the structure of sanguinarine, fourteen phenanthridine derivatives were designed and synthesized in the current study. The cytotoxic activities of synthesized compounds were evaluated against five human cancer cell lines (MCF-7, PC3, Hela, A549, and HepG2 cell lines) via MTT assay. Among all the compounds tested, molecule 8a exhibited significant cytotoxic activity against MCF-7 cells with a IC50 value of 0.28 μM. A following up enzymatic assay indicated that compound 8a could inhibit the activity of DNA topoisomerase I/II. Further mechanistic studies performed in the MCF-7 cell line revealed that compound 8a could arrest cell cycle in S phase and induce cell apoptosis via downregulation of Bcl-2 and upregulation of Bax. Collectively, a potent DNA topoisomerase inhibitor (8a) was discovered, which exhibited potential as a candidate chemotherapeutic agent for the management of tumors in the present study

Quantum correlations and synchronization measures

The phenomenon of spontaneous synchronization is universal and only recently advances have been made in the quantum domain. Being synchronization a kind of temporal correlation among systems, it is interesting to understand its connection with other measures of quantum correlations. We review here what is known in the field, putting emphasis on measures and indicators of synchronization which have been proposed in the literature, and comparing their validity for different dynamical systems, highlighting when they give similar insights and when they seem to fail.Comment: book chapter, 18 pages, 7 figures, Fanchini F., Soares Pinto D., Adesso G. (eds) Lectures on General Quantum Correlations and their Applications. Quantum Science and Technology. Springer (2017