Scaling in Depth: Unlocking Robustness Certification on ImageNet

Despite the promise of Lipschitz-based methods for provably-robust deep learning with deterministic guarantees, current state-of-the-art results are limited to feed-forward Convolutional Networks (ConvNets) on low-dimensional data, such as CIFAR-10. This paper investigates strategies for expanding certifiably robust training to larger, deeper models. A key challenge in certifying deep networks is efficient calculation of the Lipschitz bound for residual blocks found in ResNet and ViT architectures. We show that fast ways of bounding the Lipschitz constant for conventional ResNets are loose, and show how to address this by designing a new residual block, leading to the \emph{Linear ResNet} (LiResNet) architecture. We then introduce \emph{Efficient Margin MAximization} (EMMA), a loss function that stabilizes robust training by simultaneously penalizing worst-case adversarial examples from \emph{all} classes. Together, these contributions yield new \emph{state-of-the-art} robust accuracy on CIFAR-10/100 and Tiny-ImageNet under $\ell_2$ perturbations. Moreover, for the first time, we are able to scale up fast deterministic robustness guarantees to ImageNet, demonstrating that this approach to robust learning can be applied to real-world applications. We release our code on Github: \url{https://github.com/klasleino/gloro}

MCNTs@MnO2 nanocomposite cathode integrated with soluble O2-carrier Co-salen in electrolyte for high-performance Li-air batteries

Li–air batteries (LABs) are promising because of their high energy density. However, LABs are troubled by large electrochemical polarization during discharge and charge, side reactions from both carbon cathode surface/peroxide product and electrolyte/superoxide intermediate, as well as the requirement for pure O2. Here we report the solution using multiwall carbon nanotubes (MCNTs)@MnO2 nanocomposite cathode integrated with N,N′-bis(salicylidene)ethylenediaminocobalt(II) (CoII-salen) in electrolyte for LABs. The advantage of such a combination is that on one hand, the coating layer of δ-MnO2 with about 2–3 nm on MCNTs@MnO2 nanocomposite catalyzes Li2O2 decomposition during charge and suppresses side reactions between product Li2O2 and MCNT surface. On the other hand, CoII-salen works as a mobile O2-carrier and accelerates Li2O2 formation through the reaciton of (CoIII-salen)2-O22– + 2Li+ + 2e– → 2CoII-salen + Li2O2. This reaction route overcomes the pure O2 limitation and avoids the formation of aggressive superoxide intermediate (O2– or LiO2), which easily attacks organic electrolyte. By using this double-catalyst system of Co-salen/MCNTs@MnO2, the lifetime of LABs is prolonged to 300 cycles at 500 mA g–1 (0.15 mA cm–2) with fixed capacity of 1000 mAh g–1 (0.30 mAh cm–2) in dry air (21% O2). Furthermore, we up-scale the capacity to 500 mAh (5.2 mAh cm–2) in pouch-type batteries (∼4 g, 325 Wh kg–1). This study should pave a new way for the design and construction of practical LABs

Polydopamine-Decorated Microcomposites Promote Functional Recovery of an Injured Spinal Cord by Inhibiting Neuroinflammation

Neuroinflammation following spinal cord injury usually aggravates spinal cord damage. Many inflammatory cytokines are key players in neuroinflammation. Owing largely to the multiplicity of cytokine targets and the complexity of cytokine interactions, it is insufficient to suppress spinal cord damage progression by regulating only one or a few cytokines. Herein, we propose a two-pronged strategy to simultaneously capture the released cytokines and inhibit the synthesis of new ones in a broad-spectrum manner. To achieve this strategy, we designed a core/shell-structured microcomposite, which was composed of a methylprednisolone-incorporated polymer inner core and a biocompatible polydopamine outer shell. Thanks to the inherent adhesive nature of polydopamine, the obtained microcomposite (MP-PLGA@PDA) efficiently neutralized the excessive cytokines in a broad-spectrum manner within 1 day after spinal cord injury. Meanwhile, the controlled release of immunosuppressive methylprednisolone reduced the secretion of new inflammatory cytokines. Benefiting from its efficient and broad-spectrum capability in reducing the level of cytokines, this core/shell-structured microcomposite suppressed the recruitment of macrophages and protected the injured spinal cord, leading to an improved recovery of motor function. Overall, the designed microcomposite successfully achieved the two-pronged strategy in cytokine neutralization, providing an alternative approach to inhibit neuroinflammation in the injured spinal cord.Peer reviewe

MCNTs@MnO2 Nanocomposite Cathode Integrated with Soluble O2Carrier Co-salen in Electrolyte for High-Performance LiAir Batteries

Li–air batteries (LABs) are promising because of their high energy density. However, LABs are troubled by large electrochemical polarization during discharge and charge, side reactions from both carbon cathode surface/peroxide product and electrolyte/superoxide intermediate, as well as the requirement for pure O2. Here we report the solution using multiwall carbon nanotubes (MCNTs)@MnO2 nanocomposite cathode integrated with N,N′-bis(salicylidene)ethylenediaminocobalt(II) (CoII-salen) in electrolyte for LABs. The advantage of such a combination is that on one hand, the coating layer of δ-MnO2 with about 2–3 nm on MCNTs@MnO2 nanocomposite catalyzes Li2O2 decomposition during charge and suppresses side reactions between product Li2O2 and MCNT surface. On the other hand, CoII-salen works as a mobile O2-carrier and accelerates Li2O2 formation through the reaciton of (CoIII-salen)2-O22– + 2Li+ + 2e– → 2CoII-salen + Li2O2. This reaction route overcomes the pure O2 limitation and avoids the formation of aggressive superoxide intermediate (O2– or LiO2), which easily attacks organic electrolyte. By using this double-catalyst system of Co-salen/MCNTs@MnO2, the lifetime of LABs is prolonged to 300 cycles at 500 mA g–1 (0.15 mA cm–2) with fixed capacity of 1000 mAh g–1 (0.30 mAh cm–2) in dry air (21% O2). Furthermore, we up-scale the capacity to 500 mAh (5.2 mAh cm–2) in pouch-type batteries (∼4 g, 325 Wh kg–1). This study should pave a new way for the design and construction of practical LABs

Development and optimisation of in vitro sonodynamic therapy for glioblastoma

Sonodynamic therapy (SDT) is currently on critical path for glioblastoma therapeutics. SDT is a non-invasive approach utilising focused ultrasound to activate photosensitisers like 5-ALA to impede tumour growth. Unfortunately, the molecular mechanisms underlying the therapeutic functions of SDT remain enigmatic. This is primarily due to the lack of intricately optimised instrumentation capable of modulating SDT delivery to glioma cells in vitro. Consequently, very little information is available on the effects of SDT on glioma stem cells which are key drivers of gliomagenesis and recurrence. To address this, the current study has developed and validated an automated in vitro SDT system to allow the application and mapping of focused ultrasound fields under varied exposure conditions and setup configurations. The study optimizes ultrasound frequency, intensity, plate base material, thermal effect, and the integration of live cells. Indeed, in the presence of 5-ALA, focused ultrasound induces apoptotic cell death in primary patient-derived glioma cells with concurrent upregulation of intracellular reactive oxygen species. Intriguingly, primary glioma stem neurospheres also exhibit remarkably reduced 3D growth upon SDT exposure. Taken together, the study reports an in vitro system for SDT applications on tissue culture-based disease models to potentially benchmark the novel approach to the current standard-of-care.</p

The role of tripartite motif-containing 28 in cancer progression and its therapeutic potentials

Tripartite motif-containing 28 (TRIM28) belongs to tripartite motif (TRIM) family. TRIM28 not only binds and degrades its downstream target, but also acts as a transcription co-factor to inhibit gene expression. More and more studies have shown that TRIM28 plays a vital role in tumor genesis and progression. Here, we reviewed the role of TRIM28 in tumor proliferation, migration, invasion and cell death. Moreover, we also summarized the important role of TRIM28 in tumor stemness sustainability and immune regulation. Because of the importance of TRIM28 in tumors, TIRM28 may be a candidate target for anti-tumor therapy and play an important role in tumor diagnosis and treatment in the future

Form Finding of Asymmetric Cable Network Reflector with Flexible Ring Truss

In this work, the form finding of an asymmetric cable network reflector is considered by taking into account the elastic deformation of the flexible ring truss. Firstly, by treating the boundary nodes as fixed nodes, the balance equations of the structure are transformed into linear equations using the force density method (FDM). Next, the genetic algorithm (GA) is used to find the force density values that satisfy the surface accuracy required to complete the form finding of a cable network reflector. Secondly, a design procedure is presented by incorporating the elastic deformation of the ring truss. Finally, using an iterative process, the coordinates of the boundary nodes are modified to repeat the first step to obtain better surface accuracy. Numerical experiments are presented to demonstrate the effectiveness of the proposed method in comparison with the conventional method

A Review of Deep Learning Applications in Tunneling and Underground Engineering in China

With the advent of the era of big data and information technology, deep learning (DL) has become a hot trend in the research field of artificial intelligence (AI). The use of deep learning methods for parameter inversion, disease identification, detection, surrounding rock classification, disaster prediction, and other tunnel engineering problems has also become a new trend in recent years, both domestically and internationally. This paper briefly introduces the development process of deep learning. By reviewing a number of published papers on the application of deep learning in tunnel engineering over the past 20 years, this paper discusses the intelligent application of deep learning algorithms in tunnel engineering, including collapse risk assessment, water inrush prediction, crack identification, structural stability evaluation, and seepage erosion in mountain tunnels, urban subway tunnels, and subsea tunnels. Finally, it explores the future challenges and development prospects of deep learning in tunnel engineering

Shunt Damping Vibration Control Technology: A Review

Smart materials and structures have attracted a significant amount of attention for their vibration control potential in engineering applications. Compared to the traditional active technique, shunt damping utilizes an external circuit across the terminals of smart structure based transducers to realize vibration control. Transducers can simultaneously serve as an actuator and a sensor. Such unique advantage offers a great potential for designing sensorless devices to be used in structural vibration control and reduction engineering. The present literature combines piezoelectric shunt damping (PSD) and electromagnetic shunt damping (EMSD), establishes a unified governing equation of PSD and EMSD, and reports the unique vibration control performance of these shunts. The schematic of shunt circuits is given and demonstrated, and some common control principles and equations of these shunts are summarized. Finally, challenges and perspective of the shunt damping technology are discussed, and suggestions made based on the knowledge and experience of the authors