Distributed power analysis attack on SM4 encryption chip.

Encryption chips are specialized integrated circuits that incorporate encryption algorithms for data encryption and decryption, ensuring data confidentiality and security. In China, the domestic SM4 algorithm is commonly utilized, as opposed to the international AES encryption algorithm. These widely implemented encryption standards have been proven to be difficult to crack through crypt analysis methods Currently, power consumption side-channel attacks are the most prevalent method. They involve capturing power consumption data during the encryption process and subsequently recovering the encryption key from this data. The two leading methods are Differential Power Analysis (DPA) and machine learning techniques. DPA does not necessitate prior knowledge but relies heavily on the number of power consumption curves. With only 50 power consumption data points, the accuracy is a mere 80%. Machine learning methods require prior knowledge, achieving an accuracy rate above 95% with only 30 power traces, albeit with training times typically exceeding 15 min. In this paper, a distributed energy analysis attack approach was presented based on Correlation Power Analysis (CPA). The power consumption data was divided into 16 subsets, with each subset corresponding to 8 bytes of the key. By training each subset separately, the 8-byte key's corresponding power consumption data is reduced to only 100 dimensions, resulting in a 76% decrease in cracking time and a 3% improvement in cracking accuracy rate.This article also trains a more complex 256 classification model to directly crack the final key, achieving a success rate of 28% in cracking 128-bit passwords with only 1 power trace.

Inferring evolutionary trajectories from cross-sectional transcriptomic data to mirror lung adenocarcinoma progression.

Lung adenocarcinoma (LUAD) is a deadly tumor with dynamic evolutionary process. Although much endeavors have been made in identifying the temporal patterns of cancer progression, it remains challenging to infer and interpret the molecular alterations associated with cancer development and progression. To this end, we developed a computational approach to infer the progression trajectory based on cross-sectional transcriptomic data. Analysis of the LUAD data using our approach revealed a linear trajectory with three different branches for malignant progression, and the results showed consistency in three independent cohorts. We used the progression model to elucidate the potential molecular events in LUAD progression. Further analysis showed that overexpression of BUB1B, BUB1 and BUB3 promoted tumor cell proliferation and metastases by disturbing the spindle assembly checkpoint (SAC) in the mitosis. Aberrant mitotic spindle checkpoint signaling appeared to be one of the key factors promoting LUAD progression. We found the inferred cancer trajectory allows to identify LUAD susceptibility genetic variations using genome-wide association analysis. This result shows the opportunity for combining analysis of candidate genetic factors with disease progression. Furthermore, the trajectory showed clear evident mutation accumulation and clonal expansion along with the LUAD progression. Understanding how tumors evolve and identifying mutated genes will help guide cancer management. We investigated the clonal architectures and identified distinct clones and subclones in different LUAD branches. Validation of the model in multiple independent data sets and correlation analysis with clinical results demonstrate that our method is effective and unbiased.

Integrated mRNA sequence optimization using deep learning.

The coronavirus disease of 2019 pandemic has catalyzed the rapid development of mRNA vaccines, whereas, how to optimize the mRNA sequence of exogenous gene such as severe acute respiratory syndrome coronavirus 2 spike to fit human cells remains a critical challenge. A new algorithm, iDRO (integrated deep-learning-based mRNA optimization), is developed to optimize multiple components of mRNA sequences based on given amino acid sequences of target protein. Considering the biological constraints, we divided iDRO into two steps: open reading frame (ORF) optimization and 5' untranslated region (UTR) and 3'UTR generation. In ORF optimization, BiLSTM-CRF (bidirectional long-short-term memory with conditional random field) is employed to determine the codon for each amino acid. In UTR generation, RNA-Bart (bidirectional auto-regressive transformer) is proposed to output the corresponding UTR. The results show that the optimized sequences of exogenous genes acquired the pattern of human endogenous gene sequence. In experimental validation, the mRNA sequence optimized by our method, compared with conventional method, shows higher protein expression. To the best of our knowledge, this is the first study by introducing deep-learning methods to integrated mRNA sequence optimization, and these results may contribute to the development of mRNA therapeutics.

Composite Braided Fabric Coupled with Photothermal and Electrothermal Processes for Stable and Continuous All-Day Desalination.

In this study, a carbon fiber/tencel composite braided fabric was used in stable and continuous all-day desalination technology with superior photothermal and electrothermal conversion capability. The desalination performance was regulated by adjusting the braiding parameters. Because the water in carbon fibers is maintained in the capillary state and thus evaporates more easily in clusters, it required less energy to evaporate water off the composite fabric. Under 1 sun illumination, the average evaporation rate and the evaporation efficiency were 1.84 kg m-2 h-1 and 88.8%, respectively. When a small amount of electricity (3 V) was applied, the evaporation rate of the braided fabric was maintained at over 1.88 kg m-2 h-1, and a superior desalination performance during the daytime was achieved. Under continuous all-day operation, most of the organics, metal ions, and contaminants were effectively eliminated from the water, which satisfied the WHO drinkable water standards. Our results can contribute to paving the way for efficient and stable wastewater treatment, seawater desalination, and drinking water collection methods.

DOTA: Deep Learning Optimal Transport Approach to Advance Drug Repositioning for Alzheimer's Disease.

Alzheimer's disease (AD) is the leading cause of age-related dementia, affecting over 5 million people in the United States and incurring a substantial global healthcare cost. Unfortunately, current treatments are only palliative and do not cure AD. There is an urgent need to develop novel anti-AD therapies; however, drug discovery is a time-consuming, expensive, and high-risk process. Drug repositioning, on the other hand, is an attractive approach to identify drugs for AD treatment. Thus, we developed a novel deep learning method called DOTA (Drug repositioning approach using Optimal Transport for Alzheimer's disease) to repurpose effective FDA-approved drugs for AD. Specifically, DOTA consists of two major autoencoders: (1) a multi-modal autoencoder to integrate heterogeneous drug information and (2) a Wasserstein variational autoencoder to identify effective AD drugs. Using our approach, we predict that antipsychotic drugs with circadian effects, such as quetiapine, aripiprazole, risperidone, suvorexant, brexpiprazole, olanzapine, and trazadone, will have efficacious effects in AD patients. These drugs target important brain receptors involved in memory, learning, and cognition, including serotonin 5-HT2A, dopamine D2, and orexin receptors. In summary, DOTA repositions promising drugs that target important biological pathways and are predicted to improve patient cognition, circadian rhythms, and AD pathogenesis.

Enhancing the Spun Yarn Properties by Controlling Fiber Stress Distribution in the Spinning Triangle with Rotary Heterogeneous Contact Surfaces.

Control of tension distribution in the spinning triangle region that can facilitate fiber motion and transfer is highly desirable for high quality yarn production. Here, the key mechanisms and a mechanical model of gradient regulation of fiber tension and motion with rotary heterogeneous contact surfaces were theoretically analyzed. The linear velocity gradient, effected on a fiber strand using rotary heterogeneous contact surfaces, could balance and stabilize the structure and stress distribution of spinning triangle area, which could capture exposed fiber to reduce hairiness formation and enhance the internal and external fiber transfer to strengthen the fiber utilization rate. Then, varied yarns spun without and with the rotary grooved and rotary heterogeneous contact surfaces were tested to compare the property improvement for verifying above-mentioned theory. The hairiness, irregularity, and tensity of the yarns spun with rotary heterogeneous contact surfaces spun yarns were significantly improved compared to other spun yarns, which effectively corresponded well to the theoretical analysis. Based on this spinning method, this effective, low energy-consuming, easy spinning apparatus can be used with varied fiber materials for high-quality yarn production.

Application of Machine Vision in Classifying Gait Frailty Among Older Adults.

Background: Frail older adults have an increased risk of adverse health outcomes and premature death. They also exhibit altered gait characteristics in comparison with healthy individuals. Methods: In this study, we created a Fried's frailty phenotype (FFP) labelled casual walking video set of older adults based on the West China Health and Aging Trend study. A series of hyperparameters in machine vision models were evaluated for body key point extraction (AlphaPose), silhouette segmentation (Pose2Seg, DPose2Seg, and Mask R-CNN), gait feature extraction (Gaitset, LGaitset, and DGaitset), and feature classification (AlexNet and VGG16), and were highly optimised during analysis of gait sequences of the current dataset. Results: The area under the curve (AUC) of the receiver operating characteristic (ROC) at the physical frailty state identification task for AlexNet was 0.851 (0.827-0.8747) and 0.901 (0.878-0.920) in macro and micro, respectively, and was 0.855 (0.834-0.877) and 0.905 (0.886-0.925) for VGG16 in macro and micro, respectively. Furthermore, this study presents the machine vision method equipped with better predictive performance globally than age and grip strength, as well as than 4-m-walking-time in healthy and pre-frailty classifying. Conclusion: The gait analysis method in this article is unreported and provides promising original tool for frailty and pre-frailty screening with the characteristics of convenience, objectivity, rapidity, and non-contact. These methods can be extended to any gait-related disease identification processes, as well as in-home health monitoring.

First-principles study of cohesion strength and stability of titanium-carbon interfaces using vdW interaction.

Interface adhesion and stability between titanium and carbon materials have been investigated by first-principles calculation, in which three different DFT-PBE, DFT-LDA and optB88-vdW approaches are considered. Our calculation reveals that the formation of carbon vacancy in graphene would enhance the interface stability and increase interfacial strength, which may be due to a strong hybridization between titanium atom and the sp2 dangling bonds of the carbons near the vacancy. It is also found that the van der Waals interaction has less effects on cohesion properties of the titanium/graphite interfaces, and the Ti-C bond of titanium-carbon interfaces is weaker than that of the TiC bulk. The derived results are discussed in depth by means of electron distribution and Bader transfer analysis, and could be used as a guiding parameter for exploring the fundamental properties of titanium-carbon products as well as various potential applications.

Corrigendum: Strain-stress relationship and dislocation evolution of W-Cu bilayers from a constructed n-body W-Cu potential (2019 J. Phys.: Condens. Matter 31 305002).

An n-body W-Cu potential is constructed under the framework of the embedded-atom method by means of a proposed function of the cross potential. This W-Cu potential is realistic to reproduce mechanical property and structural stability of WCu solid solutions within the entire composition range, and has better performances than the three W-Cu potentials already published in the literature. Based on this W-Cu potential, molecular dynamics simulation is conducted to reveal the mechanical property and dislocation evolution of the bilayer structure between pure W and W0.7Cu0.3 solid solution. It is found that the formation of the interface improves the strength of the W0.7Cu0.3 solid solutions along tensile loading perpendicular to the interface, as the interface impedes the evolution of the dislocation lines from the W0.7Cu0.3 solid solutions to the W part. Simulation also reveals that the interface has an important effect to significantly reduce the tensile strength and critical strain of W along the tensile loading parallel to the interface, which is intrinsically due to the slip of the edge or screw dislocations at low strains as a result of the lattice mismatch.

Corrigendum to "Effects of trigonal deformation on electronic structure and thermoelectric properties of bismuth" [2018 J Phys Condens Matter 30 285504].

In the mentioned paper [1], the cohesive energy E (eV/atom) as the function of the c/a in Table 3 should be corrected as follows.

Photocured Materials with Self-Healing Function through Ionic Interactions for Flexible Electronics.

Photocured materials with self-healing function have the merit of long lifetime and environmentally benign preparation process and thus find potential applications in various fields. Herein, a novel imidazolium-containing photocurable monomer, (6-(3-(3(2-hydroxyethyl)-1 H-imidazol-3-ium bromide)propanoyloxy)hexyl acrylate, IM-A), was designed and synthesized. Self-healing polymers were prepared by fast photocuring with IM-A, isobornyl acrylate, 2-(2-ethoxyethoxy)ethyl acrylate, and 2-hydroxyethyl acrylate as the monomers. The mechanical and self-healing properties of the polymers were tuned by varying the contents of IM-A and other monomers. The as-prepared self-healing polymer IB7-IM5 exhibited a tensile strength of 3.1 MPa, elongation at break of 205%, healing efficiency of 93%, and a wide healing temperature range from room temperature to 120 °C. The self-healing polymer was also employed as a flexible substrate to fabricate a flexible electronic device, which could be healed and completely restore its conductivity after the device was damaged.

8-Layer Shifted Hexagonal Perovskite Ba8MnNb6O24: Long-Range Ordering of High-Spin d5 Mn2+ Layers and Electronic Structure.

A new 8-layer shifted hexagonal perovskite Ba8MnNb6O24 has been synthesized in air, featuring unusual long-range B-cation ordering with single octahedral high-spin d5 Mn2+ layers separated by ∼1.9 nm within the corner-sharing octahedral d0 Nb5+ host, analogous to Ba8(Zn/Co)Nb6O24. The large size and charge differences between high-spin Mn2+ and Nb5+, as well as the out-of-center distortion of NbO6 octahedra associated with the bonding covalence and second-order Jahn-Teller effect of Nb5+, drive long-range cationic ordering, thus stabilizing Ba8MnNb6O24. The Ba8MnNb6O24 pellet exhibits a high dielectric permittivity, εr ∼ 38, and a large temperature coefficient of resonant frequency, τf ∼ 20 ppm/K, but a dielectric loss ( Qf ∼ 987 GHz) and conductivity (∼10-8-10-3 S/cm within 473-1173 K) much higher than those of Ba8ZnNb6O24. Electronic structures from density functional theory calculations reveal that Ba8MnNb6O24 is a Mott insulator in contrast with the charge-transfer insulator nature of Ba8ZnNb6O24, and they confirm that the off-center distortion of Nb5+ contributes to stabilization of the 8-layer ordered shifted structure. The contrast between conductivity and dielectric loss of Ba8MnNb6O24 and Ba8ZnNb6O24 is understood based on the electronic structure that depends on high-spin d5 Mn2+ and d10 Zn2+ cations. The hopping of 3d valence electrons in high-spin Mn2+ to Nb5+ 4d conduction bands over a small gap (∼2.0 eV) makes Ba8MnNb6O24 more conductive than Ba8ZnNb6O24, where the electrons are conducted via the hopping of a lattice O 2p valence electron to the Nb5+ 4d conduction bands over a larger gap (∼3.9 eV). The high microwave dielectric loss of BMN may be mainly ascribed to the half-filled Mn 3d orbits, which is understood based on the softened infrared modes that increase the lattice vibration anharmonicity as well as the resonant spin excitation of unpaired d electrons.

Folding to Curved Surfaces: A Generalized Design Method and Mechanics of Origami-based Cylindrical Structures.

Origami structures enrich the field of mechanical metamaterials with the ability to convert morphologically and systematically between two-dimensional (2D) thin sheets and three-dimensional (3D) spatial structures. In this study, an in-plane design method is proposed to approximate curved surfaces of interest with generalized Miura-ori units. Using this method, two combination types of crease lines are unified in one reprogrammable procedure, generating multiple types of cylindrical structures. Structural completeness conditions of the finite-thickness counterparts to the two types are also proposed. As an example of the design method, the kinematics and elastic properties of an origami-based circular cylindrical shell are analysed. The concept of Poisson's ratio is extended to the cylindrical structures, demonstrating their auxetic property. An analytical model of rigid plates linked by elastic hinges, consistent with numerical simulations, is employed to describe the mechanical response of the structures. Under particular load patterns, the circular shells display novel mechanical behaviour such as snap-through and limiting folding positions. By analysing the geometry and mechanics of the origami structures, we extend the design space of mechanical metamaterials and provide a basis for their practical applications in science and engineering.