Efficiency improvement of the frequency-domain BEM for rapid transient elastodynamic analysis

The frequency-domain fast boundary element method (BEM) combined with the exponential window technique leads to an efficient yet simple method for elastodynamic analysis. In this paper, the efficiency of this method is further enhanced by three strategies. Firstly, we propose to use exponential window with large damping parameter to improve the conditioning of the BEM matrices. Secondly, the frequency domain windowing technique is introduced to alleviate the severe Gibbs oscillations in time-domain responses caused by large damping parameters. Thirdly, a solution extrapolation scheme is applied to obtain better initial guesses for solving the sequential linear systems in the frequency domain. Numerical results of three typical examples with the problem size up to 0.7 million unknowns clearly show that the first and third strategies can significantly reduce the computational time. The second strategy can effectively eliminate the Gibbs oscillations and result in accurate time-domain responses

Selection of Reference Genes for Expression Analysis in Chinese Medicinal Herb Huperzia serrata

Huperzine A (HupA) is a powerful and selective inhibitor of acetylcholinesterase. It has attracted widespread attention endangering the ultimate plant sources of Lycopodiaceae family. In this study, we used Huperzia serrata, extensively used in Traditional Chinese medicine (TCM), a slow growing vascular plant as the model plant of the Lycopodiaceae family to develop and validate the reference genes. We aim to use gene expression platform to understand the gene expression of different tissues and developmental stages of this medicinal herb. Eight candidate reference genes were selected based on RNA-seq data and evaluated with qRT-PCR. The expression of L/ODC and cytochrome P450s genes known for their involvement in lycopodium alkaloid biosynthesis, were also studied to validate the selected reference genes. The most stable genes were TBP, GAPDH, and their combination (TBP + GAPDH). We report for the first time the reference gene of H. serrata’s different tissues which would provide important insights into understanding their biological functions comparing other Lycopodiaceae plants and facilitate a good biopharming approach

Correlational Analysis of Sarcopenia and Multimorbidity Among Older Inpatients

BACKGROUND: Sarcopenia and multimorbidity are common in older adults, and most of the available clinical studies have focused on the relationship between specialist disorders and sarcopenia, whereas fewer studies have been conducted on the relationship between sarcopenia and multimorbidity. We therefore wished to explore the relationship between the two. METHODS: The study subjects were older patients (aged ≥ 65 years) who were hospitalized at the Department of Geriatrics of the First Affiliated Hospital of Chongqing Medical University between March 2016 and September 2021. Their medical records were collected. Based on the diagnostic criteria of the Asian Sarcopenia Working Group in 2019, the relationship between sarcopenia and multimorbidity was elucidated. RESULTS: 1.A total of 651 older patients aged 65 years and above with 2 or more chronic diseases were investigated in this study, 46.4% were suffering from sarcopenia. 2. Analysis of the relationship between the number of chronic diseases and sarcopenia yielded that the risk of sarcopenia with 4-5 chronic diseases was 1.80 times higher than the risk of 2-3 chronic diseases (OR 1.80, 95%CI 0.29-2.50), and the risk of sarcopenia with ≥ 6 chronic diseases was 5.11 times higher than the risk of 2-3 chronic diseases (OR 5.11, 95% CI 2.97-9.08), which remained statistically significant, after adjusting for relevant factors. 3. The Charlson comorbidity index was associated with skeletal muscle mass index, handgrip strength, and 6-meter walking speed, with scores reaching 5 and above suggesting the possibility of sarcopenia. 4. After adjusting for some covariates among 14 common chronic diseases in older adults, diabetes (OR 3.20, 95% CI 2.01-5.09), cerebrovascular diseases (OR 2.07, 95% CI 1.33-3.22), bone and joint diseases (OR 2.04, 95% CI 1.32-3.14), and malignant tumors (OR 2.65, 95% CI 1.17-6.55) were among those that still a risk factor for the development of sarcopenia. CONCLUSION: In the hospitalized older adults, the more chronic diseases they have, the higher the prevalence of sarcopenia. When the CCI is 5, attention needs to be paid to the occurrence of sarcopenia in hospitalized older adults

Efficiency Enhancement in Polymer Solar Cells With a Polar Small Molecule Both at Interface and in the Bulk Heterojunction Layer

The polar molecules, including ferroelectric materials with large dipole moments, have been applied as interfacial layers to increase the efficiency of organic solar cells by increasing the bounded charge separation, tuning the energy levels, etc. Here, we report a small polar molecule 2-cyano-3- (4-(diphenylamino) phenyl)acrylic acid (TPACA) that can be either blended in the active layer or at the polymer/electrode interface to increase the efficiency of organic solar cell devices after poling. It is found that the built-in potential of the device is increased by 0.2 V after poling under negative bias. Blending TPACA into the active layer has shown to be a universal method to increase the efficiency of polymer solar cells. The efficiency is increased by 30–90% for all the polymer:fullerene systems tested, with the highest efficiency reaching 7.83% for the poly[4,8-bis-(2-ethyl-hexyl-thiophene-5-yl)-benzo[1,2-b:4,5-b’]dithiophene-2,6-diyl]-alt-[2-(2’-ethyl-hexanoyl)-thieno[3,4-b]thiophen-4,6-diyl]: [6,6]-phenyl-C71 -butyric acid methyl ester (PBDTTT-CT:PC70BM) system

Scale-MIA: A Scalable Model Inversion Attack against Secure Federated Learning via Latent Space Reconstruction

Federated learning is known for its capability to safeguard participants' data privacy. However, recently emerged model inversion attacks (MIAs) have shown that a malicious parameter server can reconstruct individual users' local data samples through model updates. The state-of-the-art attacks either rely on computation-intensive search-based optimization processes to recover each input batch, making scaling difficult, or they involve the malicious parameter server adding extra modules before the global model architecture, rendering the attacks too conspicuous and easily detectable. To overcome these limitations, we propose Scale-MIA, a novel MIA capable of efficiently and accurately recovering training samples of clients from the aggregated updates, even when the system is under the protection of a robust secure aggregation protocol. Unlike existing approaches treating models as black boxes, Scale-MIA recognizes the importance of the intricate architecture and inner workings of machine learning models. It identifies the latent space as the critical layer for breaching privacy and decomposes the complex recovery task into an innovative two-step process to reduce computation complexity. The first step involves reconstructing the latent space representations (LSRs) from the aggregated model updates using a closed-form inversion mechanism, leveraging specially crafted adversarial linear layers. In the second step, the whole input batches are recovered from the LSRs by feeding them into a fine-tuned generative decoder. We implemented Scale-MIA on multiple commonly used machine learning models and conducted comprehensive experiments across various settings. The results demonstrate that Scale-MIA achieves excellent recovery performance on different datasets, exhibiting high reconstruction rates, accuracy, and attack efficiency on a larger scale compared to state-of-the-art MIAs

Cross-plane transport in a single-molecule two-dimensional van der Waals heterojunction

Two-dimensional van der Waals heterostructures (2D-vdWHs) stacked from atomically thick 2D materials are predicted to be a diverse class of electronic materials with unique electronic properties. These properties can be further tuned by sandwiching monolayers of planar organic molecules between 2D materials to form molecular 2D-vdW heterojunctions (M-2D-vdWHs), in which electricity flows in a cross-plane way from one 2D layer to the other via a single molecular layer. Using a newly developed cross-plane break junction (XPBJ) technique, combined with density functional theory calculations, we show that M-2D-vdWHs can be created, and that cross-plane charge transport can be tuned by incorporating guest molecules. More importantly, the M-2D-vdWHs exhibit distinct cross-plane charge transport signatures, which differ from those of molecules undergoing in-plane charge transport

GFI1 downregulation promotes inflammation-linked metastasis of colorectal cancer.

Inflammation is frequently associated with initiation, progression, and metastasis of colorectal cancer (CRC). Here, we unveil a CRC-specific metastatic programme that is triggered via the transcriptional repressor, GFI1. Using data from a large cohort of clinical samples including inflammatory bowel disease and CRC, and a cellular model of CRC progression mediated by cross-talk between the cancer cell and the inflammatory microenvironment, we identified GFI1 as a gating regulator responsible for a constitutively activated signalling circuit that renders CRC cells competent for metastatic spread. Further analysis of mouse models with metastatic CRC and human clinical specimens reinforced the influence of GFI1 downregulation in promoting CRC metastatic spread. The novel role of GFI1 is uncovered for the first time in a human solid tumour such as CRC. Our results imply that GFI1 is a potential therapeutic target for interfering with inflammation-induced CRC progression and spread