Lightweight and Unobtrusive Data Obfuscation at IoT Edge for Remote Inference

Executing deep neural networks for inference on the server-class or cloud backend based on data generated at the edge of Internet of Things is desirable due primarily to the limited compute power of edge devices and the need to protect the confidentiality of the inference neural networks. However, such a remote inference scheme incurs concerns regarding the privacy of the inference data transmitted by the edge devices to the curious backend. This paper presents a lightweight and unobtrusive approach to obfuscate the inference data at the edge devices. It is lightweight in that the edge device only needs to execute a small-scale neural network; it is unobtrusive in that the edge device does not need to indicate whether obfuscation is applied. Extensive evaluation by three case studies of free spoken digit recognition, handwritten digit recognition, and American sign language recognition shows that our approach effectively protects the confidentiality of the raw forms of the inference data while effectively preserving the backend's inference accuracy.Comment: This paper has been accepted by IEEE Internet of Things Journal, Special Issue on Artificial Intelligence Powered Edge Computing for Internet of Thing

Clinical value of M1 macrophage-related genes identification in bladder urothelial carcinoma and in vitro validation

Background: Tumor microenvironment (TME) takes a non-negligible role in the progression and metastasis of bladder urothelial carcinoma (BLCA) and tumor development could be inhibited by macrophage M1 in TME. The role of macrophage M1-related genes in BLCA adjuvant therapy has not been studied well. Methods: CIBERSOR algorithm was applied for identification tumor-infiltrating immune cells (TICs) subtypes of subjects from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) data sets. We identified potential modules of M1 macrophages by weighted gene co-expression network analysis (WGCNA). Nomogram was determined by one-way Cox regression and lasso regression analysis for M1 macrophage genes. The data from GEO are taken to verify the models externally. Kaplan-Meier and receiver operating characteristic (ROC) curves validated prognostic value of M1 macrophage genes. Finally, we divided patients into the low-risk group (LRG) and the high-risk group (HRG) based on the median risk score (RS), and the predictive value of RS in patients with BLCA immunotherapy and chemotherapy was investigated. Bladder cancer (T24, 5637, and BIU-87) and bladder uroepithelial cell line (SV-HUC-1) were used for in vitro validation. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was employed to validate the associated genes mRNA level. Results: 111 macrophage M1-related genes were identified using WGCNA. RS model containing three prognostically significant M1 macrophage-associated genes (FBXO6, OAS1, and TMEM229B) was formed by multiple Cox analysis, and a polygenic risk model and a comprehensive prognostic line plot was developed. The calibration curve clarified RS was a good predictor of prognosis. Patients in the LRG were more suitable for programmed cell death protein 1 (PD1) and cytotoxic T lymphocyte associate protein-4 (CTLA4) combination immunotherapy. Finally, chemotherapeutic drug models showed patients in the LRG were more sensitive to gemcitabine and mitomycin. RT-qPCR result elucidated the upregulation of FBXO6, TMEM229B, and downregulation of OAS1 in BLCA cell lines. Conclusion: A predictive model based on M1 macrophage-related genes can help guide us in the treatment of BLCA

keqing: knowledge-based question answering is a nature chain-of-thought mentor of LLM

Large language models (LLMs) have exhibited remarkable performance on various natural language processing (NLP) tasks, especially for question answering. However, in the face of problems beyond the scope of knowledge, these LLMs tend to talk nonsense with a straight face, where the potential solution could be incorporating an Information Retrieval (IR) module and generating response based on these retrieved knowledge. In this paper, we present a novel framework to assist LLMs, such as ChatGPT, to retrieve question-related structured information on the knowledge graph, and demonstrate that Knowledge-based question answering (Keqing) could be a nature Chain-of-Thought (CoT) mentor to guide the LLM to sequentially find the answer entities of a complex question through interpretable logical chains. Specifically, the workflow of Keqing will execute decomposing a complex question according to predefined templates, retrieving candidate entities on knowledge graph, reasoning answers of sub-questions, and finally generating response with reasoning paths, which greatly improves the reliability of LLM's response. The experimental results on KBQA datasets show that Keqing can achieve competitive performance and illustrate the logic of answering each question.Comment: 12 pages, 6 figure

Dynamic response mechanism of initial failure of coal mass induced by in-situ stress in an outburst inoculation process of the working face for coal mining

There is still a great challenge to reveal the micro-macro dynamic mechanical behavior of initial coal failure induced by mining stress field in working face as a necessary condition for the outburst occurrence. The multivariate stress loading paths for the damage and instability of mining coal were constructed based on the typical coal and gas outburst accident of mining face. PFC3D discrete software was used to carry out the visual simulation of damage and instability of coal under multiple working conditions and scales. The dynamic response law of damage and instability of mining coal was revealed, the dynamic evolution behavior of cracks in mining coal was clarified, and the prospect of outburst prevention technologies was put forward based on the initial failure process of coal induced by in-situ stress under mining. The results shown that the failure type and strength of the mined coal varied significantly with the loading and unloading rate of the principal stress. In the process of gradual unloading of stress, the macroscopic fracture surface of coal presented the form of single inclined plane or conjugate shear plane, and the failure strength of coal decreased with the increase of unloading rate. With the gradual loading in both directions of stress at the same rate, unidirectional sudden unloading or a certain residual stress maintaining state presented a macro fracture surface parallel to the direction of the intermediate principal stress. And the failure strength of coal decreased with the increase of the unloading degree or the decrease of the residual stress. Under different stress loaded, the tension-shear failure process of coal appeared successively with shear and tension cracks. In the process of instability caused by mining coal damage, the dynamic evolution of cracks presented intermittent, progressive and paroxysmal composite characteristics. The overall development process of cracks can be characterized as the initial appearance of new cracks (intermittent-sudden increase stage), crack expansion (gradual-slow increase stage), penetration and expansion (paroxysmal-slow increase stage), and the overall tearing process of coal (sudden increase stage). The mechanical strength of coal was regarded as one of the main controlling factors affecting the occurrence of outbursts. The difficulty of initial failure of coal induced by in-situ stress depended critically on the stress loading and unloading path. The coal was most prone to initial failure when the unidirectional principal stress was suddenly unloaded or the bidirectional principal stress was gradually unloaded. Based on this mechanical law, the “ideal mining mode of outburst prediction in mining working face” was proposed to represent the most dangerous state of coal in the working face

Macrophages Phenotype Regulated by IL-6 Are Associated with the Prognosis of Platinum-Resistant Serous Ovarian Cancer: Integrated Analysis of Clinical Trial and Omics

Background. The treatment of platinum-resistant recurrent ovarian cancer (PROC) is a clinical challenge and a hot topic. Tumor microenvironment (TME) as a key factor promoting ovarian cancer progression. Macrophage is a component of TME, and it has been reported that macrophage phenotype is related to the development of PROC. However, the mechanism underlying macrophage polarization and whether macrophage phenotype can be used as a prognostic indicator of PROC remains unclear. Methods. We used ESTIMATE to calculate the number of immune and stromal components in high-grade serous ovarian cancer (HGSOC) cases from The Cancer Genome Atlas database. The differential expression genes (DEGs) were analyzed via protein–protein interaction network, Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene ontology (GO) analysis to reveal major pathways of DEGs. CD80 was selected for survival analysis. IL-6 was selected for gene set enrichment analysis (GSEA). A subsequent cohort study was performed to confirm the correlation of IL-6 expression with macrophage phenotype in peripheral blood and to explore the clinical utility of macrophage phenotype for the prognosis of PROC patients. Results. A total of 993 intersecting genes were identified as candidates for further survival analysis. Further analysis revealed that CD80 expression was positively correlated with the survival of HGSOC patients. The results of GO and KEGG analysis suggested that macrophage polarization could be regulated via chemokine pathway and cytokine–cytokine receptor interaction. GSEA showed that the genes were mainly enriched in IL-6-STAT-3. Correlation analysis for the proportion of tumor infiltration macrophages revealed that M2 was correlated with IL-6. The results of a cohort study demonstrated that the regulation of macrophage phenotype by IL-6 is bidirectional. The high M1% was a protective factor for progression-free survival. Conclusion. Thus, the macrophage phenotype is a prognostic indicator in PROC patients, possibly via a hyperactive IL-6-related pathway, providing an additional clue for the therapeutic intervention of PROC

A Soy Protein-Based Composite Film with a Hierarchical Structure Inspired by Nacre

This article develops a strategy to fabricate a novel bio-based film with excellent toughness and high strength

Molecular Bubble and Outflow in S Mon Revealed by Multiband Datasets

We identify a molecular bubble, and study the star formation and its feedback in the S Mon region, using multiple molecular lines, young stellar objects (YSOs), and infrared data. We revisit the distance to S Mon, ~722+/-9 pc, using Gaia Data Release 3 parallaxes of the associated Class II YSOs. The bubble may be mainly driven by a massive binary system (namely 15 Mon), the primary of which is an O7V-type star. An outflow is detected in the shell of the bubble, suggesting ongoing star formation activities in the vicinity of the bubble. The total wind energy of the massive binary star is three orders of magnitude higher than the sum of the observed turbulent energy in the molecular gas and the kinetic energy of the bubble, indicating that stellar winds help to maintain the turbulence in the S Mon region and drive the bubble. We conclude that the stellar winds of massive stars have an impact on their surrounding environment.Comment: 34 pages,19 figures, 5 tables, Accepted for publication in Ap

Advances on transition metal oxides catalysts for formaldehyde oxidation:a review

This article highlights recent advances in the development of transition metal-based catalysts for formaldehyde oxidation, particularly the enhancement of their catalytic activity for low-temperature oxidation. Various factors that enhance low-temperature activity are reviewed, such as morphology and tunnel structures, synthesis methods, specific surface area, amount and type of active surface oxygen species, oxidation state, and density of active sites are discussed. In addition, catalyst immobilization for practical air purification, reaction mechanism of formaldehyde oxidation, and the reaction parameters affecting the overall efficiency of the reaction are also reviewed