Λ\Lambda-Split: A Privacy-Preserving Split Computing Framework for Cloud-Powered Generative AI

In the wake of the burgeoning expansion of generative artificial intelligence (AI) services, the computational demands inherent to these technologies frequently necessitate cloud-powered computational offloading, particularly for resource-constrained mobile devices. These services commonly employ prompts to steer the generative process, and both the prompts and the resultant content, such as text and images, may harbor privacy-sensitive or confidential information, thereby elevating security and privacy risks. To mitigate these concerns, we introduce $\Lambda$-Split, a split computing framework to facilitate computational offloading while simultaneously fortifying data privacy against risks such as eavesdropping and unauthorized access. In $\Lambda$-Split, a generative model, usually a deep neural network (DNN), is partitioned into three sub-models and distributed across the user's local device and a cloud server: the input-side and output-side sub-models are allocated to the local, while the intermediate, computationally-intensive sub-model resides on the cloud server. This architecture ensures that only the hidden layer outputs are transmitted, thereby preventing the external transmission of privacy-sensitive raw input and output data. Given the black-box nature of DNNs, estimating the original input or output from intercepted hidden layer outputs poses a significant challenge for malicious eavesdroppers. Moreover, $\Lambda$-Split is orthogonal to traditional encryption-based security mechanisms, offering enhanced security when deployed in conjunction. We empirically validate the efficacy of the $\Lambda$-Split framework using Llama 2 and Stable Diffusion XL, representative large language and diffusion models developed by Meta and Stability AI, respectively. Our $\Lambda$-Split implementation is publicly accessible at https://github.com/nishio-laboratory/lambda_split.Comment: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

Time-dependent Solutions with Null Killing Spinor in M-theory and Superstrings

Imposing the condition that there should be a null Killing spinor with all the metrics and background field strengths being functions of the light-cone coordinates, we find general 1/2 BPS solutions in D=11 supergravity, and discuss several examples. In particular we show that the linear dilaton background is the most general supersymmetric solution without background under the additional requirement of flatness in the string frame. We also give the most general solutions for flat spacetime in the string frame with RR or NS-NS backgrounds, and they are characterized by a single function.Comment: 12 pages; v2: typos corrected, refs. added; v3: typos corrected, to appear in PL

Matrix String Description of Cosmic Singularities in a Class of Time-dependent Solutions

A large class of time-dependent solutions with 1/2 supersymmetry were found previously. These solutions involve cosmic singularities at early time. In this paper, we study if matrix string description of the singularities in these solutions with backgrounds is possible and present several examples where the solutions can be described well in the perturbative picture.Comment: 12 pages, v2: typos corrected, a ref. adde

Ground state of the spin-1/2 chain of green dioptase at high fields

The gem-stone dioptase Cu6Si6O18.6H2O has a chiral crystal structure of equilateral triangular helices consisting of Cu-3d spins. It shows an antiferromagnetic order with an easy axis along c at TN = 15.5 K under zero field, and a magnetization jump at HC = 13.5 T when the field is applied along c-axis. By 29Si-NMR measurements, we have revealed that the high-field state is essentially the two sub-lattice structure, and that the component within ab-plane is collinear. The result indicates no apparent match with the geometrical pattern of helical spin chain.Comment: SCES2013, Hongo, Toky

Point Cloud-based Proactive Link Quality Prediction for Millimeter-wave Communications

This study demonstrates the feasibility of point cloud-based proactive link quality prediction for millimeter-wave (mmWave) communications. Previous studies have proposed machine learning-based methods to predict received signal strength for future time periods using time series of depth images to mitigate the line-of-sight (LOS) path blockage by pedestrians in mmWave communication. However, these image-based methods have limited applicability due to privacy concerns as camera images may contain sensitive information. This study proposes a point cloud-based method for mmWave link quality prediction and demonstrates its feasibility through experiments. Point clouds represent three-dimensional (3D) spaces as a set of points and are sparser and less likely to contain sensitive information than camera images. Additionally, point clouds provide 3D position and motion information, which is necessary for understanding the radio propagation environment involving pedestrians. This study designs the mmWave link quality prediction method and conducts realistic indoor experiments, where the link quality fluctuates significantly due to human blockage, using commercially available IEEE 802.11ad-based 60 GHz wireless LAN devices and Kinect v2 RGB-D camera and Velodyne VLP-16 light detection and ranging (LiDAR) for point cloud acquisition. The experimental results showed that our proposed method can predict future large attenuation of mmWave received signal strength and throughput induced by the LOS path blockage by pedestrians with comparable or superior accuracy to image-based prediction methods. Hence, our point cloud-based method can serve as a viable alternative to image-based methods.Comment: Submitted to IEEE Transactions on Machine Learning in Communications and Networkin

Trans-Inpainter: Wireless Channel Information- Guided Image Restoration via Multimodal Transformer

Image inpainting is a critical computer vision task to restore missing or damaged image regions. In this paper, we propose Trans-Inpainter, a novel multimodal image inpainting method guided by Channel State Information (CSI) data. Leveraging the power of transformer architectures, Trans-Inpainter effectively extracts visual information from CSI time sequences, enabling high-quality and realistic image inpainting. To evaluate its performance, we compare Trans-Inpainter with RF-Inpainter, the state-of-the-art radio frequency (RF) signal-based image inpainting technique. Through comprehensive experiments, Trans-Inpainter consistently demonstrates superior performance in various scenarios. Additionally, we investigate the impact of CSI data variations on Trans-Inpainter's imaging ability, analyzing individual sensor data, fused data from multiple sensors, and altered CSI matrix dimensions. These insights provide valuable references for future wireless sensing and computer vision studies

Complete integrability of derivative nonlinear Schr\"{o}dinger-type equations

We study matrix generalizations of derivative nonlinear Schr\"{o}dinger-type equations, which were shown by Olver and Sokolov to possess a higher symmetry. We prove that two of them are `C-integrable' and the rest of them are `S-integrable' in Calogero's terminology.Comment: 14 pages, LaTeX2e (IOP style), to appear in Inverse Problem

Automated bone marrow analysis using the CD4000 automated haematology analyser

At present, bone marrow analysis is performed microscopically, but is time consuming and labour intensive. No automated methods have been successfully applied to classification of bone marrows cells because automated blood cell analysers have been incapable of identifying erythroblasts. The present study was designed to evaluate automated analysis of bone marrow aspirates with the CELL-DYN 4000 (CD4000) haematology analyser, which enables automated determination of erythroblast counts in both the normal mode (haemolytic time; 11.5s) and the resistant RBC mode (34.0s). The percentages of subpopulations including lymphocytes, neutrophils and erythroblasts were obtained with the CD4000, and as a reference, differential counts by microscopic observation of May–Grünwald–Giesa-stained films of bone marrow aspirates were performed (n=98). Significant correlations (P < 0.01) between the results obtained with the two methods were observed for total nucleated cell count and lymphocytes, neutrophils, erythroblasts and myeloid/erythroid (M/E) ratio. However, there were biases in the average percentages of erythroblasts, lymphocytes and M/E ratio obtained using the normal mode with the CD4000 toward values lower than those obtained with the microscopic method. Using the RBC resistant mode with the CD4000, the average percentages of erythroblasts, lymphocytes and M/E ratio approximated those obtained with the microscopic method. In conclusion, the CD4000 in resistant RBC mode is more useful for analysis of bone marrow aspirates than is the normal mode, because the former better approximates the M/E ratio than the latter

Jellyfish mucin may have potential disease-modifying effects on osteoarthritis

<p>Abstract</p> <p>Background</p> <p>We aimed to study the effects of intra-articular injection of jellyfish mucin (qniumucin) on articular cartilage degeneration in a model of osteoarthritis (OA) created in rabbit knees by resection of the anterior cruciate ligament. Qniumucin was extracted from <it>Aurelia aurita </it>(moon jellyfish) and <it>Stomolophus nomurai </it>(Nomura's jellyfish) and purified by ion exchange chromatography. The OA model used 36 knees in 18 Japanese white rabbits. Purified qniumucin extracts from <it>S. nomurai </it>or <it>A. aurita </it>were used at 1 mg/ml. Rabbits were divided into four groups: a control (C) group injected with saline; a hyaluronic acid (HA)-only group (H group); two qniumucin-only groups (M groups); and two qniumucin + HA groups (MH groups). One milligram of each solution was injected intra-articularly once a week for 5 consecutive weeks, starting from 4 weeks after surgery. Ten weeks after surgery, the articular cartilage was evaluated macroscopically and histologically.</p> <p>Results</p> <p>In the C and M groups, macroscopic cartilage defects extended to the subchondral bone medially and laterally. When the H and both MH groups were compared, only minor cartilage degeneration was observed in groups treated with qniumucin in contrast to the group without qniumucin. Histologically, densely safranin-O-stained cartilage layers were observed in the H and two MH groups, but cartilage was strongly maintained in both MH groups.</p> <p>Conclusion</p> <p>At the concentrations of qniumucin used in this study, injection together with HA inhibited articular cartilage degeneration in this model of OA.</p

Expression of anti-fungal peptide, β-defensin 118 in oral fibroblasts induced by C. albicans β-glucan-containing particles

Objective: Although oral fibroblasts are thought to have the potential to enhance host defenses against Candida albicans , it is unknown whether they are able to recognize Candida cell components to increase the expression of antifungal peptides, such as defensin factors, against Candida infection. Methodology: We performed expression profiles of defensin genes induced by heat-killed C. albicans in oral immortalized fibroblasts (GT1) using cDNA microarray analysis. From those results, quantitative RT-PCR was used to examine the effects of Candida β-glucan-containing particles (β-GPs) on β-Defensin 118 (DEFB 118) expression in oral mucosal cells. Furthermore, the antifungal activities of recombinant DEFB 118 against C. albicans and C. glabrata were investigated using fungicidal assays. Results: Microarray analysis showed that DEFB118, β-Defensin 129 (DEFB129), and α-Defensin 1 (DEFA1) genes were induced by heat-killed C. albicans and that their mRNA expressions were also significantly increased by live as well as heat-killed C. albicans . Next, we focused on DEFB118, and found that GT1, primary fibroblasts, and RT7 (oral immortalized keratinocytes) constitutively expressed DEFB118 mRNA expression in RT-PCR. Furthermore, C. albicans β-GPs significantly increased the expression of DEFB118 mRNA in GT1 and primary fibroblasts. Although DEFB118 mRNA expression in RT7 was significantly induced by both live and heat-killed C. albicans, C. albicans β-GPs failed to have an effect on that expression. Finally, recombinant DEFB118 significantly decreased the survival of both strains of C. albicans in a dose-dependent manner, whereas no effects were seen for both C. glabrata strains. Conclusion: DEFB118, induced by C. albicans β-GPs from oral fibroblasts, may play an important role in oral immune responses against C. albicans infection