Technology diffusion in communication networks

The deployment of new technologies in the Internet is notoriously difficult, as evidence by the myriad of well-developed networking technologies that still have not seen widespread adoption (e.g., secure routing, IPv6, etc.) A key hurdle is the fact that the Internet lacks a centralized authority that can mandate the deployment of a new technology. Instead, the Internet consists of thousands of nodes, each controlled by an autonomous, profit-seeking firm, that will deploy a new networking technology only if it obtains sufficient local utility by doing so. For the technologies we study here, local utility depends on the set of nodes that can be reached by traversing paths consisting only of nodes that have already deployed the new technology. To understand technology diffusion in the Internet, we propose a new model inspired by work on the spread of influence in social networks. Unlike traditional models, where a node's utility depends only its immediate neighbors, in our model, a node can be influenced by the actions of remote nodes. Specifically, we assume node v activates (i.e. deploys the new technology) when it is adjacent to a sufficiently large connected component in the subgraph induced by the set of active nodes; namely, of size exceeding node v's threshold value \theta(v). We are interested in the problem of choosing the right seedset of nodes to activate initially, so that the rest of the nodes in the network have sufficient local utility to follow suit. We take the graph and thresholds values as input to our problem. We show that our problem is both NP-hard and does not admit an (1-o(1) ln|V| approximation on general graphs. Then, we restrict our study to technology diffusion problems where (a) maximum distance between any pair of nodes in the graph is r, and (b) there are at most \ell possible threshold values. Our set of restrictions is quite natural, given that (a) the Internet graph has constant diameter, and (b) the fact that limiting the granularity of the threshold values makes sense given the difficulty in obtaining empirical data that parameterizes deployment costs and benefits. We present algorithm that obtains a solution with guaranteed approximation rate of O(r^2 \ell \log|V|) which is asymptotically optimal, given our hardness results. Our approximation algorithm is a linear-programming relaxation of an 0-1 integer program along with a novel randomized rounding scheme.National Science Foundation (S-1017907, CCF-0915922

EXTH-08. REPLACEMENT OF MICROGLIA BY BRAIN-ENGRAFTED MACROPHAGES PREVENTS MEMORY DEFICITS AFTER THERAPEUTIC WHOLE-BRAIN IRRADIATION

Abstract Microglia have a distinct origin compared to blood circulating myeloid cells. Under normal physiological conditions, microglia are maintained by self-renewal, independent of hematopoietic progenitors. Following genetic or pharmacologic depletion, newborn microglia derive from the local residual pool and quickly repopulate the entire brain. The depletion of brain resident microglia during therapeutic whole-brain irradiation fully prevents irradiation-induced synaptic loss and recognition memory deficits but the mechanisms driving these protective effects are unknown. Here, we demonstrate that after CSF-1R inhibitor-mediated microglia depletion and therapeutic whole-brain irradiation, circulating monocytes engraft into the brain and replace the microglia pool. These monocyte-derived brain-engrafted macrophages have reduced phagocytic activity compared to microglia from irradiated brains, but similar to locally repopulated microglia without brain irradiation. Transcriptome comparisons reveal that brain-engrafted macrophages have both monocyte and embryonic microglia signatures. These results suggest that monocyte-derived brain-engrafted macrophages represent a novel therapeutic avenue for the treatment of brain radiotherapy-induced cognitive deficits

Do ultrastructural changes in aged peritoneum contribute to ovarian cancer metastasis? [abstract]

Epithelial ovarian cancer (EOC) will affect 1 in 69 women born in the United States today. Currently, 80% of women newly diagnosed with EOC already have metastatic disease, thus early intervention during the metastatic process will improve the long-term survival rates of women with EOC. Metastasis in EOC occurs through a unique process where cells are shed from a primary tumor and form multicellular aggregates (MCA) that disseminate intraperitoneally in the ascites fluid

Compact and High-Performance TCAM Based on Scaled Double-Gate FeFETs

Ternary content addressable memory (TCAM), widely used in network routers and high-associativity caches, is gaining popularity in machine learning and data-analytic applications. Ferroelectric FETs (FeFETs) are a promising candidate for implementing TCAM owing to their high ON/OFF ratio, non-volatility, and CMOS compatibility. However, conventional single-gate FeFETs (SG-FeFETs) suffer from relatively high write voltage, low endurance, potential read disturbance, and face scaling challenges. Recently, a double-gate FeFET (DG-FeFET) has been proposed and outperforms SG-FeFETs in many aspects. This paper investigates TCAM design challenges specific to DG-FeFETs and introduces a novel 1.5T1Fe TCAM design based on DG-FeFETs. A 2-step search with early termination is employed to reduce the cell area and improve energy efficiency. A shared driver design is proposed to reduce the peripherals area. Detailed analysis and SPICE simulation show that the 1.5T1Fe DG-TCAM leads to superior search speed and energy efficiency. The 1.5T1Fe TCAM design can also be built with SG-FeFETs, which achieve search latency and energy improvement compared with 2FeFET TCAM.Comment: Accepted by Design Automation Conference (DAC) 202

Lysophoshatidic acid regulation of cell surface-associated proteases

Abstract only availableLysophosphatidic acid (LPA) is a potential biomarker of ovarian cancer and is thought to promote early stages of cancer progression through the stimulation of two cell surface associated proteases. The affects of LPA on the expression and cell surface association of two proteolytic enzymes associated with ovarian cancer progression, matrix metalloproteinase-9 (MMP-9) and urokinase-type plasminogen activator (uPA), were analyzed. Both MMP-9 and uPA have been linked with cancer cell invasion due to their proteolytic activity. The cell surface association and activation of MMP-9 is a chief mechanism by which cells invade collagen rich barriers, whereas the increased binding of uPA to its cell surface receptor promotes the conversion of plasminogen to plasmin which also promotes cell invasion. LPA was shown to increase the expression of the MMP-9 protease in a concentration dependent manner in both OVCA 429 and OVCA 433 ovarian cancer cell cultures at concentrations well below those normally found in ascites fluids ( 1 M). LPA treatment (80 M) showed as much as a 3.5 fold increase in MMP-9 expression. Further, LPA treatment increased the expression of MMP-9 over MMP-2 in conditioned media of both OVCA 429 and OVCA 433 cells. Stimulation of uPA activity was also shown in culture medium but required the elevated concentrations ( 20 M) often found in the ascites of ovarian cancer patients. Inhibitor studies showed that inhibition of PI-3K signaling (most evidently in OVCA 433 cells) and p38 MAPK (namely in OVCA 429 cells) repressed LPA stimulation of MMP-9 expression in a dose-dependent fashion. Future studies involving matrigel invasion assays will evaluate the functional consequence of LPA-stimulated MMP-9 expression and enhanced cell surface proteolysis on ovarian cancer cell invasive activity.NIH grant to M.S Stac

Cross-identity Video Motion Retargeting with Joint Transformation and Synthesis

In this paper, we propose a novel dual-branch Transformation-Synthesis network (TS-Net), for video motion retargeting. Given one subject video and one driving video, TS-Net can produce a new plausible video with the subject appearance of the subject video and motion pattern of the driving video. TS-Net consists of a warp-based transformation branch and a warp-free synthesis branch. The novel design of dual branches combines the strengths of deformation-grid-based transformation and warp-free generation for better identity preservation and robustness to occlusion in the synthesized videos. A mask-aware similarity module is further introduced to the transformation branch to reduce computational overhead. Experimental results on face and dance datasets show that TS-Net achieves better performance in video motion retargeting than several state-of-the-art models as well as its single-branch variants. Our code is available at https://github.com/nihaomiao/WACV23_TSNet.Comment: WACV 202