Wi-Fi Teeter-Totter: Overclocking OFDM for Internet of Things

The conventional high-speed Wi-Fi has recently become a contender for low-power Internet-of-Things (IoT) communications. OFDM continues its adoption in the new IoT Wi-Fi standard due to its spectrum efficiency that can support the demand of massive IoT connectivity. While the IoT Wi-Fi standard offers many new features to improve power and spectrum efficiency, the basic physical layer (PHY) structure of transceiver design still conforms to its conventional design rationale where access points (AP) and clients employ the same OFDM PHY. In this paper, we argue that current Wi-Fi PHY design does not take full advantage of the inherent asymmetry between AP and IoT. To fill the gap, we propose an asymmetric design where IoT devices transmit uplink packets using the lowest power while pushing all the decoding burdens to the AP side. Such a design utilizes the sufficient power and computational resources at AP to trade for the transmission (TX) power of IoT devices. The core technique enabling this asymmetric design is that the AP takes full power of its high clock rate to boost the decoding ability. We provide an implementation of our design and show that it can reduce the IoT's TX power by boosting the decoding capability at the receivers

Memory-augmented Neural Machine Translation

Neural machine translation (NMT) has achieved notable success in recent times, however it is also widely recognized that this approach has limitations with handling infrequent words and word pairs. This paper presents a novel memory-augmented NMT (M-NMT) architecture, which stores knowledge about how words (usually infrequently encountered ones) should be translated in a memory and then utilizes them to assist the neural model. We use this memory mechanism to combine the knowledge learned from a conventional statistical machine translation system and the rules learned by an NMT system, and also propose a solution for out-of-vocabulary (OOV) words based on this framework. Our experiments on two Chinese-English translation tasks demonstrated that the M-NMT architecture outperformed the NMT baseline by $9.0$ and $2.7$ BLEU points on the two tasks, respectively. Additionally, we found this architecture resulted in a much more effective OOV treatment compared to competitive methods

Flexible and Creative Chinese Poetry Generation Using Neural Memory

It has been shown that Chinese poems can be successfully generated by sequence-to-sequence neural models, particularly with the attention mechanism. A potential problem of this approach, however, is that neural models can only learn abstract rules, while poem generation is a highly creative process that involves not only rules but also innovations for which pure statistical models are not appropriate in principle. This work proposes a memory-augmented neural model for Chinese poem generation, where the neural model and the augmented memory work together to balance the requirements of linguistic accordance and aesthetic innovation, leading to innovative generations that are still rule-compliant. In addition, it is found that the memory mechanism provides interesting flexibility that can be used to generate poems with different styles

L-Ascorbic Acid Activates TET2 DNA Dioxygenase to Suppress Tumor Growth as a Co-substrate

The α-KG-dependent tumor suppressor ten-eleven translocation methyl-cytosine dioxygenase 2 (TET2) is frequently mutated in blood cancers and has impaired activities in solid tumors, both contributing to the DNA hypermethylation and tumorigenesis. L-Ascorbic acid, commonly known as vitamin C, has been reported to stimulate TET2 enzymatic activities with high specificity to upregulate gene expression involved in anti-tumor activities that suppress cancer progression. Other general reducers, such as glutathione, do not display the same effect. Previous studies suggested that intracellular accumulation of vitamin C is required for ascorbic activation of TET2 and that the vitamin C stimulation of TET2 is independent of iron uptake or the α-KG co-substrate production level. The molecular basis of how ascorbic acid regulates TET2 remains a mystery. Computational molecular docking study supports our hypothesis that vitamin C directly binds to the active site of TET2 as a novel co-substrate and activator, elevating the turnover rate of TET2 through direct recycling of the ferrous ion co-factor by reduction. Using Saturation Transfer Difference (STD) Nuclear Magnetic Resonance (NMR) spectroscopy, my study validated the direct binding of vitamin C to TET2. Some, but not all, mutations of amino acids in the TET2 active site known to be involved in binding with the co-substrate α-KG disrupt vitamin C-TET2 binding, suggesting that vitamin C occupies similar but nonidentical binding sites with α-KG. I also show that vitamin C treatment increases the expression of chemokines and PD-L1 genes in a TET2-dependent manner upon interferon treatment in both breast cancer 4T1 and melanoma B16 cell lines. Uncovering the mechanism of vitamin C regulation of TET2 through co-substrate binding will stimulate further studies on the broad class of α-KG dependent dioxygenases and provide mechanistic support for stimulating TET2 activity by vitamin C as adjuvant therapy for cancer immunotherapy.Bachelor of Scienc

Basaloid squamous cell carcinoma of the maxillary gingiva: A case report and review of the literature

Basaloid squamous cell carcinoma (BSCC) is a rare, but distinct histologic variant of squamous cell carcinoma in the head and neck region. It is considered to have a poor prognosis due to its aggressive behavior and tendency to metastasize. The usual sites of BSCC are the floor of the mouth, hypopharynx and base of the tongue, and according to the English-language literature its presentation in the gingiva is somewhat uncommon. In the current report, the unusual case of a 40-year-old male is presented; the patient exhibited a painless irregular mass in the maxillary gingiva, which infiltrated the maxillary sinus, as observed by computed tomography. Hematoxylin and eosin-stained sections revealed a diagnosis of BSCC with typical central necrosis in the cancer nests, which contained basaloid and squamous cells. Immunohistochemistry revealed that p63 was weakly positive, high molecular weight cytokeratin (CK) was focally positive, and S-100, CK7, CK14 and vimentin were negative. It must be noted that histopathology results may be incorrectly interpreted as adenoid cystic carcinoma, undifferentiated carcinoma and basal cell adenocarcinoma

DiffCloth: Diffusion Based Garment Synthesis and Manipulation via Structural Cross-modal Semantic Alignment

Cross-modal garment synthesis and manipulation will significantly benefit the way fashion designers generate garments and modify their designs via flexible linguistic interfaces. However, despite the significant progress that has been made in generic image synthesis using diffusion models, producing garment images with garment part level semantics that are well aligned with input text prompts and then flexibly manipulating the generated results still remains a problem. Current approaches follow the general text-to-image paradigm and mine cross-modal relations via simple cross-attention modules, neglecting the structural correspondence between visual and textual representations in the fashion design domain. In this work, we instead introduce DiffCloth, a diffusion-based pipeline for cross-modal garment synthesis and manipulation, which empowers diffusion models with flexible compositionality in the fashion domain by structurally aligning the cross-modal semantics. Specifically, we formulate the part-level cross-modal alignment as a bipartite matching problem between the linguistic Attribute-Phrases (AP) and the visual garment parts which are obtained via constituency parsing and semantic segmentation, respectively. To mitigate the issue of attribute confusion, we further propose a semantic-bundled cross-attention to preserve the spatial structure similarities between the attention maps of attribute adjectives and part nouns in each AP. Moreover, DiffCloth allows for manipulation of the generated results by simply replacing APs in the text prompts. The manipulation-irrelevant regions are recognized by blended masks obtained from the bundled attention maps of the APs and kept unchanged. Extensive experiments on the CM-Fashion benchmark demonstrate that DiffCloth both yields state-of-the-art garment synthesis results by leveraging the inherent structural information and supports flexible manipulation with region consistency

DiffCloth: Diffusion Based Garment Synthesis and Manipulation via Structural Cross-modal Semantic Alignment

Cross-modal garment synthesis and manipulation will significantly benefit the way fashion designers generate garments and modify their designs via flexible linguistic interfaces.Current approaches follow the general text-to-image paradigm and mine cross-modal relations via simple cross-attention modules, neglecting the structural correspondence between visual and textual representations in the fashion design domain. In this work, we instead introduce DiffCloth, a diffusion-based pipeline for cross-modal garment synthesis and manipulation, which empowers diffusion models with flexible compositionality in the fashion domain by structurally aligning the cross-modal semantics. Specifically, we formulate the part-level cross-modal alignment as a bipartite matching problem between the linguistic Attribute-Phrases (AP) and the visual garment parts which are obtained via constituency parsing and semantic segmentation, respectively. To mitigate the issue of attribute confusion, we further propose a semantic-bundled cross-attention to preserve the spatial structure similarities between the attention maps of attribute adjectives and part nouns in each AP. Moreover, DiffCloth allows for manipulation of the generated results by simply replacing APs in the text prompts. The manipulation-irrelevant regions are recognized by blended masks obtained from the bundled attention maps of the APs and kept unchanged. Extensive experiments on the CM-Fashion benchmark demonstrate that DiffCloth both yields state-of-the-art garment synthesis results by leveraging the inherent structural information and supports flexible manipulation with region consistency.Comment: accepted by ICCV202

E2F1 Suppresses Oxidative Metabolism and Endothelial Differentiation of Bone Marrow Progenitor Cells

RATIONALE: The majority of current cardiovascular cell therapy trials use bone marrow progenitor cells (BM PCs) and achieve only modest efficacy; the limited potential of these cells to differentiate into endothelial-lineage cells is one of the major barriers to the success of this promising therapy. We have previously reported that the E2F transcription factor 1 (E2F1) is a repressor of revascularization after ischemic injury. OBJECTIVE: We sought to define the role of E2F1 in the regulation of BM PC function. METHODS AND RESULTS: Ablation of E2F1 (E2F1 deficient) in mouse BM PCs increases oxidative metabolism and reduces lactate production, resulting in enhanced endothelial differentiation. The metabolic switch in E2F1-deficient BM PCs is mediated by a reduction in the expression of pyruvate dehydrogenase kinase 4 and pyruvate dehydrogenase kinase 2; overexpression of pyruvate dehydrogenase kinase 4 reverses the enhancement of oxidative metabolism and endothelial differentiation. Deletion of E2F1 in the BM increases the amount of PC-derived endothelial cells in the ischemic myocardium, enhances vascular growth, reduces infarct size, and improves cardiac function after myocardial infarction. CONCLUSION: Our results suggest a novel mechanism by which E2F1 mediates the metabolic control of BM PC differentiation, and strategies that inhibit E2F1 or enhance oxidative metabolism in BM PCs may improve the effectiveness of cell therapy