Achieving Max-Min Throughput in LoRa Networks

With growing popularity, LoRa networks are pivotally enabling Long Range connectivity to low-cost and power-constrained user equipments (UEs). Due to its wide coverage area, a critical issue is to effectively allocate wireless resources to support potentially massive UEs in the cell while resolving the prominent near-far fairness problem for cell-edge UEs, which is challenging to address due to the lack of tractable analytical model for the LoRa network and its practical requirement for low-complexity and low-overhead design. To achieve massive connectivity with fairness, we investigate the problem of maximizing the minimum throughput of all UEs in the LoRa network, by jointly designing high-level policies of spreading factor (SF) allocation, power control, and duty cycle adjustment based only on average channel statistics and spatial UE distribution. By leveraging on the Poisson rain model along with tailored modifications to our considered LoRa network, we are able to account for channel fading, aggregate interference and accurate packet overlapping, and still obtain a tractable and yet accurate closed-form formula for the packet success probability and hence throughput. We further propose an iterative balancing (IB) method to allocate the SFs in the cell such that the overall max-min throughput can be achieved within the considered time period and cell area. Numerical results show that the proposed scheme with optimized design greatly alleviates the near-far fairness issue, and significantly improves the cell-edge throughput.Comment: 6 pages, 4 figures, published in Proc. International Conference on Computing, Networking and Communications (ICNC), 2020. This paper proposes stochastic-geometry based analytical framework for a single-cell LoRa network, with joint optimization to achieve max-min throughput for the users. Extended journal version for large-scale multi-cell LoRa network: arXiv:2008.0743

Distributed Quantile Regression Analysis and a Group Variable Selection Method

This dissertation develops novel methodologies for distributed quantile regression analysis for big data by utilizing a distributed optimization algorithm called the alternating direction method of multipliers (ADMM). Specifically, we first write the penalized quantile regression into a specific form that can be solved by the ADMM and propose numerical algorithms for solving the ADMM subproblems. This results in the distributed QR-ADMM algorithm. Then, to further reduce the computational time, we formulate the penalized quantile regression into another equivalent ADMM form in which all the subproblems have exact closed-form solutions and hence avoid iterative numerical methods. This results in the single-loop QPADM algorithm that further improve on the computational efficiency of the QR-ADMM. Both QR-ADMM and QPADM enjoy flexible parallelization by enabling data splitting across both sample space and feature space, which make them especially appealing for the case when both sample size n and feature dimension p are large. Besides the QR-ADMM and QPADM algorithms for penalized quantile regression, we also develop a group variable selection method by approximating the Bayesian information criterion. Unlike existing penalization methods for feature selection, our proposed gMIC algorithm is free of parameter tuning and hence enjoys greater computational efficiency. Although the current version of gMIC focuses on the generalized linear model, it can be naturally extended to the quantile regression for feature selection. We provide theoretical analysis for our proposed methods. Specifically, we conduct numerical convergence analysis for the QR-ADMM and QPADM algorithms, and provide asymptotical theories and oracle property of feature selection for the gMIC method. All our methods are evaluated with simulation studies and real data analysis

PEA265: Perceptual Assessment of Video Compression Artifacts

The most widely used video encoders share a common hybrid coding framework that includes block-based motion estimation/compensation and block-based transform coding. Despite their high coding efficiency, the encoded videos often exhibit visually annoying artifacts, denoted as Perceivable Encoding Artifacts (PEAs), which significantly degrade the visual Qualityof- Experience (QoE) of end users. To monitor and improve visual QoE, it is crucial to develop subjective and objective measures that can identify and quantify various types of PEAs. In this work, we make the first attempt to build a large-scale subjectlabelled database composed of H.265/HEVC compressed videos containing various PEAs. The database, namely the PEA265 database, includes 4 types of spatial PEAs (i.e. blurring, blocking, ringing and color bleeding) and 2 types of temporal PEAs (i.e. flickering and floating). Each containing at least 60,000 image or video patches with positive and negative labels. To objectively identify these PEAs, we train Convolutional Neural Networks (CNNs) using the PEA265 database. It appears that state-of-theart ResNeXt is capable of identifying each type of PEAs with high accuracy. Furthermore, we define PEA pattern and PEA intensity measures to quantify PEA levels of compressed video sequence. We believe that the PEA265 database and our findings will benefit the future development of video quality assessment methods and perceptually motivated video encoders.Comment: 10 pages,15 figures,4 table

The anticipatory unfolded protein response and estrogen receptor mutations in breast cancer

Estrogen, acting via estrogen receptor α (ERα), stimulates cancer cell proliferation and metastasis. Endocrine therapy targeting E2:ERα activity often leads to development of antiestrogen resistance. Approximately 30% of patients who have metastatic endocrine therapy resistant breast cancer express ERα mutations. Two of the most common and therefore widely studied mutations are ERαY537S and ERαD538G. Patients whose metastatic breast tumors express Y537S or D538G mutations have 1 year and 6 months shorter median survival time than patients whose metastatic tumors express wild-type ERα. To better characterized the aggressive phenotypes of the ERα mutations in breast cancer cells, we used CRISPR-Cas9 technology to replace wild-type ERα in T47D, human breast cancer cells, with the most common mutations, ERαY537S and ERαD538G. The mutant cells exhibit partially estrogen-independent and antiestrogen resistant gene expression and cell proliferation. A novel invasion-dissociation-rebinding (IDR) assay demonstrated that the mutant cells have a higher tendency to dissociate from invasion sites and rebind to a second site. Compared to wild type breast tumors, mutant tumors exhibited dramatic increases in lung metastasis. The ERαY537S mutation further enhanced the metastatic capability of the breast tumors. Gene set enrichment analysis (GSEA) showed Myc target pathways are highly induced in mutant cells. Moreover, chromatin immunoprecipitation showed constitutive, fulvestrant-resistant, recruitment of ERα mutants to the Myc enhancer region, resulting in estrogen-independent Myc overexpression in mutant cells and tumors. Knockdown and overexpression experiments showed Myc is necessary and sufficient for ligand-independent proliferation of the mutant cells but had no effect on metastasis-related phenotypes. Other than gain-of-function mutations, breast cancer cells can develop therapy resistance via recently described pathways of hormone action. Our laboratory recently revealed that estrogen acting through ERα, rapidly phosphorylates and activates phospholipase C γ (PLCγ) resulting in transient calcium release from endoplasmic reticulum and mild activation of the unfolded protein response. I identified that this anticipatory UPR is a conserved pathway shared by different mitogenic hormones including epidermal growth factor, estrogen and progesterone. EGF rapidly induced a calcium increase in the cytosol and moderate activation of the IRE1α and ATF6α arms of the UPR, resulting in induction of BiP chaperone. Knockdown or inhibition of EGF receptor (EGFR), PLCγ or IP3 receptor (IP3R) blocks the increase in intracellular Ca2+. While blocking the increase in intracellular Ca2+ by locking the IP3R calcium channel with 2-APB had no effect on EGF activation of the ERK or AKT signaling pathways, it abolished EGF-mediated immediate early gene expression, suggesting EGF stimulated calcium efflux and signaling transduction are two independent pathways and are both essential for EGF regulated gene expression. Knockdown of ATF6α or XBP1, which regulate UPR-induced chaperone production, inhibited EGF stimulated cell proliferation. These data highlight the importance of anticipatory UPR pathway in the normal actions of mitogenic hormones. Unlike EGFR which functions as a receptor tyrosine kinase, ERα cannot directly phosphorylate PLCγ. Using the small molecule ERα biomodulator, BHPI, which uses the same pathway as E2 and induces toxic hyperactivation of the anticipatory UPR, we applied unbiased long-term-selection on ERα positive breast cancer cells and isolated T47D and MCF-7 cells that proliferate in the presence of a lethal concentration of BHPI. We showed that 4 out of 11 T47D and almost all MCF-7 BHPI resistant clones have reduced Src expression. Src overexpression by virus transduction in resistant clones restored sensitivity to BHPI. Furthermore, in wild-type cells, several-fold knockdown of Src, but not of ERα, strongly blocked BHPI-mediated UPR activation and subsequent HMGB1 release and necrotic cell death. Supporting Src kinase linking estrogen and progesterone to activation of the anticipatory UPR, we identified extranuclear complexes of ERα:Src:PLCγ and progesterone receptor:Src:PLCγ. Thus, Src plays a previously undescribed pivotal role in activation of the tumor protective anticipatory UPR, thereby increasing the resilience of breast cancer cells

Baculovirus-mediated promoter assay and transcriptional analysis of white spot syndrome virus orf427 gene

BACKGROUND: White spot syndrome virus (WSSV) is an important pathogen of the penaeid shrimp with high mortalities. In previous reports, Orf427 of WSSV is characterized as one of the three major latency-associated genes of WSSV. Here, we were interested to analyze the promoter of orf427 and its expression during viral pathogenesis. RESULTS: in situ hybridization revealed that orf427 was transcribed in all the infected tissues during viral lytic infection and the translational product can be detected from the infected shrimp. A time-course RT-PCR analysis indicated that transcriptional products of orf427 could only be detected after 6 h post virus inoculation. Furthermore, a baculovirus-mediated promoter analysis indicated that the promoter of orf427 failed to express the EGFP reporter gene in both insect SF9 cells and primary shrimp cells. CONCLUSION: Our data suggested that latency-related orf427 might not play an important role in activating virus replication from latent phase due to its late transcription during the lytic infection

Impact of agricultural activities on pesticide residues in soil of edible bamboo shoot plantations

Edible bamboo shoot is one of the most important vegetables in Asian countries. Intensive agricultural management measures can cause many negative influences, such as soil acidification and excessive pesticide residues. In the present study, more than 300 soil samples were collected from edible bamboo shoot plantations in six areas throughout Zhejiang province, China, to investigate the soil pesticide pollution and its change after different agricultural activities. Thirteen organic chemicals were detected; nine less than that detected during a similar study executed in 2003–2004. All the detected residues were far below the Chinese national environmental standards for agricultural soils. The pesticide residues in bamboo plantations showed a decline over the past decade. Organic materials used for mulching and plantation’s background of being formerly a paddy field are two important factors increasing the pesticide residues. Conversely, lime application to acidified soil and mulching with uncontaminated new mountain soil could decrease the residues significantly. Our results indicated that the current agricultural activities are efficient in reducing pesticide residues in the soil of bamboo shoot plantations and should be further promoted