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Partial Differentiation of Real Binary Functions
2008
Formalized Mathematics
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In this article, we define two single-variable functions SVF1 and SVF2, then discuss partial differentiation of real binary functions by dint of one variable function SVF1 and SVF2. The main properties of partial differentiation are shown [7] .
doi:10.2478/v10037-008-0041-z
fatcat:odhxeg7nnvbvre5ejdzxwzpvzq
Photonics-assisted compressive sampling system for wideband spectrum sensing (Invited Paper)
2017
Chinese Optics Letters (COL)
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Compressive sampling (CS) has attracted considerable attention in microwave and radio frequency (RF) fields in recent years. It enables the acquisition of high-frequency signals at a rate much smaller than their Nyquist rates. Combined with photonics technology, traditional CS systems can significantly enlarge their operating bandwidth, which offers great potential for spectrum sensing in cognitive radios. In this Letter, we review our recent work on photonic CS systems for wideband spectrum
doi:10.3788/col201715.010012
fatcat:dq3yfssplrdwfbufbi3wqbwfrq
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... sing. First, a proof-of-concept photonics-assisted CS system is demonstrated; it is capable of acquiring numerous radar pulses in an instantaneous bandwidth spanning from 500 MHz to 5 GHz with a 500-MHz analog-to-digital converter (ADC). To further reduce the acquisition bandwidth, multi-channel photonics-assisted CS systems are proposed for the first time, enabling the acquisition of multi-tone signals with frequencies up to 5 GHz by using 120-MHz ADCs. In addition, the system bandwidth is increased from 5 to 20 GHz by employing time-interleaved optical sampling.
Slug-upregulated miR-221 promotes breast cancer progression through suppressing E-cadherin expression
2016
Scientific Reports
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It is generally regarded that E-cadherin is downregulated during tumorigenesis via Snail/Slug-mediated E-cadherin transcriptional reduction. However, this transcriptional suppressive mechanism cannot explain the failure of producing E-cadherin protein in metastatic breast cancer cells after overexpressing E-cadherin mRNA. Here we reveal a novel mechanism that E-cadherin is post-transcriptionally regulated by Slug-promoted miR-221, which serves as an additional blocker for E-cadherin expression
doi:10.1038/srep25798
pmid:27174021
pmcid:PMC4865839
fatcat:7s6l7wdkrjdmhicdwljrd5fsky
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... n metastatic tumor cells. Profiling the predicted E-cadherin-targeting miRNAs in breast cancer tissues and cells showed that miR-221 was abundantly expressed in breast tumor and metastatic MDA-MB-231 cells and its level was significantly higher in breast tumor or MDA-MB-231 cells than in distal nontumor tissue and low-metastatic MCF-7 cells, respectively. MiR-221, which level inversely correlated with E-cadherin level in breast cancer cells, targeted E-cadherin mRNA open reading frame (ORF) and suppressed E-cadherin protein expression. Depleting or increasing miR-221 level in breast cancer cells induced or decreased E-cadherin protein level, leading to suppressing or promoting tumor cell progression, respectively. Moreover, miR-221 was specifically upregulated by Slug but not Snail. TGF-β treatment enhanced Slug activity and thus increased miR-221 level in MCF-7 cells. In summary, our results provide the first evidence that Slug-upregulated miR-221 promotes breast cancer progression via reducing E-cadherin expression. Understanding the mechanisms that govern tumor metastasis, a main reason of tumor-related mortality 1 , is a great challenge in cancer research 2 . Epithelial-mesenchymal transition (EMT) is a key step in the progression of tumors toward metastasis and invasion 3 . Cells that undergone EMT rapidly lose the cell-cell contacts, acquire mesenchymal properties and develop migratory and invasive capacity 4 . Although the EMT process is complex, the hallmark of EMT is the downregulation of E-cadherin, an essential adhesive molecule in the establishment of epithelial adhesion junction and a tight polarized cell layer 5 . Downregulation of E-cadherin expression has been found in carcinomas arising in various tissues 6,7 . In human breast cancer, loss of expression of E-cadherin affect the invasive or metastatic behavior of breast cancer cells and was associated with poorly differentiated tumors and poorer prognosis 8, 9 . Previous studies revealed that E-box elements in the E-cadherin promoter played a critical negative regulatory role in E-cadherin gene transcription in breast cancer cell lines. Two zinc-finger transcription factors known to bind E-box elements, Slug and Snail, are potential repressors of E-cadherin transcription 5,10-12 . The correlation between the expression of Slug and the loss of E-cadherin transcripts was suggested by analyzing the expression patterns of Slug, Snail and E-cadherin in breast cancer cell lines 13 . However, recent studies have shown that E-cadherin expression might be also modulated at a posttranscriptional level 1 . Although the level of E-cadherin expression is significantly decreased or even no during tumorigenesis, tumor cells still contain considerable amount of E-cadherin mRNA 14, 15 . The disparity between E-cadherin protein and mRNA levels in metastatic tumor cells was also confirmed by our experiment of overexpressing E-cadherin protein in metastatic tumor cells, in which no E-cadherin protein was produced while E-cadherin mRNA was overexpressed (Zen et al., unpublished). MicroRNAs (miRNAs), as a class of noncoding RNAs, that regulate gene expression at posttranscriptional level, resulting in either mRNA degradation or translational inhibition 16, 17 . Accumulating evidence has demonstrated that miRNAs play a key role in the cellular processes of differentiation, proliferation, maturation and apoptosis 18, 19 . Nagaoka et al. reported that knockdown of miR-200a in mammary glands prevented increases in E-cadherin mRNA expression and thus decreased E-cadherin signal 20 . Ma et al. reported that miR-9 could inhibit E-cadherin expression by binding to the 3′ -UTR of E-cadherin mRNA 1 . However, in our E-cadherin reexpression experiment, only E-cadherin (ORF) region without 5′ -UTR (contains transcription factor binding sites) and 3′ -UTR (contains classical miRNA binding sites) has been cloned into expression vector, what caused that metastatic cancer cells fail to increase the protein level of E-cadherin with highly transcribed E-cadherin (ORF) mRNA level. This disparity between E-cadherin mRNA and protein level strongly argues that there is a previously unidentified mechanism to regulate E-cadherin expression at posttranscriptional level. In the present study, we determined a novel miRNA-based regulatory mechanism for E-cadherin expression in metastatic breast cancer cell. We demonstrated that Slug specifically promoted miR-221 expression, which in turn, directly targeted the E-cadherin mRNA transcript, leading to reduction of E-cadherin protein level. Furthermore, both in vitro and in vivo results showed that Slug-promoted miR-221 enhanced the breast tumor progression through reducing E-cadherin protein expression. Results Posttranscriptional regulation of E-cadherin in breast tumor tissues and metastatic MDA-MB-231 cells. First, we compared the protein expression and mRNA level of E-cadherin in breast tumor tissues and distal normal tissue, as well as metastatic breast cancer MDA-MB-231 cells and non-metastatic MCF-7 cancer cells. In the experiment, 8 paired breast tumor tissue and distal normal tissue samples were collected and tested. As shown in Fig. 1a and Fig. S1 , E-cadherin protein expression in metastatic MDA-MB-231 cells and breast tumor was significantly lower than that in normal tissue and MCF-7 cells, respectively. The levels of E-cadherin mRNA are also lower in MDA-MB-231and tumor tissue cells than in MCF-7 cells and normal tissue (Fig. 1b) ,
Exotic Electronic Property of Phosphorene Nanoribbons Driven by External Electric Field
[article]
2019
arXiv
pre-print
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Author contributions Jifan Hu and Hongwei Qin proposed the main ideal of this work. Liang Liu did numerical calculations. Liang Liu and Jifan Hu wrote the manuscript. ...
arXiv:1904.04991v1
fatcat:b5pra7fom5hg7hk63bypyyjr74
Weighing Counts: Sequential Crowd Counting by Reinforcement Learning
[article]
2020
arXiv
pre-print
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We formulate counting as a sequential decision problem and present a novel crowd counting model solvable by deep reinforcement learning. In contrast to existing counting models that directly output count values, we divide one-step estimation into a sequence of much easier and more tractable sub-decision problems. Such sequential decision nature corresponds exactly to a physical process in reality scale weighing. Inspired by scale weighing, we propose a novel 'counting scale' termed LibraNet
arXiv:2007.08260v1
fatcat:w2f2co6kfbh65mta7vd2sfe5uq
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... e the count value is analogized by weight. By virtually placing a crowd image on one side of a scale, LibraNet (agent) sequentially learns to place appropriate weights on the other side to match the crowd count. At each step, LibraNet chooses one weight (action) from the weight box (the pre-defined action pool) according to the current crowd image features and weights placed on the scale pan (state). LibraNet is required to learn to balance the scale according to the feedback of the needle (Q values). We show that LibraNet exactly implements scale weighing by visualizing the decision process how LibraNet chooses actions. Extensive experiments demonstrate the effectiveness of our design choices and report state-of-the-art results on a few crowd counting benchmarks. We also demonstrate good cross-dataset generalization of LibraNet. Code and models are made available at: https://git.io/libranet
Knowledge Distillation via the Target-aware Transformer
[article]
2022
arXiv
pre-print
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Knowledge distillation becomes a de facto standard to improve the performance of small neural networks. Most of the previous works propose to regress the representational features from the teacher to the student in a one-to-one spatial matching fashion. However, people tend to overlook the fact that, due to the architecture differences, the semantic information on the same spatial location usually vary. This greatly undermines the underlying assumption of the one-to-one distillation approach.
arXiv:2205.10793v1
fatcat:4aehzge26jah7phukgi6sldcem
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... this end, we propose a novel one-to-all spatial matching knowledge distillation approach. Specifically, we allow each pixel of the teacher feature to be distilled to all spatial locations of the student features given its similarity, which is generated from a target-aware transformer. Our approach surpasses the state-of-the-art methods by a significant margin on various computer vision benchmarks, such as ImageNet, Pascal VOC and COCOStuff10k. Code will be released soon.
The Arecibo Ultra-Deep Survey
[article]
2020
arXiv
pre-print
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China and the International Centre for Radio Astronomy Research (ICRAR) in the University of Western Australia (UWA) for financial support during Hongwei Xi studying at ICRAR. ...
Martin10
Masui13
Neeleman16
Noterdaeme09
Noterdaeme12
Peroux03
Prochaska05
Prochaska09
Rao00
Rao06
Rao17
Rhee13
Rhee16
Rhee18
Songaila10
Zafar13
Zwaan05
This work
Kim15
Dave17
Hongwei ...
arXiv:2012.09516v1
fatcat:kepb53n3dzgkzpsxpev23tj2h4
Exploring Inter-Channel Correlation for Diversity-preserved KnowledgeDistillation
[article]
2022
arXiv
pre-print
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Knowledge Distillation has shown very promising abil-ity in transferring learned representation from the largermodel (teacher) to the smaller one (student).Despitemany efforts, prior methods ignore the important role ofretaining inter-channel correlation of features, leading tothe lack of capturing intrinsic distribution of the featurespace and sufficient diversity properties of features in theteacher network.To solve the issue, we propose thenovel Inter-Channel Correlation for Knowledge
arXiv:2202.03680v1
fatcat:p5kwvbmjmjb4bczurbix57324i
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... ation(ICKD), with which the diversity and homology of the fea-ture space of the student network can align with that ofthe teacher network. The correlation between these twochannels is interpreted as diversity if they are irrelevantto each other, otherwise homology. Then the student isrequired to mimic the correlation within its own embed-ding space. In addition, we introduce the grid-level inter-channel correlation, making it capable of dense predictiontasks. Extensive experiments on two vision tasks, includ-ing ImageNet classification and Pascal VOC segmentation,demonstrate the superiority of our ICKD, which consis-tently outperforms many existing methods, advancing thestate-of-the-art in the fields of Knowledge Distillation. Toour knowledge, we are the first method based on knowl-edge distillation boosts ResNet18 beyond 72% Top-1 ac-curacy on ImageNet classification. Code is available at:https://github.com/ADLab-AutoDrive/ICKD.
Pinning controllability of autonomous Boolean control networks
2016
Science China Information Sciences
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Autonomous Boolean networks (ABNs), which are developed to model the Boolean networks (BNs) with regulatory delays, are well known for their advantages of characterizing the intrinsic evolution rules of biological systems such as the gene regulatory networks. As a special type of ABNs with binary inputs, the autonomous Boolean control networks (ABCNs) are introduced for designing and analyzing the therapeutic intervention strategies where the binary inputs represent whether a certain medicine
doi:10.1007/s11432-016-5579-8
fatcat:ksszcplsdvbafh4f4dcem7mfli
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... dominated or not. An important problem in the therapeutic intervention is to design a control sequence steering an ABCN from an undesirable location (implying a diseased state) to a desirable one (corresponding to a healthy state). Motivated by such background, this paper aims to investigate the reachability and controllability of ABCNs with pinning controllers. Several necessary and sufficient criteria are provided by resorting to the semi-tensor product techniques of matrices. Moreover, an effective pinning control algorithm is presented for steering an ABCN from any given states to the desired state in the shortest time period. Numerical examples are also presented to demonstrate the results obtained.
Benchmarking the Robustness of LiDAR-Camera Fusion for 3D Object Detection
[article]
2022
arXiv
pre-print
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There are two critical sensors for 3D perception in autonomous driving, the camera and the LiDAR. The camera provides rich semantic information such as color, texture, and the LiDAR reflects the 3D shape and locations of surrounding objects. People discover that fusing these two modalities can significantly boost the performance of 3D perception models as each modality has complementary information to the other. However, we observe that current datasets are captured from expensive vehicles that
arXiv:2205.14951v1
fatcat:l3b4cudjunfgnbooy2dcxjtecy
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... are explicitly designed for data collection purposes, and cannot truly reflect the realistic data distribution due to various reasons. To this end, we collect a series of real-world cases with noisy data distribution, and systematically formulate a robustness benchmark toolkit, that simulates these cases on any clean autonomous driving datasets. We showcase the effectiveness of our toolkit by establishing the robustness benchmark on two widely-adopted autonomous driving datasets, nuScenes and Waymo, then, to the best of our knowledge, holistically benchmark the state-of-the-art fusion methods for the first time. We observe that: i) most fusion methods, when solely developed on these data, tend to fail inevitably when there is a disruption to the LiDAR input; ii) the improvement of the camera input is significantly inferior to the LiDAR one. We further propose an efficient robust training strategy to improve the robustness of the current fusion method. The benchmark and code are available at https://github.com/kcyu2014/lidar-camera-robust-benchmark
Pharmacological Actions of Multi-Target-Directed Evodiamine
2013
Molecules
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Evodiamine, a naturally occurring indole alkaloid, is one of the main bioactive ingredients of Evodiae fructus. With respect to the pharmacological actions of evodiamine, more attention has been paid to beneficial effects in insults involving cancer, obesity, nociception, inflammation, cardiovascular diseases, Alzheimer's disease, infectious diseases and thermo-regulative effects. Evodiamine has evolved a superior ability to bind various proteins, so we also argue that it is good starting point
doi:10.3390/molecules18021826
pmid:23434865
pmcid:PMC6270287
fatcat:gtrsr445dbcllmon2i3n6edeq4
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... for multi-target drugs. This review is primarily addressed to the description of the recent advances in the biological activity studies of evodiamine, with a focus on pharmacological mechanism. The present review also includes the pharmacokinetics and the detailed exploration of target-binding properties of evodiamine in an attempt to provide a direction for further multi-target drug design.
MiR-19b suppresses PTPRG to promote breast tumorigenesis
2016
OncoTarget
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Authorsʼ contributions These authors were involved with this manuscript: C Zhang, H Liang and X Chen (study concept and design, analysis and interpretation of data); X Chen (drafting of the manuscript) ...
doi:10.18632/oncotarget.11799
pmid:27602768
pmcid:PMC5325428
fatcat:5cnewal4vfepfgtgob7tbm3xta
New Role of Red Blood Cells in Absorption of DNA Bearing Tumorigenic Mutations from Lung Cancer Tissue
[article]
2021
medRxiv
pre-print
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Red blood cells (RBC) are commonly assumed to be vehicles for oxygen, carbon dioxide, and cells' metabolic byproducts. In this study, we investigated whether RBC may contain cancer-cell derived DNA and whether such cargo may be used as a biomarker for detecting cancer. Using an in vitro co-culture system, we showed that RBC could absorb DNA bearing tumorigenic mutations from cancer cell lines. Next, we demonstrated that we could detect common genetic mutations, including EGFR 19 deletion,
doi:10.1101/2021.01.15.21249747
fatcat:iuggjlvyyjdsrdvrrllx6usvd4
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... and KRAS G12 in RBC collected from early-stage non-small cell lung cancer patients. We were able to repeat our finding using both next-generation sequencing and droplet digital PCR. Our study highlights a new biological phenomenon involving RBC and their translational potential as a novel liquid biopsy technology platform that can be used for early cancer screening.
Prognostic Nutritional Index, Another Prognostic Factor for Extranodal Natural Killer/T Cell Lymphoma, Nasal Type
2020
Frontiers in Oncology
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Objective: The prognostic nutritional index (PNI) is a significant prognostic factor in diffuse large B cell lymphoma, follicular lymphoma, and other malignancies. The current study aimed to explore its prognostic role in extranodal natural killer/T cell lymphoma (ENKTL). Methods: Patients diagnosed with ENKTL and treated during 2002 and 2018 (n = 184) were retrospectively recruited. PNI was calculated from albumin concentration (g/L) and total lymphocyte count (*109/L). The association of PNI
doi:10.3389/fonc.2020.00877
pmid:32637354
pmcid:PMC7317673
fatcat:cpuwzoexcnbkra3wj7wpii5lzq
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... nd overall survival (OS) or progression-free survival (PFS) was assessed in univariate analysis and multivariate Cox regression validated by the 10-fold cross-validation method. Results: Survival analyses showed that both OS and PFS differed significantly between PNI groups stratified by a cutoff value of 49.0. The 3- and 5-year OS were 42.5 and 36.3% in the low-PNI (PNI < 49) subgroup and 70.6% and 63.9% (P < 0.001) in the high-PNI (PNI ≥ 49) subgroup, respectively. The corresponding PFS showed a similar pattern (38.4, 32.4 vs. 64.8, 54.0%, P < 0.001). Multivariate analysis indicated that PNI was significantly independent for both OS (HR = 0.517, 95% CI = 0.322-0.831, P = 0.006) and PFS (HR = 0.579, 95% CI = 0.373-0.899, P = 0.015). Furthermore, integrating PNI into the models of IPI (International Prognostic Index), KPI (Korean Prognostic Index), and PINK (prognostic index of natural killer lymphoma) could improve the area under the curve (AUC) and reduce the integrated Brier score (IBS) and Akaike Information Criterion (AIC) value of each model. Conclusion: PNI was a significant prognostic indicator for ENKTL.
Secreted microRNAs from tumor cells can suppress immune function
2016
Oncoimmunology
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z These authors contributed equally to this work. Our recent study reported an interesting finding that tumor cells can actively manipulate host immune function to facilitate tumor immune escape through the secretion of microRNAs (miRNAs). As an extension of this finding, we showed that blockage of the function of tumor-secreted miRNAs represents an effective therapeutic approach for cancer treatment.
doi:10.4161/2162402x.2014.982407
pmid:27141407
pmcid:PMC4839375
fatcat:n7224frisnbt7fmmjq2dlfoary
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