A Resource Allocation Algorithm for Ultra-Dense Networks Based on Deep Reinforcement Learning

The resource optimization of ultra-dense networks (UDNs) is critical to meet the huge demand of users for wireless data traffic. But the mainstream optimization algorithms have many problems, such as the poor optimization effect, and high computing load. This paper puts forward a wireless resource allocation algorithm based on deep reinforcement learning (DRL), which aims to maximize the total throughput of the entire network and transform the resource allocation problem into a deep Q-learning process. To effectively allocate resources in UDNs, the DRL algorithm was introduced to improve the allocation efficiency of wireless resources; the authors adopted the resource allocation strategy of the deep Q-network (DQN), and employed empirical repetition and target network to overcome the instability and divergence of the results caused by the previous network state, and to solve the overestimation of the Q value. Simulation results show that the proposed algorithm can maximize the total throughput of the network, while making the network more energy-efficient and stable. Thus, it is very meaningful to introduce the DRL to the research of UDN resource allocation

Role of convection in redistributing formaldehyde to the upper troposphere over North America and the North Atlantic during the summer 2004 INTEX campaign

Measurements of formaldehyde (CH2O) from a tunable diode laser absorption spectrometer (TDLAS) were acquired onboard the NASA DC‐8 aircraft during the summer 2004 INTEX‐NA campaign to test our understanding of convection and CH2O production mechanisms in the upper troposphere (UT, 6–12 km) over continental North America and the North Atlantic Ocean. The present study utilizes these TDLAS measurements and results from a box model to (1) establish sets of conditions by which to distinguish “background” UT CH2O levels from those perturbed by convection and other causes; (2) quantify the CH2O precursor budgets for both air mass types; (3) quantify the fraction of time that the UT CH2O measurements over North America and North Atlantic are perturbed during the summer of 2004; (4) provide estimates for the fraction of time that such perturbed CH2O levels are caused by direct convection of boundary layer CH2O and/or convection of CH2O precursors; (5) assess the ability of box models to reproduce the CH2O measurements; and (6) examine CH2O and HO2 relationships in the presence of enhanced NO. Multiple tracers were used to arrive at a set of UT CH2O background and perturbed air mass periods, and 46% of the TDLAS measurements fell within the latter category. In general, production of CH2O from CH4 was found to be the dominant source term, even in perturbed air masses. This was followed by production from methyl hydroperoxide, methanol, PAN‐type compounds, and ketones, in descending order of their contribution. At least 70% to 73% of the elevated UT observations were caused by enhanced production from CH2O precursors rather than direct transport of CH2O from the boundary layer. In the presence of elevated NO, there was a definite trend in the CH2O measurement–model discrepancy, and this was highly correlated with HO2 measurement–model discrepancies in the UT

Study on Target Detection & Recognition Using Laser 3D Vision Systems for Automatic Ship Loader

This paper purposes a solution of the target detection and identification for automatic ship loader. For automatic ship loaders, the operation target should be detected and identified continuously and real-timely. By using the laser measurement systems (LMS), the ship cargo holds and the bulk cargo can be rebuilt as a group of 3D points. Then the image processing algorithm can identify the positions, sizes and shapes of the cargo holds and the bulk cargo from the 3D points. Based on the target information identified by the image processing algorithm, the ship loader can finish the loading operation automatically. At last, this paper describes and analyzes the experiment of the cargo height detection using LMS in Coal Terminal of Tianjin Port

A Chinese cave links climate change, social impacts, and human adaptation over the last 500 years.

The collapse of some pre-historical and historical cultures, including Chinese dynasties were presumably linked to widespread droughts, on the basis of synchronicities of societal crises and proxy-based climate events. Here, we present a comparison of ancient inscriptions in Dayu Cave from Qinling Mountains, central China, which described accurate times and detailed impacts of seven drought events during the period of 1520-1920 CE, with high-resolution speleothem records from the same cave. The comparable results provide unique and robust tests on relationships among speleothem δ(18)O changes, drought events, and societal unrest. With direct historical evidences, our results suggest that droughts and even modest events interrupting otherwise wet intervals can cause serious social crises. Modeling results of speleothem δ(18)O series suggest that future precipitation in central China may be below the average of the past 500 years. As Qinling Mountain is the main recharge area of two large water transfer projects and habitats of many endangered species, it is imperative to explore an adaptive strategy for the decline in precipitation and/or drought events.We gratefully acknowledge the NBRPC (2013CB955902), NSFC (41372192; 41290254; 41230524; 41023006), and the WLF-CAS for funding this research. This study was also partially supported by Taiwan MOST (103-2119-M-002-022) and NTU (101R7625) grants. H.C. and R.L.E. received financial support from the U.S. NSF (EAR-0908792 and EAR-1211299), and S.F.M.B. received support from the Swiss NSF (CRSI22_132646/1).This is the final version. It was first published by NPG at http://www.nature.com/srep/2015/150717/srep12284/full/srep12284.html#author-information

A Chinese cave links climate change, social impacts, and human adaptation over the last 500 years

The collapse of some pre-historical and historical cultures, including Chinese dynasties were presumably linked to widespread droughts, on the basis of synchronicities of societal crises and proxy-based climate events. Here, we present a comparison of ancient inscriptions in Dayu Cave from Qinling Mountains, central China, which described accurate times and detailed impacts of seven drought events during the period of 1520–1920 CE, with high-resolution speleothem records from the same cave. The comparable results provide unique and robust tests on relationships among speleothem δ18O changes, drought events, and societal unrest. With direct historical evidences, our results suggest that droughts and even modest events interrupting otherwise wet intervals can cause serious social crises. Modeling results of speleothem δ18O series suggest that future precipitation in central China may be below the average of the past 500 years. As Qinling Mountain is the main recharge area of two large water transfer projects and habitats of many endangered species, it is imperative to explore an adaptive strategy for the decline in precipitation and/or drought events

Coastal New England pilot study to determine fossil and biogenic formaldehyde source contributions using radiocarbon

Author Posting. © American Geophysical Union, 2010. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research 115 (2010): D10301, doi:10.1029/2009JD012810.Compound specific radiocarbon analyses of atmospheric formaldehyde are reported as fraction modern (Fm) for a limited number of winter and summer air samples collected in coastal southern New England in 2007. The 11 of 13 samples with Fm 0.2 (max ∼ 0.35) were collected on days with strong northwesterly flow and the least urban impact. The Fm data were combined with VOC observations from the Rhode Island Department of Environmental Management, estimates of oxygenated VOC (OVOC), and back trajectories to interpret the relative contributions of biogenic and fossil carbon sources. It is argued that CH2O sources were dominated by pollutant VOCs and OVOCs from upwind coastal cities as opposed to more local biogenic VOCs at the times of sample collection.This research was supported by a graduate student internship program at WHOI National Ocean Sciences Accelerator Mass Spectrometry Facility (NSF OCE‐9807266) and by NASA project NNG04GB38G

Integrated Bioinformatic Analysis of a Competing Endogenous RNA Network Reveals a Prognostic Signature in Endometrial Cancer

In endometrial carcinoma, the clinical outcome directly correlates with the TNM stage, but the lack of sufficient information prevents accurate prediction. The molecular mechanism underlying the competing endogenous RNA (ceRNA) hypothesis has not been investigated in endometrial cancer. Multi-bioinformatic analyses, including differentially expressed gene analysis, ceRNA network construction, Cox regression analysis, function enrichment analysis, and protein-protein network analysis, were performed on the sequence data acquired from The Cancer Genome Atlas (TCGA) data bank. A ceRNA network comprising 366 mRNAs, 27 microRNAs (miRNAs), and 66 long non-coding RNAs (lncRNAs) was established. Survival analysis performed with the univariate Cox regression analysis revealed nine lncRNAs with prognostic power in endometrial carcinoma. In multivariate Cox regression analysis, a signature comprising LINC00491, LINC00483, ADARB2-AS1, and C8orf49 showed remarkable prognostic power. Risk score and neoplasm status, but not TNM stage, were independent prognostic factors of endometrial carcinoma. A ceRNA network comprising differentially expressed mRNAs, miRNAs, and lncRNAs may reveal the molecular events involved in the progression of endometrial carcinoma. In addition, the signature with prognostic value may discriminate patients with increased risk for poor outcome, which may allow physicians to take accurate decisions

Formaldehyde over North America and the North Atlantic during the summer 2004 INTEX campaign: Methods, observed distributions, and measurement‐model comparisons

A tunable diode laser absorption spectrometer (TDLAS) was operated on the NASA DC‐8 aircraft during the summer INTEX‐NA study to acquire ambient formaldehyde (CH2O) measurements over North America and the North Atlantic Ocean from ∼0.2 km to ∼12.5 km altitude spanning 17 science flights. Measurements of CH2O in the boundary layer and upper troposphere over the southeastern United States were anomalously low compared to studies in other years, and this was attributed to the record low temperatures over this region during the summer of 2004. Formaldehyde is primarily formed over the southeast from isoprene, and isoprene emissions are strongly temperature‐dependent. Despite this effect, the median upper tropospheric (UT) CH2O mixing ratio of 159 pptv from the TDLAS over continental North America is about a factor of 4 times higher than the median UT value of 40 pptv observed over remote regions during TRACE‐P. These observations together with the higher variability observed in this study all point to the fact that continental CH2O levels in the upper troposphere were significantly perturbed during the summer of 2004 relative to more typical background levels in the upper troposphere over more remote regions. The TDLAS measurements discussed in this paper are employed together with box model results in the companion paper by Fried et al. to further examine enhanced CH2O distributions in the upper troposphere due to convection. Measurements of CH2O on the DC‐8 were also acquired by a coil enzyme fluorometric system and compared with measurements from the TDLAS system

Circ_0040039 May Aggravate Intervertebral Disk Degeneration by Regulating the MiR-874-3p-ESR1 Pathway

The functional alteration of nucleus pulposus cells (NPCs) exerts a crucial role in the occurrence and progression of intervertebral disk degeneration (IDD). Circular RNAs and microRNAs (miRs) are critical regulators of NPC metabolic processes such as growth and apoptosis. In this study, bioinformatics tools, encompassing Gene Ontology pathway and Venn diagrams analysis, and protein–protein interaction (PPI) network construction were used to identify functional molecules related to IDD. PPI network unveiled that ESR1 was one of the most critical genes in IDD. Then, a key IDD-related circ_0040039-miR-874-3p-ESR1 interaction network was predicted and constructed. Circ_0040039 promoted miR-874-3p and repressed ESR1 expression, and miR-874-3p repressed ESR1 expression in NPCs, suggesting ESR1 might be a direct target of miR-874-3p. Functionally, circ_0040039 could enhance NPC apoptosis and inhibit NPC growth, revealing that circ_0040039 might aggravate IDD by stabilizing miR-874-3p and further upregulating the miR-874-3p-ESR1 pathway. This signaling pathway might provide a novel therapeutic strategy and targets for the diagnosis and therapy of IDD-related diseases