On the optimization problems in multiaccess communication systems

In a communication system, the bandwidth is often a primary resource. In order to support concurrent access by numerous users in a network, this finite and expensive resource must be shared among many independent contending users. Multi-access protocols control this access of the resource among users to achieve its efficient utilization, satisfy connectivity requirements and resolve any conflict among the contending users. Many optimization problems arise in designing a multi-access protocol. Among these, there is a class of optimization problems known as NP-complete, and no polynomial algorithm can possibly solve them. Conventional methods may not be efficient arid often produce poor solutions. In this dissertation, we propose a neural network-based algorithm for solving NP-complete problems encountered in multi-access communication systems. Three combinatorial optimization problems have been solved by the proposed algorithms; namely, frame pattern design in integrated TDMA communication networks, optimal broadcast scheduling in multihop packet radio networks, and optimal channel assignment in FDM A mobile communication networks. Numerical studies have shown encouraging results in searching for the global optimal solutions by using this algorithm. The determination of the related parameters regarding convergence and solution quality is investigated in this dissertation. Performance evaluations and comparisons with other algorithms have been performed

Representation of Dormant and Active Microbial Dynamics for Ecosystem Modeling

Dormancy is an essential strategy for microorganisms to cope with environmental stress. However, global ecosystem models typically ignore microbial dormancy, resulting in major model uncertainties. To facilitate the consideration of dormancy in these large-scale models, we propose a new microbial physiology component that works for a wide range of substrate availabilities. This new model is based on microbial physiological states and is majorly parameterized with the maximum specific growth and maintenance rates of active microbes and the ratio of dormant to active maintenance rates. A major improvement of our model over extant models is that it can explain the low active microbial fractions commonly observed in undisturbed soils. Our new model shows that the exponentially-increasing respiration from substrate-induced respiration experiments can only be used to determine the maximum specific growth rate and initial active microbial biomass, while the respiration data representing both exponentially-increasing and non-exponentially-increasing phases can robustly determine a range of key parameters including the initial total live biomass, initial active fraction, the maximum specific growth and maintenance rates, and the half-saturation constant. Our new model can be incorporated into existing ecosystem models to account for dormancy in microbially-mediated processes and to provide improved estimates of microbial activities.Comment: 38 pages, 2 Tables, 4 Figure

Correlation of expressions of S100A8 and S100A9 and its prognostic potential in nasopharyngeal carcinoma

Purpose: To investigate the expressions of S100 calcium-binding proteins A8 (S100A8) and S100 A9 (S100A9) in nasopharyngeal carcinoma (NPC) tissues and their correlation with clinical pathological characteristics and prognosis of NPC.Methods: Ninety-two NPC tissue samples and 92 nasopharyngitis tissue samples (controls) were collected. All the NPC patients were on follow-up for more than 5 years. The expressions of S100A8 and S100A9 were determined in these tissues by immunohistochemistry. The relationship between the expressions of S100A8 and S100A9, and the clinico-pathological features were analyzed by Spearman correlation analysis, and the results evaluated by Kaplan-Meier method.Results: The differences between their expressions in the two tissues were statistically significant (p < 0.05). Neither gender nor age was associated with expressions of S100A8 and S100A9 (p > 0.05), but they were closely related to the degree of differentiation, clinical stages and metastasis of lymph node (p < 0.05). The expression of S100A8 had significant positive correlation with the expression of S100A9 (r = 0.393, p = 0.000). Prognosis of patients with positive expressions of S100A8 and S100A9 was poor, when compared to patients with negative expressions of these proteins (p < 0.05).Conclusion: Expressions of S100A8 and S100A9 are closely related to the development of NPC. High expressions of the two proteins may have an important influence in the progress of tumor invasion but are associated with poor prognosis of NPC. These findings could be significant indicators of early diagnosis, effectiveness of treatment and prognosis of NPC.Keywords: S100A8, S100A9, Calcium-binding proteins, Prognosis, Nasopharyngeal carcinoma, Prognosi

Soil extracellular enzyme activities, soil carbon and nitrogen storage under nitrogen fertilization: A meta-analysis

Nitrogen (N) fertilization affects the rate of soil organic carbon (SOC) decomposition by regulating extracellular enzyme activities (EEA). Extracellular enzymes have not been represented in global biogeochemical models. Understanding the relationships among EEA and SOC, soil N (TN), and soil microbial biomass carbon (MBC) under N fertilization would enable modeling of the influence of EEA on SOC decomposition. Based on 65 published studies, we synthesized the activities of α-1,4-glucosidase (AG), β-1,4-glucosidase (BG), β-d-cellobiosidase (CBH), β-1,4-xylosidase (BX), β-1,4-N-acetyl-glucosaminidase (NAG), leucine amino peptidase (LAP), urease (UREA), acid phosphatase (AP), phenol oxidase (PHO), and peroxidase (PEO) in response to N fertilization. The proxy variables for hydrolytic C acquisition enzymes (C-acq), N acquisition (N-acq), and oxidative decomposition (OX) were calculated as the sum of AG, BG, CBH and BX; AG and LAP; PHO and PEO, respectively. The relationships between response ratios (RRs) of EEA and SOC, TN, or MBC were explored when they were reported simultaneously. Results showed that N fertilization significantly increased CBH, C-acq, AP, BX, BG, AG, and UREA activities by 6.4, 9.1, 10.6, 11.0, 11.2, 12.0, and 18.6%, but decreased PEO, OX and PHO by 6.1, 7.9 and 11.1%, respectively. N fertilization enhanced SOC and TN by 7.6% and 15.3%, respectively, but inhibited MBC by 9.5%. Significant positive correlations were found only between the RRs of C-acq and MBC, suggesting that changes in combined hydrolase activities might act as a proxy for MBC under N fertilization. In contrast with other variables, the RRs of AP, MBC, and TN showed unidirectional trends under different edaphic, environmental, and physiological conditions. Our results provide the first comprehensive set of evidence of how hydrolase and oxidase activities respond to N fertilization in various ecosystems. Future large-scale model projections could incorporate the observed relationship between hydrolases and microbial biomass as a proxy for C acquisition under global N enrichment scenarios in different ecosystems

Multi-year incubation experiments boost confidence in model projections of long-term soil carbon dynamics

Global soil organic carbon (SOC) stocks may decline with a warmer climate. However, model projections of changes in SOC due to climate warming depend on microbially-driven processes that are usually parameterized based on laboratory incubations. To assess how lab-scale incubation datasets inform model projections over decades, we optimized five microbially-relevant parameters in the Microbial-ENzyme Decomposition (MEND) model using 16 short-term glucose (6-day), 16 short-term cellulose (30-day) and 16 long-term cellulose (729-day) incubation datasets with soils from forests and grasslands across contrasting soil types. Our analysis identified consistently higher parameter estimates given the short-term versus long-term datasets. Implementing the short-term and long-term parameters, respectively, resulted in SOC loss (–8.2 ± 5.1% or –3.9 ± 2.8%), and minor SOC gain (1.8 ± 1.0%) in response to 5 °C warming, while only the latter is consistent with a meta-analysis of 149 field warming observations (1.6 ± 4.0%). Comparing multiple subsets of cellulose incubations (i.e., 6, 30, 90, 180, 360, 480 and 729-day) revealed comparable projections to the observed long-term SOC changes under warming only on 480- and 729-day. Integrating multi-year datasets of soil incubations (e.g., \u3e 1.5 years) with microbial models can thus achieve more reasonable parameterization of key microbial processes and subsequently boost the accuracy and confidence of long-term SOC projections

Differential effects of warming and nitrogen fertilization on soil respiration and microbial dynamics in switchgrass croplands

The mechanistic understanding of warming and nitrogen (N) fertilization, alone or in combination, on microbially mediated decomposition is limited. In this study, soil samples were collected from previously harvested switchgrass (Panicum virgatum L.) plots that had been treated with high N fertilizer (HN: 67 kg N ha−1) and those that had received no N fertilizer (NN) over a 3-year period. The samples were incubated for 180 days at 15 °C and 20 °C, during which heterotrophic respiration, δ13C of CO2, microbial biomass (MB), specific soil respiration rate (Rs: respiration per unit of microbial biomass), and exoenzyme activities were quantified at 10 different collections time. Employing switchgrass tissues (referred to as litter) with naturally abundant 13C allowed us to partition CO2 respiration derived from soil and amended litter. Cumulative soil respiration increased significantly by 16.4% and 4.2% under warming and N fertilization, respectively. Respiration derived from soil was elevated significantly with warming, while oxidase, the agent for recalcitrant soil substrate decomposition, was not significantly affected by warming. Warming, however, significantly enhanced MB and Rs indicating a decrease in microbial growth efficiency (MGE). On the contrary, respiration derived from amended litter was elevated with N fertilization, which was consistent with the significantly elevated hydrolase. N fertilization, however, had little effect on MB and Rs, suggesting little change in microbial physiology. Temperature and N fertilization showed minimal interactive effects likely due to little differences in soil N availability between NN and HN samples, which is partly attributable to switchgrass biomass N accumulation (equivalent to ~53% of fertilizer N). Overall, the differential individual effects of warming and N fertilization may be driven by physiological adaptation and stimulated exoenzyme kinetics, respectively. The study shed insights on distinct microbial acquisition of different substrates under global temperature increase and N enrichment

Effects of nitrogen fertilization and bioenergy crop type on topsoil organic carbon and total Nitrogen contents in middle Tennessee USA

Nitrogen (N) fertilization affects bioenergy crop growth and productivity and consequently carbon (C) and N contents in soil, it however remains unclear whether N fertilization and crop type individually or interactively influence soil organic carbon (SOC) and total N (TN). In a three-year long fertilization experiment in switchgrass (SG: Panicum virgatum L.) and gamagrass (GG: Tripsacum dactyloides L.) croplands in Middle Tennessee USA, soil samples (0–15cm) were collected in plots with no N input (NN), low N input (LN: 84 kg N ha-1 yr-1 in urea) and high N input (HN: 168 kg N ha-1 yr-1 in urea). Besides SOC and TN, the aboveground plant biomass was also quantified. In addition to a summary of published root morphology data based on a separated mesocosm experiment, the root leachable dissolved organic matter (DOM) of both crops was also measured using archived samples. Results showed no significant interaction of N fertilization and crop type on SOC, TN or plant aboveground biomass (ABG). Relative to NN, HN (not LN) significantly increased SOC and TN in both crops. Though SG showed a 15–68% significantly higher ABG than GG, GG showed a 9.3–12% significantly higher SOC and TN than SG. The positive linear relationships of SOC or TN with ABG were identified for SG. However, GG showed structurally more complex and less readily decomposed root DOM, a larger root volume, total root length and surface area than SG. Collectively, these suggested that intensive N fertilization could increase C and N stocks in bioenergy cropland soils but these effects may be more likely mediated by the aboveground biomass in SG and root chemistry and morphology in GG. Future studies are expected to examine the root characteristics in different bioenergy croplands under the field fertilization experiment

Reduced carbon use efficiency and increased microbial turnover with soil warming

Global soil carbon (C) stocks are expected to decline with warming, and changes in microbial processes are key to this projection. However, warming responses of critical microbial parameters such as carbon use efficiency (CUE) and biomass turnover (rB) are not well understood. Here, we determine these parameters using a probabilistic inversion approach that integrates a microbial-enzyme model with 22 years of carbon cycling measurements at Harvard Forest. We find that increasing temperature reduces CUE but increases rB, and that two decades of soil warming increases the temperature sensitivities of CUE and rB. These temperature sensitivities, which are derived from decades-long field observations, contrast with values obtained from short-term laboratory experiments. We also show that long-term soil C flux and pool changes in response to warming are more dependent on the temperature sensitivity of CUE than that of rB. Using the inversion-derived parameters, we project that chronic soil warming at Harvard Forest over six decades will result in soil C gain of \u3c1.0% on average (1st and 3rd quartiles: 3.0% loss and 10.5% gain) in the surface mineral horizon. Our results demonstrate that estimates of temperature sensitivity of microbial CUE and rB can be obtained and evaluated rigorously by integrating multidecadal datasets. This approach can potentially be applied in broader spatiotemporal scales to improve long-term projections of soil C feedbacks to climate warming

Quantification of effects of climate variations and human activities on runoff by a monthly water balance model: A case study of the Chaobai River basin in northern China

The Chaobai River basin in northern China consists of two major tributaries, the Chao River and Bai River. Monthly observations of precipitation, streamfiow, and panevaporation data are available for 35 years (1961-1966 and 1973-2001). Using the annual time series of the observed streamfiow, one break point at 1979 is detected and is adopted to divide the data set into two study periods, the "before" and "after" periods marking the onset of significant anthropogenic alteration of the flow (reservoirs and silt retention dams, five times increase in population) and significant changes in land use (conversion to terraced fields versus sloping fields). The distributed time-variant gain model (DTVGM) was used to evaluate the water resources of the area. Furthermore, the Bayesian method used by Engeland et al. (2005) was used in this paper to evaluate two uncertainty sources (i.e., the model parameter and model structure) and for assessing the DTVGM's performance over the Chaobai River basin. Comparing the annual precipitation means over 13 years (1961-1966 and 1973-1979), the means of the second period (1980-2001) decreased by 5.4% and 4.9% in the Chao River and Bai River basins, respectively. However, the related annual runoff decreased by 40.3% and 52.8%, respectively, a much greater decline than exhibited by precipitation. Through the monthly model simulation and the fixing-changing method, it is determined that decreases in runoff between the two periods can be attributed to 35% (31%) from climate variations and 68% (70%) from human activities in the Chao River (Bai River). Thus, human impact exerts a dominant influence upon runoff decline in the Chaobai River basin compared to climate. This study enhances our understanding of the relative roles of climate variations and human activities on runoff. © 2009 by the American Geophysical Union.published_or_final_versio

One-time nitrogen fertilization shifts switchgrass soil microbiomes within a context of larger spatial and temporal variation

Soil microbiome responses to short-term nitrogen (N) inputs remain uncertain when compared with previous research that has focused on long-term fertilization responses. Here, we examined soil bacterial/archaeal and fungal communities pre- and post-N fertilization in an 8 year-old switchgrass field, in which twenty-four plots received N fertilization at three levels (0, 100, and 200 kg N ha-1 as NH4NO3) for the first time since planting. Soils were collected at two depths, 0–5 and 5–15 cm, for DNA extraction and amplicon sequencing of 16S rRNA genes and ITS regions for assessment of microbial community composition. Baseline assessments prior to fertilization revealed no significant pre-existing divergence in either bacterial/archaeal or fungal communities across plots. The one-time N fertilizations increased switchgrass yields and tissue N content, and the added N was nearly completely removed from the soil of fertilized plots by the end of the growing season. Both bacterial/archaeal and fungal communities showed large spatial (by depth) and temporal variation (by season) within each plot, accounting for 17 and 12–22% of the variation as calculated from the Sq. root of PERMANOVA tests for bacterial/archaeal and fungal community composition, respectively. While N fertilization effects accounted for only ~4% of overall variation, some specific microbial groups, including the bacterial genus Pseudonocardia and the fungal genus Archaeorhizomyces, were notably repressed by fertilization at 200 kg N ha-1. Bacterial groups varied with both depth in the soil profile and time of sampling, while temporal variability shaped the fungal community more significantly than vertical heterogeneity in the soil. These results suggest that short-term effects of N fertilization are significant but subtle, and other sources of variation will need to be carefully accounted for study designs including multiple intra-annual sampling dates, rather than one-time “snapshot” analyses that are common in the literature. Continued analyses of these trends over time with fertilization and management are needed to understand how these effects may persist or change over time