Miracle-dz/UniFAR-FTUs huggingface dataset:
Fast responses of climate system to carbon dioxide, aerosols and sulfate aerosols without the mediation of SST in the CMIP5

In this study, fast climate system responses to CO2, aerosols and sulfate aerosols are studied based on simulations of Coupled Model Inter‐comparison Project Phase 5 (CMIP5) atmospheric models. We demonstrate that the fast climate adjustments caused by CO2 forcing lead to decreases in global annual mean cloud fractions, evaporation and precipitation and to increases in the global annual mean net radiative forcing and atmospheric water vapour content. The inhibition of rainfall is primarily caused by the reduced oceanic precipitation. Regionally, Africa, South Asia, East Asia and Australia exhibit pronounced increases in rainfall, which are presumably attributed to the strengthened summer monsoon caused by the increased land–sea thermal contrast. Aerosols and sulfate aerosols exhibit only a slight effect on the global hydrological cycle before global surface temperature changes. However, by affecting the land–sea thermal contrast, they can have profound effects on regional‐scale hydrological cycles, such as those over southern Africa, South Asia and East Asia in the boreal summer. Moreover, the cloud fast feedback under the aerosol forcing is highly associated with the way of dealing with aerosols in the atmospheric model.
The clustering of galaxies in the SDSS-III Baryon Oscillation Spectroscopic Survey: weighing the neutrino mass using the galaxy power spectrum of the CMASS sample

We measure the sum of the neutrino particle masses using the three-dimensional galaxy power spectrum of the Sloan Digital Sky Survey III (SDSS-III) Baryon Oscillation Spectroscopic Survey Data Release 9 the constant MASS (CMASS) galaxy sample. Combined with the cosmic microwave background, supernova and additional baryonic acoustic oscillation data, we find upper 95 per cent confidence limits (CL) of the neutrino mass Σmν < 0.340 eV within a flat Λ cold dark matter (ΛCDM) background, and Σmν < 0.821 eV, assuming a more general background cosmological model. The number of neutrino species is measured to be Neff = 4.308 ± 0.794 and 4.032+0.870-0.894 for these two cases, respectively. We study and quantify the effect of several factors on the neutrino measurements, including the galaxy power spectrum bias model, the effect of redshift-space distortion, the cut-off scale of the power spectrum and the choice of additional data. The impact of neutrinos with unknown masses on other cosmological parameter measurements is investigated. The fractional matter density and the Hubble parameter are measured to be ΩM=0.2796±0.0097, H0=69.72+0.90−0.91 km s−1 Mpc−1 (flat ΛCDM) and ΩM=0.2798+0.0132−0.0136, H0=73.78+3.16−3.17 km s−1 Mpc−1 (more general background model). Based on a Chevallier–Polarski–Linder parametrization of the equation-of-state w of dark energy, we find that w = −1 is consistent with observations, even allowing for neutrinos. Similarly, the curvature ΩK and the running of the spectral index αs are both consistent with zero. The tensor-to-scalar ratio is constrained down to r < 0.198 (95 per cent CL, flat ΛCDM) and r < 0.440 (95 per cent CL, more general background model).
Spatio-temporal Evolution of Agricultural Eco-efficiency in Loess Plateau of East Gansu Province: A Case Study of Qingyang City

Based on the definition of ecological efficiency raised by World Business Council for sustainable development(WBCSD), the article applied undesired-output SBM model of Data Envelopment Analysis(DEA) to analyze the spatio-temporal evolution of agricultural eco-efficiency in Loess Plateau of East Gansu Province in 2001-2011. The results indicated that: the agricultural ecological-efficiency in Qingyang City is declining overall, and the spatial discrepancy of eco-efficiency is enlarging. According to the spatial distribution of eco-efficiency, Qingyang can be divided into two regions: 1) The high agricultural eco-efficiency region includes Xifeng, Heshui, Ningxian, Zhengning county which possess good ecological environment, abundant water resource and developed agriculture. 2) The low agricultural eco-efficiency region includes Qingcheng, Huachi, Huanxian, Zhenyuan county which have fragile ecological condition and the scarce water resource. The reasons for inducing low eco-efficiency are disproportional factor inputs, low efficiency of resources utilization and excessive redundancy of undesired outputs. Furthermore, the article analyzed the redundancy of elements of agricultural input in the regions where have lower ecological efficiency in order to put forward the way to improve the ecological efficiency.
Diapycnal Transport and Pattern Formation in Double-Diffusive Convection

Abstract : This work analyzes the role of double-diffusive convection in constraining diapycnal velocity in the mid-latitude thermocline and in the initiation and maintenance of the deep convection associated with polynya and sea ice thinning events. Previously, no comprehensive high-resolution modeling studies of the possible role of double-diffusion in these areas have been conducted. A series of simulations using a numerical, multi-scale, MPI-based general circulation model is presented to remedy this dearth of knowledge. The effects of turbulent-dominated and purely double-diffusive regimes are compared to dual turbulent/double-diffusive systems and results are used to assess the likely roles of double-diffusion in constraining diapycnal velocity and delaying convection onset in high-latitude regions of marginal water column stability. High-resolution numerical modeling indicates that when both double-diffusion and turbulence are present, the constraints on diapycnal velocity loosen (tighten) with the increase of the fraction of the overall mixing attributed to turbulence (double-diffusion). The results of this study also indicate that double-diffusion could play an important role in delaying the onset of deep convection in the vicinity of Maud Rise in the eastern Weddell Sea, and may contribute to polynya formation and the persistence of interannual sea ice thinning.
Robust Multivariate and Nonlinear Time Series Models

Time series modeling and analysis is central to most financial and econometric data modeling. With increased globalization in trade, commerce and finance, national variables like gross domestic productivity (GDP) and unemployment rate, market variables like indices and stock prices and global variables like commodity prices are more tightly coupled than ever before. This translates to the use of multivariate or vector time series models and algorithms in analyzing and understanding the relationships that these variables share with each other. Autocorrelation is one of the fundamental aspects of time series modeling. However, traditional linear models, that arise from a strong observed autocorrelation in many financial and econometric time series data, are at times unable to capture the rather nonlinear relationship that characterizes many time series data. This necessitates the study of nonlinear models in analyzing such time series. The class of bilinear models is one of the simplest nonlinear models. These models are able to capture temporary erratic fluctuations that are common in many financial returns series and thus, are of tremendous interest in financial time series analysis. Another aspect of time series analysis is homoscedasticity versus heteroscedasticity. Many time series data, even after differencing, exhibit heteroscedasticity. Thus, it becomes important to incorporate this feature in the associated models. The class of conditional heteroscedastic autoregressive (ARCH) models and its variants form the primary backbone of conditional heteroscedastic time series models. Robustness is a highly underrated feature of most time series applications and models that are presently in use in the industry. With an ever increasing amount of information available for modeling, it is not uncommon for the data to have some aberrations within itself in terms of level shifts and the occasional large fluctuations. Conventional methods like the maximum likelihood and least squares are well known to be highly sensitive to such contaminations. Hence, it becomes important to use robust methods, especially in this age with high amounts of computing power readily available, to take into account such aberrations. While robustness and time series modeling have been vastly researched individually in the past, application of robust methods to estimate time series models is still quite open. The central goal of this thesis is the study of robust parameter estimation of some simple vector and nonlinear time series models. More precisely, we will briefly study some prominent linear and nonlinear models in the time series literature and apply the robust S-estimator in estimating parameters of some simple models like the vector autoregressive (VAR) model, the (0, 0, 1, 1) bilinear model and a simple conditional heteroscedastic bilinear model. In each case, we will look at the important aspect of stationarity of the model and analyze the asymptotic behavior of the S-estimator.
This information is current as Dendritic Cells Innate Immune Response of Human Recruitment Domain of RIGI Modifies the A Common Polymorphism in the Caspase and

Infection of human dendritic cells (DCs) by negative-strand RNA viruses, such as Newcastle disease virus, leads to the induction of the IFNb gene, IFNB1, through the activation of the RNA helicase RIG-I, which is encoded by DDX58. Expression levels of IFNB1 and DDX58 in infected DCs showed positive correlations at the population and the single-cell levels. DDX58 has a common and potentially functional single nucleotide polymorphism, rs10813831 (A/G), encoding an Arg7Cys amino acid change in the RIG-I protein caspase recruitment domain (CARD). Quantitative RT-PCR analysis on Newcastle disease virus-infected primary DCs from 130 individuals revealed a significant association of the Arg7Cys single nucleotide polymorphism with increased IFNB1 and DDX58 transcription. Allelic imbalance analysis ruled out allele-specific DDX58 message levels and suggested that the observed association between Arg7Cys and IFNB1 and DDX58 transcription originated from a functional change in RIG-I due to the amino acid substitution in the CARD. DDX58 transfection experiments in 293T cells confirmed a biological functional difference between RIG-I 7Cys and the more common RIG-I 7Arg. Taken together, these data indicate that the innate immune response to viral infection of human cells is modified by a functional polymorphism in the RIG-I CARD. D endritic cells (DCs) are considered the " first responders " to viral infection by the innate immune system. They also play a crucial role in the development of viral Ag-specific adaptive immunity (1). A key step in the DC response to viral infection is the induction of IFNb (IFNB1), a secreted cyto-kine that complexes with type 1 IFNRs to initiate a coordinated signaling pathway leading to widespread viral resistance (2, 3). Induction of IFNB1 can be triggered through TLRs (4) or through TLR-independent pathways, which are activated by the caspase recruitment domain (CARD) family RNA helicases RIG-I (RIG-I, encoded by DDX58) or MDA5 (encoded by MDA5) (5, 6). RIG-I and MDA5 proteins contain two CARDs and an RNA helicase domain. RIG-I undergoes a conformational change upon interacting with short, double-stranded, 59-triphosphate-containing viral RNA (6–8), an interaction that may depend on sequence context (9). Its CARDs unwind to form RIG-I homomultimers (10) and bind to another CARD family protein mitochondrial antiviral signaling protein (MAVS), also called IPS-1, Cardif, and VISA, at the mitochondrial membrane (11–15). RIG-I binding to mitochondrial antiviral sig-naling protein leads to the activation of several transcription factors, including AP1, IFN regulatory factors, and NF-kB, to assemble the enhanceosome of IFNB1 and, thus, initiate …
IOECCH: Improved Optimized Energy-Efficient Connected Coverage Heuristic Algorithm in WSNs

Target points coverage in Wireless Sensor Networks (WSNs) is affected by random deployment of sensor nodes; which could lead to coverage hole problem in the network area. In this paper, an Improved Optimized Energy Efficient Connected Coverage Heuristic (IOECCH) algorithm is proposed to achieve target points coverage contribution with increasing network lifetime. Sensor nodes are divided into sensing nodes and relaying nodes to perform interconnected coverage sets. Simulation results illustrate that IOECCH can increase network lifetime compared to other algorithms.
Optimal and Robust Estimation: With an Introduction to Stochastic Control Theory, Second Edition

OPTIMAL ESTIMATION Classical Estimation Theory Mean-Square Estimation Maximum-Likelihood Estimation The Cramer-Rao Bound Recursive Estimation Wiener Filtering Problems Discrete-Time Kalman Filter Deterministic State Observer Linear Stochastic Systems The Discrete-Time Kalman Filter Discrete Measurements of Continuous-Time Systems Error Dynamics and Statistical Steady State Frequency Domain Results Correlated Noise and Shaping Filters Optimal Smoothing Problems Continuous-Time Kalman Filter Derivation from Discrete Kalman Filter Some Examples Derivation from Wiener-Hopf Equation Error Dynamics and Statistical Steady State Frequency Domain Results Correlated Noise and Shaping Filters Discrete Measurements of Continuous-Time Systems Optimal Smoothing Problems Kalman Filter Design and Implementation Modeling Errors, Divergence, and Exponential Data Weighting Reduced-Order Filters and Decoupling Using Suboptimal Gains Scalar Measurement Updating Problems Estimation for Nonlinear Systems Update of the Hyperstate General Update of Mean and Covariance Extended Kalman Filter Application to Robotics and Adaptive Sampling Problems ROBUST ESTIMATION Robust Kalman Filter Systems with Modeling Uncertainties Robust Finite Horizon Kalman A Priori Filter Robust Stationary Kalman A Priori Filter Convergence Analysis Linear Matrix Inequality Approach Robust Kalman Filtering for Continuous-Time Systems Problems H-Infinity Filtering of Continuous-Time Systems H-Infinity Filtering Problem Finite Horizon H-Infinity Linear Filter Characterization of All Finite Horizon H-Infinity Linear Filters Stationary H-Infinity Filter-Riccati Equation Approach Relationship with the Kalman Filter Convergence Analysis H-Infinity Filtering for a Special Class of Signal Models Stationary H-Infinity Filter-Linear Matrix Inequality Approach Problems H-Infinity Filtering of Discrete-Time Systems Discrete-Time H-Infinity Filtering Problem H-Infinity A Priori Filter H-Infinity A Posteriori Filter Polynomial Approach to H-Infinity Estimation J-Spectral Factorization Applications in Channel Equalization Problems OPTIMAL STOCHASTIC CONTROL Stochastic Control for State Variable Systems Dynamic Programming Approach Continuous-Time Linear Quadratic Gaussian Problem Discrete-Time Linear Quadratic Gaussian Problem Problems Stochastic Control for Polynomial Systems Polynomial Representation of Stochastic Systems Optimal Prediction Minimum Variance Control Polynomial Linear Quadratic Gaussian Regulator Problems Appendix A: Review of Matrix Algebra Basic Definitions and Facts Partitioned Matrices Quadratic Forms and Definiteness Matrix Calculus References Index
Communal Non-Consumptive Natural Resources Conservation Practices in Western Tanzania

The communal-indigenous non-consumptive natural resources conservation practice contribution on community economy in western Tanzania was studied. The study focused on forest and wildlife because they are most affected by land conversion and degradation. An economic benefit model of the communal-indigenous non-consumptive natural resources conservation practice effect was developed. To assess magnitude of effect of the practice, specific null hypothesis (H₂) was developed and tested. The null hypothesis stated that H₂: Communal - indigenous non-consumptive terrestrial natural resources management approach does not significantly impact community economic benefit. The empirical study administered a four point-scaled numerical survey questionnaire to 400 respondents and 40 Key Informant Interviews. Quantitative data were analyzed by SPSS while qualitative data were analyzed by Excel framing summarizing technique. Descriptive statistics realized that the communal non-consumptive natural resources conservation mean was 46.99, almost equal to the average mean of 47. Moreover, the model had strong linear relation. Pearson (r) covariance statistical relationship correlation coefficient of Pearson (r) = 0.68, p<. 001. Furthermore, the contribution of communal-non-consumptive natural resources conservation practice on community economic benefit was calculated through multiple linear regression techniques. Multiple linear regression results showed that regression coefficient B= 1.34 at 95% confidence interval (CI) = 1.23, 1.44; p=0.000. The result implied that an increase of one unit of the communal non-consumptive natural resources conservation practice was associated with an increase of 1.34 community economic benefit (CEB). The study results rejected the null hypothesis suggesting that the alternative hypothesis may be true. The study concludes that communal non-consumptive management approaches likely significantly impact community economic benefit (CEB). Therefore, to enjoy strong community economy, communal-non-consumptive natural resources conservation should be given significant attention. Additionally, to gain more community economic benefit, an integrated hybrid combo of consumptive approaches such as sustainable timber with non-consumptive approaches
Vision Based Pad Detection for Autonomous Landing Quadcopter

Robust developments in the world of robotics with the presence of commonly called Unmanned Aerial Vehicles (UAV), the use of these UAVs can be categorized quite broadly such as for military, security, and other purposes, one of the efforts to improve the performance of UAVs is to add a feature to be able to land autonomously on the landing pad. This research focuses on designing the quadcopter so that it can land precisely on the landing pad using image processing algorithms. First the captured image will be converted to grayscale, then the thresholding method is carried out and followed by a morphological process to eliminate noise and produce a clear image, then the detected image will be displayed in a frame that will calculate the distance to the middle point, then it will be used as Pulse Width Modulation (PWM) input to adjust the direction of motion of the UAV so that it can land autonomously, Testing is carried out to test the accuracy and precision of the designed algorithm. The results of the experiment show an accuracy rate of 94.76% and a precision level of 96.59% with an average landing time of 19 seconds and an average detection time is 8.55 milliseconds.
Journal of Theoretical and Applied Information Technology

The main objective of this paper is to explain the functioning of a device, designed to sense the real time motion changes of an object. This motion sensing device Digital Accelerometer can be used to sense any change in the position of an object with respect to its original position, all along the three axes. This Digital accelerometer is to be put into its function controlled by a Field Programmable Gate Array (FPGA). The above motion sensing device connected with the FPGA will also be useful in reducing complexity factors such as area consumption, cost, etc in installing the objects and at the same time, the device could also be introduced in an easier way. This paper is mainly to deal with the experimental procedure in detecting such changes using this motion sensing device Digital Accelerometer.
Journal of Theoretical and Applied Information Technology

In recommender systems, modeling user interest is a basic step to understand user's personal features. Traditional methods mostly just use the items that the target users navigated as their interests, which makes the inherent information unclear to the system and thus the recommendations are not intelligent enough. In this paper, we investigate the utility of topic model called LDA for the task of modeling user interests which are assumed as the latent variables behind user activities in the systems. By using such a probabilistic model on the generation of user profiles, the relationships amongst user、item and interest are constructed. Each user can be considered as a generation of the model. Based on this user interest model, we propose three item ranking methods for personalized recommendation. In order to get a better model for each algorithm, we use a simple automatic parameter turning way to select the model parameters. After carefully selecting the parameters, our methods can all receive encouraging results for recommender systems.
Complex Approach to Synthesizing Neural Network Regulators for Unstable Nonlinear Control Objects

The use of neural network controllers in automatic control systems of complex nonlinear dynamic objects is an actual direction of development of modern control theory. The authors propose an approach based on the simultaneous synthesis of a neural network Lyapunov function with a controller that guarantees the stability of a closed-loop system. Unlike previous studies devoted to the synthesis of autonomous control systems, this paper presents a method for synthesizing tracking systems. An algorithm is also proposed to optimize the transient time. An example of controller synthesis for an unstable control object is considered
A high-resolution vegetation, fire, and climate history from the Aishihik Region, Yukon Territory, Canada

Paleocological studies based on the analysis of lake sediments offer the potential for high resolution and well-dated records of past environmental conditions. A 2.7 m sediment core raised from Lake WA01 (unofficial name, 61°14'41"N, 136°55'35"W, 1000 m.a.s.l.) in the Aishihik region of the southwest Yukon Territory documents the post-glacial vegetation, fire, and climate history of the region surrounding the study site. The earliest portion of the WA01 pollen record was characterized by the establishment of open birch-shrub tundra at the study site. Picea glauca then established ca. 9,900 cal yrs BP, and has since remained dominant on the landscape Progressively decreasing precipitation in the region over the last ca. 9,000 years, noted in a previous study by Viau et al. (2008), is not captured in the Lake WA01 climate reconstructions. From ca. 9,900 cal yrs BP to the present day, reconstructed mean July temperatures and total annual precipitation at the study site remained essentially constant. A short period of low total annual precipitation is noted from deglaciation at 10,500 cal yrs BP to 9,900 cal yrs BP. The regional-scale fire regime surrounding the study site increased gradually in intensity over the course of the Holocene. Local fires in the area immediately surrounding the study lake decreased gradually in frequency and/or size over the course of the Holocene, though the exact cause remains unclear. An alternating pattern in the sediment loss-on-ignition from Lake WA01 is related to similar trends in D0 values from the Mount Logan oxygen isotope record (Fisher et al., 2008). Based on a positive association between sediment carbonate content and enriched D0 values from the Mount Logan record, it is proposed that periods of increased and decreased sediment carbonate content in the WA01 core are indicative of wetter and drier conditions at the study site, respectively.