Miracle-dz/UniFAR-FTUs huggingface dataset:
Number of soil profiles needed to give a reliable overall estimate of soil organic carbon storage using profile carbon density data

Abstract Soil profile data are the basis for estimating soil organic carbon (SOC) storage and any changes in SOC storage, which are of great significance in terms of global climate change. Estimates based on various profile data have been made for SOC storage in China. Modeling studies have given contrasting results on changes in SOC storage in Chinese croplands. A certain number of measured soil profile data are needed to validate the modeled results. In the present study, we examined the relationships between sample size, population variance and detection limit using the central limit theorem and the statistical properties of the normal distribution. Based on the profile dataset from the Second National Soil Survey in China, we calculated that to derive a reliable estimate of the overall mean SOC density for all the soils of China, a sample size of 4,000 soil profiles is needed. In this case, a reliable estimate is defined as having a 95% confidence interval and allowing a ±5% detection limit of SOC. The necessary sample size for cropland soils is 1,250. Our results indicate that approximately 100 samples only are needed to validate a modeled SOC loss of 20–30% in cropland soils in China. By aggregating the soil profiles in the dataset into soil orders and calculating the variance of each soil order, we show that the sample sizes in the dataset are insufficient to give reliable estimates on the carbon densities of most soil orders; thus, we conclude that there is considerable uncertainty in the SOC distribution maps resulting from the Second National Soil Survey.
Malignancies Associated with Radiation in Aerospace Personnel-A Review of Evidence and Studies

It is no secret in the realm of Aerospace Medicine that radiation is considered to be a hazard to the health and safety of personnel such as astronauts, pilots, aircrew members, flight attendants and so on and so forth. The forms of radiation to which such individuals are constantly exposed to include extra-vehicular radiation e.g. UV and cosmic radiation and radiation emitted from onboard apparatuses, fuel etc. Now, it is thought that the former (i.e. extra-vehicular radiation) poses more health risks to humans upon exposure in comparison to the latter. These risks include the development of malignancies, teratogenicity, mutagenicity and non-cancerous tissue damage e.g. cataracts. It is essential to appreciate the fact that the inhabitants of earth who do not engage in frequent air/space travel are protected to a certain extent from the above mentioned deleterious effects. Such protection is primarily received by means of the earth’s magnetic field and the atmosphere. Individuals who fly at high altitudes e.g. commercial pilots and aircrew members are less protected, especially if flight routes are high latitude (i.e. further away from the equator). Their counterparts in space (astronauts) however are not subject to this protection at all during occupation, and thus are potentially exposed to greater magnitudes of extravehicular ionising radiation.
Integrated emission inventory and modeling to assess distribution of particulate matter mass and black carbon composition in Southeast Asia

Abstract. This is part of a research study addressing the potential co-benefits associated with selected black carbon (BC) emission reduction measures on mitigation of air pollution and climate forcing in Southeast Asia (SEA). This paper presents details of emission inventory (EI) results and WRF–CHIMERE model performance evaluation. The SEA regional emissions for 2007 were updated with our EI results for Indonesia, Thailand, and Cambodia and used for the model input. WRF–CHIMERE-simulated 2007 PM10, PM2.5, and BC over the SEA domain (0.25° × 0.25°) and the results were evaluated against the available meteorology and air quality monitoring data in the domain. WRF hourly simulation results were evaluated using the observed data at eight international airport stations in five SEA countries and showed a satisfactory performance. WRF–CHIMERE results for PM10 and PM2.5 showed strong seasonal influence of biomass open burning while the BC distribution showed the influence of urban activities in big SEA cities. Daily average PM10 constructed from the hourly concentrations were obtained from the automatic monitoring stations in three large SEA cities, i.e., Bangkok, Kuala Lumpur, and Surabaya, for model evaluation. The daily observed PM2.5 and BC concentrations obtained from the Improving Air Quality in Asian Developing Countries (AIRPET) project for four cities (i.e., Bangkok, Hanoi, Bandung, and Manila) were also used for model evaluation. In addition, hourly BC concentrations were taken from the measurement results of the Asian Pacific Network (APN) project at a suburban site in Bangkok. The modeled PM10 and BC satisfactorily met all suggested statistical criteria for PM evaluation. The modeled PM2.5∕PM10 ratios estimated for four AIRPET sites ranged between 0.47 and 0.59, lower than observed values of 0.6–0.83. Better agreement was found for BC∕PM2.5 ratios with the modeled values of 0.05–0.33 as compared to the observation values of 0.05–0.28. AODEM (extended aerosol optical depth module) was used to calculate the total columnar aerosol optical depth (AOD) and BC AOD up to the top of the domain at 500 hPa (∼ 5500 m), which did not include the free-tropospheric long-range transport of the pollution. The model AOD results calculated using the internal mixing assumption were evaluated against the observed AOD by both AERONET and MODIS satellite in 10 countries in the domain. Our model results showed that the BC AOD contributed 7.5–12 % of the total AOD, which was in the same range reported by other studies for places with intensive emissions. The results of this paper are used to calculate the regional aerosol direct radiative forcing under different emission reduction scenarios to explore potential co-benefits for air quality improvement, reduction in the number of premature deaths, and climate forcing mitigation in SEA in 2030 (Permadi et al., 2017a).
Dynamic Enforcement of Differential Privacy

With recent privacy failures in the release of personal data, differential privacy received considerable attention in the research community. This mathematical concept, despite its young age (Dwork et al., 2006), has grabbed the attention of many researchers for its robustness against identification of individuals even in presence of background information. Besides that, its flexible definition makes it compatible with different data sources, data mining algorithms and data release models. Its compositionality properties facilitate design of differential privacy aware programming languages and frameworks that empower non-experts to construct complex data mining analyses with proven differential privacy guarantees. The goal of this research is to introduce new (and improve the current) differential privacy backed frameworks, prominent both in utility and flexibility of use. We study dynamic enforcement of differential privacy both in the centralised model in which a trusted curator process data stored in a centralised database and the local model with no trust on the third party. For the centralised model the thesis mostly focuses on the privacy impact of the basic building blocks used in these frameworks, proving correctness of the system built upon them. %The correctness is important since some frameworks (in this case PINQ) derivate from theory without proper justification. With respect to accuracy, we present personalised differential privacy as an improved method of enforcing privacy that provides better data utilisation and other benefits. In this setting, individuals take control of their privacy requirements rather than being seen as a part of a database. As a result, they can opt-in to a database with their expected privacy level and optionally opt-out later. We further study the privacy implication of other building blocks such as different kinds of sampling and partitioning. For the local model we propose a general framework in which the users can verify the recieved analyses and with a flexible policy express their privacy preference in different forms such as enforcing their personalised privacy budget.
An Agent-Based Approach To Nodes’ Misbehaviour Detection In Mobile Ad-Hoc Networks

: Existing Misbehaviour Detection Systems in Mobile Ad-hoc Networks (MANETs) are challenged with routing overhead and high latency resulting from complexity and failure to isolate and block misbehaving nodes for the reason that it is difficult to detect them as they participate fully in route finding. In this work, a Mobile Agent-Based Acknowledgement scheme (MAACK) was formulated to address this problem using an object oriented algorithm deployed to report misbehaving nodes to the source and destination by registering the Internet Protocol (IP) address of misbehaving nodes in their header. The scheme was simulated using Network Simulator-3 (NS-3) and results benchmarked with an existing scheme; the Enhanced Adaptive Acknowledgment (EAACK) using packet delivery ratio, routing overhead and latency as performance metrics in the two scenarios. The results showed that the MAACK paradigm guaranteed a higher packet delivery ratio, lower latency and routing overhead than the EAACK scheme. The model can be adapted by Ad-Hoc network protocol developers.
AC2011-740: CREATIVITYANDINNOVATION:ACOMPARATIVEANAL- YSIS OF DEFINITIONS AND ASSESSMENT MEASURES

Paul Skaggs is an associate professor and program chair of industrial design at Brigham Young University. He joined the faculty at BYU after twenty-two years experience in industry. Fourteen years of which he operated his own full-service design consulting firm. Clients included Kodak, Fisher-Price, Federal Express, Motorola, AT&T, Xerox and Hewlett-Packard, to name a few. Paul also taught conducted creativity seminars for in house engineering groups. Paul received his BFA from Brigham Young University and his MFA from Rochester Institute of Technology.
'Flavescence dorée' phytoplasma genome: a metabolism oriented towards glycolysis and protein degradation.

The 670 kbp chromosome of 'flavescence doree' phytoplasma line FD92 was partially sequenced by pyrosequencing and SOLEXA. More than 94% of the chromosome could be assembled and the 22 largest contigs representing 85% of the chromo- some were annotated under the semi-automatic annotation platform iANT. Out of 464 chromosomal coding sequences (CDS), 174 CDS (38%) were involved in information transfer (DNA replication, protein production, RNA modification and regulation), 88 CDS (19%) were encoding metabolic enzymes, 40 CDS (9%) corresponded to transporters, 8 CDS (1%) corresponded to cellular processes, whereas 145 CDS (31%) remained cryptic. At this stage of incomplete assembly, repeated sequences were underesti- mated and transposon and phage-related CDS (2%) could not yet be precisely evaluated. FD92 phytoplasma possesses a complete glycolytic pathway and has a prominent system for proteolysis possibly resulting from the adaptation to its woody hosts.
Fog forecasting: ``old fashioned'' semi-empirical methods from radio sounding observations versus ``modern'' numerical models

Despite the recently improved skill of numerical weather prediction (NWP) models, fog remains difficult to forecast. Hence, we examine whether empirical methods as developed in the 60s&70s are reasonable alternatives forecast tools. It appears that the so-called Fog Stability Index (FSI), solely bas ed on routine radio sounding observations, has reasonable skill. Also, the FSI has been optimized for 12 stations in the Netherlands, after which FSI reaches a high forecast skill. It appears this skil l approaches the skill of direct MM5 model output.
The influences of relationship marketing in the housing brokerage market

Many companies and salesmen try to build and maintain long-term relationship with their customer. The influences of relationship marketing activities are important issue of the housing brokerage Market. The aims of study are to learn the impacts of relationship marketing on customer satisfaction and customer loyalty in the housing brokerage Market. The researchers survey the customers and use the regression analysis method to test the relationships between relationship marketing, customer satisfaction and customer loyalty in Taiwan. The research results show that the relationship marketing positively impacts on customer satisfaction and customer loyalty, then customer satisfaction positively impacts on customer loyalty. Customer satisfaction plays a mediating role between relationship marketing and customer loyalty. Besides, the study confirm that brokers’ expertise moderates the relationship of relationship marketing process. The findings suggest that the brokers’ relationship marketing and expertise empirically impact on the customers.
Grandchildren and Their Grandparents' Labor Supply

We study how becoming a grandparent affects grandparents’ labor supply. In a simple model of the allocation of time in which seniors care about their offspring’s welfare and also value time spent with family children, the sign of the effect is ambiguous. Using data from the Panel Study of Income Dynamics we find evidence that becoming a grandparent causes a reduction of employed grandmother’s hours of work. We identify a lower bound of about 190. This effect originates towards the bottom of the hours distribution (i.e., among women less attached to the labor market). For employed grandfathers, the effect is also negative, originates towards the top of the hours distribution (i.e., where overtime work is substantial), but is smaller and more imprecisely estimated than for women. We also find that for working grandmothers the effect is stronger the closer grandparents and grandchildren live and during the first years since becoming a grandparent (i.e., when the grandchildren are younger). The “extensive margin” of grandparenting (becoming a grandparent) turns out to be much more important in generating these effects than the corresponding “intensive” margin (having additional grandchildren).
The Micro Contribution to Macro Sociology

It is a mistake to regard the micro-macro program as merely the theme "the smaller the better. " I have argued, following the precedent of various micro-reductionists (Blumer, Homans, the ethnomethodologists) that we ought to translate macro sociological phenomena as much as possible into the micro realities of which they are composed. (Notice, however, that I say "translation," not all-out reduction; for there are irreducible macro features in the spatial, temporal, and numerical arrangements among microsituations: Collins, 1988: 394-5.) It is not an argument against micro-translation to propose counter-examples in the physical sciences, for instance to point out that the structure of biological organisms is no more real than the molecular level of the DNA. The aim of
Multi-Compartmental Modeling of Nitrogen Translocation in Sorghums Differing in Nitrogen Use Efficiency

ABSTRACT Some cultivars of sorghum [Sorghum bicolor (L.) Moench] are more efficient than others in using nitrogen (N) from the soil to produce grain. A study was conducted to test the hypothesis, that the processes involved in the translocation of N differed between two sorghum lines, China 17, a N-efficient genotype, and Tx623, a less efficient genotype, during their ontogenetic development. Both cultivars were grown in the field and periodically sampled to determine the amount of N in above-ground parts of the plants, i.e. stalk, leaves, and grain. Compartmental modeling, which is based on sets of differential equations that describe the flow of material through compartments, was used as the basis for analysis of the rates and rate constants of N which had moved among parts of the plant. Compartmental models are relatively simple, systematic mathematical representations that can be used to aid in understanding how different plant parts influence plant-N dynamics. China 17's rate constants between upper parts of the stalk and between the upper stalk and grain were larger in the earlier part of the season and became smaller toward the end than Tx623 meaning that China 17 was more capable of moving N to the upper parts of the plant earlier in the season than was Tx623. However, no differences in rate constants were detected for stalk to leaves and within leaves rate constants, meaning that the N-movement processes in the leaves were essentially the same between the two genotypes. The model also detected pseudo-compartments associated with the upper leaves in both genotypes which indicated that there are several processes or other rate-controlling factors associated with N flow in the leaves. A multi-compartmental model, based on rather simple assumptions and which only required N for each plant part over time, was used to describe N translocation between plant parts for two different sorghum genotypes. The model was able to detect fundamental differences between the genotypes in terms of N translocation processes, however more work is needed to understand the physiological processes underlying the results.
Ship Detection and Classification on Optical Remote Sensing Images Using Deep Learning

Ship detection and classification is critical for national maritime security and national defense. Although some SAR (Synthetic Aperture Radar) image-based ship detection approaches have been proposed and used, they are not able to satisfy the requirement of real-world applications as the number of SAR sensors is limited, the resolution is low, and the revisit cycle is long. As massive optical remote sensing images of high resolution are available, ship detection and classification on theses images is becoming a promising technique, and has attracted great attention on applications including maritime security and traffic control. Some digital image processing methods have been proposed to detect ships in optical remote sensing images, but most of them face difficulty in terms of accuracy, performance and complexity. Recently, an autoencoder-based deep neural network with extreme learning machine was proposed, but it cannot meet the requirement of real-world applications as it only works with simple and small-scaled data sets. Therefore, in this paper, we propose a novel ship detection and classification approach which utilizes deep convolutional neural network (CNN) as the ship classifier. The performance of our proposed ship detection and classification approach was evaluated on a set of images downloaded from Google Earth at the resolution 0.5m. 99% detection accuracy and 95% classification accuracy were achieved. In model training, 75× speedup is achieved on 1 Nvidia Titanx GPU.
Financial Liberalization and Volatility in Emerging Market Economies

The recent East Asian crisis has highlighted the relationship between financial development and output volatility. In this essay we develop a simple model of a small open economy producing a tradeable good using a non-tradeable input and where firms access to borrowings and investment depends on current cash flows. We then show, first that macroeconomic volatility only occurs at intermediate levels of financial development; second, that whilst full financial liberalization, including an unrestricted opening to foreign lending, can destabilize an emerging market economy, in contrast output volatility can be avoided if the same economy opens up to foreign direct investment only. We also draw several policy conclusions regarding the adequate responses to financial crises.
Walking Pattern Generation using Approximate Unstable Zero Cancelation and Its Compensation Method

This paper suggests a walking pattern generation method using an approximate unstable zero cancelation and its compensation. Basically, there exists an error in the walking pattern generation method for humanoid robots using both a pole-zero cancelation by series approximation (PZCSA) and a linear quadratic regulator (LQR) method suggested in (12). This error is caused by the approximate pole-zero cancelation for removing an unstable zero. As an alternative of this problem, firstly, we construct an estimator for position/acceleration errors of Center of Mass (CoM) and a position of Zero Moment Point (ZMP), and then they are used for compensating the ZMP error and the CoM error using a low pass filter. Through these simple procedures, finally, we show that both the ZMP and CoM errors can be removed through numerical simulations.
The Quest for Purchasing Power Parity with a Series-specific Unit Root Test Using Panel Data

A unit root testing procedure is presented that exploits the well-established power advantages of panel estimation while rectifying a deficiency in other panel unit root tests. This procedure, which takes into account contemporaneous cross-correlation and heterogeneous serial correlation of the regression residuals, allows determination of which members of the panel reject the null hypothesis of a unit root and which do not. Applying the procedure to real exchange rates yields results that are in broad agreement with those obtained from single-equation unit root tests. There is little evidence that a unit root can be rejected in dollar-based real exchange rates for the floating rate period.
Consensus of Noisy Multiagent Systems with Markovian Switching Topologies and Time-Varying Delays

Stochastic multiagent systems have attracted much attention during the past few decades. This paper concerns the continuous-time consensus of a network of agents under directed switching communication topologies governed by a time-homogeneous Markovian process. The agent dynamics are described by linear time-invariant systems, with random noises as well as time-varying delays. Two types of network-induced delays are considered, namely, delays affecting only the output of the agents’ neighbors and delays affecting both the agents’ own output and the output of their neighbors. We present necessary and sufficient consensus conditions for these two classes of multiagent systems, respectively. The design method of consensus gains allows for decoupling the design problem from the graph properties. Numerical simulations are implemented to test the effectiveness of our obtained results as well as the tightness of necessary/sufficient conditions.