Miracle-dz/UniFAR-FTUs huggingface dataset:
Soil property changes over a 120-yr chronosequence from forest to agriculture in western Kenya

Much of the native forest in the highlands of western Kenya has been converted to agricultural land in order to feed the growing population, and more land is being cleared. In tropical Africa, this land use change results in progressive soil degradation, as the period of cultivation increases. Both rates and variation in infiltration, soil carbon concentration and other soil parameters are influenced by management within agricultural systems, but they have rarely been well documented in East Africa. We constructed a chronosequence for an area of western Kenya, using two native forest sites and six fields that had been converted to agriculture for up to 119 yr. We assessed changes in infiltrability (the steady-state infiltration rate), bulk density, proportion of macro- and microaggregates in soil, soil C and N concentrations, as well as the isotopic signature of soil C (δ 13 C), along the 119-yr chronosequence of conversion from natural forest to agriculture. Infiltration, soil C and N decreased within 40 yr after conversion, while bulk density increased. Median infiltration rates fell to about 15% of the initial values in the forest, and C and N concentrations dropped to around 60%, whilst the bulk density increased by 50%. Despite high spatial variability, these parameters have correlated well with time since conversion and with each other.
Mass Extinction And The Structure Of The Milky Way

We use the most up to date Milky Way model and solar orbit data in order to test the hypothesis that the Sun's galactic spiral arm crossings cause mass extinction events on Earth. To do this, we created a new model of the Milky Way's spiral arms by combining a large quantity of data from several surveys. We then combined this model with a recently derived solution for the solar orbit to determine the timing of the Sun's historical passages through the Galaxy's spiral arms. Our new model was designed with a symmetrical appearance, with the major alteration being the addition of a spur at the far side of the Galaxy. A correlation was found between the times at which the Sun crosses the spiral arms and six known mass extinction events. Furthermore, we identify five additional historical mass extinction events that might be explained by the motion of the Sun around our Galaxy. These five additional significant drops in marine genera that we find include significant reductions in diversity at 415, 322, 300, 145 and 33 Myr ago. Our simulations indicate that the Sun has spent ~60% of its time passing through our Galaxy's various spiral arms. Also, we briefly discuss and combine previous work on the Galactic Habitable Zone with the new Milky Way model.
Towards the Generation of Bilingual Chinese-English Multi-word Expressions from Large Scale Parallel Corpora: An Experimental Approach

There is increasing practical need for bilingual lexicon in wide ranging applications such as CAT systems and in cross-lingual information retrieval. The need for more sophisticated and more extensive resources involving bilingual multi-word expressions has increased even more for the bilingual processing of complex texts such as legal documents, technical names, contracts and patents. We report here a preliminary attempt at successful efforts to mine bilingual MWEs from 300+k Chinese-English patents.
Improved Framework for Appropriate Components Selection

Component based software engineering (CBSE) approach is used to develop a software system from preexisting software components. It is difficult to select a suitable component from the library of components for the problem of CBSE. Appropriate software component selection plays an important role for the success of project. Many approaches are suggested to solve component selection problem. In this paper, the component selection is done by improving the integrated component selection framework by including the pliability metric to cut down the time and cost. Pliability is a flexible measure that assesses software quality. We anticipate that the proposed solution will solve the component selection problem of software industry.
Tail reconnection in the global magnetospheric context: Vlasiator first results

Abstract. The key dynamics of the magnetotail have been researched for decades and have been associated with either three-dimensional (3-D) plasma instabilities and/or magnetic reconnection. We apply a global hybrid-Vlasov code, Vlasiator, to simulate reconnection self-consistently in the ion kinetic scales in the noon–midnight meridional plane, including both dayside and nightside reconnection regions within the same simulation box. Our simulation represents a numerical experiment, which turns off the 3-D instabilities but models ion-scale reconnection physically accurately in 2-D. We demonstrate that many known tail dynamics are present in the simulation without a full description of 3-D instabilities or without the detailed description of the electrons. While multiple reconnection sites can coexist in the plasma sheet, one reconnection point can start a global reconfiguration process, in which magnetic field lines become detached and a plasmoid is released. As the simulation run features temporally steady solar wind input, this global reconfiguration is not associated with sudden changes in the solar wind. Further, we show that lobe density variations originating from dayside reconnection may play an important role in stabilising tail reconnection.
FIRST DETECTION IN GAMMA-RAYS OF A YOUNG RADIO GALAXY: FERMI-LAT OBSERVATIONS OF THE COMPACT SYMMETRIC OBJECT PKS 1718−649

We report the γ-ray detection of a young radio galaxy, PKS 1718−649, belonging to the class of compact symmetric objects (CSOs), with the Large Area Telescope (LAT) on board the Fermi satellite. The third Fermi Gamma-ray LAT catalog (3FGL) includes an unassociated γ-ray source, 3FGL J1728.0−6446, located close to PKS 1718−649. Using the latest Pass 8 calibration, we confirm that the best-fit 1σ position of the γ-ray source is compatible with the radio location of PKS 1718−649. Cross-matching of the γ-ray source position with the positions of blazar sources from several catalogs yields negative results. Thus, we conclude that PKS 1718−649 is the most likely counterpart to the unassociated LAT source. We obtain a detection test statistics TS ∼ 36 (>5σ) with a best-fit photon spectral index Γ = 2.9 ± 0.3 and a 0.1–100 GeV photon flux density F0.1−100 GeV = (11.5 ± 0.3) × 10−9 ph cm−2 s−1. We argue that the linear size (∼2 pc), the kinematic age (∼100 years), and the source distance (z = 0.014) make PKS 1718−649 an ideal candidate for γ-ray detection in the framework of the model proposing that the most compact and the youngest CSOs can efficiently produce GeV radiation via inverse-Compton scattering of the ambient photon fields by the radio lobe non-thermal electrons. Thus, our detection of the source in γ-rays establishes young radio galaxies as a distinct class of extragalactic high-energy emitters and yields a unique insight on the physical conditions in compact radio lobes interacting with the interstellar medium of the host galaxy.
In-utero social interaction of twins

We model pre-birth twins' competition for maternal resources inside the womb. When the innate endowment affects both birth weight and the post-birth outcome directly, pre-natal social interaction leads to bias in thestandard twin fixed-effects estimator. We propose a test of social interaction that is based on data on triplets, and find some evidence for social interaction. We then use an instrumental-variable estimation strategy that recovers consistently the returns to birth weight. Our estimation results indicate that the returns to birth weight are closer to the sibling-based estimates than the twin fixed-effects estimates reported in the previous literature.
Robustness of Deep Learning Architectures with Respect to Training Data Variation

The use of deep neural networks (DNN) revolutionized machine learning tasks like image classification and segmentation [6]. However, DNNs are black box models developed with the aim to generalize a given training set and thus to process unknown data. Due to the high amount of model parameters, it is yet impossible to fully understand the decision making process. The identification of parameters with poor generalization is hard and manual improvement is impossible. Thus, robustness is subject of consideration.
High Level Framework for Bridge Inspection Using LiDAR-Equipped UAV

According to Statistics Canada, bridges in Canada have a service life of approximately 43 years. With the majority of bridges passing half of their expected service life, a large amount of investment needs to be made to inspect and maintain them in a safe condition. Manual inspection methods are both time-consuming and costly, which may discourage further inspections and follow-up of defects. Thus, there is a great need for using an automated data collection system. Surface defects (e.g. cracks) in concrete bridges can be inspected using 3D Light Detection and Ranging (LiDAR) scanner as a Non-Destructive Testing (NDT) method. However, the commonly used terrestrial LiDAR is limited to stationary data collection, which reduces the accessibility to some components of the bridges. To tackle this limitation, a LiDAR attached to an Unmanned Aerial Vehicle (UAV) provides more flexibility and accessibility for inspecting large surface areas without threatening inspectors’ safety. After providing a comprehensive literature review about the usage of UAVs and LiDAR for the inspection of different types of structures, this paper proposes a high level framework for bridge inspection using LiDAR-equipped UAV. The framework includes the following steps: (1) planning a collisionfree optimized path with respect to the minimum cost and maximum coverage considering a variety of constrains and requirements related to the hardware and the inspection task, and (2) data analysis for detecting the surface defects based on the collected
Relevant Indicators of Relative Expertise in Economic Problem Solving: A Factor Analysis.

MF01/PCO2 Plus Postage. Content Analysis; Correlation; *Economic Factors; Economic Research; *Economics; *Economics Education; *Factor Analysis; Higher Education; Least Squares Statistics; Problem Solving This paper reports preliminary research into the nature of relative expertise in economic problem solving. Specifically, this report s.ieks to address the question of whether the presence of economic knowledge alone accounts for expertise in economic problem solving or whether both economic knowledge and the development and employment of economic problem solving strategies are necessary prerequisites for acquiring expertise in economic problem solving. The researchers examined literal transcripts generated from the "talk-aloud" protocols of 28 participants responding to three economic problems. Each sub-group contained four participants: (I) high school students who had taken economics and those who had not taken economics; (2) undergraduate economics majors and non-majors; (3) graduate students in economics; and (4) Ph.D. economists employed in public and private forecasting and academic Ph.D. economists. The study employed a causal-comparative design with members of the seven sub-sample groups identified by the researcher. Three economics problems were employed in the study with several phases of data gatl-ering involved in the analysis of data. Extensive charts and graphs accompany the text. Contains 41 references. (EH) *********************************************************************** Reproductions supplied by EDRS are the best that can be made from the original document. *********************************************************************
On the Limits to Inequality in Representation

The correspondence between public preferences and public policy is a critical rationale for representative democratic government. This view has been put forward in the theoretical literature on democracy and representation (e.g., Dahl 1971; Pitkin 1967; Birch 1971) and in “functional” theories of democratic politics (Easton 1965; Deutsch 1963), both of which emphasize the importance of popular control of policymaking institutions. Political science research also shows a good amount of correspondence between opinion and policy, though to varying degrees, across a range of policy domains and political institutions in the U.S. and elsewhere. This is of obvious significance.Earlier versions of this paper were presented at the 2006 Annual Meetings of the American Political Science Association, Philadelphia, at the Elections, Public Opinion and Parties specialist group, Nottingham, England, and at the 2007 National Conference of the Midwest Political Science Association, Chicago. We thank Vinod Menon for assistance with data collection and Kevin Arceneaux, Suzie DeBoef, Harold Clarke, Peter Enns, Mark Franklin, Martin Gilens, John Griffin, Will Jennings, Rich Joslyn, Benjamin Page, David Sanders, David Weakliem, John Zaller, and the anonymous reviewers for comments.
Extraction and characterization of proteins from skim rubber.

To optimize the extraction of proteins from skim natural rubber (NR), solution type, number of extractions and sample size were examined. Two solutions, phosphate buffered saline (PBS) and sodium dodecyl sulfate (SDS), were used for protein extraction. The protein content was determined by Bradford assay. SDS-polyacrylamide gel electrophoresis (SDS-PAGE) was employed to check the molecular weight of the extract. Analysis of protein purity by Fourier Transform Infrared (FTIR), spectrometer UV-Vis spectrometer and Carbon-Hydroger-Nitrogen (CHN) analyzer was also carried out on the extract from skim NR and compared with bovine serum albumin (BSA), a model protein. The results revealed that all factors had significant effects on the levels of protein extracted. A high extractable protein (EP) content was obtained from the skim NR using a small amount of specimen in fresh SDS solution and repeating the extraction step three times (12 h/time). SDS-PAGE demonstrated that the EP had three subunit molecular weights of 66, 78 and 116 kDa. Protein impurities could be detected by the CHN method, infrared technique and UV absorbance analysis.
Improvement of the Spin Torque for a Fast Spin-Transfer Driven Magnetization Reversal

For a fast writing operation in a spin-transfer magnetic random access memory (ST-MRAM) cell, the exertion of a large initial torque is one of the plausible ways to switch a magnetic moment without the help of the thermal fluctuations. We have fabricated perpendicular-to-plane (CPP) spin-valves with another reference layer polarizing electrons to the out-of-plane or the hard-axis in-plane, and studied the sidewall geometry as the angle of argon plasma during the ion mill etching. Summary of Research: The magnetization behavior of a nanomagnet under the effect of an external magnetic field and with the transfer of the spin angular momentum from a spin-polarized electron current has been extensively studied for the last decade. One effect that can be caused by this spin transfer effect is the magnetization reversal of the nanomagnet between two stable states, and the other is the steady state oscillation of the magnetic moment if the applied field is sufficiently large. Those effects open a possibility of the technological applications such as ST-MRAM and a current-tunable nano-scale microwave generator. One of the issues for the ST-MRAM is to lower the onset current (Ic) for the switching or to increase the switching speed while keeping its thermal stability. From the modified LLG-equations [1], the magnitude of the spin-torque is approximately proportional to I sin(q) where I is the applied dc current and q is the angle between the magnetic moments of the fixed and free layer. There are two different reversal mechanisms which depend on the scale of current [2]. In the first case when the applied dc current is smaller than Ic, the critical current for switching in the absence of thermal effect, the reversal is thermally activated. In this case, small magnitudes of spin-torque are exerted to the moment of the free layer at the beginning of the reversal process due to the thermal fluctuations of the nanomagnet about its equilibrium position parallel or anti-parallel to the reference layer ferromagnet. Therefore the switching time is relatively slow, generally more than 100 ns, and there is a stochastic dispersion of reversal rates as the function of bias currents. In the other case when large currents more than few times Ic are applied the magnitude of the spin-torque itself is enough to get the moment of a free layer excited. In this regime the magnetization reversal is more consistent and fast (~ 1 ns) which is the desirable regime for the MRAM application. To date several methods have been investigated for reducing the magnitude of the current Figure 1: (I) dual spin-valve with in-plane polarized reference layer (II) dual spin-valve with out-of-plane polarized reference layer (III) conventional spin-valve.
Near Infrared Diode Laser THz Systems

Abstract. The generation and detection of radiation in the THz frequency range can be achieved with many different electronic and photonic concepts. Among the many different photonic THz systems the most versatile are based on diode lasers. In this paper we describe and review the different concepts and optimization ideas for diode laser based THz systems in order to achieve the best performance for different types of THz setups.
Differential Analysis of the Cytochrome p450 Acaricide-Resistance Genes in Panonychus citri (Trombidiformes: Tetranychidae) Strains

Abstract The citrus red mite, Panonychus citri (McGregor) (Trombidiformes: Tetranychidae), a highly destructive pest in citrus groves around the world, has developed resistance to many registered acaricides. Hexythiazox is a selective miticide that has been widely used to control citrus mites in a variety of crops. Forty-six cytochrome P450 mono-oxygenase genes related to general pesticide resistance in other insect species were obtained from the transcriptomes of the hexythiazox-resistant (RR) and hexythiazox-susceptible (SS) strains of P. citri and divided into 4 clans, 15 families and 24 subfamilies. Sequence analyses of each CYP resulted in detection of 3 mutationsin the CYP307A1 gene (841-A to C, 1395-T to C, 1491-T to C) that differed between the 2 strains. Only the change at an amino acid position (278-lysine to glutamine) resulted in a sense mutation. One SNP site was also detected in CYP381A2 (40-A to T) causing a sense amino acid mutation (14-threonine to serine). Seven of these P450s belonged to the CYP2 clan, CYP3 clan and CYP4 clan based on digital gene expression (DGE) library sequencing with a |log2 ratio| value greater than 2, but there were no significant differences revealed by qRT-PCR analysis. This study provides essential information for future research on the hexythiazox-resistance mechanism of P. citri. More methods are needed to further elucidate the molecular mechanisms of resistance to hexythiazox in P. citri.
Determination of entangled quantum states of a trapped atom

(September 18, 1996)We propose a method for measuring entangled vibronicquantum states of a trapped atom. It is based on the nonlin-ear dynamics of the system that appears by resonantly drivinga weak electronic transition. The proposed technique allowsthe direct sampling of a Wigner-function matrix, displayingall knowable information on the quantum correlations of themotional and electronic degrees of freedom of the atom. Itopens novel possibilities for testing fundamental predictionsof the quantum theory concerning interaction phenomena.PACS numbers: 03.65. Bz, 42.50. Vk, 32.80. PjI. INTRODUCTION
GPS-structural health monitoring of a long span bridge using neural network adaptive filter

Abstract The movement of bridge deck bearings plays a significant role in the safety of bridges. Real time kinematic global positioning system (GPS) continuous health monitoring using relative deformations was carried out on a long span Zhujiang Huangpu Bridge. The neural network aided adaptive filter is used to predict and adjust the GPS monitoring data. The statistical moments in time and frequency domains were used to analyse the movement of the bridge deck. The results indicate that (1) the proposed neural network with the adaptive filter model can be used to de-noise the GPS health monitoring signals, (2) the GPS is highly sensitive for bridge deck movements, (3) the statistical moments can be used to detect the movements and errors of the GPS observations, and (4) the bridge is very safe under different loads.
OBJECT RECOGNITION IN LAKE AND ESTUARY

OBJECT RECOGNITION IN LAKE AND ESTUARY ENVIRONMENTS A.J. Punch, M.S.T. Western Carolina University (April 2011) Director: Dr. Brian Howell Traditionally, autonomous underwater vehicles employ multiple configurations of sensor payloads in order to accomplish a specific mission. Due to advances in imaging technology, imaging sonar arrays and optical imaging devices are among these payloads. Independent of mission specifics, the majority of imaging data is either stored onboard the vehicle or transmitted to a base station for later analysis. In either situation, there is limited local real time analysis and limited mission duration. One focus for increasing real time analysis is the reduction of image information. By using image processing techniques, such as edge detection, less relevant information can be eliminated while preserving important object features. This reduced object information is then used as inputs to a neural network. A neural network is a cognitive algorithm which has the ability to adapt to achieve desired tasks. These networks are able to generalize and make decisions based on partial or limited input information. The goal of this research is to create an autonomous in-situ recognition system for marine environments, specifically the processing and classification of object image data. Image information will be applied to a neural network approach to mimic higher order decision making in an artificial cognitive algorithm.
Renewal of Psychophysical Qualities of Professional Sportsman

Purpose: To proof scientifically the necessity of using massage and functional music for athletes of various sport as the means of restoration of psychophysical qualities during the preparation time. Methods: Analysis of scientific literature, questionnaires (Eysenck-Q, SAM-Q), assessment of recovery rate after a special work and statistical analysis. Sample: A total of 12 subjects were recruited for the trial. All study participants were within the age range of 18 to 30 years old. They were professional athletes of shooting and cycling who had more than 10 years of experience in sports. Results: The combination of sports massage and well-designed music enhances the recovery of sportsmen according to SAM-Q (shooting: group +28%; cycling: group +23%). Also, according to a special work on training (with a recovery rate of shooters: group +28%; the recovery rate in riders: group +26% ). Conclusions: The combination of sports massage and efficient music does make the process of renewal of sportsmen`s psychophysical qualities more effective. During the research, we observed that the shooters had better results in recovery of psychophysical qualities than the sportsman of cycling. Implications: Understanding the processes of restoring the psychophysical qualities of athletes can help to increase their sports endurance and improve their performance in sports.