Miracle-dz/UniFAR-FTUs huggingface dataset:
Conifer phytotoxicity and vegetation control efficacy of ten selected herbicides

approved: '1 Robert W. Rose, Jr. Ten herbicides (atrazine, azafenidin, chlorsulfuron, clopyralid, hexazinone, imâzapic, imazapyr, metsulfuron, pendimethalin, and sulfometuron) were evaluated for phytotoxicity in first-year seedlings of eight conifer species (Douglas-fir, grand fir, noble fir, redwood, Sitka spruce, western hemlock, western red cedar, and western white pine). Six of these herbicides (atrazine, clopyralid, hexazinone, imazapyr, metsulfuron, and sulfometuron) were also evaluated for vegetation control efficacy. Azafenedin, chiorsulfuron, imazapic, imazapyr, metsulfuron, pendimethalin, and sulfometuron were applied as fail site preparation treatments prior to spring conifer planting. Atrazine, clopyralid, hexazinone, and sulfometuron were applied as spring release treatments after conifer planting. All herbicides were applied at an operational rate (lx), as determined by label recommendations and industry standards, and a rate equal to three times the operational rate (3x). Treatments were replicated at three sites in western Oregon and Washington. Most of the herbicides tested in this study exhibited high levels of conifer safety. At the operational rate, hexazinone and sulfometuron were the only herbicides to cause significant injury to any of the conifer species tested. The hexazinone lx treatment caused mortality in western red cedar. The spring sulfometuron lx treatment caused mortality in grand fir and both sulfometuron lx treatments caused growth reductions in western red cedar. In addition, sulfometuron produced a subtle but non-significant trend of growth inhibition in five of the remaining six species, and appears to be a mild growth inhibitor in most conifers. Otherwise, none of the herbicides caused significant injury at the operational rate. Hexazinone and sulfometuron afforded the best overall weed control of the herbicides tested, Sulfometuron provided equal or better weed control as a fall site preparation treatment than as a spring release treatment. Atrazine provided the best combination of weed control efficacy and overall conifer safety. Clopyralid provided good control of weeds in the Asteraceae and Polygonaceae families, but was generally ineffective against other species. Metsulfuron and imazapyr were generally ineffective against the herbaceous species present in this study. Herbicide recommendations for various combinations of conifer crop and target weed species are provided in convenient reference tables. These tables facilitate the design of herbicide prescriptions for a variety of reforestation scenarios in the Pacific Northwest. Few of these herbicides are acutely toxic to any of the conifer species tested. We specify the conifer/herbicide combinations that should be avoided. Otherwise, foresters have a great deal of flexibility in developing vegetation management prescriptions with these chemicals. Conifer Phytotoxicity and Vegetation Control Efficacy of Ten Selected Herbicides
A multiagent approach for modelling SMEs mechatronic supply chains

Abstract This paper presents the application of the multiagent system for modelling supply chains involving Small and Medium Enterprises (SMEs) in the mechatronic industry. This work is a combination of two research scopes. The first one deals with the identification of the different concepts able to model the particular manufacturing systems and production context in Savoie – France. The second one outlines the development process based on an agent modelling approach, which offers an easy and reusable modelling of supply chain concepts.
Formal Analysis of Fault-tolerant Group Key Management Using ZooKeeper

Security-as-a-Service (SecaaS) is gaining popularity, with cloud-based anti-spam and anti-virus leading the way. In this work we look at key management as a security service and focus on group key management witha central group key manager. Specifically, we analyze are writing logic model of a ZooKeeper-based group key management service specified in Maude and study its tolerance to faults and performance as it scales to service larger groups using the PVeStA statistical model checking tool.
History of Additive Manufacturing and the 2009 Roadmap for Additive Manufacturing : Looking Back and Looking Ahead

Additive Manufacturing (AM) has roots in topography and photosculpture which date back almost 150 years. Both of these early technologies might be categorized as manual " cut and stack " approaches to building a freeformed object in a layerwise fashion. The first successful AM process was effectively a powder deposition method with an energy beam proposed by Ciraud in 1972. Other historical developments in AM will be described in the presentation. Transitioning from the oldest developments in AM to the most recent, earlier this year sixty-five experts in AM gathered in the Washington DC area to develop a research roadmap for AM. The results of that effort are described.
Lidar observation of Asian dust events during the ACE-Asia 2001 IOP at Gosan, Jeju Island, Korea

In general Asian dust storms occurring during the spring season in the northeast Asia play an important role in radiative forcing and regional climate change. In order to investigate the characteristic of optical properties of Asian dust particles atmospheric aerosol vertical profile was measured with a multi-wavelength LIDAR system developed by ADEMRC, K-JIST and a collocated micro-pulse LIDAR (MPL) during the ACE-Asia intensive observation period, 11 March ~ 4 May 2001 at the Gosan super site (33°17'N, 126°10'E) in Jeju Island, Korea. Air mass backward trajectory analysis shows that air masses came from either the northwestern Chinese desert regions or northeastern Chinese sandy areas. It has been shown that combining the LIDAR data and back trajectory analysis can assess the transport characteristics of atmospheric aerosol during the Asian dust events. The LIDAR-derived aerosol optical depth values were compared with those measured by a collocated AERONET sun photometer. Relationship between the LIDAR data and chemical data of atmospheric particulate matters observed at the surface has been analyzed.
Surveyor: a DSEL for representing and analyzing strongly typed surveys

Polls and surveys are increasingly employed to gather information about attitudes and experiences of all kinds of populations and user groups. The ultimate purpose of a survey is to identify trends and relationships that can inform decision makers. To this end, the data gathered by a survey must be appropriately analyzed. Most of the currently existing tools focus on the user interface aspect of the data collection task, but pay little attention to the structure and type of the collected data, which are usually represented as potentially tag-annotated, but otherwise unstructured, plain text. This makes the task of writing data analysis programs often difficult and error-prone, whereas a typed data representation could support the writing of type-directed data analysis tools that would enjoy the many benefits of static typing. In this paper we present Surveyor, a DSEL that allows the compositional construction of typed surveys, where the types describe the structure of the data to be collected. A survey can be run to gather typed data, which can then be subjected to analysis tools that are built using Surveyor's typed combinators. Altogether the Surveyor DSEL realizes a strongly typed and type-directed approach to data gathering and analysis. The implementation of our DSEL is based on GADTs to allow a flexible, yet strongly typed representation of surveys. Moreover, the implementation employs the Scrap-Your-Boilerplate library to facilitate the type-dependent traversal, extraction, and combination of data gathered from surveys.
Sarcoplasmic reticulum Ca2+ transport and gene expression in congestive heart failure are modified by imidapril treatment.

This study was designed to test the hypothesis that blockade of the renin-angiotensin system improves cardiac function in congestive heart failure by preventing changes in gene expression of sarcoplasmic reticulum (SR) proteins. We employed rats with myocardial infarction (MI) to examine effects of an angiotensin-converting enzyme inhibitor, imidapril, on SR Ca(2+) transport, protein content, and gene expression. Imidapril (1 mg.kg(-1). day(-1)) was given for 4 wk starting 3 wk after coronary artery occlusion. Infarcted rats exhibited a fourfold increase in left ventricular end-diastolic pressure, whereas rates of pressure development and decay were decreased by 60 and 55%, respectively. SR Ca(2+) uptake and Ca(2+) pump ATPase, as well as Ca(2+) release and ryanodine receptor binding activities, were depressed in the failing hearts; protein content and mRNA levels for Ca(2+) pump ATPase, phospholamban, and ryanodine receptor were also decreased by approximately 55-65%. Imidapril treatment of infarcted animals improved cardiac performance and attenuated alterations in SR Ca(2+) pump and Ca(2+) release activities. Changes in protein content and mRNA levels for SR Ca(2+) pump ATPase, phospholamban, and ryanodine receptor were also prevented by imidapril treatment. Beneficial effects of imidapril on cardiac function and SR Ca(2+) transport were not only seen at different intervals of MI but were also simulated by another angiotensin-converting enzyme inhibitor, enalapril, and an ANG II receptor antagonist, losartan. These results suggest that blockade of the renin-angiotensin system may increase the abundance of mRNA for SR proteins and, thus, may prevent the depression in SR Ca(2+) transport and improve cardiac function in congestive heart failure due to MI.
Spatial averaging of water content by time domain reflectometry : Implications for twin rod probes with and without dielectric coatings

The averaging of apparent relative dielectric permittivities by time domain reflectometry (TDR) is examined for properties varying along TDR waveguides and in the plane perpendicular to a TDR probe. A square root averaging model with uniform weighting factors describes the measured apparent relative dielectric permittivity for axially varying materials; variations in the transverse plane are described by an inverse averaging model with nonuniform spatial weighting. We define the sensitivity of a TDR probe as the change in the measured travel time for a given change in the average soil water content for rods of a fixed length. For rods with dielectric coatings, this sensitivity increases with the dielectric permittivity of the coating and the rod radius and decreases with the soil dielectric permittivity. Due to the dependence of the sensitivity on the soil water content, coated rods will not measure the actual average water content for conditions of axially variable water contents.
Speaker recognition using Mel frequency Cepstral Coefficients (MFCC) and Vector quantization (VQ) techniques

This paper presents a fast and accurate automatic voice recognition algorithm. We use Mel frequency Cepstral Coefficient (MFCC) to extract the features from voice and Vector quantization technique to identify the speaker, this technique is usually used in data compression, it allows to model a probability functions by the distribution of different vectors, the results that we achieve were 100% of precision with a database of 10 speakers.
Maternal effects and range expansion: a key factor in a dynamic process?

Species that depend on ephemeral habitat often evolve distinct dispersal strategies in which the propensity to disperse is closely integrated with a suite of morphological, behavioural and physiological traits that influence colonizing ability. These strategies are maintained by natural selection resulting from spatial and temporal variation in resource abundance and are particularly evident during range expansion. Yet the mechanisms that maintain close alignment of such strategies with resource availability, integrate suites of dispersal traits and generate variability in dispersal propensity are rarely known. Breeding females can influence offspring phenotype in response to changes in current environmental conditions, making maternal effects uniquely suited to bridge fluctuations in resource abundance in the maternal generation and variation in offspring dispersal ability. Western bluebirds' (Sialia mexicana) dependence on nest cavities—an ephemeral resource—has led to the evolution of two distinct dispersal phenotypes: aggressive males that disperse and non-aggressive males that remain philopatric and cooperate with their relatives. Over the last 40 years, western bluebirds rapidly expanded their geographical range, providing us with an opportunity to test, in newly established populations, the importance of maternal effects for generating variability in dispersal propensity. Here, I show that, under variable resource conditions, breeding females group offspring of different competitive ability in different positions in the egg-laying order and, consequently, produce aggressive males that are more likely to disperse when resources are low and non-aggressive philopatric males when resources are abundant. I then show experimentally that the association between resource availability and sex-specific birth order is robust across populations. Thus, this maternal effect enables close tracking of resource availability and may explain how variation in dispersal is generated in newly colonized populations. More generally, these results suggest that, as a key source of variation in colonizing phenotypes, maternal effects are of crucial importance for understanding the dynamics of range expansion.
Vertical seismic profiling: Separation of upgoing and downgoing acoustic waves in a stratified medium

One of the essential steps in the processing of a vertical seismic profile is the separation of upgoing and downgoing signals. With this perspective in mind, seismic data recorded in a borehole are modeled in terms of these waves and a mathematically optimal “least‐squares” technique for extracting them is derived. The method imposes practically no constraints on the spacing between recording levels and allows almost perfect rejection of a coherent downgoing signal. The exact formulation of the one‐dimensional model requires that acoustic impedance information be included, but a reasonable and realistic approximation can neglect impedance. We derive frequency‐wavenumber response plots for the two limiting cases of even and randomly spaced levels and compare these to the response of a “conventional” velocity filtering technique. By a careful study of available logs, recording levels can be chosen to optimize geophone coupling rather than insisting on uniform spatial sampling. Data editing, normalization, a.
Recognising Sets and Their Elements: Tree Kernels for Entity Instantiation Identification

We apply tree kernels to entity instantiations. An entity instantiation is an entity relationship, in which a set of entities is mentioned, and then a member or subset of this set is introduced. We present the first reliably annotated intrasentential entity instantiation corpus, along with an extension to the intersentential annotations in McKinlay and Markert (2011). We then apply tree kernels to both interand intrasentential entity instantiations, showing comparable results to an extensive set of unstructured features. The combination of tree kernels and unstructured features leads to significant improvements over either method in isolation.
Information Density and Syntactic Repetition

In noun phrase (NP) coordinate constructions (e.g., NP and NP), there is a strong tendency for the syntactic structure of the second conjunct to match that of the first; the second conjunct in such constructions is therefore low in syntactic information. The theory of uniform information density predicts that low-information syntactic constructions will be counterbalanced by high information in other aspects of that part of the sentence, and high-information constructions will be counterbalanced by other low-information components. Three predictions follow: (a) lexical probabilities (measured by N-gram probabilities and head-dependent probabilities) will be lower in second conjuncts than first conjuncts; (b) lexical probabilities will be lower in matching second conjuncts (those whose syntactic expansions match the first conjunct) than nonmatching ones; and (c) syntactic repetition should be especially common for low-frequency NP expansions. Corpus analysis provides support for all three of these predictions.
Using Partial Orders to Improve Automatic Verification Methods

In this paper, we present a verification method for concurrent finite-state systems that attempts to avoid the part of the combinatorial explosion due to the modeling of concurrency by interleavings. The behavior of a system is described in terms of partial orders (more precisely in terms of Mazurkiewicz's traces) rather than in terms of interleavings. We introduce the notion of “trace automation” which generates only one linearization per partial order. Then we show how to use trace automata to prove program correctness.
Decoding Intra-Limb and Inter-Limb Kinematics During Treadmill Walking From Scalp Electroencephalographic (EEG) Signals

Brain-machine interface (BMI) research has largely been focused on the upper limb. Although restoration of gait function has been a long-standing focus of rehabilitation research, surprisingly very little has been done to decode the cortical neural networks involved in the guidance and control of bipedal locomotion. A notable exception is the work by Nicolelis' group at Duke University that decoded gait kinematics from chronic recordings from ensembles of neurons in primary sensorimotor areas in rhesus monkeys. Recently, we showed that gait kinematics from the ankle, knee, and hip joints during human treadmill walking can be inferred from the electroencephalogram (EEG) with decoding accuracies comparable to those using intracortical recordings. Here we show that both intra- and inter-limb kinematics from human treadmill walking can be achieved with high accuracy from as few as 12 electrodes using scalp EEG. Interestingly, forward and backward predictors from EEG signals lagging or leading the kinematics, respectively, showed different spatial distributions suggesting distinct neural networks for feedforward and feedback control of gait. Of interest is that average decoding accuracy across subjects and decoding modes was ~ 0.68±0.08, supporting the feasibility of EEG-based BMI systems for restoration of walking in patients with paralysis.
Text Categorization Based on Boosting Association Rules

Associative classification is a novel and powerful method originating from association rule mining. In the previous studies, a relatively small number of high-quality association rules were used in the prediction. We propose a new approach in which a large number of association rules are generated. Then, the rules are filtered using a new method which is equivalent to a deterministic Boosting algorithm. Through this equivalence, our approach effectively adapts to large-scale classification tasks such as text categorization. Experiments with various text collections show that our method achieves one of the best prediction performance compared with the state-of-the-arts of this field.
Using Kernel Alignment to Select Features of Molecular Descriptors in a QSAR Study

Quantitative structure-activity relationships (QSARs) correlate biological activities of chemical compounds with their physicochemical descriptors. By modeling the observed relationship seen between molecular descriptors and their corresponding biological activities, we may predict the behavior of other molecules with similar descriptors. In QSAR studies, it has been shown that the quality of the prediction model strongly depends on the selected features within molecular descriptors. Thus, methods capable of automatic selection of relevant features are very desirable. In this paper, we present a new feature selection algorithm for a QSAR study based on kernel alignment which has been used as a measure of similarity between two kernel functions. In our algorithm, we deploy kernel alignment as an evaluation tool, using recursive feature elimination to compute a molecular descriptor containing the most important features needed for a classification application. Empirical results show that the algorithm works well for the computation of descriptors for various applications involving different QSAR data sets. The prediction accuracies are substantially increased and are comparable to those from earlier studies.
Destination Recreation: A Generational Exploration of Psychographic Characteristics related to Vacation Recreation Activity Preferences

This study investigated the association between the preferred vacation recreation activities of different generations of travelers and their individual psychographic profile characteristics as based on Stanley Plog's (1972) model. Additionally an attempt was made to classify recreation activities across the psychographic continuum as either Dependable (Psychocentric) or Venturer (Allocentric) activities in accordance with respondent scores from Plog's adapted psychographic instrument. The results indicated an overlap between respondent psychographic scores and their projected vacation recreation activity preferences. There were demographic differences in how travelers distributed across Plog's continuum as well though the data suggested a uniform psychographic distribution across the generational cohorts providing support for similarly active tourism preferences across the generations.
A review of practical numerical modelling methods for the advanced interpretation of ground-penetrating radar in near-surface environments

As ground-penetrating radar (GPR) technology improves, there is an increasing demand for more sophisticated and detailed interpretational tools. Numerical modelling has become one of the most popular advanced analysis methods and there is a wide range of electromagnetic modelling approaches available to the GPR user. The finite-difference time-domain (FDTD) technique is one of the most common, as it provides modellers with a robust, flexible, yet accurate, modelling scheme that is capable of simulating GPR wave propagation in complex, three-dimensional, heterogeneous, lossy, subsurface environments. Through the use of a well-constrained example, the realistic modelling of near-surface GPR is evaluated including the practical limitations, computational procedures and application constraints of the FDTD method. The results show that, despite some obvious deficiencies, even a relatively basic FDTD model can provide important additional information for the advanced interpretation of observed GPR data.