Miracle-dz/UniFAR-FTUs huggingface dataset:
Groundwater and agriculture: Insights from farmers in central Minnesota on how to protect both

In agricultural areas with groundwater that is highly sensitive to pollution and surface water resources that are sensitive to groundwater withdrawal, farmers are under pressure from government agencies and environmental groups to improve their on-farm management practices (Kennedy 2015a, 2015b; Marcotty 2012). One area where conflicts over groundwater and agriculture are growing is the central sands region of Minnesota, United States (Gunderson 2014; Haugen 2014; Marcotty 2013; Robertson 2009; Vogel 2014b). This area is characterized by coarse-textured soils formed from glacial outwash (USDA NRCS 2018), a water table that is vulnerable to pollution (Adams 2016), and extensive agricultural production with crops such as corn (Zea mays L.), soybean (Glycine max [L.] Merr.), alfalfa (Medicago sativa L.), wheat (Triticum aestivum L.), oats (Avena sativa L.), potato (Solanum tuberosum L.), and dry edible beans (Phaseolus vulgaris L.) (USDA NASS 2014, 2017). While the trend of change in nitrate (NO3) concentrations over time in this region is either stable (Minnesota Pollution Control Agency et al. 2018) or slightly increasing (MDA 2015b), the extent of NO3 contamination in groundwater is already widespread (MN EQB 2017). Nitrate concentrations in groundwater are found at elevated levels in this region for public water systems (PWS) (MDH 2018)…
Exploring the Diversity and Antimicrobial Potential of Marine Actinobacteria from the Comau Fjord in Northern Patagonia, Chile

Bioprospecting natural products in marine bacteria from fjord environments are attractive due to their unique geographical features. Although, Actinobacteria are well known for producing a myriad of bioactive compounds, investigations regarding fjord-derived marine Actinobacteria are scarce. In this study, the diversity and biotechnological potential of Actinobacteria isolated from marine sediments within the Comau fjord, in Northern Chilean Patagonia, were assessed by culture-based approaches. The 16S rRNA gene sequences revealed that members phylogenetically related to the Micrococcaceae, Dermabacteraceae, Brevibacteriaceae, Corynebacteriaceae, Microbacteriaceae, Dietziaceae, Nocardiaceae, and Streptomycetaceae families were present at the Comau fjord. A high diversity of cultivable Actinobacteria (10 genera) was retrieved by using only five different isolation media. Four isolates belonging to Arthrobacter, Brevibacterium, Corynebacterium and Kocuria genera showed 16S rRNA gene identity <98.7% suggesting that they are novel species. Physiological features such as salt tolerance, artificial sea water requirement, growth temperature, pigmentation and antimicrobial activity were evaluated. Arthrobacter, Brachybacterium, Curtobacterium, Rhodococcus, and Streptomyces isolates showed strong inhibition against both Gram-negative Pseudomonas aeruginosa, Escherichia coli and Salmonella enterica and Gram-positive Staphylococcus aureus, Listeria monocytogenes. Antimicrobial activities in Brachybacterium, Curtobacterium, and Rhodococcus have been scarcely reported, suggesting that non-mycelial strains are a suitable source of bioactive compounds. In addition, all strains bear at least one of the biosynthetic genes coding for NRPS (91%), PKS I (18%), and PKS II (73%). Our results indicate that the Comau fjord is a promising source of novel Actinobacteria with biotechnological potential for producing biologically active compounds.
Color image-adaptive watermarking

A novel scheme for the watermarking of colour images is presented in this communication. The first objective is to find the most suitable alternative to RGB color space, which is highly correlated. Colour spaces with linear relation to RGB colour space with uncorrelated components are found to be most suitable for watermarking applications. Second objective is to make the scheme adaptive to o/spl circ/c$80a/spl ring/ colour image. This is achieved by keeping the PSNR in a predefined quality range, while timing the watermark strength parameter. Watermark detection is fast and blind, i.e. only the watermark generation and coefficient randomization keys are needed, and not the original image. The presented results demonstrate the robustness of the method against some common image processing attacks such as compression, scaling, uniform or gaussian noise addition, median filtering, cropping and multiple watermarking.
Expectancies of Rural and Urban Parents Applying for Children's Services at Community Mental Health Centers

Responses to a 15-item Expectation Survey Questionnaire from 256 parents who were applying for children's services showed similar expectations from parents of rural and urban residence: family, friends, or school personnel gave advice; the center would have child specialists, such as counselors, psychologists, and psychiatrists to help children and mothers; appointments within a week were likely; and talking not medication would characterize treatments.
Synthesis for logical initializability of synchronous finite state machines

We present a new method for the synthesis for logical initializability of synchronous state machines. The goal is to produce a gate-level implementation that is initializable when simulated by a 3-valued (0,1,X) simulator. We build on the approach of Cheng and Agrawal (1989,92) who constrain state assignment to translate functional initializability into logic initializability. We propose an alternative method which is guaranteed safe and not as conservative. In addition, we propose necessary and sufficient conditions on 2-level and multi-level logic synthesis to insure 3-valued simulation succeeds.
Alcohol Sales and Risk of Serious Assault

Background Alcohol is a contributing cause of unintentional injuries, such as motor vehicle crashes. Prior research on the association between alcohol use and violent injury was limited to survey-based data, and the inclusion of cases from a single trauma centre, without adequate controls. Beyond these limitations was the inability of prior researchers to comprehensively capture most alcohol sales. In Ontario, most alcohol is sold through retail outlets run by the provincial government, and hospitals are financed under a provincial health care system. We assessed the risk of being hospitalized due to assault in association with retail alcohol sales across Ontario. Methods and Findings We performed a population-based case-crossover analysis of all persons aged 13 years and older hospitalized for assault in Ontario from 1 April 2002 to 1 December 2004. On the day prior to each assault case's hospitalization, the volume of alcohol sold at the store in closest proximity to the victim's home was compared to the volume of alcohol sold at the same store 7 d earlier. Conditional logistic regression analysis was used to determine the associated relative risk (RR) of assault per 1,000 l higher daily sales of alcohol. Of the 3,212 persons admitted to hospital for assault, nearly 25% were between the ages of 13 and 20 y, and 83% were male. A total of 1,150 assaults (36%) involved the use of a sharp or blunt weapon, and 1,532 (48%) arose during an unarmed brawl or fight. For every 1,000 l more of alcohol sold per store per day, the relative risk of being hospitalized for assault was 1.13 (95% confidence interval [CI] 1.02–1.26). The risk was accentuated for males (1.18, 95% CI 1.05–1.33), youth aged 13 to 20 y (1.21, 95% CI 0.99–1.46), and those in urban areas (1.19, 95% CI 1.06–1.35). Conclusions The risk of being a victim of serious assault increases with alcohol sales, especially among young urban men. Akin to reducing the risk of driving while impaired, consideration should be given to novel methods of preventing alcohol-related violence.
Estimating Sheep Pain Level Using Facial Action Unit Detection

Assessing pain levels in animals is a crucial, but time-consuming process in maintaining their welfare. Facial expressions in sheep are an efficient and reliable indicator of pain levels. In this paper, we have extended techniques for recognising human facial expressions to encompass facial action units in sheep, which can then facilitate automatic estimation of pain levels. Our multi-level approach starts with detection of sheep faces, localisation of facial landmarks, normalisation and then extraction of facial features. These are described using Histogram of Oriented Gradients, and then classified using Support Vector Machines. Our experiments show an overall accuracy of 67% on sheep Action Units classification. We argue that with more data, our approach on automated pain level assessment can be generalised to other animals.
Mathematical analysis of long tail economy using stochastic ranking processes

We present a new method of estimating the distribution of sales rates of, e.g., book titles at an online bookstore, from the time evolution of ranking data found at websites of the store. The method is based on new mathematical results on an infinite particle limit of the stochastic ranking process, and is suitable for quantitative studies of the long tail structure of online retails. We give an example of a fit to the actual data obtained from Amazon.co.jp, which gives the Pareto slope parameter of the distribution of sales rates of the book titles in the store.
An Integral Equation Modeling of Electromagnetic Scattering from the Surfaces of Arbitrary Resistance Distribution

In this paper the problem of electromagnetic scattering from the resistive surfaces is carefully surveyed. We model this problem by the integral equations of the second kind. A new set of orthogonal basis functions is used to solve these integral equations via collocation method. Numerical solutions of these equations are given for some cases of resistance distributions. Presented method in this paper can be easily generalized to apply to other cases.
Trend of normalized difference vegetation index (NDVI) over Turkey

Ecosystem productivity, biome distribution, and forest carbon stocks are likely to be changed by the climate change. These ecosystems changes can be identified using Satellite based normalized difference vegetation index (NDVI). In this study, global inventory modeling and mapping studies (GIMMS) NDVI data acquired by the advanced very highresolution radiometer (AVHRR) was used for analyzing the trend over Turkey for the period 1982-2015. The acquired data has bi-monthly nature, and the maximum value of composite method was used for finding monthly NVDI. The obtained NDVI was then clipped to the study area, and then the trend was estimated using Annual aggregated time series (AAT) and seasonal adjusted time series (SAT) methods. In AAT method the annual averages were calculated and then the trend was estimated. In SAT, the seasonal component removed from the time series and the seasonal adjusted time series used for estimating the trend. The gradient latitudinal and longitudinal trend was also implemented to investigate the spatial trend. The gradient was calculated as the trend of the blocks of a specific latitude of longitude over the whole Turkey to have better interpretation of the spatial trend from south to north and east to west. The results showed that throughout Turkey the NDVI has an increasing and decreasing trend, but the increasing trend is dominant as 89.9% and 79.1% of the total area using AAT and SAT respectively are significant increasing trend. One the other hand, only 0.45% and 0.36% of the total area has significant decreasing trend using AAT and SAT respectively and the rest of the area has no significant trend. The seasonal adjusted method showed most of the no trend areas is distributed through the eastern part and the far western part of Turkey. The Annual aggregated trend showed similar pattern with largest no trend area centered in the far eastern part of Turkey. The gradient analysis showed decreasing in the magnitude of the positive NDVI trend when moving from the west to the east, and no specific pattern in the south north direction.
Robust fault diagnosis for a class of nonlinear systems using fuzzy-neural and sliding mode approaches

A robust fault diagnosis (FD) scheme integrating Takagi-Sugeno (T-S) fuzzy-neural models and sliding mode technique is presented for a class of nonlinear systems that can be described by T-S fuzzy models. A fuzzy-neural observer and a fuzzy-neural sliding mode observer are constructed respectively. A modified back-propagation (BP) algorithm is used to update the parameters of these two observers. Finally, the proposed FD scheme is applied to a satellite orbital control system. Simulation results show that this robust fault diagnosis strategy is effective for a class of nonlinear systems.
A dual-band circularly-polarized stacked patch antenna with a small frequency-ratio

A novel dual-band circularly-polarized (CP) stacked patch antenna is presented in this paper. The antenna consists of two layers of FR4 substrates separated by an air gap. The dual-band circular polarization is achieved from aperture-coupled elements by a rotated square patch and a circular patch, which are etched on the top and bottom sides of the upper substrate. Computed results show that the -10 dB reflection coefficient bandwidths are 15.4% centered at 2.18 GHz and 14.2% centered at 2.5 GHz, respectively. The 3 dB axial-ratio (AR) bandwidths are 2.75% and 2.6%, which are within the reflection coefficient bandwidths. The frequency ratio of dual bands is 1.148.
Identifying target populations for screening or not screening using logic regression

Colorectal cancer remains a significant public health concern despite the fact that effective screening procedures exist and that the disease is treatable when detected at early stages. Numerous risk factors for colon cancer have been identified, but none are very predictive alone. We sought to determine whether there are certain combinations of risk factors that distinguish well between cases and controls, and that could be used to identify subjects at particularly high or low risk of the disease to target screening. Using data from the Seattle site of the Colorectal Cancer Family Registry, we fit logic regression models to combine risk factor information. Logic regression is a methodology that identifies subsets of the population, described by Boolean combinations of binary coded risk factors. This method is well suited to situations in which interactions between many variables result in differences in disease risk. We found that neither the logic regression models nor stepwise logistic regression models fit for comparison resulted in criteria that could be used to direct subjects to screening. However, we believe that our novel statistical approach could be useful in settings where risk factors do discriminate between cases and controls, and illustrate this with a simulated data set. Copyright © 2004 John Wiley & Sons, Ltd.
K-core Decomposition: a Tool for the Visualization of Large Scale Networks

We use the k-core decomposition to visualize large scale complex networks in two dimensions. This decomposition, based on a recursive pruning of the least connected vertices, allows to disentangle the hierarchical structure of networks by progressively focusing on their central cores. By using this strategy we develop a general visualization algorithm that can be used to compare the structural properties of various networks and highlight their hierarchical structure. The low computational complexity of the algorithm, O(n+e), where 'n' is the size of the network, and 'e' is the number of edges, makes it suitable for the visualization of very large sparse networks. We apply the proposed visualization tool to several real and synthetic graphs, showing its utility in finding specific structural fingerprints of computer generated and real world networks.
Evolution of loading protocols in implant dentistry for partially dentate arches

Better outcomes for patients receiving dental implants as part of oral rehabilitation remains a constant goal. Advances in implant design, clinical protocols and biomaterials provide opportunities to accelerate treatment, increasing efficiency, predictability and patient satisfaction. It is important to understand that these changes can result in negative outcomes and increased risk. This article reviews the existing published evidence relating to accelerated clinical protocols and patient outcomes. Subsequent to the review, clinical recommendations are offered.
Price-Based Resource Allocation for Spectrum-Sharing Femtocell Networks: A Stackelberg Game Approach

This paper investigates price-based resource allocation strategies for two-tier femtocell networks, in which a central macrocell is underlaid with distributed femtocells, all operating over the same frequency band. Assuming that the macrocell base station (MBS) protects itself by pricing the interference from femtocell users, a Stackelberg game is formulated to study the joint utility maximization of the macrocell and femtocells subject to a maximum tolerable interference power constraint at the MBS. Two practical femtocell network models are investigated: sparsely deployed scenario for rural areas and densely deployed scenario for urban areas. For each scenario, two pricing schemes: uniform pricing and non-uniform pricing, are proposed. The Stackelberg equilibriums for the proposed games are characterized, and an effective distributed interference price bargaining algorithm with guaranteed convergence is proposed for the uniform-pricing case. Numerical examples are presented to verify the proposed studies. It is shown that the proposed schemes are effective in resource allocation and macrocell protection for both the uplink and downlink transmissions in spectrum-sharing femtocell networks.
Augmented AMG‐shifted Laplacian preconditioners for indefinite Helmholtz problems

Discrete representations of the Helmholtz operator generally give rise to extremely difficult linear systems from an iterative solver perspective. This is due in part to the large oscillatory near null space of the linear system. Typical iterative methods do not effectively reduce error components in the subspace associated with this near null space. Traditional coarse grids used within multilevel solvers also cannot capture these components because of their oscillatory nature. While the shifted Laplacian is a popular method allowing multigrid preconditioners to achieve improved convergence, it is still unsatisfactory for higher‐frequency problems. This paper analyzes the shifted Laplacian through polynomial smoothers to show its effect on the spectrum of the discrete Helmholtz operator. This analysis reveals desirable features of the shifted Laplacian preconditioners as well as limitations. Shifted Laplacian techniques are first extended to smoothed aggregation algebraic multigrid. Motivated by analysis, we propose augmenting the algebraic multigrid shifted Laplacian with a two‐grid error correction step. This additional step consists of the generalized minimal residual iterations applied to a projected version of the unshifted equations on a single auxiliary coarse grid. Results indicate that augmentation can improve the convergence significantly and can reduce the overall solve time on two‐dimensional and three‐dimensional problems. Copyright © 2015 John Wiley & Sons, Ltd.
Physiological and Yield Responses of Groundnut(Arachis hypogaea L.) Genotypes to Drought

Groundnut (Arachis hypogaea L.) is an important oil seed crop mainly grown as rainfed crop. Due to erratic rainfall and frequent drought during the crop growth period, groundnut yields are generally low and unstable under rainfed conditions. Drought during critical crop growth stages is crucial for yield in groundnut varieties. But tolerant genotypes may give better yield due to maintenance of physiological responses that were triggered during drought. The experiment was conducted in the Department of Crop Physiology, Tamil Nadu Agricultural University, Coimbatore during 2015-2016 to study physiological characters responsible for improving yield of different groundnut genotypes viz., CO 7, COGn 4, TMV 7 and TMVGn 13 under water stress at different flowering phases viz., pre flowering drought (PFD) during 15- 30 DAS, flowering drought (FD) during 35-50 DAS and post flowering drought (PoFD) during 75-90 DAS by withholding irrigation and control was also maintained with watering up to field capacity for comparison. Observations on various physiological parameters viz., leaf area, root length, relative water content, osmotic potential and leaf gas exchange parameters including, photosynthetic rate, transpiration rate and stomatal conductance were studied during stress and recovery period. Among the treatments, the plants under PFD performed better in recording higher value of physiological parameters under stress and recovered quickly. The variety, CO7 was found to perform well under all stages of stress followed by TMV 7, TMVGn 13 and COGn 4 with respect to physiological parameters and yield.
Evaluation of Subsequent Heat Treatment Routes for Near-β Forged TA15 Ti-Alloy

TA15 Ti-alloy is widely used to form key load-bearing components in the aerospace field, where excellent service performance is needed. Near-β forging technology provides an attractive way to form these complicated Ti-alloy components but subsequent heat treatment has a great impact on the final microstructure and mechanical properties. Therefore evaluation and determination of the heat treatment route is of particular significance. In this paper, for the near-β forged TA15 alloy, the formation and evolution of microstructures under different subsequent heat treatment routes (annealing, solution and aging, toughening and strengthening) were studied and the cooling mode after forging was also considered. Then, the type and characteristics of the obtained microstructures were discussed through quantitative metallographic analysis. The corresponding mechanical properties (tensile, impact toughness, and fracture toughness) and effects of microstructural characteristics were investigated. Finally, for a required microstructure and performance a reasonable heat treatment route was recommended. The work is of importance for the application and development of near-β forging technology.
A Scalable Peer-to-Peer Presence Directory

Instant Messaging (IM) has emerged as a popular communication service over the Internet. One of the themes of IM systems is to provide a presence directory that carries information on user’s presence or absence to his/her friends. In this paper, we present new presence directory architecture and give a comparison of existing presence directories. We first introduce the distributed buddy-list search problem. We then present P2Dir, a distributed peer-to-peer presence directory protocol to address this problem. For each newly arriving user, the protocol is used to search for network presence of his/her buddies and also to notify them on his/her presence. P2Dir organizes directory servers into a 2-hop P2P overlay for efficient buddy searching. Moreover, P2Dir leverages the breadth-first search algorithm and a onehop caching strategy to achieve small constant search latency on average. We measure the performance of our P2Dir system, in terms of search cost and search satisfaction, where search cost is defined as total number of messages incurred among the directories upon the arrival of a user, and search satisfaction is defined as the time it takes to search for the newly arriving user’s buddy list and to notify presence of the newly arriving user to his/her buddies. We evaluate the performance of our P2Dir system in terms of search cost and search satisfaction through simulations, and compare it with a mesh-based presence protocol. The results show that our P2Dir achieves performance gains in search cost without sacrificing search satisfaction.