bluuebunny/crossref_metadata_2025_split huggingface dataset:
Non-cell autonomous control of precerebellar neuron migration by Slit and Robo proteins
Authors: Dominici Chloé , Rappeneau Quentin , Zelina Pavol , Fouquet Stéphane , Chédotal Alain 
Published: December 2017

ABSTRACT
During development, precerebellar neurons migrate tangentially from the dorsal hindbrain to the floor plate. Their axons cross it but their cell bodies stop their ventral migration upon reaching the midline. It has previously been shown that Slit chemorepellents and their receptors, Robo1 and Robo2, might control the migration of precerebellar neurons in a repulsive manner. Here, we have used a conditional knockout strategy in mice to test this hypothesis. We show that the targeted inactivation of the expression of Robo1 and Robo2 receptors in precerebellar neurons does not perturb their migration and that they still stop at the midline. The selective ablation of the expression of all three Slit proteins in floor-plate cells has no effect on pontine neurons and only induces the migration of a small subset of inferior olivary neurons across the floor plate. Likewise, we show that the expression of Slit proteins in the facial nucleus is dispensable for pontine neuron migration. Together, these results show that Robo1 and Robo2 receptors act non-cell autonomously in migrating precerebellar neurons and that floor-plate signals, other than Slit proteins, must exist to prevent midline crossing.
A Method for Attributing Patient‐Level Metrics to Rotating Providers in an Inpatient Setting
Authors: Herzke Carrie A. , Michtalik Henry J. , Durkin Nowella , Finkelstein Joseph , Deutschendorf Amy , Miller Jason , Leung Curtis , Brotman Daniel J. 
Published: December 2017

BACKGROUNDIndividual provider performance drives group metrics, and increasingly, individual providers are held accountable for these metrics. However, appropriate attribution can be challenging, particularly when multiple providers care for a single patient.OBJECTIVEWe sought to develop and operationalize individual provider scorecards that fairly attribute patient‐level metrics, such as length of stay and patient satisfaction, to individual hospitalists involved in each patient's care.DESIGNUsing patients cared for by hospitalists from July 2010 through June 2014, we linked billing data across each hospitalization to assign “ownership” of patient care based on the type, timing, and number of charges associated with each hospitalization (referred to as “provider day weighted”). These metrics were presented to providers via a dashboard that was updated quarterly with their performance (relative to their peers). For the purposes of this article, we compared the method we used to the traditional method of attribution, in which an entire hospitalization is attributed to 1 provider, based on the attending of record as labeled in the administrative data.RESULTSProvider performance in the 2 methods was concordant 56% to 75% of the time for top half versus bottom half performance (which would be expected to occur by chance 50% of the time). While provider percentile differences between the 2 methods were modest for most providers, there were some providers for whom the methods yielded dramatically different results for 1 or more metrics.CONCLUSIONWe found potentially meaningful discrepancies in how well providers scored (relative to their peers) based on the method used for attribution. We demonstrate that it is possible to generate meaningful provider‐level metrics from administrative data by using billing data even when multiple providers care for 1 patient over the course of a hospitalization.
Design and Testing of Novel Hydraulic Pump/Motors to Improve the Efficiency of Agricultural Equipment
Authors: Breidi Farid , Garrity Jordan , Lumkes John 
Published: December 2017

Abstract. Hydraulic systems are prevalent in agricultural machinery and equipment and can be found transmitting power for vehicle drive wheels, powering attachments, and controlling motion (booms, steering, load height, etc.). Agricultural applications of fluid power have advanced in terms of capability and efficiency, but opportunities remain for significant improvements in efficiency, noise reduction, and reliability. The average system-level hydraulic efficiency of current mobile agricultural machines is only 21.1%. Because nearly all hydraulic systems use pumps to convert engine power to fluid power, improving the efficiency of the pumps (and motors when used as actuators) significantly impacts the system efficiency. This work examines the impact of using more efficient digital pump/motors to improve the overall efficiency of agricultural equipment, such as tractors, harvesters, planters, fertilizers, sprayers, and attachments. Maintaining higher pump/motor efficiency throughout the operating range is the central principal for the energy savings. Currently used variable-displacement pumps have low efficiencies at low displacement levels due to constant losses that do not scale with the power produced. Digital pump/motors minimize these inefficiencies because energy losses scale more closely with the power produced. Experimental results indicate an average efficiency of 85% when operating at 20% to 100% displacement. This efficiency is 15% to 20% higher on average than with current variable-displacement axial piston pumps. This study demonstrates that achieving this improvement in the efficiency of the pump/motors used in tractors and harvesters alone would conservatively save $61.7 million worth of energy annually for end users in the U.S. agricultural sector. Keywords: Agricultural equipment, Digital hydraulics, Efficiency improvement, Hydraulic pump/motor.
Vehicle Impact Analysis Using Vehicle Tracking Systems on Military Lands
Authors: Svendsen Niels  G. , Koch Daniel    J. , Gertner George   Z. , Howard Heidi   R. , Ayers Paul   D. 
Published: December 2017

Abstract. Although the impacts of military vehicles on the landscape have been studied extensively, research has not looked at full-scale multi-vehicle events to estimate land disturbance. Currently, the military extensively uses live and simulated training to prepare troops for combat, and these systems can provide data for accurate determination of the land disturbance patterns resulting from training activities. This article examines a full-scale multi-vehicle event and determines the total moving-vehicle disturbance (event-based impact). It provides a methodology for using in-field simulation and training systems to generate information on vehicle mobility impacts. This article illustrates how such information can be used to determine changes in the Universal Soil Loss Equation (USLE) C factor for areas of disturbed land. For land managers, the major benefit of this approach is rapid identification of locations that are intensely used and therefore subject to land degradation. Additionally, this approach provides a means to readily quantify those impacts as related to vegetation removal and erosion potential. To illustrate this approach, 84 military vehicles were monitored at Orchard Training Area, Idaho, in August 2008, and 592,132 data points were collected to measure distance traveled, average velocity, and turning radius at 1 s intervals. The data were then processed and mapped to ascertain the impacts on vegetation and potential changes in the C factor. Results indicated that vehicles spent 15.9% of the time and 5.9% of the distance traveled off-road. The vegetation removal rate ranged from 0% to 48%, and the cumulative area of vegetation removed was 156,424.9 m2. Future work in this area should focus on developing vehicle impact models for forecasting land disturbance regimes. Keywords: Environmental impact, Impact, Modeling, Off-road vehicles, Soil erosion modeling, Vehicle, Vehicle tracking.
Analysis of Parameter Sensitivity and Identifiability of Root Zone Water Quality Model (RZWQM) for Dryland Sugarbeet Modeling
Authors: Anar Mohammad J. , Lin Zhulu , Ma Liwang , Bartling Patricia N. S. , Teboh Jasper M. , Ostlie Michael 
Published: December 2017

Abstract. Sugarbeet is being considered as one of the most viable feedstock alternatives to corn for biofuel production since herbicide-resistant energy beets were deregulated by the USDA in 2012. Growing sugarbeets for biofuel production may have significant impacts on soil health and water quality in the north-central regions of the U.S., where 50% of the nation’s total sugarbeets were produced in 2015. Almost all the current sugarbeet models simulate only plant growth and yield but have no capability to simulate the effects of sugarbeet production on soil and water quality. The Root Zone Water Quality Model (RZWQM) is a widely used model that simulates crop yield, water flow, and transport of salts and nitrogen in crop fields. RZWQM is currently linked to 23 specific crop models in the Decision Support System for Agrotechnology Transfer (DSSAT) version 4.0, not including a sugarbeet model. In this study, the Crop and Environment REsource Synthesis (CERES) in RZWQM was adapted for sugarbeet simulation to model the soil and water quality impact of sugarbeet for biofuel production. The Beet model was then evaluated against dryland sugarbeet production at the Carrington Research and Extension Station (North Dakota) in 2014 and 2015. The PEST (Parameter ESTimation) tool in RZWQM was used for parameter estimation and sensitivity and identifiability analysis. The model did reasonably well in both 2014 (d-statistic = 0.709 to 0.992; rRMSE = 0.066 to 1.211) and 2015 (d-statistic = 0.733 to 0.990; rRMSE = 0.043 to 0.930) in terms of simulating leaf area index, top weight, root weight, soil water content, and soil nitrates. Under dry conditions, the most sensitive soil parameters were soil bulk densities and saturated hydraulic conductivities in different layers. Identifiability analysis also showed that three to five model parameters may be identifiable by calibration datasets. RZWQM enhanced with a sugarbeet module and its parameter analysis can be used for water use optimization under dryland conditions. Keywords: Biofuels, CERES, DSSAT, RZWQM, Sugarbeet.
Implementing Standardized Reference Evapotranspiration and Dual Crop Coefficient Approach in the DSSAT Cropping System Model
Authors: DeJonge Kendall C. , Thorp Kelly  R. 
Published: December 2017

Abstract. While methods for estimating reference evapotranspiration (ETo or ETr) and subsequent crop ET (ETc) via crop coefficient (Kc) and dual crop coefficient (Kcb, Ke) methods have been standardized since 2005 and 1998, respectively, the current version of the DSSAT cropping system model (CSM) has not been updated to fully implement these methods. In this study, two major enhancements to the model’s ET routines were evaluated: (1) addition of the ASCE Standardized Reference Evapotranspiration Equation so that both grass and alfalfa reference ET were properly calculated using the most recent reference ET standard and (2) addition of the FAO-56 dual crop coefficient approach to determine potential ET, which combined an evaporative coefficient (Ke) for potential evaporation with a dynamic basal crop coefficient (Kcb) for potential transpiration as a function of simulated leaf area index. Previously published data sets for maize in Colorado (five years) and cotton in Arizona (seven years) were used to parameterize the model. Simulations of ETo were compared to outputs from Ref-ET software, and simulated crop coefficients were contrasted among three crop coefficient methods: the current approach (Kcs), a previously published adjustment to the model’s Kc equation (Kcd), and a new dual Kc approach that follows FAO-56 explicitly (Kcb). Results showed that crop coefficient simulations with the new ETo-Kcb method better mimicked theoretical behavior, including spikes in the soil evaporation coefficient (Ke) due to irrigation and rainfall events and basal crop coefficient response as associated with simulated crop growth. Simulated ETc and yield with the new ETo-Kcb method were up to 4% higher and 28% lower for cotton and up to 13% higher and 26% lower for maize, respectively, than that with the current ETo-Kcs method, indicating that the seasonal ETc effects were minimal while yield effects were more substantial. Use of FAO-56 concepts and current ET standards in DSSAT-CSM demonstrated a well-accepted ET benchmark to guide assessment of other ET methods in the model and made the model much more conceptually relevant to irrigation and ET specialists. Keywords: Cotton, DSSAT, Evaporation, Evapotranspiration, FAO-56, Maize, Reference crop ET, Standardization, Transpiration.
ARIMA Modeling of Animal Zone Temperature in Weaned Piglet Buildings: Design of the Model
Authors: Besteiro Roberto , Ortega Juan A. , Arango Tamara , Rodriguez Manuel R. , Fernandez Maria D. , Ortega Juan A. 
Published: December 2017

Abstract. Predictive models provide an efficient tool for improving environmental control in livestock buildings. In this article, a robust and accurate ARIMA model for forecasting temperature inside a building for weaned piglets in the range 6 to 20 kg live weight was built. The candidate models presented in this article predict 10 min values during a complete production cycle, which makes them suitable as predictive models for improving control strategies. The accuracy of the base model, which used outdoor temperature as a predictor variable, can be improved by appropriately replacing the outliers in the time series. Because accuracy increases with the increase in the number of predictor variables, the model that used four variables (temperature at the air outlet, area of the air outlet through the fan, volume of air extracted, and animal live weight) provided the best results, with a maximum absolute error of 0.840°C, a root mean square error of 0.204°C, and random residuals according to the Ljung-Box statistic. This model used only the values of the last 20 min for the forecast, which suggests low thermal inertia in the animal zone. In addition, the model includes predictor variables that are representative of outdoor conditions, operation of the systems, and animal health status. Keywords: ARIMA, Forecast, Model, Piglet, Temperature.
Choice Between Fluorescent and Poultry-Specific LED Lights by Pullets and Laying Hens
Authors: Liu Kai , Xin Hongwei , Chai Lilong 
Published: December 2017

Abstract. Light plays an important role in poultry development, production performance, health, and well-being. Light technology continues to advance, and accordingly new light products are finding applications in poultry operations. However, research concerning responses of young and adult laying hens to light sources is relatively lacking. This study assessed the choice between a Dim-to-Red poultry-specific light-emitting diode (LED) light (PS-LED, correlated color temperature or CCT = 2000K) and a warm-white fluorescent light (FL, CCT = 2700K) by pullets and laying hens (W-36 breed) via preference test. Birds with different prior lighting experiences were evaluated for their light choice, including (1) pullets (14 to 16 weeks of age or WOA) reared under incandescent light (designated as PINC), (2) layers (44 to 50 WOA) under PS-LED (LLED) throughout the pullet and laying phases, and (3) layers under FL (LFL) throughout the pullet and laying phases. Each bird category consisted of 12 replicates, three birds per replicate. Each replicate involved a 6-day preference test, during which the birds could move freely between two interconnected compartments that contained PS-LED and FL, respectively. Time spent and feed intake by the birds under each light were measured and then analyzed with generalized linear mixed models. Results showed that regardless of prior lighting experience, birds in all cases showed stronger choice for FL (p = 0.001 to 0.030), as evidenced by higher proportions of time spent under it. Specifically, the proportion of time spent (mean ±SEM) under FL versus PS-LED was 58.0% ±2.9% vs. 42.0% ±2.9% for PINC, 53.7% ±1.6% vs. 46.3% ±1.6% for LLED, and 54.2% ±1.2% vs. 45.8% ±1.2% for LFL. However, the proportions of daily feed intake occurring under FL and PS-LED were comparable in all cases (p = 0.419 to 0.749). The study thus reveals that prior lighting experience of the pullets or layers did not affect their choice of FL versus PS-LED. While the birds exhibited a somewhat stronger choice for FL, this tendency did not translate into differences in the proportion of feed use under each light type. Keywords: Behavior and welfare, Computer vision, Poultry Lighting, Preference assessment.
Bio-Crude Production via Hydrothermal Liquefaction of Enteromorpha prolifera: Operating Condition Optimization and High-Resolution FT-ICR Mass Spectral Analysis
Authors: Zhang Jixiang , Qian Cheng , Jiang Baohui 
Published: December 2017

Abstract. is one of the main species causing green tide. In this study, hydrothermal liquefaction of E. was carried out, and the operating conditions were optimized using response surface methodology. The results indicated that hydrothermal liquefaction at 295°C with 14% solids content produced the highest bio-oil yield of 18.4%. The higher heating value was 31.9 to 34.2 MJ kg-1 and almost monotonically increased with increasing reaction temperature. The energy recovery, carbon recovery, and nitrogen recovery of bio-crude were mainly dependent on yield rather than elemental composition as the investigated variables changed. The chemical composition of bio-crude was characterized by Fourier transform ion cyclotron resonance mass spectrometry. The acidic O-containing compounds were mainly O2 class compounds, namely hexadecanoic acid and octadecanoic acid. The basic N-containing compounds were mainly nitrogenous heterocyclic compounds with carbon numbers of 20 to 40 and high degrees of unsaturation. Keywords: Bio-crude, FT-ICR MS, Hydrothermal liquefaction, Response surface methodology.
Development and Preliminary Evaluation of a New Bin Filler for Apple Harvesting and In-Field Sorting Machine
Authors: Zhang Zhao , Pothula Anand Kumar , Lu Renfu 
Published: December 2017

Abstract. The bin filler, which is used for filling the fruit container or bin with apples coming from the sorting system, plays a critical role in the self-propelled apple harvest and in-field sorting (HIS) machine that is being developed in our laboratory. Two major technical challenges in developing the bin filler are limited space in the HIS machine and high throughput. A literature review showed that despite many different types of bin fillers currently available for in-field use, none of them is suitable for the HIS machine because of their large size, use of the bin rotating design concept, and high unit cost. Effort has thus been made on the development of new bin filling technology for use with the HIS machine. The new bin filler mainly consists of a mechanical system with a pinwheel design and an automatic control system. A key innovation in the mechanical system is the use of two foam rollers to catch freely falling apples, which has greatly simplified the bin filler design and also made the system compact and lower in cost. The control system is mainly composed of an onboard Arduino microcontroller and three sensors (one infrared sensor and two Hall effect sensors) to monitor and measure the status of apples filling the bin as well as the rotational speed of the pinwheel. A program was developed for the Arduino microcontroller to record and process the data from the sensors in real-time to achieve automatic control of the bin filling. Laboratory tests with ‘Gala’ apples demonstrated that 97% of apples that had been handled by the new bin filler were rated Extra Fancy grade, and its performance exceeded the industry’s requirement for bruising damage to apples. Keywords: Apples, Automatic control, Bin filling, Bruising, Harvest, Sensors, Sorting and grading.
Influence of a Young Pinus radiata Canopy on Aerial Spray Drift
Authors: Richardson Brian , Strand Tara M. , Thistle Harold , Hiscox April , Kimberley Mark O. , Schou Wayne C. 
Published: December 2017

Abstract. An experiment was undertaken to test the hypothesis that AGDISP, a mechanistic model that simulates the landing position of droplets aerially released for pesticide application, overestimates downwind airborne spray concentrations by not accounting for the turbulence generated within the canopy sublayer. AGDISP is used by pesticide regulators in many parts of the world to quantify exposure from aerial pesticide spraying as part of an assessment of risks to public health and the environment. Using a novel design, airborne spray drift was measured in a 3.2 m high radiata pine plantation, 65 m downwind from the aerial spray flight line, using a small circular sampling array. The spray sampling array consisted of a central 10 m high mast plus a set of 16 secondary masts distributed evenly around a circle with a radius of 5 m from the central mast. All spray applications were made with a Bell Jet Ranger using a spray mix of water plus a fluorescent tracer and a droplet spectrum with a volume median diameter of 101 µm. A single treatment comprised six passes along the flight line, and there were 28 replications. Airborne spray was sampled with both rotorods and artificial foliage placed at four heights on the central mast, ranging from approximately half canopy height to 3 times canopy height. The secondary towers sampled airborne spray using the same collectors placed at just above canopy height and at half canopy height. Other measurements included leaf area distribution, prevailing meteorological conditions, and turbulence using sonic anemometers. Backscatter LiDAR was used in an attempt to quantify the height and density of the spray cloud in the vicinity of the central mast. Rotorod and artificial foliage deposition values were highly correlated, giving confidence in the sampling approach. Neither wind speed nor release height had a significant effect on airborne spray flux in the 0 to 10 m zone, but results were complicated by a spurious negative correlation between wind speed and spray release height. The lack of dependence of deposition on wind speed in this experiment is surprising but is explained both by the variance in the data as well as the physics of small droplet movement in the atmosphere. At the individual sample level, measurements of airborne spray using either rotorods or artificial foliage were poorly correlated with AGDISP predictions. However, when data were averaged across replications, there was a very strong correlation between measurements and AGDISP data, even though in absolute terms, and as hypothesized, AGDISP significantly overpredicted the quantity of airborne spray. As indicated from a comparison with measured deposition, the backscatter LiDAR appeared effective in describing the spray cloud profile, and it suggested a total spray cloud profile that was more complex than the AGDISP model prediction. Keywords: Aerial application, AGDISP, Canopy deposition, Pesticides, Spray drift.