bluuebunny/crossref_metadata_2025_split huggingface dataset:
Aversive operant conditioning alters the phototactic orientation of the marbled crayfish
Authors: Okada Shione , Hirano Natsumi , Abe Toshiki , Nagayama Toshiki 
Published: February 2021

ABSTRACTAversive learning was applied to affect the phototactic behaviour of the marbled crayfish. Animals initially showed negative phototaxis to white light and positive taxis to blue light. Using an aversive learning paradigm, we investigated the plasticity of innate behaviour following operant conditioning. The initial rate of choosing a blue-lit exit was analysed by a dual choice experiment between blue-lit and white-lit exits in pre-test conditions. During training, electrical shocks were applied to the animals when they oriented to the blue-lit exit. Memory tests were given to analyse the orientation rate to the blue-lit exit in trials 1 and 24 h after training and these rates were compared with the pre-test. In general, animals avoided the blue-lit exit in the memory tests. When training was carried out three times, the long-term memory was retained for at least 48 h, although a single bout of training was also enough to form a long-term memory. Cooling animals at 4°C or injection of cycloheximide immediately after training altered the formation of long-term memory, but had no effect on short-term memory formation. Administration of the adenylate cyclase inhibitor SQ22536, the PKA inhibitor H89 or the CREB inhibitor KG-501 immediately after training also blocked the formation of long-term memory, but had no effect on short-term memory formation. Thus, our pharmacological behavioural analyses showed that new protein synthesis was necessary to form long-term memories and that the cAMP/PKA/CREB pathway is the main signal cascade for long-term memory formation in the marbled crayfish.
The Variance Learning Curve
Authors: Bavafa Hessam , Jónasson Jónas Oddur 
Published: February 2021

The expansive learning curve literature in operations management has established how various facets of prior experience improve average performance. In this paper, we explore how increased cumulative experience affects performance variability or consistency. We use a two-stage estimation method of a heteroskedastic learning curve model to examine the relationship between experience and performance variability among paramedics at the London Ambulance Service. We find that, for paramedics with lower experience, an increase in experience of 500 jobs reduces the variance of task completion time by 8.7%, in addition to improving average completion times by 2.7%. Similar to prior results on the average learning curve, we find a diminishing impact of additional experience on the variance learning curve. We provide an evidence base for how to model the learning benefits of cumulative experience on performance in service systems. Our findings imply that the benefits of learning are substantially underestimated if the consistency effect is ignored. Specifically, our estimates indicate that queue lengths (or wait times) might be overestimated by as much as 4% by ignoring the impact of the variance learning curve in service systems. Furthermore, our results suggest that previously established drivers of productivity should be revisited to examine how they affect consistency, in addition to average performance. This paper was accepted by Charles Corbett, operations management.
The Calendar Effects of the Idiosyncratic Volatility Puzzle: A Tale of Two Days?
Authors: Cao Jie , Chordia Tarun , Zhan Xintong 
Published: February 2021

The idiosyncratic volatility (IVOL) anomaly exhibits strong calendar effects. The negative relation between IVOL and the next-month return obtains mainly in the third week of the month. The IVOL-return relation is generally negative on Mondays and positive on Fridays. However, the positive impact is absent on the third Friday because of selling pressure from stocks delivered at option expiration. This imbalance between the negative and positive returns during the third week of the month has a large impact on the IVOL-return relation. Removing the third Friday and subsequent Monday return reduces the monthly IVOL effect by at least 40%. This paper was accepted by Karl Diether, finance.
Direct Seeding of Basmati Rice through Improved Drills: Potential and Constraints in Pakistani Farm Settings
Authors: Cheema Muhammad Jehanzeb Masud , Nauman Muhammad Hafiz , Ghafoor Abdul , Farooque Aitazaz Ahsan , Haydar Zeeshan , Ashraf Muhammad Umair , Awais Muhammad 
Published: February 2021

Abstract.In Pakistan, rice is an important cash crop and is cultivated over 2.75 mha, generally as traditionally transplanted rice (TTPR). High labor costs and water requirements, time intensiveness, low plant populations, and increased methane emissions are problems associated with TTPR. Alternatively, direct seeded rice (DSR) is now being adopted by rice growers for saving of labor cost (1-2 compared to 50-60 person-days/ha for TTPR), for time and water saving (10% to 30%), and most importantly for achieving the optimal plant population. Technical issues in machine design, and direct seeding, lack of farmers’ awareness about the technology, and social issues are the major hurdles in wide scale adoption of this effective intervention. To identify and address these issues, a testing and calibration activity was conducted during 2017 in the eight major basmati rice producing districts of Punjab, Pakistan. Twenty-one DSR drills (model 2017) being used in the field were tested to determine efficiency and farmers’ perceptions of the technology were noted. Plant germination percentage and vegetation vigor were also measured. The drawbacks in design, manufacturing, and assembling were identified in the DSR drills and modifications were made in the new model to improve efficiency. Fifty-three randomly selected modified DSR drills (model 2018) were calibrated in 2018 before the start of the rice-sowing season. In 2017 the study showed large variability in the row-to-row distance, seed rate and distances of individual drills, and resulting seed germination ranged from 20% to 90% sown at different sites. In 2018, the standard deviation (SD) of seed rate was improved from SD = 19.7 to 6.6 g/40 rev/tine while SD of row-to-row distance was reduced from 0.81 to 0.61 cm as compared to 2017 drill. The plant vigor measured in terms of the Normalized Difference Vegetation Index (NDVI) showed a good relationship with the plant population (R2 = 0.66) except at a few locations where weeds dominated. Important social issues identified were farmer’s lack of interest in preparing the land, precision land leveling, seed treatment, timely inputs, and farmer’s traditional thinking. However, farmers were motivated to consider adopting the DSR technology by demonstration plots established in 2017 by the Nuclear Institute for Agriculture &amp; Biology (NIAB) and the Rice Research Institute (RRI), Kala Shah Kaku. Increased DSR machine sales in 2018 indicate the technology is being more widely adopted. Keywords: Direct seeded rice drills, Normalized Difference Vegetation Index (NDVI), Plant population, Precision planting, Traditionally transplanted rice.
An Automatic Detector for Fungal Spores in Microscopic Images Based on Deep Learning
Authors: Zhang Ying , Li Jiangtao , Tang Fang , Zhang Haiyang , Cui Zhaojun , Zhou Huiling 
Published: February 2021

HighlightsA fungal spore dataset with microscopic images was established.A fungal spore detector, FSNet, based on deep learning was proposed to automatically recognize and count fungal spores in microscopic images.A framework based on a CNN for feature extraction was designed to enrich feature maps.A loss was formulated to decrease the number of missed detections due to clustered spores.Abstract. The most common cause of spoiled grain in storage is the growth of fungi on the grain. In China, the level of fungal infection is indicated by the quantity and the categories of fungal spores in grain samples. In most Chinese grain depots, the recognition and counting of fungal spores in grain samples are conducted with microscopes, which are mainly operated manually by professionals. This method is time-consuming, laborious and error-prone. In this article, a fungal spore detector, named FSNet, was proposed to automatically recognize and count fungal spores in microscopic images. To enrich the features in feature maps, a multi-layer fusion structure based on convolutional neural network for feature extraction was designed using deep, intermediate and shallow layers. Moreover, the detection performance of FSNet was further improved by a designed loss for clustered spores, an anchor optimization and region sampling strategy. Our method achieved 91.6% mean average precision [intersection-over-union (IoU) &gt; 0.6]. The experimental results indicated that our method was capable of recognizing and counting fungal spores in microscopic images, and it is very effective for the early detection of fungal infection. Keywords: Fungal spore detection, Deep learning, Microscopic images.
Growth Characteristics of Summer Cover Crop Grasses and their Relation to Soil Aggregate Stability and Wind Erosion Control in Arid Southwest
Authors: Darapuneni Murali K. , Idowu Omololu J. , Sarihan Bilgi , DuBois David , Grover Kulbhushan , Sanogo Soum , Djaman Koffi , Lauriault Leonard , Omer Mohammed , Dodla Syam 
Published: February 2021

HighlightsFour summer cover crops under two irrigation regimes were tested for soil wind erosion control.Soil aggregate stability and wind erosion losses were improved with plant cover in the peak summer.Sorghum sudan is a prominent summer species for wind erosion control in the arid southwest. Abstract. Cover crops can have significant impacts on minimizing soil erosion by wind, which is a common problem in the arid southwest. A study was conducted at NMSU Leyendecker Plant Science Center, Las Cruces, New Mexico, to evaluate the impacts of selected summer cover crops on soil loss during wind erosion events. Four summer grass species [Japanese millet (Echinochloa esculenta), pearl millet (Pennisetum glaucum), brown top millet (Urochloa ramosa (L.) Nguyen), and sorghum sudangrass (Sorghum bicolor × S. bicolor var. Sudanese)] were randomly assigned to four blocks under two irrigation regimes (full-irrigation and deficit-irrigation). Results showed significant effect of grasses on horizontal soil flux compared to control under both irrigation regimes. When comparing the grasses, sorghum sudan grass performed better than the other tested summer cover crops for soil surface protection from wind erosion with its higher ground coverage, higher plant density, taller plant height and higher amount of biomass, while brown top millet was least effective in terms of plant and erosion control characteristics (P=0.05). Pearl millet and Japanese millet performed better than brown top millet, but was as effective as sorghum sudan as barriers against the wind erosion. Therefore, sorghum sudan is a prominent cover crop for summer in the arid zones of desert southwest. Producers of this region can be significantly benefited from the current research recommendations about cover crops choices for summer season. Keywords: Arid climates, Cover cropping, Summer grasses, Wind erosion control.
Granular Fertilizer Mass Flow Measurement and Vehicle Experiments Based on Microwave Doppler Method
Authors: Huang Jiayun , Yang Liwei , Zhang Jiqin , Hu Hao 
Published: February 2021

HighlightsA microwave Doppler-based fertilizer mass flow measurement system was developed.The measurement system was applied in vehicle experiments.Power spectra of mass flow signal and vibration signal were obtained and analyzed.Interference suppression algorithm based on CA-CFAR reduced vibration interference.Fertilizer mass flow measurement accuracy was improved by interference suppression.Abstract. The fertilizer mass flow measurement system is typically installed on the fertilizer applicator. However, vehicle vibrations are inevitable during field operation of fertilizing equipment, and can interfere with mass flow signals, thereby affecting the accuracy of mass flow measurements. In this article, a mass flow measurement system based on the microwave Doppler method was introduced. The dominant frequency (fdot) related to fertilizer velocity and the power spectral density (PSD) related to fertilizer concentration were obtained from the Doppler signal of the granular fertilizer processed using fast Fourier transform. The product of fdot and PSD is defined as the sensor output value (SOV). The relationship between SOV, PSD, and fertilizer mass flow (FMF) was studied under vehicle conditions. The linear regression models of 22-8-10 (MOP) high-nitrogen poly-?-glutamic acid fertilizer were established using the least squares method, and the vibration signals were measured. Based on analysis of the power spectra of the mass flow and vibration signals, an interference suppression algorithm based on cell average constant false alarm rate (CA-CFAR) was presented to reduce vibration interference. To verify the performance of the novel vibration interference reduction algorithm, vehicle experiments were conducted at different tractor velocities. The results show that mass flow measurements ranged from 1300 to 3000 g min-1. It was found that using only the PSD related to concentration for flow measurement gave better measurement accuracy compared with SOV, and relative errors of the system were within 8.1%. Correlation between the PSD and FMF improved with interference suppression algorithm based on CA-CFAR. The determination coefficient increased from 0.01 to 0.92, 0.97 to 0.99, and 0.96 to 0.98 at three different tractor velocities, respectively. From the results, it was evident that the algorithm effectively eliminated vibration interference signals in vehicle conditions. In future work, the conditions of the soil will be considered and the performance of the mass flow measurement system will be tested in the field. Keywords: Fertilizer mass flow, Microwave Doppler radar, Tractor vibration, Vehicle experiment, Vibration interference suppression.
Detection and Test of Rind-Pith Adhesive Strength of Corn Stalks
Authors: Huang Wanyuan , Gong Yuanjuan , Bai Xuewei 
Published: February 2021

HighlightsA detection clamp for the rind-pith adhesive strength of corn stalks based on peeling method was designed.A rind-pith adhesive strength detection method was proposed taking average peeling strength as the test index.The characteristics of rind-pith adhesive strength were analyzed, and a mathematical model between average peeling strength and influencing factors was established.Abstract. Rind-pith separation of corn stalks is one of the effective measures for realizing high-value utilization of stalks. Therefore, it is necessary to study rind-pith adhesive strength of stalks and its influencing factors to determine effective separation methods. In this study, a peeling method was put forward and single factor and multi-factor tests were carried out to explore the rind-pith adhesive strength. The analysis of single factor tests showed that sampling location, moisture content, and peeling speed were all significant on the average rind-pith peeling strength and the Fp = 25.70 &gt; F0.05 (4, 20) = 2.87, Fm = 112.46 &gt; F0.05 (4, 20) = 2.87 and Fs = 231.21 &gt; F0.05 (6, 28) = 2.45. The mathematical model between average peeling strength and influencing factors was established through multi-factor tests. The model was analyzed and optimized, and the significance sequence of influencing factors is sampling location &gt; moisture content &gt; peeling speed, and the effect of interaction between moisture content and sampling location was significant (P&lt;0.05). It can be concluded that the rind-pith peeling strengths of internode sections among 1st-7th internodes of corn stalks were 360.09-450.01 N/m, which are smaller and more favorable for mechanical separation for stalks with moisture content of 15%-20% and at peeling speed of 30-40 mm/min. The results of this study may provide a theoretical reference for the modeling of corn stalks and the subsequent simulation and optimization of rind-pith separation machines. Keywords: Average peeling strength, Adhesive strength, Corn stalks, Rind-pith Separation.
Systematic Water-Saving Management for Strawberry in Basic Greenhouses Based on the Internet of Things
Authors: Li Qun , Cao Bing , Wang Xing , Wu Jiu Jiang , Wang You Ke 
Published: February 2021

A new application of the internet of things in a low-cost greenhouse with no networked intelligent control equipment.The systematic water-saving management focused over the whole growth stage of crops, and it can effectively increase yield and quality.Replace some chemical fertilizer with fully-decomposed organic fertilizer and new types of fertilizer to reduce negative impact on soil and the environment.Regarding pesticide usage, we advocate prevention first and treatment second.Improve systematic water-saving management with regard decreases in crop yield and quality.Abstract. A basic greenhouse is an inexpensive type of greenhouse, which lacks networked intelligent control equipment; it is currently the most common type of greenhouse used in China. To manage planting activities intelligently and improve water use efficiency in these greenhouses, an intelligent planting management platform for strawberry based on the internet of things (IoT) is developed. On the platform, human-computer interaction occurs through the WeChat app on a mobile phone so that manual control of the strawberry environment in the greenhouse can be conducted. In this study, we add a user module in the perception layer of the IoT to obtain the information and manually control the environment in a basic greenhouse. The network layer uses narrowband IoT wireless transmission technology based on 4G. The application layer is designed with a systematic water-saving management knowledge base for strawberry. The systematic water-saving management feature includes seven parts: strawberry variety selection, planting seedlings, flower and fruit thinning, environmental control, disease and pest prevention and treatment, fertilizer management, and water-saving irrigation. Through the human–computer interaction platform, growers can receive decision-making options, planting management evaluation, query information retrieval, and regular relevant planting information. The application results of the platform showed the following: compared with management experience of growers, the water use efficiency of yield (WUEy) increased by 128.55%, the water use efficiency of production value (WUEpy) increased by 226.31%; the amount of chemical fertilizer decreased by 40%, the amount of pesticide decreased by 61.67%, and the cost of pesticide decreased by 32.48%; thus a decrease in the use of both fertilizer and pesticide was achieved. This study can directly provide technical support for strawberry intelligent management in basic greenhouses, and can also be used as a basic platform intelligent management systems for other crops grown in basic greenhouses. Keywords: Basic greenhouse, Intelligent agriculture, Internet of things, Sensor network , Systematic water-saving management, Water-use efficiency.
Dual-modal imaging with non-contact photoacoustic microscopy and fluorescence microscopy
Authors: Zhou Jiasheng , Wang Wei , Jing Lili , Chen Sung-Liang 
Published: February 2021

Simultaneous imaging of complementary absorption and fluorescence contrasts with high spatial resolution is useful for biomedical studies. However, conventional dual-modal photoacoustic (PA) and fluorescence imaging systems require the use of acoustic coupling media due to the contact operation of PA imaging, which causes issues and complicates the procedure in certain applications such as cell imaging and ophthalmic imaging. We present a novel dual-modal imaging system which combines non-contact PA microscopy (PAM) based on PA remote sensing and fluorescence microscopy (FLM) into one platform. The system enables high lateral resolution of 2 and 2.7 µm for PAM and FLM modes, respectively. In vivo imaging of a zebrafish larva injected with a rhodamine B solution is demonstrated, with PAM visualizing the pigment and FLM revealing the injected rhodamine B.
Improved exclusive breastfeeding rates in preterm infants after a neonatal nurse training program focusing on six breastfeeding-supportive clinical practices
Authors: Maastrup Ragnhild , Rom Ane L. , Walloee Sisse , Sandfeld Helle B. , Kronborg Hanne 
Published: February 2021

BackgroundEarly breast milk expression, prolonged skin-to-skin contact, rooming-in, use of test-weighing and minimizing use of pacifiers are positively associated with exclusive breastfeeding of preterm infants, whereas use of nipple shields is negatively associated.AimTo test whether a training program for neonatal nurses with a focus on these six breastfeeding-supportive clinical practices affects the rate of preterm infants exclusively breastfed at discharge to home, the postmenstrual age at establishment of exclusive breastfeeding, and maternal self-reported use of the practice in the neonatal intensive care unit, the.MethodsA quasi-experimental multi-centre intervention study from 2016–2019 including a control group of 420 preterm mother-infant dyads, an intervention with a training program for neonatal nurses and implementation of weekly breastfeeding meetings for neonatal nurses, and an intervention group of 494 preterm mother-infant dyads.ResultsSignificantly more preterm infants in the intervention group were exclusively breastfed at discharge to home (66.6%) than in the control group (58.1%) p = 0.008. There was no significant difference in postmenstrual age at establishment of exclusive breastfeeding between control and intervention group (37.5 vs.37.8 weeks, p = 0.073). Compared to the control group the number of infants continuing daily skin-to-skin contact after incubator care increased (83.2% vs. 88.3%, p = 0.035), infants using a nipple shield decreased (61.8% vs. 54.2%, p = 0.029), and the number of mothers initiating breast milk expression before six hours post-partum increased (32.6% vs. 42.4%, p = 0.007). There was a significant correlation between percentage of neonatal nurses participating in the breastfeeding training program and changes in exclusive breastfeeding rates (Pearson Correlation 0.638, p = 0.047).ConclusionExclusive breastfeeding rates in preterm infants and maternal self-reported use of breastfeeding-supportive practices increased by training neonatal nurses in the six clinical practices. It is important to include all nurses in the breastfeeding training program to ensure positive effect on exclusive breastfeeding rates.