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In this paper, we present an automatic motion planner for agricultural robots that allows us to set up a robot to follow rows without having to explicitly enter waypoints. In most cases, when robots are used to cover large agricultural areas, they will need waypoints as inputs, either as premeasured coordinates in an outdoor environment, or as positions in a map in an indoor environment. This can be a tedious process as several hundreds or even thousands of waypoints will be needed for large farms. In particular, we find that in unstructured environments such as the ones found on farms, the need for waypoints increases. In this paper, we present an approach that enables robots to safely traverse not only between straight rows but also through curved rows without the need for any predetermined waypoints. Most types of infrastructure found in agriculture, such as polytunnels, are built on uneven terrain, thus containing a mix of straight and curved plant rows, for which traditional methods of row following will fail. Different from traditional approaches of row following that only consider straight‐line‐of‐sight rows, our approach identifies the rows on each side with the goal of staying in the middle of the rows, even if the rows are not straight. Waypoints are only needed on the very extreme of the rows, and these will be automatically generated by the system. With our approach, the robot can just be placed in the corner of the field and will then determine the trajectory without further input from the user. We thus obtain an approach that can reduce the installation time from potentially hours to just a matter of minutes. The final autonomous system is low cost and efficient for various tasks that requires moving between plant rows inside a polytunnel. Several experiments were performed and the robot demonstrates 1.4% position drift over 21 m of navigation path. [ABSTRACT FROM AUTHOR]

The growing world population calls for more efficient and sustainable farming technologies. Automating agricultural tasks has great potential to improve farming technologies. A key requirement for full automation is the ability of agricultural vehicles to accurately navigate entire fields without damaging value crops. One important precondition for autonomous navigation is localization, that is, the ability of a vehicle to accurately estimate its pose relative to the crops. A majority of localization approaches detect crop rows to track the heading and lateral offset of the vehicle. This is sufficient to guide the vehicle along crop rows while driving inside the field. However, switching between rows requires a longitudinal pose estimate to determine when to turn at the end of the field. Additionally, at the end of the field sensor data contains less crop row structure and more noise from wild growing vegetation. This can lead to false‐positive crop row detections. In this paper, we present a localization approach that goes beyond state‐of‐the‐art crop row following algorithms by providing robust pose estimates not only inside the field but also at the end of the field. The underlying concept of our approach is to estimate the vehicle pose relative to a global navigation satellite system (GNSS)‐referenced map of crop rows. This allows us to fuse crop row detections with GNSS signals to obtain a pose estimate with the accuracy comparable to a row following approach in the heading and lateral offset, while at the same time maintaining at least GNSS accuracy along the row. Employing a GNSS‐referenced map of crop rows poses several challenges. To relate the detected crop rows to those in the map, we propose a data association strategy that finds correspondences between two sets of lines, that is, crop rows. Furthermore, we improve the GNSS‐based longitudinal pose estimate by detecting the end of the field from vegetation data. Additionally, we introduce a novel method to determine false‐positive crop row detections to increase the overall robustness in particular in challenging scenarios at the end of the field. Extensive real‐world experiments on three different types of crops demonstrate that our localization approach is well suited for fully autonomous navigation in entire fields. [ABSTRACT FROM AUTHOR]

Two sorghum [Sorghum bicolor (L.) Moench] backcross‐nested association mapping (BC‐NAM) populations (Reg. no. MP‐5, NSL 546724 MAP) have been developed, composed of 30 families totaling 2189 BC1F4 lines using an elite maintainer (B) or restorer (R) line as the recurrent parent. The families were derived from unadapted founder lines that were backcrossed to BTx623 and/or RTx436 based on the fertility reaction score and phylogenetic analysis of the founder lines. These unadapted founder lines were selected based on agronomic fitness, breeder desirability, and genetic diversity and represent a range of races and working groups. The 30 families were developed from 27 founder parents—three of the founder parents were backcrossed to both recurrent parents to provide a genetic relationship across all 30 families. Each family consists of 45–100 BC1F4 lines selected for standard agronomic fitness, and each population was genotyped using genotype‐by‐sequencing. To identify families that possess (or segregate for) traits of interest, 13 lines from each population were randomly selected and phenotyped for a range of agronomic and stress tolerance traits. These BC‐NAM populations, which are adapted to US production regions and possess novel genetic diversity, have application in genetic research as a mapping resource for traits of interest and for sorghum breeding programs to diversify R and B line parental heterotic pools. Core Ideas: Sorghum improvements are based on access to genetic diversity within elite, adapted germplasm.Access to diversity in sorghum genetics is limited by maturity and plant height requirements.The development of backcrossed‐derived nested association populations provides both a genetic and breeding resource.These populations are available for both research and breeding purposes. [ABSTRACT FROM AUTHOR]

Aims: Understanding the suite of environmental changes impacting migration and disentangling these from the dependencies between migratory stages is fundamental to understanding the drivers and mechanisms causing spatial shifts to migratory bird distributions. In this review, our objectives are to: (i) provide evidence of spatial change at all migratory stages, (ii) identify the key mechanisms driving change, (iii) discuss how anthropogenic change influences migratory patterns, (iv) highlight interdependencies between migratory stages and (v) offer a framework for understanding migratory pattern changes. Location: Migratory land birds globally. Methods: We defined a literature search to find examples of spatial changes in avian migrations and their underlying mechanisms. From the top 1000 search results, sorted by relevance, we retained 81 papers published between 1991 and 2020. Results: Spatial shifts in migratory bird distributions occur throughout the annual cycle, but patterns vary across taxa and migratory stages. Since avian migrants occupy multiple sites across the annual cycle, environmental change has particularly complex repercussions for their distributions. Multiple environmental changes can affect distributions at each migratory stage due to fitness asymmetries between migratory strategies and individuals responding flexibly to environmental changes within and across generations. Spatial changes at one stage (e.g. breeding) can also trigger further indirect spatial changes at other stages (e.g. stopovers) due to dependencies between stages. Conclusions: To understand the drivers and mechanisms underpinning spatial changes, comprehensive year‐round distributional data are crucial for observing change across multiple migratory stages and disentangling competing drivers. Biologging technology could elucidate the mechanisms causing changes to individual‐level strategies and uncover fitness asymmetries between strategies. Ultimately, gaining a clearer understanding of spatial changes will aid in predicting distributional responses to anthropogenic change in migratory birds. This is paramount for mitigating the effects of anthropogenic change and assessing future population viability within this vulnerable and extensive taxonomic group. [ABSTRACT FROM AUTHOR]

The diurnal cycle is often poorly reproduced in global climate model (GCM) simulations, particularly in terms of rainfall frequency and amplitude. While improvements in the regional climate model (RCM) with bias‐corrected boundaries have been reported in previous studies, they assumed that diurnal patterns are simulated correctly by the GCM, potentially leading to inaccuracies in the maximum rainfall timing and magnitude within the RCM domain. Here we provide the first examination of improvements to the diurnal cycle, within a RCM domain, achieved through the use of sophisticated bias‐corrected lateral and lower boundary conditions. Results show that the RCMs with bias‐corrected boundaries generally present improvement in capturing both rainfall timing and magnitude, particularly in northern Australia, where a strong diurnal pattern in rainfall is prevalent. We show that correcting systematic sub‐daily multivariate bias in RCM boundaries improves the diurnal rainfall cycle, which is particularly important in regions where short‐term intense precipitation occurs. Plain Language Summary: Global climate models have limitations in simulating precipitation characteristics at sub‐daily time scales, leading to significant bias in capturing rainfall timing and magnitude in regional climate model (RCM) simulations that use global climate model data as input. Previous studies have applied various bias correction approaches to the boundary conditions of RCMs, but they often assume that GCM sub‐daily rainfall patterns are simulated correctly, leading to a significant bias in maximum rainfall timing and magnitude within the domain. This study investigates the consequences of multivariate sub‐daily bias correction on the boundary conditions in order to evaluate the model performance for short‐term precipitation events. The results show that RCMs with bias‐corrected boundary conditions exhibit improvement across Australia, especially in northern Australia, which regularly experiences intense sub‐daily rainfall. Key Points: Regional climate model (RCM) with uncorrected boundaries poorly represented 3‐hourly precipitation with only 20%∼30% agreements compared to observationsSub‐daily bias correction of RCM lateral boundaries improves the sub‐daily representation of fields entering the RCM domainSub‐daily multivariate bias correction on the boundaries resulted in additional improvements, especially in northern Australia [ABSTRACT FROM AUTHOR]

Water plays a central role in several socioeconomic and environmental nexuses. Faced with various anthropogenic pressures that act as water scarcity drivers and knowing that the unavailability of water can be a limiting factor for economic development, there is an urgent need for the design and evaluation of economic instruments that help in the management of water resources. This article presents a proposal and assessment for a Pigouvian water charge instrument. The instrument suggests imposing a charge based on the amount of water consumed, targeting the agriculture, livestock, forest extraction, and aquaculture sectors. The revenue generated from this charge could be utilized to fund reforestation initiatives and support government expenditures, thereby creating both environmental and economic advantages. Based on a calibrated static computable general equilibrium economic model for the Brazilian Mantiqueira region, it was possible to estimate that a water charge policy at a rate of R$ 0.10/m3 (US$ 0.026/m3) could lead to an increase in the Brazilian GDP in the benchmark year by US$ 10.7 million. Economic benefits could also be verified at the regional level, especially in those areas where there are water‐intensive economic activities. On the environmental side, the water charge could incentivize actions capable of recovering approximately 80 km2 of natural areas. Key Points: Mantiqueira region houses a singular forest biome and provides fresh water to densely populated regions in BrazilPigouvian water charge instrument can achieve economic and environmental benefitsInterregional computable general equilibrium economic models have the flexibility to evaluate ex‐ante water resources management policies [ABSTRACT FROM AUTHOR]

Most bacteria use the tubulin homolog FtsZ to organize their cell division. FtsZ polymers initially assemble into mobile complexes that circle around a ring‐like structure at the cell midpoint, followed by the recruitment of other proteins that will constrict the cytoplasmic membrane and synthesize septal peptidoglycan to divide the cell. Despite the need for FtsZ polymers to associate with the membrane, FtsZ lacks intrinsic membrane binding ability. Consequently, FtsZ polymers have evolved to interact with the membrane through adaptor proteins that both bind FtsZ and the membrane. Here, we discuss recent progress in understanding the functions of these FtsZ membrane tethers. Some, such as FtsA and SepF, are widely conserved and assemble into varied oligomeric structures bound to the membrane through an amphipathic helix. Other less‐conserved proteins, such as EzrA and ZipA, have transmembrane domains, make extended structures, and seem to bind to FtsZ through two separate interactions. This review emphasizes that most FtsZs use multiple membrane tethers with overlapping functions, which not only attach FtsZ polymers to the membrane but also organize them in specific higher‐order structures that can optimize cell division activity. We discuss gaps in our knowledge of these concepts and how future studies can address them. [ABSTRACT FROM AUTHOR]

Maize monoculture is one of the major restrictions limiting maize productivity in Western Ethiopia. Although the inclusion of legumes in cropping systems is an essential approach for the sustainable management of farming systems and for reducing the nitrogen (N) fertilizer requirement for maize production in the long term, the effects of soybean on the sustainability of maize productivity and soil fertility are unclear in Ethiopia. Continuous cropping of maize has led to extensive degradation of soil and a decrease in crop productivity in Western Ethiopia. Thus, the study was conducted to compare the long‐term impact of soybean on the sustainability of the production system in soybean–maize rotation and to monitor soil fertility dynamics in soybean–maize rotational systems. Nine different soybean–maize rotation treatments were laid out in Randomized Complete Block Design (RCBD) with three replications. The study results showed that soybean–maize rotation gave a relatively steady yield compared to the maize mono‐cropping system. Soybean–maize rotation improves the productivity of component crops in cropping systems. The highest maize grain yield was recorded from soybean–maize rotation with fertilizer application for the two components (RS + M+) and soybean–maize rotation without fertilizer application for the soybean component (RS‐M+), respectively. Soybean grain yield was significantly correlated with OC (%), OM (%), and TN (%), whereas maize yield was adversely correlated with soil parameters, except soil pH. Overall, the knowledge we can contribute to the readers from this study is that soybean–maize rotation plays an important role in achieving sustainable agriculture by increasing soil fertility and achieving stable soybean and maize yields and soybean should be inoculated with Rhizobium strain year after year continuously. Thus, it can be concluded that soybean–maize rotation with fertilizer applications (RS + M+) for two components can be used in maize belt areas of Western Ethiopia. [ABSTRACT FROM AUTHOR]

The combination of enzymes and chemically responsive smart materials presents considerable opportunities in anti‐fouling, sensing or medicine. Among stimuli‐responsive polymers, liquid crystal elastomers (LCEs) have emerged as a leading actuator platform due to their inherent programmability, realizing large shape transformations upon exposure to stimuli. Herein, three different hydrolytic enzymes are immobilized into acid‐responsive LCEs, which impart the LCEs with sensitivity to three distinctive classes of biomolecules: lipids, carbohydrates, and peptides. Dye‐doped biocatalytic LCEs readily switch their color and shape upon exposure to the appropriate substrate. Twisted nematic patterning and direct ink writing are used to showcase the versatility of shape changes the enzyme‐containing LCEs may undergo. Multiplexed responsiveness is also demonstrated using a connected array of 3D printed disks, each containing a different enzyme, highlighting the excellent chemical selectivity of the LCEs. This work presents a novel platform of versatile bioresponsive color‐switchable actuators that may have application in a wide range of fields. [ABSTRACT FROM AUTHOR]

Craving, induced by substance‐related cues, contributes to continued substance use and relapse. Therefore, regulation of craving (ROC) is important for treatment success. Distraction involves disengaging from craving‐inducing cues; whereas, reappraisal requires engaging with potential risks of substance use. Given this difference in elaboration, we addressed the question whether reappraisal entails lasting advantages over distraction in successful ROC. To elucidate how this is implemented neurally, we examined the late positive potential (LPP) as an electrocortical indicator of motivated attention to cues. N = 62 smokers viewed smoking‐related pictures and indicated the degree of craving each picture induced. While viewing the pictures, EEG was recorded, and the participants focused on the long‐term negative (LATER) or short‐term positive (NOW) consequences of smoking or performed an arithmetic task to distract themselves from processing the pictures (DISTRACT). After a break, all pictures were presented again without regulation instruction (re‐exposure). Results revealed that LATER and DISTRACT achieved similar degrees of immediate ROC success, but only LATER had a sustained effect during re‐exposure. In contrast, LPP amplitudes were more prominently reduced during DISTRACT than LATER, and there was no difference in LPP amplitudes during re‐exposure. These findings imply that it may be beneficial to engage with the risks of drug use (reappraisal) rather than avoiding triggers of craving (distraction). However, these effects do not seem to be mediated by lasting changes in cue‐related motivated attention (LPP). [ABSTRACT FROM AUTHOR]

The increasing availability of satellite imagery has supported a rapid expansion in forward‐looking studies seeking to track and predict how climate change will influence wild population dynamics. However, these data can also be used in retrospect to provide additional context for historical data in the absence of contemporaneous environmental measurements. We used 167 Landsat‐5 Thematic Mapper (TM) images spanning 13 years to identify environmental drivers of fitness and population size in a well‐characterized population of banner‐tailed kangaroo rats (Dipodomys spectabilis) in the southwestern United States. We found evidence of two decoupled processes that may be driving population dynamics in opposing directions over distinct time frames. Specifically, increasing mean surface temperature corresponded to increased individual fitness, where fitness is defined as the number of offspring produced by a single individual. This result contrasts with our findings for population size, where increasing surface temperature led to decreased numbers of active mounds. These relationships between surface temperature and (i) individual fitness and (ii) population size would not have been identified in the absence of remotely sensed data, indicating that such information can be used to test existing hypotheses and generate new ecological predictions regarding fitness at multiple spatial scales and degrees of sampling effort. To our knowledge, this study is the first to directly link remotely sensed environmental data to individual fitness in a nearly exhaustively sampled population, opening a new avenue for incorporating remote sensing data into eco‐evolutionary studies. [ABSTRACT FROM AUTHOR]

Computational thinking is the process of solving a problem in a way that can be readily automated by a computer. Decomposition, pattern recognition, abstraction, and algorithm design are four major components of computational thinking. We conducted an experiment to study the effectiveness of smartphone apps for teaching computational thinking to 7‐year‐old children. The first experimental group was taught computational thinking using four apps, one for each component. The second experimental group was taught computational thinking using the chalk and board approach. The control group was not imparted any lesson in computational thinking. The intervention period lasted 8 weeks and was followed by a posttest and a retention test conducted after another 2 weeks. The children showed interest in learning computational thinking and could solve problems that are inspired by real‐world engineering problems during the intervention period. They could analyze and debug (77%) their own work. The performance of the children in the two experiment groups was significantly better than those in the control group in the posttest and the retention test (F = 26.470, p <.05). This means that 7‐year‐old children can learn computational thinking from suitable mediums. No significant difference was observed in the performance of the children in the posttest and the retention test (p >.05), denoting that children can retain the concepts of computational thinking. Including computational thinking lessons at the K‐12 level can encourage children to enroll in engineering programs in the future. We recommend standardization of content and development of age‐specific apps for teaching computational thinking. [ABSTRACT FROM AUTHOR]

Phosphate detection has garnered widespread attention due to its biological and environmental impact. Among several optical techniques, time‐resolved fluorescence (TRF) provides a sensitive way for the discrimination of analytes in a complex mixture as it exhibits less interference from the background, therefore providing a high signal‐to‐noise ratio. The sensitization of rare earth metal (REM) ions by semiconducting quantum dots (QDs) can help the former overcome the drawback of low absorption coefficient, therefore allowing exploitation of the additional advantage of the REM, namely the long‐excited state lifetime. Here, we have developed a TRF‐based sensor array consisting of three QDs, i.e. MoS2, WS2 and MoSe2 as energy sensitizers for Tb3+ ions. Different QDs possess variable energy transfer abilities for Tb3+ ions. Therefore, they can be used to discriminate phosphates. It was also observed that CrO42− can competitively bind to Tb3+ and further enhance the efficiency of the sensor array so that it could discriminate six different phosphates at 200 μM concentration in aqueous as well as serum medium with a detection limit of 10 μM in aqueous medium. Therefore, the sensitivity of the TRF‐based sensor array is rarely compromised in a complex mixture, which is advantageous over a fluorescence‐based sensor array. [ABSTRACT FROM AUTHOR]

This study examines the intergenerational transmission of technology in historical China by constructing a genealogy dataset of the Huang family from 1400 to 1800. The family specialised in woodblock carving for book production, and their names were documented in these volumes, enabling measurement of technological output. Analysing 902 individuals across 16 generations reveals that carving skills were primarily transmitted from fathers to sons, with little influence from other family members or external artisans. Moreover, the production of books by the Huang family experienced a decline in the early 17th century, potentially attributed to weather shocks and decreased demand for books. [ABSTRACT FROM AUTHOR]

The automation of agricultural machines is an irreversible trend considering the demand for improved productivity and lack of labor in handling agricultural tasks. Unstructured working environments and weather often inhibit a seemingly simple task from being fully autonomously performed. In this context, we propose a remote driving system (RDS) to aid agricultural machines designed to operate autonomously. Particularly, we modify a commercial speed sprayer for orchard environments into a robotic speed sprayer to evaluate the proposed RDS's usability and test three sensor configurations in terms of human performance. Furthermore, we propose a confidence error ellipse‐based task performance measure to evaluate human performance. In addition, we present field experimental results describing how the sensor configurations affect human performance. We find that a combination of a semiautonomous line tracking device and a wide‐angle camera is the most effective for spraying. Finally, we discuss how to improve the proposed RDS in terms of usability and obtain a more accurate measure of human performance. [ABSTRACT FROM AUTHOR]

Ecological weed management (EWM) considers that not all non‐crop plants cause harm, and that non‐harmful species 'aliae plantae' should be retained to provide multiple positive benefits. Only plants causing 'significant harm' are defined as weeds and should be controlled. However, this is difficult to achieve with current herbicide and mechanical weeding technologies. Robotic weeders may be able to facilitate EWM. Four Levels of robotic weeders are defined: Level 1 are row followers; Level 2 identify individual crop plants and weed around them; Level 3 individually identify all plants and individually kill all non‐crop plants; Level 4 weeders individually distinguish crop plants, aliae plantae, and weeds and only kill the weeds, thus facilitating EWM. Currently only Levels 1–3 robotic weeders exist. The aim of proposing Level 4 robotic weeders is to highlight, particularly to roboticists, that the end goal of robotic weeding should not be crop monocultures, but biodiverse fields through EWM. It is envisaged that Level 4 robotic weeders would not just operate in vegetable crops, which are the current focus of Level 3 weeders, but in all crops, such as fruit trees, where they could, for example, control weeds in living mulches. It is therefore considered essential that weed scientists and roboticists collaborate to ensure that robotic weeders achieve EWM, not monocultures. If this vision can be realised, it could usher in a revolution in weed management. [ABSTRACT FROM AUTHOR]

SUMMARY: The clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR‐related nuclease 9 (Cas9) system enables precise, simple editing of genes in many animals and plants. However, this system has not been applied to rose (Rosa hybrida) due to the genomic complexity and lack of an efficient transformation technology for this plant. Here, we established a platform for screening single‐guide RNAs (sgRNAs) with high editing efficiency for CRISPR/Cas9‐mediated gene editing in rose using suspension cells. We used the Arabidopsis thaliana U6‐29 promoter, which showed high activity for driving sgRNA expression, to modify the CRISPR/Cas9 system. We used our highly efficient optimized CRISPR/Cas9 system to successfully edit RhEIN2, encoding an indispensable component of the ethylene signaling pathway, resulting in ethylene insensitivity in rose. Our optimized CRISPR/Cas9 system provides a powerful toolbox for functional genomics, molecular breeding, and synthetic biology in rose. [ABSTRACT FROM AUTHOR]

Precise segmentation of infant brain magnetic resonance (MR) images into gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) are essential for studying neuroanatomical hallmarks of early brain development. However, for 6‐month‐old infants, the extremely low‐intensity contrast caused by inherent myelination hinders accurate tissue segmentation. Existing convolutional neural networks (CNNs) based segmentation models for this task generally employ single‐scale symmetric convolutions, which are inefficient for encoding the isointense tissue boundaries in baby brain images. Here, we propose a 3D mixed‐scale asymmetric convolutional segmentation network (3D‐MASNet) framework for brain MR images of 6‐month‐old infants. We replaced the traditional convolutional layer of an existing to‐be‐trained network with a 3D mixed‐scale convolution block consisting of asymmetric kernels (MixACB) during the training phase and then equivalently converted it into the original network. Five canonical CNN segmentation models were evaluated using both T1‐ and T2‐weighted images of 23 6‐month‐old infants from iSeg‐2019 datasets, which contained manual labels as ground truth. MixACB significantly enhanced the average accuracy of all five models and obtained the most considerable improvement in the fully convolutional network model (CC‐3D‐FCN) and the highest performance in the Dense U‐Net model. This approach further obtained Dice coefficient accuracies of 0.931, 0.912, and 0.961 in GM, WM, and CSF, respectively, ranking first among 30 teams on the validation dataset of the iSeg‐2019 Grand Challenge. Thus, the proposed 3D‐MASNet can improve the accuracy of existing CNNs‐based segmentation models as a plug‐and‐play solution that offers a promising technique for future infant brain MRI studies. [ABSTRACT FROM AUTHOR]

In many practices, scientists are particularly interested in detecting which of the predictors are truly associated with a multivariate response. It is more accurate to model multiple responses as one vector rather than separating each component one by one. This is particularly true for complex traits having multiple correlated components. A Bayesian multivariate variable selection (BMVS) approach is proposed to select important predictors influencing the multivariate response from a candidate pool with ultrahigh dimension. By applying the sample‐size‐dependent spike and slab priors, the BMVS approach satisfies the strong selection consistency property under certain conditions, which represents the advantages of BMVS over other existing Bayesian multivariate regression‐based approaches. The proposed approach considers the covariance structure of multiple responses without assuming independence and integrates the estimation of covariance‐related parameters together with all regression parameters into one framework through a fast‐updating Markov chain Monte Carlo (MCMC) procedure. It is demonstrated through simulations that the BMVS approach outperforms some other relevant frequentist and Bayesian approaches. The proposed BMVS approach possesses a flexibility of wide applications, including genome‐wide association studies with multiple correlated phenotypes and a large scale of genetic variants and/or environmental variables, as demonstrated in the real data analyses section. The computer code and test data of the proposed method are available as an R package. [ABSTRACT FROM AUTHOR]

The Muslim countries have a lower democracy level on average than the other countries. Yet, this cross‐country comparison is not sufficient to blame Islam for the democracy deficit. This issue is related to the numerous fixed characteristics that differ across the countries and that also have an effect on democracy. When the differences are not considered, the estimates mix the effect of the fixed characteristics with the effect that Islam has on democracy. We show this issue for a large set of countries covering the period 1950–2015. In cross‐country comparisons, we find a negative link between the share of Muslims in the total population and common measures for democracy. Yet, when the fixed characteristics are considered, the negative link vanishes. Thus, the lower democracy level has to be due to a fixed characteristic; it cannot be associated to (time‐varying) Muslim shares. Numerous empirical specifications support this finding. We also measure Islam by the average per‐day length of fasting during the month of Ramadan exploring whether the intensity of practicing the core teachings of Islam has a negative effect on democracy. Again, the evidence rejects a negative effect of Islam on democracy. If anything, the effect is positive. The findings are important for social coexistence. [ABSTRACT FROM AUTHOR]

The farming industry constantly seeks the automation of different processes involved in agricultural production, such as sowing, harvesting and weed control. The use of mobile autonomous robots to perform those tasks is of great interest. Arable lands present hard challenges for Simultaneous Localization and Mapping (SLAM) systems, key for mobile robotics, given the visual difficulty due to the highly repetitive scene and the crop leaves movement caused by the wind. In recent years, several Visual‐Inertial Odometry (VIO) and SLAM systems have been developed. They have proved to be robust and capable of achieving high accuracy in indoor and outdoor urban environments. However, they were not properly assessed in agricultural fields. In this study we assess the most relevant state‐of‐the‐art VIO systems in terms of accuracy and processing time on arable lands to better understand how they behave on these environments. In particular, the evaluation is carried out on a collection of sensor data recorded by our wheeled robot in a soybean field, which was publicly released as the Rosario data set. The evaluation shows that the highly repetitive appearance of the environment, the strong vibration produced by the rough terrain and the movement of the leaves caused by the wind, expose the limitations of the current state‐of‐the‐art VIO and SLAM systems. We analyze the systems failures and highlight the observed drawbacks, including initialization failures, tracking loss and sensitivity to Inertial Measurement Unit saturation. Finally, we conclude that even though certain systems like ORB‐SLAM3 and stereo Multi‐State Constraint Kalman Filter show good results with respect to others, more improvements should be done to make them reliable in agricultural fields for certain applications such as soil tillage of crop rows and pesticide spraying. [ABSTRACT FROM AUTHOR]

Simultaneous Localization and Mapping (SLAM) is a process to use multiple sensors to position an unmanned mobile vehicle without previous knowledge of the environment, and meanwhile construct a map of this environment for the further applications. Over the past three decades, SLAM has been intensively researched and widely applied in mobile robot control and unmanned vehicle navigation. SLAM technology has demonstrated a great potential in autonomously navigating the mobile robot and simultaneously reconstructing the three‐dimensional (3D) information of surrounding environment. With the vigorous driving of sensor technology and 3D reconstruction algorithms, many attempts have been conducted to propose novel systems and algorithms combined with different sensors to solve the SLAM problem. Notably, SLAM has been extended to various aspects of agriculture involved with autonomous navigation, 3D mapping, field monitoring, and intelligent spraying. This paper focuses on the recent developments and applications of SLAM, particularly in complex and unstructured agricultural environment. A detailed summary of the developments of SLAM is given from three main fundamental types: light detection and ranging SLAM, Visual SLAM, and Sensor Fusion SLAM, and we also discuss the applications and prospects of SLAM technology in agricultural mapping, agricultural navigation, and precise automatic agriculture. Particular attention has been paid to the SLAM sensors, systems, and algorithms applied in agricultural tasks. Additionally, the challenges and future trends of SLAM are reported. [ABSTRACT FROM AUTHOR]

Accurate robot localization relative to orchard row centerlines is essential for autonomous guidance where satellite signals are often obstructed by foliage. Existing sensor‐based approaches rely on various features extracted from images and point clouds. However, any selected features are not available consistently, because the visual and geometrical characteristics of orchard rows change drastically when tree types, growth stages, canopy management practices, seasons, and weather conditions change. In this study, we introduce a novel localization method that does not rely on features; instead, it relies on the concept of a row‐sensing template, which is the expected observation of a 3D sensor traveling in an orchard row, when the sensor is anywhere on the centerline and perfectly aligned with it. First, the template is built using a few measurements, provided that the sensor's true pose with respect to the centerline is available. Then, during navigation, the best pose estimate (and its confidence) is estimated by maximizing the match between the template and the sensed point cloud using particle‐filtering. The method can adapt to various orchards and conditions by rebuilding the template. Experiments were performed in a vineyard, and in an orchard in different seasons. Results showed that the lateral mean absolute error (MAE) was less than 3.6% of the row width, and the heading MAE was less than 1.72°. Localization was robust, as errors did not increase when less than 75% of measurement points were missing. The results indicate that template‐based localization can provide a generic approach for accurate and robust localization in real‐world orchards. [ABSTRACT FROM AUTHOR]

Increasing global population, climate change, and shortage of labor pose significant challenges for meeting the global food and fiber demand, and agricultural robots offer a promising solution to these challenges. This paper presents a new robotic system architecture and the resulting modular agricultural robotic system (MARS) that is an autonomous, multi‐purpose, and affordable robotic platform for in‐field plant high throughput phenotyping and precision farming. There are five essential hardware modules (wheel module, connection module, robot controller, robot frame, and power module) and three optional hardware modules (actuation module, sensing module, and smart attachment). Various combinations of the hardware modules can create different robot configurations for specific agricultural tasks. The software was designed using the Robot Operating System (ROS) with three modules: control module, navigation module, and vision module. A robot localization method using dual Global Navigation Satellite System antennas was developed. Two line‐following algorithms were implemented as the local planner for the ROS navigation stack. Based on the MARS design concept, two MARS designs were implemented: a low‐cost, lightweight robotic system named MARS mini and a heavy‐duty robot named MARS X. The autonomous navigation of both MARS X and mini was evaluated at different traveling speeds and payload levels, confirming satisfactory performances. The MARS X was further tested for its performance and navigation accuracy in a crop field, achieving a high accuracy over a 537 m long path with only 15% of the path having an error larger than 0.05 m. The MARS mini and MARS X were shown to be useful for plant phenotyping in two field tests. The modular design makes the robots easily adaptable to different agricultural tasks and the low‐cost feature makes it affordable for researchers and growers. [ABSTRACT FROM AUTHOR]

This paper presents a vision‐based, subspace optimal controller aiming to improve the row transition performance of an agricultural robot in a strawberry field. The contribution of this paper is twofold. First, only RGB cameras, instead of complicated sensor suites, are used for cross‐bed navigation and row alignment. Second, a real‐time adaptive dynamic programming‐based algorithm is designed for an optimal row transition. The conditions for row alignment are derived in an augmented pixel coordinate frame. Based on these conditions, a simple motion rule is utilized to reduce the search space dimension so that the proposed algorithm can be implemented in real‐time. Additionally, the inverse‐dynamics policy of the algorithm is updated using vision feedback at each control step to adapt to uncertainties. The proposed controller is tested in both simulations and field experiments. In a simulation comparison, the minimum‐time solution achieved using the proposed algorithm is 44.7 s, which is very close to that of a benchmark algorithm (44.4 s). However, the CPU time required by the proposed algorithm is only 4.3% of time needed by the benchmark algorithm. Twenty field experiments using the presented design were all successful in row transition, with a mean final alignment error of 0.5 cm. [ABSTRACT FROM AUTHOR]

Panicle structure trait is one of the most important factors affecting yield. Exploring novel regulation genes and clarifying the genetic mechanism have an important meaning to the improvement of rice yield. A recombinant inbred line (RIL) derived from the cross between 'Longdao5' (Japonica) and 'Zhongyouzao8' (Indica) was used to identify quantitative trait loci (QTLs) for grain number and panicle structure traits under multiple environments. Seventy‐seven QTLs were detected, 21 or 20 of which were stably and reliably detected under two or more than three ecological environments, respectively. These QTLs of the grain number and panicle structure (qGNPS) clustered on chromosomes 1, 4, 5 and 10 with pleiotropic genetic overlap effect and stable expression, and then, the major QTL clusters qGNPS4.1 and qGNPS10 were unreported. The novel stable expression major QTL cluster qGNPS4.1 control with grain number and secondary branch number was detected on chromosome 4 under multiple environments. Using the segregating RHL‐F2 and F2:3 population, we narrowed the location of qGNPS4.1 to a 214.94‐kb region. These results will lay the foundation for the major QTL clone and also will enrich the molecular marker‐assisted selection of grain number and panicle structure for molecular breeding in rice. [ABSTRACT FROM AUTHOR]

Pesticide spraying is one of the risky and very essential task in agriculture to protect plants from harmful organisms. Many farmers are used manual pesticide spraying devices that they carry these devices on their shoulders and spray on the entire plant. Due to this, harmful pesticide chemicals spread into the air and may enter into the body of farmers and farm workers through the breathing system and mostly affect their body parts even, so many farmers lost their life. For this serious problem, we present the best solution to perform this task without the intervention of man is to utilize a robotic system in an agriculture. This paper analyses the state‐of‐the‐art reviews in the development of autonomous pesticide spraying robots that are divided into four main categories; platform mobility and steering, localization and navigation control, sensing and target detection, and pesticide spraying arrangement. This paper also focused on the efficient methodology that can be used for future perspectives to enhance pesticide spraying operations in an agriculture. In this paper, to achieve target spraying operation, a suitable navigation control algorithm for platform movement and an efficient trajectory planning algorithm for shortest link movement are designed which covers the shortest distance to visit all targeted pests on the plant. This technique will help to reduce the overdose of toxic pesticides hence minimize the wastage of pesticides and also control its dangerous effects on the human being and on the environment. [ABSTRACT FROM AUTHOR]

The design changes to the kiwifruit harvester are demonstrated in a large-scale field trial involving over 12,000 individual kiwifruits. The authors introduced an autonomous robot tracking kiwi flower using computer vision techniques and spraying pollen with their novel sprayer. The last paper by Wu et al. proposes an intelligent weeding system that combines vision crop-weed classification with a spot spraying and mechanical weeding unit. [Extracted from the article]

Intercropping can improve yield and nitrogen use efficiency in organic vegetable production by pairing crops with complementary resource use. An intercrop field experiment was conducted to determine yield, root growth and nitrogen (N) dynamics using faba bean (Vicia faba L.) grown as a vegetable and pointed cabbage (Brassica oleracea var. capitata cv. conica). Both crops were grown in monocropping (MC) and intercropping systems (IC). Minirhizotrons were used to measure root growth. Yield of pointed cabbage per metre row was 28% higher under the IC system than under MC, whereas faba bean yield as fresh seeds did not differ. The land equivalent ratio was 1.06, showing that improved yield under IC resulted from efficient land resource use. Even though MC cabbage had the highest aboveground biomass, total N accumulation was higher under IC and MC faba bean systems. Both root frequency and intensity were greater under IC faba bean rows compared with MC faba bean because of the presence of cabbage roots in faba bean rows. Monocropped cabbage had the highest root intensity and the lowest amount of soil mineral N in the 0–1.5 m depth after harvest. Monocropped cabbage was efficient in assimilating N, whereas MC faba bean was efficient in exporting N as harvestable yield. The nitrogen use efficiency using the IC system (75%) was higher than growing faba bean (44%) and cabbage (65%) alone. Thus, faba bean as an intercrop in organic cabbage production systems improves land and N use efficiency by complementary root growth. [ABSTRACT FROM AUTHOR]

The merits of three climate smart agriculture (CSA) technologies implemented by farmers were assessed in Machinga district of Malawi with respect to their soil quality and maize yield effects. Data were collected from farms implementing the three CSA technologies, namely conservation agriculture (CA), maize–pigeonpea (Maize‐PP) intercrops and a local organic and inorganic soil amendment known as Mbeya fertilization (Mbeya‐fert), from 2018 to 2019. With respect to resilience and adaptation, particulate organic matter, soil organic carbon (SOC), N, P, K, Ca and Mg all significantly improved while bulk densities were lowered under the three CSA systems. Higher annual biomass inputs and improved water infiltration from the Maize‐PP intercrops were observed. With respect to productivity, CA and Mbeya‐fert improved maize yields by 51 and 19%, respectively, compared to conventional farmer practices. With regard to climate change mitigation, increases in measured SOC in the top 20 cm depth compared to the conventional farmer practices amounted to 6.5, 12 and 10.5 t C ha−1 for CA, Mbeya‐fert, and Maize‐PP intercrops, respectively, over a period of 2–6 years. This suggests higher potential for carbon sequestration from CSA technologies. Furthermore, use of drought tolerant varieties, timely weeding and optimum plant populations, increased productivity. Improved gross margins from CSA practices were also apparent. Thus, employing these CSA technologies could enable farmers to be more resilient, productive and adapt better to climate change shocks leading to improved food security and livelihoods. [ABSTRACT FROM AUTHOR]

We introduce a novel measure of performance of polymer composites based on physical parameters whose behavior depends on levels of dopant concentration used during their preparation. The performance measure is based on a joint analysis of measurements of the physical parameters exhibiting non‐trivial correlations that vary across different levels of dopant concentrations. In contrast to traditional multivariate analysis, we treat data from parameter measurements as being obtained from functional parameters, and develop the performance measure based on the joint average function of parameters that encodes the correlation structure. An optimal level of dopant concentration is then ascertained with respect to the performance measure. While the proposed measure is general enough to be applicable to any chosen physical parameters, we demonstrate its utility in the context of assessing performance using microstructural and nonlinear optical parameters. Computing of the measure and optimal dopant concentration are carried out using Monte Carlo sampling, which further facilitates uncertainty quantification. [ABSTRACT FROM AUTHOR]

I study the effect of progressive taxation on internal migration and welfare using a quantitative dynamic model of geographic mobility. The model, which is analytically tractable, predicts that a more progressive tax‐transfer scheme reduces internal migration rates. The magnitude of this relationship is consistent with reduced‐form evidence for OECD countries. The internal migration channel contributes to significantly lower optimal tax progressivity relative to the one‐location version of the economy. The optimal sequence of tax progressivity along the transition features a relatively high degree of tax progressivity early on, followed by a declining path of tax progressivity over time. [ABSTRACT FROM AUTHOR]

Management constraints in reduced tillage organic vegetable production may be alleviated by combining strip tillage (ST) with overwintering cereal–legume cover crop mixtures. Field studies in Michigan and New York over 6 site‐years evaluated the effects of preceding cover crops, including cereal rye (R; Secale cereale L.), hairy vetch (V; Vicia villosa Roth) and crimson clover (CC; Trifolium incarnatum), on N availability, weed management, and yields in ST organic cabbage (Brassica oleracea L. var. capitata). Cover crop treatments included R–legume mixtures (RV and RCC) planted under two spatial arrangements, standard full‐width mixed [‐M] vs. segregated strips [‐S] (legumes planted in‐row and R between‐row), and R and V monocultures. Cover crop aboveground biomass (5–10 Mg ha–1) and N content (>90 kg N ha–1) were not different among RV and RCC but the C/N of RCC was 58% greater than RV. Cabbage yields after RCC‐M were lower than RV‐M in five of six cases with yield reductions ranging from 22 to 41%. Spatial arrangement had no effect on cabbage yield after RV but improved yields after RCC from 23 to 39% in one, relatively dry, site‐year. Without N fertilizer, yields after RV and V were equivalent to or greater than R‐S with 134 kg N ha–1 in seven of nine and four of four cases, respectively. Legume species and spatial arrangement had little or no impact on the efficacy of in‐row mechanical cultivation, hand‐weeding time or weed biomass. Overall, N supplied from V and RV mixtures was an important driver of ST organic cabbage yields across different soil types and weather conditions. Core Ideas: Rye–crimson clover produced similar biomass to rye–vetch but supplied less N to cabbage.Nitrogen benefits of segregating cover crops were limited to rye–crimson clover in a dry year.Cover crop treatments had little to no effect on cultivation efficacy or hand‐weeding time.Cabbage yields were related to available N rather than weed competition in most site‐years.Vetch reduced fertilizer N required for ST cabbage across soil types and weather conditions. [ABSTRACT FROM AUTHOR]

Event‐related potentials (ERPs) derived from electroencephalography (EEG) have proven useful for understanding linguistic processes during language perception and production. Words are commonly produced in sequences, yet most ERP studies have used single‐word experimental designs. Single‐word designs reduce potential ERP overlap in word sequence production. However, word sequence production engages brain mechanisms in different ways than single word production. In particular, speech monitoring and planning mechanisms are more engaged than for single words since several words must be produced in a short period of time. This study evaluates the feasibility of recording ERP components in the context of word sequence production, and whether separate components could be isolated for each word. Scalp EEG data were acquired, while participants recited word sequences from memory at a regular pace, using a tongue‐twister paradigm. The results revealed fronto‐central error‐related negativity, previously associated with speech monitoring, which could be distinguished for each word. Its peak amplitude was sensitive to Cycle and Phonological Similarity. However, an effect of sequential production was also observable on baseline measures, indicating baseline shifts throughout the word sequence due to concurrent sustained medial‐frontal EEG activity. We also report a late left anterior negativity (LLAN), associated with verbal response planning and execution, onsetting around 100 ms before the first word in each cycle and sustained throughout the rest of the cycle. This work underlines the importance of considering the contribution of transient and sustained EEG activity on ERPs, and provides evidence that ERPs can be used to study sequential word production. Words are commonly produced in sentences, yet most ERP studies have used single‐word experimental designs. This study establishes the feasibility of recording ERP components in the context of word sequence production and underlines the importance of considering the contribution of transient and sustained EEG activity on ERPs while we speak. [ABSTRACT FROM AUTHOR]

The topology and chemical functionality of metal–organic frameworks (MOFs) make them promising candidates for membrane gas separation; however, few meet the criteria for industrial applications, that is, selectivity of >30 for CO2/CH4 and CO2/N2. This paper reports on a dense CAU‐10‐H MOF membrane that is exceptionally CO2‐selective (ideal selectivity of 42 for CO2/N2 and 95 for CO2/CH4). The proposed membrane also achieves the highest CO2 permeability (approximately 500 Barrer) among existing pure MOF membranes with CO2/CH4 selectivity exceeding 30. State‐of‐the‐art atomistic simulations provide valuable insights into the outstanding separation performance of CAU‐10‐H at the molecular level. Adsorbent–adsorbate Coulombic interactions are identified as a crucial factor in the design of CO2‐selective MOF membranes. [ABSTRACT FROM AUTHOR]

This article analyzes how state power and authority were established and critiqued through the performative, material, and sensory characteristics of Harare's Criminal Magistrates' Courts in Zimbabwe. Drawing on courtroom observations and interviews conducted with human rights lawyers and their clients between 2010 and 2018, this article shows how Zimbabwe's deteriorating political and economic situation after 2000 caused a decline of the material conditions in court. Lawyers and their clients played on this decline to emphasize how the state failed to display its authority. Simultaneously, these material conditions highlighted the ruling party's (ZANU‐PF) preoccupation with law's coercive rather than legitimating utility. A focus on material attributes, however, does not suffice in examining the ways in which court proceedings impose and challenge the authority of the law and of the state. The sensory dimensions of courtrooms also require attention. Within the courtroom, it was vital for actors to engage the visual, auditory, and—importantly—the olfactory reminders of the horrific conditions in police detention and prison. By doing so, lawyers and their clients reasserted and questioned not only the authority of law but also the control certain state actors exerted on and over the bodies and emotions of Zimbabwean citizens within legal spaces. [ABSTRACT FROM AUTHOR]

Cognitive training should not only improve performance of the trained task, but also untrained abilities. Exposure to novelty can improve subsequent memory performance, suggesting that novelty exposure might be a critical factor to promote the effects of cognitive training. Therefore, we combined a 4‐week working memory training with novelty exposure. Neuropsychological tests and MRI data were acquired before and after training to analyze behavior and changes in gray matter volume, myelination, and iron levels. In total, 83 healthy older humans participated in one of three groups: Two groups completed a 4‐week computerized cognitive training of a two‐back working memory task, either in combination with novel or with familiarized nature movies. A third group did not receive any training. As expected, both training groups showed improvements in task specific working memory performance and reaction times. However, there were no transfer or novelty effects on fluid intelligence, verbal memory, digit‐span, and executive functions. At the neural level, no significant micro‐ or macrostructural changes emerged in either group. Our findings suggest that working memory training in healthy older adults is associated with task‐specific improvements, but these gains do not transfer to other cognitive domains, and it does not lead to structural brain changes. [ABSTRACT FROM AUTHOR]

The spectrum of the Laplace‐Beltrami operator is instrumental for a number of geometric modeling applications, from processing to analysis. Recently, multiple methods were developed to retrieve an approximation of a shape that preserves its eigenvectors as much as possible, but these techniques output a subset of input points with no connectivity, which limits their potential applications. Furthermore, the obtained Laplacian results from an optimization procedure, implying its storage alongside the selected points. Focusing on keeping a mesh instead of an operator would allow to retrieve the latter using the standard cotangent formulation, enabling easier processing afterwards. Instead, we propose to simplify the input mesh using a spectrum‐preserving mesh decimation scheme, so that the Laplacian computed on the simplified mesh is spectrally close to the one of the input mesh. We illustrate the benefit of our approach for quickly approximating spectral distances and functional maps on low resolution proxies of potentially high resolution input meshes. [ABSTRACT FROM AUTHOR]

Background: In experimental placebo and nocebo studies, neutral control treatments are often administered for comparison with active treatments, but are of little interest, as, on average, they result in little change. Yet, when considered at an individual level, they fluctuate between baseline and subsequent measurements and may reveal important information about participants' placebo/nocebo responding tendencies.Methods: In a paradigm involving application of creams paired with positive, negative and neutral expectations, some subjects rated identical stimuli in the neutral condition as more painful while others as less painful after treatment with inert cream. We divided subjects into two groups based on the median split in these pre-post responses in the neutral control condition, and investigated (a) fMRI signal differences (post minus pre) between the two groups in neutral condition, and (b) seed-based resting state connectivity of the bilateral amygdala, known to be involved in emotional self-regulation, as well as ambiguous stimulus processing and aversive learning.Results: The results suggested that subjects who rated the same pain stimuli after treatment with explicitly neutral cream as more painful showed stronger fMRI activation of the amygdala during the experiment and had higher connectivity between the left amygdala and the striatum at rest. Neutral pre-post changes predicted behavioural placebo/nocebo response in this and two independent datasets.Conclusion: These findings suggest that measuring pre-post change in the neutral control condition might provide important information about subjects' individual differences in placebo/nocebo response.Significance: Pre-post changes in pain ratings in neutral conditions are modulated by amygdala activity and connectivity and can be used to predict placebo/nocebo responses. [ABSTRACT FROM AUTHOR]

In grassy ecosystems of south‐eastern Australia, fire maintains richness of native forbs. It is commonly thought that fire promotes regeneration indirectly by reducing competition for light and providing gaps for recruitment, rather than directly stimulating germination. However, physiological dormancy and morphophysiological dormancy are common, and few studies have explored responses to fire‐cues among dormant or hard‐to‐germinate forbs. Recent studies from other fire‐prone ecosystems suggest that in some cases, fire‐cues may not alleviate physiological or morphophysiological dormancy, but instead promote germination in combination with treatments which alleviate dormancy. We experimentally tested the prevailing hypothesis that perennial forbs common in south‐eastern Australian grassy ecosystems do not germinate in direct response to fire. Responses to fire‐cues both inherently and in combination with treatments which alleviate dormancy were investigated for seven species. Two fire‐cues (smoke and heat) plus a treatment of both heat + smoke were applied to fresh seed at three temperatures (35/25°C, 30/20°C and 25/15°C). Following this, the effect of fire‐cues on seed that had undergone warm stratification, cold stratification and dry‐after‐ripening was investigated. Three species — Arthropodium strictum, Cheiranthera cyanea and Dianella revoluta — responded to fire‐cues inherently, although germination in C. cyanea was low. High germination of D. revoluta was found when fire‐cues were combined with warm stratification. Fire‐cues had no effect on germination of Brunonia australis, Burchardia umbellata and Eryngium ovinum. Germination of Stypandra glauca was zero following all treatment combinations. Our finding that fire‐cues promote germination of three of the seven study species did not provide sufficient evidence to reject the current hypothesis that germination of perennial forbs is not typically promoted by fire‐cues. However, this study highlights the important direct role fire‐cues can play in promoting germination of some perennial forbs both inherently and in combination with treatments used to alleviate physiological dormancy. [ABSTRACT FROM AUTHOR]

CEO compensation can influence the kinds of strategies that firms adopt. We argue that performance-related compensation creates an incentive to look for overly ambitious, hard to implement strategies. At a cost, shareholders can curb this tendency by precommitting to a regime of CEO overcompensation in highly changeable environments. Alternatively shareholders can commit to low CEO pay, although this requires a commitment mechanism (either by the board of the individual company, or by the society as a whole) to counter the incentive to renegotiate upwards. We study the conditions under which the different policies for CEO compensation are preferred by shareholders. [ABSTRACT FROM AUTHOR]

Southern leaf blight (SLB) caused by the fungus Cochliobolus heterostrophus (Drechs.) Drechs. is a major foliar disease of maize worldwide. Our objectives were to identify quantitative trait loci (QTL) for resistance to SLB and flowering traits in recombinant inbred line (RIL) population derived from the cross of inbred lines LM5 (resistant) and CM140 (susceptible). A set of 207 RILs were phenotyped for resistance to SLB at three time intervals for two consecutive years. Four putative QTL for SLB resistance were detected on chromosomes 3, 8 and 9 that accounted for 54% of the total phenotypic variation. Days to silking and anthesis–silking interval (ASI) QTL were located on chromosomes 6, 7 and 9. A comparison of the obtained results with the published SLB resistance QTL studies suggested that the detected bins 9.03/02 and 8.03/8.02 are the hot spots for SLB resistance whereas novel QTL were identified in bins 3.08 and 8.01/8.04. The linked markers are being utilized for marker‐assisted mobilization of QTL conferring resistance to SLB in elite maize backgrounds. Fine mapping of identified QTL will facilitate identification of candidate genes underlying SLB resistance. [ABSTRACT FROM AUTHOR]

This paper describes a light detection and ranging (LiDAR)‐based autonomous navigation system for an ultralightweight ground robot in agricultural fields. The system is designed for reliable navigation under cluttered canopies using only a 2D Hokuyo UTM‐30LX LiDAR sensor as the single source for perception. Its purpose is to ensure that the robot can navigate through rows of crops without damaging the plants in narrow row‐based and high‐leaf‐cover semistructured crop plantations, such as corn (Zea mays) and sorghum (Sorghum bicolor). The key contribution of our work is a LiDAR‐based navigation algorithm capable of rejecting outlying measurements in the point cloud due to plants in adjacent rows, low‐hanging leaf cover or weeds. The algorithm addresses this challenge using a set of heuristics that are designed to filter out outlying measurements in a computationally efficient manner, and linear least squares are applied to estimate within‐row distance using the filtered data. Moreover, a crucial step is the estimate validation, which is achieved through a heuristic that grades and validates the fitted row‐lines based on current and previous information. The proposed LiDAR‐based perception subsystem has been extensively tested in production/breeding corn and sorghum fields. In such variety of highly cluttered real field environments, the robot logged more than 6 km of autonomous run in straight rows. These results demonstrate highly promising advances to LiDAR‐based navigation in realistic field environments for small under‐canopy robots. [ABSTRACT FROM AUTHOR]

Pigeons chose between two options on a concurrent‐chains task with a single response requirement in the initial link. The suboptimal option ended with food 20% of the time whereas the optimal option ended with food 80% of the time. During a Sig‐Both condition, terminal‐link stimuli on both options signaled whether or not food would occur. During a Sig‐Sub condition, terminal‐link stimuli on the suboptimal option provided differential signals, but stimuli on the optimal option did not differentially signal the food and no food outcomes. Initial‐link choices revealed a clear preference for the optimal option in the Sig‐Both condition, but preference shifted toward suboptimality in the Sig‐Sub condition. These findings show that pigeon suboptimal choice is not singularly driven by signal value, as has been suggested, but also by reinforcer frequency. [ABSTRACT FROM AUTHOR]

Abstract: The strategic interactions of mega‐regional blocs such as the Trans‐Pacific Partnership (TPP), the Regional Comprehensive Economic Partnership and even the ‘One Belt and One Road’ (OBOR) in the Asia‐Pacific reflects the dual purposes of large countries as they seek not only the welfare gains from trade liberalisation, but also the leadership in a trading bloc or the right to set the rules. This paper designs two sequential network formation games – a leadership game and a trade liberalisation game, to model this phenomenon and predict the equilibrium result. In the first game, we show how the incorporation of leadership affects the choices among different trading structures. Specifically, we show that the parallel trading blocs emerge as the equilibrium outcome only when there exists large loss from giving up leadership. In the second game, we describe how the globalisation is arrived and conduct numerical simulations to test our theoretical results. The predictions of the game are supported by the real‐world data based on simulation results. [ABSTRACT FROM AUTHOR]