Large Machinery Research Articles

Agricultural Machinery Operator Monitoring System (Ag-OMS): A Machine Learning Approach for Real-Time Operator Safety Assessment

Highlights A machine learning-based real-time monitoring system for agricultural machinery operators was developed. Categorization of tractor operators’ behaviors in real-time into low, medium, and high-risk safety behaviors. Visual and sound feedback alert system of Ag-OMS triggered when operators engaged in unsafe operating behaviors. ABSTRACT. The 2015 CS-CASH (Central States Center for Agricultural Safety and Health, 2015) Injury Surveillance Surveys showed that around 19% of injuries to agricultural producers are related to tractors or large agricultural machinery, yet only a limited number of studies are found that address tools and methods for monitoring safety behaviors of agricultural machinery operators in real-time. The current safety behavior monitoring approaches require an in-person presence, which can be both time- and cost-inefficient, and the other available methods lack a feedback element to alert operators in real-time. As a result, the research presented in this study aimed to develop an automated approach to monitoring tractor operators' safety behaviors through the use of a trained machine learning (ML) model and a feedback system to alert operators when they engage in unsafe practices. For the ML model development, a skeleton-detecting algorithm called OpenPose was used to detect real-time human postures in a livestreaming video feed from a camera installed in the tractor cab. The model was then trained on three separate categories of tractor operators’ safety operating behaviors, and this trained classifier was used to label operators’ safety behaviors in real time based on the three safety classes. A feedback mechanism controlled by an onboard microcontroller was then used to alert the operators when unsafe operating behavior was detected to facilitate safe practices. This monitoring system, named Ag-OMS (Agricultural Machinery Operators Monitoring System), monitored the ingress/egress operators’ behaviors in real-time entering and exiting the tractor cab. The Ag-OMS successfully identified the ingress/egress operators’ behaviors with an accuracy of 97% on the testing datasets for all safety risk categories. Keywords: Ag-OMS, Machine learning (ML), Safety behaviors, OpenPose, Tractor operator.

Modeling the ribosome as a bipartite graph.

Developing mathematical representations of biological systems that can allow predictions is a challenging and important research goal. It is demonstrated here how the ribosome, the nano-machine responsible for synthesizing all proteins necessary for cellular life, can be represented as a bipartite network. Ten ribosomal structures from Bacteria and six from Eukarya are explored. Ribosomal networks are found to exhibit unique properties despite variations in the nodes and edges of the different graphs. The ribosome is shown to exhibit very large topological redundancies, demonstrating mathematical resiliency. These results can potentially explain how it can function consistently despite changes in composition and connectivity. Furthermore, this representation can be used to analyze ribosome function within the large machinery of network theory, where the degrees of freedom are the possible interactions, and can be used to provide new insights for translation regulation and therapeutics.

Algorithms with randomization-based acceleration strategies for sound source localization by non-synchronous measurements

The Non-Synchronous Measurements is an efficient technique to improve the acoustic image of conventional beamforming for sound source localization. It is unable to quickly reveal the sound sources of the large machinery which requires a large synthetic array with many microphones to capture enough sound pressure data. In this paper, four Non-Synchronous Measurement algorithms with improved computational efficiency are demonstrated. They are implemented by combining the Alternative Direction Method of Multipliers (ADMM) method with different randomization-based acceleration strategies. The new algorithms are developed firstly by (1) using Randomized Singular Value Decomposition (RSVD) to construct the projection basis, and then by (2) migrating the computation platform from the Central Processing Unit to the Graphics Processing Unit for the Cross-Spectral Matrix completion steps, (3) accelerating the soft threshold shrinkage operator with RSVD, or (4) replacing the soft threshold shrinkage with RSVD-enhanced optimal shrinkage in the Cross-Spectral Matrix completion steps. Numerical simulations are carried out under different conditions, including the number of sequential measurement positions, the step length between two sequential measurement positions, the frequency of the sound sources, and the Signal-to-Noise Ratio of the sound pressure signals measured by the microphones. The sound source localization performance of the improved algorithms is assessed by examining their acoustic maps, and the computational performance of these algorithms is compared through their Cross-Spectral Matrix reconstruction errors and time consumption.

Direct immersogeometric fluid flow and heat transfer analysis of objects represented by point clouds

Immersogeometric analysis (IMGA) is a geometrically flexible method that enables one to perform multiphysics analysis directly using complex computer-aided design (CAD) models. While the IMGA approach is well-studied and has a remarkable advantage over traditional CFD, IMGA still requires a well-defined B-rep model to represent the geometry. Obtaining such a model can sometimes be equally as challenging as creating a body-fitted mesh. To address this issue, we develop a novel IMGA approach for the simulation of incompressible and compressible flows around complex geometries represented by point clouds in this work. The point cloud representation of geometries is a direct method for digitally acquiring geometric information using LiDAR scanners, optical scanners, or other passive methods such as multi-view stereo images. The point cloud object’s geometry is represented using a set of unstructured points in the Euclidean space with (possible) orientation information in the form of surface normals. Due to the absence of topological information in the point cloud model, there are no guarantees for the geometric representation to be watertight or 2-manifold or to have consistent normals. To perform IMGA directly using point cloud geometries, we first develop a method for estimating the inside–outside information and the surface normals directly from the point cloud. We also propose a method to compute the Jacobian determinant for the surface integration (over the point cloud) necessary for the weak enforcement of Dirichlet boundary conditions. We validate these geometric estimation methods by comparing the geometric quantities computed from the point cloud with those obtained from analytical geometry and tessellated CAD models. In this work, we also develop thermal IMGA to simulate heat transfer in the presence of flow over complex geometries. The proposed framework is tested for a wide range of Reynolds and Mach numbers on benchmark problems of geometries represented by point clouds, showing the robustness and accuracy of the method. Finally, we demonstrate the applicability of our approach by performing IMGA on large industrial-scale construction machinery represented using a point cloud of more than 12 million points.

Design and Implementation of a vibration monitor protecting the cable from external destruction

Underground cable is one of the main components of urban power supply systems. However, it is often damaged by large machinery in the process of urban road construction. To protect the underground cable, this paper proposes a novel design of a smart vibration device based on a complex embedded system, including the STM32 control chip, vibration sensors, NB-IoT communication module, and charging module. Through vibration signal detection of the excavator and other large-scale mechanical behavior, the vibration device can indicate the direction where the damage is occurring, and send out a warning message to the operation center. Finally, some experiments for vibration monitoring devices are conducted to verify their effectiveness and future application potential prospects.

Genetic Alterations in Members of the Proteasome 26S Subunit, AAA-Atpase (PSMC) Gene Family Transmit Proteasome Inhibitor Resistance in Multiple Myeloma By Impacting the ADP/ATP Binding Pocket

Background For the treatment of Multiple Myeloma (MM), proteasome inhibitors (PIs) are highly efficient and widely used, but resistance is a major obstacle to successful therapy. Several underlying mechanisms have been proposed but were only reported for a minority of resistant patients e.g., mutations in the PI binding domain PSMB5. However, the proteasome is a large and complex machinery and its mechanistic understanding remains incomplete. In this study, we unravel the role of the six ATPases of the 19S proteasome regulator (PSMC1-6) in MM resistance. Methods As an example of cancer evolution and the acquisition of PI resistance, we conducted an in-depth analysis of an index patient applying deep sequencing of immunoglobulin rearrangements (IG), FISH, and WES in serial samples at MGUS, newly diagnosed MM, and five later timepoints including two relapses. Then we expand towards generic meta-analyses of PSMC alterations in our own and other published datasets comprising 1,499 newly diagnosed (NDMM) and 447 PI pretreated MM (PMM) patients for WGS/WES. For RNA sequencing, we analyzed 16 normal plasma cells (NPCs) and 360 NDMM patients. Furthermore, we explore the structural impact of PSMC single nucleotide variants on the proteasome and their relevance for PI resistance using 3D modeling with Chimera and Pymol. Results The WES analysis of our index patient uncovers a PSMC2 Y429S mutation acquired at the second relapse after intensive bortezomib-containing therapy. We functionally confirm this variant to mediate PI resistance in the cell line RPMI 8226. In the meta-analysis, a total of 36 mutations were identified (mutation incidence: 1.85%). The PSMC5 G152S mutation was found in three independent patients, and a G152R in a fourth patient, thus, representing a potential hotspot. Based on 3D structural projections, the identified mutations can be clustered into three main groups: first, mutations affecting the intrinsic conformation of the respective subunit; second, mutations perturbing the PSMC protomer interactions and the proper folding/functioning of the whole complex; and third, mutations impairing the ADP/ATP binding pocket (Figure). Nine mutations belong to the third category interacting with the adenine ring or the phosphate groups of the ATP. The expression analysis reveals a significant upregulation of PSMC3 (P=0.003), PSMC4 (P≤0.001), and PSMC5 (P=0.043) from NPC to NDMM. Conclusions The 19S hexameric AAA ATPase ring of the 26S proteasome is responsible for unfolding and introducing the substrates into the catalytic 20S complex. PSMC gene alterations are structurally often located in regulatory sites for activity e.g. impacting the ADP/ATP binding pocket. The following activation of the 26S proteasome increases the PI tolerance and represents a new PI resistance mechanism. Moreover, changes in the expression level of the PSMC members seem to play a role not only in the development of PI resistance but already in the development of MM, probably by increasing the protein turnover capacity of myeloma cells. This study opens the way to explore new classes of proteasome inhibitors avoiding this kind of mechanism of resistance. Figure:Mutations in the'PSMC' subunits of the 19S Base AAA-ATPase hexamer accumulate in proximity to the ATP/ADP binding pockets. The backbone of the PSMC hexamer is displayed as a ribbon diagram, mutations (red) and ADP (blue) as 3D spheres (PDB 5GJR). The mutations cluster in areas responsible for proper folding and functioning of the complex or in proximity to the ADP/ATP binding pockets, exemplarily shown for PSMC1, PSMC2, and PSMC5. ADP is presented as a wireframe stick in light green (PDB 5GJQ). The PSMC2Y429S mutation of the index patient is indicated in yellow. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Some differences but all at risk: Improving farm safety for young people-An Australian experience.

A significant portion of on-farm deaths and injuries in Australia occur among young people working on the farm. Since most Australian farms are still family owned and operated, young people are an integral part of everyday operations and the farm is a place where these young people live, work and play. This paper describes how the international Gear Up for Ag Health and Safety™ program, originally developed in North America, was further developed for a younger Australian audience (ages 12-19) enrolled in agricultural programs at secondary or vocational schools. In addition, we share insight on demographics, self-reported farm safety behaviours, and the most common farm tasks being performed by program participants utilising a pre-survey originally developed for program customisation. Of particular importance were the most common farming tasks reported by this group. The most common tasks performed on Australian farms included a large variety of vehicle use (farm vehicles, motorbikes, and quadbikes) and handling livestock. Females reported operating vehicles and other farm equipment at the same rates as males. Males were more likely to be working with large heavy machinery and driving trucks, while females were more likely to be working with livestock and using horses for stockwork. Both males and females reported low use of PPE and poor safety habits. In future Australian programs, it will be important to address the conspicuous use of motor vehicles, quadbikes, motor bikes and machinery at early ages, and to target gender-specific tasks to reduce risks on the farm.

Environmental Impact Assessment of Production Plant during Construction Period

Based on the construction project of a manufacturing plant, the environmental impact assessment of possible environmental pollution during the construction period was carried out from the perspective of atmosphere, water, noise, and solid waste. The analysis of air pollution indicates that dust and motor vehicle exhaust are the main air pollution factors, of which dust emission is 33 t, and the daily emission of NOx, CO, and THC in tail gas is 5.35 kg, 3.7 kg, and 1.1 kg, respectively. The annual average wind speed of the area where the factory is located is 3.15 m/s, and the average wind speed in August is 2.50 m/s, which is 20.6% lower than the annual average. The annual average monthly precipitation is 59.5 mm, and the precipitation in July is 186.4 mm, which is 213.3% higher than the monthly average. Therefore, summer is the best time for construction. Meanwhile, in addition to taking road hardening measures to reduce emissions, dust can also be restrained through watering, and motor vehicle exhaust is reduced through reasonable operation. Water pollution analysis shows that the pH of groundwater in the factory is within the standard limit range (6.5-8.5), and the maximum standard index is less than 0.1, with a very high level of reaching the standard. Cleaning engineering machinery will produce wastewater containing petroleum substances and suspended solids. The amount of wastewater produced every day is 0.5 m3, which can be used for dust suppression. The daily amount of sewage during the construction period is 0.6 m3, which can be directly discharged to the pipe network without polluting local water sources. Noise pollution analysis shows that the minimum distance between day construction and night construction is 50 m and 281 m, respectively. Although there is large construction machinery in the construction area, the construction area itself is in the production area and there are other noise pollution sources around it, so there will not be obvious noise pollution during the construction period. The analysis of solid waste pollution indicates that the total amount of construction waste generated during the construction period is about 4.2 t, and the daily production of domestic waste is 21 kg. Part of various solid wastes is collected and treated in a centralized manner, while the rest can conducted with landfill treatment after part of them is recycled and utilized, without causing significant pollution to the local environment.

Roles of minor spliceosome in intron recognition and the convergence with the better understood major spliceosome.

Catalyzed by spliceosomes in the nucleus, RNA splicing removes intronic sequences from precursor RNAs in eukaryotes to generate mature RNA, which also significantly increases proteome complexity and fine-tunes gene expression. Most metazoans have two coexisting spliceosomes; the major spliceosome, which removes >99.5% of introns, and the minor spliceosome, which removes far fewer introns (only 770 at present have been predicted in the human genome). Both spliceosomes are large and dynamic machineries, each consisting of five small nuclear RNAs (snRNAs) and more than 100 proteins. However, the dynamic assembly, catalysis, and protein composition of the minor spliceosome are still poorly understood. With different splicing signals, minor introns are rare and usually distributed alone and flanked by major introns in genes, raising questions of how they are recognized by the minor spliceosome and how their processing deals with the splicing of neighboring major introns. Due to large numbers of introns and close similarities between the two machinery, cooperative, and competitive recognition by the two spliceosomes has been investigated. Functionally, many minor-intron-containing genes are evolutionarily conserved and essential. Mutations in the minor spliceosome exhibit a variety of developmental defects in plants and animals and are linked to numerous human diseases. Here, we review recent progress in the understanding of minor splicing, compare currently known components of the two spliceosomes, survey minor introns in a wide range of organisms, discuss cooperation and competition of the two spliceosomes in splicing of minor-intron-containing genes, and contributions of minor splicing mutations in development and diseases. This article is categorized under: RNA Processing > Processing of Small RNAs RNA Processing > Splicing Mechanisms RNA Structure and Dynamics > RNA Structure, Dynamics and Chemistry.

Comparison of Eye and Face Features on Drowsiness Analysis.

Drowsiness is one of the leading causes of traffic accidents. For those who operate large machinery or motor vehicles, incidents due to lack of sleep can cause property damage and sometimes lead to grave consequences of injuries and fatality. This study aims to design learning models to recognize drowsiness through human facial features. In addition, this work analyzes the attentions of individual neurons in the learning model to understand how neural networks interpret drowsiness. For this analysis, gradient-weighted class activation mapping (Grad-CAM) is implemented in the neural networks to display the attention of neurons. The eye and face images are processed separately to the model for the training process. The results initially show that better results can be obtained by delivering eye images alone. The effect of Grad-CAM is also more reasonable using eye images alone. Furthermore, this work proposed a feature analysis method, K-nearest neighbors Sigma (KNN-Sigma), to estimate the homogeneous concentration and heterogeneous separation of the extracted features. In the end, we found that the fusion of face and eye signals gave the best results for recognition accuracy and KNN-sigma. The area under the curve (AUC) of using face, eye, and fusion images are 0.814, 0.897, and 0.935, respectively.

Mechanistic Insights into the Long-range Allosteric Regulation of KRAS Via Neurofibromatosis Type 1 (NF1) Scaffold Upon SPRED1 Loading

Allosteric regulation is the most direct and efficient way of regulating protein function, wherein proteins transmit the perturbations at one site to another distinct functional site. Deciphering the mechanism of allosteric regulation is of vital importance for the comprehension of both physiological and pathological events in vivo as well as the rational allosteric drug design. However, it remains challenging to elucidate dominant allosteric signal transduction pathways, especially for large and multi-component protein machineries where long-range allosteric regulation exits. One of the quintessential examples having long-range allosteric regulation is the ternary complex, SPRED1–RAS–neurofibromin type 1 (NF1, a RAS GTPase–activating protein), in which SPRED1 facilitates RAS–GTP hydrolysis by interacting with NF1 at a distal, allosteric site from the RAS binding site. To address the underlying mechanism, we performed extensive Gaussian accelerated molecular dynamics simulations and Markov state model analysis of KRAS–NF1 complex in the presence and absence of SPRED1. Our findings suggested that SPRED1 loading allosterically enhanced KRAS–NF1 binding, but hindered conformational transformation of the NF1 catalytic center for RAS hydrolysis. Moreover, we unveiled the possible allosteric pathways upon SPRED1 binding through difference contact network analysis. This study not only provided an in-depth mechanistic insight into the allosteric regulation of KRAS by SPRED1, but also shed light on the investigation of long-range allosteric regulation among complex macromolecular systems.

Development of knitted reinforced structures with self-diagnostic function for composite applications

The research aims the development of knitted reinforcement structures for inducing self-diagnostic properties into knitted reinforced composites for structural health monitoring. Conductive carbon fiber was used in knitted inlaid structures as inlay yarns, and l × 1 Rib knitted base fabric of polyester filament yarn was used for knitting. The reinforcement’s conductive nature induced self-diagnostic properties into composites using correlation of mechanical damages and changes in electrical resistance values. Single and double stimuli layers and inlay patterns of 3 × 1, 6 × 1 and 9 × 1 was used to check their impact on self-diagnostic properties. Mechanical testing and real-time electrical resistance monitoring proved knitted structures as a solution to induce self-diagnostic properties into composite materials. Composites having double stimuli (conductive) layers exhibited better self-diagnostic properties than single stimuli layer composites, and the self-diagnostic properties also improved as the inlay pattern of reinforcement moved from 9 × 1 to 6 × 1 and 3 × 1 inlay. Such knitted reinforced self-diagnostic composites could be practically used in structural health monitoring applications, e.g., complicated structures of large buildings infrastructures and machinery which require record of each minor happening with structures to keep smooth and successful running of the system.

Funny friends? Dutch foreign policy, Great Britain and European integration in the ‘long’ 1970s

ABSTRACT This article is concerned with the still understudied and frequently misunderstood 1970s. It homes in on Dutch foreign policy regarding Great Britain and European integration to question the long-standing assumption that Dutch policymaking in this period became ‘realistic’ and consumed by a yearning for ‘instrumental supranationalism’. Through a study of Dutch and British government archives, this paper thus lays bare the contradictions that inhered in Dutch visions of European integration and asks how Dutch aims could be squared with support for British accession, ultimately demonstrating why ‘realistic’ and ‘irrational’ are perilous analytical categories when used to interrogate large bureaucratic machineries composed of many individuals with different goals and desires struggling over limited resources.

Study of Diesel Spray Impinging Ignition and Combustion Characteristics Under Variable Ambient Densities Based on the Visualization Experiment

Abstract The application of turbocharged intercooler direct injection (DI) diesel engine in large diesel vehicle transportation and construction machinery will be indispensable for a long time in the future. The extreme condition of the plateau has become a hotspot in the research of diesel combustion. When the diesel engine works on the cold-start or low-load/low-speed condition, the problems of combustion and emission caused by abnormal supercharging of a turbocharger are apparent. The development of the miniaturization of diesel engines can effectively avoid liquid-wall impingement. However, the low density of the plateau will bring inevitable combustion modes, such as impinging ignition and combustion. This study summarized the relationship among spray, fuel–air mixing, ignition, soot formation, and ambient density under the condition of impinging ignition and nonliquid spray impingement, providing a reference for the further research and improvement of diesel engine combustor structure design. The effect of ambient density change on diesel spray mainly weakens radial air entrainment in the fuel injection. There was apparent impinging ignition at 11.37 g/m3 density, and the ignition time delay was 0.2 ms longer than that at 16.07 g/m3, corresponding to the 0 m altitude. Under high altitude with more significant density, the combustion is more intense under higher temperature. However, the larger flame diffusion area under low density leads to the larger soot distribution area and more considerable soot generation.

Research and Development of Electric Power Lifting Truck

Equipment and materials are completely dependent on large machinery and human forklift, which is difficult to ensure the high efficiency of transportation. As a supplement to large transportation machinery and vehicles, it can make up for the lack of low transportation capacity of human-based transportation equipment, and solve the prominent problems such as backward material transportation equipment, poor road adaptability, time-consuming and laborious. The electric power assisted lifting truck to be developed can realize “one kilometer” of materials the transportation reserve with high travel efficiency has become the “range extender” of large vehicles. With the help of high and new technology, the R & D of electric power assisted lifting truck adopts the contractor guarantee mode to realize complementary advantages, resource sharing, joint development and win-win cooperation, so as to provide technical support for material support. The electric power assisted lifting truck is mainly composed of walking system, lifting system, control system and auxiliary system, which meets the needs of strong road trafficability, time-saving and labor-saving, simple operation, convenient maintenance, safety and reliability and low cost, and improves the rapid, accurate and convenient guarantee ability of materials.

Disentangling the recognition complexity of a protein hub using a nanopore

WD40 repeat proteins are frequently involved in processing cell signaling and scaffolding large multi-subunit machineries. Despite their significance in physiological and disease-like conditions, their reversible interactions with other proteins remain modestly examined. Here, we show the development and validation of a protein nanopore for the detection and quantification of WD40 repeat protein 5 (WDR5), a chromatin-associated hub involved in epigenetic regulation of histone methylation. Our nanopore sensor is equipped with a 14-residue Win motif of mixed lineage leukemia 4 methyltransferase (MLL4Win), a WDR5 ligand. Our approach reveals a broad dynamic range of MLL4Win-WDR5 interactions and three distant subpopulations of binding events, representing three modes of protein recognition. The three binding events are confirmed as specific interactions using a weakly binding WDR5 derivative and various environmental contexts. These outcomes demonstrate the substantial sensitivity of our nanopore sensor, which can be utilized in protein analytics.

On the relationships between the size of agricultural machinery, soil quality and net revenues for farmers and society

Mechanization in agriculture has greatly improved the efficiency of field operations, but also resulted in heavier agricultural vehicles, which has led to increased risks of soil compaction. Hence, farmers benefit from machinery with higher capacity but may suffer from decreased yields caused by compaction. Compaction may result in further environmental costs to society. We present a framework that relates the machinery capacity to soil compaction and its impacts on crop yields and environmental disservices, and associated revenues and costs for farmers and society. We combined simulations using a soil compaction model and a soil-crop model with simple economic analyses. We applied the framework to a case study of cereal production in Sweden, to derive the optimal combine harvester size that maximizes the farmer's private profit and the societal net benefit, respectively. Increased machinery size decreased harvesting costs, but also reduced simulated crop yields and thus crop revenue as a result of soil compaction. Furthermore, in the model simulations, compaction also increased surface run-off, nitrogen leaching and greenhouse gas emissions. Intermediate machinery size maximized the farmer's net revenue. Net benefits for society were highest for the lowest possible compaction level, due to the considerable external costs from soil compaction. We show that the optimal machinery size and thus compaction level for maximum farmer revenue would decrease if either producer prices were higher, harvesting costs savings from larger machinery were smaller, or if farmers were charged for (part of the) environmental costs.

The modifying enzyme Tsr3 establishes the hierarchy of Rio kinase binding in 40S ribosome assembly.

Ribosome assembly is an intricate process, which in eukaryotes is promoted by a large machinery comprised of over 200 assembly factors (AFs) that enable the modification, folding, and processing of the ribosomal RNA (rRNA) and the binding of the 79 ribosomal proteins. While some early assembly steps occur via parallel pathways, the process overall is highly hierarchical, which allows for the integration of maturation steps with quality control processes that ensure only fully and correctly assembled subunits are released into the translating pool. How exactly this hierarchy is established, in particular given that there are many instances of RNA substrate "handover" from one highly related AF to another, remains to be determined. Here we have investigated the role of Tsr3, which installs a universally conserved modification in the P-site of the small ribosomal subunit late in assembly. Our data demonstrate that Tsr3 separates the binding of the Rio kinases, Rio2 and Rio1, with whom it shares a binding site. By binding after Rio2 dissociation, Tsr3 prevents rebinding of Rio2, promoting forward assembly. After rRNA modification is complete, Tsr3 dissociates, thereby allowing for recruitment of Rio1 into its functional site. Inactive Tsr3 blocks Rio1 function, which can be rescued using mutants that bypass the requirement for Rio1 activity. Finally, yeast strains lacking Tsr3 randomize the binding of the two kinases, leading to the release of immature ribosomes into the translating pool. These data demonstrate a role for Tsr3 and its modification activity in establishing a hierarchy for the function of the Rio kinases.

Development of a high-throughput field phenotyping rover optimized for size-limited breeding fields as open-source hardware.

Phenotyping is a critical process in plant breeding, especially when there is an increasing demand for streamlining a selection process in a breeding program. Since manual phenotyping has limited efficiency, high-throughput phenotyping methods are recently popularized owing to progress in sensor and image processing technologies. However, in a size-limited breeding field, which is common in Japan and other Asian countries, it is challenging to introduce large machinery in the field or fly unmanned aerial vehicles over the field. In this study, we developed a ground-based high-throughput field phenotyping rover that could be easily introduced to a field regardless of the scale and location of the field even without special facilities. We also made the field rover open-source hardware, making its system available to public for easy modification, so that anyone can build one for their own use at a low cost. The trial run of the field rover revealed that it allowed the collection of detailed remote-sensing images of plants and quantitative analyses based on the images. The results suggest that the field rover developed in this study could allow efficient phenotyping of plants especially in a small breeding field.

Enzymology and Dynamics by Cryogenic Electron Microscopy.

Cryogenic electron microscopy (cryo-EM) has revolutionized the field of structural biology, particularly in solving the structures of large protein complexes or cellular machineries that play important biological functions. This review focuses on the contribution and future potential of cryo-EM in related emerging applications-enzymatic mechanisms and dynamic processes. Work on these subjects can benefit greatly from the capability of cryo-EM to solve the structures of specific protein complexes in multiple conditions, including variations in the buffer condition, ligands, and temperature, and to capture multiple conformational states, conformational change intermediates, and reaction intermediates. These studies can expand the structural landscape of specific proteins or protein complexes in multiple dimensions and drive new advances in the fields of enzymology and dynamic processes. The advantages and complementarity of cryo-EM relative to X-ray crystallography and nuclear magnetic resonance with regard to these applications are also addressed.