A computational grid-to-place-cell transformation model indicates a synaptic driver of place cell impairment in early-stage Alzheimer’s Disease

Alzheimer’s Disease (AD) is characterized by progressive neurodegeneration and cognitive impairment. Synaptic dysfunction is an established early symptom, which correlates strongly with cognitive decline, and is hypothesised to mediate the diverse neuronal network abnormalities observed in AD. However, how synaptic dysfunction contributes to network pathology and cognitive impairment in AD remains elusive. Here, we present a grid-cell-to-place-cell transformation model of long-term CA1 place cell dynamics to interrogate the effect of synaptic loss on network function and environmental representation. Synapse loss modelled after experimental observations in the APP/PS1 mouse model was found to induce firing rate alterations and place cell abnormalities that have previously been observed in AD mouse models, including enlarged place fields and lower across-session stability of place fields. Our results support the hypothesis that synaptic dysfunction underlies cognitive deficits, and demonstrate how impaired environmental representation may arise in the early stages of AD. We further propose that dysfunction of excitatory and inhibitory inputs to CA1 pyramidal cells may cause distinct impairments in place cell function, namely reduced stability and place map resolution.

Evaluation of four point cloud similarity measures for the use in autonomous driving

Measuring the similarity between point clouds is required in many areas. In autonomous driving, point clouds for 3D perception are estimated from camera images but these estimations are error-prone. Furthermore, there is a lack of measures for quality quantification using ground truth. In this paper, we derive conditions point cloud comparisons need to fulfill and accordingly evaluate the Chamfer distance, a lower bound of the Gromov Wasserstein metric, and the ratio measure. We show that the ratio measure is not affected by erroneous points and therefore introduce the new measure “average ratio”. All measures are evaluated and compared using exemplary point clouds. We discuss characteristics, advantages and drawbacks with respect to interpretability, noise resistance, environmental representation, and computation.

The Role of Gender and Familiarity in a Modified Version of the Almeria Boxes Room Spatial Task

Individual factors like gender and familiarity can affect the kind of environmental representation that a person acquires during spatial navigation. Men seem to prefer relying on map-like survey representations, while women prefer using sequential route representations. Moreover, a good familiarity with the environment allows more complete environmental representations. This study was aimed at investigating gender differences in two different object-position learning tasks (i.e., Almeria Boxes Tasks) assuming a route or a survey perspective also considering the role of environmental familiarity. Two groups of participants had to learn the position of boxes placed in a virtual room. Participants had several trials, so that familiarity with the environment could increase. In both tasks, the effects of gender and familiarity were found, and only in the route perspective did an interaction effect emerge. This suggests that gender differences can be found regardless of the perspective taken, with men outperforming women in navigational tasks. However, in the route task, gender differences appeared only at the initial phase of learning, when the environment was unexplored, and disappeared when familiarity with the environment increased. This is consistent with studies showing that familiarity can mitigate gender differences in spatial tasks, especially in more complex ones.

Spatio-temporal voxel layer: A view on robot perception for the dynamic world

The spatio-temporal voxel grid is an actively maintained open-source project providing an improved three-dimensional environmental representation that has been garnering increased adoption in large, dynamic, and complex environments. We provide a voxel grid and the Costmap 2-D layer plug-in, Spatio-Temporal Voxel Layer, powered by a real-time sparse occupancy grid with constant time access to voxels which does not scale with the environment’s size. We replace ray-casting with a new clearing technique we dub frustum acceleration that does not assume a static environment and in practice, represents moving environments better. Our method operates at nearly 400% less CPU load on average while processing 9 QVGA resolution depth cameras as compared to the voxel layer. This technique also supports sensors such as three-dimensional laser scanners, radars, and additional modern sensors that were previously unsupported in the available ROS Navigation framework that has become staples in the roboticists’ toolbox. These sensors are becoming more widely used in robotics as sensor prices are driven down and mobile compute capabilities improve. The Spatio-Temporal Voxel Layer was developed in the open with community feedback over its development life cycle and continues to have additional features and capabilities added by the community. As of February 2019, the Spatio-Temporal Voxel Layer is being used on over 600 robots worldwide in warehouses, factories, hospitals, hotels, stores, and libraries. The open-source software can be viewed and installed on its GitHub page at https://github.com/SteveMacenski/spatio_temporal_voxel_layer .

The Layout of Maize Variety Test Sites Based on the Spatiotemporal Classification of the Planting Environment

An appropriate layout of crop multi-environment trial (MET) sites is imperative for evaluating new crop varieties’ performance in terms of agronomic traits and stress tolerance, and this information is used to determine the utilization value and suitable promotion region of new varieties. Actually, traditional maize test sites have been selected according to the experience of breeding experts, which leads to the strong subjective and unscientific conclusions regarding sites, as well as test results that are not representative of the target population of environments (TPE). Therefore, in this study, we proposed a new method for MET sites layout. Meteorological data, maize growth period data, and county-level maize planting area data were collected for the spatiotemporal classification of a given maize planting region to analyze change rules in the environmental category of each minimum research unit within the study period. If the occurrence frequency of its final attribution category reaches a certain threshold (50%), this minimum research unit is classified as a typical environment region; otherwise, it is classified as an atypical environment region. Then, the number of test sites in each environmental category is allocated by spatial stratified sampling. At last, we establish the optimal test sites layout and a reliability measurement (test adequacy) methods. The practicability of this method was proved by taking the Three Northeastern Provinces of China as the study area. The result shows that there should be 112 test sites in the study area, the distribution of the test sites is uniform, and the environmental representation is high. Test adequacy analysis of the test sites reveals that most of the environmental categories have a test adequacy that reaches 1 in each test period. The method proposed in this paper provides support for the scientific layout of crop varieties test sites and helps to improve the representative and reliability of variety test results while optimizing resources.

Fatigue Performance and Crack Growth Assessments of Riser Welds in Mild Sour Environment

Fatigue design of deepwater riser system in a sour environment is a challenging task in a project cycle. More often, the challenge is in identifying an appropriate project specific fatigue curve using accurate environmental representation, and establishing a crack growth curve to confirm the acceptance criteria of the welds. Conventional practice in industry is to use a knock down factor (KDF) to capture the effect of corrosion fatigue, rather than taking an effort in executing detailed test/qualification program. A KDF approach can turn out to be very unreliable, specifically, for mild sour environment where significant test data are not available. As a result, there can be several impacts, including delivery of an under-designed system with potential operational risks. This paper presents comprehensive findings from a sour service qualification program executed in a project cycle. The sour environment is mild, and is slightly above NACE limit (0.1psi ppH2S, pH ∼ 6). The program included a detailed scope of work consisting of in-air and in-environment fatigue test as well as limited scope in understanding fatigue crack growth rate in the same environment. The material used is API 5L X65 seamless pipe with mechanized GMAW girth weld. The results show the unpredictable side of corrosion fatigue, especially in this kind of mild sour environment, which is not well understood.