Learning and Its Neural Correlates in a Virtual Environment for Honeybees

The search for neural correlates of operant and observational learning requires a combination of two (experimental) conditions that are very difficult to combine: stable recording from high order neurons and free movement of the animal in a rather natural environment. We developed a virtual environment (VE) that simulates a simplified 3D world for honeybees walking stationary on an air-supported spherical treadmill. We show that honeybees perceive the stimuli in the VE as meaningful by transferring learned information from free flight to the virtual world. In search for neural correlates of learning in the VE, mushroom body extrinsic neurons were recorded over days during learning. We found changes in the neural activity specific to the rewarded and unrewarded visual stimuli. Our results suggest an involvement of the mushroom body extrinsic neurons in operant learning in the honeybee (Apis mellifera)

Eavesdropping on Honeybee Communication via Electrostatic Field Recordings

As a canary in a coalmine warns of dwindling breathable air, the honeybee can indicate the health of an ecosystem. Honeybees are the most important pollinators of fruit-bearing flowers, and share similar ecological niches with many other pollinators; therefore, the health of a honeybee colony can reflect the conditions of a whole ecosystem. The health of a colony may be mirrored in social signals that bees exchange during their sophisticated body movements such as the waggle dance. To observe these changes, we developed an automatic system that records and quantifies social signals under normal beekeeping conditions. Here, we describe the system and report representative cases of normal social behavior in honeybees. Our approach utilizes the fact that honeybee bodies are electrically charged by friction during flight and inside the colony, and thus they emanate characteristic electrostatic fields when they move their bodies. These signals, together with physical measurements inside and outside the colony (temperature, humidity, weight of the hive, and activity at the hive entrance) will allow quantification of normal and detrimental conditions of the whole colony. The information provided instructs how to setup the recording device, how to install it in a normal bee colony, and how to interpret its data

5G New Radio for Terrestrial Broadcast: A Forward-Looking Approach for NR-MBMS

"© 2019 IEEE. Personal use of this material is permitted. Permissíon from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertisíng or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works."[EN] 3GPP LTE eMBMS release (Rel-) 14, also referred to as further evolved multimedia broadcast multicast service (FeMBMS) or enhanced TV (EnTV), is the first mobile broadband technology standard to incorporate a transmission mode designed to deliver terrestrial broadcast services from conventional high power high tower (HPHT) broadcast infrastructure. With respect to the physical layer, the main improvements in FeMBMS are the support of larger inter-site distance for single frequency networks (SFNs) and the ability to allocate 100% of a carrier's resources to the broadcast payload, with self-contained signaling in the downlink. From the system architecture perspective, a receive-only mode enables free-to-air (FTA) reception with no need for an uplink or SIM card, thus receiving content without user equipment registration with a network. These functionalities are only available in the LTE advanced pro specifications as 5G new radio (NR), standardized in 3GPP from Rel-15, has so far focused entirely on unicast. This paper outlines a physical layer design for NR-MBMS, a system derived, with minor modifications, from the 5G-NR specifications, and suitable for the transmission of linear TV and radio services in either single-cell or SFN operation. This paper evaluates the NR-MBMS proposition and compares it to LTE-based FeMBMS in terms of flexibility, performance, capacity, and coverage.This work was supported in part by the European Commission through the 5G-PPP Project 5G-Xcast (H2020-ICT-2016-2 call) under Grant 761498.Gimenez, JJ.; Carcel, JL.; Fuentes, M.; Garro, E.; Elliott, S.; Vargas, D.; Menzel, C.... (2019). 5G New Radio for Terrestrial Broadcast: A Forward-Looking Approach for NR-MBMS. IEEE Transactions on Broadcasting. 65(2):356-368. https://doi.org/10.1109/TBC.2019.291211735636865

Analysis of Channel Blockage of MNSR Reactor Using the System Thermal-Hydraulic Code RELAP5/MOD3.3

The increased extensive use of research reactors and improved regulatory and operational safety requirements have increased the use of more realistic simulations of the plant phenomena involved during steady-state and transient conditions. The earlier adopted conservative model assumptions in the reactor safety analysis which were based on conservatism are now been replaced with best-estimate methodologies. The best-estimate approach aims at providing a detailed realistic description of postulated accident scenarios based on best-available modelling methodologies and numerical solution strategies sufficiently verified against experimental data from differently scaled separate and integral effect test facilities. The core behaviour of Ghana Research Reactor one (GHARR-1) Miniature Neutron Source Reactor (MNSR) during the loss of flow has been investigated. Steady-state and transient analysis were done with best estimate code RELAP5/MOD3.3. The simulated transient characterizes a Loss-of- Flow-Accident (LOFA) type transient. The study forms part of the ongoing core conversion program that is currently ongoing at the facility to convert the reactor from highly-enriched uranium (HEU) to low-enriched uranium (LEU) fuel. Partial and total blockage of coolant to the reactor core transients were performed to study the behaviour of the reactor. It was observed in the case of partial blockage that although boiling occurred in the blocked channels, which lead to increase in both coolant and cladding temperature, the reactor presented a safer steady again due to in-flow of coolant from adjacent channels to the blocked channels. The calculations showed that cladding and coolant temperatures of blocked channels are below the melting point of the assembly. For total blockage the calculations ended abruptly at about 70 s after the start of transient. Therefore we could not observe the whole transient but the observed phenomena indicate unsafe behaviour of the reactor

Aqueous Nile blue: a simple, versatile and safe reagent for the detection of latent fingermarks

Nile blue A in aqueous solution undergoes spontaneous hydrolysis to the photoluminescent compound Nile red. This reagent provides a simple and safe approach to the detection of latent fingermarks on porous and non-porous surfaces

Deep-Learning based segmentation and quantification in experimental kidney histopathology

BACKGROUND: Nephropathologic analyses provide important outcomes-related data in experiments with the animal models that are essential for understanding kidney disease pathophysiology. Precision medicine increases the demand for quantitative, unbiased, reproducible, and efficient histopathologic analyses, which will require novel high-throughput tools. A deep learning technique, the convolutional neural network, is increasingly applied in pathology because of its high performance in tasks like histology segmentation. METHODS: We investigated use of a convolutional neural network architecture for accurate segmentation of periodic acid-Schiff-stained kidney tissue from healthy mice and five murine disease models and from other species used in preclinical research. We trained the convolutional neural network to segment six major renal structures: glomerular tuft, glomerulus including Bowman\u27s capsule, tubules, arteries, arterial lumina, and veins. To achieve high accuracy, we performed a large number of expert-based annotations, 72,722 in total. RESULTS: Multiclass segmentation performance was very high in all disease models. The convolutional neural network allowed high-throughput and large-scale, quantitative and comparative analyses of various models. In disease models, computational feature extraction revealed interstitial expansion, tubular dilation and atrophy, and glomerular size variability. Validation showed a high correlation of findings with current standard morphometric analysis. The convolutional neural network also showed high performance in other species used in research-including rats, pigs, bears, and marmosets-as well as in humans, providing a translational bridge between preclinical and clinical studies. CONCLUSIONS: We developed a deep learning algorithm for accurate multiclass segmentation of digital whole-slide images of periodic acid-Schiff-stained kidneys from various species and renal disease models. This enables reproducible quantitative histopathologic analyses in preclinical models that also might be applicable to clinical studies

Data harmonisation for information fusion in digital healthcare: A state-of-the-art systematic review, meta-analysis and future research directions.

Removing the bias and variance of multicentre data has always been a challenge in large scale digital healthcare studies, which requires the ability to integrate clinical features extracted from data acquired by different scanners and protocols to improve stability and robustness. Previous studies have described various computational approaches to fuse single modality multicentre datasets. However, these surveys rarely focused on evaluation metrics and lacked a checklist for computational data harmonisation studies. In this systematic review, we summarise the computational data harmonisation approaches for multi-modality data in the digital healthcare field, including harmonisation strategies and evaluation metrics based on different theories. In addition, a comprehensive checklist that summarises common practices for data harmonisation studies is proposed to guide researchers to report their research findings more effectively. Last but not least, flowcharts presenting possible ways for methodology and metric selection are proposed and the limitations of different methods have been surveyed for future research

Pressure-based lift estimation and its application to feedforward load control employing trailing-edge flaps

This experimental load control study presents results of an active trailing-edge flap feedforward controller for wind turbine applications. The controller input is derived from pressure-based lift estimation methods that rely either on a quasi-steady method, based on a three-hole probe, or on an unsteady method that is based on three selected surface pressure ports. Furthermore, a standard feedback controller, based on force balance measurements, is compared to the feedforward control. A Clark-Y airfoil is employed for the wing that is equipped with a trailing-edge flap of x/c=30% chordwise extension. Inflow disturbances are created by a two-dimensional active grid. The Reynolds number is Re=290 000, and reduced frequencies of k=0.07 up to k=0.32 are analyzed. Within the first part of the paper, the lift estimation methods are compared. The surface-pressure-based method shows generally more accurate results, whereas the three-hole probe estimate overpredicts the lift amplitudes with increasing frequencies. Nonetheless, employing the latter as input to the feedforward controller is more promising as a beneficial phase lead is introduced by this method. A successful load alleviation was achieved up to reduced frequencies of k=0.192.DFG, 218736457, Experimentelle Untersuchung von Strömungskontrollmethoden zur Lastkontrolle an Windkraftanlagen mittels einer Forschungswindkraftanlage im WindkanalDFG, 414044773, Open Access Publizieren 2021 - 2022 / Technische Universität Berli

Understanding and protecting vulnerable financial consumers

This article considers how consumer protection law and policy should address the interests of particularly vulnerable financial consumers. Specifically, the article proposes a taxonomy of vulnerability which helps to identify (a) what makes consumers particularly vulnerable, and (b) how consumer protection law and consumer policy (broadly understood) can respond to these causes in a way that provides such consumers with appropriate protection. Changes to economic conditions, legal requirements on traders and our understanding of consumer behaviour make discussion of these issues particularly topical. There is little doubt that finding solutions is extremely difficult. Trade-offs are necessary and some enduring factors that contribute to vulnerability, in particular poverty, sometimes appear intractable. Nevertheless, it is submitted that by identifying clearly both why consumers are vulnerable and how the factors that lead to such vulnerability can be addressed, it is possible to construct an environment which respects consumer choice while ensuring that the most vulnerable are protected appropriately

Fish Assemblage Relationships with Physical Habitat in Wadeable Iowa Streams

Fish assemblages play a key role in stream ecosystems and are influenced by physical habitat. We analyzed fish assemblages and physical habitat at 93 randomly selected sites on second- through fifth-order wadeable Iowa streams to explore fish assemblage relationships with reach-scale physical habitat in this agriculturally dominated landscape. Sites were sampled using DC electrofishing and the wadeable streams physical habitat protocol of the U.S. Environmental Protection Agency\u27s Environmental Monitoring and Assessment Program. In all, 82 species were collected, with species richness at sites averaging 14. Over 80% of the sites had fish assemblages rated as fair (53%) or poor (32%) based on a fish index of biotic integrity (FIBI). Ordination separated sites from the two major river drainages along an axis of impairment, with sites in the Missouri River drainage exhibiting lower FIBI scores than sites in the Mississippi River drainage. Physical habitat at most sites exhibited fine substrates, eroding banks, and low-gradient, nonmeandering channel and was dominated by glides. Thirty physical habitat variables describing channel morphology, channel cross section and bank morphology, fish cover, human disturbance, large woody debris, relative bed stability, residual pool, riparian vegetation, and substrate differed significantly between sites with FIBI scores rated as poor and those with FIBI scores rated as good or excellent. Eighteen physical habitat variables were significant predictors of fish assemblage metrics and FIBI in multiple linear regression models, with adjusted R 2 values ranging from 0.12 to 0.58. Seventy percent of the model coefficients reflected substrate (40%), residual pool (21%), and fish cover (9%) variables. Fish assemblages in wadeable Iowa streams are strongly associated with the quality of physical habitat. Thus, understanding and addressing the determinants of physical habitat are crucial for managing streams in Iowa and other agricultural regions