Missing Bridge Research Articles

Higher-order interactions between hippocampal CA1 neurons are disrupted in amnestic mice.

Across systems, higher-order interactions between components govern emergent dynamics. Here we tested whether contextual threat memory retrieval in mice relies on higher-order interactions between dorsal CA1 hippocampal neurons requiring learning-induced dendritic spine plasticity. We compared population-level Ca2+ transients as wild-type mice (with intact learning-induced spine plasticity and memory) and amnestic mice (TgCRND8 mice with high levels of amyloid-β and deficits in learning-induced spine plasticity and memory) were tested for memory. Using machine-learning classifiers with different capacities to use input data with complex interactions, our findings indicate complex neuronal interactions in the memory representation of wild-type, but not amnestic, mice. Moreover, a peptide that partially restored learning-induced spine plasticity also restored the statistical complexity of the memory representation and memory behavior in Tg mice. These findings provide a previously missing bridge between levels of analysis in memory research, linking receptors, spines, higher-order neuronal dynamics and behavior.

Train-induced vibration response reconstruction for bridge damage detection with a deep learning methodology

Sensor malfunctions in bridge structural health monitoring system (BSHMS) could cause the missing of measured data, reducing the accuracy of damage detection. It is of great significance to reconstruct the data of faulty sensors with measured data of well-functioning sensors for bridge structural state assessment. In this paper, a train-induced vibration response reconstruction approach for bridge damage detection is proposed. An enhanced deep densely connected neural network (ED-DCNN) introducing a multi-head self-attention mechanism and a skip connection is designed to reconstruct the missing bridge responses, aiming to improve the vibration correlation between the faulty sensors and good sensors and benefit the learning of temporal and spatial features of responses. Then to further validate the accuracy and reliability of the ED-DCNN, an alternate down-sampling residual network (AD-ResNet) is built to identify bridge damage with the complete responses, including the reconstructed ones and the measured, which extracts the structural damage features at different scales utilizing different types of residual blocks in an alternating manner. The efficiency and robustness of the two networks are comprehensively studied using the collected acceleration data from a heavy-haul railway bridge, considering different noise levels. The results demonstrate that under various conditions, the reconstructed responses match the real responses well in time domain, with a low RMSE below 0.4% and a high correlation coefficient of 0.9744, which indicates that the incorporation of a multi-head self-attention module effectively improves the construction of correlations between responses. Additionally, the natural frequencies of bridge are accurately identified from the reconstructed responses. In terms of bridge damage detection, taking both the measured and reconstructed responses as inputs, the identification accuracy obviously improves by 33.57% compared to cases without the reconstructed responses, further emphasizing an excellent reconstruction capability of the ED-DCNN.

The Ontology of Biological Attributes (OBA)—computational traits for the life sciences

Existing phenotype ontologies were originally developed to represent phenotypes that manifest as a character state in relation to a wild-type or other reference. However, these do not include the phenotypic trait or attribute categories required for the annotation of genome-wide association studies (GWAS), Quantitative Trait Loci (QTL) mappings or any population-focussed measurable trait data. The integration of trait and biological attribute information with an ever increasing body of chemical, environmental and biological data greatly facilitates computational analyses and it is also highly relevant to biomedical and clinical applications. The Ontology of Biological Attributes (OBA) is a formalised, species-independent collection of interoperable phenotypic trait categories that is intended to fulfil a data integration role. OBA is a standardised representational framework for observable attributes that are characteristics of biological entities, organisms, or parts of organisms. OBA has a modular design which provides several benefits for users and data integrators, including an automated and meaningful classification of trait terms computed on the basis of logical inferences drawn from domain-specific ontologies for cells, anatomical and other relevant entities. The logical axioms in OBA also provide a previously missing bridge that can computationally link Mendelian phenotypes with GWAS and quantitative traits. The term components in OBA provide semantic links and enable knowledge and data integration across specialised research community boundaries, thereby breaking silos.

A bioelectric neural interface towards intuitive prosthetic control for amputees

Objective. While prosthetic hands with independently actuated digits have become commercially available, state-of-the-art human-machine interfaces (HMI) only permit control over a limited set of grasp patterns, which does not enable amputees to experience sufficient improvement in their daily activities to make an active prosthesis useful. Approach. Here we present a technology platform combining fully-integrated bioelectronics, implantable intrafascicular microelectrodes and deep learning-based artificial intelligence (AI) to facilitate this missing bridge by tapping into the intricate motor control signals of peripheral nerves. The bioelectric neural interface includes an ultra-low-noise neural recording system to sense electroneurography (ENG) signals from microelectrode arrays implanted in the residual nerves, and AI models employing the recurrent neural network (RNN) architecture to decode the subject’s motor intention. Main results. A pilot human study has been carried out on a transradial amputee. We demonstrate that the information channel established by the proposed neural interface is sufficient to provide high accuracy control of a prosthetic hand up to 15 degrees of freedom (DOF). The interface is intuitive as it directly maps complex prosthesis movements to the patient’s true intention. Significance. Our study layouts the foundation towards not only a robust and dexterous control strategy for modern neuroprostheses at a near-natural level approaching that of the able hand, but also an intuitive conduit for connecting human minds and machines through the peripheral neural pathways.Clinical trial: DExterous Hand Control Through Fascicular Targeting (DEFT). Identifier: NCT02994160.

Children and adolescents with epilepsy in rehabilitation centers: A French prospective transversal study

IntroductionThe reason why some children and adolescent with epilepsy (CAWE) still challenge the “inclusive” educative policy needs to be explored. Methods/patientsWe conducted a transversal study in French medical, social, and educative rehab centers (MSERCs) dedicated to CAWE to describe the profile of 263 centers-involved (CI)-CAWE. Centers-involved CAWE were prospectively followed from September 2012 to August 2013. Medical, social, and educative rehab centers were dichotomized according to their care-provider agreement (i.e., CAWE of “moderate” (M) vs. “severe” (S) conditions).Clinical factors known to impact clinical outcome and quality of life (QoL) in epilepsy and four disabling conditions at risk to impact school life (i.e., cognitive and psychiatric/behavioral disorders, risk of physical hazards (i.e., refractory seizures with unpredictable loss of tone and/or awareness), and one or more seizure/week) were evaluated. The electronic chart of the French collaborative database (namely GRENAT) was used for data collection allowing comparison with the profile of 731 “normally integrated and schooled” (NIS)-CAWE extracted from GRENAT and matching for generation (i.e., born between 1988 and 2006). ResultsCenters-involved CAWE's profile was found, after adjustment, to be associated with clinical factors and disabling conditions reflecting the poorest clinical outcome and health-related quality of life (HR-QoL) (all p < 0.001). A cutoff of two disabilities/child highly discriminated NIS-CAWE vs. CI-CAWE. Centers-involved CAWE of S-MSERCs were the most severe (all p < 0.001), and the type of cognitive disability (i.e., intellectual disability (ID) vs. specific learning disorders (SLD)) highly paralleled the types of MSERCs (S vs. M). Using a parent-informant questionnaire, the number of disabilities/child was found to correlate with both the evaluation of the impact of epilepsy (r = 0.47, p < 0.001) and the HR-QoL (r = 0.37, p < 0.001). A satisfactory social life was reported (83.8%) even after S vs. M dichotomization (77.2% vs. 94.7%; p < 0.001). ConclusionMultiple disabilities rather than epilepsy per se challenge the inclusive educative policy. Evaluation of disabilities could be the missing bridge to optimize this policy and understand its limits.

A right to remoteness? A missing bridge and articulations of indigeneity along an East Siberian railroad.

The Soviet Union and its successor states have been avid supporters of a modernisation paradigm aimed at ‘overcoming remoteness’ and ‘bringing civilisation’ to the periphery and its ‘backward’ indigenous people. The Baikal–Amur Mainline (BAM) railroad, built as a much‐hyped prestige project of late socialism, is a good example of that. The BAM has affected indigenous communities and reconfigured the geographic and social space of East Siberia. Our case study, an Evenki village located fairly close to the BAM, is (in)famous today for its supposed refusal to get connected via a bridge to the nearby railroad town. Some actors portray this disconnection as a sign of backwardness, while others celebrate it as the main reason for native language retention and cultural preservation. Focusing on discourses linking the notions of remoteness and cultural revitalisation, the article argues for conceptualising the story of the missing bridge not as the result of political resistance but rather as an articulation of indigeneity, which foregrounds cultural rights over more contentious political claims. Thus, the article explores constellations of remoteness and indigeneity, posing the question whether there might be a moral right to remoteness to be claimed by those who view spatial distance as a potential resource.

Organophosphorus Chemistry without PCl3: A Bridge from Hypophosphorous Acid to H‐Phosphonate Diesters

AbstractA process for the conversion of hypophosphorous acid (H3PO2, HPA) and alcohols into various H‐phosphonate diesters [(RO)2P(O)H] is described. The new reaction provides a missing bridge between HPA and important H‐phosphonates, completely avoiding the use of PCl3. Nickel chloride or nickel on silica catalyze the oxidative phosphorylation of alkyl phosphinates with various alcohols or water. The reaction is atom economic and avoids the formation of waste products. The previous need for both chlorine and base is completely avoided.

Typical deterministic and stochastic bridge deterioration modelling incorporating backward prediction model

A backward prediction model (BPM) has been developed to generate the missing bridge condition ratings in past years, thereby ensuring adequate condition data as required in long-term performance modelling. The BPM establishes a correlation between the known condition ratings and the non-bridge factors, including climate condition, traffic volume and population growth. The aim of this study is to confirm the ability of BPM in improving the prediction accuracy using the existing bridge deterioration models. The prediction accuracies of typical deterministic and stochastic bridge deterioration models are compared when different sets of BPM-generated historical condition ratings are used as input. Comparisons indicate that the prediction error decreases as more historical condition ratings are made available. Notwithstanding the above findings, several limitations of the current deterministic and stochastic bridge deterioration models are also worth noting and further research is essential to improve the prediction accuracy of bridge deterioration modelling.

Hypothesis

Hypothesis