Braitenberg Vehicles as Developmental Neurosimulation

The connection between brain and behavior is a longstanding issue in the areas of behavioral science, artificial intelligence, and neurobiology. Particularly in artificial intelligence research, behavior is generated by a black box approximating the brain. As is standard among models of artificial and biological neural networks, an analogue of the fully mature brain is presented as a blank slate. This model generates outputs and behaviors from a priori associations, yet this does not consider the realities of biological development and developmental learning. Our purpose is to model the development of an artificial organism that exhibits complex behaviors. We will introduce our approach, which is to use Braitenberg Vehicles (BVs) to model the development of an artificial nervous system. The resulting developmental BVs will generate behaviors that range from stimulus responses to group behavior that resembles collective motion. Next, we will situate this work in the domain of artificial brain networks. Then we will focus on broader themes such as embodied cognition, feedback, and emergence. Our perspective will then be exemplified by three software instantiations that demonstrate how a BV-genetic algorithm hybrid model, multisensory Hebbian learning model, and multi-agent approaches can be used to approach BV development. We introduce use cases such as optimized spatial cognition (vehicle-genetic algorithm hybrid model), hinges connecting behavioral and neural models (multisensory Hebbian learning model), and cumulative classification (multi-agent approaches). In conclusion, we will revisit concepts related to our approach and how they might guide future development.Comment: 32 pages, 8 figures, 2 table

Transformer-Based Multi-Aspect Multi-Granularity Non-Native English Speaker Pronunciation Assessment

Automatic pronunciation assessment is an important technology to help self-directed language learners. While pronunciation quality has multiple aspects including accuracy, fluency, completeness, and prosody, previous efforts typically only model one aspect (e.g., accuracy) at one granularity (e.g., at the phoneme-level). In this work, we explore modeling multi-aspect pronunciation assessment at multiple granularities. Specifically, we train a Goodness Of Pronunciation feature-based Transformer (GOPT) with multi-task learning. Experiments show that GOPT achieves the best results on speechocean762 with a public automatic speech recognition (ASR) acoustic model trained on Librispeech.Comment: Accepted at ICASSP 2022. Code at https://github.com/YuanGongND/gopt Interactive Colab demo at https://colab.research.google.com/github/YuanGongND/gopt/blob/master/colab/GOPT_GPU.ipynb . ICASSP 202

Asynchronous RIS-assisted Localization: A Comprehensive Analysis of Fundamental Limits

The reconfigurable intelligent surface (RIS) has drawn considerable attention for its ability to enhance the performance of not only the wireless communication but also the indoor localization with low-cost. This paper investigates the performance limits of the RIS-based near-field localization in the asynchronous scenario, and analyzes the impact of each part of the cascaded channel on the localization performance. The Fisher information matrix (FIM) and the position error bound (PEB) are derived. Besides, we also derive the equivalent Fisher information (EFI) for the position-related intermediate parameters. Enabled by the derived EFI, we verify that both the ranging and bearing information of the user can be obtained when the near-field model is considered for the RIS-User equipment (UE) part of the channel, while only the direction of the UE can be inferred in the far-field scenario. This result is well known in the scenario that the curvature of arrival (COA) is directly sensed by the traditional active large-scale array, and we prove that it still holds when the COA is sensed passively by the large RIS. For the base station (BS)-RIS part of the channel, we reveal that this part of the channel determines the type of the gain provided by the BS antenna array. Besides, in the single-carrier, single snapshot case, it requires both the BS-RIS and the RIS-UE part of the channel works in the near-field scenario to localize the UE. We also show that the well-known focusing control scheme for RIS, which maximizes the received SNR, is not always a good choice and may degrade the localization performance in the asynchronous scenario. The simulation results validate the analytic work. The impact of the focusing control scheme on the PEB performances under synchronous and asynchronous conditions is also investigated

Genome-Wide Mendelian Randomization Identifies Putatively Causal Gut Microbiota For Multiple Peptic Ulcer Diseases

OBJECTIVE: The pathogenesis of peptic ulcer diseases (PUDs) involves multiple factors, and the contribution of gut microbiota to this process remains unclear. While previous studies have associated gut microbiota with peptic ulcers, the precise nature of the relationship, whether causal or influenced by biases, requires further elucidation. DESIGN: The largest meta-analysis of genome-wide association studies was conducted by the MiBioGen consortium, which provided the summary statistics of gut microbiota for implementation in the Mendelian randomization (MR) analysis. Summary statistics for five types of PUDs were compiled using the FinnGen Consortium R8 release data. Various statistical techniques, including inverse variance weighting (IVW), MR-Egger, weighted median (WM), weighted mode, and simple mode, were employed to assess the causal relationships between gut microbiota and these five PUDs. RESULT: In the intestinal microbiome of 119 known genera, we found a total of 14 causal associations with various locations of PUDs and reported the potential pathogenic bacteria of CONCLUSION: In this study, the pathogenic bacterial genera in the gut microbiota that promote the occurrence of PUDs were found to be causally related. There are multiple correlations between intestinal flora and PUDs, overlapping PUDs have overlapping associated genera. The variance in ulcer-related bacterial genera across different locations underscores the potential influence of anatomical locations and physiological functions

Genome-wide Mendelian randomization identifies putatively causal gut microbiota for multiple peptic ulcer diseases

ObjectiveThe pathogenesis of peptic ulcer diseases (PUDs) involves multiple factors, and the contribution of gut microbiota to this process remains unclear. While previous studies have associated gut microbiota with peptic ulcers, the precise nature of the relationship, whether causal or influenced by biases, requires further elucidation.DesignThe largest meta-analysis of genome-wide association studies was conducted by the MiBioGen consortium, which provided the summary statistics of gut microbiota for implementation in the Mendelian randomization (MR) analysis. Summary statistics for five types of PUDs were compiled using the FinnGen Consortium R8 release data. Various statistical techniques, including inverse variance weighting (IVW), MR-Egger, weighted median (WM), weighted mode, and simple mode, were employed to assess the causal relationships between gut microbiota and these five PUDs.ResultIn the intestinal microbiome of 119 known genera, we found a total of 14 causal associations with various locations of PUDs and reported the potential pathogenic bacteria of Bilophila et al. Among them, four had causal relationships with esophageal ulcer, one with gastric ulcer, three with gastroduodenal ulcer, four with duodenal ulcer, and two with gastrojejunal ulcer.ConclusionIn this study, the pathogenic bacterial genera in the gut microbiota that promote the occurrence of PUDs were found to be causally related. There are multiple correlations between intestinal flora and PUDs, overlapping PUDs have overlapping associated genera. The variance in ulcer-related bacterial genera across different locations underscores the potential influence of anatomical locations and physiological functions

Diagnostic value of cell-free DNA to biliary tract cancers: a meta-analysis

Objective·To comprehensively evaluate the diagnostic accuracy of cell-free DNA (cfDNA) to biliary tract cancer (BTC), and provide a basis for better clinical application.Methods·Clinical studies on the diagnostic value of cfDNA to BTC were collected by searching eight databases from inception to April 2023. The studies were selected according to the inclusion and exclusion criteria, and then data was extracted. The threshold effects were assessed with Spearman′s rank correlation analysis, and heterogeneity among the included studies was analyzed by using Cochran′s Q test and I2 test. A bivariate mixed-effects model was fitted, and statistics such as overall sensitivity, specificity, and area under the curve (AUC) were calculated to determine the diagnostic performance. The subgroup analyses were carried out based on the study type, sample size, detection method, sample source, and diagnostic reference standard.Results·A total of 28 diagnosis tests were included, all of which were evaluated as medium-high quality by using Diagnostic Accuracy Studies Tool Version 2 (QUADAS-2). The presence of threshold effects was found by using the Spearman rank correlation analysis. The pooled sensitivity was 0.80 (95%CI 0.67‒0.88), and specificity was 0.96 (95%CI 0.92‒0.98), positive likelihood ratio (PLR) was 22.7 (95%CI 9.4‒55.2), negative likelihood ratio (NLR) was 0.21 (95%CI 0.12‒0.36), and diagnostic odds ratio (DOR) was 108 (95%CI 31‒374), respectively. The AUC of the summary receiver operating characteristic (SROC) curve was 0.96 (95%CI 0.94‒0.98), demonstrating the high accuracy of cfDNA in the diagnosis of BTC. The results of subgroup analyses suggested that the accuracy and sensitivity of choosing different testing methods and sample sources varied.Conclusion·The detection of cfDNA has high sensitivity and specificity in diagnosing BTC, and is suitable for the patients suspected to be malignant after screening with imaging tests and conventional tumor markers. However, the standardization and uniformity of detection methods and sample sources still need to be further standardized by conducting clinical studies on a wider population

RhoA/Rock activation represents a new mechanism for inactivating Wnt/β-catenin signaling in the aging-associated bone loss

The Wnt/β-catenin signaling pathway appears to be particularly important for bone homeostasis, whereas nuclear accumulation of β-catenin requires the activation of Rac1, a member of the Rho small GTPase family. The aim of the present study was to investigate the role of RhoA/Rho kinase (Rock)-mediated Wnt/β-catenin signaling in the regulation of aging-associated bone loss. We find that Lrp5/6-dependent and Lrp5/6-independent RhoA/Rock activation by Wnt3a activates Jak1/2 to directly phosphorylate Gsk3β at Tyr216, resulting in Gsk3β activation and subsequent β-catenin destabilization. In line with these molecular events, RhoA loss- or gain-of-function in mouse embryonic limb bud ectoderms interacts genetically with Dkk1 gain-of-function to rescue the severe limb truncation phenotypes or to phenocopy the deletion of β-catenin, respectively. Likewise, RhoA loss-of-function in pre-osteoblasts robustly increases bone formation while gain-of-function decreases it. Importantly, high RhoA/Rock activity closely correlates with Jak and Gsk3β activities but inversely correlates with β-catenin signaling activity in bone marrow mesenchymal stromal cells from elderly male humans and mice, whereas systemic inhibition of Rock therefore activates the β-catenin signaling to antagonize aging-associated bone loss. Taken together, these results identify RhoA/Rock-dependent Gsk3β activation and subsequent β-catenin destabilization as a hitherto uncharacterized mechanism controlling limb outgrowth and bone homeostasis

Correction: RhoA/Rock activation represents a new mechanism for inactivating Wnt/β-catenin signaling in the aging-associated bone loss

Correction to "RhoA/Rock activation represents a new mechanism for inactivating Wnt/β-catenin signaling in the aging-associated bone loss

2023 Low-Power Computer Vision Challenge (LPCVC) Summary

This article describes the 2023 IEEE Low-Power Computer Vision Challenge (LPCVC). Since 2015, LPCVC has been an international competition devoted to tackling the challenge of computer vision (CV) on edge devices. Most CV researchers focus on improving accuracy, at the expense of ever-growing sizes of machine models. LPCVC balances accuracy with resource requirements. Winners must achieve high accuracy with short execution time when their CV solutions run on an embedded device, such as Raspberry PI or Nvidia Jetson Nano. The vision problem for 2023 LPCVC is segmentation of images acquired by Unmanned Aerial Vehicles (UAVs, also called drones) after disasters. The 2023 LPCVC attracted 60 international teams that submitted 676 solutions during the submission window of one month. This article explains the setup of the competition and highlights the winners' methods that improve accuracy and shorten execution time.Comment: LPCVC 2023, website: https://lpcv.ai