Distribution of user-perceived usefulness of four presentation styles of opinion summarization

In this study, four opinion summarization styles were compared under an experimental environment. Thirty four participants sorted thirty two cards into five usefulness categories. Every eight cards belong to one presentation style. It was found that the users spent the shortest time on cards in “not at all useful” category. The time of viewing “extremely useful” cards was also shorter than that of “somewhat useful”, “useful”, and “very useful” cards. This result can be explained with the components of the usefulness categories. Tag clouds and Aspect oriented sentiments needed less time to view. They are the major styles in “not at all useful” and “extremely useful”. Paragraph summaries and Group samples requested more time and they took at least 50% in “somewhat useful”, “useful”, and “very useful”. The findings are consistent with our previous results

Adaptive recurrent vision performs zero-shot computation scaling to unseen difficulty levels

Humans solving algorithmic (or) reasoning problems typically exhibit solution times that grow as a function of problem difficulty. Adaptive recurrent neural networks have been shown to exhibit this property for various language-processing tasks. However, little work has been performed to assess whether such adaptive computation can also enable vision models to extrapolate solutions beyond their training distribution's difficulty level, with prior work focusing on very simple tasks. In this study, we investigate a critical functional role of such adaptive processing using recurrent neural networks: to dynamically scale computational resources conditional on input requirements that allow for zero-shot generalization to novel difficulty levels not seen during training using two challenging visual reasoning tasks: PathFinder and Mazes. We combine convolutional recurrent neural networks (ConvRNNs) with a learnable halting mechanism based on Graves (2016). We explore various implementations of such adaptive ConvRNNs (AdRNNs) ranging from tying weights across layers to more sophisticated biologically inspired recurrent networks that possess lateral connections and gating. We show that 1) AdRNNs learn to dynamically halt processing early (or late) to solve easier (or harder) problems, 2) these RNNs zero-shot generalize to more difficult problem settings not shown during training by dynamically increasing the number of recurrent iterations at test time. Our study provides modeling evidence supporting the hypothesis that recurrent processing enables the functional advantage of adaptively allocating compute resources conditional on input requirements and hence allowing generalization to harder difficulty levels of a visual reasoning problem without training.Comment: 37th Conference on Neural Information Processing Systems (NeurIPS 2023

CD-GraB: Coordinating Distributed Example Orders for Provably Accelerated Training

Recent research on online Gradient Balancing (GraB) has revealed that there exist permutation-based example orderings that are guaranteed to outperform random reshuffling (RR). Whereas RR arbitrarily permutes training examples, GraB leverages stale gradients from prior epochs to order examples -- achieving a provably faster convergence rate than RR. However, GraB is limited by design: While it demonstrates an impressive ability to scale-up training on centralized data, it does not naturally extend to modern distributed ML workloads. We therefore propose Coordinated Distributed GraB (CD-GraB), which uses insights from prior work on kernel thinning to translate the benefits of provably faster permutation-based example ordering to distributed settings. With negligible overhead, CD-GraB exhibits a linear speedup in convergence rate over centralized GraB and outperforms baselines empirically, including distributed RR, on a variety of benchmark tasks

Activity-dependent neurorehabilitation beyond physical trainings: "mental exercise" through mirror neuron activation

The activity dependent brain repair mechanism has been widely adopted in many types of neurorehabilitation. The activity leads to target specific and non-specific beneficial effects in different brain regions, such as the releasing of neurotrophic factors, modulation of the cytokines and generation of new neurons in adult hood. However physical exercise program clinically are limited to some of the patients with preserved motor functions; while many patients suffered from paralysis cannot make such efforts. Here the authors proposed the employment of mirror neurons system in promoting brain rehabilitation by "observation based stimulation". Mirror neuron system has been considered as an important basis for action understanding and learning by mimicking others. During the action observation, mirror neuron system mediated the direct activation of the same group of motor neurons that are responsible for the observed action. The effect is clear, direct, specific and evolutionarily conserved. Moreover, recent evidences hinted for the beneficial effects on stroke patients after mirror neuron system activation therapy. Finally some music-relevant therapies were proposed to be related with mirror neuron system

Improving statistical inference on pathogen densities estimated by quantitative molecular methods: malaria gametocytaemia as a case study

BACKGROUND: Quantitative molecular methods (QMMs) such as quantitative real-time polymerase chain reaction (q-PCR), reverse-transcriptase PCR (qRT-PCR) and quantitative nucleic acid sequence-based amplification (QT-NASBA) are increasingly used to estimate pathogen density in a variety of clinical and epidemiological contexts. These methods are often classified as semi-quantitative, yet estimates of reliability or sensitivity are seldom reported. Here, a statistical framework is developed for assessing the reliability (uncertainty) of pathogen densities estimated using QMMs and the associated diagnostic sensitivity. The method is illustrated with quantification of Plasmodium falciparum gametocytaemia by QT-NASBA. RESULTS: The reliability of pathogen (e.g. gametocyte) densities, and the accompanying diagnostic sensitivity, estimated by two contrasting statistical calibration techniques, are compared; a traditional method and a mixed model Bayesian approach. The latter accounts for statistical dependence of QMM assays run under identical laboratory protocols and permits structural modelling of experimental measurements, allowing precision to vary with pathogen density. Traditional calibration cannot account for inter-assay variability arising from imperfect QMMs and generates estimates of pathogen density that have poor reliability, are variable among assays and inaccurately reflect diagnostic sensitivity. The Bayesian mixed model approach assimilates information from replica QMM assays, improving reliability and inter-assay homogeneity, providing an accurate appraisal of quantitative and diagnostic performance. CONCLUSIONS: Bayesian mixed model statistical calibration supersedes traditional techniques in the context of QMM-derived estimates of pathogen density, offering the potential to improve substantially the depth and quality of clinical and epidemiological inference for a wide variety of pathogens

Targeted ablation and reorganization of the principal preplate neurons and their neuroblasts identified by golli promoter transgene expression in the neocortex of mice

The present study delineates the cellular responses of dorsal pallium to targeted genetic ablation of the principal preplate neurons of the neocortex. Ganciclovir treatment during prenatal development (E11–E13; where E is embryonic day) of mice selectively killed cells with shared S-phase vulnerability and targeted expression of a GPT [golli promoter transgene, linked to HSV-TK (herpes simplex virus-thymidine kinase), τ-eGFP (τ-enhanced green fluorescent protein) and lacZ (lacZ galactosidase) reporters] localized in preplate neurons. Morphogenetic fates of attacked neurons and neuroblasts, and their successors, were assessed by multiple labelling in time-series comparisons between ablated (HSV-TK+/0) and control (HSV-TK0/0) littermates. During ablation generation, neocortical growth was suppressed, and compensatory reorganization of non-GPT ventricular zone progenitors of dorsal pallium produced replacements for killed GPT neuroblasts. Replacement and surviving GPT neuroblasts then produced replacements for killed GPT neurons. Near-normal restoration of their complement delayed the settlement of GPT neurons into the reconstituted preplate, which curtailed the outgrowth of pioneer corticofugal axons. Based on this evidence, we conclude that specific cell killing in ablated mice can eliminate a major fraction of GPT neurons, with insignificant bystander killing. Also, replacement GPT neurons in ablated mice originate exclusively by proliferation from intermediate progenitor GPT neuroblasts, whose complement is maintained by non-GPT progenitors for inductive regulation of the total complement of GPT neurons. Finally, GPT neurons in both normal and ablated mice meet all morphogenetic criteria, including the ‘outside-in’ vertical gradient of settlement, presently used to identify principal preplate neurons. In ablated mice, delayed organization of these neurons desynchronizes and isolates developing neocortex from the rest of the brain, and permanently impairs its connectivity

Extraction of Antioxidant Effective Components from Black Wheat Bran and Evaluation of its Antioxidant Capacity

Black wheat bran is by-products of the black wheat processing， which is rich in many physiological active substances， including anthocyanins， phenolic acids and dietary fiber. In this study， the antioxidant activity of black wheat bran was extracted with different solvents and its antioxidant capacity was evaluated.The results showed that the dry matter yield of 75% ethanol extract was the highest， which was 10.72%. The content of total phenol extracted by 50% ethanol extract was the highest， which was 2.9 mg/ 100 mL. The scavenging power of DPPH was the strongest in 50% ethanol extract， and the antioxidant extraction capacity of DPPH was the strongest in 75% ethanol extract. 75% acetone extract had the strongest scavenging effect on ABTS， and 75% methanol extract had the strongest antioxidant extraction effect on ABTS. Therefore， the antioxidant capacities of different solvent extracts are different， and the comprehensive comparison shows that 50% ethanol is more suitable for the extraction of antioxidant active components from black wheat bran