Performance and mechanisms of the Maoist economy: a holistic approach, 1950-1980

This article probes performance and mechanisms of the Maoist economy from 1950 to 1980, a period commonly regarded as a turning point that ushered in a bumpy but new path for China’s new economic fortune, including industrialisation and modernisation. Mao and his government have often been regarded as a developer and moderniser for China. This study questions it. To that end, the Maoist economy is re-conceptualised, re-examined, and re-assessed with qualitative and quantitative evidence including empirical modelling. The key findings suggest that the Maoist economy was a closed one with industrial dependence on agriculture in an urbanrural zero-sum. In the end, despite the official propaganda agriculture declined, industrial workforce stagnated, and the population was poor. This gloomy performance justified the post-Mao reforms and opening up, a game changer that put China on a very different trajectory of growth and development

MULTISCRIPT: Multimodal Script Learning for Supporting Open Domain Everyday Tasks

Automatically generating scripts (i.e. sequences of key steps described in text) from video demonstrations and reasoning about the subsequent steps are crucial to the modern AI virtual assistants to guide humans to complete everyday tasks, especially unfamiliar ones. However, current methods for generative script learning rely heavily on well-structured preceding steps described in text and/or images or are limited to a certain domain, resulting in a disparity with real-world user scenarios. To address these limitations, we present a new benchmark challenge -- MultiScript, with two new tasks on task-oriented multimodal script learning: (1) multimodal script generation, and (2) subsequent step prediction. For both tasks, the input consists of a target task name and a video illustrating what has been done to complete the target task, and the expected output is (1) a sequence of structured step descriptions in text based on the demonstration video, and (2) a single text description for the subsequent step, respectively. Built from WikiHow, MultiScript covers multimodal scripts in videos and text descriptions for over 6,655 human everyday tasks across 19 diverse domains. To establish baseline performance on MultiScript, we propose two knowledge-guided multimodal generative frameworks that incorporate the task-related knowledge prompted from large language models such as Vicuna. Experimental results show that our proposed approaches significantly improve over the competitive baselines.Comment: Accepted by AAAI 2024. 11 pages, 9 figures, 4 table

The Art of SOCRATIC QUESTIONING: Zero-shot Multimodal Reasoning with Recursive Thinking and Self-Questioning

Chain-of-Thought prompting (CoT) enables large-scale language models to solve complex reasoning problems by decomposing the problem and tackling it step-by-step. However, Chain-of-Thought is a greedy thinking process that requires the language model to come up with a starting point and generate the next step solely based on previous steps. This thinking process is different from how humans approach a complex problem e.g., we proactively raise sub-problems related to the original problem and recursively answer them. In this work, we propose Socratic Questioning, a divide-and-conquer fashion algorithm that simulates the self-questioning and recursive thinking process. Socratic Questioning is driven by a Self-Questioning module that employs a large-scale language model to propose sub-problems related to the original problem as intermediate steps and Socratic Questioning recursively backtracks and answers the sub-problems until reaches the original problem. We apply our proposed algorithm to the visual question-answering task as a case study and by evaluating it on three public benchmark datasets, we observe a significant performance improvement over all baselines on (almost) all datasets. In addition, the qualitative analysis clearly demonstrates the intermediate thinking steps elicited by Socratic Questioning are similar to the human's recursively thinking process of a complex reasoning problem.Comment: 15 pages, 12 figure, 2 algorithm

Megasphaera elsdenii Lactate Degradation Pattern Shifts in Rumen Acidosis Models

Background: Megasphaera elsdenii is an ecologically important rumen bacterium that metabolizes lactate and relieves rumen acidosis (RA) induced by a high-grain-diet. Understanding the regulatory mechanisms of the lactate metabolism of this species in RA conditions might contribute to developing dietary strategies to alleviate RA. Methods: Megasphaera elsdenii was co-cultured with four lactate producers (Streptococcus bovis, Lactobacilli fermentum, Butyrivibrio fibrisolvens, and Selenomonas ruminantium) and a series of substrate starch doses (1, 3, and 9 g/L) were used to induce one normal and two RA models (subacute rumen acidosis, SARA and acute rumen acidosis, ARA) under batch conditions. The associations between bacterial competition and the shift of organic acids' (OA) accumulation patterns in both statics and dynamics manners were investigated in RA models. Furthermore, we examined the effects of substrate lactate concentration and pH on Megasphaera elsdenii's lactate degradation pattern and genes related to the lactate utilizing pathways in the continuous culture. Results and Conclusion: The positive growth of M. elsdenii and B. fibrisolvens caused OA accumulation in the SARA model to shift from lactate to butyrate and resulted in pH recovery. Furthermore, both the quantities of substrate lactate and pH had remarkable effects on M. elsdenii lactate utilization due to the transcriptional regulation of metabolic genes, and the lactate utilization in M. elsdenii was more sensitive to pH changes than to the substrate lactate level. In addition, compared with associations based on statics data, associations discovered from dynamics data showed greater significance and gave additional explanations regarding the relationships between bacterial competition and OA accumulation

Hybrid Group IV Nanophotonic Structures Incorporating Diamond Silicon-Vacancy Color Centers

We demonstrate a new approach for engineering group IV semiconductor-based quantum photonic structures containing negatively charged silicon-vacancy (SiV$^-$) color centers in diamond as quantum emitters. Hybrid SiC/diamond structures are realized by combining the growth of nanoand micro-diamonds on silicon carbide (3C or 4H polytype) substrates, with the subsequent use of these diamond crystals as a hard mask for pattern transfer. SiV$^-$ color centers are incorporated in diamond during its synthesis from molecular diamond seeds (diamondoids), with no need for ionimplantation or annealing. We show that the same growth technique can be used to grow a diamond layer controllably doped with SiV$^-$ on top of a high purity bulk diamond, in which we subsequently fabricate nanopillar arrays containing high quality SiV$^-$ centers. Scanning confocal photoluminescence measurements reveal optically active SiV$^-$ lines both at room temperature and low temperature (5 K) from all fabricated structures, and, in particular, very narrow linewidths and small inhomogeneous broadening of SiV$^-$ lines from all-diamond nano-pillar arrays, which is a critical requirement for quantum computation. At low temperatures (5 K) we observe in these structures the signature typical of SiV$^-$ centers in bulk diamond, consistent with a double lambda. These results indicate that high quality color centers can be incorporated into nanophotonic structures synthetically with properties equivalent to those in bulk diamond, thereby opening opportunities for applications in classical and quantum information processing

Case report: Macrophage activation syndrome in a patient with Kabuki syndrome

Macrophage activation syndrome (MAS), is a severe and fatal complication of various pediatric inflammatory disorders. Kabuki syndrome (KS), mainly caused by lysine methyltransferase 2D (KMT2D; OMIM 602113) variants, is a rare congenital disorder with multi-organ deficiencies. To date, there have been no reported cases of MAS in patients with KS. This report describes a case of a 22-year-old male with Kabuki syndrome (KS) who developed MAS. This unique case not only deepens the understanding of the involvement of KMT2D in immune regulation and disease, but expands the phenotype of the adult patient to better understand the natural history, disease burden, and management of patients with KS complicated with autoimmune disorders

Megasphaera elsdenii Lactate Degradation Pattern Shifts in Rumen Acidosis Models

Background:Megasphaera elsdenii is an ecologically important rumen bacterium that metabolizes lactate and relieves rumen acidosis (RA) induced by a high-grain-diet. Understanding the regulatory mechanisms of the lactate metabolism of this species in RA conditions might contribute to developing dietary strategies to alleviate RA.Methods:Megasphaera elsdenii was co-cultured with four lactate producers (Streptococcus bovis, Lactobacilli fermentum, Butyrivibrio fibrisolvens, and Selenomonas ruminantium) and a series of substrate starch doses (1, 3, and 9 g/L) were used to induce one normal and two RA models (subacute rumen acidosis, SARA and acute rumen acidosis, ARA) under batch conditions. The associations between bacterial competition and the shift of organic acids’ (OA) accumulation patterns in both statics and dynamics manners were investigated in RA models. Furthermore, we examined the effects of substrate lactate concentration and pH on Megasphaera elsdenii’s lactate degradation pattern and genes related to the lactate utilizing pathways in the continuous culture.Results and Conclusion: The positive growth of M. elsdenii and B. fibrisolvens caused OA accumulation in the SARA model to shift from lactate to butyrate and resulted in pH recovery. Furthermore, both the quantities of substrate lactate and pH had remarkable effects on M. elsdenii lactate utilization due to the transcriptional regulation of metabolic genes, and the lactate utilization in M. elsdenii was more sensitive to pH changes than to the substrate lactate level. In addition, compared with associations based on statics data, associations discovered from dynamics data showed greater significance and gave additional explanations regarding the relationships between bacterial competition and OA accumulation

Less is More: Learning Reference Knowledge Using No-Reference Image Quality Assessment

Image Quality Assessment (IQA) with reference images have achieved great success by imitating the human vision system, in which the image quality is effectively assessed by comparing the query image with its pristine reference image. However, for the images in the wild, it is quite difficult to access accurate reference images. We argue that it is possible to learn reference knowledge under the No-Reference Image Quality Assessment (NR-IQA) setting, which is effective and efficient empirically. Concretely, by innovatively introducing a novel feature distillation method in IQA, we propose a new framework to learn comparative knowledge from non-aligned reference images. And then, to achieve fast convergence and avoid overfitting, we further propose an inductive bias regularization. Such a framework not only solves the congenital defects of NR-IQA but also improves the feature extraction framework, enabling it to express more abundant quality information. Surprisingly, our method utilizes less input while obtaining a more significant improvement compared to the teacher models. Extensive experiments on eight standard NR-IQA datasets demonstrate the superior performance to the state-of-the-art NR-IQA methods, i.e., achieving the PLCC values of 0.917 (vs. 0.884 in LIVEC) and 0.686 (vs. 0.661 in LIVEFB)

Complete coherent control of silicon vacancies in diamond nanopillars containing single defect centers

Arrays of identical and individually addressable qubits lay the foundation for the creation of scalable quantum hardware such as quantum processors and repeaters. Silicon-vacancy (SiV) centers in diamond offer excellent physical properties such as low inhomogeneous broadening, fast photon emission, and a large Debye–Waller factor. The possibility for all-optical ultrafast manipulation and techniques to extend the spin coherence times makes them promising candidates for qubits. Here, we have developed arrays of nanopillars containing single (SiV) centers with high yield, and we demonstrate ultrafast all-optical complete coherent control of the excited state population of a single SiV center at the optical transition frequency. The high quality of the chemical vapor deposition (CVD) grown SiV centers provides excellent spectral stability, which allows us to coherently manipulate and quasi-resonantly read out the excited state population of individual SiV centers on picosecond timescales using ultrafast optical pulses. This work opens new opportunities to create a scalable on-chip diamond platform for quantum information processing and scalable nanophotonics applications