Finite Time Performance Analysis of MIMO Systems Identification

This paper is concerned with the finite time identification performance of an n dimensional discrete-time Multiple-Input Multiple-Output (MIMO) Linear Time-Invariant system, with p inputs and m outputs. We prove that the widely-used Ho-Kalman algorithm and Multivariable Output Error State Space (MOESP) algorithm are ill-conditioned for MIMO system when n/m or n/p is large. Moreover, by analyzing the Cramer-Rao bound, we derive a fundamental limit for identifying the real and stable (or marginally stable) poles of MIMO system and prove that the sample complexity for any unbiased pole estimation algorithm to reach a certain level of accuracy explodes superpolynomially with respect to n/(pm). Numerical results are provided to illustrate the ill-conditionedness of Ho-Kalman algorithm and MOESP algorithm as well as the fundamental limit on identification.Comment: 9 pages, 4 figure

MindMap: Knowledge Graph Prompting Sparks Graph of Thoughts in Large Language Models

LLMs usually exhibit limitations in their ability to incorporate new knowledge, the generation of hallucinations, and the transparency of their decision-making process. In this paper, we explore how to prompt LLMs with knowledge graphs (KG), working as a remedy to engage LLMs with up-to-date knowledge and elicit the reasoning pathways from LLMs. Specifically, we build a prompting pipeline that endows LLMs with the capability of comprehending KG inputs and inferring with a combined implicit knowledge and the retrieved external knowledge. In addition, we investigate eliciting the mind map on which LLMs perform the reasoning and generate the answers. It is identified that the produced mind map exhibits the reasoning pathways of LLMs grounded on the ontology of knowledge, hence bringing the prospects of probing and gauging LLM inference in production. The experiments on three question & answering datasets also show that MindMap prompting leads to a striking empirical gain. For instance, prompting a GPT-3.5 with MindMap yields an overwhelming performance over GPT-4 consistently. We also demonstrate that with structured facts retrieved from KG, MindMap can outperform a series of prompting-with-document-retrieval methods, benefiting from more accurate, concise, and comprehensive knowledge from KGs.Comment: 7 pages, 8 figures, 9 table

Graphic characterization and clustering configuration descriptors of determinant space for molecules

Quantum Monte Carlo approaches based on the stochastic sampling of the determinant space have evolved to be powerful methods to compute the electronic states of molecules. These methods not only calculate the correlation energy at an unprecedented accuracy but also provides insightful information on the electronic structure of computed states, e.g. the population, connection, and clustering of determinants, which have not been fully explored. In this work, we devise a configuration graph for visualizing the determinant space, revealing the nature of the molecule's electronic structure. In addition, we propose two analytical descriptors to quantify the extent of configuration clustering of multi-determinant wave functions. The graph and descriptors provide us with a fresh perspective of the electronic structure of molecules and can assist the further development of configuration interaction based electronic structure methods

An Approach to the Production of Soluble Protein from a Fungal Gene Encoding an Aggregation-Prone Xylanase in Escherichia coli

The development of new procedures and protocols that allow researchers to obtain recombinant proteins is of fundamental importance in the biotechnology field. A strategy was explored to overcome inclusion-body formation observed when expressing an aggregation-prone fungal xylanase in Escherichia coli. pHsh is an expression plasmid that uses a synthetic heat-shock (Hsh) promoter, in which gene expression is regulated by an alternative sigma factor (σ32). A derivative of pHsh was constructed by fusing a signal peptide to xynA2 gene to facilitate export of the recombinant protein to the periplasm. The xylanase was produced in a soluble form. Three factors were essential to achieving such soluble expression of the xylanase: 1) the target gene was under the control of the Hsh promoter, 2) the gene product was exported into the periplasm, and 3) gene expression was induced by a temperature upshift. For the first time we report the expression of periplasmic proteins under the control of an Hsh promoter regulated by σ32. One unique feature of this approach was that over 200 copies of the Hsh promoter in an E. coli cell significantly increased the concentration of σ32. The growth inhibition of the recombinant cells corresponded to an increase in the levels of soluble periplasmic protein. Therefore, an alternative protocol was designed to induce gene expression from pHsh-ex to obtain high levels of active soluble enzymes

Gamification of mobile wallet as an unconventional innovation for promoting Fintech:An fsQCA approach

Although digitalisation brings important possibilities to banking &amp; finance service, implementing digital technologies in practices can be challenging. Indeed, the adoption of new innovative technology in the banking &amp; finance sector lags behind other business sectors. Many of the valuable banking &amp; finance-related technologies have not been adopted in relation to the strategic implications of decisions in domains such as the development of service innovation and personalization, value co-creation, and marketing strategies. In particular, there is a paucity of research in using gamification to explore ways of customising banking &amp; finance fintech offerings, improving customers’ experience, and developing efficient banking &amp; finance marketing tactics. Drawing on the UTAUT2 and Otcalysis gamification framework, this study develops a research model investigating what configurations of motivations, expectations and conditions can shape consumers’ behavioral intention to adopt a gamified mobile wallet system. Findings suggest that combining effort expectancy, facilitating conditions and perceived value leads to higher intention to use gamified mobile wallet. Accordingly, firms need to consider the three core conditions when design relevant gamifications.</p

Active travel by built environment and lifecycle stage: Case study of Osaka metropolitan area

Active travel can contribute to physical activity achieved over a day. Previous studies have examined active travel associated with trips in various western countries, but few studies have examined this question for the Asian context. Japan has high levels of cycling, walking and public transport, similar to The Netherlands. Most studies have focused either on children or on adults separately, however, having children in a household will change the travel needs and wants of that household. Thus, here a household lifecycle stage approach is applied. Further, unlike many previous studies, the active travel related to public transport is included. Lastly, further to examining whether the built environment has an influence on the accumulation of active travel minutes, a binary logistic regression examines the built environment's influence on the World Health Organization's recommendations of physical activity. The findings suggest that there is a clear distinction between the urbanized centers and the surrounding towns and unurbanized areas. Further, active travel related to public transport trips is larger than pure walking trips. Females and children are more likely to achieve the WHO recommendations. Finally, car ownership is a strong negative influence

Single-shot compressed ultrafast photography: a review

Compressed ultrafast photography (CUP) is a burgeoning single-shot computational imaging technique that provides an imaging speed as high as 10 trillion frames per second and a sequence depth of up to a few hundred frames. This technique synergizes compressed sensing and the streak camera technique to capture nonrepeatable ultrafast transient events with a single shot. With recent unprecedented technical developments and extensions of this methodology, it has been widely used in ultrafast optical imaging and metrology, ultrafast electron diffraction and microscopy, and information security protection. We review the basic principles of CUP, its recent advances in data acquisition and image reconstruction, its fusions with other modalities, and its unique applications in multiple research fields

Overcoming Recency Bias of Normalization Statistics in Continual Learning: Balance and Adaptation

Continual learning entails learning a sequence of tasks and balancing their knowledge appropriately. With limited access to old training samples, much of the current work in deep neural networks has focused on overcoming catastrophic forgetting of old tasks in gradient-based optimization. However, the normalization layers provide an exception, as they are updated interdependently by the gradient and statistics of currently observed training samples, which require specialized strategies to mitigate recency bias. In this work, we focus on the most popular Batch Normalization (BN) and provide an in-depth theoretical analysis of its sub-optimality in continual learning. Our analysis demonstrates the dilemma between balance and adaptation of BN statistics for incremental tasks, which potentially affects training stability and generalization. Targeting on these particular challenges, we propose Adaptive Balance of BN (AdaB$^2$N), which incorporates appropriately a Bayesian-based strategy to adapt task-wise contributions and a modified momentum to balance BN statistics, corresponding to the training and testing stages. By implementing BN in a continual learning fashion, our approach achieves significant performance gains across a wide range of benchmarks, particularly for the challenging yet realistic online scenarios (e.g., up to 7.68%, 6.86% and 4.26% on Split CIFAR-10, Split CIFAR-100 and Split Mini-ImageNet, respectively). Our code is available at https://github.com/lvyilin/AdaB2N.Comment: Accepted by NeurIPS 202

Melatonin modulates the effects of diethylstilbestrol (DES) on the anterior pituitary of the female Wistar rat.

We studied the anti-tumorigenic effect of melatonin in diethylstilbestrol (DES)-treated anterior pituitaries in rats. Twenty-one female Wistar rats were randomly allocated into three groups: vehicle control rats, DES-treated rats, and DES-treated rats co-administrated with melatonin beginning at week 13. At the end of 16 weeks, rats were weighed and decapitated for morphological studies, including an H+E staining-based score evaluation in regard to cell proliferation, angiogenesis, immunostaining for VEGF, MMP-9, and AQP-1, and electron microscopy. Compared with vehicle, long-term treatment of DES significantly reduced rat body weight and increased H+E score, both of which were counteracted by melatonin. Administration of melatonin also reduced the expression of VEGF and MMP-9, although no changes were detected in AQP-1 expression. In rats cotreated with melatonin, the RER loosened and accumulated more secretion granules. We thus concluded that melatonin can modulate the effects of DES on the rat anterior pituitary by downregulating expression of VEGF and MMP-9 and suppressing the release of secretion granules, suggesting a therapeutic potential in estrogen-induced pituitary malfunctions