Linking key intervention timing to rapid decline of the COVID-19 effective reproductive number to quantify lessons from mainland China

Effective reproductive numbers (Rt) were calculated from data on the COVID-19 outbreak in China and linked to dates in 2020 when different interventions were enacted. From a maximum of 3.98 before the lockdown in Wuhan City, the values of Rt declined to below 1 by the second week of February, after the construction of hospitals dedicated to COVID-19 patients. The Rt continued to decline following additional measures in line with the policy of “early detection, early report, early quarantine, and early treatment.” The results provide quantitative evaluations of how intervention measures and their timings succeeded, from which lessons can be learned by other countries dealing with future outbreaks

3DShape2VecSet: A 3D Shape Representation for Neural Fields and Generative Diffusion Models

We introduce 3DShape2VecSet, a novel shape representation for neural fields designed for generative diffusion models. Our shape representation can encode 3D shapes given as surface models or point clouds, and represents them as neural fields. The concept of neural fields has previously been combined with a global latent vector, a regular grid of latent vectors, or an irregular grid of latent vectors. Our new representation encodes neural fields on top of a set of vectors. We draw from multiple concepts, such as the radial basis function representation and the cross attention and self-attention function, to design a learnable representation that is especially suitable for processing with transformers. Our results show improved performance in 3D shape encoding and 3D shape generative modeling tasks. We demonstrate a wide variety of generative applications: unconditioned generation, category-conditioned generation, text-conditioned generation, point-cloud completion, and image-conditioned generation.Comment: Accepted by SIGGRAPH 2023 (Journal Track), Project website: https://1zb.github.io/3DShape2VecSet/, Project demo: https://youtu.be/KKQsQccpBF

Large-Scale Green Supplier Selection Approach under a Q-Rung Interval-Valued Orthopair Fuzzy Environment

As enterprises pay more and more attention to environmental issues, the green supply chain management (GSCM) mode has been extensively utilized to guarantee profit and sustainable development. Greensupplierselection(GSS),whichisakeysegmentofGSCM,hasbeeninvestigated to put forward plenty of GSS approaches

Prediction of Water Consumption in Hospitals Based on a Modified Grey GM (0, 1∣sin) Model of Oscillation Sequence: The Example of Wuhan City

Water shortage is one of the main factors limiting urban construction and development. Scientific forecasting of water consumption is an important approach for the rational allocation of water resources. Taking the hospitals in Wuhan City as an example and basing the analysis on the characteristics of actual water consumption, we proposed a modified grey GM (0, 1∣sin) model of oscillation sequence. Using the grey theory, the variable weight-strengthening buffer operator (VWSBO) was introduced into this model to weaken the interference of the disturbance term on the data sequence. The actual quarterly total water consumption data for hospitals in Wuhan City during the period from 2010 to 2012 were used to verify the effectiveness and practicality of this modified grey GM (0, 1∣sin) model in predicting water consumption. In terms of the model’s fitting performance, the mean absolute percentage error (MAPE) of the modified model was 3.77%, indicating a higher prediction accuracy than the traditional grey GM (0, 1∣sin) model of oscillation sequences. Therefore, the modified grey GM (0, 1∣sin) model we established in this study can provide a scientific reference for administrative departments to forecast water consumption

Patent Litigation As a Leading Market Indicator

The purpose of this paper is to introduce patent litigation as a leading indicator of market growth. We model the intensity of patent litigation and the market growth for the personal computer and cellular phone market in the US. By means of these analytic models, we show that patent litigation is a leading indicator to market growth. We are also able to very precisely delineate discrete stages of the product’s market life cycle and demarcate the time when life-cycle transitions are about to take place. We close this paper with a discussion on new lines of patent research that are potentially useful for managerial practice and for investment decisions.Center for Innovation in Product Development at the Massachusetts Institute of Technology

MicroRNA expression profiling in human acute organophosphorus poisoning and functional analysis of dysregulated miRNAs

Objective: Acute organophosphorus(OP) pesticide poisoning is associated with dysfunctions in multiple organs, especially skeletal muscles, the nervous system and the heart. However, little is known about the specific microRNA (miRNA) changes that control the pathophysiological processes of acute OP poisoning damage. We aimed to explore miRNA expression profiles and gain insight into molecular mechanisms of OP toxic effects.Methods: MicroRNA expression was analyzed by TaqMan Human MicroRNA Array analysis and subsequent validated with quantitive PCR. The targets of the significantly different miRNAs were predicted with miRNA prediction databases, and pathway analysis of the predicted target genes was performed using bioinformatics resources.Results: 37 miRNAs were significantly different in the sera of poisoned patients compared to the healthy controls, including 29 miRNAs that were up-regulated and 8 miRNAs that were down-regulated. Functional analysis indicated that many pathways potentially regulated by these miRNAs are involved in skeletal muscle, nervous system and heart disorders.Conclusion: This study mapped changes in the serum miRNA expression profiles of poisoning patients and predicted functional links between miRNAs and their target genes in the regulation of acute OP poisoning. Our findings are an important resource for further understanding the role of these miRNAs in the regulation of OP-induced injury.Keywords: MicroRNA, expression profiles, human, acute organophosphorus pesticide poisoning, signaling pathways

A feedback control model of immunogenic tumours with comprehensive therapy

Surgery is the traditional method for treating cancers, but it often fails to cure patients for complex reasons so new therapeutic approaches that include both surgery and immunotherapy have recently been proposed. These have been shown to be effective, clinically, in inhibiting cancer cells while allowing retention of immunologic memory. This comprehensive strategy is guided by whether a population of tumour cells has or has not exceeded a threshold density. Conditions for successful control of tumours in an immune tumour system were modeled and the related dynamics were addressed. A mathematical model with state-dependent impulsive interventions is formulated to describe combinations of surgery with immunotherapy. By analysing the properties of the Poincar´e map, we examine the global dynamics of the immune tumour system with state-dependent feedback control, including the existence and stability of the semi-trivial order-1 periodic solution and the positive order-k periodic solution. The main results showed that surgery alone can only control the tumour size below a certain level while there is no immunologic memory. If comprehensive therapy involving combining surgery with immunotherapy is considered, then not only can the cancers be controlled below a certain level, but the immune system can also retain its activity. The existence of positive order-k periodic solutions implies that periodical therapy is needed to control the cancers. However, choosing the treatment frequency and the strength of the therapy remains challenging, and hence a strategy of individual-based therapy is suggested

Optimal configuration of hybrid AC/DC urban distribution networks for high penetration renewable energy

Existing AC medium-voltage distribution networks are facing challenges on handling increasing loads and renewable energy integrations. However, it is very difficult to build new distribution lines in urban areas. This study proposes a configuration method of hybrid AC/DC medium-voltage distribution networks, in which some existing AC lines are converted to DC operation. Existing topologies and dispatching scenarios are considered during configuration because the overall power flow can be rescheduled in the hybrid AC/DC distribution network. Therefore, transfer capacities of the lines are fully utilised, and more renewable energies are accommodated. A bi-level programming model is established embedding chance constraint programming to consider the intermittent output of renewable energy. In the upper level, a multiple objective optimal model is proposed in order to balance investments, power losses, and the maximum load level and renewable energy capacity. In the lower level, daily operations of the newly installed VSCs are optimised by a chance constraint programming. The influences of energy storage systems on the configuration are also analysed. Simulation studies are performed to verify the proposed method