Technology Venture Assessment for Early-Stage Decisions

This research aims to help technology entrepreneurs conduct effective assessments for three important early-stage decisions, namely: (1) whether to pursue a business opportunity, (2) which process to follow to define the launch product to get the business off the ground in the short term, and (3) how to strategically align technology and market development at the early stage to build competitive advantage in the longer term. As previous studies suggest that people make decisions based on judgements of certain questions, this research focuses on understanding: (a) what key questions technology do entrepreneurs consider and what underlying rationale do they follow when making the three focal decisions, and (b) how may technology entrepreneur conduct effective the key questions in an entrepreneurial environment? To understand these two main questions, the researcher selected case studies as the research method and interviewed 20 entrepreneurs from 17 technology-based firms, asking how they approached these three decisions at the early stage of their company’s development. Through case studies, this research (a) identified a set of key questions relating to each focal decision, and (b) proposed a method to help technology entrepreneurs achieve effective these questions. The findings were then developed into a tool to test with technology entrepreneurs and other stakeholders of technology entrepreneurship such as venture capitalists and incubator managers. Their positive feedback verified the main findings and highlighted a number of possible implications of this research. This research contributes to existing knowledge in both practical and theoretical perspectives. Practically, this research helps technology entrepreneurs conduct effective assessments for the three early-stage decisions. With respect to theoretical contributions, this research challenges conventional understandings of ‘what determines decision quality’ by claiming that high quality decisions do not depend principally on accurate answer to key questions, but rather require entrepreneurs’ appropriate understanding of the reliability of the answer they gave.Cambridge Trust; CSC; RADMA; Clare College; Centre for Technology Management, If

Towards universal health coverage: lessons from 10 years of healthcare reform in China.

Universal health coverage (UHC) is driving the global health agenda. Many countries have embarked on national policy reforms towards this goal, including China. In 2009, the Chinese government launched a new round of healthcare reform towards UHC, aiming to provide universal coverage of basic healthcare by the end of 2020. The year of 2019 marks the 10th anniversary of China's most recent healthcare reform. Sharing China's experience is especially timely for other countries pursuing reforms to achieve UHC. This study describes the social, economic and health context in China, and then reviews the overall progress of healthcare reform (1949 to present), with a focus on the most recent (2009) round of healthcare reform. The study comprehensively analyses key reform initiatives and major achievements according to four aspects: health insurance system, drug supply and security system, medical service system and public health service system. Lessons learnt from China may have important implications for other nations, including continued political support, increased health financing and a strong primary healthcare system as basis

Unraveling the Relationship between Content Design and Kinesthetic Learning on Communities of Practice Platforms

As a variant of the sharing economy, Communities of Practice (CoP) platforms have allowed kinesthetic learners to acquire skillsets corresponding to their interests for immediate or future use in practice. However, the impact of digital learning content design on kinesthetic learning remains underexplored in the field of information systems. We hence extend prior research by advancing content richness and structure clarity as antecedents affecting kinesthetic learners’ digestibility of contents, culminating in differential kinesthetic learning effects. To substantiate our arguments, we collected data from a leading Chinese recipe sharing platform. Whereas content richness was measured in terms of readability, verb richness, and prototypicality, structure clarity was operationalized as block structure, block quantity, and block regularity. Employing a machine learning model, we simulated and tested learners’ digestibility of image content embodied within recipes. Plans for future research beyond the current study are also discussed

Effects of Personality on Social Performance in Social Trading

On social trading platforms, the income of leader traders is largely dictated by the number of copy trades conducted by their followers. Consequently, it is imperative for leader traders to exhibit appealing personalities to entice their followers to conduct copy trades. Drawing on social capital theory, we endeavor to scrutinize the effects of traders’ personalities on the accumulation of social capital, which in turn bolsters social performance as measured by the number of copy trades. Data was extracted from a leading social trading platform. The Myers–Briggs Type Indicator personality classification system was then employed to depict leader traders’ personalities based on a novel text-based, machine learning approach. Preliminary analytical results reveal significant relationships among personality traits, social capital dimensions, and social performance. Findings from this study generate insights for social trading platforms and leader traders on exhibiting desirable personalities conducive for accumulating social capital that entice followers to conduct copy trades

Divergent Innovation: Directing the Wisdom of Crowd to Tackle Societal Challenges

Crowdsourcing is acknowledged as a promising avenue for addressing societal challenges by drawing on the wisdom of the crowd to offer diverse solutions to complex problems. Advancing a new conceptual framework of ‘divergent innovation’ which delineates between topic and quality divergence as focal metrics of performance when crowdsourcing for solutions to societal challenges, this study investigates the impacts of four ideation stimuli on divergent innovation. These four stimuli include task description concreteness, resource richness, topic entropy, and judging criteria comprehensiveness. Empirical analysis based on data sourced from an online crowd-ideation platform reveals that task description concreteness negatively affects topic divergence but positively influences quality divergence, whereas resource richness positively affects topic divergence but negatively influences quality divergence. Additionally, the relationship between topic entropy and topic divergence is U-shaped, with no significant impact on quality divergence. These findings contribute to extant literature on crowdsourcing and offer invaluable insights for practitioners

What Went Wrong? Closing the Sim-to-Real Gap via Differentiable Causal Discovery

Training control policies in simulation is more appealing than on real robots directly, as it allows for exploring diverse states in a safe and efficient manner. Yet, robot simulators inevitably exhibit disparities from the real world, yielding inaccuracies that manifest as the simulation-to-real gap. Existing literature has proposed to close this gap by actively modifying specific simulator parameters to align the simulated data with real-world observations. However, the set of tunable parameters is usually manually selected to reduce the search space in a case-by-case manner, which is hard to scale up for complex systems and requires extensive domain knowledge. To address the scalability issue and automate the parameter-tuning process, we introduce an approach that aligns the simulator with the real world by discovering the causal relationship between the environment parameters and the sim-to-real gap. Concretely, our method learns a differentiable mapping from the environment parameters to the differences between simulated and real-world robot-object trajectories. This mapping is governed by a simultaneously-learned causal graph to help prune the search space of parameters, provide better interpretability, and improve generalization. We perform experiments to achieve both sim-to-sim and sim-to-real transfer, and show that our method has significant improvements in trajectory alignment and task success rate over strong baselines in a challenging manipulation task

MyD88-dependent interplay between myeloid and endothelial cells in the initiation and progression of obesity-associated inflammatory diseases.

Low-grade systemic inflammation is often associated with metabolic syndrome, which plays a critical role in the development of the obesity-associated inflammatory diseases, including insulin resistance and atherosclerosis. Here, we investigate how Toll-like receptor-MyD88 signaling in myeloid and endothelial cells coordinately participates in the initiation and progression of high fat diet-induced systemic inflammation and metabolic inflammatory diseases. MyD88 deficiency in myeloid cells inhibits macrophage recruitment to adipose tissue and their switch to an M1-like phenotype. This is accompanied by substantially reduced diet-induced systemic inflammation, insulin resistance, and atherosclerosis. MyD88 deficiency in endothelial cells results in a moderate reduction in diet-induced adipose macrophage infiltration and M1 polarization, selective insulin sensitivity in adipose tissue, and amelioration of spontaneous atherosclerosis. Both in vivo and ex vivo studies suggest that MyD88-dependent GM-CSF production from the endothelial cells might play a critical role in the initiation of obesity-associated inflammation and development of atherosclerosis by priming the monocytes in the adipose and arterial tissues to differentiate into M1-like inflammatory macrophages. Collectively, these results implicate a critical MyD88-dependent interplay between myeloid and endothelial cells in the initiation and progression of obesity-associated inflammatory diseases

Units for Promoter Measurement in Mammalian Cells

The purpose of this RFC is to provide units for the characterization of promoter strength for use in mammalian cells. RMPU is mRNA based and directly proportional to PoPS, whereas REU is protein based and not proportional to PoPS

Study on the Effect of Polyamine Water Treatment Agent on Metal Corrosion Inhibition in Boiler Steam–Water System

A polyamine water treatment agent was prepared with the film-forming amine (N-oleyl-1,3-propylenediamine) and the neutralizing amine (cyclohexanamine) under optimal conditions. The copper sulfate liquid drop experiment showed that a protective film was formed by the polyamine water treatment agent on carbon steel. The analyses of the polarization curve and electrochemical impedance spectroscopy of carbon steel indicated that the polyamine water treatment agent exhibited geometric effects, which could inhibit both anode and cathode reactions of carbon steel, and the corrosion inhibition effect of the polyamine water treatment agent showed an extreme-concentration phenomenon. A metal corrosion experiment in a simulated boiler steam–water system indicated that the polyamine water treatment agent mitigated the corrosion of carbon steel at different temperatures, and the corrosion inhibition rates of the polyamine water treatment agent in liquid and gas environments at 150 °C were 53.84% and 67.43%, respectively, better than that at 350 °C. SEM-EDS characterization indicated that the formation of the corrosion product, iron oxide, on the carbon steel was reduced with the addition of the polyamine water treatment agent in the simulated boiler steam–water system