Design driven user study workshop for Chinese startup innovation

The paper illustrates a serial user study workshop designed for startups seeking disruptive innovation and business opportunities based on the lean process from the point view of user-centered design approach. In the Chinese market, business process moves fast. The product development cycle is relatively short which makes it easy to be interrupted and changed. Making sure the product is targeting the right marketing segment is the key to business success. Therefore, innovation has to be created on the true needs of the accurate end users. User-centered design approaches have the natural advantage to forge innovation by defining the problems of the existing products usage for the users and creating the solution that seamlessly meets the potential demands of the product users. This capability of user-centered design is extremely suitable for the early stage of the startup innovation process especially in the customer identification, market positioning, and business model generation. User study is located in the core of this user-centered innovation process. Performing a good user study ensures the product is aimed at users’ needs, which guarantees once the product is given birth it is already well-positioned in the market sharing. This is the key to the success of startup business. In this paper, a serial workshop covers the topics from what are the user study methods suitable for the lean startup innovation, how to conduct an effective interview, and how to synthesize users’ insights and find new business opportunities. By doing the workshop we try to answer the following questions which ultimately influence the nurturing process in the incubator about how design thinking can intervene to create radical innovation in startup teams: why the design driven user study is so important to the startup business? What is design thinking in the non-design background startuper’s mind and how can they incorporate the mindset in the business operation? What Chinese business environment impacts in the innovation process and how could the startups position the empathy for the users as the key for the product success

Prediction of Gender from Longitudinal MRI data via Deep Learning on Adolescent Data Reveals Unique Patterns Associated with Brain Structure and Change over a Two-year Period

Deep learning algorithms for predicting neuroimaging data have shown considerable promise in various applications. Prior work has demonstrated that deep learning models that take advantage of the data's 3D structure can outperform standard machine learning on several learning tasks. However, most prior research in this area has focused on neuroimaging data from adults. Within the Adolescent Brain and Cognitive Development (ABCD) dataset, a large longitudinal development study, we examine structural MRI data to predict gender and identify gender-related changes in brain structure. Results demonstrate that gender prediction accuracy is exceptionally high (>97%) with training epochs >200 and that this accuracy increases with age. Brain regions identified as the most discriminative in the task under study include predominantly frontal areas and the temporal lobe. When evaluating gender predictive changes specific to a two-year increase in age, a broader set of visual, cingulate, and insular regions are revealed. Our findings show a robust gender-related structural brain change pattern, even over a small age range. This suggests that it might be possible to study how the brain changes during adolescence by looking at how these changes are related to different behavioral and environmental factors

Data-Driven Modeling of Landau Damping by Physics-Informed Neural Networks

Kinetic approaches are generally accurate in dealing with microscale plasma physics problems but are computationally expensive for large-scale or multiscale systems. One of the long-standing problems in plasma physics is the integration of kinetic physics into fluid models, which is often achieved through sophisticated analytical closure terms. In this study, we successfully construct a multi-moment fluid model with an implicit fluid closure included in the neural network using machine learning. The multi-moment fluid model is trained with a small fraction of sparsely sampled data from kinetic simulations of Landau damping, using the physics-informed neural network (PINN) and the gradient-enhanced physics-informed neural network (gPINN). The multi-moment fluid model constructed using either PINN or gPINN reproduces the time evolution of the electric field energy, including its damping rate, and the plasma dynamics from the kinetic simulations. For the first time, we introduce a new variant of the gPINN architecture, namely, gPINN$p$ to capture the Landau damping process. Instead of including the gradients of all the equation residuals, gPINN$p$ only adds the gradient of the pressure equation residual as one additional constraint. Among the three approaches, the gPINN$p$-constructed multi-moment fluid model offers the most accurate results. This work sheds new light on the accurate and efficient modeling of large-scale systems, which can be extended to complex multiscale laboratory, space, and astrophysical plasma physics problems.Comment: 11 pages, 7 figure

Ultra-fast self-assembly and stabilization of reactive nanoparticles in reduced graphene oxide films.

Nanoparticles hosted in conductive matrices are ubiquitous in electrochemical energy storage, catalysis and energetic devices. However, agglomeration and surface oxidation remain as two major challenges towards their ultimate utility, especially for highly reactive materials. Here we report uniformly distributed nanoparticles with diameters around 10 nm can be self-assembled within a reduced graphene oxide matrix in 10 ms. Microsized particles in reduced graphene oxide are Joule heated to high temperature (∼1,700 K) and rapidly quenched to preserve the resultant nano-architecture. A possible formation mechanism is that microsized particles melt under high temperature, are separated by defects in reduced graphene oxide and self-assemble into nanoparticles on cooling. The ultra-fast manufacturing approach can be applied to a wide range of materials, including aluminium, silicon, tin and so on. One unique application of this technique is the stabilization of aluminium nanoparticles in reduced graphene oxide film, which we demonstrate to have excellent performance as a switchable energetic material

Understanding recovery is as important as understanding decline: the case of the crested ibis in China

The wild population of the crested ibis (Nipponia nippon) has recovered remarkably from seven individuals in 1981 to over 7000 in 2021. However, it is unclear how key factors, from endogenous density dependence to exogenous environmental pressure, have contributed to the species’ recovery. We used species distribution models to quantify the contributions of climatic variables, human impact, land form and land use in order to understand the recovery process in the context of prevailing environmental conditions. We also calculated the nest density over the past 39 years to estimate the influence of density dependence on population dynamics. We found that the interaction between rice paddy areas and water bodies (rivers, lakes and ponds) had the highest contribution to nest site selection, whereas linear terms for either rice paddies or water bodies alone had little effect. During its recovery, sub-populations in two watersheds have been constrained by high density and have experienced logistic growth, while other sub-populations in over seven watersheds are growing exponentially. Our models indicate that exogenous environmental factors are more important than density restriction at this stage. In China’s transformed landscape, the crested ibis needs both rice paddies and water bodies to fulfil its annual life cycle. Habitat protection should thus cover both habitat types to ensure the long-term survival of this still endangered species

NerveFormer: A Cross-Sample Aggregation Network for Corneal Nerve Segmentation

The segmentation of corneal nerves in corneal confocal microscopy (CCM) is of great to the quantification of clinical parameters in the diagnosis of eye-related diseases and systematic diseases. Existing works mainly use convolutional neural networks to improve the segmentation accuracy, while further improvement is needed to mitigate the nerve discontinuity and noise interference. In this paper, we propose a novel corneal nerve segmentation network, named NerveFormer, to resolve the above-mentioned limitations. The proposed NerveFormer includes a Deformable and External Attention Module (DEAM), which exploits the Transformer-based Deformable Attention (TDA) and External Attention (TEA) mechanisms. TDA is introduced to explore the local internal nerve features in a single CCM, while TEA is proposed to model global external nerve features across different CCM images. Specifically, to efficiently fuse the internal and external nerve features, TDA obtains the query set required by TEA, thereby strengthening the characterization ability of TEA. Therefore, the proposed model aggregates the learned features from both single-sample and cross-sample, allowing for better extraction of corneal nerve features across the whole dataset. Experimental results on two public CCM datasets show that our proposed method achieves state-of-the-art performance, especially in terms of segmentation continuity and noise discrimination

Dawning public health services dogma:An indigenous Southwest Chinese perspective in managing hypertension-with or without the “BPHS”?

BACKGROUND: To alleviate the rising mortality burden due to hypertension and other non-communicable diseases, a new public health policy initiative in 2009 called the Basic Public Health Services (BPHS). Program was introduced by the Chinese government. The goal of the study is to assess the feasibility and impact of a nationwide health care service—the “BPHS”. METHODS: From January to December 2021, a stratified multistage random sampling method in the survey was conducted to select 6,456 people from 8 cities/districts in Yunnan Province, China, who were above the age of 35 years. 1,521 hypertensive patients were previously aware of their high blood pressure status were matched to the BPHS program database based on ID number and then further divided into BPHS group and non-BPHS (control) group. The results of the current study are based on their responses to a short structured questionnaire, a physical examination, and laboratory tests. The association between BPHS management and its effect on the control of hypertension was estimated using multivariable logistic regression models. We evaluated the accessibility and efficacy of BPHS health care services by analyzing various variables such as blood pressure, BMI, lifestyle modification, anti-hypertensive drugs taken, and cardiovascular risk factors. RESULTS: Among the 1,521 hypertensive patients included in this study, 1,011 (66.5%) were managed by BPHS programme. The multivariable logistic regression model demonstrated that the BPHS facilitated hypertension control (OR = 1.640, 95% CI: 1.237–2.175). A higher proportion of participants receiving lifestyle guidance from the BPHS management showed lowering of total cholesterol. In comparison to the non-BPHS group, those under BPHS management adhered better to antihypertensive medications either single drug (54.3%) or in combination (17.3%) of drugs. Additionally, we also noticed that urban areas with centralized and well-established digital information management system had better hypertension treatment and control. CONCLUSIONS: Nearly two-thirds of the hypertensive patients in Yunnan Province were included in BPHS management. The impact of the national BPHS program was evident in lowering risk factors for cardiovascular diseases, promoting healthy lifestyles, lowering blood pressure, increasing medication adherence, and the better control rate of hypertension

Daratumumab With Cetrelimab, an Anti-PD-1 Monoclonal Antibody, in Relapsed/Refractory Multiple Myeloma

Patients with relapsed or refractory multiple myeloma have an immunosuppressive state with upregulation of programmed death receptor-1 on immune effector cells. Treatment with daratumumab plus cetrelimab, which targets the programmed death receptor-1, was evaluated in 9 patients with relapsed or refractory multiple myeloma. No new safety concerns were identified for the combination. The potential clinical benefit of daratumumab plus cetrelimab remains uncertain. Background: Daratumumab is approved for relapsed or refractory multiple myeloma (RRMM) as monotherapy or in combination regimens. We evaluated daratumumab plus cetrelimab, a programmed death receptor-1 inhibitor, in RRMM. Patients and Methods: This open-label, multiphase study enrolled adults with RRMM with >= 3 prior lines of therapy. Part 1 was a safety run-in phase examining dose-limiting toxicities of daratumumab (16 mg/kg intravenously weekly for cycles 1-2, biweekly for cycles 3-6, and monthly thereafter) plus cetrelimab (240 mg intravenously biweekly, all cycles). In Parts 2 and 3, patients were to be randomized to daratumumab with or without cetrelimab (same schedule as Part 1). Endpoints included safety, overall response rate, pharmacokinetics, and biomarker analyses. Results: Nine patients received daratumumab plus cetrelimab in the safety run-in, and 1 received daratumumab in Part 2 before administrative study termination following a data monitoring committee's global recommendation to stop any trial including daratumumab combined with inhibitors of programmed death receptor-1 or its ligand (programmed death-ligand 1). The median follow-up times were 6.7 months (safety run-in) and 0.3 months (Part 2). No dose-limiting toxicities occurred. All 10 patients had >= 1 treatment-emergent adverse event; 7 patients had grade 3 to 4 treatment-emergent adverse events, and none led to treatment discontinuation or death. In the safety run-in, 7 (77.7%) patients had > 1 infusion-related reaction (most grade 1-2), and 1 had a grade 2 immune-mediated reaction. Among safety run-in patients, the overall response rate was 44.4%. Conclusions: No new safety concerns were identified for daratumumab plus cetrelimab in RRMM. The short study duration and small population limit complete analysis of this combination. (C) 2020 The Author(s). Published by Elsevier Inc