343 research outputs found
Organizational Learning and Business Model Innovation:the Moderating Role of Network
Many start-ups end up with the failure because they are unable to establish the effective business model. We use the organizational learning theory and network theory to study the mechanism of business model innovation for start-ups. Based on the 256 data of start-ups, the results of PLS structural equation model analysis show that both acquisitive learning and experimental learning can significantly promote the business model innovation. The formal network and informal network play different moderating roles on the relation of organizational learning and business model innovation
G2C: A Generator-to-Classifier Framework Integrating Multi-Stained Visual Cues for Pathological Glomerulus Classification
Pathological glomerulus classification plays a key role in the diagnosis of
nephropathy. As the difference between different subcategories is subtle,
doctors often refer to slides from different staining methods to make
decisions. However, creating correspondence across various stains is
labor-intensive, bringing major difficulties in collecting data and training a
vision-based algorithm to assist nephropathy diagnosis. This paper provides an
alternative solution for integrating multi-stained visual cues for glomerulus
classification. Our approach, named generator-to-classifier (G2C), is a
two-stage framework. Given an input image from a specified stain, several
generators are first applied to estimate its appearances in other staining
methods, and a classifier follows to combine visual cues from different stains
for prediction (whether it is pathological, or which type of pathology it has).
We optimize these two stages in a joint manner. To provide a reasonable
initialization, we pre-train the generators in an unlabeled reference set under
an unpaired image-to-image translation task, and then fine-tune them together
with the classifier. We conduct experiments on a glomerulus type classification
dataset collected by ourselves (there are no publicly available datasets for
this purpose). Although joint optimization slightly harms the authenticity of
the generated patches, it boosts classification performance, suggesting more
effective visual cues are extracted in an automatic way. We also transfer our
model to a public dataset for breast cancer classification, and outperform the
state-of-the-arts significantly.Comment: Accepted by AAAI 201
The impact of social participation on Subjective Wellbeing in the older adult: the mediating role of anxiety and the moderating role of education
IntroductionThe study aims to examine the mediating role of anxiety in the relationship between social participation and Subjective Wellbeing among Chinese older adults. Additionally, it investigates the moderating ed of education in this relationship.MethodsThe data came from the Chinese Longitudinal Healthy Longevity Survey (CLHLS) published by peking University, with a sample size of 10,626 individuals aged 60 years and above. SPSS 21.0 was used for the statistical analysis of the data, and Mplus 8.0 was used for the statistical processing of the mediating and moderating effects analysis.Results(1) The social participation significantly and positively predicated Subjective Wellbeing; (2) Anxiety partially mediated the eect between social participation and Subjective Wellbeing. The mediating eect value was 0.103; (3) Education plays a moderating role in the impact of social participation on subjective Wellbeing.DiscussionIn summary, social participation can reduce the anxiety and enhance their Subjective Wellbeing. Meanwhile, the eet of social participation on Subjective Wellbeing was the greatest for the older adult with high education. The findings suggest that community-led activities can be initiated to improve social participation in the older adult. Furthermore, educational courses could be to support the healthy aging of older adults in China
Global Behavior of the Difference Equation x
We study the following difference equation xn+1=(p+xn-1)/(qxn+xn-1), n=0,1,…, where p,q∈(0,+∞) and the initial conditions x-1,x0∈(0,+∞). We show that every positive solution of the above equation either converges to a finite limit or to a two cycle, which confirms that the Conjecture 6.10.4 proposed by Kulenović and Ladas (2002) is true
Water use pattern of Pinus tabulaeformis in the semiarid region of Loess Plateau, China
Aim of the study: We analyzed the water-use strategy of P. tabulaeformis and determine the relationships between environmental factors and transpiration rates in the P. tabulaeformis woodlands.
Area of study: Loess Plateau region of Northwest China.
Material and Methods: Sap flow density of the P. tabulaeformis trees was measured with Granier-type sensors. Stand transpiration was extrapolated from the sap flow measurements of individual trees using the following Granier equation.
Main results: The mean sap flow rates of individual P. tabulaeformis trees ranged from 9 L day−1 to 54 L day−1. Photosynthetically active radiation and vapor pressure deficit were the dominant driving factors of transpiration when soil water content was sufficient (soil water content>16%), considering that soil water content is the primary factor of influencing transpiration at the driest month of the year. During the entire growing season, the maximum and minimum daily stand transpiration rates were 2.93 and 0.78 mm day−1, respectively. The mean stand transpiration rate was 1.9 mm day−1, and the total stand transpiration from May to September was 294.1 mm.
Research highlights: This study can serve as a basis for detailed analyses of the water physiology and growth of P. tabulaeformis plantation trees for the later application of a climate-driven process model.
Keywords: Sap flow; stand transpiration; environmental factor; Pinus tabulaeformis; Loess Plateau
Prognostic value of pretreatment Controlling Nutritional Status score in esophageal cancer: a meta-analysis
Background and purpose: The association between the pretreatment Controlling Nutritional Status (CONUT) score and the prognosis of esophageal cancer patients remains unclear. The aim of this meta-analysis was to further elucidate the prognostic role of the pretreatment CONUT score in esophageal cancer based on current evidence.Methods: The PubMed, Embase, Web of Science and CNKI databases were searched up to 27 September 2022. The primary and secondary outcomes were overall survival (OS) and progression-free survival (PFS)/cancer-specific survival (CSS), and the hazard ratio (HR) and 95% confidence interval (CI) were pooled for analysis.Results: A total of 11 retrospective studies involving 3,783 participants were included. The pooled results demonstrated that a higher pretreatment CONUT score was significantly related to poor OS (HR = 1.82, 95% CI: 1.31–2.54, p < 0.001), and subgroup analysis stratified by pathological type showed similar results. In addition, the pretreatment CONUT score was associated with poor PFS (HR = 1.19, 95% CI: 1.10–1.28, p < 0.001) and CSS (HR = 2.67, 95% CI: 1.77–4.02, p < 0.001).Conclusion: The pretreatment CONUT score was predictive of worse prognosis in esophageal cancer, and patients with a higher CONUT score showed worse survival
Low Loss and Magnetic Field-tuned Superconducting THz Metamaterial
Superconducting terahertz (THz) metamaterial (MM) made from superconducting
Nb film has been investigated using a continuous-wave THz spectroscopy with a
superconducting split-coil magnet. The obtained quality factors of the resonant
modes at 132 GHz and 450 GHz are about three times as large as those calculated
for a metal THz MM operating at 1 K, which indicates that superconducting THz
MM is a very nice candidate to achieve low loss performance. In addition, the
magnetic field-tuning on superconducting THz MM is also demonstrated, which
offer an alternative tuning method apart from the existed electric, optical and
thermal tuning on THz MM
Perturbed Lipidomic Profiles in Rats With Chronic Cerebral Ischemia Are Regulated by Xiao-Xu-Ming Decoction
Chronic cerebral ischemia (CCI) is a serious human health condition with lacking therapeutic agents. Moreover, its mechanism of action remains elusive, and thus novel treatment options are required. Lipid metabolism disorder are closely related to CCI. In this study, a CCI-rats model was established by the permanent occlusion of rat bilateral common carotid arteries, and then the rats were treated with a Xiao-Xu-Ming decoction (XXMD). Lipidomic profiling was conducted in both plasma and brain o determine the effects of the injury and therapy on lipid metabolism. Sphingolipid (particularly long acyl chain and total ceramides), glyceryl phosphatide, and glyceride profiles significantly changed in the brain after model induction and again after dosing. A total of 35 potential biomarkers were found in the brain and four were found in the plasma, representing both CCI injury and XXMD action. Correlations between endogenous lipids and exogenous XXMD compounds were analyzed using linear regression. Two exogenous compounds (cimifugin and 5-O-methylvisamminol) in the brain and 17 exogenous compounds in the plasma, which may represent the active constituents in XXMD, were significantly associated with lipid metabolism. This study provides a new perspective on the potential mechanism of CCI and its treatment with XXMD, as well as on discovering effective components in traditional Chinese medicines
Terahertz Spin Current Dynamics in Antiferromagnetic Hematite
An important vision of modern magnetic research is to use antiferromagnets (AFMs) as controllable and active ultrafast components in spintronic devices. Hematite (α-Fe2O3) is a promising model material in this respect because its pronounced Dzyaloshinskii-Moriya interaction leads to the coexistence of antiferromagnetism and weak ferromagnetism. Here, femtosecond laser pulses are used to drive terahertz (THz) spin currents from α-Fe2O3 into an adjacent Pt layer. Two contributions to the generation of the spin current with distinctly different dynamics are found: the impulsive stimulated Raman scatting that relies on the AFM order and the ultrafast spin Seebeck effect that relies on the net magnetization. The total THz spin current dynamics can be manipulated by a medium-strength magnetic field below 1 T. The control of the THz spin current achieved in α-Fe2O3 opens the pathway toward tailoring the exact spin current dynamics from ultrafast AFM spin sources
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