Top Management Team Tenure Diversity and Performance: The Moderating Role of Behavioral Integration

Integrating insights from organizational information processing theory and social categorization theory, we examine how top management team (TMT) tenure diversity affects team performance. We propose a theoretical framework that examines how these two conflicting processes occur simultaneously within diverse TMTs by arguing that TMT tenure variety influences information processing while TMT tenure separation influences the social categorization process. We argue for the presence of nonlinear relationships between tenure variety, tenure separation, and team performance. Furthermore, we propose that these relationships are moderated by the level of TMT behavioral integration. Based on a sample of 357 senior managers from 126 firms in China, we find that both TMT tenure variety and TMT tenure separation have opposing and nonlinear relationships with TMT performance, and the relationship between TMT tenure separation and TMT performance is moderated by the level of TMT behavioral integration. Our results help clarify the conflicting conclusions of previous TMT tenure diversity research. Our findings suggest that the effect of diversity depends on the type of diversity as they affect different processes. Our findings also explain how the opposing effects of both information processing and social categorization can occur simultaneously in the TMT. Furthermore, the effects of both processes are not linear while the level of diversity variety and diversity separation can affect the marginal effects. Finally, TMT behavioral integration processes affect how tenure diversity plays its role in team performance

Enhanced daytime secondary aerosol formation driven by gas-particle partitioning in downwind urban plumes

Anthropogenic emissions from city clusters can significantly enhance secondary organic aerosol (SOA) formation in the downwind regions, while the mechanism is poorly understood. To investigate the effect of pollutants within urban plumes on organic aerosol (OA) evolution, a field campaign was conducted at a downwind site of the Pearl River Delta region of China in the fall of 2019. A time-of-flight chemical ionization mass spectrometer coupled with a Filter Inlet for Gases and Aerosol (FIGAERO-CIMS) was used to probe the gas- and particle-phase molecular composition and thermograms of organic compounds. For air masses influenced by urban pollution, strong daytime SOA formation through gas-particle partitioning was observed, resulting in higher OA volatility. The obvious SOA enhancement was mainly attributed to the equilibrium partitioning of non-condensable (C * ≥ 100.5 μg m-3) organic vapors. We speculated that the elevated NOx concentration could suppress the formation of highly oxidized products, resulting in a smooth increase of condensable (C * < 100.5 μg m-3) organic vapors. Evidence showed that urban pollutants (NOx and VOCs) could enhance the oxidizing capacity, while the elevated VOCs was mainly responsible for promoting daytime SOA formation by increasing the RO2 production rate. Our results highlight the important role of urban anthropogenic pollutants in SOA control in the suburban region

Generative AI for Medical Imaging: extending the MONAI Framework

Recent advances in generative AI have brought incredible breakthroughs in several areas, including medical imaging. These generative models have tremendous potential not only to help safely share medical data via synthetic datasets but also to perform an array of diverse applications, such as anomaly detection, image-to-image translation, denoising, and MRI reconstruction. However, due to the complexity of these models, their implementation and reproducibility can be difficult. This complexity can hinder progress, act as a use barrier, and dissuade the comparison of new methods with existing works. In this study, we present MONAI Generative Models, a freely available open-source platform that allows researchers and developers to easily train, evaluate, and deploy generative models and related applications. Our platform reproduces state-of-art studies in a standardised way involving different architectures (such as diffusion models, autoregressive transformers, and GANs), and provides pre-trained models for the community. We have implemented these models in a generalisable fashion, illustrating that their results can be extended to 2D or 3D scenarios, including medical images with different modalities (like CT, MRI, and X-Ray data) and from different anatomical areas. Finally, we adopt a modular and extensible approach, ensuring long-term maintainability and the extension of current applications for future features

A Novel Postbiotic From Lactobacillus rhamnosus GG With a Beneficial Effect on Intestinal Barrier Function

It has long been known that probiotics can be used to maintain intestinal homeostasis and treat a number of gastrointestinal disorders, but the underlying mechanism has remained obscure. Recently, increasing evidence supports the notion that certain probiotic-derived components, such as bacteriocins, lipoteichoic acids, surface layer protein and secreted protein, have a similar protective role on intestinal barrier function as that of live probiotics. These bioactive components have been named ‘postbiotics’ in the most recent publications. We previously found that the Lactobacillus rhamnosus GG (LGG) culture supernatant is able to accelerate the maturation of neonatal intestinal defense and prevent neonatal rats from oral Escherichia coli K1 infection. However, the identity of the bioactive constituents has not yet been determined. In this study, using liquid chromatography-tandem mass spectrometry analysis, we identified a novel secreted protein (named HM0539 here) involved in the beneficial effect of LGG culture supernatant. HM0539 was recombinated, purified, and applied for exploring its potential bioactivity in vitro and in vivo. Our results showed that HM0539 exhibits a potent protective effect on the intestinal barrier, as reflected by enhancing intestinal mucin expression and preventing against lipopolysaccharide (LPS)- or tumor necrosis factor α (TNF-α)-induced intestinal barrier injury, including downregulation of intestinal mucin (MUC2), zonula occludens-1 (ZO-1) and disruption of the intestinal integrity. Using a neonatal rat model of E. coli K1 infection via the oral route, we verified that HM0539 is sufficient to promote development of neonatal intestinal defense and prevent against E. coli K1 pathogenesis. Moreover, we further extended the role of HM0539 and found it has potential to prevent dextran sulfate sodium (DSS)-induced colitis as well as LPS/D-galactosamine-induced bacterial translocation and liver injury. In conclusion, we identified a novel LGG postbiotic HM0539 which exerts a protective effect on intestinal barrier function. Our findings indicated that HM0539 has potential to become a useful agent for prevention and treatment of intestinal barrier dysfunction- related diseases

Absorbing customer knowledge: how customer involvement enables service design success

Customers are a knowledge resource outside of the firm that can be utilized for new service success by involving them in the design process. However, existing research on the impact of customer involvement (CI) is inconclusive. Knowledge about customers’ needs and on how best to serve these needs (articulated in the service concept) is best obtained from customers themselves. However, codesign runs the risk of losing control of the service concept. This research argues that of the processes of external knowledge, acquisition (via CI), customer knowledge assimilation, and concept transformation form a capability that enables the firm to exploit customer knowledge in the form of a successful new service. Data from a survey of 126 new service projects show that the impact of CI on new service success is fully mediated by customer knowledge assimilation (the deep understanding of customers’ latent needs) and concept transformation (the modification of the service concept due to customer insights). However, its impact is more nuanced. CI exhibits an “∩”-shaped relationship with transformation, indicating there is a limit to the beneficial effect of CI. Its relationship with assimilation is “U” shaped, suggesting a problem with cognitive inertia where initial learnings are ignored. Customer knowledge assimilation directly impacts success, while concept transformation only helps success in the presence of resource slack. An evolving new service design is only beneficial if the firm has the flexibility to adapt to change

Posteriori analysis on IceCube double pulse tau neutrino candidates

The IceCube Neutrino Observatory at the South Pole detects Cherenkov light emitted by charged secondary particles created by primary neutrino interactions. Double pulse waveforms can arise from charged current interactions of astrophysical tau neutrinos with nucleons in the ice and the subsequent decay of tau leptons. The previous 8-year tau double pulse analysis found three tau neutrino candidate events. Among them, the most promising one observed in 2014 is located very near the dust layer in the middle of the detector. A posterior analysis on this event will be presented in this paper, using a new ice model treatment with continuously varying nuisance parameters to do the targeted Monte Carlo re-simulation for tau and other background neutrino ensembles. The impact of different ice models on the expected signal and background statistics will also be discussed

Error-Rate Estimation Based on Multi-Signal Flow Graph Model and Accelerated Radiation Tests.

A method of evaluating the single-event effect soft-error vulnerability of space instruments before launched has been an active research topic in recent years. In this paper, a multi-signal flow graph model is introduced to analyze the fault diagnosis and meantime to failure (MTTF) for space instruments. A model for the system functional error rate (SFER) is proposed. In addition, an experimental method and accelerated radiation testing system for a signal processing platform based on the field programmable gate array (FPGA) is presented. Based on experimental results of different ions (O, Si, Cl, Ti) under the HI-13 Tandem Accelerator, the SFER of the signal processing platform is approximately 10-3(error/particle/cm2), while the MTTF is approximately 110.7 h