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This research introduces a novel integrated model that affiliates the innovative capacity of circular start-ups, as seen through their network-building capabilities, with the influential attribute of top management support as outlined in the T-O-E theory. The investigation employs a quantitative research methodology based on a random sampling technique for the entire research population. The structural equation model, utilizing SMARTPLS, is used on a dataset comprising 231 manufacturing-based circular start-ups and their franchises in India. The findings reveal significant direct and indirect relationships between networkbuilding capabilities and the innovation function of circular start-ups. The study highlights the pivotal role of top management support, following the T-O-E framework, as a complete mediator between network-building capabilities and organizational innovativeness. This inquiry establishes that effective networking and other factors confer a competitive edge upon firms. Furthermore, it contributes to the literature on the circular economy within emerging markets, offering insights applicable across various sectors like IT, hospitality, aviation, pharmaceuticals, and more. The study's implications extend to future researchers and policymakers, advocating for adopting a multi-level perspective to foster and ensure the innovativeness of circular start-ups in diverse industries. [ABSTRACT FROM AUTHOR]

Worldwide, cancer is one of the main causes of mortality and low life expectancy. There is still a gap in the effectiveness of various cancer treatments, despite the fact that several methods have been developed to lower mortality, lessen chronic pain, and enhance quality of life. Early cancer cell diagnosis and high-specificity medication administration to minimize toxicities are essential elements in providing the best possible cancer treatment. Owing to the heightened systemic toxicity and refractoriness associated with traditional cancer diagnostic and treatment instruments, alternative approaches, such as nanotechnology, are being utilized to enhance detection and alleviate the intensity of the disease. Nanotechnology-based immunotherapeutic drugs have been employed for many cancer types throughout the years to lessen the invasiveness of malignant cells while protecting normal cells at the targeting site. This review discusses the various types of nanotechnologies that are commonly used in cancer diagnosis. [ABSTRACT FROM AUTHOR]

Air-borne transmission can pose a major risk of infection spread in enclosed spaces. Venting the air out using exhaust fans and ducts is a common approach to mitigate the risk. In this work, we study the air flow set up by an exhaust fan in a typical shared washroom that can be a potential hot spot for COVID-19 transmission. The primary focus is on the regions of recirculating flow that can harbor infectious aerosol for much longer than the well-ventilated parts of the room. Computational fluid dynamics is used to obtain the steady state air flow field, and Lagrangian tracking of particles gives the spatial and temporal distribution of infectious aerosol in the domain. It is found that the washbasin located next to the door is in a prominent recirculation zone, and particles injected in this region take much longer to be evacuated. The ventilation rate is found to be governed by the air residence time in the recirculation zone, and it is much higher than the timescale based on fully mixed reactor model of the room. Increasing the fan flow rate can reduce the ventilation time, but cannot eliminate the recirculation zones in the washroom. [ABSTRACT FROM AUTHOR]

Aim: To merge the deceased donor (DD) and the paired kidney exchange (PKE) allocation processes, creating a fusion model. Materials and Methods: One of the DD kidneys are allocated to the first patient on the DD wait-list and the other kidney is allocated to the PKE registry to initiate a chain of swap transplants. The last donor of this PKE chain donates his kidney back to the second patient on the DD wait-list. Results: There was a 28.1% (P < 0.05) increase in the total number of transplants in the fusion model as compared to the standalone DD and PKE allocation. The mean gain ranges from 8.29 to 19.3 (P < 0.05) across various allocation groups for the O recipients, which is disadvantaged in the standalone PKE registry. Similarly, the mean gain ranges from 5.8 to 18.1 (P < 0.05) across various allocation groups for the AB recipients, which is disadvantaged in the standalone DD registry Furthermore, no blood group type is worse off in terms of the opportunity to receive a kidney by the fusion model. Conclusions: The fusion model can potentially increase the number of transplants that can be performed whenever a DD become available. Despite fairness considerations for patients and their living donors participating in the fusion model, this process increases the opportunity to receive a kidney as well as reduces transplant waiting time in both the registries. This would translate into a survival advantage for the patients. [ABSTRACT FROM AUTHOR]

Kidney exchange programs (KEPs) aim to find compatible kidneys for recipients with incompatible donors. Patients without a living donor depend upon deceased donor (DD) donations to get a kidney transplant. In India, a ©DD donates kidneys directly to a©DD wait-list. The idea of initiating an exchange chain starting from a ©DD kidney is proposed in a few articles (and executed in Italy in 2018), but no mathematical formulation has been given for this merger. We have introduced an integer programming formulation that creates ©DD-initiated chains, considering both paired exchange registry and ©DD allocations simultaneously and addressing the overlap issue between the exchange registry and ©DD wait-list as recipients can register for both registries independently. A long-term simulation study is done to ©analyse the gain of these DD-initiated chains over time. It suggests that even with small numbers of ©DDs, these chains can significantly increase potential transplants., Competing Interests: No potential conflict of interest was reported by the authors., (© 2023 The Operational Research Society.)