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The present study aims to quantify the flow field, flow velocity, and heat transfer features over a horizontal flat plate under the influence of an applied magnetic field, with a particular emphasis on low Prandtl number fluids. Nonlinear partial differential expressions can be incorporated into the ordinary differential framework with the use of appropriate transformations. This research utilizes the variational iteration method (VIM) to approximate solutions for the system of nonlinear differential equations that define the problem. The objective is to demonstrate superior flexibility and broader application of the VIM in addressing heat transfer issues, compared to alternative approaches. The results obtained from the VIM are compared with numerical solutions, revealing a significant level of accuracy in the approximation. The numerical findings strongly suggest that the VIM is effective in providing precise numerical solutions for nonlinear differential equations. The analysis includes an examination of the flow field, velocity, and temperature distribution across various parameters. The study found that improving temperature patterns, velocity distribution, and flow dynamics were all positively impacted by increasing the Prandtl numbers. As a result, this leads to the thickness of the boundary layer to decrease and improves heat transfer at the moving surface. Thus, the convection process becomes more efficient. When the strength of the magnetic field is increased, the velocity of the fluid decreases. This observation aligns with expectations since the magnetic field hampers the natural flow of convection. Notably, the convection process can be precisely controlled by carefully applying magnetic force. [ABSTRACT FROM AUTHOR]

In conventional diesel combustion (CDC), a centrally located multi-hole injector supplies fuel radially outwards. This study introduces and explores the concept of peripheral fuel injection (PeFI) to supply fuel from multiple locations on top of the combustion chamber using several single-hole injectors. The PeFI concept is designed to eliminate flame-wall and jet-wall interactions, and, ideally, to produce independent flames without any interference. PeFI is also intended to increase air entrainment in the near field and thus, reduce equivalence ratio at the lift-off length and subsequent soot formation. PeFI reduces wall heat transfer compared to CDC although this feature is not considered in the present study. The two methods of fuel injection are compared in a non-reacting optical chamber via high-speed imaging of the jets. N-heptane fuel at 1500 bar supply pressures is injected into a test chamber filled with nitrogen at engine relevant ambient densities of 23.0 and 18.5 kg/m3. Four configurations are trialed including a six-hole central injector and six, single-hole PeFI injectors with holes oriented at a layout angle, defined as the angle between the center of the fuel jet and chamber radius, of 0°, 15°, and 30°. Flow visualizations show jet-to-jet interactions at small layout angles for PeFI, but little to no jet-to-jet (or jet-wall) interference as the layout angle increases to 30°. Image analysis reveals that PeFI provides faster rate of injection, longer jet penetration length, greater width near the jet tip, and larger jet volume compared to those for the central injector. Overall, results demonstrate the potential of PeFI to simultaneously improve fuel efficiency and reduce emissions in diesel engines. [ABSTRACT FROM AUTHOR]

Analyses of artificial intelligence (AI) adoption focus on its adoption at the individual task level. What has received significantly less attention is how AI adoption is shaped by the fact that organizations are composed of many interacting tasks. AI adoption may, therefore, require system‐wide change, which is both a constraint and an opportunity. We provide the first formal analysis where multiple tasks may be part of an interdependent system. We find that reliance on AI, a prediction tool, increases decision variation, which, in turn, raises challenges if decisions across the organization interact. Reducing inter‐dependencies between decisions softens that impact and can facilitate AI adoption. However, it does this at the expense of synergies. By contrast, when there are mechanisms for inter‐decision coordination, AI adoption is enhanced when there are more inter‐dependencies. Consequently, we show that there are important cases where AI adoption will be enhanced when it can be adopted beyond tasks but as part of a designed organizational system. [ABSTRACT FROM AUTHOR]

New product innovation in fields like drug discovery and material science can be characterized as combinatorial search over a vast range of possibilities. Modeling innovation as a costly multi-stage search process, we explore how improvements in artificial intelligence (AI) could affect the productivity of the discovery pipeline in allowing improved prioritization of innovations that flow through that pipeline. We show how AI-aided prediction can increase the expected value of innovation and can increase or decrease the demand for downstream testing, depending on the type of innovation, and examine how AI can reduce costs associated with well-defined bottlenecks in the discovery pipeline. [ABSTRACT FROM AUTHOR]

Cyclic variations in conventional diesel combustion engines can lead to large differences in engine out emissions even at steady operation. This study uses an optically accessible constant-pressure flow chamber to acquire fuel injections in quick succession to analyze mixing, auto-ignition, and combustion of diesel-surrogate n-heptane using multiple high-speed optical diagnostics. Prior studies have utilized fewer injections and/or they rely on analysis of ensemble average behavior. These approaches do not yield information on injection-to-injection variation or provide confidence in utilizing individual injection measurements for high-fidelity computational fluid dynamics(CFD) model validation. In this study, a large set of 500 injections is used to obtain global parameters including liquid length, vapor penetration length, ignition delay time, and lift-off length. Results for multiple injections are presented to illustrate large injection to injection variations. Potential sources for these variations are analyzed to conclude localized, small scale turbulence and rate of injection variations as the likely sources. Then, a statistical method based on z-scores is proposed and implemented to identify instantaneous injections that best represent the bulk data-set of jet boundaries measured independently by three different diagnostics. This synthesis of statistics-guided screening of data set and ensemble-average analysis offers higher confidence for CFD model validation relying upon both a representative single and average injection results. [ABSTRACT FROM AUTHOR]

Two-colour pyrometry (2CP) has been used over several decades to study engine-relevant combustion processes, but results are generally regarded as qualitative or semi-quantitative. In many current 2CP systems, large measurement errors are introduced by parallax because the two measured wavelengths are not from the same line of sight. This work presents a spatially-resolved 2CP system with the objective of quantifying and reducing measurement uncertainty. An optical setup that eliminates parallax in 2CP is used together with pixel-by-pixel calibration of the camera sensor to increase measurement accuracy. Primary uncertainty terms are identified, and an error propagation analysis is performed to compute uncertainties in the final results of soot temperature, soot concentration parameter, KL, and soot mass. These methodologies are applied to investigate an auto-igniting fuel spray in a constant pressure flow rig at diesel-like conditions of high ambient pressure and temperature. Results show bias uncertainty of around 200 K (≈10%) for temperature and about 40%â€"60% for KL. High uncertainty was found to occur on the diffusion flame front where both optical thickness and soot concentrations are small. However, these uncertain measurement zones with relatively low soot concentrations contribute minimally to the total soot mass present in the reacting jet during the temporal evolution of the flame. [ABSTRACT FROM AUTHOR]

In this paper, we demonstrate the fabrication of LSPR sensor chips consisting of crystalline gold nanoparticles (AuNPs) over a large area. These crystalline AuNPs were grown on a heated silica substrate via thermal evaporation in a simple single-step fabrication process. To the best of our knowledge, the fabrication of LSPR sensor chips via the growth of crystalline AuNPs has not been demonstrated earlier. We present a process of AuNP growth wherein nanoparticles have been successfully formed for deposition thicknesses up to 40 nm at comparatively lower temperatures than what has been demonstrated earlier. The crystalline AuNPs are formed during the evaporation process, without the requirement of any additional annealing time. The growth of crystalline AuNPs, as proposed in this paper, enables the formation of AuNPs for larger values of equivalent QCM film thicknesses, going up to 40 nm, and possibly even higher. The AuNPs from different values of film thicknesses also allow the tuning of LSPR peak wavelength over a wider range of the visible spectrum. Increased crystallinity was also obtained in the nanoparticles grown at high temperatures and for larger thicknesses. The evaluation of the LSPR sensor chips containing these crystalline AuNPs showed that high surface sensitivity of 28.89 nm/nm was obtained for a conformal thin film layer of Al2O3 over the AuNPs, which is higher than what has been demonstrated earlier. These sensor chips containing crystalline AuNPs also show higher bulk sensitivity than what has been reported previously for AuNPs nanoparticles formed by template-free methods and annealing. [ABSTRACT FROM AUTHOR]

We report a substantially improved localized and bulk sensing response of a plasmonic sensor based on a plasmonic nanopillar array spacer-separated from a plasmonic thin film and operated using the conventional Kretschmann configuration. This paper describes theoretical investigations of the spectral and angular interrogation of the proposed sensors to determine the spectral or angular reflectivity minima. Shifts in the reflectivity minima are determined to obtain information on perturbations in localized (local binding analyte layer sensing) and bulk refractive index (bulk medium sensing) on the sensor surface. Optimization of the structural parameters of the proposed sensor yields a highly enhanced sensor performance, with an extremely high sensitivity (9920 nm RIU−1) and figure of merit (58.2 RIU−1) for bulk sensing response, as well as extremely high sensitivity (76 nm/nm) and figure of merit (0.5 nm−1) for localized sensing response upon spectral interrogation of the sensor. The localized surface sensitivity for the proposed sensor, which is evaluated to be 76 nm/nm, is higher than what has been reported till now. The proposed sensors do not require any sophisticated optical set-ups and can be implemented on the optical setups used for the conventional Kretschmann configuration based sensors. The proposed sensor design could easily be fabricated using the state-of-the-art top-down nanofabrication approaches and could be employed for developing highly sensitive biosensing platforms. [ABSTRACT FROM AUTHOR]

Transient, near-field mixing of a supercritical fluid injected into supercritical and subcritical environments is investigated experimentally. Fuel (propane) from a 100 μm diameter Bosch diesel injector is injected into a high-pressure test rig with a steady flow of heated, low-velocity nitrogen to control the ambient pressure and temperature. The fuel supply pressure is approximately 190 bar, allowing short injections lasting 3–4 ms to be performed in quick succession to acquire statistically significant datasets to represent the unsteady fuel–air mixing. Two test cases with the same ambient density and injector inlet pressure and temperature were chosen in an attempt to isolate effects of mixture phase behavior. Microscopic rainbow Schlieren deflectometry (RSD) is used for visualization and quantitative data acquisition. In the case of the supercritical ambient, the injector inlet and exit and ambient conditions are all supercritical. The RSD analysis reveals a mixing process similar to the single phase fluid mixing, though condensation is also observed locally, and can be explained by the adiabatic mixing theory presented in the paper. For the subcritical ambient case, the injector inlet is supercritical, but the injector exit and ambient conditions are both subcritical. The results show a rapid expansion in the near-field promoting mixing between propane and nitrogen. At downstream locations, significant condensation is also observed as predicted by the adiabatic mixing theory. The supercritical ambient case exhibited longer and narrower jet penetration compared to the subcritical ambient case. [ABSTRACT FROM AUTHOR]

Information asymmetry presents a challenge to equity crowdfunding just as in other markets for equity capital. Investors are less likely to finance startups when it is difficult to assess quality. Syndicates reduce market failures caused by information asymmetry by shifting the focal investment activities of the crowd from startups to lead investors. Syndicates align the incentives of issuers, lead investors, and follow-on investors by providing incentives for lead investors to conduct due diligence, monitor progress, and exploit their reputation. Preliminary evidence foreshadows a meaningful role for syndicates in the allocation of capital to early-stage ventures [ABSTRACT FROM AUTHOR]

Entrepreneurs must choose between alternative strategies for bringing their idea to market. They face uncertainty regarding both the quality of their idea as well as the efficacy of each strategy. Although entrepreneurs can reduce this uncertainty by conducting tests, any single test conflates the signal of the efficacy of the particular strategy and the quality of the idea. Resolving this conflation requires exploring multiple strategies. Consequently, entrepreneurial choice is enhanced by finding ways to lower the cost of testing multiple strategies, receiving guidance as to the types of tests likely to reduce signal conflation, and optimally sequencing tests based on previous beliefs. This creates a role for judgment that may be provided by trusted third parties such as mentors and investors. We hypothesize that institutions that lower the cost of transmitting and aggregating judgment spur entrepreneurial performance. This paper was accepted by David Simchi-Levi, Special Section of Management Science: 65th Anniversary. [ABSTRACT FROM AUTHOR]

Background: The maternal mortality ratio is a significant public health indicator that reflects the quality of health care services. The prevalence is still high in developing countries than in the developed countries. This study aimed to determine the MMR and identify the various risk factors and causes of maternal mortality.Methods: This is a retrospective study conducted in a tertiary care center in Eastern Nepal from 16th July 2015 to 15th July 2020. The maternal mortality ratio was calculated per 100,000 live-births over five year's study period. The causes of death, delays of maternal mortality and, different sociodemographic profiles were analyzed using descriptive statistics.Results: There was a total of 55,667 deliveries conducted during the study period. The calculated maternal mortality ratio is 129.34 per 100,000 live-births in the year 2015 to 2020. The mean age and gestational age of women with maternal deaths were 24.69 ± 5.99 years and 36.15 ± 4.38 weeks of gestation. Obstetric hemorrhage, hypertensive disorder of pregnancy and sepsis were the leading causes of maternal death. The prime contributory factors were delay in seeking health care and reaching health care facility (type I delay:40.9%).Conclusions: Despite the availability of comprehensive emergency obstetric care at our center, maternal mortality is still high and almost 75% of deaths were avoidable. The leading contributory factors of maternal mortality are delay in seeking care and delayed referral from other health facilities. The avoidable causes of maternal mortality are preventable through combined safe motherhood strategies, prompt referral, active management of labor and, puerperium. [ABSTRACT FROM AUTHOR]

Rainbow schlieren deflectometry (RSD) is applied to acquire quantitative concentration measurements in a turbulent environment for the first time. RSD methodology is developed and validated using Rayleigh scattering data available in the literature. Experiments were performed in an initially laminar, momentum-driven helium jet injected into ambient air. Full-field measurements are acquired that span the laminar, transition, and fully turbulent regions of the jet. The RSD results are shown to provide accurate measurements in each region and also confirm the self-similar nature of the fully turbulent jet. Analysis shows that the transition from laminar to turbulent flow occurs across an axial span that decreases with increasing Reynolds number. Experiments with a long exposure time were conducted to evaluate the limitations of hardware averaging of the RSD signal in comparison with software averaging. [ABSTRACT FROM AUTHOR]

Background: Vaginal cuff dehiscence is a rare but potentially grave complication after total hysterectomy. Abdominal or pelvic contents are at risk of evisceration through the vaginal opening. It is associated with significant risk for patient morbidity, such as peritonitis, bowel injury, and sepsis.Case Presentation: We report a case of vaginal cuff dehiscence in a 45-year-old multiparous Taiwanese woman who had undergone abdominal total hysterectomy and presented with vaginal cuff dehiscence precipitated by sexual intercourse. Immediate laparoscopic repair was done. Few authors have reported the utilization of the laparoscopic approach. It allows thorough inspection, visualization, and irrigation of the abdominal cavity. It is also associated with fewer intraoperative and postoperative complications.Conclusion: Laparoscopic repair is a safe treatment option to manage vaginal cuff dehiscence after total hysterectomy. [ABSTRACT FROM AUTHOR]

A significant portion of knowledge generated by university inventors remains latent (uncodified but codifiable), even though this information is valuable to firms that have licensed their inventions and famously strong incentives exist to disseminate academic findings widely. However, the licensee may access and exploit this latent knowledge by engaging the inventor during the development phase. This paper examines the hypothesis that licensing strategies that directly engage the inventor increase the likelihood and degree of commercialization success. While this may seem somewhat apparent, firms in the sample under investigation vary substantially in the degree to which they engage the inventor: one third of the sample does not engage the inventor at all. On the other hand, the hypothesis might seem surprising given the norms of open science under which university labs are expected to operate. Regression analyses based on a unique dataset of 124 license agreements associated with inventions from MIT support the hypothesis and generate results that are robust to a variety of controls. Copyright © 2005 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Recent advances in artificial intelligence are primarily driven by machine learning, a prediction technology. Prediction is useful because it is an input into decision-making. In order to appreciate the impact of artificial intelligence on jobs, it is important to understand the relative roles of prediction and decision tasks. We describe and provide examples of how artificial intelligence will affect labor, emphasizing differences between when the automation of prediction leads to automating decisions versus enhancing decision-making by humans. [ABSTRACT FROM AUTHOR]

Recent advances in artificial intelligence are primarily driven by machine learning, a prediction technology. Prediction is useful because it is an input into decision-making. In order to appreciate the impact of artificial intelligence on jobs, it is important to understand the relative roles of prediction and decision tasks. We describe and provide examples of how artificial intelligence will affect labor, emphasizing differences between when the automation of prediction leads to automating decisions versus enhancing decision-making by humans. [ABSTRACT FROM AUTHOR]