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This paper aims to realize an in-situ quality inspection system rapidly for new injection molding (IM) tasks via transfer learning (TL) approach and automation technology.

The proposed in-situ quality inspection system consists of an injection machine, USB camera, programmable logic controller and personal computer, interconnected via OPC or USB communication interfaces. This configuration enables seamless automation of the IM process, real-time quality inspection and automated decision-making. In addition, a MobileNet-based deep learning (DL) model is proposed for quality inspection of injection parts, fine-tuned using the TL approach.

Using the TL approach, the MobileNet-based DL model demonstrates exceptional performance, achieving validation accuracy of 99.1% with the utilization of merely 50 images per category. Its detection speed and accuracy surpass those of DenseNet121-based, VGG16-based, ResNet50-based and Xception-based convolutional neural networks. Further evaluation using a random data set of 120 images, as assessed through the confusion matrix, attests to an accuracy rate of 96.67%.

The proposed MobileNet-based DL model achieves higher accuracy with less resource consumption using the TL approach. It is integrated with automation technologies to build the in-situ quality inspection system of injection parts, which improves the cost-efficiency by facilitating the acquisition and labeling of task-specific images, enabling automatic defect detection and decision-making online, thus holding profound significance for the IM industry and its pursuit of enhanced quality inspection measures.

The purpose of this study is to advance turbulent thermal convection inside the constant heat-flux round tube inserted by multiple perforated twisted tapes.

The novel design of this study is accomplished by inserting several twisted tapes and drilling some circular perforations near the tape edge (C1, C3, C5: solid tapes; C2, C4, C6: perforated tapes). The turbulence flow appearances and thermal convective features are examined for various Reynolds numbers (8,000–14,000) using the renormalization group (RNG) κ−ε turbulent model and Semi-Implicit Method for Pressure-Linked Equations (SIMPLE) algorithm.

The simulated outcomes reveal that inserting more perforated-twisted tapes into the heated round tube promotes turbulent thermal convection effectively. A swirling flow caused by the twisted tapes to produce the secondary flow jets between two reverse-spin tapes can combine with the main flow passing through the perforations at the outer edge to enhance the vortex flow. The primary factors are the quantity of twisted tapes and with/without perforations, as the perforation ratio remains at 2.5 in this numerical work. Weighing friction along the tube, C6 (four reverse-spin perforated-twisted tapes) brings the uppermost thermal-hydraulic performance of 1.23 under Re = 8,000.

The constant thermo-hydraulic attributes of liquid water and the steady Newtonian fluid are research limitations for this simulated work.

The simulated outcomes will avail the inner-pipe design of a heat exchanger inserted by multiple perforated twisted tapes to enhance superior heat transfer.

These twisted tapes form tiny circular perforations along the tape edge to introduce the fluid flow through these bores and combine with the secondary flow induced between two reverse-spin tapes. This scheme enhances the swirling flow, turbulence intensity and fluid mixing to advance thermal convection since larger perforations cannot produce large jet velocity or the position of perforations is too far from the tape edge to generate a separated flow. Consequently, this work contributes a valuable cooling mechanism toward thermal engineering.

Green transition is a long-term direction of corporate development that can achieve sustainable corporate development. This study aims to investigate whether state ownership promotes corporate green transition by mitigating managerial myopia and the impact of environmental regulations, internal controls and ownership on this pathway.

Using data from 2,608 Chinese listed companies for 2010–2019, the authors investigate the relationship between state ownership, managerial myopia and corporate green transition by using fixed-effects and moderated mediation models.

State ownership can boost green transitions and alleviate managerial myopia. Managerial myopia mediates the relationship between state ownership and corporate green transition. Furthermore, environmental regulations, internal controls and ownership moderate the mediating effects of managerial myopia.

The authors construct a multidimensional green transition index to examine the influence of state ownership on corporate green transition behavior and reveal the underlying mechanism by which state ownership promotes green transition by “mitigating managerial myopia.” This study enriches the literature on state ownership, management myopia and green transition and provides important evidence for the promotion of mixed ownership reforms.

The paper examines the historical shifts in policing strategies towards individuals with SMI and vulnerable populations, highlighting the development of co-response models, introducing the concept of “untethered” co-response.

This paper conducts a review of literature to trace the evolution of police responses to individuals with serious mental illness (SMI) and vulnerable populations. It categorizes four generations of police approaches—zero-policing, over-policing, crisis intervention and co-response—and introduces a fifth generation, the “untethered” co-response model exemplified by Project SCOPE in Philadelphia.

The review identifies historical patterns of police response to SMI individuals, emphasizing the challenges and consequences associated with over-policing. It outlines the evolution from crisis intervention teams to co-response models and introduces Project SCOPE as an innovative “untethered” co-response approach.

The research acknowledges the challenges in evaluating the effectiveness of crisis intervention teams and co-response models due to variations in implementation and limited standardized models. It emphasizes the need for more rigorous research, including randomized controlled trials, to substantiate claims about the effectiveness of these models.

The paper suggests that the “untethered” co-response model, exemplified by Project SCOPE, has the potential to positively impact criminal justice and social service outcomes for vulnerable populations. It encourages ongoing policy and evaluative research to inform evidence-based practice and mitigate collateral harms associated with policing responses.

Given the rising interactions between police and individuals with mental health issues, exacerbated by the COVID-19 pandemic, the paper highlights the urgency for innovative, non-policing-driven responses to vulnerable persons.

The paper contributes to the literature by proposing a fifth generation of police response to vulnerable persons, the “untethered” co-response model and presenting Project SCOPE as a practical example.

Pre-positioning and distributing relief items are important parts of disaster management as it simultaneously considers activities from both pre- and post-disaster stages. This study aims to address this problem with a novel mathematical model.

In this research, a bi-objective mixed-integer linear programming model is developed to tackle pre-positioning and distributing relief items, and it is formulated as an integrated location-allocation-routing problem with uncertain parameters. The humanitarian supply chain consists of relief facilities (RFs) and demand points (DPs). Perishable and imperishable relief commodities (RCs), different types of vehicles, different transportation modes, a time window for delivering perishable commodities and the occurrence of unmet demand are considered. A scenario-based game theory is applied for purchasing RCs from different suppliers and an integrated best-worst method-technique for order of preference by similarity to ideal solution technique is implemented to determine the importance of DPs. The proposed model is used to solve several random test problems for verification, and to validate the model, Iran’s flood in 2019 is investigated as a case study for which useful managerial insights are provided.

Managers can effectively adjust their preferences towards response time and total cost of the network and use sensitivity analysis results in their decisions.

The model locates RFs, allocates DPs to RFs in the pre-disaster stage, and determines the routing of RCs from RFs to DPs in the post-disaster stage with respect to minimizing total costs and response time of the humanitarian logistics network.