bluuebunny/crossref_metadata_2025 huggingface dataset:
The Application of a Topology Optimization Algorithm Based on the Kriging Surrogate Model in the Mirror Design and Optimization of an Aerial Camera
Authors: Zhao Yubo , Li Lei
Published: August 2023

In a Cassegrain optical system, the surface precision of the primary mirror is an important factor in the quality of the image. The design of a lightweight primary mirror with a high-quality optical surface is crucial. In this thesis, an integrated mirror light engine design optimization process is proposed for an aviation optoelectronic device. It is based on the Kriging surrogate model and nests the topology optimization algorithm, which constructs the mirror RMS value response surface and obtains the dominant relationship between mirror structure and surface accuracy. The optimal surface figure lightweight structure of the mirror is obtained by optimizing the surrogate model with an additive criterion and multi-objective optimization analysis. The root mean square value (RMS) of the corresponding primary mirror is 10.41 nm, which is better than 1/40 λ (λ = 632.8 nm). This meets the optical design specifications. The optimal primary mirror structure is analyzed by using the finite element method, which verifies the precision of the Kriging surrogate model. It has an error of 0.28%. The kinetic analysis of the primary mirror shows that the primary mirror does not yield to plastic deformation or even failure under a three-way 20 g acceleration load. This meets the environmental suitability requirements.
Object Detection of Small Insects in Time-Lapse Camera Recordings
Authors: Bjerge Kim , Frigaard Carsten Eie , Karstoft Henrik
Published: August 2023

As pollinators, insects play a crucial role in ecosystem management and world food production. However, insect populations are declining, necessitating efficient insect monitoring methods. Existing methods analyze video or time-lapse images of insects in nature, but analysis is challenging as insects are small objects in complex and dynamic natural vegetation scenes. In this work, we provide a dataset of primarily honeybees visiting three different plant species during two months of the summer. The dataset consists of 107,387 annotated time-lapse images from multiple cameras, including 9423 annotated insects. We present a method for detecting insects in time-lapse RGB images, which consists of a two-step process. Firstly, the time-lapse RGB images are preprocessed to enhance insects in the images. This motion-informed enhancement technique uses motion and colors to enhance insects in images. Secondly, the enhanced images are subsequently fed into a convolutional neural network (CNN) object detector. The method improves on the deep learning object detectors You Only Look Once (YOLO) and faster region-based CNN (Faster R-CNN). Using motion-informed enhancement, the YOLO detector improves the average micro F1-score from 0.49 to 0.71, and the Faster R-CNN detector improves the average micro F1-score from 0.32 to 0.56. Our dataset and proposed method provide a step forward for automating the time-lapse camera monitoring of flying insects.
A Novel Catheter Shape-Sensing Method Based on Deep Learning with a Multi-Core Optical Fiber
Authors: Han Fei , He Yanlin , Zhu Hangwei , Zhou Kangpeng
Published: August 2023

In this paper, we propose a novel shape-sensing method based on deep learning with a multi-core optical fiber for the accurate shape-sensing of catheters and guidewires. Firstly, we designed a catheter with embedded multi-core fiber containing three sensing outer cores and one temperature compensation middle core. Then, we analyzed the relationship between the central wavelength shift, the curvature of the multi-core Fiber Bragg Grating (FBG), and temperature compensation methods to establish a Particle Swarm Optimization (PSO) BP neural network-based catheter shape sensing method. Finally, experiments were conducted in both constant and variable temperature environments to validate the method. The average and maximum distance errors of the PSO-BP neural network were 0.57 and 1.33 mm, respectively, under constant temperature conditions, and 0.36 and 0.96 mm, respectively, under variable temperature conditions. This well-sensed catheter shape demonstrates the effectiveness of the shape-sensing method proposed in this paper and its potential applications in real surgical catheters and guidewire.
Illuminating Progress: The Contribution of Bioluminescence to Sustainable Development Goal 6—Clean Water and Sanitation—Of the United Nations 2030 Agenda
Authors: Gregucci Denise , Nazir Faisal , Calabretta Maria Maddalena , Michelini Elisa
Published: August 2023

The United Nations Agenda 2030 Sustainable Development Goal 6 (SDG 6) aims at ensuring the availability and sustainable management of water and sanitation. The routine monitoring of water contaminants requires accurate and rapid analytical techniques. Laboratory analyses and conventional methods of field sampling still require considerable labor and time with highly trained personnel and transport to a central facility with sophisticated equipment, which renders routine monitoring cumbersome, time-consuming, and costly. Moreover, these methods do not provide information about the actual toxicity of water, which is crucial for characterizing complex samples, such as urban wastewater and stormwater runoff. The unique properties of bioluminescence (BL) offer innovative approaches for developing advanced tools and technologies for holistic water monitoring. BL biosensors offer a promising solution by combining the natural BL phenomenon with cutting-edge technologies. This review provides an overview of the recent advances and significant contributions of BL to SDG 6, focusing attention on the potential use of the BL-based sensing platforms for advancing water management practices, protecting ecosystems, and ensuring the well-being of communities.
High-Sensitivity Seismometer Development for Lunar Applications
Authors: de Paula Leandro A. N. , Norton Ronald S. , Paik Ho Jung , Schmerr Nicholas C. , Williamson Paul R. , Chui Talso C. P. , Hahn Inseob
Published: August 2023

Lunar seismology is a critical area of research, providing insights into the Moon’s internal structure, composition, and thermal history, as well as informing the design of safe and resilient habitats for future human settlements. This paper presents the development of a state-of-the-art, three-axis broadband seismometer with a low-frequency range of 0.001–1 Hz and a target sensitivity over one order of magnitude greater than previous Apollo-era instruments. The paper details the design, assembly, methodology, and test results. We compare the acceleration noise of our prototype and commercial seismometers across all three axes. Increasing the test mass and reducing its natural frequency may further improve performance. These advancements in seismometer technology hold promise for enhancing our understanding of the Moon’s and other celestial bodies’ internal structures and for informing the design of future landed missions to ocean worlds.
Accuracy Analysis and Experimental Study of a Six-Dimensional Force Sensor with Circular Flexible Spherical Joints
Authors: Wang Zhijun , Zhang Xiaotao , Li Mengxiang
Published: August 2023

This paper proposed a circular flexible spherical joint to reduce the processing difficulty and manufacturing cost, and design a six-dimensional force sensor based on it. This paper analyzes the influence of the structural parameters of the flexible spherical joints on the accuracy of the six-dimensional force sensor by comparing the force mapping matrix of flexible spherical and ideal spherical joints. As the force mapping matrix is related to the stiffness matrix, the stiffness matrix of a six-dimensional force sensor based on a circular flexible spherical joint and the force mapping matrix of the generalized external force acting on the sensor was derived. Finally, a set of optimal parameters was selected to create a prototype and was verified through finite elements and experiments. The results show that the six-dimensional force sensor with a circular flexible spherical joint has good accuracy and provides some guidance for the design and analysis of the sensor.
Automatic Tree Height Measurement Based on Three-Dimensional Reconstruction Using Smartphone
Authors: Shen Yulin , Huang Ruwei , Hua Bei , Pan Yuanguan , Mei Yong , Dong Minghao
Published: August 2023

Tree height is a crucial structural parameter in forest inventory as it provides a basis for evaluating stock volume and growth status. In recent years, close-range photogrammetry based on smartphone has attracted attention from researchers due to its low cost and non-destructive characteristics. However, such methods have specific requirements for camera angle and distance during shooting, and pre-shooting operations such as camera calibration and placement of calibration boards are necessary, which could be inconvenient to operate in complex natural environments. We propose a tree height measurement method based on three-dimensional (3D) reconstruction. Firstly, an absolute depth map was obtained by combining ARCore and MidasNet. Secondly, Attention-UNet was improved by adding depth maps as network input to obtain tree mask. Thirdly, the color image and depth map were fused to obtain the 3D point cloud of the scene. Then, the tree point cloud was extracted using the tree mask. Finally, the tree height was measured by extracting the axis-aligned bounding box of the tree point cloud. We built the method into an Android app, demonstrating its efficiency and automation. Our approach achieves an average relative error of 3.20% within a shooting distance range of 2–17 m, meeting the accuracy requirements of forest survey.
A Convolutional Autoencoder Based Fault Diagnosis Method for a Hydraulic Solenoid Valve Considering Unknown Faults
Authors: Yoo Seungjin , Jung Joon Ha , Lee Jai-Kyung , Shin Sang Woo , Jang Dal Sik
Published: August 2023

The hydraulic solenoid valve is an essential electromechanical component used in various industries to control the flow rate, pressure, and direction of hydraulic fluid. However, these valves can fail due to factors like electrical issues, mechanical wear, contamination, seal failure, or improper assembly; these failures can lead to system downtime and safety risks. To address hydraulic solenoid valve failure, and its related impacts, this study aimed to develop a nondestructive diagnostic technology for rapid and accurate diagnosis of valve failures. The proposed approach is based on a data-driven model that uses voltage and current signals measured from normal and faulty valve samples. The algorithm utilizes a convolutional autoencoder and hypersphere-based clustering of the latent variables. This clustering approach helps to identify patterns and categorize the samples into distinct groups, normal and faulty. By clustering the data into groups of hyperspheres, the algorithm identifies the specific fault type, including both known and potentially new fault types. The proposed diagnostic model successfully achieved an accuracy rate of 98% in classifying the measurement data, which were augmented with white noise across seven distinct fault modes. This high accuracy demonstrates the effectiveness of the proposed diagnosis method for accurate and prompt identification of faults present in actual hydraulic solenoid valves.
Evaluation of the Resolution in Inverse Scattering of Dielectric Cylinders for Medical Applications
Authors: Akbari Sekehravani Ehsan , Leone Giovanni
Published: August 2023

The inverse scattering problem has numerous significant applications, including in geophysical explorations, medical imaging, and radar imaging. To achieve better performance of the imaging system, theoretical knowledge of the resolution of the algorithm is required for most of these applications. However, analytical investigations about the resolution presently feel inadequate. In order to estimate the achievable resolution, we address the point spread function (PSF) evaluation of the scattered field for a single frequency and the multi-view case both for the near and the far fields and the scalar case when the angular domain of the incident field and observation ranges is a round angle. Instead of the common free space condition, an inhomogeneous background medium, consisting of a homogeneous dielectric cylinder with a circular cross-section in free space, is assumed. In addition, since the exact evaluation of the PSF can only be accomplished numerically, an analytical approximation of the resolution is also considered. For the sake of its comparison, the truncated singular value decomposition (TSVD) algorithm can be used to implement the exact PSF. We show how the behavior of the singular values and the resolution change by varying the permittivity of the background medium. The usefulness of the theoretical discussion is demonstrated in localizing point-like scatterers within a dielectric cylinder, so mimicking a scenario that may occur in breast cancer imaging. Numerical results are provided to validate the analytical investigations.
A Novel Tandem Differential Edge Sensor Layout for Segmented Mirror Telescopes
Authors: Huo Yinlong , Yang Fei , Wang Fuguo , Guo Peng , Zhu Jiakang , Liu Yuanguo
Published: August 2023

The performance of an active control system, crucial for the co-phase maintenance of segmented mirrors, is closely related to the spatial layout of sensors and actuators. This article compares two types of edge sensor layouts, vertical and horizontal, and proposes a novel tandem differential sensor layout that saves layout space and reduces the number of positioning references. The control performance of this scheme is analyzed in terms of error propagation, mode representation, and the scalable construction of the control matrix. Finally, we constructed a tandem differential-based sensor detection system to examine the performance of edge sensors and the effect of laboratory environmental variables on sensor measurements. Simulations and experiments demonstrate that this scheme has the same ability to fully characterize actuator modification modes as the Keck edge sensor layout. Although the total error multiplier is slightly larger than the latter, it has fewer scalable control matrix types and stronger spatial and segmental shape adaptation capabilities. Actual measurements show that the sensor’s own noise in a tandem differential layout is less than 20 nm, which meets the requirements for future segmented co-phase maintenance. This layout type can potentially be applied to future small and medium-sized segmented splices.
Simulation and Experimentation of a Grounding Network Detection Scheme Based on a Low-Frequency Electromagnetic Method
Authors: Duan Qingming , Zou Bofeng , Song Yuxin , Liu Yuxiang , Zhang Ruipeng
Published: August 2023

The grounding network is a significant component of substations, and the corrosion of its ground resistance is predominantly detected using the electromagnetic method. However, the application of electromagnetic methods for detecting corrosion within earthing networks has received relatively limited attention in research. Currently, the prevailing method utilizes electromagnetic techniques to identify the breakage points within the given earthing network. In this study, we propose a corrosion detection method for grounding networks based on the low-frequency electromagnetic method, which measures the resistance value between individual nodes of the network. Specifically, an excitation source signal of a predetermined frequency was transmitted to the measurement segment of the grounding network, which facilitated the direct measurement of the strength of the induced magnetic field above the center of the measuring conductor. The recorded electromagnetic data were subsequently uploaded to the host computer for data processing, and the computer interface was constructed based on a LABVIEW design. By leveraging the relationship between the induced electric potential, current strength, excitation source strength, and additional voltage detection devices, the resistance of the conductor under examination could be determined. Furthermore, the proposed method was tested under suitable conditions, and it demonstrated favorable results. Thus, the proposed method can serve as a foundation for developing electromagnetic testing instruments tailored to the investigated grounding network.
P-CSEM: An Attention Module for Improved Laparoscopic Surgical Tool Detection
Authors: Arabian Herag , Abdulbaki Alshirbaji Tamer , Jalal Nour Aldeen , Krueger-Ziolek Sabine , Moeller Knut
Published: August 2023

Minimal invasive surgery, more specifically laparoscopic surgery, is an active topic in the field of research. The collaboration between surgeons and new technologies aims to improve operation procedures as well as to ensure the safety of patients. An integral part of operating rooms modernization is the real-time communication between the surgeon and the data gathered using the numerous devices during surgery. A fundamental tool that can aid surgeons during laparoscopic surgery is the recognition of the different phases during an operation. Current research has shown a correlation between the surgical tools utilized and the present phase of surgery. To this end, a robust surgical tool classifier is desired for optimal performance. In this paper, a deep learning framework embedded with a custom attention module, the P-CSEM, has been proposed to refine the spatial features for surgical tool classification in laparoscopic surgery videos. This approach utilizes convolutional neural networks (CNNs) integrated with P-CSEM attention modules at different levels of the architecture for improved feature refinement. The model was trained and tested on the popular, publicly available Cholec80 database. Results showed that the attention integrated model achieved a mean average precision of 93.14%, and visualizations revealed the ability of the model to adhere more towards features of tool relevance. The proposed approach displays the benefits of integrating attention modules into surgical tool classification models for a more robust and precise detection.
Flexible Data Rate Allocation Using Non-Orthogonal Multiple Access (NOMA) in a Mode Division Multiplexing (MDM) Optical Power Splitter for System-on-Chip Networks
Authors: Lin Yuan-Zeng , Chow Chi-Wai , Yu Tien-Wei , Jian Yin-He , Hung Tun-Yao , Chen Jian-Wen , Yeh Chien-Hung
Published: August 2023

We put forward and demonstrate a silicon photonics (SiPh)-based mode division multiplexed (MDM) optical power splitter that supports transverse-electric (TE) single-mode, dual-mode, and triple-mode (i.e., TE0, TE1, and TE2). An optical power splitter is needed for optical signal distribution and routing in optical interconnects. However, a traditional optical splitter only divides the power of the input optical signal. This means the same data information is received at all the output ports of the optical splitter. The powers at different output ports may change depending on the splitting ratio of the optical splitter. The main contributions of our proposed optical splitter are: (i) Different data information is received at different output ports of the optical splitter via the utilization of NOMA. By adjusting the power ratios of different channels in the digital domain (i.e., via software control) at the Tx, different channel data information can be received at different output ports of the splitter. It can increase the flexibility of optical signal distribution and routing. (ii) Besides, the proposed optical splitter can support the fundamental TE0 mode and the higher modes TE1, TE2, etc. Supporting mode-division multiplexing and multi-mode operation are important for future optical interconnects since the number of port counts is limited by the chip size. This can significantly increase the capacity besides wavelength division multiplexing (WDM) and spatial division multiplexing (SDM). The integrated SiPh MDM optical power splitter consists of a mode up-conversion section implemented by asymmetric directional couplers (ADCs) and a Y-branch structure for MDM power distribution. Here, we also propose and discuss the use of the Genetic algorithm (GA) for the MDM optical power splitter parameter optimization. Finally, to provide adjustable data rates at different output ports after the MDM optical power splitter, non-orthogonal multiple access—orthogonal frequency division multiplexing (NOMA-OFDM) is also employed. Experimental results validate that, in three modes (TE0, TE1, and TE2), user-1 and user-2 achieve data rates of (user-1: greater than 22 Gbit/s; user-2: greater than 12 Gbit/s) and (user-1: greater than 12 Gbit/s; user-2: 24 Gbit/s), respectively, at power-ratio (PR) = 2.0 or 3.0. Each channel meets the hard-decision forward-error-correction (HD-FEC, i.e., BER = 3.8 × 10−3) threshold. The proposed method allows flexible data rate allocation for multiple users for optical interconnects and system-on-chip networks.
A Comparison of Walking Behavior during the Instrumented TUG and Habitual Gait
Authors: Agathos Catherine P. , Velisar Anca , Shanidze Natela M.
Published: August 2023

The timed up and go test (TUG) is a common clinical functional balance test often used to complement findings on sensorimotor changes due to aging or sensory/motor dysfunction. The instrumented TUG can be used to obtain objective postural and gait measures that are more sensitive to mobility changes. We investigated whether gait and body coordination during TUG is representative of walking. We examined the walking phase of the TUG and compared gait metrics (stride duration and length, walking speed, and step frequency) and head/trunk accelerations to normal walking. The latter is a key aspect of postural control and can also reveal changes in sensory and motor function. Forty participants were recruited into three groups: young adults, older adults, and older adults with visual impairment. All performed the TUG and a short walking task wearing ultra-lightweight wireless IMUs on the head, chest, and right ankle. Gait and head/trunk acceleration metrics were comparable across tasks. Further, stride length and walking speed were correlated with the participants’ age. Those with visual impairment walked significantly slower than sighted older adults. We suggest that the TUG can be a valuable tool for examining gait and stability during walking without the added time or space constraints.
Pseudolites to Support Location Services in Smart Cities: Review and Prospects
Authors: Liu Tong , Liu Jian , Wang Jing , Zhang Heng , Zhang Bing , Ma Yongchao , Sun Mengfei , Lv Zhiping , Xu Guochang
Published: August 2023

The location service is an important part of the smart city. A unified location service for outdoor and indoor/overground and underground activity will assist the construction of smart cities. However, with different coordinate systems and data formats, it is difficult to unify various positioning technologies on the same basis. Global navigation satellite system (GNSS)-based positioning is the only way to provide absolute location under the Earth-centered, Earth-fixed coordinate system (ECEF). Increasing indoor and underground human activity places significant demand on location-based services but no GNSS signals are available there. Fortunately, a type of satellite that is indoors, known as pseudolite, can transmit GNSS-like ranging signals. Users can obtain their position by receiving ranging signals and their resection without adding or switching other sensors when they go from outdoors to indoors. To complete the outreach of the GNSS indoors and underground to support the smart city, how to adapt the pseudolite design and unify coordinate frames for linking to the GNSS remain to be determined. In this regard, we provide an overview of the history of the research and application of pseudolites, the research progress from both the system side and the user side, and the plans for pseudolite-based location services in smart cities.
Research on the Outgoing Audit and Evaluation of Water Resource Assets of Leadership Cadres in City Y
Authors: Chen Ju , Tian Guiliang , Li Jiawen , Xu Huijun
Published: August 2023

The outgoing audit of water resource assets of leading cadres is key to promoting the management of water resource assets and investigating the responsibility for water environment damage. This paper is based on the United Nations’ Sustainable Development Goals related to water resource management and natural asset green accounting. It constructs an evaluation index system for the outgoing audit and evaluation of water resource assets from four dimensions: resource, environment, society, and economy. The paper combines the Analytic Hierarchy Process (AHP) and the initial comparison scoring method to comprehensively assess the water resource management performance of the former mayor of City Y in the Yellow River Basin during 2018–2020. The Barrier Degree Model is also utilized to identify the main influencing factors. The results indicate the following: (1) the constructed index system covers critical aspects of the outgoing audit and can comprehensively reflect the leadership cadres’ responsibilities in water resource management. (2) The comprehensive evaluation score of the former mayor of City Y during 2018–2020 is 85.66, falling within the “relatively good” range but not reaching the “excellent” standard. This suggests that, although progress has been made in water resource asset management, some issues remain. (3) At the index level, the top three factors influencing the comprehensive evaluation of the former mayor’s water resource management performance in City Y are the proportion of ammonia nitrogen emissions (9.86%), per capita water resource (9.38%), and Chemical Oxygen Demand (COD) emissions (8.93%). At the criterion level, the environmental dimension has the most significant impact on the overall evaluation results, accounting for 42.43%. The practical application of the evaluation index system in City Y can serve as a reference for improving the regulatory framework for leadership cadres’ water resource assets in other regions and provide valuable insights for international exchange in water resource management practices.
Comparative Analysis of Thermodynamic Performances of a Linear Fresnel Reflector Photovoltaic/Thermal System Using Ag/Water and Ag-CoSO4/Water Nano-Fluid Spectrum Filters
Authors: Jiang Tieliu , Zou Tianlin , Wang Gang
Published: August 2023

Renewable energy represented by solar energy has played an important role in the transformation of the energy consumption structure of the world. This study describes and studies a hybrid photovoltaic/thermal (HPVT) system using a linear Fresnel reflector concentrator (LFRC) and nano-fluid spectrum filter (NFSF). The method of designing the HPVT system is provided. Ag/water and Ag-CoSO4/water NFSFs used for this HPVT system were prepared and experimentally tested. Optical analysing results indicate that the optical efficiencies of the PV cell module (PVCM) and NFSF are 0.7556 and 0.9053 under the condition of 0.3° solar tracking error (STE), demonstrating good adaptable capacity to the STE. Moreover, the operating performances of the HPVT system using different NFSFs are compared. The comparison results demonstrate that compared with the Ag/water NFSF, the introduction of CoSO4 can enhance the thermal performance but decrease the photovoltaic efficiency of the HPVT system. When the Ag-CoSO4/water (1.2 mg–3 g/130 mL) NFSF is used, the photovoltaic and thermal efficiencies of the whole HPVT system are 0.1366 and 0.4259, and the overall exergy efficiency is 0.209. The exergy efficiency of the HPVT system will be improved if the NFSF temperature is increased appropriately or if the external convection heat transfer coefficient and environment temperature are reduced.
Exposure Assessment and Risk Characterization of Carbon-Based Nanomaterials at Different Production Scales
Authors: Fito López Carlos , Colmenar González Inmaculada , Andreu Sánchez Oscar , Vela Verónica , Domat Rodriguez Maidá
Published: August 2023

Data on the potential impact on human health of engineered nanomaterials are still scarce, with an evident lack of knowledge on the exposure levels at all stages of the life cycle. By prioritizing the responsible handling of engineered nanomaterials (ENMs), companies can promote sustainability by minimizing the risks of occupational exposure, protecting employee well-being, reducing liability, and avoiding costly environmental remediation efforts. This research aims to evaluate the risk in real scenarios involving the use of carbon-based nanomaterials in research laboratories, pilot-scale facilities, and industrial settings. Several online and offline instruments have been employed to characterize the particulate matter present in these environments, including particles in the nanometer range and relevant fractions for risk assessment purposes. Samples collected on polycarbonate filters were analyzed by scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDX). Exposure estimation has been performed by applying a decision based on tier 2 from the nanoGEM methodology, with the weighing and transferring of reduced graphene oxide (RGO) in a pilot plant being the most liberating processes, which are the activities with the highest risk of exposure. In addition, high levels of particle concentration, with peaks up to 1.7 × 105 and 4.7 × 105 part/cm3, have been found for the dispersion of carbon nanotubes (CNTs) and incorporation of carbonaceous nanoparticles into resins, respectively.
Prospects, Challenges and Sustainability of the Agri-Food Supply Chain in the New Global Economy II
Authors: Skalkos Dimitris
Published: August 2023

In the new global era, the process “from farm to fork” as a holistic approach to the production and consumption of food will become a key factor for the sustainability and progress of the food industry [...]
A Socio-Technical Study of Industry 4.0 and SMEs: Recent Insights from the Upper Midwest
Authors: Roth Katherine , Farahmand Kambiz
Published: August 2023

The implementation of Industry 4.0 is becoming increasingly prevalent in the manufacturing industry since its inception. The purposeful joint optimization of social and technical factors of organizations is imperative to the successful adoption of these newer technologies. This paper shares the outcomes of a survey conducted among a group of small, medium, and large manufacturers in Minnesota and North Dakota. The survey posed questions based on a socio-technical theory framework, Industry 4.0, and productivity outcomes. Insights were provided into how regional manufacturers were utilizing the socio-technical design framework to both integrate Industry 4.0 into the organizational design and extract value, such as increased productivity. This research identifies potential challenges, as well as advantages in the current socio-economic landscape for manufacturers that may be both impeding and encouraging the development of a competitive and sustainable manufacturing business.
A Study of the Effect of Trade Openness on Population Health: Empirical Evidence from China
Authors: Ou Jiayu , Zheng Zhiqiang , Zhang Naili
Published: August 2023

Currently, the international economy is experiencing profound and intricate transformations, while economic globalization is encountering unprecedented challenges and witnessing a surge in counter-globalization sentiments. Critics express concerns over the potential detrimental effects of trade liberalization on the welfare of low-income groups, particularly in developing countries. China, as the largest developing country, also holds the status of a major trading nation. Using panel data from 285 prefecture-level cities across China during 2000–2019, this study examines how trade openness affects population health to assess the welfare effects of trade openness, providing new theoretical perspectives and empirical evidence to further promote economic globalization and improve human health and well-being. The results show that trade openness can significantly promote population health. And, a series of robustness tests show that the above conclusion is still valid. Trade openness has a greater positive impact on the health of the population of the eastern and central regions, the coastal cities, and high-trade-openness cities. An analysis of the mechanism reveal that trade openness mainly promotes population health through channels such as labor employment, wage income, public health investment, and personal health investment. However, trade openness can also lead to environmental pollution, which has a significant negative impact on population health. Additionally, through threshold effects analysis, it becomes evident that the relationship between trade openness and population health is nonlinear. This implies that there are critical thresholds related to the economic development stage, investment in environmental governance, and environmental infrastructure construction. Falling below or exceeding these thresholds may lead to different interval effects on the impact of trade openness on population health.
Do Innovative Provincial Policies Promote the Optimization of Regional Innovation Ecosystems?
Authors: Liu Jun , Zhang Yikun , Ma Xiaoyu , Wang Huilin
Published: August 2023

Innovative provinces are essential to innovative countries and robust support for constructing national and regional innovation systems. Based on the panel data of 28 provinces from 2016 to 2019, this paper builds a regional innovation ecosystem performance evaluation system from five dimensions: innovation subject, innovation environment, innovation resource, resource flow, and interaction intermediaries. The index weighting is carried out using the principal component analysis method, and the innovation ecosystem performance of various provinces is evaluated and analyzed to determine the regional distribution status of innovation ecosystem performance. Based on a multi-period difference-in-differences model, this paper empirically tests the impact of innovative provincial policies on the innovation ecosystem performance of each region in the former innovation development stage. The results show that innovative provincial policies significantly positively impact the regional innovation ecosystems, which are multi-dimensional, long-term, and stable. The three secondary indicators, including ecological composition, resource input, and circulation flow, show a positive impact. Further research reveals that the main pathways of the effects are promoting the expansion of innovation inputs and the increase of interaction intermediaries among innovation subjects. Finally, combining the contents and impact of the previous innovative provincial policies, this paper puts forward corresponding thoughts and suggestions for the next phase of regional pilot-type innovation policies.
Analysis of Heat Transfer Behavior of Porous Wavy Fin with Radiation and Convection by Using a Machine Learning Technique
Authors: Kumar Chandan , Nimmy P. , Nagaraja Kallur Venkat , Kumar R. S. Varun , Verma Amit , Alkarni Shalan , Shah Nehad Ali
Published: August 2023

The impact of convection and radiation on the thermal distribution of the wavy porous fin is examined in the present study. A hybrid model that combines the differential evolution (DE) algorithm with an artificial neural network (ANN) is proposed for predicting the heat transfer of the wavy porous fin. The equation representing the thermal variation in the wavy porous fin is reduced to its dimensionless arrangement and is numerically solved using Rung, e-Kutta-Fehlberg’s fourth-fifth order method (RKF-45). The study demonstrates the effectiveness of this hybrid model, and the results indicate that the proposed approach outperforms the ANN model with parameters obtained through grid search (GS), showcasing the superiority of the hybrid DE-ANN model in terms of accuracy and performance. This research highlights the potential of utilizing DE with ANN for improved predictive modeling in the heat transfer sector. The originality of this study is that it addresses the heat transfer problem by optimizing the selection of parameters for the ANN model using the DE algorithm.
Prediction of China Automobile Market Evolution Based on Univariate and Multivariate Perspectives
Authors: Dai Debao , Fang Yu , Wang Shihao , Zhao Min
Published: August 2023

The automobile is an important part of transportation systems. Accurate prediction of sales prospects of different power vehicles can provide an important reference for national scientific decision making, flexible operation of enterprises and rational purchases of consumers. Considering that China has achieved the goal of 20% sales of new energy vehicles ahead of schedule in 2025, in order to accurately judge the competition pattern of new and old kinetic energy vehicles in the future, the automobile market is divided into three types according to power types: traditional fuel vehicles, new energy vehicles and plug-in hybrid vehicles. Based on the monthly sales data of automobiles from March 2016 to March 2023, the prediction effects of multiple models are compared from the perspective of univariate prediction. Secondly, based on the perspective of multivariate prediction, combined with the data of economic, social and technical factors, a multivariate prediction model with high prediction accuracy is selected. On this basis, the sales volume of various power vehicles from April 2023 to December 2025 is predicted. Univariate prediction results show that in 2025, the penetration rates of three types of vehicles will reach 43.8%, 44.4% and 11.8%, respectively, and multivariate prediction results show that the penetration rates will reach 51.0%, 37.9% and 11.1%, respectively.
The Synergistic Evolution of Resilience and Efficiency in the Digital Economy and Its Path Identification: Evidence from China
Authors: Wang Linyan , Hu Haiqing , Wang Xianzhu , Zhang Xincheng , Yan Zhishan , Liang Zhikang
Published: August 2023

An effective combination of resilience and efficiency will help to promote the high-quality development of the digital economy. In this paper, we use the entropy method, the Super-SBM model, and the Haken model to measure the digital economy resilience, digital economy efficiency, and their synergistic evolution mechanisms in 31 Chinese provinces and autonomous regions from 2013 to 2020, respectively. The results show that: (1) The resilience of the digital economy is the order parameter leading synergistic development, playing a prominent role in promoting the development of the digital economy from disorder to order. (2) Synergistic evolution has evolved from low-level to high-level, but it is in the primary stage as a whole, and the fluctuation of its development is not obvious, showing a unipolar development pattern. (3) There are significant regional differences in synergistic evolution, showing a polarization pattern, with the “Matthew effect” that the stronger the start the stronger the development. (4) Overall, the resilience and efficiency of the digital economy show a positive synergistic effect, but some provinces show a negative feedback mechanism that inhibits the orderly development of the system, there is a bias effect, and the development levels of the resilience and efficiency of the digital economy are mismatched. (5) The four paths that drive the synergistic evolution of resilience and efficiency in a high digital economy are the “Resilience Dominates Driven Path”, the “Basic Driven Path”, the “Innovation Driven Path”, and the “Balanced Driven Path”, respectively. In short, the synergistic evolution of the resilience and efficiency of the digital economy shows that the future development of the digital economy needs to cultivate endogenous momentum, pay attention to strengthening resilience in the process of continuing to build a diversified industrial system, and continuously improve the operational efficiency of the digital economy, in order to promote its high-quality development.
The Need for Next-Generation Antivenom for Snakebite Envenomation in India
Authors: Vanuopadath Muralidharan , Rajan Karthika , Alangode Aswathy , Nair Sudarslal Sadasivan , Nair Bipin Gopalakrishnan
Published: August 2023

The limitations posed by currently available antivenoms have emphasized the need for alternative treatments to counteract snakebite envenomation. Even though exact epidemiological data are lacking, reports have indicated that most global snakebite deaths are reported in India. Among the many problems associated with snakebite envenomation, issues related to the availability of safer and more efficient antivenoms are of primary concern. Since India has the highest number of global snakebite deaths, efforts should be made to reduce the burden associated with snakebite envenoming. Alternative methods, including aptamers, camel antivenoms, phage display techniques for generating high-affinity antibodies and antibody fragments, small-molecule inhibitors, and natural products, are currently being investigated for their effectiveness. These alternative methods have shown promise in vitro, but their in vivo effectiveness should also be evaluated. In this review, the issues associated with Indian polyvalent antivenoms in neutralizing venom components from geographically distant species are discussed in detail. In a nutshell, this review gives an overview of the current drawbacks of using animal-derived antivenoms and several alternative strategies that are currently being widely explored.
Community-Acquired, Bacteraemic Acinetobacter Baumannii Pneumonia: A Retrospective Review of Cases in Tropical Queensland, Australia
Authors: Riddles Timothy , Judge Daniel
Published: August 2023

Background: Community-acquired Acinetobacter pneumonia (CAAP) typically presents with rapid progression to fulminant disease and is complicated by high mortality. Australian epidemiological studies are few. Methods: We conducted a retrospective study on bacteraemic cases of CAAP over twenty years (2000–2019) in North Queensland. Cases were selected on microbiologic, clinical, and radiographic parameters. Data on patient demographics were obtained, along with microbial, antibiotic, mortality and climatic data. Results: 28 cases of CAAP were included. Nineteen (67.9%) were male, twenty-three (82.1%) were Indigenous Australians, and the mean age was 45.9 years. Most presentations were of moderate to severe pneumonia (25/28 (89.3%)). Furthermore, 90% of cases had two or more risk factors. The strongest risk factors for CAAP were alcohol excess and tobacco use. No statistically significant difference in presenting severity, ICU admission or mortality was seen between dry- and wet-season disease. Dry-season disease accounted for 35.7% of cases. Overall mortality was 28.6%. Early use of meropenem or gentamicin reduced mortality irrespective of presenting severity (mortality 17.6%) Non-targeted antibiotic therapy was associated with a non-significant difference in mortality of 44.4%. Conclusions: Early administration of targeted antibiotics can mitigate a high mortality rate. The choice of antibiotic therapy for community-acquired pneumonia should be based on severity, risk factors and clinical suspicion of CAAP rather than seasonality.
Deubiquitinase OTUD6A Regulates Innate Immune Response via Targeting UBC13
Authors: Li Zhiwei , Li Guanwen , Li Yunfei , Luo Yujie , Jiang Yuhan , Zhang Ziyu , Zhou Ziyi , Liu Shengde , Wu Chen , You Fuping
Published: August 2023

OTUD6A is a deubiquitinase that plays crucial roles in various human diseases. However, the precise regulatory mechanism of OTUD6A remains unclear. In this study, we found that OTUD6A significantly inhibited the production of type I interferon. Consistently, peritoneal macrophages and bone marrow-derived macrophages from Otud6a−/− mice produced more type I interferon after virus infection compared to cells from WT mice. Otud6a−/−− mice also exhibited increased resistance to lethal HSV-1 and VSV infections, as well as LPS attacks due to decreased inflammatory responses. Mechanistically, mass spectrometry results revealed that UBC13 was an OTUD6A-interacting protein, and the interaction was significantly enhanced after HSV-1 stimulation. Taken together, our findings suggest that OTUD6A plays a crucial role in the innate immune response and may serve as a potential therapeutic target for infectious disease.
Development of Zika Virus Mini-Replicon Based Single-Round Infectious Particles as Gene Delivery Vehicles
Authors: Wu Joh-Sin , Kan Ju-Ying , Lai Hsueh-Chou , Lin Cheng-Wen
Published: August 2023

Zika virus (ZIKV) is a type of RNA virus that belongs to the Flaviviridae family. We have reported the construction of a DNA-launched replicon of the Asian-lineage Natal RGN strain and the production of single-round infectious particles (SRIPs) via the combination of prM/E virus-like particles with the replicon. The main objective of the study was to engineer the ZIKV replicon as mammalian expression vectors and evaluate the potential of ZIKV mini-replicon-based SRIPs as delivery vehicles for heterologous gene expression in vitro and in vivo. The mini-replicons contained various genetic elements, including NS4B, an NS5 methyltransferase (MTase) domain, and an NS5 RNA-dependent RNA polymerase (RdRp) domain. Among these mini-replicons, only ZIKV mini-replicons 2 and 3, which contained the full NS5 and NS4B-NS5 genetic elements, respectively, exhibited the expression of reporters (green fluorescent protein (GFP) and cyan fluorescent protein–yellow fluorescent fusion protein (CYP)) and generated self-replicating RNAs. When the mini-replicons were transfected into the cells expressing ZIKV prM/E, this led to the production of ZIKV mini-replicon-based SRIPs. ZIKV mini-replicon 3 SRIPs showed a significantly higher yield titer and a greater abundance of self-replicating replicon RNAs when compared to ZIKV mini-replicon 2 SRIPs. Additionally, there were disparities in the dynamics of CYP expression and cytotoxic effects observed in various infected cell types between ZIKV mini-replicon 2-CYP and 3-CYP SRIPs. In particular, ZIKV mini-replicon 3-CYP SRIPs led to a substantial decrease in the survival rates of infected cells at a MOI of 2. An in vivo gene expression assay indicated that hACE2 expression was detected in the lung and brain tissues of mice following the intravenous administration of ZIKV mini-replicon 3-hACE2 SRIPs. Overall, this study highlights the potential of ZIKV mini-replicon-based SRIPs as promising vehicles for gene delivery applications in vitro and in vivo.
Construction of River Health Assessment System in Areas with Significant Human Activity and Its Application
Authors: Jiao Hongbo , Li Yinan , Wei Huaibin , Liu Jing , Cheng Liming , Chen Yongrui
Published: August 2023

The assessment of river health holds paramount significance in diagnosing the conditions of river water environments, and its research serves as a crucial foundation for the functional management and restoration of rivers. We discuss the concept and assessment criteria of health in areas characterized by significant human activity. Utilizing the “over the riverbank” and “under the riverbank” quantification criteria as the framework, a comprehensive river health assessment index system is developed, encompassing seven aspects (riparian zone condition, pollution discharge condition, human–water interaction, physical structure, water environment, water ecology, and socio-economic service function) and 35 indicators. This study introduces the River Health Index (RHI), specifically tailored for regions with significant human activity, facilitating the quantitative assessment of river health status and precise calculation of the River Health Index in these areas. The research employs the RHI to assess the health condition of the Cangzhou section of the Qingliang River in China. The results indicate that the Qingliang River is in a suboptimal state of health, with the key limiting factors being the aspects of “water environment” and “water ecology”. The research demonstrates that the proposed river health assessment system for areas with significant human activity effectively reflects the objective reality of the Qingliang River, exhibiting a high level of reliability and applicability.