Safety Hazards Research Articles

Experimental and Modeling Analysis of Polypropylene Fiber Reinforced Concrete Subjected to Alkali Attack and Freeze-Thaw Cycling Effect.

The durability of concrete materials in harsh environmental conditions, particularly in cold regions, has garnered significant attention in civil engineering research in recent years. Concrete structures in these areas are often damaged by the combined effects of alkali-silica reaction (ASR) and freeze-thaw cycles, leading to structural cracks and significant safety hazards. Numerous studies have demonstrated that polypropylene fiber concrete exhibits excellent crack resistance and durability, making it promising for applications in cold regions. This study elucidates the impact of alkali content on concrete durability by comparing the mechanical properties and durability of different alkali-aggregate concretes. The principal experimental methodologies employed include freeze-thaw cycle experiments, which examine patterns of mass loss; fluctuations in the dynamic modulus of elasticity; and changes in mechanical properties before and after freeze cycles. The findings indicate that increased alkali content in concrete reduces its strength and durability. At 100% alkali-aggregate content, compressive strength decreases by 35.5%, flexural strength by 32.9%, mass loss increases by 35.85%, relative dynamic elastic modulus by 39.4%, and residual strength by 97.28%, indicating higher alkali content leads to diminished durability. Additionally, this paper introduces a constitutive damage model, validated by a strong correlation with experimental stress-strain curves, to effectively depict the stress-strain relationship of concrete under varying alkali contents. This research contributes to a broader understanding of concrete durability in cold climates and guides the selection of materials for sustainable construction in such environments.

Investigation of Solid Polymer Electrolytes for NASICON-Type Solid-State Symmetric Sodium-Ion Battery.

The inevitable shift toward renewable energy and electrification necessitates earth-abundant sodium reserves for next-generation Na-based energy storage technologies. By coupling the benefits of solid electrolytes over traditional nonaqueous electrolytes due to their safety hazards, solid-state sodium-ion batteries hold huge prospects in the future. This work presents a comprehensively developed solid-state sodium-ion symmetric full cell operating at room temperature enabled through a poly(vinylidene fluoride-co-hexafluoropropylene) (PVDF-HFP)-based polymer electrolyte and modified NASICON-structured positive and negative electrodes. Among the investigated polymer electrolytes, PVDF-HFP-NaTFSI was found to outperform other counterparts by achieving a higher ionic conductivity and delivered an appreciable electrochemical stability window. By further delving into the properties of PVDF-HFP-NaTFSI, it was found to possess the least crystallinity, minimal porous structure, lowest melting point, and fusion enthalpy, indicating better ion transport than other investigated polymer electrolytes. The as-assembled solid-state battery revealed a storage capacity of 74 mAh g-1 at 0.1 C with a specific energy density of 130 Wh kgcathode_active_material-1 and demonstrated an impressive capacity retention of 84% of the initial capacity after 200 cycles. The structure and morphology retention of the cycled electrode and electrolyte through postmortem analysis bolster the electrochemo-mechanical stability of the developed solid cell. The findings reported here on polymer electrolytes persuade expedient solutions for developing ambient temperature solid-state sodium-ion batteries with promising electrochemical performance for commercialization in the near future.

Room-temperature self-healing polyurethane with superior mechanical properties based on supramolecular structure for flame retardant application

Self-healing polymers, with their ability to extend service life and conserve resources, have garnered significant attention across various fields due to their immense potential applications. However, most repairable polymers typically require high temperatures for repair, and their relatively weak mechanical properties limit their practical use. Moreover, the flammability of polymers not only poses safety hazards during use but also fails to meet specific requirements for flame retardancy in certain fields. Addressing these issues, this study successfully designed a reactive self-extinguishing room-temperature self-healing polyurethane (PU) by introducing hyperbranched catechol (DBPA) onto the PU main chain. The prepared self-healing PU elastomer (DPU) exhibited high tensile strength (∼51.2 MPa), outstanding toughness (∼119.0 MJ/m3), recyclability, and good flame retardancy. Through intermolecular and intramolecular multilevel hydrogen bonding, the prepared DPU0.6 achieved room-temperature self-healing with an efficiency of approximately 71.2 %. The results showed that the addition of trace amounts of DBPA (0.6 wt%) significantly enhanced the flame retardancy and thermal stability of DPU. Compared to DPU0, the heat release rate (HRR) of DPU0.6 decreased by approximately 13 %, the total heat release (THR) reduced by 18 %, and the time to ignition (TTI) was extended by 7 s (reduced by ∼ 21 %). This study not only provides insights into the synthesis and design of novel self-healing PU but also further expands the application scope of self-healing PU.

Guided wave multi-frequency damage localization method in variable-thickness structures by one pair of sensors based on frequency-dependent velocity anisotropy

Variable thickness structures are prevalent in aircraft, ships, and other machines, necessitating numerous sensors for health monitoring to reduce safety hazards. This paper presents a guided wave multi-frequency localization method based on frequency-dependent velocity anisotropy. This method achieves damage localization in variable-thickness structures with a pair of sensors and can effectively reduce the number of sensors used for monitoring. Variations in structural thickness cause a gradient in guided wave velocity that bends the propagation path. Different thickness variations with different directions cause wave velocity anisotropy. As a result, variations in thickness cause possible damage loci determined by echo time to deviate from an elliptical shape. Because the velocity anisotropy is frequency-dependent, damage loci at different frequencies are close but do not overlap and intersect only at the damage location. So, the multi-frequency method can increase the damage information acquired by a single pair of sensors, enabling damage localization. Experimental validation was conducted on a steel plate with linearly varying thicknesses. The feasibility of the multi-frequency localization method was verified by successfully locating the damage at three different locations using a pair of receiver-excitation sensors. In addition, the experiments demonstrated the capability of this multi-frequency method in improving the localization accuracy of sensor networks. The method has potential applications in monitoring systems lightweight, phased arrays, and imaging enhancement.

Ergonomic challenges of mortuary attendants in Ghana: an exploratory study

Objective. Mortuary attendants in Ghana face various occupational health and safety hazards, including ergonomic and psychosocial factors, which can impact both their well-being and the quality of service provided. However, there is limited knowledge about the specific ergonomic hazards they encounter. This study aims to investigate and understand these ergonomic hazards at selected hospital mortuaries in Ghana. Methods. The study used a qualitative approach to investigate the experiences of 19 mortuary attendants, selected through purposive sampling. Semi-structured interviews were conducted and recorded digitally, and focused on participants’ demographics, work experiences, challenges and coping strategies. The collected data were transcribed verbatim and analyzed thematically. Results. The study found that mortuary attendants face ergonomic hazards, leading to physical discomfort, sleep problems and the need for sick leave and self-medication. Poor working conditions were a major risk factor. Conclusion. The study recommends the immediate inclusion of fundamental occupational health and safety practices into the informal apprenticeship training for mortuary attendants. Additionally, the study underscores the importance of providing necessary equipment to mortuary attendants to reduce or eliminate ergonomic hazards in their work environments.

Green Solution Processing of Halide Perovskite Solar Cells: Status and Future Directions

Halide perovskite solar cells have achieved impressive efficiencies above 26%, making them a promising technology for the future of solar energy. However, the current fabrication methods rely on highly toxic solvents, which pose significant safety and environmental hazards. It is crucial to develop greener and safer alternatives to these solvents to facilitate the commercialization of perovskite solar cells. In this review, the safety and hazard evaluations of conventional toxic solvents and discuss the selection criteria for solvents that affect the morphology, nucleation, crystallization, and performance of perovskite solar cells. Furthermore, recent research into green solvent alternatives is evaluated and their properties are compared to those of commonly used solvents. In this review, fundamental insights are provided into the progress and challenges of green‐solution processing of perovskite solar cells, which will be essential for advancing this technology toward commercialization.

The Effect of Dynamic Effects and Color Transparency of AR-HUD Navigation Graphics on Driving Behavior Regarding Inattentional Blindness

In-vehicle Augmented Reality Head-Up Displays (AR-HUDs) offer drivers integrated navigation and vehicle status information, thereby improving the driving experience. Many studies explored the effects of AR-HUD navigation design and information presentation on driving performance; however, these studies neglected the occurrence of inattentional blindness, which may lead to potential safety hazards. This study used a two-factor within-subjects design to investigate how dynamic effects (pulsation, blinking, movement) and color transparency levels (T1, T0.75, T0.5, T0.35) of AR-HUD navigation graphics influence inattentional blindness and user experience. The results indicated that color transparency significantly affects the drivers’ inattentional blindness behavior and user experience. Specifically, T0.75 resulted in the lowest inattentional blindness, while T0.5 was associated with the shortest reaction time (without blindness) and highest user satisfaction. Dynamic effects did not significantly impact inattentional blindness, but blinking reduced reaction time (without blindness). This study provides design insights for vehicle AR-HUD navigation interfaces.

3D self-supporting core-shell silicon-carbon nanofibers-based host enables confined Li+ deposition for lithium metal battery

Three-dimensional (3D) porous hosts play pivotal roles in realizing dendrite-free lithium metal anodes (LMAs) owing to their high specific area. However, uneven local electric field and lack of lithiophilic sites on the reactive interface cause nonuniform lithium ion (Li+) deposition, leading to Li dendrite growth and parasitic reactions. These issues will inevitably incur short cycling life and severe safety hazards of lithium metal batteries. Herein, a 3D self-supporting host composed of hollow carbon nanofibers incorporated with silicon (Si) nanoparticles inside (Si-HCF) is constructed as Li metal host by a scalable coaxial electrospinning technique. During the first cycle, the Si nanoparticles is alloyed with Li+ to form lithiophilic Li-Si alloy, contributing to deliver a low nucleation overpotential and homogeneous surface potential confirmed by Kelvin probe force microscopy, finally guiding Li+ flux homogeneously throughout the fibrous mat. As expected, the Li metal can percolate through Si-HCF host reversibly without uncontrollable Li dendrites and the Si-HCF exhibits a stable cycle life of Li plating/stripping over 1400 h. Additionally, the full cell combined with LiFePO4 cathodes presents steady cycling over 400 cycles with a high average coulombic efficiency of 99.4 %. This work provides new insights for the synthesis of 3D hosts with controllable nucleation sites to homogenize Li+ deposition in LMAs.

Development of Solid-State Lithium-Ion Batteries (LIBs) to Increase Ionic Conductivity through Interactions between Solid Electrolytes and Anode and Cathode Electrodes

Although in general ions are not able to migrate in the solid-state position due to rigid skeletal structure, in some solid electrolytes with a low energy barrier and high ionic conductivities, these ion transition can occur. In this work, we considered several solid electrolytes including lithium phosphorus oxy-nitride (LIPON), a lithium super-ionic conductor (SILICON), and thio-LISICON. For the fabrication and characterization of the solid electrolyte’s fabrication, we used a single-step ball milling (SSBM) procedure. Through this research on all-solid-state rechargeable lithium-ion batteries, our target is to discuss solving several problems in solid LIBs that have recently escalated due to raised concerns relating to safety hazards such as solvent leakage and the flammability of the liquid electrolytes used for commercial LIBs. Through this research, we tested the conductivity amounts of various substrates containing amorphous glass, SSBM, and glass-ceramic samples. Obviously, the SSBM glass-ceramics increased the conductivity, and we also found that the values for conductivity attained by SSBM were higher than those values for glass-ceramics. Using an SSBM technique, silicon nanoparticles were used as an anode material and it was found that the charge and discharge curves in the battery cell cycled between 0.009 and 1.45 V versus Li+/Li at a current density of 210 mA g−1 at room temperature. Since high resistance causes degradation between the cathode material (LiCoO2) and the solid electrolyte, we added GeS2 and SiS2 to the Li2S-P2S5 system to obtain higher conductivities and better stability of the electrode–electrolyte interface.

Dual Li ion transport channels in a dynamical supramolecular solid electrolyte toward safety and high-performance Li metal batteries

The polymer based quasi-solid electrolyte (QSE), which combines the high ionic conductivity of the liquid electrolytes with the excellent mechanical flexibility of the polymer matrix, is highly desired and most promising for Li metal batteries (LMBs). However, the Li+ transfer pathways in QSE is not clear enough, and the practical applications in LMBs are also hindered by safety hazards arising from risks of mechanical damage, flammability and high voltage instability. Here, a dynamical supramolecular QSE with abundant hydrogen bonds to fabricate stable and safety LMBs, is reported. In this designed electrolyte, both thermal stability and superior interface stability with anode/cathode electrodes were achieved. Notably, the dual Li+ transport channels in QSE were investigated using in-situ FTIR technology and DFT calculations, providing insights into both the “wet” liquid phase and “dry” polymer chain channels. Benefiting from this design, the Li||NCM622 full batteries based on this QSE exhibit excellent long-term cycling stability.

Mechanical properties and microscopic mechanism of solid waste based binder solidified stone waste

The stone waste generated by stone industry occupy land resources, cause safety hazards and need to be efficiently resourcefully utilized. In this study, the CGF solid waste based binder (abbreviated as CGF) with calcium carbide residue (CCR), ground granulated blast furnace slag (GGBS), and fly ash (FA) as components was developed to solidify the stone waste. Through “treating waste with waste”, the resource utilization of solid waste was realized. The mechanical properties and reaction mechanism of CGF solidified stone waste were investigated through unconfined compressive strength (UCS), XRD, and SEM–EDS tests. The results show that CGF has the better solidify effect on stone waste, and its strength meets the requirements of the road base material standards. Compared to cement, the CGF solidified stone waste existed higher UCS at both 7 and 28 d of curing. The UCS of CGF solidified stone waste reaches 2.93 and 4.42 MPa under curing of 7 and 28 d at 5% binder content, which is 1.61 and 1.37 times higher that of P.O. 42.5 cement. Furthermore, the primary mineral-based stone wastes will not react with the binder, and the CGF generates gelling products such as C-S–H C-A-H, and C-A-S–H through alkali-activated reactions between the components of CGF. These gelling products enhance the UCS of solidified stone wastes through cementing and filling effects. The findings provide a feasible approach with low-carbon emission and low-cost for resourceful utilization of stone wastes.

Emotional geographies of roadkill: Stained experiences of tourism in Tasmania

AbstractGlobally, road fatalities affect wildlife populations and ecosystems, leading to ecological imbalances, economic losses, and safety hazards for both animals and humans. However, the emotional toll on humans is less well understood. This research explores tourists’ responses to roadkill, using emotional geography as the overarching framework, and focusing on the island state of Tasmania in Australia. Tasmania is known for its diverse and abundant native wildlife, as well as the unfortunate distinction of having Australia’s highest rate of wildlife fatalities caused by vehicle collisions, commonly referred to as roadkill. A mixed‐method questionnaire asked respondents to share emotions, and we then considered their relationships to socio‐demographic attributes. Around 97% of respondents encountered roadkill during their stays, and 63% encountered live animals on or near the road. Tourists identified sadness as the most felt emotion when confronted with the consequences of wildlife–vehicle collisions. Anger and disgust were also experienced, primarily because of the unpleasant sight of roadkill and the realisation that animals suffered. Women reported being more negatively affected than men. Tourists who had visited to see wildlife were more affected than those who had not. Analysis leads to the conclusion that unplanned, sporadic, unexpected, and confronting encounters with dead animals detract from the tourism experience for most, especially encounters with wildlife was anticipated as a positive experience on tour. Such findings have wider implications for those working in the tourism industry in mainland Australia, Canada, and South Africa, where roadkill is also problematic.

Kinetics study on inhibiting battery thermal runaway using an inorganic phase change material with a super high thermochemical storage capacity

Lithium-ion batteries are susceptible to fires and explosions due to thermal runaway, a serious safety hazard. This study explores the potential of using hydrated inorganic salt (TCM40) composite phase change materials to prevent thermal runaway in battery packs. TCM40 composites stand out due to their exceptional thermochemical heat storage capacity, which allows them to effectively absorb excess heat during runaway events. The research investigates how thermal conductivity, thermal storage capacity, and cell spacing influence the propagation of thermal runaway. The findings demonstrate that TCM40 composites, with a thermal storage density exceeding 1000 kJ/kg, are significantly more effective in preventing thermal runaway compared to traditional latent heat storage phase change materials with lower capacities. To gain a comprehensive understanding of thermal runaway mitigation, a combined thermal management model was developed. This model integrates a battery thermal runaway model with a kinetic model describing the decomposition of TCM40 composites. The analysis reveals that the high heat absorption capability of TCM40 composites minimizes heat transfer to neighboring cells during thermal runaway. Furthermore, the model provides valuable insights into the synergistic effects of thermal conductivity and heat storage capacity on runaway propagation. This knowledge can be directly applied to design safer battery packs, even for compact configurations where cell spacing is less than 2 mm. This study offers significant advancements in both thermal protection materials and design strategies for lithium-ion battery packs. These advancements have the potential to significantly improve battery system safety and minimize the risk of explosions.

Research on Train-Induced Vibration of High-Speed Railway Station with Different Structural Forms.

Elevated stations are integral components of urban rail transit systems, significantly impacting passengers' travel experience and the operational efficiency of the transportation system. However, current elevated station designs often do not sufficiently consider the structural dynamic response under various operating conditions. This oversight can limit the operational efficiency of the stations and pose potential safety hazards. Addressing this issue, this study establishes a vehicle-bridge-station spatial coupling vibration simulation model utilizing the self-developed software GSAP V1.0, focusing on integrated station-bridge and combined station-bridge elevated station designs. The simulation results are meticulously compared with field data to ensure the fidelity of the model. Analyzing the dynamic response of the station in relation to train parameters reveals significant insights. Notably, under similar travel conditions, integrated stations exhibit lower vertical acceleration in the rail-bearing layer compared to combined stations, while the vertical acceleration patterns at the platform and hall layers demonstrate contrasting behaviors. At lower speeds, the vertical acceleration at the station concourse level is comparable for both station types, yet integrated stations exhibit notably higher platform-level acceleration. Conversely, under high-speed conditions, integrated stations show increased vertical acceleration at the platform and hall levels compared to combined stations, particularly under unloaded double-line working conditions, indicating a superior dynamic performance of combined stations in complex operational scenarios. However, challenges such as increased station height due to bridge box girder maintenance, track layer waterproofing, and track girder support maintenance exist for combined stations, warranting comprehensive evaluation for station selection. Further analysis of integrated station-bridge structures reveals that adjustments in the floor slab thickness at the rail-bearing and platform levels significantly reduce dynamic responses, whereas increasing the rail beam height notably diminishes displacement responses. Conversely, alterations in the waiting hall floor slab thickness and frame column cross-sections exhibit a minimal impact on the station dynamics. Overall, optimizing structural dimensions can effectively mitigate dynamic responses, offering valuable insights for station design and operation.

GMS-YOLO: An Algorithm for Multi-Scale Object Detection in Complex Environments in Confined Compartments.

Many compartments are prone to pose safety hazards such as loose fasteners or object intrusion due to their confined space, making manual inspection challenging. To address the challenges of complex inspection environments, diverse target categories, and variable scales in confined compartments, this paper proposes a novel GMS-YOLO network, based on the improved YOLOv8 framework. In addition to the lightweight design, this network accurately detects targets by leveraging more precise high-level and low-level feature representations obtained from GhostHGNetv2, which enhances feature-extraction capabilities. To handle the issue of complex environments, the backbone employs GhostHGNetv2 to capture more accurate high-level and low-level feature representations, facilitating better distinction between background and targets. In addition, this network significantly reduces both network parameter size and computational complexity. To address the issue of varying target scales, the first layer of the feature fusion module introduces Multi-Scale Convolutional Attention (MSCA) to capture multi-scale contextual information and guide the feature fusion process. A new lightweight detection head, Shared Convolutional Detection Head (SCDH), is designed to enable the model to achieve higher accuracy while being lighter. To evaluate the performance of this algorithm, a dataset for object detection in this scenario was constructed. The experiment results indicate that compared to the original model, the parameter number of the improved model decreased by 37.8%, the GFLOPs decreased by 27.7%, and the average accuracy increased from 82.7% to 85.0%. This validates the accuracy and applicability of the proposed GMS-YOLO network.

Accurate modeling and safety evaluation of dented pipeline with internal pressure based on reverse modeling technique

ABSTRACT As a common form for pipeline geometric defects, dents can induce the local stress concentration of the pipeline, which would result in the debilitation of the bearing capacity and bring huge safety hazards. In this paper, the accurate surface profiles of dented pipeline are acquired based on the 3D scanning technology and deformation detection technology, respectively. Then, the dented pipeline models are constructed by the reverse modeling technique, and the stress distribution characteristics of the dented pipeline in the operation condition are simulated using ABAQUS. The maximum von Mises stresses of a dented pipeline obtained from two proposed modeling techniques are basically consistent. However, the deformation detection technology can effectively avoid the excavation work for buried pipelines. Therefore, the reverse modeling technique based on the deformation detection technology has strong feasibility in practical projects and significant application value in the safety assessment of submarine pipelines, where excavation work is impractical.

Current Status and Analysis of Natural Gas Pipeline Hydrogen Blending and Transportation Development

Hydrogen doping in natural gas pipelines is one of the means to realize large-scale, long-distance and low-cost hydrogen transportation, but hydrogen doping in natural gas pipelines has brought about non-negligible impacts on pipeline operating conditions, safety and maintenance, etc., and has certain potential safety hazards. To this end, the technical research and engineering application of hydrogen doping in natural gas pipelines at home and abroad are discussed, and the main factors affecting the safe transportation of hydrogen doping in natural gas pipelines are discussed, i.e., physical changes of natural gas caused by hydrogen doping, hydrogen failure, and uneven mixing. The results show that the hydrogen doping of natural gas puts new requirements on the existing pipe materials, and relevant experiments need to be carried out in order to reveal the mechanism of hydrogen failure, and whether gas aggregation occurs after the shutdown of hydrogen-doped natural gas pipelines is closely related to whether hydrogen failure occurs in the pipelines or not. The above results clarify the risks of hydrogen-doped transportation, which can provide a reference for the promotion of large-scale hydrogen-doped mixing and transmission projects and practical operation.

Analysis of Early-Stage Behavior and Multi-Parameter Early Warning Algorithm Research for Overcharge Thermal Runaway of Energy Storage LiFePO4 Battery Packs

Overcharging of lithium-ion batteries may lead to severe thermal runaway (TR) incidents, resulting in significant economic losses and safety hazards. Therefore, it is crucial to research early warning methods for TR behavior in overcharged lithium batteries. This study initially conducted overcharging experiments on LiFePO4 battery packs under different initial charging states and charging rates, analyzing variations in temperature, voltage, and inter-group pressure during overcharging. The TR process was divided into three stages: non-overcharged, early, and middle. Based on this, temperature change rate, pressure change rate, and voltage were extracted as input feature parameters, and the Mean Shift algorithm was employed for stage identification and classification of overcharging experiments on LiFePO4 battery packs. According to experimental results, the algorithm achieved an accuracy of over 96% in stage identification and classification of TR in overcharged lithium batteries, accurately determining the current stage of TR and providing a reliable and effective solution for preventing TR in overcharged lithium batteries.

Evaluating Dimensionality Reduction Methods for the Detection of Industrial IoT Attacks in Edge Computing

Edge computing is essential for 6G mobile networks for improving reliability, reducing data rates and latency, and enhancing mobile connectivity. Edge computing is also meant to meet the increasing demands of the Internet of Things (IoT)/ Internet of Everything (IoE). In these approaches, IIoT systems necessitate precision, reliability, and scalability, while vulnerabilities in IIoT systems may lead to financial losses and safety hazards. To tackle this, Edge AI/ML-based IDSs provide adaptability and robustness for IIoT security challenges. These solutions improve security levels, threat detection rates, and response times. However, main issues such as limited resources and the accuracy of attack detection rate are challenged nowadays. In this paper, we present contributions in proposing an intrusion detection system (IDS) for edge devices deploying a lightweight deep neural network to detect IIoT attacks. We present performance analysis of the typical dimensionality reduction methods and balancing data features of the Edge-IIoT dataset to get higher performance metrics than other state-of-the-art studies.

Detection of coal gangue based on MSRCR algorithm and improved lightweight YOLOv8n

ABSTRACT Traditional methods for coal gangue sorting exhibit low efficiency, significant safety hazards, and limited applicability. Existing machine vision-based coal gangue image recognition methods struggle to balance model recognition speed and accuracy. In response to these challenges, this paper first utilizes the improved MSRCR algorithm to process images, enhancing the dark areas of coal gangue images while ensuring uniform brightness enhancement and image clarity. Furthermore, a novel lightweight coal gangue recognition method is proposed based on YOLOv8n, aiming to reduce data redundancy and improve recognition accuracy. Experimental results demonstrate that the improved lightweight model has a computational load of 7.1 GFLOPs, representing only 86.6% of the original model. The model detection rate is 73 fps, a 17 fps improvement over the original model. The accuracy, recall rate, and average precision reach 98.1%, 97.6%, and 98.9%, respectively, with improvements of 1.1, 0.9, and 0.5% points over the original model. The missing detection phenomenon is avoided effectively, and the accuracy and portability of the model are improved.