Dual Objective Research Articles

The Role of Cells and Cytokines in Male Infertility Induced by Orchitis.

Recent studies on male infertility reveal a growing worry: more infertile men are dealing with inflammation in the testis. Analyzing testicular biopsies from infertile men highlights a significant presence of inflammation. This connection, supported by clinical and pathological evidence, emphasizes that testicular inflammation hampers sperm production, leading to lasting declines in sperm count and quality. However, the exact reasons behind male infertility due to orchitis, a type of testicular inflammation, are still uncertain. Understanding these fundamental aspects of molecular signals and cellular mechanisms in testicular inflammation is crucial. Our review delves into recent literature with a dual objective: elucidating potential mechanisms involving immune cells, non-immune cells, and cytokines that link orchitis to male infertility, while also paving the way for precise interventions and solutions to address the challenges of male infertility.

Steel exoskeletons for integrated seismic/energy retrofit of existing buildings - General framework and case study

The implementation of strategies for the decarbonization of the existing buildings by 2050 and the reduction of polluting emissions is urgent, for energy, economic and environmental reasons. Moreover, the built heritage undergoes structural deterioration for which restoration interventions are required. Seismic and energy improvement strategies are usually treated separately. Conversely, this paper proposes a holistic approach to improve both structural and energy efficiency of existing buildings. The innovative aspect is to obtain a dual objective by exploiting a single element, i.e., the exoskeleton. This component is an external self-supporting structural system connected to the existing building structure for improving strength, stiffness, and/or dissipation capacity under seismic actions. Contemporarily, it defines a new building envelope with different functions, such as ventilated wall, solar greenhouse, shields, and support for insulating panels or solar panels. This approach is applied to a case study, a reinforced concrete building in central Italy. The exoskeleton is rigidly connected to the existing building and designed to absorb the seismic loads and prevent damage to the structure under seismic excitation. The exoskeleton is also used for energy retrofit, by combining active and passive solutions. A design procedure is illustrated step-by-step for the case study. The results show a significant improvement of thermal characteristics of the building envelope, with a relevant reduction of primary energy, and of the seismic capacity of the existing structure that preserves its elastic behaviour. Moreover, this approach is also convenient from an economic point of view compared to a total demolition and reconstruction.

The exact worst-case convergence rate of the alternating direction method of multipliers

AbstractRecently, semidefinite programming performance estimation has been employed as a strong tool for the worst-case performance analysis of first order methods. In this paper, we derive new non-ergodic convergence rates for the alternating direction method of multipliers (ADMM) by using performance estimation. We give some examples which show the exactness of the given bounds. We also study the linear and R-linear convergence of ADMM in terms of dual objective. We establish that ADMM enjoys a global linear convergence rate if and only if the dual objective satisfies the Polyak–Łojasiewicz (PŁ) inequality in the presence of strong convexity. In addition, we give an explicit formula for the linear convergence rate factor. Moreover, we study the R-linear convergence of ADMM under two scenarios.

English Language Skills for Islamic Economic Students: Expectation versus Reality

This study focuses on the English language instruction provided to students majoring in Islamic Economics, aiming to equip them with the necessary skills for successful engagement both in the classroom and the workplace. The research conducted for this purpose had a dual objective: firstly, to investigate the perspectives of both students and lecturers on the types of English language skills required for an Islamic Economics major, and secondly, to assess the relevance of the current English for Specific Purposes (ESP) course in meeting the students' actual needs. The participants in this qualitative descriptive study included three lecturers and 219 students enrolled in the third and fifth semesters of the Islamic Economics Study Program at a State Islamic University in Indonesia. The study employed qualitative research methods, utilizing two data collection methods: an online survey addressing student demographics and perceived language skill needs, and interviews with participating lecturers. The findings reveal disparities between the perceptions of instructors and students regarding essential linguistic abilities. While the majority of students prioritize speaking and writing, instructors emphasize reading and proper grammar. The study recommends a redesign of the existing ESP syllabus to better align with the identified needs of the students.

Gender‐based learning and behavioural differences in an educational social media platform

AbstractBackgroundGender differences in the use of educational environments and social media platforms have been a topic of interest in research. Several studies have examined the disparities between female and male participants in terms of participation, engagement, and motivations in either educational or social media platforms. On this end, this study proceeds to explore gender disparities in an innovative educational environment that sees the incorporation of an educational component within a simulated social media environment.ObjectivesDriven by a dual objective, this study aims to first investigate the impact of gender on skills development in an educational social media platform, and second, to explore the behavioural differences between female and male adolescents social interactions within the platform.MethodsThe study involved 142 high school students in Barcelona and utilised an ad‐hoc questionnaire to assess students' skills. To explore students' behaviour within the platform, actions such as likes, comments, publishing, visiting profiles, and viewing images, were recorded using the Experience API.Results and ConclusionsOur study's findings indicate that both female and male students benefited from the intervention implemented within the educational social media platform. Moreover, the results revealed distinct interaction patterns between female and male participants. These findings provide valuable insights into how adolescents of different genders interact within an educational social media platform. Additionally, the design principles outlined in this study can inform the development of future educational social media interventions that effectively engage the preferences of both genders.

A Dual Neural Network Approach to Topology Optimization for Thermal-Electromagnetic Device Design

Topology optimization for engineering problems often requires multiphysics (dual objective functions) and multi-timescale considerations to be coupled with manufacturing constraints across a range of target values. We present a dual neural network approach to topology optimization to optimize a 3-dimensional thermal-electromagnetic device (optical shutter) for maximum temperature rise across a range of extinction ratios while also considering manufacturing tolerances. One neural network performs the topology optimization, allocating material to each sub-pixel within a repeating unit cell. The size of each sub-pixel is selected with manufacturing considerations in mind. The other neural network is trained to predict performance of the device using extinction ratio and temperature rise over a given time period. Training data is generated using a finite element model for both the electromagnetic wave frequency domain and thermal time domain problems. Optimized designs across a range of targets are shown.

On the need to create a new profession in France: The dental assistant specializing in advanced practices

The law modernizing the French health care system sets out the legal framework for what can be called “advanced practice” for medical auxiliaries. This type of health care practice already exists in many countries. In France, we have chosen to deploy it within a team, starting with the nursing profession. Advanced practice has a dual objective: to improve access to care and the quality of patient care by reducing doctors’ workloads in targeted pathologies. In addition, advanced practice encourages paramedical professionals to diversify and develop their skills to a high level. Among medical auxiliaries, dental assistants could benefit from this legal framework, in a country where access to primary care and oral health education is complicated, if not impossible in some “medical deserts.” The role of these new health care professionals would therefore be to deliver preventive oral care (primary, secondary, and tertiary prevention) to promote and improve patients’ oral health.

Urban water resources management with energy constraint and carbon emission intensity under uncertainty: A dual objective optimization model

Water production, utilization and recycle in urban system associated with a large amount of energy consumption and carbon emission that has increasingly international attention under sustainable development goals. In this study, a comprehensive urban water resources system management model is proposed under water-energy-carbon nexus and multiple uncertainties. The water-energy-carbon nexus was reflected in the processes of water extraction, water production and sewage treatment, and two objectives of maximizing the system benefit and minimizing carbon emission is transformed into two linear programming problem through the dual-objective interval fractional programming. Considering the interaction among water supply/demand, pollutants discharge control, energy consumption and self-energy utilization, indirect carbon emission as the main constraints, the developed model is applied to a typical water and energy sources shortage area of Qingdao city in north China. Multiple scenarios related to energy consumption and carbon emission control are designed to search the relationship among energy consumption, carbon emission and water resources allocation schemes. The results indicated that water demand as the main driving factor of energy consumption and carbon emission in urban water system cannot be directly limited through water supply structure adjustment. Through introducing self-energy supply (sludge utilization) and energy consumption control, water resources allocation schemes and water supply structure would be changed to improve energy saving potential with an obvious decrease trend of carbon emission intensity from 0.7921 tCO2/MWh to 0.5544 tCO2/MWh. The model could effectively provide reasonable urban water system management strategies under different water allocation demands and carbon emission challenges scenarios and deal with multiple uncertainties in decision-making process.

Synthesis of a Stable and High-Concentration BaHfxTi1−xO3 Sol–Gel for High Electromechanical Performance of Bulk Ceramics

Lead-based materials are widely used in piezoceramics due to their high electromechanical properties. However, due to environmental protection and sustainable development, the use of the toxic element lead (Pb) in electronic devices is strictly restricted, therefore requiring the rapid development of piezoelectric-based devices with lead-free ceramics. In this context, a lead-free doped barium titanate was studied with a dual objective. First, a new sol–gel method to synthesize Hf4+-doped BaHfxTi1−xO (BHT) with x = 0.05, 0.075, and 0.10 is presented. Such BHT sols were prepared at high concentrations of up to 1 M. Dilution in ethylene glycol allowed parameters (viscosity, colloid sizes, etc.) to be controlled, which ensured a time-stable sol for several months at room temperature. Second, densified bulk ceramics with attrited powders were obtained from these sols and showed very good electromechanical properties, with a thickness coupling factor of kt = 47% (BaHf0.05Ti0.95O3 sintered at 1500 °C/6 h). These results are a first step that will allow the processing of lead-free piezoelectric thick films using a sol–gel composite method for vibrational energy harvesting applications.

Resilience and performance: capturing their synergy for ongoing success

PurposeMost companies struggle to meet the dual goals of sustaining competitive advantage and ensuring high resilience during crises. Those that do, research tells, adapt their operational practices along the crisis cycle, combining an effective cost approach at the start of a crisis, while quickly relaunching their investment to grow ahead of competition, just when they learn that the crisis is peaking, and not too late, when the crisis is over. This cycle alignment is possibly the crucial, but not the only, factor for success. We update early research to show that companies succeeding in this dual objective also take a proactive strategy approach of capturing the complementarities between both performance and resilience during a period of high turbulence. This complementarity relies on exploiting dynamic capabilities common to both resilience and performance, and on leveraging the resilience process as a foundation for strategic renewal going forward.Design/methodology/approachThe research relies on case studies, complemented by an original survey sample, collected just after the peak of the covid-19 pandemic, of 4,000 multinational firms spread across 18 industries termed NACE2, a statistical classification of economic activities in the European Community. This study included 10 countries outside the European Community. The sample collects information on five core enterprise capabilities (agility, innovativeness, active ecosystem play and digital/sustainability maturity, flexible work practices) and uses a variety of quantitative techniques to assess that existence and size of synergies captured by firms.FindingsCompanies meeting the dual goal of resilience and performance are more than doubling their rate of profit growth relatively to peers, after the peak of the crisis, by leveraging of synergies between performance and resilience.Originality/valueThe topic is essential for management, given the elevated turbulence. This research confirms that resilience and performance are synergistic and helps make companies using each crisis boost performance forward.

The optimal allocation of H-SFCL in MVDC SPS

Medium voltage direct current shipboard power system (MVDC SPS) is the development trend of navy in the future. At present, one of the bottlenecks restricting the development of MVDC SPS is that the short fault. There is a lack of effective means to limit short fault current to protect MVDC SPS. This paper presents a method of applying a hybrid type superconducting fault current limiter (H-SFCL) to MVDC SPS protection. The architecture and system modeling of MVDC SPS are introduced, and the mechanism of bipolar DC short fault is analyzed. The topology and working principle of H-SFCL are introduced. The small-scale prototype experiment is done, the current limiting effect of H-SFCL is compared with resistive type superconducting fault current limiter (R-SFCL) and flux-coupling type superconducting fault current limiter (FC-SFCL) in the prototype test, so as to verify the superiority of H-SFCL. A dual objective hierarchical optimization configuration method is proposed, and the number and position of H-SFCLs are verified on a four-terminal system, as well as multi-objective optimization for H-SFCLs. A fault isolation and H-SFCL optimal allocation evaluation model is proposed; An improved method suitable for fault isolation and multi-objective optimal allocation of H-SFCLs is proposed to address the issue of breaking timing between internal switches in H-SFCLs and external circuit breakers in the optimization process. The research results indicate that the proposed optimal allocation method can optimize the inductance, resistance, and switch breaking time inside the current limiter, and can match the timing with the external circuit breaker; The proposed multi-objective optimization configuration method has a maximum effective individual ratio of 88% in the first 20 generations of improvement, and the improved iteration speed has significantly increased. In the 5th generation, the effective individual ratio can reach 100%.

Understanding travel mode choice through the lens of COVID-19: a systematic review of pandemic commuters

ABSTRACT The COVID-19 pandemic disrupted travel behaviours for very large numbers of people including those who shifted to teleworking and those without the option to work from home. While there is much valuable transport research that has examined the former category, it is still unknown how certain people such as health sector employees and delivery drivers changed their physical commuting in transport contexts that were radically different from those existing normally in urban areas. Based on a systematic review of 36 scientific publications on commuting during pandemic, this study pursues a dual objective. First, by examining the interrelated institutional, physical, and socio-psychological processes that supported or hindered low-carbon transport the study revealed that (A) public transport (PT) reduced service levels and concerns related to COVID were positively associated with substantial shifts away from PT towards car and active travel; (B) this positive association was found to be even stronger in the existence of pre-pandemic habit of car use for commute and strong negative emotions like fear triggered by environmental changes and health risks. Second, by synthesising the key findings from the literature, this study provides significant implications for how mode choice is modelled through the Theory of Planned Behavior and Norm Activation Model. By questioning whether the pandemic commuters had a “normal” set of travel mode alternatives to choose from, the study draws attention to the nuances of mode “choice” versus mode “use” and moves beyond the assumption that commuting always results from individuals making choices. It also argues that the role of (negative) emotions along with the importance of proximity to, or separation from, other bodies on how people commute should be considered in future research. Finally, the crucial role of COVID-19 in changing travel-related norms and the resulting long-term implications for policy interventions require further investigation by future research.

Optimization strategy for SAM in nuclear power plants based on NSGA-II

Abstract The Severe Accident Management Guide (SAMG) is an important component of nuclear safety regulations. Many studies are being conducted to optimize severe accident management (SAM) strategies. To ensure the safety of nuclear power plants, decision makers need to monitor multiple parameters with security threats. Therefore, it is particularly important to search optimal SAM strategies under different numbers of mitigation targets. The Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is an evolutionary algorithm that does not require derivative differentiation and is capable of population search. In this study, a nuclear power plant accident optimization strategy is developed using the Modular Accident Analysis Program (MAAP) in conjunction with NSGA-II. The strategy enables decision makers to consider multiple mitigation objectives in a complex decision environment. Focusing on the CPR1000, this study applies the optimization strategy to automatically search for optimal mitigation strategies for small break loss of coolant accident (SBLOCA) and station blackout hot leg creep rupture accidents (SBOHLCR). Comparing the optimization results with the basic accident sequence, it is found that the reactor pressure vessel (RPV) failure time is delayed from 72,702 s to 128,730 s under SBLOCA and from 23,828 s to 28,363 s under SBOHLCR. This study has also verified that the optimal SAM strategy obtained by the strategy through dual objective optimization has better mitigation effects than a strategy that only considers one objective. This optimization strategy has the potential to be applied to other types of severe accident management studies in the future.

Model predictive control for smart buildings: a simulation approach within Indian context

PurposeIn the context of a developing country, Indian buildings need further research to channelize energy needs optimally to reduce energy wastage, thereby reducing carbon emissions. Also, reduction in smart devices’ costs with sequential advancements in Information and Communication Technology have resulted in an environment where model predictive control (MPC) strategies can be easily implemented. This study aims to propose certain preemptive measures to minimize the energy costs, while ensuring the thermal comfort for occupants, resulting in better greener solutions for building structures.Design/methodology/approachA simulation-based multi-input multi-output MPC strategy has been proposed. A dual objective function involving optimized energy consumption with acceptable thermal comfort has been achieved through simultaneous control of indoor temperature, humidity and illumination using various control variables. A regression-based lighting model and seasonal auto-regressive moving average with exogenous inputs (SARMAX) based temperature and humidity models have been chosen as predictor models along with four different control levels incorporated.FindingsThe mathematical approach in this study maintains an optimum tradeoff between energy cost savings and satisfactory occupants’ comfort levels. The proposed control mechanism establishes the relationships of output variables with respect to control and disturbance variables. The SARMAX and regression-based predictor models are found to be the best fit models in terms of accuracy, stability and superior performance. By adopting the proposed methodology, significant energy savings can be accomplished during certain hours of the day.Research limitations/implicationsThis study has been done on a specific corporate entity and future analysis can be done on other corporate or residential buildings and in other geographical settings within India. Inclusion of sensitivity analysis and non-linear predictor models is another area of future scope.Originality/valueThis study presents a dynamic MPC strategy, using five disturbance variables which further improves the overall performance and accuracy. In contrast to previous studies on MPC, SARMAX model has been used in this study, which is a novel contribution to the theoretical literature. Four levels of control zones: pre-cooling, strict, mild and loose zones have been used in the calculations to keep the Predictive Mean Vote index within acceptable threshold limits.

A novel supported Mn-Ce catalyst with meso-microporous structure for low temperature synergistic removal of nitrogen oxides and toluene: structure–activity relationship and synergistic mechanism

The design and preparation of highly stable and active bifunctional catalysts that function well over a wide temperature range and resist poisoning is a major obstacle in the dual objective of eliminating nitrogen oxides and toluene from flue gas. In this reported work, a series of supported Mn-Ce catalysts with different molecular sieves support (microporous MnCe/ZSM-5, mesoporous MnCe/AlMCM-41 and micro-mesoporous MnCe/ZSM-5@AlMCM-41) were developed and their reaction performance was evaluated for the process of simultaneously removal of NOx and toluene. Of the catalysts prepared, the MnCe/ZSM-5@AlMCM-41 catalyst appeared to exhibit excellent catalytic activity and good poisoning resistance. The catalysts’ structure–activity relationships were studied using a series of characterizations. These characterization test results revealed that the outstanding catalytic activity and poisoning resistance of the MnCe/ZSM-5@AlMCM-41 catalyst were associated with its suitable micro-mesopore proportion, high ratio of Mn4+, Ce3+ and the abundance of various active oxygen groups on the catalyst surface. Further investigation revealed the details of the synergistic mechanism of the catalysts that were responsible for catalytic removal of NOx and toluene. The results of this work showed that 1) appropriate proportions of mesopores in the catalysts mitigated the reaction of toluene or oxidation intermediates with NH3 and NO to form nitrogen-containing intermediate species (benzonitrile and benzamide). This reduced the population of these N-containing intermediate species present at the catalyst’s active sites; 2) appropriate proportions of mesopores in the catalysts helped to reduce the reaction between the nitrite/nitrate groups with toluene, thus promoting the utilization of activated nitrate/nitrite species in the NH3-SCR reaction.

Improved Genetic Algorithm Based on Oscillation Factor to Solve the AUV Path Planning Problem

In this paper, the bi-objective AUV path planning problem considering the shortest path and the minimum path smoothness is studied. Firstly, a mathematical model of the problem is established and a two-dimensional Cartesian coordinate system model is used to model the AUV working environment. Then the dual objective is normalized and transformed into an adaptation function by dimensionality reduction. An improved Genetic Algorithm is proposed to solve the problem according to its characteristics. An initial solution generation strategy for the n-1 equipartition method based on the improved oscillation factor is designed, and an elite retention strategy with simulated annealing operation is introduced to improve the genetic strategy. To verify the effectiveness of the improved algorithm in this paper, simulation experiments were conducted by the Microsoft Visual Studio platform. After the comparison and analysis of the three algorithms, the algorithm proposed in this paper has shorter and smoother paths, faster convergence speed, and more obvious advantages in the quality of the solution.

Analyzing the effects of energy productivity: the case of European Union countries.

The surge in fossil fuel consumption, culminating in global warming and climate change, compels nations to implement protective measures. Consequently, the concepts of "sustainable growth" and the "green economy" have gained prominence in response to heightened environmental consciousness. In light of these imperatives, nations have embarked on the formulation of sustainable and environmentally conscious policies, with the dual objective of safeguarding the environment and fostering economic growth. These factors have collectively contributed to the growing significance of energy policies within European nations, spurring a burgeoning momentum in research areas pertaining to energy efficiency and energy productivity. While extant literature has demonstrated the positive environmental impact of energy productivity, there exists a paucity of research pertaining to its economic implications. Energy productivity, defined as achieving equivalent or greater output with reduced energy consumption, bears the potential to influence economic output, thereby exerting cascading effects on various facets of the economy, including growth and exports. The principal aim of this study is to highlight that the augmentation of energy productivity can yield not only environmental advantages but also economic benefits. To achieve this objective, we conduct econometric analyses on panel data spanning the years 2000 to 2020 across the 27 member states of the European Union. Specifically, we explore the effects of energy productivity on diverse economic parameters, encompassing economic growth, high technology exports, medium and high technology exports, total exports, and trade volume. Employing the Driscoll-Kraay standard errors estimator, our findings evince that energy productivity exerts statistically significant and positive influences on economic growth, medium and high technology exports, total exports, and trade volume.

Financial development, energy consumption, and economic growth in the ASEAN countries: evidence from the PVAR approach.

The Association of Southeast Asian Nations (ASEAN), a new global economic force, has struggled to achieve a dual objective of enhanced economic growth and improved environmental quality. Financial development is generally considered an important tool in achieving these simultaneous objectives. This paper examines the response mechanism and the inter-relationship between the ASEAN region's financial development, energy consumption, and economic growth. Unlike previous studies, the paper uses a generalized method of moments panel vector autoregression (GMM-panel VAR) framework for the 1981-2021 period. The second-generation Granger causality test is used to identify their causality relationship. Economic growth supports financial development and reduces energy consumption from fossil fuel sources in the ASEAN countries. Financial development also reduces fossil fuel energy consumption. The bi-directional relationship between economic growth and fossil fuel energy consumption exists. Energy consumption and financial development are also bi-directionally linked. However, only the unidirectional Granger causality from economic growth to financial development is found. The variance decomposition analysis results confirm that economic growth accounts for the most significant variance in fossil fuel energy consumption and financial development in the ASEAN countries. Policy implications have emerged based on these findings.

Implementation of Indian National plasma policy at blood bank of a tertiary care hospital: A step towards strengthening of blood transfusion services

IntroductionThe World Health Organization has advocated that every country should make its own policy for ensuring safe and adequate supply of plasma derived medicinal products through mobilization and usage of locally collected plasma. The National Plasma Policy (NPP) of India was published in 2014 with a dual objective to achieve self sufficiency in the production of plasma derived medicinal products and at the same time to augment the component preparation facilities in India and overall upliftment of blood transfusion services in the country. Thus the present study was done to access the impact of implementation of NPP in our blood bank on the blood transfusion services in our hospital. Materials and methodsThe present study was a retrospective observational study conducted in the department of transfusion medicine of a tertiary care hospital in India involving analysis of data from 1st January 2019 till 31st December 2022. For the purpose of data analysis the time period was divided into 2 periods: (i) Pre-NPP implementation period from 1st January 2019 till 31st December 2020; (ii) Post-NPP period from 1st January 2021 till 31st December 2022. The following parameters were compared for the two periods: (i) component preparation rate; (ii) percentage of component therapy; (iii) total number of FFP transferred to plasma fractionation centers; (iv) total amount of exchange amount generated in lieu of transferred FFP to plasma fractionation centers. ResultsThe component preparation rate after NPP implementation was significantly higher as compared to the pre NPP implementation period (93.81% vs 56.70%; p = 0.007). The percentage of component therapy in the patients was also significantly higher as compared to the pre-NPP implementation period (97.9% vs 73.6%; p = 0.005). The total amount of exchange amount generation in Indian rupee (INR) after NPP implementation was INR 1419462 (15835€) while it was INR 636898 (7105€) in the pre NPP implementation period. This amount was utilized for procurement of various blood bank equipment, in addition 2 lab technicians were also hired for the blood bank. ConclusionsThe implementation of NPP resulted in upliftment of blood transfusion services in our hospital. Other low and middle income countries can benefit from implementation of similar plasma policy in their countries.

A High-Precision Ensemble Model for Forest Fire Detection in Large and Small Targets

Forest fires are major forestry disasters that cause loss of forest resources, forest ecosystem safety, and personal injury. It is often difficult for current forest fire detection models to achieve high detection accuracy on both large and small targets at the same time. In addition, most of the existing forest fire detection models are single detection models, and using only a single model for fire detection in a complex forest environment has a high misclassification rate, and the accuracy rate needs to be improved. Aiming at the above problems, this paper designs two forest fire detection models (named WSB and WSS) and proposes an integrated learning-based forest fire detection model (named WSB_WSS), which also obtains high accuracy in the detection of forest fires with large and small targets. In order to help the model predict the location and size of forest fire targets more accurately, a new edge loss function, Wise-Faster Intersection over Union (WFIoU), is designed in this paper, which effectively improves the performance of the forest fire detection algorithm. The WSB model introduces the Simple-Attention-Module (SimAM) attention mechanism to make the image feature extraction more accurate and introduces the bi-directional connectivity and cross-layer feature fusion to enhance the information mobility and feature expression ability of the feature pyramid network. The WSS model introduces the Squeeze-and-Excitation Networks (SE) attention mechanism so that the model can pay more attention to the most informative forest fire features and suppress unimportant features, and proposes Spatial Pyramid Pooling-Fast Cross Stage Partial Networks (SPPFCSPC) to enable the network to extract features better and speed up the operation of the model. The experimental findings demonstrate that the WSB model outperforms other approaches in the context of identifying forest fires characterized by small-scale targets, achieving a commendable accuracy rate of 82.4%, while the WSS model obtains a higher accuracy of 92.8% in the identification of large target forest fires. Therefore, in this paper, a more efficient forest fire detection model, WSB_WSS, is proposed by integrating the two models through the method of Weighted Boxes Fusion (WBF), and the accuracy of detecting forest fires characterized by small-scale targets attains 83.3%, while for forest fires with larger dimensions, the accuracy reaches an impressive 93.5%. This outcome effectively leverages the strengths inherent in both models, consequently achieving the dual objective of high-precision detection for both small and large target forest fires concurrently.