Planning Methods Research Articles

An Improved HBA Method for Path Planning of Substation Inspection Robots

Aiming at the problems of honey badger algorithm (HBA) in the path planning of substation inspection robot, such as long path length, time-consuming search and high obstacle risk rate, an improved HBA algorithm called IHBA is proposed. Firstly, the honey badger population is initialized by reverse learning mechanism to increase its diversity. Secondly, the adaptive weight factor is used to improve the density factor of the HBA, which effectively balances the exploration capacity in different stages and improves the optimization accuracy of the population. Finally, the elite mutation strategy is used to strengthen the honey badgers’ location, which can guide the population to produce offspring in the food source area with better adaptability. To verify the improved effect of the algorithm and its path planning performance, the path planning experiments are designed, which indicate that compared with the BOA, IACO, GFA and classic HBA, the proposed IHBA in this paper has shorter path, higher search efficiency and lower obstacle risk rate, which can not only help the substation inspection robot plan the optimal path globally, but also increase the smoothness of the planned path.

Documenting the availability and accessibility of reproductive health services for youth in Albania

Abstract Youth in Albania are initiating sexual activity at an earlier age. However, use of all forms of contraception has declined in the last decade and uptake now stands at 4%. The self-reported prevalence of sexually transmitted infections (STIs) and STI symptoms has risen dramatically, as has reliance on abortion as a predominant method of family planning. In 2020-2022, we conducted a multi-method qualitative study in Albania to document the availability and accessibility of sexual and reproductive health (SRH) services and examine challenges that youth face when seeking SRH care. This study comprised a document review, a curriculum review, a community-based survey with 273 youth, semi-structured interviews with 15 youth, semi-structured interviews with 15 key informants, and a service mapping exercise in Tirana. Lack of adequate infrastructure and bureaucratic hurdles make it difficult for youth to navigate and access SRH services in Albania. A third of survey participants (n = 90, 33%) expressed discomfort inquiring about SRH matters, while nearly two-thirds rarely or never sought SRH services from a doctor or clinic. Furthermore, Albania’s school-based sexuality education curriculum lacks in topics, content, and responsiveness, resulting in inconsistent learning experiences and limited knowledge of SRH. Sexuality education is primarily focused on the anatomy and physiology of reproduction, leading to significant knowledge gaps in other aspects of SRH. Only half of survey participants (n = 150, 55%) had received any education on birth control, contraception, or family planning; and only few had knowledge about gender identity (n = 103, 38%), or consent (n = 77; 28%). Widespread lack of awareness and fear of judgment contribute to the underutilization of SRH services among youth in Albania. Improving knowledge and awareness, alongside investing in infrastructure and capacities, are essential to enhancing accessibility and quality of SRH services for Albanian youth. Key messages • Lack of knowledge and awareness prevent youth from accessing SRH services. • Establishing youth-friendly services and training health providers and educators are crucial to delivering confidential and non-judgmental youth-friendly SRH care.

6.D. Skills building seminar: Family Vulnerability Scale: Why and how to use at Primary Health Care to promote health equity?

Abstract Family vulnerability encompasses multiple perspectives that are interconnected with the health needs of each family member. Families experiencing vulnerability face heightened risks of poor health outcomes. Nonetheless, these vulnerabilities are further compounded by systemic inequalities within healthcare systems, where biological or clinical factors are exclusively considered to organize and/or prioritize access, especially given the scarcity of valid instruments to measure family vulnerability. Primary Health Care (PHC) plays a pivotal role in addressing health inequalities, especially considering its bond with community. From this context, the Family Vulnerability Scale for Brazil (EVFAM-BR, in Portuguese) was developed and validated, been composed of 14 items about four dimensions (income, healthcare, family and violence) (2019-2023). By reducing the gap between science and practice, the implementation process of EVFAM-BR was started at the same year the scale was validated (2023). First, it occurred at 14 PHC services in São Paulo (Southeast Region, Brazil) and second, since 2024 has been implemented at Boa Vista (North Region, Brazil). Also, between 2024 and 2026, the implementation of EVFAM-BR is expected to take place in other Brazilian states participating in the third phase of the PlanificaSUS project, which is developed aiming to support State health departments to implement the Health Care Planning method to organize and integrate PHC and specialized outpatient care based on population health care needs. At this stage, capacity building is needed to align the concept of family vulnerability and to train PHC managers and health professionals on how to apply and use results from EVFAM-BR. This training has already been performed for around 1,000 health professionals from two different regions of Brazil, including managers, Community Health Workers, nurses, and physicians. The present workshop proposal aims to disseminate the EVFAM-BR and to offer the EVFAM-BR experience. It proposes knowledge transferring throughout participants engagement at three activities. Activity 1) “Family Vulnerability: From concept to a scale validity and application”: it is designed to engage participants to discuss about the family vulnerability concept and applicability at PHC, and to discuss on how EVFAM-BR implementation process has been occurring at Brazil and how can be tailored to other contexts. Activity 2) “Role Play: Practicing EVFAM-BR”: Two cases will be used for role play dynamics that will take place in trios, in which one will represent the community health worker, another will be the patient and the third will be the observer. Activity 3) That ones that assumed observer role will share their experiences of using EVFAM-BR. Finally, a discussion will be facilitated based on the participants’ impressions and a review of the main points covered throughout the workshop. Key messages • Family vulnerability stratification (through EVFAM-BR) is essential to plan services achieving equity and qualified population-based care management and to qualify patient approach and care. • Family Vulnerability Scale (EVFAM-BR) training represents efforts to reduce the gap between research and practice and contributes to address social determinants of health on healthcare.

Research on Obstacle-Avoidance Trajectory Planning for Drill and Anchor Materials Handling by a Mechanical Arm on a Coal Mine Drilling and Anchoring Robot

At present, China’s coal mine permanent tunneling support commonly uses mechanized drilling and anchoring equipment; there are low support efficiency, labor intensity, and other issues. In order to further improve the support efficiency and liberate productivity, this paper further researches the trajectory planning of the drilling and anchoring materials of the robotic arm for the drilling machine “grasping–carrying–loading–unloading” on the basis of the drilling and anchoring robotic system designed by the team in the previous stage. Firstly, the kinematic model of the robotic arm with material was established by improving the D-H parameter method. Then, the working space of the robotic arm with the material was analyzed using the Monte Carlo method. The singular bit-shaped region of the robotic arm was restricted, and obstacles were removed from the working space. The inverse kinematics was utilized to solve the feasible domain of the robotic arm with material. Secondly, in order to avoid blind searching, the guidance of the Bi-RRT algorithm was improved by adding the target guidance factor, and the two-way tree connection strategy for determining the feasible domain was combined with the Bi-RRT algorithm’s feasible domain judgment bi-directional tree connection strategy to improve the convergence speed of the Bi-RRT algorithm. Then, in order to adapt to the dynamic environment and avoid the global planning algorithm from falling into the local minima, on the basis of the above planning methods, an improved Bi-RRT trajectory planning algorithm incorporating the artificial potential field was proposed, which takes the planned paths as the guiding potential field of the artificial potential field to make full use of the global information and avoid falling into the local minimization. Finally, a simulation environment was built in a ROS environment to compare and analyze the planning effect of different algorithms. The simulation results showed that the improved Bi-RRT trajectory planning algorithm incorporating the artificial potential field improved the optimization speed by 69.8% and shortened the trajectory length by 46.6% compared with the traditional RRT algorithm.

Family planning knowledge, use, and associated factors among women with mental illness and epilepsy in Rwanda: a cross-sectional study

IntroductionFamily planning knowledge and access to quality family planning services occupy a central position in the lives of all women of reproductive age. However, women with mental illness and epilepsy who are at a high risk of sexual violence, unwanted pregnancies, poor obstetric outcomes, and drug interaction consequences, need it the most. Understanding their family planning knowledge and utilization remains crucial for meeting their needs. The present study aims to assess knowledge, use of family planning, and associated factors among women living with mental illness and epilepsy who attend the Ndera Neuropsychiatric Hospital and affiliated branches.MethodologyA cross-sectional study was conducted between October 2022 and February 2023. The study involved a purposive sample of 289 women who attended the Ndera Neuropsychiatric Hospital and its two affiliated branches during the data collection period. Psychiatric nurses administered a structured questionnaire. Data were analyzed using descriptive statistics, and multiple logistic regression analysis was performed to assess the factors associated with the use of family planning methods.ResultsOut of 289 who participated in the study, the majority (96.9%) were aware of family planning methods, most (67.8%) had used one method once in their life course, a half (51.9%) were using a family planning method at the time of data collection, and a slight number (26%) expressed intentions of using a family planning method in the future. The most known and used methods were respectively the injectable (17.5%) and oral contraceptive pill (17.5%). Regarding the natural family planning methods, breastfeeding and withdrawal were less used. Being single (AOR = 66.4, 95% CI: 9.8, 44) or married (AOR = 51.4, 95% CI: 11.9–22), having a primary level of education (AOR = 5.6, 95% CI: 2.0, 15.9), knowing a contraceptive method (AOR = 5.8, 95% CI: 0.6, 49) and suffering from brief psychotic disorders (AOR = 2.7, 95% CI: 1.1, 6.6) predicted a higher utilization of family planning.ConclusionMost of the women with mental illness in this study were aware of family planning methods and had used one of the family planning methods in life. The national average is below when it comes to family planning awareness. It is important to improve family planning education and counseling for women who attend psychiatric outpatient clinics.

Automated planning of curved needle channels in 3D printed patient-tailored applicators for cervical cancer brachytherapy.

Purpose&#xD;Patient-tailored intracavitary/interstitial (IC/IS) brachytherapy (BT) applicators may increase dose conformity in cervical cancer patients. Current configuration planning methods in these custom applicators rely on manual specification or a small set of (straight) needles. This work introduces and validates a two-stage approach for establishing channel configurations in the 3D printed patient-tailored ARCHITECT applicator. &#xD;&#xD;Methods&#xD;For each patient, the patient-tailored applicator shape was based on the first BT application with a commercial applicator and integrated connectors to a commercial (Geneva) intrauterine tube and two lunar ring channels. First, a large candidate set was generated of channels that steer the needle to desired poses in the target region and are contained in the applicator. The channels' centrelines were represented by Bézier curves. Channels running between straight target segments and entry points were optimised and refined to ensure (dynamic) feasibility. Second, channel configurations were selected using geometric coverage optimisation. This workflow was applied to establish patient-tailored geometries for twenty-two patients previously treated using the Venezia applicator. Treatment plans were automatically generated using the in-house developed algorithm BiCycle. Plans for the clinically used configuration, TPclin, and patient-tailored configuration, TParch, were compared.&#xD;&#xD;Results&#xD;Channel configurations could be generated in clinically feasible time (median: 2651s, range 1826-3812s). All TParchand TPclinplans were acceptable, but planning aims were more frequently attained with patient-tailored configurations (115/132 versus 100/132 instances). Median CTVIRD98and bladderD2cm3doses significantly improved (p< 0.001 andp< 0.01 respectively) in TParchplans in comparison with TPclinplans, and in approximately half of the patients dosimetric indices improved. &#xD;&#xD;Conclusion&#xD;Automated patient-tailored BT channel configuration planning for 3D printed applicators is clinically feasible. A treatment planning study showed that all plans met planning limits for the patient-tailored configurations, and in selected cases improved the plan quality in comparison with commercial applicator configurations.&#xD.

The Assessment of Land Suitability for Urban Expansion and Renewal for Coastal Urban Agglomerations: A Pilot Study of the Guangdong-Hong Kong-Macao Greater Bay Area

Effectively and rationally allocating land resources, while coordinating urban expansion with internal renewal strategies, is crucial for achieving high-quality regional development in coastal urban agglomerations. Land-use suitability assessment (LSA) is a key method for coastal land-use planning, but it is primarily used to delineate ecological redlines or areas for urban expansion, often overlooking the spatial analysis needed for urban renewal. This is particularly critical in coastal urban agglomerations facing land scarcity and ecological fragility. Here, we combined land use and the Analytical Hierarchical Process (to consider stakeholder priorities) in a Minimum cumulative resistance model (MCRM) to determine suitable coastal urban growth and renewal based on a suite of 12 indicators relevant to development intensity and stock space. Application to the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) indicates a dominance of the Ecological Buffer Zone (70.5%), and the available stock space in the GBA comprises only 9.2% of the total area. Our modeling framework tailored different development strategies for different cities: Huizhou and Zhaoqing had space for urban expansion to varying degrees, while other cities were found to be suitable for urban renewal due to low stock space and high development intensity. Our modeling approach, incorporating stakeholder input and objective evaluation of geographic land-use information, can assist planners in improving ecological security while promoting high-quality developments in coastal areas.

Multi-stage planning of clean resources and energy storage assets with hybrid uncertainty modeling for low-carbon resilient distribution systems

Climate change drives the urgent need for low-carbon and resilient energy system transitions. However, current planning methods ignore the inherent conflicts between carbon emission reduction and resilience enhancement, failing to optimally balance asset allocation for both aspects. They also neglect the long-term dynamic and stochastic nature of transitions, exposing systems to hybrid uncertainties. This paper presents a multi-stage dynamic planning method for clean resources and energy storage assets in power distribution networks. First, to facilitate low-carbon and resilient transitions, adaptive, stage-wise planning decisions are optimally determined under various planning strategies to mitigate risks stemming from hybrid uncertainties. Second, to precisely quantify the impact of hybrid uncertainties on decision-making, a systematic hybrid-uncertainty modeling approach is designed to capture short- and long-term uncertainties arising from both exogenous and endogenous factors. Third, to alleviate computational complexity, a decomposition-based stochastic dynamic dual integer programming method with augmented cut generation is introduced, which decomposes the original problem into stage-wise subproblems coordinated through forward and backward steps. Numerical results show that the proposed method generates cost-effective planning schemes, yielding $60 K in savings and reducing carbon emissions by 3853 tons. The method also demonstrates strong scalability, with a 52% reduction in solution time for large-scale planning problems.

Near‐Infrared Nanoparticle‐Mediated Photothermal Cancer Therapy: A Comprehensive Review of Advances in Monitoring and Controlling Thermal Effects for Effective Cancer Treatment

ABSTRACTPhotothermal therapy (PTT) has emerged as a promising alternative to conventional cancer treatments such as radiation therapy, chemotherapy, and surgery. PTT uses light‐absorbing nanomaterials to induce localized hyperthermia and selectively eliminate cancer cells, thus offering advantages over traditional interventions. This literature review focuses on nanoparticles for PTT, their heating properties, and their functions in theragnostic applications for photothermal cancer treatment. It highlights the fundamental principles, recent spectroscopic developments for diagnosis and treatment monitoring, clinical advancements in near‐infrared (NIR) nanoparticle‐mediated PTT, and emerging numerical methods for preclinical planning of PTT.

Optimal planning of SOP in distribution network considering 5G BS collaboration

AbstractThe flexibility of soft open point (SOP) in spatial power regulation enhances the distribution network's (DN) integration of large‐scale renewable energy sources. However, the high cost of SOP and its limited capability for temporal power regulation impede its widespread adoption. Given the rapid expansion of 5G base stations (BSs), utilizing their energy storage to participate in DN planning and operation optimization provides a promising solution. Therefore, this paper proposes an optimal planning method of SOP in DN, considering collaborations with 5G BSs. The objective is to enhance DN’s power regulation in both temporal and spatial dimensions, while minimizing the investment cost of SOP and fully utilizing the unused capacity in base station energy storage (BSES). Firstly, the flexible regulation models of SOP and 5G BS are established, with the real‐time dispatchability of BSES formulated. Then, a bi‐level optimization model is proposed, where the planning layer aims to minimize the total cost, while the operational layer aims to decrease the average voltage deviation. Additionally, an improved Shapley value method based on interactive power is developed for benefit allocation, which enhances the engagement of 5G BSs to participate in DN regulation. The effectiveness of proposed method is validated by simulation results.

Integrating lean production and agile project management: a planning and control model for multi-project environments in construction

The Last Planner System (LPS) and Scrum are established planning and control methods that have produced positive results in managing complex projects. They are based on two different but overlapping theoretical frameworks: Lean Production and Agile Project Management. However, there is a lack of academic studies on how to combine those methods and whether their theoretical underpinnings are compatible. Furthermore, previous studies about those methods have not addressed the context of multiple projects developed simultaneously, and the connections between project management from the perspective of client organisations and production management from the perspective of suppliers. This research work proposes a planning and control model for this context. Using Design Science Research (DSR), an empirical study was carried out at a department store company in Brazil. The practical contributions of this study are related to adapting and combining LPS and Scrum elements to the context investigated. The model includes innovative practices, such as integrated look-ahead planning meetings between the project and the production management levels and using Scrum practices to remove certain constraints. This study also sheds light on the commonalities and differences between LPS and Scrum based on how they support the application of important production principles in construction.

Individual empowerment and community norm effects of engaging young husbands in reproductive health in rural India: findings from a pilot study

BackgroundDespite decades of a call to action to engage men in reproductive health, men are often left out of programs and interventions. In India, where half of pregnancies are reported as unintended, patriarchal gender norms and still dominant patterns of arranged marriages make engaging men in family planning and strengthening couples communication critical in increasing reproductive autonomy and helping young couples meet their reproductive goals. This study explores the feasibility and acceptability from the men’s perspective of the pilot of a gender transformative intervention for newly married couples in India.MethodsA pilot study was conducted of TARANG, a 4 month intervention for newly married women, with light touch engagement of husbands (4 sessions). A total of 41 husbands participated in the pilot, and we collected baseline knowledge and endline feasibility and acceptability data from them, along with in depth qualitative interviews with 13 men. The study was conducted in June 2023-January 2024.ResultsMen had low levels of knowledge about biology, family planning, with the majority of men reporting that no one had provided them information about these topics. Most men wanted to delay the first birth by at least 2 years, yet less than a quarter had discussed childbearing plans with their partner or engaged in family planning methods. While all men reported high acceptability (satisfaction and usefulness), feasibility (participation) was low, with only 43% attending 2 or more sessions. Main barriers to participation included commitments due to work and migration. Men reported that the intervention led to improvements in their relationships with their wives, gave them a sense of empowerment, and led them to become resources for other men in their community.ConclusionsMen in these rural communities are not receiving the information that they need to meet their reproductive goals, however, they greatly desire this information and ways to improve relationships with their new wives. Such an intervention appears to have the potential to help change norms and spread information in the community and provide men with positive, life affirming feelings. Providing information through technology could address barriers to in-person engagement.Trial registration clinicaltrials.gov 03/13/24.NCT06320964

Route Planning Method of UAV Patrol Based on High Precision Tower Model

The high-precision positioning technology of industrial Unmanned Aerial Vehicle (UAV) plays a vital role in intelligent trajectory planning in power inspection. First, the information on power facilities is collected and processed to form a planning grid to optimize the flight path and correct the trajectory of UAV. However, the preparatory work is more complex, and the algorithm model which needs more detailed and complex terrain database data is not universal enough. To improve the safety of UAV and the efficiency of path planning, we establish a three-dimensional model of the power tower, calculate the coordinate position of the inspection work according to the information of the high-voltage transmission tower, and then determine the corresponding relationship between the inspection point and the flight trajectory combined with the safe distance. Based on the set of random interference semaphores and model rasterization, the discrete error strategy and Euler method are introduced to improve the performance. In each iteration, the best solution is first updated using the execution strategy. We continue to calculate the spatial coordinates of all reference points and provide the coordinate position distribution for the flight mission. The solution of equipment inspection trajectory optimization is realized by using dynamic obstacle perception. The proposed discrete measurement error self-correction algorithm is deployed on the flight platform to guide UAV inspection tasks according to the point cloud coordinate model of transmission equipment in the power system and to correct the flight route in time. To verify the research results, the Algorithm Artemisinin optimization and Whale Optimization Algorithm test verify that the ability of the proposed algorithm to get rid of local optimization is improved by 8.94% and, 12.42% respectively compared with other optimization algorithms. The convergence accuracy is 12.4% and 7.9% higher than other schemes, and it has a better effect in solving numerical problems. The research results using the embedded system to complete the task deployment and unloading provide a reference for trajectory planning and task design in different application scenarios.

Multi-Stage Rolling Grid Expansion Planning for Distribution Networks Considering Conditional Value at Risk

Existing single-stage planning and multi-stage non-rolling planning methods for distribution networks have problems such as low equipment utilization efficiency and poor investment benefits. In order to solve the above problems, this paper firstly proposes a multi-stage rolling planning method for distribution networks based on analyzing the limitations of the existing planning methods, which divides the planning cycle of the distribution network into multiple planning stages, and makes rolling amendments to the planning scheme of each stage according to the latest information during the planning cycle. Then, a multi-stage rolling planning model of distribution network taking into account conditional value at risk is established with the objective of minimizing the total investment and operation cost of the distribution network. On the one hand, the users’ electricity bill is taken into account in the objective function, and the necessity of this part of the benefits is demonstrated. On the other hand, the conditional value at risk is used to quantify the uncertainty of the operation cost in the process of the expansion planning of the distribution network, which reduces the operation cost risk of the distribution network. Next, this paper uses the rainflow counting method to characterize the capacity decay characteristics of energy storage in the distribution network, and proposes an iterative solution framework that considers energy storage capacity decay to solve the proposed model. Finally, the proposed method is applied to an 18-node distribution network planning case. This confirms that the multi-stage rolling planning method could improve the investment benefits and reduce the investment cost by approximately 27.27%. Besides, it will increase the total cost by approximately 2750 USD in the case if the users’ electricity bill is not taken into account. And the maximum capacity of energy storage may decay to 87.6% of the initial capacity or even lower during operation, which may cause the line current to exceed the limit if it is not taken into account.

Research on Global Off-Road Path Planning Based on Improved A* Algorithm

In field driving activities, off-road areas usually lack existing paths that can be directly driven on by ground vehicles, but their surface environments can still satisfy the planning and passage requirements of some off-road vehicles. Additionally, the existing path planning methods face limitations in complex field environments characterized by undulating terrains and diverse land cover types. Therefore, this study introduces an improved A* algorithm and an adapted 3D model of real field scenes is constructed. A velocity curve is fitted in the evaluation function to reflect the comprehensive influences of different slopes and land cover types on the traffic speed, and the algorithm not only takes the shortest distance as the basis for selecting extension nodes but also considers the minimum traffic speed. The 8-neighborhood search method of the traditional A* algorithm is improved to a dynamic 14-neighborhood search method, which effectively reduces the number of turning points encountered along the path. In addition, corner thresholds and slope thresholds are incorporated into the algorithm to ensure the accessibility of path planning, and some curves and steep slopes are excluded, thus improving the usability and safety of the path. Experimental results show that this algorithm can carry out global path planning in complex field environments, and the planned path has better passability and a faster speed than those of the existing approaches. Compared with those of the traditional A* algorithm, the path planning results of the improved algorithm reduce the path length by 23.30%; the number of turning points is decreased by 33.16%; and the travel time is decreased by 38.92%. This approach is conducive to the smooth progress of various off-road activities and has certain guiding significance for ensuring the efficient and safe operations of vehicles in field environments.

Research on the path planning integrated with multi-steer modes for heavy reconfigurable unit

Heavy reconfigurable units (HRUs) can form the heavy transportation vehicular platform (HTVP) to perform transportation for large equipment, by combining with each other. With all-wheel-independent-steered, the HRU can realize multi-steer modes (MSMs) such as Ackermann steer mode (ASM), diagonal steering mode (DSM), and zero radius steer mode (ZSM). However, with heavy weight and long wheelbase, the HRU’s mobility is poor if it only employs ASM. Therefore, this paper proposes a hierarchical path planning architecture, realizing path planning integrated with the above steer modes. This architecture includes the MSMs behaviors planning layer (upper layer) and smooth path planning layer (low layer). Firstly, this paper innovative proposes the MSM graph-based search algorithm in the upper layer, which extends nodes through graph-based searching on the grid map considering MSMs information. Then, the upper layer generates MSMs nodes sequence considering improved cost function for MSMs. Secondly, smooth path planning methods for the MSMs are respectively applied to the ASM sequence, DSM sequence, and ZSM sequence. Comparative simulations are shown as results based on measured parameters from real HRU. The results from the proposed method have the lowest or one of the lowest time cost compared with pure ASM planner and special steer modes planner used in the simulations. The maximum optimization rate can reach 10% or more.

Application of experimental planning methods for an analytical description of the areas of operability of marine electromechanical systems

The topic of the study is to consider the possibility of using experimental planning methods to mathematically describe areas of performance in relation to marine electromechanical systems. A definition is given and a graphic illustration of the field of operability is provided. It is shown that information about the boundary of the field of operability allows solving the most important tasks of controlling the state of ship electromechanical systems of various functional purposes. Possible ways of solving the problem of constructing a field of efficiency and the difficulties of their practical implementation are given. The method of analytical description of the operability domain is considered, which assumes an independent approximation of each hypersurface that makes up the operability domain. It is shown that for such an approximation it is convenient to use polynomial dependencies, which can be obtained as a result of using experimental planning methods. The main advantages of this approach are considered, including the possibility of solving the problem in the case of a high dimension of the space of primary parameters, in the space of which the area of operability is built. It is noted that in order to obtain a unified analytical description of the field of operability, the properties of logical R-functions can be used, which make it possible to make the transition from logical functions to analytical dependencies. It is proved that polynomial dependencies have the properties of R-functions and can be used in such a transformation. The resulting analytical description of the health area is universal and does not depend on the configuration of the area itself. Unlike the known methods of analytical approximation of the field of operability, it is characterized by an exceptionally low methodological error and allows us to solve with high reliability the problem of parametric synthesis of marine electromechanical systems according to the criterion of the reserve of operability, as well as the tasks of evaluating and predicting their condition during operation. The considered example clearly demonstrated the sequence of solving the problem of analytical description of the field of operability and allowed us to conclude about the complex configuration of this area even for special cases and the simplest electromechanical systems.

Modern Family Planning Utilization and Associated Factors among Hiv Women of Reproductive Age Attending at Care and Treatment Clinics (CTC) in Mwanza City,tanzania

Background: In Sub-Saharan Africa HIV/AIDS prevalence remains high and makes it the world’s most severely affected region. The use of family planning helps to prevent unplanned pregnancies among HIV positive women of reproductive age. There is a dearth of evidence on the preferred methods, reasons for use and non-use and discontinuation of the use of family planning among HIV positive women of reproductive age appearing at HIV Care and Treatment Clinics (CTCs) in Mwanza City. Therefore this study was conducted to determine family planning uptake, methods preferred and the reasons for discontinuation of the use of family planning among HIV positive women of reproductive age appearing at HIV Care and Treatment Clinics (CTCs) in Mwanza City. Objective: To determine family planning uptake, methods preferred and reasons for discontinuation among HIV positive women of reproductive age appearing at HIV Care and Treatment Clinics (CTCs) in Mwanza City. Methodology: This is a hospital based cross-sectional study involving 440 HIV positive reproductive age women (18 – 49 years) who were attending Bugando Medical Centre, Sekou Toure Regional Referral Hospital and Buzuruga Health Centre HIV Care and Treatment Clinics was carried out. A structured pre tested questionnaire was used to collect data on socio-demographic characteristics, information on current family planning use, health service related factors, family factors, disclosure and ART status, and factors associated with modern family planning use. Data analysis was done using STATA version 13 according to objectives. Results: A total of 440 participants were enrolled in the study and their median age was 36 [IQR 30 – 42] years. Majority, 246(56.2%) of the participants were aged 35 to 49 years. Majority 279 (63.4%) of women attained primary education. Factor associated with family planning discontinuation were not been counseled on FP(AOR 5.5; 95% CI 2.0 – 15.1; p-value 0.001), Partner has desire of children AOR 0.3; 95% CI 0.1 – 0.8;p-value=0.029), Advanced stage of HIV(AOR13.4; 95% CI 5.1 – 35.0; p-value&lt;0.001 ), Divorced women(AOR 3.2; 95% CI 1.1 – 9.7; p-value=0.038) and women’s age ≥35 years(AOR 6.8; 95% CI 2.2-20.9 p-value=0.001). Conclusion: The overall uptake of modern family planning methods was low. Integration of modern family planning services within the CTCs was low too in all the facilities. Furthermore, the proportions of HIV positive women using dual family planning methods were very low. Factor associated with family planning discontinuation were not been counseled on FP, Partner has desire of children, Advanced stage of HIV, Divorced women and women’s age ≥35 years.

Socio-Economical Analysis of a Green Reverse Logistics Network under Uncertainty: A Case Study of Hospital Constructions

This study addresses the critical issue of managing construction and demolition waste in urban environments. Effective waste management is not only essential for minimizing costs but also for enhancing sustainability and reducing environmental impact. In this context, the research introduces a green reverse logistics model designed for C&amp;D waste management, integrating both sustainability considerations and current regulatory frameworks, such as LEED. A key innovation of this model is the incorporation of electric vehicles for waste collection, compared to traditional diesel vehicles, as part of the logistical process, as carbon emission is a significant concern. By evaluating the limitations and opportunities associated with electric vehicles, alongside robust optimization to manage uncertainties in waste collection, the model seeks to balance environmental, social, and economic objectives. It further incorporates decision-making tools like fuzzy logic to optimize multi-objective outcomes across various waste facilities, including separation labs, incineration centers, recycling centers, and landfills. A case study conducted in Tehran validates the model, highlighting the socio-economic and environmental benefits of using electric vehicles in waste collection. Sensitivity analysis indicates that hybrid and socially focused policies perform best under high-impact scenarios, although results can differ with varying data sets. Despite the complexity of managing reverse logistics networks, this research provides valuable insights for supply chain planners. It suggests potential future directions, such as the application of metaheuristic algorithms and improved stochastic planning methods.

Multi-stage automatic and rapid ablation and needle trajectory planning method for CT-guided percutaneous liver tumor ablation.

Computer-assisted planning methods have increasingly contributed to preoperative ablation planning; however, these methods cannot automatically obtain the final optimal solution within a short time and are rarely validated in practice, greatly limiting their clinical applicability. We aimed to propose a full-automatic multi-stage ablation and needle trajectory planning method for CT-guided percutaneous liver ablation to attain the final optimal plans under multiple clinical constraints rapidly. Our proposed method integrates the ablation zone planning fulfilling complete tumor coverage and critical structure avoidance while reaching a trade-off between ablation number and healthy tissue damage, and needle trajectory planning under multiple clinical constraints. Our needle trajectory planning determines feasible skin entry regions based on hard constraints, where the multi-objective optimization (MOO) considering soft constraints is performed using the Pareto Optimality and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods for the final optimal solution. The performance of our proposed method was evaluated on 30 tumors of various characteristics from 23 patients and clinically validated in five clinical cases. Our proposed method achieved 99.8% treatment zone coverage and 40.5% ablation efficiency without involving critical structures, and completely satisfied multiple clinical constraints in all needle trajectory planning results. The average planning time was 23.6 s for tumors of different sizes. All the plans were considered clinically acceptable by the doctors' evaluation. Our method achieved complete tumor coverage without complications in clinical case validation. Our proposed planning method can generate a final optimal plan satisfying multiple clinical constraints within a short time, potentially facilitating preoperative planning for hepatic tumor ablation.