Priority Consideration Research Articles

Встановлення та юридичне оформлення кордонів Української РСР з сусідами – встановлення та часткові уточнення кордонів з РСФРР в 1920-х рр.

This article is the first part of a series of 5 articles dedicated to the establishment of the borders of the Ukrainian SSR (and its legal continuation under the Union Constitution of 5 December 1936 of the Ukrainian SSR) with the neighbouring Soviet republics – the RSFSR, the Belorussian SSR (BSSR) and the Moldavian ASSR (Moldavian Autonomous Socialist Soviet Republic; since 1936 – the Moldavian Autonomous Soviet Socialist Republic) and the latter’s legal successor – the Moldavian SSR. The author points out that the borders of the Ukrainian SSR and the RSFSR (the then names of the republics) in the 1920s were established not on the basis of the ethnographic principle, but for reasons of economic expediency, with priority consideration of Moscow’s interests. For example, the city of Sudzha, which at one time was proclaimed by the Bolsheviks as one of the capitals of “Soviet Ukraine”, became part of the RSFSR. The Russian side emphasised in every possible way that certain disputed regions were important for providing the RSFSR with bread, coal and labour, not stopping short of unilateral actions without the consent of the Ukrainian side and acts of sabotage during the transfer of certain disputed territories to the Ukrainian SSR. The position of the Ukrainians was weakened by the “international” leadership of the republic, driven by the Communist Party’s discipline. At the same time, the existing border between independent Ukraine and the Russian Federation should not be revised, and Ukraine does not claim any Russian territories, including Kursk, as stated in a special statement by the Ukrainian Foreign Ministry in August 2024.

A Two Phases Multiobjective Trajectory Optimization Scheme for Multi-UGVs in the Sight of the First Aid Scenario.

Timely delivery of first aid supplies is significant to saving lives when an accident happens. Among the promising solutions provided for such scenarios, the application of unmanned vehicles has attracted ever more attention. However, such scenarios are often very complex, while the existing studies have not fully addressed the trajectory optimization problem of multiple unmanned ground vehicles (multi-UGVs) against the scenario. This study focuses on multi-UGVs trajectory optimization in the sight of first aid supply delivery tasks in mass accidents. A two-stage completely decoupling fuzzy multiobjective optimization strategy is designed. On the first stage, with the proposed timescale involved tridimensional tunneled collision-free trajectory (TITTCT) algorithm, collision-free coarse tunnels are build within a tridimensional coordinate system, respectively, for the UGVs as the corresponding configuration space for a further multiobjective optimization. On the second stage, a fuzzy multiobjective transcription method is designed to solve the decoupled optimal control problem (OCP) within the configuration space with the consideration of priority constrains. Following the two-stage design, the computational time is significantly reduced when achieving an optimal solution of the multi-UGV trajectory planning, which is crucial in a first aid task. In addition, other objectives are optimized with the aspiration level reflected. Simulation studies and experiments have been curried out to testify the effectiveness and the improved computational performance of the proposed design.

Spatial analysis of the impact of urban built environment on cardiovascular diseases: a case study in Xixiangtang, China

BackgroundThe built environment, as a critical factor influencing residents' cardiovascular health, has a significant potential impact on the incidence of cardiovascular diseases (CVDs).MethodsTaking Xixiangtang District in Nanning City, Guangxi Zhuang Autonomous Region of China as a case study, we utilized the geographic location information of CVD patients, detailed road network data, and urban points of interest (POI) data. Kernel density estimation (KDE) and spatial autocorrelation analysis were specifically employed to identify the spatial distribution patterns, spatial clustering, and spatial correlations of built environment elements and diseases. The GeoDetector method (GDM) was used to assess the impact of environmental factors on diseases, and geographically weighted regression (GWR) analysis was adopted to reveal the spatial heterogeneity effect of environmental factors on CVD risk.ResultsThe results indicate that the built environment elements and CVDs samples exhibit significant clustering characteristics in their spatial distribution, with a positive correlation between the distribution density of environmental elements and the incidence of CVDs (Moran’s I > 0, p < 0.01). Further factor detection revealed that the distribution of healthcare facilities had the most significant impact on CVDs (q = 0.532, p < 0.01), followed by shopping and consumption (q = 0.493, p < 0.01), dining (q = 0.433, p < 0.01), and transportation facilities (q = 0.423, p < 0.01), while the impact of parks and squares (q = 0.174, p < 0.01) and road networks (q = 0.159, p < 0.01) was relatively smaller. Additionally, the interaction between different built environment elements exhibited a bi-factor enhancement effect on CVDs. In the local analysis, the spatial heterogeneity of different built environment elements on CVDs further revealed the regional differences and complexities.ConclusionsThe spatial distribution of built environment elements is significantly correlated with CVDs to varying degrees and impacts differently across regions, underscoring the importance of the built environment on cardiovascular health. When planning and improving urban environments, elements and areas that have a more significant impact on CVDs should be given priority consideration.

The relationship between sustainable values and the pro-environmental behaviour of outdoor sports tourism enthusiasts

ABSTRACT The prevalence of outdoor sports tourism has posed certain threats to the natural environment. In recent years, incidents of outdoor sports enthusiasts damaging ecological environments and historical sites have become increasingly common. Thus, it is imperative to encourage these enthusiasts to protect environmental ecosystems, and sustainability has become a priority consideration for those participating in outdoor sports tourism. This paper explores the multiple mediating roles of environmental knowledge and attitudes in the relationship between sustainable values and the pro-environmental behaviours of outdoor sports tourism enthusiasts. The study aims to provide references and suggestions for promoting environmentally responsible behaviours in outdoor sports tourism and to support the sustainable development of sports tourism in China and globally. The research targets outdoor sports tourism enthusiasts, analysing data from 1079 survey responses. Structural Equation Modeling (SEM) is used to test the direct and indirect effects between variables. The results indicate that sustainable values have a positive impact on environmental attitudes, environmental knowledge, and pro-environmental behaviours. Furthermore, environmental attitudes and knowledge play a positive mediating role between sustainable values and pro-environmental behaviours. Lastly, this paper offers substantial suggestions to promote the sustainable development of outdoor sports tourism.

Aphallia with Anal Stenosis and Congenital Cyanotic Heart Disease: A Rare Case Report

Aphallia, an extremely rare urogenital anomaly, presents complex challenges in diagnosis and management. This anomaly, often accompanied by other congenital malformations, necessitates multidisciplinary care, and careful consideration of treatment priorities. We describe a case of a neonate diagnosed with aphallia along with anal stenosis, bilateral hydroureteronephrosis, and tetralogy of Fallot. Despite prompt intervention plans, the neonate’s condition deteriorated rapidly, highlighting the urgency and complexity of managing aphallia-associated complications. While embryological insights offer some understanding of its etiology, the clinical manifestation of aphallia underscores the need for immediate supportive measures and thoughtful decision-making regarding gender assignment and surgical interventions. Beyond medical considerations, emotional and psychological support for families navigating treatment decisions is paramount.

Balancing clean and quality production goals: A multi-analytical approach to scrutinizing the influencing factors in China's manufacturing industry

Under the strategies of "high-quality development" and "dual carbon goals", the manufacturing industry in China is confronted with the simultaneous challenges of ensuring the production of high-quality goods and adopting environmentally friendly production practices. The integration of cleaner production and quality management has received widespread attention; however, existing research cannot comprehensively identify the interactive factors between quality management and cleaner production and analyze their mechanism of action. This research employed a multi-faceted approach involving meetings, interviews, and online data to access primary materials, and complemented by grounded theory and quality tool (5M1E), a total of 18 quality factors that exert a substantial impact on the attainment of clean production objectives were ultimately identified. To meticulously assess the interrelationships among factors, this study employed the interval value hesitant preference relationship DEMATEL-AISM technique. The findings of the study emphasize the significance of Employee Quality Skill Level (F1) and Production Environment Quality (F15) as critical quality factors that should be given priority and careful consideration by managers aiming for a cleaner production process. The results of this study have the potential to enhance the manufacturing industry's ability to predict and prevent quality and environmental issues, thereby ensuring the long-term sustainability of clean production and effective quality management.

An exploratory framework for mapping, mechanism, and management of urban soundscape quality: From quietness to naturalness

BackgroundDespite growing attention from researchers and governments, challenges persist in comprehensively assessing urban sound quality by integrating both quietness and naturalness aspects. GoalsThis study aimed to develop an innovative soundscape quality index that concurrently evaluates quietness and naturalness in urban soundscapes. Our objectives included conducting urban soundscape quality mapping, analyzing influential mechanisms, and identifying priority zones for sound environment management. ApproachesWe collected sound pressure level (SPL) and raw audio data, from which we computed a normalized difference soundscape index (NDSI). With a dataset comprising 28 explanatory variables encompassing land use, built environment, vegetation characteristics, and temporal factors, we employed the random forest (RF) model to predict 10 indicators, including eight SPL-related indices, NDSI, and the QNS (quietness and naturalness soundscape) index. Crucially, we utilized SHAP (SHapley Additive exPlanations) values to interpret the RF model. FindingsSpatial variations in quietness and naturalness were evident, closely associated with road networks and vegetation, respectively, with discernible temporal variations. The top three variables influencing QNS were distance to major roads, normalized difference vegetation index (NDVI), and proportion of tree coverage. Moreover, interaction effects highlighted dual negative or synergistic promoting effects on QNS from factors such as road width, human disturbance, vegetation configurations, and land cover. Notably, these mechanisms were successfully applied to six typical tourist attractions in Xiamen city, where five types of management zones were mapped based on priority considerations of population density and soundscape quality. Interestingly, natural soundscape reserves were highly correlated with city parks, high-risk zones predominantly overlapped with road networks, and potential zones comprised inner communities between streets. SignificanceThe framework demonstrated effectiveness in mapping, exploring mechanisms, and guiding management strategies for the urban sound environment.

Efficient data management in Internet of Things: A survey of data aggregation techniques

The Internet of Things (IoT) refers to a vast network of interconnected devices, objects, and systems powered by sensors, software, and connectivity capabilities. The interconnectivity of IoT devices has led to a substantial increase in data production. Efficiently managing and analyzing large data volumes is a significant challenge for IoT systems. To address this challenge, data aggregation is the primary process. IoT data aggregation aims to provide high-quality service by ensuring fast data transmission, high reliability, minimal energy consumption, and data priority consideration. Data aggregation involves collecting data from multiple sensors and devices and then integrating it using a function to minimize system traffic. This paper thoroughly examines data aggregation techniques in the IoT context. Techniques are grouped according to underlying principles, and their potential applications, advantages, and limitations are discussed.

Abstract LB091: A multigene signature for immunotherapy in patients with high risk non-muscle-invasive bladder cancer

Abstract Introduction: Approximately 80% of bladder cancer patients are initially diagnosed with non-muscle invasive bladder cancer (NMIBC). However, most NMIBC patients have a high recurrence rates, and up to 45% progress to muscle-invasive bladder cancer (MIBC) and metastatic disease. Treatment for NMIBC includes transurethral resection and, depending on the risk of recurrence or progression, intravesical chemotherapy or immunotherapy, such as Bacillus Calmette-Guérin(BCG). Our aim is to use a multigene signature in patients with high-risk NMIBC to determine whether patients may benefit from improved ICIs compared to conventional PD-L1 expression and to evaluate the clinical utility. Methods: A multi-gene signature obtained from the various NMIBC data was applied to stratify the UROMOL2021 cohort (n=535) using consensus clustering. Each subtype was distinguished by biological pathway analysis. Validation analysis was performed in three independent cohorts including the IMvigor210 (n=298), IMvigor010 (n=377) and ABACUS (n=148) clinical trials treated with PD-L1 inhibitors. The log-rank test, chi-square test, Fisher’s exact test, and cox regression analysis were used to evaluate clinical utility. Results: Based on consensus cluster analysis, NMIBC patients in the UROMOL2021 cohort were classified into five subgroups exhibiting unique characteristics, including DNA damage repair (DDR). Cross-validation was performed using two independent NMIBC cohorts and one MIBC cohort. Survival analysis showed that the subgroup associated with DDR (DDR and DDR+Tcell) had the highest rates of relapse and disease progression (progression-free survival, p&amp;lt;0.001) and benefited from Immune checkpoint inhibitors (ICIs) (response, p=0.01; overall survival, p=0.004). Conclusions: This study suggests that the multi-gene signature may play a role to enhance the responsiveness of ICIs for high-risk NMIBC. Additionally, it is important to help improve ICI treatment approaches that currently focus on PD-L1 expression on cancer cells, allowing more patients to receive priority consideration for ICI therapy. Citation Format: Seung-Woo Baek, Seon-Kyu Kim, Sun-Hee Leem, In-Sun Chu. A multigene signature for immunotherapy in patients with high risk non-muscle-invasive bladder cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB091.

A time-varying competitive swarm optimizer for integrated flight recovery with multi-objective and priority considerations

Integrating aircraft and crew recovery is a growing topic in providing an efficient recovery system after a disruption. Most existing models only conduct from airline perspective and treat all disturbed flights homogeneously. However, in a realistic operation, the decision objectives are multiple with the interplay of stakeholders. Moreover, flights with first-aid items hold special priority. Thus, this paper presents a new Integrated Aircraft and Crew Recovery with Multi-objective and Priority, namely IACR_MP. To solve IACR_MP efficiently, an ad-hoc particle swarm optimization-based optimizer is designed. Time-varying tri-competition with different evolutionary mechanisms is developed to achieve a balance between exploitation and exploration capacities. Three repair schemes are built to prevent low feasibility caused by high constraints, and a self-exploration strategy is used to detect the potential zones of contemporary non-dominated solutions. Finally, six instances with different scales are used for algorithm performance analyses. Results illustrate that our algorithm has good solution quality and significantly outperforms its competitors in solving the IACR_MP. Moreover, our framework can provide a series of specific recovery schemes, providing decision support with more choices to airline managers.

Editorial: nutrition at key stages of the lifecycle.

Nutritional requirements of individuals vary across the lifecycle, according to activity, age and gender. To optimize human health, consideration of nutritional priorities at each stage is needed. This conference brought together multidisciplinary experts in maternal and child nutrition and health, cardiometabolic and plant-based nutrition and dietitians involved in the care of vulnerable populations, plus nutritional metabolism, health and ageing. The presentations highlighted the most important nutrition research in these areas, updating knowledge and suggesting how dietary advice and policy could be adapted to incorporate research findings. With the global increase in non-communicable disease (NCD) and nutrition being considered as a key modifiable risk factor for the prevention and management of NCD, this conference was much needed.

Carbon emission inequality and fairness from energy consumption by prefecture-level cities in China

This paper focuses on the conceptualization and quantification of carbon emission inequality and fairness from energy consumption. In order to more accurately measure the carbon emissions generated by electricity consumption in each city, we firstly propose a new method for calculating the carbon emission factor for electricity, and calculates the carbon emissions from energy consumption in 282 prefecture-level cities in China from 2003 to 2019. Through the application of the Theil-Kaya decomposition mechanism and the improved Atkinson index, we conducted an in-depth study of the carbon emission inequality and fairness indicators from energy consumption. The results show that (1) Although China's overall inequality has declined, it remains significant in the western region, with its inequality indicator fluctuating from 0.548 in 2003 to 0.683 in 2019.(2) The decomposition of the drivers of inequality indicators shows that the contribution of GDP per capita to inequality is increasingly being replaced by energy intensity and the energy carbon emission factor, with energy intensity emerging as the main driver, contributing more than 40% to inequality in 2019, both overall and in the three regions.(3) The results for the fairness indicator, on the other hand, show a certain degree of divergence. Further Dynamic Time Warping fitting analysis shows that regardless of how the public's sensitivity to carbon emissions varies, the change trends of the fairness and inequality indicators for carbon emissions in the eastern region show a high degree of convergence, even in the two most extreme cases. The fit is poorest in the western region, but improves significantly if public's sensitivity to carbon emissions increases. (4)To sum up, some policies that are consistent with the context of the times, such as the East-West regional counterparts and the construction of a new type of power system, are worthy of priority consideration by the Government.

Rule extraction based on PROMETHEE-assisted multi-objective genetic algorithm for generating interpretable neural networks

Rule extraction from artificial neural networks (ANNs) refers to the process of identifying the underlying decision-making logic used by the network in its predictions. This involves converting the complex, non-linear relationships between inputs and outputs in the network into a set of interpretable rules. The main objective of rule extraction is to enhance the interpretability of decision-making in artificial neural networks (ANNs) and make it more understandable for human experts, especially in critical domains like healthcare, where clear decision-making is essential. Despite the ability of machine learning methods to interpret ANNs, interpreting complex neural networks remains limited, as most studies tend to sacrifice one criterion, related to rule quality, in favor of another. Rule extraction methods applied directly to complex neural networks may produce overly specific rules that are tailored to the training data. Such rules can suffer from overfitting and may not generalize well to unseen data. Also, The use of multiobjective genetic algorithms for rule extraction can result in a large number of rules, making it challenging for decision-makers to interpret them. This study proposes an innovative approach to address challenges in rule extraction from complex artificial neural networks (ANNs) by integrating a multiobjective genetic algorithm with the PROMETHEE method. By integrating these techniques, the study aims to identify meaningful relationships between inputs and outputs of ANNs, generating concise and reliable rules that are ranked based on support, confidence, and lift values. The use of PROMETHEE's rule ranking mechanism enabled the consideration of rule priority during candidate selection, guiding the genetic algorithm towards discovering high-quality rule sets and efficiently exploring the search space. This approach not only enhances the quality of extracted rules but also facilitates efficient decision-making by striking a balance between rule accuracy, fidelity, and comprehensibility, thus contributing to advancing the understanding of complex neural networks. By equally weighting the criteria (support, confidence, and lift) during the rule ranking mechanism, our approach achieved high coverage rates ranging from 94.88 % to 100 % and generated a manageable number of rules that could be easily interpreted by human experts, ranging from 5 to 10.5. These findings demonstrate the potential of our approach to significantly improve decision-making accuracy and interpretability across various real-world applications, making it a promising tool for applications in healthcare, finance, and other fields.

Assessing the Empowerment of Mosques with the Maqashid Sharia Index

&lt;p&gt;&lt;em&gt;This study aims to assess the mosque empowerment index formula based on Maqashid Sharia. This formula serves as an instrument to measure the level of mosque empowerment in Bogor, Indonesia. It consists of six criteria based on the Maqashid Sharia, including protecting religion, life, intellect, lineage, property, and the environment. The data analysis technique employs the Analytical Network Process (ANP) in conjunction with the Super Decision 2.10 software to construct the index model structure. The results of the formula calculation in each of the three model mosques revealed significant discrepancies. The Andalusia Mosque has achieved a remarkable score of 0.96, positioning it as the top-ranking mosque in terms of its significant degree of empowerment within the local community. The following mosque is the Ar-Rahman Mosque, which has a value of 0.69 and is classified as an empowered mosque. Finally, the Al-Muhaajirin mosque has a value of 0.57, indicating that it belongs to the group of quite empowered mosques and can be given priority consideration for help in the future. Specifically, this study becomes the first comprehensive assessment of mosque empowerment in Indonesia by utilizing the Maqashid Sharia Index across three mosques.&lt;/em&gt;&lt;/p&gt;

Metrics for Decision-Making in Energy Justice

Energy equity and justice have become priority considerations for policymakers, practitioners, and scholars alike. To ensure that energy equity is incorporated into actual decisions and analysis, it is necessary to design, use, and continually improve energy equity metrics. In this article, we review the literature and practices surrounding such metrics. We present a working definition for energy justice and equity, and connect them to both criteria for and frameworks of metrics. We then present a large sampling of energy equity metrics, including those focused on vulnerability, wealth creation, energy poverty, life cycle, and comparative country-level dynamics.We conclude with a discussion of the limitations, gaps, and trade-offs associated with these various metrics and their interactions thereof.

Multi-resource scheduling of moldable workflows

Resource scheduling plays a vital role in High-Performance Computing (HPC) systems. Most scheduling research in HPC has focused on only a single type of resource (e.g., computing cores or I/O resource). With the advancement in hardware architectures and the increase in data-intensive HPC applications, there is a need to simultaneously consider a diverse set of resources (e.g., computing cores, cache, memory, I/O, and network resources) in the design of runtime schedulers for improving the overall application performance. In this paper, we study multi-resource scheduling to minimize the makespan of computational workflows comprised of moldable parallel jobs. Moldable jobs allow the scheduler to flexibly select a variable set of resources before execution, thus can adapt to the available system resources (as compared to rigid jobs) while staying easy to design and implement (as compared to malleable jobs). We propose a Multi-Resource Scheduling Algorithm (MRSA), which combines a novel resource allocation strategy and an extended list scheduling scheme to schedule the jobs. We prove that, on a system with d types of schedulable resources, MRSA achieves an approximation ratio of 1.619d+2.545d+1 for any d≥1, and a ratio of d+3d23+O(d3) when d is large (i.e., d≥22). We also present improved approximation results for workflows comprised of jobs with special precedence constraints (e.g., series-parallel graphs, trees, and independent jobs). Further, we prove a lower bound of d on the approximation ratio of any list-based scheduling algorithm with local priority considerations. Finally, we conduct a comprehensive set of simulations to evaluate the performance of the algorithm using synthetic workflows of different structures and moldable jobs following different speedup models. The results show that MRSA fares better than the theoretical bound predicts, and that it consistently outperforms two baseline heuristics under a variety of parameter settings, illustrating its robust practical performance.

From agenda to action: JBI Evidence Synthesis and the United Nations Sustainable Development Goals.

This pilot study sought to map the alignment of publications in JBI Evidence Synthesis to the United Nations Sustainable Development Goal (SDG) 3 (global health and well-being) and to understand JBI authors' awareness of and engagement with the goals. This will contribute to a larger-scale analysis to assist the JBI Collaboration in engaging with and working toward achieving the SDGs. In 2015, the United Nations agreed on 17 SDGs as the central framework for sustainable development worldwide. However, in the wake of the global pandemic, the 2030 SDG agenda is in jeopardy due to multiple cascading and intersecting crises. The Global Commission on Evidence has urged the evidence community to consider how it might more meaningfully contribute to the evidence architecture. As we pass the midway point to the SDG 2030 target date, it is timely to reflect on the contribution of those in the evidence synthesis community to achieving these important global objectives. A 2-phase study was conducted utilizing desktop audit methods. SDG 3 targets were mapped across systematic and scoping reviews published in JBI Evidence Synthesis using established key terms, followed by a brief author survey and thematic analysis. The results of this pilot study indicate that 28.5% of syntheses published in JBI Evidence Synthesis address 11 of the 13 targets of SDG 3. SDGs are not currently a priority consideration for most JBI Evidence Synthesis authors, but there is a desire to learn more and integrate the goals into their prioritization processes. While this was only a small pilot study, it is indicative of a need to reset and recommit to mutual global agendas to transform the evidence ecosystem, and to maximize the limited resources available in order to truly have a global impact on health outcomes.

Exploring the evidence of Middle Amazonian aquifer sedimentary outburst residues in a Martian chaotic terrain

The quest for past Martian life hinges on locating surface formations linked to ancient habitability. While Mars' surface is considered to have become cryogenic ~3.7 Ga, stable subsurface aquifers persisted long after this transition. Their extensive collapse triggered megafloods ~3.4 Ga, and the resulting outflow channel excavation generated voluminous sediment eroded from the highlands. These materials are considered to have extensively covered the northern lowlands. Here, we show evidence that a lacustrine sedimentary residue within Hydraotes Chaos formed due to regional aquifer upwelling and ponding into an interior basin. Unlike the northern lowland counterparts, its sedimentary makeup likely consists of aquifer-expelled materials, offering a potential window into the nature of Mars' subsurface habitability. Furthermore, the lake’s residue’s estimated age is ~1.1 Ga (~2.3 Ga post-peak aquifer drainage during the Late Hesperian), enhancing the prospects for organic matter preservation. This deposit’s inferred fine-grained composition, coupled with the presence of coexisting mud volcanoes and diapirs, suggest that its source aquifer existed within abundant subsurface mudstones, water ice, and evaporites, forming part of the region’s extremely ancient (~ 4 Ga) highland stratigraphy. Our numerical models suggest that magmatically induced phase segregation within these materials generated enormous water-filled chambers. The meltwater, originating from varying thermally affected mudstone depths, could have potentially harbored diverse biosignatures, which could have become concentrated within the lake’s sedimentary residue. Thus, we propose that Hydraotes Chaos merits priority consideration in future missions aiming to detect Martian biosignatures.

An Independent Degree-eight Mars Gravity Field Model and the Expected Results from the Tianwen-1 Mission

Tianwen-1 is China’s first independent interplanetary exploration mission, targeting Mars, and includes orbiting, landing, and rover phases. Similar to previous Mars missions, the Tianwen-1 orbiter was designed for polar orbits during the scientific mission period but has an exceptional eccentricity of approximately 0.59. We provide the first independent eight-degree Martian gravity field model in this paper, which was developed exclusively by a team working in China with our independent software as well, based on about two months of radiometric Doppler and range data from only the Tianwen-1 mission. This model is independent from the models created by the groups at NASA Jet Propulsion Laboratory and Goddard Space Flight Center in the United States, as well as the Centre National d’Etudes Spatiales in France. Furthermore, in order to optimize the engineering and scientific benefits, we proposed a number of potential orbits for the extended Tianwen-1 mission. In order to solve a higher-degree independent Mars gravity field model, the viability of modifying the perigee height was investigated, with the priority considerations of fuel savings and implementation hazards being controlled.

TURATS BEHAVIOR: DEMONSTRATING HALAL LIFESTYLE IN PESANTREN THROUGH HALAL COSMETICS

Pesantren is the oldest Islamic Education institution in Indonesia. Until now, its role has beenvital in conveying Islamic teachings and values and forming a society with Islamic character.However exclusive it is, its existence is always required to adjust to the times and lifestylechanges. Islamic teachings through Turast taught in pesantren have formed a lifestyle that inrecent years has become a trend, namely the halal lifestyle. So it becomes interesting to studyhow students' lifestyles should reflect what they have learned from Turast. This research isqualitative, to answer this problem data mining uses interviews and documentation. The resultsof this study state that pesantren have built the halal lifestyle of santri, one of which is throughhalal cosmetics. Most informants from the 2 pesantren where this study took place stated thatthe halal logo is a priority consideration in choosing and buying halal cosmetics. Halal awarenesswhich then becomes halal behavior begins and is guarded by Islamic values that they learn fromthe yellow book or Turats. Supporting the system in shaping this halal behavior is the exampleof Kyai as the leader of the pesantren and the existence of Koperasi Pesantren (Kopontren) thathave a strong commitment by only providing and selling cosmetics with the halal logo. Theresults of this study will contribute to related industries and can be used as a potential issue inpolicy-making related to pesantren and halal products.Keywords: Halal cosmetics, Halal Lifestyle, Islamic Boarding School