Final Allocation Research Articles

Evaluación del desempeño inicial de estacas y plántulas en una plantación de copales (<i>Bursera copallifera</i> y <i>B. bipinnata</i>)

Background: Copal is a resin that is used in religious and cultural ceremonies; it is extracted from Bursera bipinnata and Bursera copallifera, and obtained both from natural populations and maintained trees. Questions: What propagation method (rooted cuttings or seeds) is more suitable for each species? How is field performance in terms of survival and growth of rooted cuttings and seedlings for each species? Study species: Bursera bipinnata and B. copallifera Study site and dates: Santiago Tepetlapa, Morelos 2016-1018 Methods: Plants were propagated in 2015-2016. In 2016, 133 plants were planted: 42 rooted cuttings and 27 seedlings of B. bipinnata, and 26 and 38, respectively, of B. copallifera. Growth was evaluated for one year and survival for two years. Relative growth rate (RGR) was measured, as well as biomass allocation to different organs. Results: In B. bipinnata propagation by rooted cuttings is more feasible, and by seeds in B. copallifera. During the first-year rooted cuttings showed higher survival than seedlings, but in the second year it was higher in cuttings of B. bipinnata (65 %), than in all other plants (< 15 %). There were differences between species in final biomass allocation in rooted cuttings, but not in seedlings; there were no differences between species in RGR. Conclusions: Rooted cuttings showed a better performance than seedlings; especially those of B. bipinnata. These results can contribute to the establishment of plantations of these species in agroforestry systems and restoration.

Reactive power and voltage control based on reactive power compensation coefficient and sensitivity factor

Abstract Aiming at the problems that the existing reactive power allocation methods do not take into account the specific operating state of each doubly-fed induction generator (DFIG) and the established optimization model has many variables and is complicated, this paper proposes to construct an optimization model based on reactive power compensation coefficient and sensitivity factor, to reduce the number of variables in the mathematical model and simplify the expression of the relationship between each key parameter, so the speed of the reactive power and voltage control are improved. In the process of constructing specific optimization models, the objective of minimizing the active loss takes into account the operating copper consumption of each DFIG. The objective of minimizing the voltage fluctuation of each DFIG is also taken into account, in addition to the operating state constraints of each DFIG, so that the final reactive power allocation is more practical. In solving the multi-objective optimization problem, the improved NSGA-II algorithm is utilized, which can achieve the simultaneous optimization of multiple objectives, and when combined with the simplified model established in this paper, the correctness and speed of obtaining the optimal solution set of Pareto can be further improved. Finally, the effectiveness of the proposed strategy in reducing active losses and voltage fluctuations in wind farms is verified by simulation examples.

Decentralized pure exchange processes on networks

AbstractWe define a class of pure exchange Edgeworth trading processes that under minimal assumptions converge to a stable set in the space of allocations, and characterise the Pareto set of these processes. Choosing a specific process belonging to this class, that we define fair trading, we analyse the trade dynamics between agents located on a weighted network. We determine the conditions under which there always exists a one-to-one map between the set of networks and the set of limit points of the dynamics, and derive an analog of the Second Welfare Theorem for networks. This result is used to explore what is the effect of the network topology on the trade dynamics and on the final allocation.

Sustainable flood control strategies under extreme rainfall: Allocation of flood drainage rights in the middle and lower reaches of the yellow river based on a new decision-making framework

Climate change has exacerbated the frequency and magnitude of extreme rainfall, which has led to the perpetuation of flooding as a hazard to humans and society. China has begun to consider introducing Flood drainage rights (FDR), a sustainable flood control measure, into non-engineering measures as a complement to engineering measures for flood control. FDR represent the right of regions to discharge regional floodwaters caused by extreme rainfall into the river, and are the primary means of controlling the amount of floodwaters from regions when regional flood capacity is exceeded. However, existing studies on quantitative FDR allocation still have limitations, and some previous methods have resulted in allocation schemes that are not entirely reasonable and fair because they do not comprehensively consider the influencing factors of FDR or the allocation method is unreasonable. This paper explores the impact of flooding on rural and agricultural areas. We incorporate the factors of agricultural economy and security and construct a system of the allocation indicators of FDR composed of five principles: Natural Environmental Endowment, General Economic and Social Development, Agricultural Economy and Security, Macro policy regulation, and Respect for Historical Background. Second, considering the influence of expert judgment and data of different time nodes on the allocation of FDR, we introduce the concepts of expert weight and time weight into the allocation model of FDR, and construct a new set of framework for the allocation of FDR, i.e., "[(expert weight + subjective weight)+(time weight + objective weight)]+decision making model ". To reduce the loss of information during the transformation of subjective judgments, we also introduced triangular fuzzy numbers for the transformation between expert judgments and numbers. Finally, we take the five provinces in the middle and lower reaches of the Yellow River as an example. Using the data from 2010 to 2021, we obtain the final allocation scheme (proportion) of FDR as Henan (33.26%) > Shaanxi (23.08%) > Inner Mongolia (21.31%) > Shanxi (14.44%) > Shandong (7.91%). On this basis, this paper utilizes sensitivity analysis and comparative validation to demonstrate the rationality and effectiveness of the method, and identifies several indicators that have a greater impact on the results of the allocation of FDR. FDR can form part of a set of integrated flood management system together with flood control projects, which greatly alleviates the drainage conflicts arising from flooding caused by extreme precipitation. Under extreme rainfall conditions, FDR improves drainage efficiency and minimizes the overall damage caused by flooding in the watershed. This study can contribute to the sustainable development of the watershed and provide a reference for the promotion and utilization of sustainable flood control measures.

Dynamics of human-machine task allocation in intelligent production processes: A case study

Efficiency and effectiveness in advanced production systems depend on judicious task allocation between humans and machine entities. Despite growing academic interest in human–machine task allocation, theoretical research that can effectively guide practice remains lacking. This paper develops a dynamic human–machine task allocation framework aimed at addressing this gap through the identification and evaluation of task complexity and economic benefits influencing task allocation. We conduct a case study on human–machine task allocation during the transition from manual to intelligent production, utilizing actual task data from both manual and intelligent production lines for the same products. This case study provides practical support for our theoretical framework and yields additional insights into human–machine task allocation. Key findings include: (1) Technological progress has demonstrated significant replacement and reinstatement effects, promoting machines to replace humans in performing more complex tasks while generating new manual tasks related to smart devices. (2) The core considerations for human–machine task allocation are task complexity and task intensity. Although technological progress has facilitated the automation of highly complex tasks, the final allocation is ultimately determined by the economic benefits associated with task intensity. (3) The production pattern in the electronics manufacturing industry has evolved from a traditional manual-led approach to a human–machine collaboration pattern in intelligent production lines. Machines focus on production, while human workers handle setup tasks. This transformation allows intelligent production lines to combine the high productivity of machines with the flexibility of humans.

Posted offers with charitable promises: True preferences and strategic behavior

We report experimental findings on the role of charitable promises in settings with posted offers. We vary the enforceability of such promises within variants of ultimatum games where the proposer suggests a split between herself, the responder and a charitable donation. By reneging on initial pledges, dishonest proposers can change the final allocation to their advantage. Providing ex post information on actual donations while leaving the contract incomplete outperforms a complete contract where proposers cannot renege on their charitable promises. The ex post information allows proposers to improve their image by voluntarily giving more than pledged and thus proving that the charitable pledge was not used for strategic reasons. We identify proposer competition as another (surprising) mechanism that partly eliminates cheating among accepted offers, but it also favors offers without charitable pledge.

Navigating the uncertainty: the impact of a student-centered final year project allocation mechanism on student performance

The Final Year Project (FYP) is one of the most important courses for every undergraduate student, and the effective operation of the FYPs in higher education still faces challenges, such as uneven resource distribution and limited efficiency. This study reports a mixed-methods approach to study the impact of a student-centered FYP allocation mechanism on student performance. This research aims to investigate how aligning students’ FYP choices with their interests can inspire motivation and enhance academic performance. More importantly, this mechanism improves students’ academic resilience, enabling them to navigate unexpected contextual factors. The study’s findings take into account various aspects, including student satisfaction with the allocation process, future improvement methods, and the relationship between interest and context. The outcomes observed in this study support our hypotheses, indicating the improvements in students’ academic performance as well as the pass and completion rates. Moreover, this research contributes to ‘resilience theory’ by exploring students’ adaptability to contextual changes and their enhancement of academic resilience. This study proposes recommendations for cultivating a dynamic student-centered classroom environment. Future work could pay attention to addressing the limitations of this study, exploring other factors influencing FYP allocation, and integrating more quantitative measures for a comprehensive assessment of its impact.

Comprehensive Evaluation of Resilience for Qinling Tunnel Group Operation Safety System Based on Combined Weighting and Cloud Model

An extensive network of tunnels has recently been constructed in the Qinling Mountains. Characterized by high and steep terrain, this network has led to frequent traffic accidents. To address this issue, this paper introduces the theory of resilience into the evaluation system of safety systems during the operation period of highway tunnel groups. Based on this, this paper establishes a resilience evaluation index system for the operation safety system of highway tunnel groups, including a human system, vehicle system, and road system. To address both qualitative and quantitative issues concerning the indicators, this paper employs the analytic hierarchy process (AHP) and entropy weight method to combine and assign weights to the resilience evaluation indicators. Subsequently, the cloud model method is utilized to quantify the level of resilience of the highway tunnel group safety system during the operation period. The study results unveiled the patterns of traffic accidents within the Qinling Tunnel Group from the perspectives of vehicle, road, and human factors. The final weight allocation reveals that the road system has the highest proportion, exerting the greatest influence as a primary level index. Moreover, by taking the Qinling Tunnel Group on the Xihan Expressway as an engineering example, the resilience level of the case project was analyzed and obtained. Proposals for enhancing resilience were put forth, taking into account the project’s unique attributes, encompassing adaptability, resistance, and recovery. Overall, this study validates the feasibility and reliability of the proposed method for assessing the resilience of highway networks, offering empirical support for transportation administrators in the implementation of resilience-enhancing strategies.

Data-driven traffic signal adaptive control algorithm integrating vehicle perception and traffic flow data

Due to the equipment error, environmental interference and data transmission delay of vehicle flow detection, the accuracy and real-time performance of vehicle perception and traffic flow data will be affected to some extent, resulting in poor traffic signal control effect. Therefore, a data-driven traffic signal adaptive control algorithm is designed by integrating vehicle perception and traffic flow data. To complete the modeling of urban traffic, the discrete distribution and continuous distribution of traffic are obtained. Based on this research environment, the DV-hop localization algorithm is improved to sense the vehicle position. Based on the phase space reconstruction of traffic flow time series and vehicle location information, traffic flow data is predicted. Based on the driving of traffic data, the vehicle types are divided into small, medium and large three categories, and the impact weights are assigned respectively, and the weight values affecting the final allocation of green time are obtained to realize the allocation of green time. The experimental results show that: The research algorithm can not only predict the traffic flow intensity effectively, but also the predicted results are highly coincident with the actual traffic flow intensity. Vehicle arrival rates are higher, vehicle delays are shorter, and vehicles stop fewer times on average.

How to Get Observing Time on the DOT

The article describes the approach followed by the Devasthal Time Allocation Committee to evaluate observing proposals to the Devasthal Optical Telescope (DOT) over the period 2020–2023, the results of the time allocation process, and some statistics of the proposals and final time allocation. It also provides some suggestions to the Aryabhatta Research Institute of Observational Sciences that aim to improve the DOT science output and the quality of observing proposals, as well as suggestions to DOT proposers to help improve their chances of obtaining DOT observing time in the future.

Collaborative Allocation Method of En-Route Network Resources Based on Stackelberg Game Model

To further enhance fairness in the allocation of en-route space–time resources in the collaborative trajectory selection program, a study on the plan preferences between air traffic control (ATC) and airlines in the selection process of the final plan is conducted based on the initial resource allocation plans, considering the roles of airlines in resources allocation decisions. By using Stackelberg game theory, a game model is established for the roles played by ATC and airlines in the process of selecting plans. Then, combining the overall consideration of ATC for all affected flights, the preferences of airlines for initial allocation plans are obtained, and the option range of selectable plans is narrowed down to determine the optimal allocation plan. The results of the example analysis show that the proposed model and method can effectively select the optimal allocation plan from the six initial allocation plans, select the trajectories and entry slots in the congestion areas for airlines that better meet the operation demand, and provide the decision basis with more preferences for ATC to select the final allocation plan. When ATC prefers the lowest overall delay cost, the delay cost of the selected optimal allocation plan is 267.7 min, which is 23.84% lower than the traditional RBS algorithm; when considering the preferences of the main base airline in East China, the delay cost of the selected optimal allocation plan is 287.7 min, which is 18.15% lower than the traditional RBS algorithm.

Study on regional carbon quota allocation at provincial level in China from the perspective of carbon peak

This paper constructs a carbon quota allocation index that takes into account equity, efficiency and ecological construction, and calculates carbon emissions and energy consumption data in important periods based on the expected carbon emission targets and economic and social development indicators of the Chinese government. Based on the calculated carbon emissions, the zero-sum game data Envelopment model (ZSG-DEA) is used to discuss the initial allocation of regional quotas and the optimal carbon quota scheme. The results show that:(1) there is a large gap between the optimal carbon quota and the initial carbon quota allocation in Shandong, Guangdong, Jiangsu and other provinces in 2025, and the implementation of emission reduction measures should be accelerated. (2) By 2030, the final allocation of Beijing, Tianjin, Inner Mongolia, Qinghai, Shanghai, Ningxia, Liaoning and Xinjiang will be positive. The provinces with negative final allocation should carry out the work of carbon peak as soon as possible to avoid increasing the pressure of emission reduction in the future. (3) The central region faces greater pressure of emission reduction, while the western region can accept the transfer of carbon emissions from other regions over time. The research conclusions have important policy implications for establishing a fair and effective carbon quota allocation mechanism, achieving the national total carbon emission control target, stimulating the vitality of the unified carbon market, and promoting regional coordinated emission reduction.

Carbon Emission Projection and Carbon Quota Allocation in the Beijing–Tianjin–Hebei Region of China under Carbon Neutrality Vision

Supported by the coordinated development strategy, the Beijing–Tianjin–Hebei (BTH) region has achieved rapid development but also faces severe energy consumption and environmental pollution problems. As the main responsibility of emission reduction, the coordinated and orderly implementation of carbon emission reduction in Beijing, Tianjin, and Hebei is of great significance to the realization of the carbon neutrality target. Based on this, this study comprehensively uses the expanded STIRPAT model, optimized extreme learning machine (ELM) network, entropy method, and zero-sum gains DEA (ZSG-DEA) model to explore the carbon emission drivers, long-term emission reduction pathway, and carbon quota allocation in the BTH region. The results of the driving factor analysis indicate that the proportion of non-fossil energy consumption is a significant driving factor for Beijing’s carbon emissions, and the improvement of the electrification level can inhibit the carbon emissions. The total energy consumption has the greatest impact on the carbon emissions of Tianjin and Hebei. The simulation results reveal that under the constraint of the carbon neutrality target, Beijing, Tianjin, and Hebei should formulate more stringent emission reduction measures to ensure that the overall carbon emission will reach its peak in 2030. The cumulative emission reduction rate should exceed 60% in 2060, and negative carbon technology should be used to offset carbon emissions of not less than 360 million tons (Mt) per year by 2060. Furthermore, the allocation results show that Beijing will receive a greater carbon quota than Hebei. The final allocation scheme will greatly promote and encourage carbon emission reduction in Hebei Province, which is conducive to achieving the goal of carbon neutrality.

Interneuron odyssey: molecular mechanisms of tangential migration.

Cortical GABAergic interneurons are critical components of neural networks. They provide local and long-range inhibition and help coordinate network activities involved in various brain functions, including signal processing, learning, memory and adaptative responses. Disruption of cortical GABAergic interneuron migration thus induces profound deficits in neural network organization and function, and results in a variety of neurodevelopmental and neuropsychiatric disorders including epilepsy, intellectual disability, autism spectrum disorders and schizophrenia. It is thus of paramount importance to elucidate the specific mechanisms that govern the migration of interneurons to clarify some of the underlying disease mechanisms. GABAergic interneurons destined to populate the cortex arise from multipotent ventral progenitor cells located in the ganglionic eminences and pre-optic area. Post-mitotic interneurons exit their place of origin in the ventral forebrain and migrate dorsally using defined migratory streams to reach the cortical plate, which they enter through radial migration before dispersing to settle in their final laminar allocation. While migrating, cortical interneurons constantly change their morphology through the dynamic remodeling of actomyosin and microtubule cytoskeleton as they detect and integrate extracellular guidance cues generated by neuronal and non-neuronal sources distributed along their migratory routes. These processes ensure proper distribution of GABAergic interneurons across cortical areas and lamina, supporting the development of adequate network connectivity and brain function. This short review summarizes current knowledge on the cellular and molecular mechanisms controlling cortical GABAergic interneuron migration, with a focus on tangential migration, and addresses potential avenues for cell-based interneuron progenitor transplants in the treatment of neurodevelopmental disorders and epilepsy.

A Drone Scheduling Method for Emergency Power Material Transportation Based on Deep Reinforcement Learning Optimized PSO Algorithm

Stable material transportation is essential for quickly restoring the power system following a disaster. Drone-based material transportation can bypass ground transportation’s limitations and reduce transit times. However, the current drone flight trajectory distribution optimization model cannot meet the need for mountainous emergency relief material distribution following a disaster. A power emergency material distribution model with priority conditions is proposed in this paper, along with a two-layer dynamic task-solving framework that takes task dynamics into account. This research proposes an algorithm (TD3PSO) that combines the particle swarm algorithm (PSO) updating technique with the double-delay depth deterministic policy gradient algorithm (TD3) algorithm’s capacity to dynamically parameterize. The final task allocation experiment demonstrates that the modified TD3PSO significantly outperforms the conventional algorithm on the Solomon data set, with an improvement of 26.3% on average over the RLPSO algorithm and a 11.0% reduction in the volatility of the solving impact. When solving under realistic circumstances, the solution effect increases by 1.6% to 13.4%, and the redistribution experiment confirms the framework’s efficacy. As a result, the algorithm and architecture suggested in this paper may successfully address the issue of scheduling drones for power emergencies while enhancing transportation efficiency.

When Participatory Budgeting (PB) funds schools, who benefits? An equity analysis of PB-associated investments in NYC public schools

ABSTRACT Equity goals have shaped participatory budgeting (PB) in North America, but little is known about their impact on PB allocations. Focusing on New York City (PBNYC), this paper examines whether PB-associated increases in public school investments have benefited higher needs students. The paper proposes a model of three key project decision-points in a PB process and examines equity at each: project development, vote, and final budget allocation. Across three PBNYC cycles, analyses confirm the use of two potentially equity advancing tactics during project development: equity descriptors were found for 7.2% of school-related ballot items; and bundling described 33.9% of school-related ballot items. Both tactics were associated with winning PB votes. However, in those years, PB-funded school projects did not benefit higher (or lower) needs students compared to school projects council members funded on their own discretion. Interviews with PB volunteers support these findings and highlight diverse assessments of need and equity.

Evaluating Effectiveness of Student Final Year Project Allocation: a Case Study at Universiti Brunei Darussalam

The allocation of final year projects is a critical task for universities to ensure that students receive the best possible academic experience. The allocation problem is often complex, and universities face several challenges, including balancing staff workload, taking into consideration students’ preferences as well as allocating resources optimally. This paper presents a Linear Programming approach for optimising student final year project allocation to address the mentioned challenges. By considering students’ preferences, staff workload, and project quality, the proposed model provides an optimal and fair project allocation scheme. The model’s effectiveness was demonstrated through a case study in Mathematical Sciences, Faculty of Science, UBD, using real data. The results obtained from the LP model are both feasible and optimal, indicating that the approach provides an unbiased allocation of supervisors to project students satisfying all constraints. The model allows for flexibility in fine-tuning the allocation scheme, as it can accommodate different levels of quality preferences and student priorities. It is believed that the proposed LP model can provide necessary support for the project coordinator to make informed decisions regarding final year project allocation. The model can also save time and resources by providing solution quickly and efficiently.

Adding epitope compatibility to deceased donor kidney allocation criteria: recommendations from a pan-Canadian online public deliberation

BackgroundThe widening supply–demand imbalance for kidneys necessitates finding ways to reduce rejection and improve transplant outcomes. Human leukocyte antigen (HLA) epitope compatibility between donor and recipient may minimize premature graft loss and prolong survival, but incorporating this strategy to deceased donor allocation criteria prioritizes transplant outcomes over wait times. An online public deliberation was held to identify acceptable trade-offs when implementing epitope compatibility to guide Canadian policymakers and health professionals in deciding how best to allocate kidneys fairly.MethodsInvitations were mailed to 35,000 randomly-selected Canadian households, with over-sampling of rural/remote locations. Participants were selected for socio-demographic diversity and geographic representation. Five two-hour online sessions were held from November–December 2021. Participants received an information booklet and heard from expert speakers prior to deliberating on how to fairly implement epitope compatibility for transplant candidates and governance issues. Participants collectively generated and voted on recommendations. In the final session, kidney donation and allocation policymakers engaged with participants. Sessions were recorded and transcribed.ResultsThirty-two individuals participated and generated nine recommendations. There was consensus on adding epitope compatibility to the existing deceased donor kidney allocation criteria. However, participants recommended including safeguards/flexibility around this (e.g., mitigating declining health). They called for a transition period to epitope compatibility, including an ongoing comprehensive public education program. Participants unanimously recommended regular monitoring and public sharing of epitope-based transplant outcomes.ConclusionsParticipants supported adding epitope compatibility to kidney allocation criteria, but advised safeguards and flexibility around implementation. These recommendations provide guidance to policymakers about incorporating epitope-based deceased donor allocation criteria.

Residence-based priorities and school choice

Many countries use centralized school choice procedures to assign pupils to schools. To address excess demand for a particular school, ties are broken according to priority points granted based on various criteria, such as proximity to the school. Using a unique reform undertaken in Madrid (Spain), we estimate the impact of abolishing residence-based priorities on families’ school choices, the stated motivation for choosing a school, and the final school allocation. Utilizing several administrative datasets on school applications, we find that the reform increases families’ out-of-district school assignments and assignments to schools further away from their home address. Parents of immigrant children did not change their application behavior in the first years of the reform but caught up with natives three years after its implementation. Children generally accessed slightly better-performing schools, particularly those from lower-educated backgrounds.

Optimal Allocation of Energy Storage Capacity in Distributed Micro-grid Based on Improved Whale Algorithm

At present, the setting of monitoring nodes for optimal allocation of energy storage capacity in micro-grid is generally target-based, with slow allocation speed and weak pertinence, which can easily lead to the increase of the final difference adjustment coefficient and affect the final allocation effect. Therefore, the research and analysis on the optimal allocation method of distributed micro-grid energy storage capacity based on the improved whale algorithm are proposed. According to the actual disposal requirements and standards, the basic operation frequency and reserve capacity of the micro-grid are determined, the multi-level monitoring node deployment form is set, the monitoring range is expanded, and the speed and pertinence of configuration are improved to complete the layout of energy storage capacity monitoring nodes. The optimal allocation model of the improved whale calculation of grid energy storage capacity is constructed. The optimal allocation is realized by constraint programming. The test results verify that the energy storage power of the micro-grid will be enhanced with the increase of the frequency modulation times of energy storage calculated by the whale calculation optimization configuration test group. In this context, the difference adjustment coefficient of the micro-grid configuration becomes lower, only 1.03, indicating that in the process of practical application, the energy storage capacity configuration of micro-grid is optimized. The frequency modulation fluctuation is slowed down, the running frequency is faster, and the method has practical application value.