Distribution Scheme Research Articles

Airline revenue management, distribution and passengers: market trends in a technology driven triangle

PurposeThe aim of this paper is a first attempt to map and describe airline information systems (IS) market, in the context of the latest trends affecting air services distribution, revenue management (RM) and passengers in the airline industry.Design/methodology/approachRM evolution has greatly affected airline revenues and load factors in a global environment characterized by fierce competition. The distribution of air services has shifted gradually from a model dependent on travel agents and other intermediaries toward a new trend of do-it-yourself (DIY) bookings through the Internet. The resulting new and significantly more complex environment mandates the connection between revenue management systems (RMS) and reservation systems (RS) through third parties (aggregators) that have emerged and are ready to perform this task. In this context, a market review has been carried out, following the approach of a structured literature review to illustrate this ecosystem.FindingsData collected from the vendors depict the market size and capabilities, highlighting that the market for IS in the airline industry is based on a relational triangle of dependence and competition that includes RS, RMS and aggregators.Originality/valueMapping both technological and functional backgrounds and the operation of current distribution systems and their linking with RMS and methods is deemed a necessity for identifying and describing the mechanisms that are defining the B2B relationship and the subsequent need to improve the ways current distribution schemes combined with RM applications are addressing changing market needs, reflecting the new behavioral models of the customers.

EXPRESS: Distribution Strategy, Capability Investment, and Government Regulation

This paper investigates how a manufacturer’s internal sourcing capability and government regulation influence the supplier’s distribution strategy and the manufacturer’s sourcing and capability investment decisions. We consider a supply chain consisting of a supplier that produces a critical component, an independent manufacturer that also has the capability to produce the component in-house, and a dependent manufacturer without such capability. We first consider a scenario in which the supplier chooses its distribution strategy—either offering its component to both manufacturers or establishing an exclusive selling agreement with a single manufacturer. We explore how the supplier’s optimal distribution strategy (dual or exclusive selling) depends on the terms and process of the contract and on the independent manufacturer’s ability to produce a high-quality component in-house. We also show that, in equilibrium, the independent manufacturer may invest in a high capability level (leading to a high-quality component) as a strategic deterrent against the supplier’s decision to engage in an exclusive selling agreement with the dependent manufacturer. We further consider a setting with mandatory exclusion, imposed by government regulation, that affects free trade among parties. We show that mandatory exclusion can exacerbate or mitigate the independent manufacturer’s incentive to invest in internal sourcing capability, relative to a setting in which the supplier determines its distribution strategy in the absence of such government regulations. Moreover, we show that mandatory exclusion always hurts the supplier, but it can benefit or hurt the manufacturers as well as the consumers, depending on the independent manufacturer’s investment cost and the conditions leading to an exclusionary contract under free trade.

Optimizing a multimodal hub and spoke network for vaccine distribution using regional vulnerability index during healthcare emergencies

Purpose A vaccination strategy to cover the susceptible population is key to containing the spread of any virus during a healthcare emergency. This study quantifies the susceptibility of a region based on initial infection rates to prioritize optimal vaccine distribution strategies. The authors propose a metric, the regional vulnerability index (RVI), that identifies the degree of susceptibility/vulnerability of a region to virus infections for strategically locating hubs for vaccine storage and distribution. Design/methodology/approach A two-phase methodology is used to address this problem. Phase 1 uses a modified Susceptible-Infected-Recovered (SIR) model, ModSIR, to estimate the RVI. Phase 2 leverages this index to model a P-Center problem, prioritizing vulnerable regions through a Mixed Integer Quadratically Constrained Programming model, along with three variations that incorporate the RVI. Findings Results indicate a weighting scheme based on the population-to-RVI ratio fosters fair distribution and equitable coverage of vulnerable regions. Comparisons with the public distribution strategy outlined by the Government of India reveal similar zonal segregations. Additionally, the network generated by our model outperforms the actual distribution network, corroborated by network metrics such as degree centrality, weighted degree centrality and closeness centrality. Originality/value This research presents a novel approach to prioritizing vaccine distribution during pandemics by applying epidemiological predictions to an integer-programming framework, optimizing COVID-19 vaccine allocation based on historical infection data. The study highlights the importance of strategic planning in public health response to effectively manage resources in emergencies.

Digital channel-enabled distributed force decoding via small datasets for hand-centric interactions.

Tactile interfaces are essential for enhancing human-machine interactions, yet achieving large-scale, precise distributed force sensing remains challenging due to signal coupling and inefficient data processing. Inspired by the spiral structure of Aloe polyphylla and the processing principles of neuronal systems, this study presents a digital channel-enabled distributed force decoding strategy, resulting in a phygital tactile sensing system named PhyTac. This innovative system effectively prevents marker overlap and accurately identifies multipoint stimuli up to 368 regions from coupled signals. By integrating physics into model training, we reduce the dataset size to just 45 kilobytes, surpassing conventional methods that typically exceed 1 gigabyte. Results demonstrate PhyTac's impressive fidelity of 97.7% across a sensing range of 0.5 to 25 newtons, enabling diverse applications in medical evaluation, sports training, virtual reality, and robotics. This research not only enhances our understanding of hand-centric actions but also highlights the convergence of physical and digital realms, paving the way for advancements in AI-based sensor technologies.

Dynamic Event-Triggered-Based Finite-Time Distributed Tracking Control of Networked Multi-UAV Systems

The distributed tracking of multiple unmanned aerial vehicles (UAVs) is a hotspot due to its broad applications in various fields, while continuous communication among UAVs is often impractical, especially in time-sensitive tasks or environments with limited bandwidth. With this in mind, this paper presents a finite-time leader-following distributed tracking control scheme for general multi-agent systems, with a particular emphasis on its application for networked UAVs. Theoretically, a dynamic event-triggered mechanism is proposed, which features a novel finite-time stable dynamic variable within its triggering rule, ensuring that neither controller updates nor trigger detection requires continuous communication. This event-triggered finite-time controller facilitates efficient network resource management and timely mission response in UAV cooperation, enhancing adaptability to onboard wireless communication networks and time-sensitive tasks. The method allows for the customization of parameters in the internal dynamic variables to adjust the convergence rate and event-triggering frequency of the system, while also preventing Zeno behavior. Moreover, a Lyapunov-based analysis is conducted to theoretically verify the finite-time stability of the closed-loop system and its applicability in directed communication networks. Finally, some numerical simulations are performed to validate the effectiveness of the proposed distributed control scheme for networked multi-UAV systems.

Inhabiting Space in Digital City Models. Exploring Immersive Design in Futuristic Digital Environments

Introduction: Nowadays we find numerous virtual environments that challenge the limits of the imagination. An example of this challenge is the video game Cyberpunk 2077, whose scenario recreates a futuristic environment based on a vertical distribution scheme. In contrast to the horizontal distribution schemes that we normally observe in open-world digital environments, a new field of analysis opens up on how high-rise virtual cities are shaped and designed. Objective: The aim of the research is to extract and understand the design keys that allow the space to be experienced in the most dynamic and immersive way possible in these virtual spaces. Methodology: The methodology uses the case method and seeks to defragment the design codes that make up this digital city, extrapolating them to the physical experience of real architecture. Results: By decomposing the video game and its contents, a whole mapping of information is extracted that allows us to understand the established design links. Discussion: It is observed how the visual language graphed in plan is insufficient to understand the multiplicity of levels that the futuristic city presents, being relevant presence of the elevation when it comes to understanding the space and the magnitude of its interconnections.

YOLOv8‐ESW: An Improved Oncomelania hupensis Detection Model

ABSTRACTTraditional Oncomelania hupensis detection relies on human eye observation, which results in reduced efficiency due to easy fatigue of the human eye and limited individual cognition, an improved YOLOv8 O. hupensis detection algorithm, YOLOv8‐ESW(expectation–maximization attention [EMA], Small Target Detection Layer, and Wise‐IoU), is proposed. The original dataset is augmented using the OpenCV library. To imitate image blur caused by motion jitter, salt and pepper, and Gaussian noise were added to the dataset; to imitate images from different angles captured by the camera in an instant, affine, translation, flip, and other transformations were performed on the original data, resulting in a total of 6000 images after data enhancement. Considering the insufficient feature fusion problem caused by lightweight convolution, We present the expectation–EMA module (E), which innovatively incorporates a coordinate attention mechanism and convolutional layers to introduce a specialized layer for small target detection (S). This design significantly improves the network's ability to synergize information from both superficial and deeper layers, better focusing on small target O. hupensis and occluded O. hupensis. To tackle the challenge of quality imbalance among O. hupensis samples, we employ the Wise‐IoU (WIoU) loss function (W). This approach uses a gradient gain distribution strategy and improves the model convergence speed and regression accuracy. The YOLOv8‐ESW model, with 16.8 million parameters and requiring 98.4 GFLOPS for computations, achieved a mAP of 92.74% when tested on the O. hupensis dataset, marking a 4.09% improvement over the baseline model. Comprehensive testing confirms the enhanced network's efficacy, significantly elevating O. hupensis detection precision, minimizing both missed and false detections, and fulfilling real‐time processing criteria. Compared with the current mainstream models, it has certain advantages in detection accuracy and has reference value for subsequent research in actual detection.

Impact of Climate Change on the Habitat Distribution of Decapterus macarellus in the South China Sea

This study examines the potential distribution of Mackerel scad (Decapterus macarellus) in the South China Sea under future climate scenarios (SSP 1.26, SSP 2.45, SSP 5.85) using an ensemble species distribution model (SDM). Key environmental variables included sea surface salinity (SSS), sea surface height (SSH), sea surface temperature (SST), mixed-layer depth (MLD), chlorophyll-a concentration (CHL), and sea-bottom temperature (SBT). Results show that SST and MLD are the primary drivers of habitat suitability, with current suitable habitats concentrated in the northern offshore areas. Projections for the 2050s and 2090s indicate a reduction in suitable habitats, particularly under high-emission scenarios, with more gradual reductions under low-emission scenarios. Habitat loss is most pronounced in the northern South China Sea, while the central region is projected to see an expansion of suitable habitats. These findings highlight the climate impact on D. macarellus distribution and inform sustainable management strategies for the species in the region.

Numerical study on the application of low-turbulence air curtain surrounding laminar airflow distribution in operating rooms

Abstract Laminar airflow (LAF) is essential for maintaining a sterile environment in operating rooms, but its rapid unidirectional flow decay leads to low airflow efficiency and increases energy consumption. The objective of this study is to investigate the energy-saving and air quality benefits of using a low-turbulence air curtain around laminar airflow, which is referred to as protective laminar airflow (PLAF). Numerical simulations were used to model airflow and particle transport, and a series of experiments were conducted in a real operating room at St. Olavs Hospital, Norway, to validate the simulation results. The findings indicate that when the unidirectional airflow supply velocity is maintained at 0.25 m/s, combined with an air curtain that has the width of 2 cm and the velocity of 1.5 m/s, the PLAF system outperforms the conventional LAF system operating at a unidirectional airflow supply velocity of 0.30 m/s. This configuration results in a 17.3% energy saving, showing the potential of this airflow distribution strategy to enhance both cleanliness and energy efficiency.

Research on Benefit Distribution of Old Residential Area Renovation Projects under the New PPP Mechanism

The introduction of the new PPP mechanism will bring about huge changes in the implementation methods and revenue sources of old residential area renovation PPP projects implemented in the past in China. In order to cope with thechanges brought about by the new PPP mechanism and ensure the smooth implementation of the project, it is necessary to study and explore the scientific and reasonable revenue distribution mechanism for old residential area renovation projects under the new PPP mechanism. Based on the research achievements of predecessors and the characteristics of the project, this paper determines the four indicators of resource input ratio, risk allocation ratio, innovation ability, and community residents' satisfaction as the influencing factors of project revenue distribution, and uses them to revise the initial Shapley value revenue distribution model. The paper then conducts an empirical analysis of the M old residential area renovation project in H City as an example. After the revision, the social capital will receive higher project revenue allocation than the initial allocation value due to its greater resource input, greater risk allocation proportion, stronger innovation ability, and higher community residents' satisfaction, verifying the fairness and rationality of the revenue distribution model constructed in this paper and its ability to motivate the participation entities to improve both the economic and social benefits of the project and promote the successful completion of the project. The research content of this paper can provide ideas for the revenue distribution scheme research of old residential area renovation projects under the new PPP mechanism, and has certain reference value.

Frugal business model innovation in an Indian emerging market: a multiple case study

Purpose This multiple case study aims to investigate the frugal business model innovation exemplified by three pioneering organisations in India: Aravind Eye Care System (AECS), ChotuKool and SELCO India. This study elucidates the key factors contributing to their success and explores the broader implications for frugal innovation in addressing societal challenges in emerging markets. Design/methodology/approach The authors use a qualitative case study methodology to analyse the approaches of AECS, ChotuKool and SELCO India towards product development, distribution strategies and financing mechanisms and their impact on underserved communities. Data is collected through archival research and analysis of secondary sources. Findings The findings of the study reveal common themes and unique characteristics of frugal business model innovation across the three organisations. Key findings include innovative approaches to product/service design, distribution channels tailored to reach underserved populations and the implementation of flexible financing mechanisms to make products/services accessible to low-income consumers. Research limitations/implications This study enhances the understanding of frugal innovation in emerging markets and highlights the importance of affordability, accessibility and sustainability in driving positive social impact. Limitations include focus on only three case studies and the qualitative nature of the research, which may limit generalisability. Practical implications This study offers insights for managers and decisionmakers on implementing frugal innovation strategies to address societal challenges and promote inclusive growth in emerging markets. Key managerial implications include the importance of understanding local contexts, building partnerships and leveraging innovative financing mechanisms. The study provides guidance for practitioners and social entrepreneurs in developing scalable and sustainable solutions for underserved communities. Practical implications include the adoption of decentralised distribution models, customisation of products/services and investment in capacity-building and training programmes. Social implications The study highlights the significant impact of frugal business model innovation on underserved communities, including improved access to essential services, enhanced quality of life and socioeconomic empowerment. Implications for society include the potential for frugal innovation to address pressing societal challenges and promote inclusive growth. Originality/value The originality and value of this study lie in its comprehensive analysis of frugal business model innovation across multiple sectors in the Indian context. By examining the experiences of AECS, ChotuKool and SELCO India, the study contributes to the literature on frugal innovation and provides actionable insights for businesses, policymakers and development practitioners seeking to create positive social impact in emerging countries.

Global scaled consensus in finite-time for variable-order multi-agent systems with discontinuous inherent dynamics and switching topologies

This paper investigates the global asymptotic scaled consensus and global finite-time scaled consensus for variable-order multi-agent systems with discontinuous inherent dynamics and switching topologies. Via the switched distributed control schemes, sufficient scaled consensus criteria of multi-agent systems are established. As for global finite-time scaled consensus, the settling time for the consensus of multi-agent systems is explicitly evaluated, which is related to fractional-order derivative, control parameters, and average dwell time. Two simulation examples and one comparison are presented to imply the efficacy of the proposed control strategies.

Interval-valued optimal control strategies for vaccine distribution and infection awareness investment in preservation technology

Purpose This study aims to explore the global threat of diseases that affect people, such as diarrheal, Hepatitis B, Rotavirus, Measles diseases, emphasizing the integration of disease vaccines into immunization programs globally as recommended by the World Health Organization, resulting in significant case reductions. Design/methodology/approach Notably, it stresses the necessity of raising awareness about diseases and vaccines through promotional efforts alongside effective inventory management because of vaccine perishability, highlighting preservation techniques and cold storage. Addressing environmental concerns, including carbon emissions from vaccine deterioration, the study proposes green technology investments aligned with Sustainable Development Goals to mitigate these impacts. Additionally, advanced optimization algorithms, including ant colony, modified flower pollination, cuckoo search and particle swarm optimization algorithms, are used to optimize pricing, preservation strategies, green investments and replenishment schedules. The research also uses the concept of interval values to enhance the robustness of the optimization framework. Through numerical experiments, the study demonstrates the effectiveness of this dynamic investment approach, providing empirical validation. Findings Furthermore, sensitivity analysis on critical parameters yields valuable insights for decision-makers, underscoring the importance of dynamically managing vaccine inventory. The study offers practical solutions and managerial insights that can inform policy decisions and strategic planning in disease response efforts. Originality/value This study concludes by emphasizing how creative green technology approaches can help decision-makers manage the social and environmental effects of vaccine inventories in the health care of people.

Market dynamics and distribution strategy in the agricultural industry: An exploratory study

Market dynamics and distribution strategy in the agricultural industry: An exploratory study

Approach to Publishing a Scientific (Radiology) Book.

In the modern landscape of information technology, the role of books remains pivotal in education and research, especially in scientific fields such as radiology. This article outlines a comprehensive approach to publishing a scientific book in radiology, from the initial concept to distribution and ongoing updates. The process is influenced by factors such as the author's motivation, expertise, and target audience. Key prerequisites include a clear understanding of the subject, proficiency in writing and layout planning, and adherence to publication ethics. The book's content should be tailored to the intended readership, with considerations for content depth and presentation style. Decisions regarding book size, color versus black-and-white printing, and publication format (print vs. online) are crucial. Factors such as cost, physical characteristics, and the choice between paperback and hardcover affect both the book's accessibility and its durability. The online version offers interactive features and updatable content, while print versions provide a tactile reading experience. Authors are responsible for content creation, including illustrations, and chapter structure. Editors play a crucial role in maintaining uniformity, overseeing content quality, and ensuring technical accuracy. Collaboration with section editors and coauthors is often necessary for comprehensive coverage. Effective distribution and marketing strategies are essential for reaching the target audience. Options include direct retail distribution or using aggregators. Regular updates are vital to keep the book relevant amidst the fast-growing field of radiology. This guide serves as a practical roadmap for aspiring authors and editors in the field of radiology.

Trichuriasis in Human Patients from Côte d'Ivoire Caused by Novel Trichuris incognita Species with Low Sensitivity to Albendazole/Ivermectin Combination Treatment.

Albendazole/ivermectin combination therapy is a promising alternative to benzimidazole monotherapy alone for Trichuris trichiura control. We used fecal DNA metabarcoding to genetically characterize Trichuris spp. populations in patient samples from Côte d'Ivoire showing lower (egg reduction rate <70%) albendazole/ivermectin sensitivity than those from Laos and Tanzania (egg reduction rates >98%). Internal transcribed spacer (ITS) 1 and ITS2 metabarcoding revealed the entire detected Côte d'Ivoire Trichuris population was phylogenetically distinct from T. trichiura found in Laos and Tanzania and was more closely related to T. suis. Mitochondrial genome sequencing of 8 adult Trichuris worms from Côte d'Ivoire confirmed their species-level differentiation. Sequences from human patients in Cameroon and Uganda and 3 captive nonhuman primates suggest this novel species, T. incognita, is distributed beyond Côte d'Ivoire and has zoonotic potential. Continued surveillance by using fecal DNA metabarcoding will be needed to determine Trichuris spp. geographic distribution and control strategies.

On-detector power distribution for CMS-HGCAL: a busbar-based approach

An on-detector power distribution scheme for the High Granularity Calorimeter (HGCAL) Phase-2 upgrade of CMS is under development. This scheme is based on a heavy-copper flexible printed circuit board (FPC), allowing for an efficient use of the tight integration space, with minimal insulation overhead, excellent electrical and thermal performance and simplified integration, when compared with a wired solution. This work introduces the technology, how it allows the HGCAL challenges to be overcome, and the characterization studies. Prototypes testing are presented to validate the concept and quantify the manufacturability, electrical performance, and safety of the proposed solution.

Targeted distribution of long-lasting insecticidal nets by community health workers to sustain household coverage: A pilot feasibility study in Western Uganda.

Universal coverage is defined by the World Health Organization as 1 long-lasting insecticidal net (LLIN) for 2 people in a household. While Uganda has been a leader in the distribution of LLINs, there are concerns regarding the longevity of LLINs. The main aim of this study was to address the LLIN coverage gap that emerges in the period after mass distribution campaigns through the implementation of a novel LLIN distribution strategy utilizing the existing community healthcare worker (CHW) infrastructure. We conducted a pilot feasibility study in two villages randomized to be the control or intervention. CHWs in both villages carried out their regular duties and calculated household eligibility to receive LLINs, classified as having a child under five positive for malaria and being below universal coverage. Only CHWs in the intervention village distributed LLINs to eligible households to reach universal coverage. Summary statistics were calculated for intervention implementation and malaria outcomes. Structured interviews were conducted with CHWs to assess burden and community acceptability of the intervention. Of the children evaluated by the CHWs, 102 of 169 (60.3%) and 112 of 171 (65.5%) were tested for malaria, of which 62 (60.7%) and 71 (63.3%) tested positive in the intervention and control villages, respectively. Only three households were at universal coverage. There was an increase from 4.0% to 6.5% of households meeting universal coverage in the intervention village, compared to a decrease from 7.8% to 1.8% in the control village after the follow-up period. There was an increase in the number of children under the age of 5 who slept under an LLIN the previous night from 15.7% to 31.6% in the intervention village compared to a decrease in the control village from 29.1% to 10.5%. No CHWs reported an increased burden from the intervention and all reported favorable opinions. Our pilot study demonstrates the feasibility and acceptability of targeted LLIN distributions leveraging the existing structure to supplement national distribution campaigns in Uganda. Overall, this work highlights the critical need for novel approaches to sustain LLIN coverage between distribution campaigns, particularly towards the end of the 3-year cycle.

Improved GOA-based fuzzy PI speed control of PMSM with predictive current regulation.

To address the susceptibility of conventional vector control systems for permanent magnet synchronous motors (PMSMs) to motor parameter variations and load disturbances, a novel control method combining an improved Grasshopper Optimization Algorithm (GOA) with a variable universe fuzzy Proportional-Integral (PI) controller is proposed, building upon standard fuzzy PI control. First, the diversity of the population and the global exploration capability of the algorithm are enhanced through the integration of the Cauchy mutation strategy and uniform distribution strategy. Subsequently, the fusion of Cauchy mutation and opposition-based learning, along with modifications to the optimal position, further improves the algorithm's ability to escape local optima. The improved GOA is then employed to optimize the contraction-expansion factor of the variable universe fuzzy PI controller, achieving enhanced control performance for PMSMs. Additionally, to address the high torque and current ripple issues commonly associated with traditional PI controllers in the current loop, Model Predictive Control (MPC) is adopted to further improve control performance. Finally, experimental results validate the effectiveness of the proposed control scheme, demonstrating precise motor speed control, rapid and stable current tracking, as well as improved system robustness.

Imbalance in nitrogen and phosphorus allocation between tree roots and leaves induced by nitrogen addition.

The allocation of limiting elements, such as nitrogen (N) and phosphorus (P), in plant organs is essential for nutrient cycling between soil and plants (soil-plant nutrient cycling) and functional optimization in plant communities. Unprecedented inputs of anthropogenic N have caused drastic N and P imbalances in terrestrial ecosystems. However, the effects of N addition on the allocation strategies of N and P between plant organs remain unclear. In this study, we conducted a long-term, multilevel N addition experiment to investigate the allocation strategies for N and P in plant leaves and fine roots. We found that N addition significantly increased leaf N concentration, leaf P concentration, and leaf N:P ratios, while significantly decreasing fine root N concentration, fine root P concentration, and fine root N:P ratios. Additionally, we demonstrated a higher proportional increase of N in leaves and a lower proportional decrease of P in fine roots with N addition. Furthermore, our analyses revealed that N addition influenced the allocation of N and P between plant leaves and fine roots through changes in plant growth patterns and nutrient distribution strategies. These changes were driven by a significant increase in soil inorganic N concentration, a decrease in soil N cycling and a reduction in mycorrhizal symbiosis. Our findings suggest that N addition will likely lead to an imbalance between the N and P cycles in temperate forest ecosystems, due to the unequal allocation of N and P between tree roots and leaves. This imbalance may, in turn, have negative implications for the provision of ecosystem services.