BuffGraph: Enhancing Class-Imbalanced Node Classification via Buffer Nodes

Class imbalance in graph-structured data, where minor classes are significantly underrepresented, poses a critical challenge for Graph Neural Networks (GNNs). To address this challenge, existing studies generally generate new minority nodes and edges connecting new nodes to the original graph to make classes balanced. However, they do not solve the problem that majority classes still propagate information to minority nodes by edges in the original graph which introduces bias towards majority classes. To address this, we introduce BuffGraph, which inserts buffer nodes into the graph, modulating the impact of majority classes to improve minor class representation. Our extensive experiments across diverse real-world datasets empirically demonstrate that BuffGraph outperforms existing baseline methods in class-imbalanced node classification in both natural settings and imbalanced settings. Code is available at https://anonymous.4open.science/r/BuffGraph-730A

A Survey of Imbalanced Learning on Graphs: Problems, Techniques, and Future Directions

Graphs represent interconnected structures prevalent in a myriad of real-world scenarios. Effective graph analytics, such as graph learning methods, enables users to gain profound insights from graph data, underpinning various tasks including node classification and link prediction. However, these methods often suffer from data imbalance, a common issue in graph data where certain segments possess abundant data while others are scarce, thereby leading to biased learning outcomes. This necessitates the emerging field of imbalanced learning on graphs, which aims to correct these data distribution skews for more accurate and representative learning outcomes. In this survey, we embark on a comprehensive review of the literature on imbalanced learning on graphs. We begin by providing a definitive understanding of the concept and related terminologies, establishing a strong foundational understanding for readers. Following this, we propose two comprehensive taxonomies: (1) the problem taxonomy, which describes the forms of imbalance we consider, the associated tasks, and potential solutions; (2) the technique taxonomy, which details key strategies for addressing these imbalances, and aids readers in their method selection process. Finally, we suggest prospective future directions for both problems and techniques within the sphere of imbalanced learning on graphs, fostering further innovation in this critical area.Comment: The collection of awesome literature on imbalanced learning on graphs: https://github.com/Xtra-Computing/Awesome-Literature-ILoG

An Online Joint Optimization Approach for QoE Maximization in UAV-Enabled Mobile Edge Computing

Given flexible mobility, rapid deployment, and low cost, unmanned aerial vehicle (UAV)-enabled mobile edge computing (MEC) shows great potential to compensate for the lack of terrestrial edge computing coverage. However, limited battery capacity, computing and spectrum resources also pose serious challenges for UAV-enabled MEC, which shorten the service time of UAVs and degrade the quality of experience (QoE) of user devices (UDs) {\color{b} without effective control approach}. In this work, we consider a UAV-enabled MEC scenario where a UAV serves as an aerial edge server to provide computing services for multiple ground UDs. Then, a joint task offloading, resource allocation, and UAV trajectory planning optimization problem (JTRTOP) is formulated to maximize the QoE of UDs under the UAV energy consumption constraint. To solve the JTRTOP that is proved to be a future-dependent and NP-hard problem, an online joint optimization approach (OJOA) is proposed. Specifically, the JTRTOP is first transformed into a per-slot real-time optimization problem (PROP) by using the Lyapunov optimization framework. Then, a two-stage optimization method based on game theory and convex optimization is proposed to solve the PROP. Simulation results validate that the proposed approach can achieve superior system performance compared to the other benchmark schemes

Joint Task Offloading and Resource Allocation in Aerial-Terrestrial UAV Networks with Edge and Fog Computing for Post-Disaster Rescue

Unmanned aerial vehicles (UAVs) play an increasingly important role in assisting fast-response post-disaster rescue due to their fast deployment, flexible mobility, and low cost. However, UAVs face the challenges of limited battery capacity and computing resources, which could shorten the expected flight endurance of UAVs and increase the rescue response delay during performing mission-critical tasks. To address this challenge, we first present a three-layer post-disaster rescue computing architecture by leveraging the aerial-terrestrial edge capabilities of mobile edge computing (MEC) and vehicle fog computing (VFC), which consists of a vehicle fog layer, a UAV client layer, and a UAV edge layer. Moreover, we formulate a joint task offloading and resource allocation optimization problem (JTRAOP) with the aim of maximizing the time-average system utility. Since the formulated JTRAOP is proved to be NP-hard, we propose an MEC-VFC-aided task offloading and resource allocation (MVTORA) approach, which consists of a game theoretic algorithm for task offloading decision, a convex optimization-based algorithm for MEC resource allocation, and an evolutionary computation-based hybrid algorithm for VFC resource allocation. Simulation results validate that the proposed approach can achieve superior system performance compared to the other benchmark schemes, especially under heavy system workloads.Comment: 18 pages, 6 figure

Influence of photochemical loss of volatile organic compounds on understanding ozone formation mechanism

Volatile organic compounds (VOCs) tend to be consumed by atmospheric oxidants, resulting in substantial photochemical loss during transport. An observation-based model was used to evaluate the influence of photochemical loss of VOCs on the sensitivity regime and mechanisms of ozone formation. Our results showed that a VOC-limited regime based on observed VOC concentrations shifted to a transition regime with a photochemical initial concentration of VOCs (PIC-VOCs) in the morning. The net ozone formation rate was underestimated by 3 ppbh(-1) (similar to 36 ppb d(-1)) based on the measured VOCs when compared with the PIC-VOCs. The relative contribution of the RO2 path to ozone production based on the PIC-VOCs accordingly increased by 13.4 %; in particular, the contribution of alkene-derived RO(2 )increased by approximately 10.2 %. In addition, the OH-HO2 radical cycle was obviously accelerated by highly reactive alkenes after accounting for photochemical loss of VOCs. The contribution of local photochemistry might be underestimated for both local and regional ozone pollution if consumed VOCs are not accounted for, and policymaking on ozone pollution prevention should focus on VOCs with a high reactivity.Peer reviewe

Risk Factors Associated with Pain Severity in Patients with Non-specific Low Back Pain in Southern China

Study Design A prospective cross-sectional study. Purpose To evaluate the risk factors associated with the severity of pain intensity in patients with non-specific low back pain (NSLBP) in Southern China. Overview of Literature Low back pain (LBP) is the leading cause of activity limitation and work absence throughout the world, so a firm understanding of the risk factor associated with NSLBP can provide early and prompt interventions that are aimed at attaining long-term results. Methods Participants were recruited from January 2014 to January 2016 and were surveyed using a self-designed questionnaire. Anonymous assessments included Short Form 36-Item Health Survey (SF-36) and Visual Analogue Scale (VAS). The association between the severity of NSLBP and these potential risk factors were evaluated. Results A total of 1,046 NSLBP patients were enrolled. The patients with primary school education, high body mass index (BMI), those exposed to sustained durations of driving and sitting, smoking, recurrent LBP had increased VAS and Oswestry Disability Index (ODI) scores with lower SF-36 scores (p 10 kg objects in a quarter of their work time for >10 years had higher VAS and ODI scores with lower SF-36 scores (p <0.01). Multiple logistic regression showed lower levels of education, LBP for 1–7 days, long-lasting LBP in last year, smoking, long duration driving, and higher BMI were associated with more severe VAS score. Conclusions The severity of NSLBP is associated with lower levels of education, poor standards of living, heavy physical labor, long duration driving, and sedentary lifestyle. Patients with recurrent NSLBP have more severe pain. Reducing rates of obesity, the duration of heavy physical work, driving or riding, and attenuating the prevalence of sedentary lifestyles and smoking may reduce the prevalence of NSLBP

A New Type of Quartz Smog Chamber : Design and Characterization

Publisher Copyright: ©Since the 1960s, many indoor and outdoor smog chambers have been developed worldwide. However, most of them are made of Teflon films, which have relatively high background contaminations due to the wall effect. We developed the world's first medium-size quartz chamber (10 m(3)), which is jointed with 32 pieces of 5 mm thick polished quartz glasses and a stainless-steel frame. Characterizations show that this chamber exhibits excellent performance in terms of relative humidity (RH) (2-80%) and temperature (15-30 +/- 1 degrees C) control, mixing efficiency of the reactants (6-8 min), light transmittance (>90% above 290 nm), and wall loss of pollutants. The wall loss rates of the gas-phase pollutants are on the order of 10(-4) min(-1) at 298 K under dry conditions. It is 0.08 h(-1) for 100-500 nm particles, significantly lower than those of Teflon chambers. The photolysis rate of NO2 (J(NO2)) is automatically adjustable to simulate the diurnal variation of solar irradiation from 0 to 0.40 min(-1). The inner surface of the chamber can be repeatedly washed with deionized water, resulting in low background contaminations. Both experiments (toluene-NOx and alpha-pinene-ozone systems) and box model demonstrate that this new quartz chamber can provide high-quality data for investigating SOA and O-3 formation in the atmosphere.Peer reviewe

The opium poppy genome and morphinan production.

Morphinan-based painkillers are derived from opium poppy (Papaver somniferum L.). We report a draft of the opium poppy genome, with 2.72 gigabases assembled into 11 chromosomes with contig N50 and scaffold N50 of 1.77 and 204 megabases, respectively. Synteny analysis suggests a whole-genome duplication at ∼7.8 million years ago and ancient segmental or whole-genome duplication(s) that occurred before the Papaveraceae-Ranunculaceae divergence 110 million years ago. Syntenic blocks representative of phthalideisoquinoline and morphinan components of a benzylisoquinoline alkaloid cluster of 15 genes provide insight into how this cluster evolved. Paralog analysis identified P450 and oxidoreductase genes that combined to form the STORR gene fusion essential for morphinan biosynthesis in opium poppy. Thus, gene duplication, rearrangement, and fusion events have led to evolution of specialized metabolic products in opium poppy