Scale Threshold Research Articles

Needs of older adults in Kazakhstan: analysis and psychometric properties of the localized version of the EASYCare standard 2010 instrument

BackgroundStudies about the needs of older individuals in Central Asia are very sparse. Thus, this study aimed to evaluate the needs of older adults in Kazakhstan with the EASYCare Standard 2010 (EC) questionnaire.MethodsThe study involved 524 participants aged 65 and older from various regions in Kazakhstan. Data were collected by trained research staff, and the participants’ needs were examined using median split with the three summarizing indexes of the EC system (Independence score, Risk of breakdown in care, and Risk of falls).ResultsSubjects with primary education had approximately double odds of scoring above the median compared to those with higher education in Independence score (p < 0.01) and Risk of breakdown in care (p < 0.01). Individuals with primary education also had 60% higher odds of scoring above the Risk of falls scale threshold, indicating a risk in this category (p < 0.05). For the Risk of falls scores, financial situation was also significant; individuals having not enough to make ends meet had 75% higher odds than the remaining ones (p < 0.01).ConclusionOur analysis highlights the importance of tailored interventions to address the unmet needs of the Kazakh population, particularly among those with lower education and those with financial concerns. The study also underscores the need for sustainable, comprehensive eldercare policies in Kazakhstan that account for the growing older population.

Color code decoder with improved scaling for correcting circuit-level noise

Two-dimensional color codes are a promising candidate for fault-tolerant quantum computing, as they have high encoding rates, transversal implementation of logical Clifford gates, and resource-efficient magic state preparation schemes. However, decoding color codes presents a significant challenge due to their structure, where elementary errors violate three checks instead of just two (a key feature in surface code decoding), and the complexity of extracting syndrome is greater. We introduce an efficient color-code decoder that tackles these issues by combining two matching decoders for each color, generalized to handle circuit-level noise by employing detector error models. We provide comprehensive analyses of the decoder, covering its threshold and sub-threshold scaling both for bit-flip noise with ideal measurements and for circuit-level noise. Our simulations reveal that this decoding strategy nearly reaches the best possible scaling of logical failure (pfail∼pd/2) for both noise models, where p is the noise strength, in the regime of interest for fault-tolerant quantum computing. While its noise thresholds are comparable with other matching-based decoders for color codes (8.2% for bit-flip noise and 0.46% for circuit-level noise), the scaling of logical failure rates below threshold significantly outperforms the best matching-based decoders.

Multiscale Sensitivity Analysis of Landscape Fragmentation in Plantation Forests on the Loess Plateau

ABSTRACTEffectively quantifying plantation forest fragmentation is crucial for vegetation restoration and management on the Loess Plateau. Forest area density (FAD) effectively measures fragmentation, with multiscale sensitivity analysis essential for determining the appropriate window scale threshold. This study uses plantation forest data from different geomorphological types (hilly gully and plateau gully region) of the Loess Plateau. Various window sizes are applied to evaluate the FAD threshold curve and its derivative for determining a stable fragmentation threshold, while a structural equation model is employed to analyze the drivers of forest fragmentation. The results are as follows: (1) FAD variability decreases with increasing window size, leveling off after reaching the threshold. (2) Thresholds vary by forest type and county. (3) Two principal components explain 81.27% of the window stabilization threshold variation, with strong correlations between similar fragmentation types. (4) Fragmentation slowed between 2000 and 2022, with hilly gully region more fragmented than plateau gully region. (5) Stand structure mitigates fragmentation, with topographic and climate change influences showing heterogeneity. “Core” maintain stability, while “Islet” drive fragmentation. This study emphasizes the importance of scale‐specific analysis and adaptive management strategies in mitigating forest fragmentation. This study supports optimizing ecological restoration and targeted conservation strategies, promoting sustainable forest management on the Loess Plateau.

Experience-based food insecurity in Bangladesh: Evidence from Household Income and Expenditure Survey 2022.

This paper examines the current state of food insecurity in Bangladesh and its socio-economic drivers using data from the latest Household Income and Expenditure Survey (HIES 2022). Unlike previous studies that relied on less precise measures of food insecurity, such as food expenditure, diversity, and calorie intake, this study employs the internationally recognized Food Insecurity Experience Scale (FIES) and Rasch model-based thresholds to classify households as food secure or insecure. Multilevel logistic regression is used to identify significant predictors of moderate and severe food insecurity, considering the hierarchical structure of the data, with households nested within geographical clusters. Key factors found to be significantly associated with food security include the wealth index, land ownership, education of the household head, family size, remittance income and exposure to shocks. A classification tree, a popular machine learning method, is also applied to explore important interactions among these determinants. The tree analysis confirms the importance of several regression-based predictors and identifies households at the highest risk of food insecurity through variable interactions. Factors such as poverty, lack of land ownership, low education levels, and high dependency ratios collectively increase a household's vulnerability to moderate food insecurity to around 51% while the national prevalence is 19%. District-level maps of food insecurity prevalence reveal significant regional disparities, underscoring the need for targeted, district-specific interventions to effectively combat food insecurity. More broadly, policies promoting education and family planning, training in better shock management, and facilitating remittance flows through simplified processes may contribute to addressing the food insecurity challenge.

Immediate Effects of Distinct Intensities of Transcutaneous Spinal Direct Current Stimulation on Chronic Pain: A Randomized Controlled Trial.

This study aimed to assess the immediate effects of transcutaneous spinal direct current stimulation (tsDCS) on pain outcomes, measured using the visual analog scale (VAS) and pressure pain thresholds in a cohort of 55 participants experiencing chronic pain using a controlled, randomized trial with 55 participants allocated into 2 groups: 2 mA and 0.5 mA of tsDCS for 20 min. Anodal stimulation was applied on the 12th thoracic vertebra, with the cathode positioned on the 7th cervical vertebra. Pain outcomes were assessed before and post intervention using the VAS and pressure algometry. Between- and within-group differences, along with chi-square tests, were used to determine the differences and responsiveness. Significance was established at p < 0.05. Findings showed significant temporal effects for both VAS (p < 0.001) and pressure algometry (p = 0.04). However, no between-group differences were noted for the time × group factor for VAS (p = 0.46) and pressure algometry (p = 0.78). No significant between-group differences were observed for the responsiveness analysis. The results indicate that a single 20-min session of 2 and 0.5 mA tsDCS improves pain scores for both intensities equally. However, there were no statistically significant between-group differences in pain perception or pressure pain threshold.

Complex multivariate model predictions for coral diversity with climatic change

AbstractModels of the future of coral reefs are potentially sensitive to theoretical assumptions, variable selectivity, interactions, and scales. A number of these aspects were evaluated using boosted regression tree models of numbers of coral taxa trained on ~1000 field surveys and 35 spatially complete influential environmental proxies at moderate scales (~6.25 km2). Models explored influences of climate change, water quality, direct human‐resource extraction, and variable selection processes. We examined the predictions for numbers of coral taxa using all variables and compared them to models based on variables commonly used to predict climate change and human influences (eight and nine variables). Results indicated individual temperature variables alone had lower predictive ability (R2 &lt; 2%–7%) compared to human influence variables (6%–18%) but overall climate had a higher training–testing fit (70%) than the human influence (63%) model. The full variable model had the highest fit to the full data (27 variables; R2 = 85%) and indicated the strongly interactive and complex role of environmental and human influence variables when making moderate‐scale biodiversity predictions. Projecting changes using Coupled Model Intercomparison Project (CMIP) 2050 Representative Concentration Pathways (RCP2.6 and 8.5) water temperature predictions indicated high local variability and fewer negative effects than predictions made by coarse scale threshold and niche models. The persistence of coral reefs over periods of rapid climate change is likely to be caused by smaller scale variability that is poorly simulated with coarse scale modeled predictions.

Quasi-continuous exhaust operational space

Abstract The IPED predictive pedestal code has been used to determine the critical gradients for the onset of 1) separatrix ballooning modes and 2) global peeling-ballooning modes as a function of plasma shaping. This results in a scaling of the onset threshold of separatrix ballooning modes as a function of elongation and triangularity αedge,crit = 0.64κ2.2(1+δ)0.9, while the critical gradient for global peeling-balloonig modes increases as αedge,crit 1.5. This implies that operational space for a ballooning unstable separatrix and stable peeling-ballooning modes exists at sufficiently high shaping. Applying a collisional broadnening based scaling of the separatrix gradients allows the critical separatrix density, required to drive the separatrix ballooning mode, to be derived from global plasma parameters for any operational scenario on any device. Evaluations for ASDEX Upgrade, JET, and the ITER 15 MA baseline plasma predict critical separatrix densities of 0.3-0.4 nGW for QCE access, making the QCE an attractive operational scenario for fusion devices.

ESG performance and green innovation of Chinese enterprises: Based on the perspective of financing constraints

Sustainable development needs to rely on green innovation. Enterprise ESG performance rating to alleviate the information asymmetry between enterprises and investors, for the green innovation provides development opportunities. However, there is a lack of research on the mechanism of the two based on the perspective of financing constraints. Therefore, considering the theories of sustainable development, green innovation, financing constraints and stakeholders, the basic mechanism and non-linear mechanism of ESG and green innovation are explored, aiming to provide reference for playing the role of ESG performance in promoting green innovation. The results show that better ESG performance can significantly promote the output of green innovation, and this promoting effect exists for both high-end green innovation and low-end green innovation, and its main channel is to alleviate financing constraints. In addition, this incentive exists a double threshold of digital finance and a single threshold of enterprise scale. Perfect digital finance and larger enterprise scale will strengthen the incentive effect of enterprise ESG performance on green innovation output. Considering financing constraints, this study further clarifies the relationship between enterprises ESG performance and green innovation, enriching the theoretical framework of green innovation and offering a new pathway for advancing green innovation among Chinese enterprises.

Wavelet detection method for transient electrical energy disturbance with noise

Abstract Electric energy signals are often contaminated by noise during the collection process, which affects the accurate positioning of disturbances. The discontinuity of traditional hard threshold functions can lead to oscillations, while excessive smoothness of soft threshold functions can lead to signal distortion. The optimized threshold function and scale adaptive processing on the selection of the threshold are proposed. The wavelet thresholding method is used to process voltage sag, rise, and interrupt signals containing noise. The denoised signal is decomposed into five scale wavelets using db7 wavelet and detected by using wavelet transform modulus maximum and signal singularity principle. Experiments have shown that optimized threshold and threshold function not only effectively denoise but also retain the effective mutation point information in the original signal, and the new method is reliable in detection.

THE EFFECT OF EXERCISES OF DIFFERENT INTENSITY APPLIED AFTER TOTAL KNEE ARTHROPLASTY ON POST-OPERATIVE PAIN: RANDOMIZED CONTROLLED TRIAL

Purpose: This study aimed to investigate the changes in pain following exercise sessions with different intensities in patients who underwent total knee arthroplasty (TKA). Methods: This is a repeated measure and single-blinded randomized controlled study. Thirty-six patients who underwent TKA (age, 64.9 ± 7.42 years) were randomly assigned to either low-intensity exercises (LIEs) group or high-intensity exercises (HIEs) group. Exercise programs lasted for five days during the hospitalization period. Pain intensity was assessed by visual analog scale (VAS) and pressure pain thresholds (PPTs) were measured over quadriceps and biceps brachii and muscles immediately before and after exercise. Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) subscale (pain, stiffness, and physical function) scores were recorded at two points in baseline and discharge from the hospital. Results: The pain intensity decreased in patients in both groups after TKA. PPTs increased in both groups at all tested sites following the first, third, and fifth exercise bouts. HIE program had a greater positive effect on the pain intensity after the first exercise session than LIE program on the PPTs ([Formula: see text] &lt; 0.05). HIE program was more effective in order to reduce pain severity immediately after the exercise sessions in patients ([Formula: see text]: 0.5, [Formula: see text] &lt; 0.05). WOMAC scores significantly improved in both groups during the discharge from the hospital ([Formula: see text] = 0.001). Conclusion: Our results found that both LIE and HIE programs performed during hospitalization after TKA declined pain intensity. Particularly notable were the substantial improvements observed in managing post-operative pain, especially following the second exercise session. The HIE program proved more effective in improving stiffness, and enhancing physical function.

First measurement of Gallium Arsenide as a low-temperature calorimeter

In the quest for direct dark matter detection, innovative approaches to lower the detection threshold and explore the sub-GeV mass range, have gained high relevance in the last decade. This study presents the pioneering use of Gallium Arsenide (GaAs) as a low-temperature calorimeter for probing dark matter-electron interactions within the DAREDEVIL (DARk-mattEr DEVIces for Low energy detection) project. Our experimental setup features a GaAs crystal at an ultralow temperature of 15 mK, coupled with a Neutron Transmutation Doped Germanium (NTD-Ge) thermal sensor for precise energy estimation. This configuration is the first step towards detecting single electrons scattered by dark matter particles within the GaAs crystal, to improve the sensitivity to low-mass dark matter candidates significantly. Taking advantage of the production of optical phonons in polar materials such as GaAs gives the possibility to study the scattering of sub-MeV dark matter. This paper presents a detailed analysis of the detector’s response, using a calibration spectrum using α\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\alpha $$\\end{document} particles and X-ray events. While the results do not meet the ambitious eV scale threshold yet, they establish a solid benchmark for assessing the detector’s current performance and sensitivity. This work not only highlights the detector’s potential but also sets the stage for future enhancements aimed at achieving the eV threshold, underscoring the promising direction of this detector technology. These findings demonstrate the feasibility of using GaAs as a cryogenic calorimeter and hence open new avenues for investigating the elusive nature of dark matter through innovative direct detection techniques.

Olfactory dysfunction in patients with type 2 diabetes mellitus.

diabetic complications and olfactory dysfunction (OD) in patients with type 2 diabetes mellitus (T2DM) seem related. This study aims to evaluate the prevalence of OD in T2DM patients and to analyze its relationship with diabetic complications. 130 T2DM patients and 100 comparable controls were enrolled. Olfaction was evaluated using the Extended Smell Test (TDI) and the Italian brief Questionnaire of Olfactory Disorders â€" Brief-IT-QOD. T2DM patients were divided into: "Group 1" patients with no complications, and "Group 2" patients with at least one diabetic complication. Non-parametric tests were used. Machine learning algorithms were applied to explore which variables were most important in predicting the presence of OD in T2DM. The prevalence of OD was significantly higher in Group 2 than in controls (71.4% vs 30%) and in Group 1 (71.4% vs 43.3%). However, when comparing the TDI scores between Group 1 and 2 the only significant difference was found for the discrimination scale and not for the identification and threshold scales. Brief-IT-QOD scores were significantly higher in Group 2 than in controls. The Random Forest and variable importance algorithms highlighted the relevance of LDL, glycated hemoglobin, type of complication (macrovascular) and age in determining OD in T2DM. The last three variables were included in a nomogram for the prediction of OD risk in T2DM. T2DM patients with diabetic complications are more frequently affected by OD. Poor glycemic control, LDL values, age and presence of macrovascular complications are the more important factors in determining OD in T2DM patients.

Scale-dependent behavior of microstructure characteristics of laser powder bed fused TiB2/AlSi10Mg composite

The pre-alloyed TiB2/AlSi10Mg composite, a new high-strength aluminum alloy developed for laser powder bed fusion (LPBF) technology, offers promising applications in lightweight and multi-scaled structures. However, thermal behavior during LPBF is markedly scale-dependent, leading to microstructural variations that significantly affect the load-bearing capacity of multi-scaled structures. Therefore, this study systematically investigates the scale-dependent behavior of microstructure characteristics of this composite. Utilizing a hatching scanning strategy, it was found that the marginal zones of samples are predominantly composed of coarse Al cell and Al grain structures, contrasting with the fine microstructures in the central zones. With increasing structure scale, cell and grain structures in both the marginal and central zones become more refined, with cell sizes reducing by 49 %–72 % (∼3.02 µm → 0.86–1.55 µm). Particularly, the minimum-scaled structures also feature broken eutectic Si particles and nanopores. The essence is primarily due to the low heat dissipation with higher peak temperature and longer duration time at high temperatures in both the small-scale structures and marginal zones. Additionally, smaller structures correlate with reduced microhardness and tensile strength, accompanied by the “softening” of the marginal zones. The strength of the minimum-scaled structure is only half that of the standard sample. Our findings suggest a scale threshold of 2.0 mm for researching scale effect. Encouragingly, incorporating additional contour scanning significantly counteracts the adverse influence of the scale effect. Owing to the combined influence of extended inter-layer time and laser remelting, all samples demonstrate a distinctly refined microstructure. This results in consistently high levels of microhardness and strength, with the “hardening” of the marginal zones. Eventually, the relationship between mechanical properties and microstructure sizes is established. This study provides valuable insights into the innovative designs and engineering applications of multi-scaled structures in LPBF using various materials.

Identification and Quenching of Nugget Galaxies in the RESOLVE Survey at z = 0

We present a complete census of candidate nuggets, i.e., dense galaxies likely formed by compaction with intense gas influx, within the volume-limited redshift z ∼ 0 REsolved Spectroscopy Of a Local VolumE (RESOLVE) survey. These nuggets span all evolutionary stages and 3 orders of magnitude in stellar mass (M * ∼ 108 to 1011 M ⊙) from the dwarf to the giant regime. We develop selection criteria for our z ∼ 0 nugget candidates based on structure and introduce the use of environmental criteria to eliminate nugget-like objects with suspected non-compaction origins. The resulting z ∼ 0 nuggets follow expectations with respect to structure (i.e., density, size), population frequency, and likely origins. We show that the properties of our nugget census are consistent with permanent quenching above the gas-richness threshold scale (halo mass M halo ∼ 1011.4 M ⊙), cyclic temporary quenching below the threshold scale, and feedback from active galactic nuclei (AGN) assisting in permanent quenching. As predicted in simulations, most nuggets quench within a halo mass range of M halo ∼ 1011.45 to 1011.9 M ⊙. We find ∼0.29 dex scatter around the star-forming main sequence for candidate blue nuggets below the threshold scale, which is consistent with temporary quenching as seen in simulations. A transitional population of green nuggets appears above the threshold scale. AGN also become more common in nuggets above this scale, and we see a likely AGN excess in nuggets versus comparably selected non-nuggets. Our results provide the first observational confirmation of the mass-dependent, AGN-mediated shift from cyclic quenching to halo quenching in nuggets.

Thermal comfort evaluation of student dormitory buildings in Syiah Kuala University

Abstract This study aims to analyse the thermal conditions of the student dormitory building against differences of orientation in tropical climates, which significantly impacts the thermal comfort of dormitory room occupants. Student dormitory building has a multi-floor design that accommodates a variety of daily student activities in it. The dormitory building that was chosen as the object of this study is the women’s dormitory building Rusunawa A which is located in the campus area of Syiah Kuala University. The research method used was quantitative with a descriptive approach. Quantitative data collected in the form of measurement results of physical variables include air temperature, radiant temperature, humidity, and air flow velocity in the sample rooms selected as the research object. Results indicate that the physical variables of thermal comfort in natural building design are influenced by the orientation of the building. Field survey data, based on thermal comfort factors measured in the Student Dormitory building, indicates an uncomfortable temperature exceeding the threshold scale of SNI 03-6572-2001.

Environmentally-friendly calcite scale mitigation: encapsulation of CDs@ MS composite within membranes framework for nanofiltration

Scale formation caused by the precipitation of sparingly soluble salts such as CaCO3 is a major challenge in membrane-based desalination technologies, leading to flux decline and increased energy costs. Surface modification using nanoscale coatings is a promising approach to mitigate membrane fouling. In this work, we demonstrate the antiscalant properties of a MoS2-carbon quantum dot (CDs@MS-NF) composite with a nanoflower-like structure coating for suppressing calcite scale formation. The CDs@ MS-NF coating was synthesized via a solvothermal method and applied to a polyamide reverse osmosis membrane surface using an in-situ growth technique. Characterization revealed uniform coverage of MoS2 nanosheets decorated with CDs@MS-NF on the membrane surface. Static fouling tests simulating calcium sulfate scaling conditions were conducted to evaluate the antifouling performance. The CDs@MS-NF coated membrane exhibited a flux reduction of only 11 %, compared to 34 % for the unmodified membrane after 24 hours. Further analyses showed a calcite nucleation induction time of 5.2 hours and a critical scaling threshold of 1.8 times the solubility for the CDs@ MS-NF coated membrane, indicating significant inhibition of scale formation. We hypothesize that the CDs@ MS-NF nanocomposite layer alters surface charge and wettability while also catalyzing redox reactions to hinder calcite crystal growth. This work demonstrates that multifunctional two-dimensional nanocomposite coatings can effectively mitigate membrane scaling through multiple synergistic mechanisms.

Composite fault feature extraction for gears based on MCKD-EWT adaptive wavelet threshold noise reduction

For the strong noise gear fault vibration signal is relatively weak, and the transmission path is complex and variable, in the case of composite faults, the modulation of different fault characteristics of the frequency, coupling, resulting in the actual acquisition of the fault characteristics are difficult to extract and separate. Aiming at fault feature extraction and separation, an adaptive threshold denoising fault detection method based on Maximum correlated kurtosis deconvolution (MCKD) and Empirical wavelet transform (EWT) is proposed. Firstly, envelope entropy and information entropy are used as fitness functions, and the parameters of the MCKD algorithm are optimized by the improved particle swarm algorithm, then the empirical wavelet decomposition is carried out on the signals, and finally adaptive wavelet threshold denoising is carried out on the decomposed Intrinsic mode functions (IMFs) components. The results of experimental data analysis show that compared with the feature extraction methods such as spatial scale threshold EWT-MCKD and Complete Ensemble Empirical Mode Decomposition (CEEMDAN)-MCKD, the proposed method is more suitable for the diagnosis of gear composite faults in a strong background noise environment, the noise interference is effectively suppressed, and the extraction effect of gear composite fault features is more obvious.

Outlier Detection by Energy Minimization in Quantized Residual Preference Space for Geometric Model Fitting

Outliers significantly impact the accuracy of geometric model fitting. Previous approaches to handling outliers have involved threshold selection and scale estimation. However, many scale estimators assume that the inlier distribution follows a Gaussian model, which often does not accurately represent cases in geometric model fitting. Outliers, defined as points with large residuals to all true models, exhibit similar characteristics to high values in quantized residual preferences, thus causing outliers to cluster away from inliers in quantized residual preference space. In this paper, we leverage this consensus among outliers in quantized residual preference space by extending energy minimization to combine model error and spatial smoothness for outlier detection. The outlier detection process based on energy minimization follows an alternate sampling and labeling framework. Subsequently, an ordinary energy minimization method is employed to optimize inlier labels, thereby following the alternate sampling and labeling framework. Experimental results demonstrate that the energy minimization-based outlier detection method effectively identifies most outliers in the data. Additionally, the proposed energy minimization-based inlier segmentation accurately segments inliers into different models. Overall, the performance of the proposed method surpasses that of most state-of-the-art methods.

Olfactory Function and Surgery of the Lateral Nasal Wall - Systematic Review.

This study aimed to comprehend the influence of surgery on the lateral nasal wall, primarily focusing on the inferior turbinates, and its impact on olfactory function. A systematic review was carried out utilizing electronic databases like PubMed, Cochrane (including various registers and databases), and Web of Science. No restrictions were imposed on publication year or language. The PRISMA criteria guided study selection, and predefined inclusion and exclusion criteria were employed. Risk of bias assessment for randomized controlled trials (RCTs) utilized the "Revised Cochrane risk-of-bias tool for randomized trials (RoB 2)," while Hawker et al. scale evaluated the quality of non-RCT studies. The review encompassed nine studies after rigorous selection and bias assessment. All studies unanimously demonstrated improved olfactory function following surgery on the inferior turbinate. Different surgical techniques and olfactory assessment methods were employed across studies. Evaluation encompassed pre- and post-surgery olfactory measurements. Most studies employed the Visual Analogue Scale (VAS) and commercial smell test kits (like Sniffin' Stick Test). The Nasal Obstruction Symptom Evaluation (NOSE) scale was used in two studies, and the butanol threshold test in one. Olfactory improvement was measured through enhanced patient numbers or nasal cavities, often expressed via VAS scores. One study utilized both patient count and VAS scores. A few studies also employed NOSE scale and olfactory threshold measurements. All studies consistently concluded that olfactory function post-surgery was superior to preoperative measures. The collective evidence strongly suggests that surgery on inferior turbinates has a positive impact on olfactory function, as indicated by the studies reviewed. Nonetheless, for a comprehensive understanding of surgical efficacy, future research should incorporate randomized controlled trials featuring control groups. This would facilitate the establishment of optimal surgical techniques for specific indications and the formulation of practical guidelines.

Reliability analysis of urban road traffic network under targeted attack strategies considering traffic congestion diffusion

The cascading failures caused by traffic congestion diffusion may deteriorate traffic network reliability. Comprehending urban traffic congestion mechanisms is essential for road network planning and traffic management against cascading failures. To uncover this, the reliability of urban road traffic network (URTN) under cascading failure considering different attack strategies is analyzed. The cascading failure model is established based on the improved nonlinear load-capacity relationship. Five kinds of attack strategies including Strength Attack (SA), Betweenness Centrality Attack (BCA), Eigenvector Centrality Attack (ECA), Closeness Centrality Attack (CCA), and Random Attack (RA) are selected. In particular, the capacity affected by traffic congestion is considered, providing a new perspective for the study of traffic congestion diffusion. A state update equation for networks is proposed to simulate the network congestion diffusion. Finally, a case study is conducted by using the URTN of Shanghai as the background. The results show that the network will experience large-scale congestion when high-importance nodes are attacked. The congestion degree is the highest under CCA strategy, network efficiency is the lowest under ECA strategy, and traffic quality is the poorest under CCA strategy. As the congestion critical failure threshold decreases, the speed and scale of cascading failures caused by traffic congestion diffusion are greater. Maintaining proper traffic management and control capability can largely reduce the cascading effect to a great extent and improve the reliability of the network. The results can provide a research basis for traffic management to improve network reliability.