Intrinsic Complexity Research Articles

Clinical features and mutation analysis of class 1/2/3 BRAF mutation colorectal cancer.

BRAF (B-Raf proto-oncogene, serine/threonine kinase)-mutated colorectal cancer (CRC) still has poor prognostic. The efficacy of BRAF inhibitor is unpredictable just that intrinsic genetic complexity, immune microenvironment and partially unknown reason. Understanding the co-mutation mechanism can help improve treatment and follow-up strategies. We retrospectively analyzed 35 (BRAF-mutated/BRAF wild-type) Chinese CRC and 125 Western CRC who underwent next-generation sequencing (NGS). Co-occurrence mutation analysis, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was enabled in this study. Thirty-five (10.32%) patients were BRAF-mutated, with 17 patients were BRAF V600E in Beijing Hospital. Patients with BRAF mutation had significant association with high tumor mutational burden (TMB-H) (P=0.0004) and high microsatellite instability (MSI-H) (P=0.0003) than those with BRAF wild-type. In 125 BRAF-mutated Western CRC patients, the frequency of age at diagnosis, gender, sample type, Tumor-Node-Metastasis (TNM), MSI, TMB, and BRAF mutation type was consistent with Chinese data. However, the primary tumor location showed significant statistical differences (P<0.0001). Class 1 were more likely to occur in elder and female. Western cohort was consistent with above in Chinese cohort. Other clinicopathological features were not significantly associated with mutation type. However, Western cohort showed class 1 exhibited primary sample type predominance in both class 1 vs. others (P<0.05) and class 1 vs. class 3 (P<0.05). Meanwhile, the data showed TMB-H (57.69% vs. 11.76%, P<0.001) and MSI-H (28.21% vs. 0%, P<0.05) of the class 1 BRAF mutation proportion were significantly higher, compared with class 3 BRAF mutation. In concurrent oncogenic mutations, compared with non-class 1 BRAF mutation, class 1 are more likely to co-occur with passenger mutation. Data from Western populations showed similar results. We also found that the class 1 mutation was mutually exclusive with co-KRAS (Kirsten rat sarcoma viral oncogene homologue) mutation in CRC, and co-APC (APC regulator of WNT signaling pathway) mutation appeared more frequently in non-class 1 BRAF mutation. KEGG pathway showed that fewer proto-cancer signaling pathways were enriched in the class 1, which further confirmed that this type had stronger tumorigenicity. GO enrichment also proved that class 1 had stronger tumorigenicity. Finally, prognostic analysis showed median overall survival (mOS) of 19.43 months in class 1 vs. 47.57 months in non-class 1 (P=0.0002). Further study showed that the mOS of class 1, class 2, class 3 and class NA (unknown) was 19.43, 28.50, 47.57 months and not reached (P=0.0001), respectively. This study showed class 1/non-class 1 BRAF mutation in CRC had significantly differences in co-mutation features, genomic markers and prognostic. Understanding BRAF mutation types and co-mutation mechanism will contribute to accurately grasping treatment and follow-up strategies and promoting the development of precision therapy for CRC in the future.

A constitutive model for transversely isotropic dispersive materials

Due to their intrinsic complexity, it is not easy to model the mechanical behaviour of biomaterials. Despite the challenges they faced, some researchers have presented mathematical models to describe some aspects of the mechanical response of soft tissues. Since most of the materials of biological interest are composites made of different constituents reinforced by collagen and/or elastin fibres, material dispersion and anisotropy are non-negligible. Within the theory of elasticity, several models for anisotropic materials have been developed. The same cannot be said for anisotropic dispersive materials. The models available in the literature that account for material dispersion are valid only for isotropic materials. This paper aims at introducing a very general model for anisotropic dispersion in transversely isotropic bodies within the theory of simple materials of differential type. Our model has the potential to represent a first step towards a better understanding of the mechanical response of fibre-reinforced soft materials.

Information Technology and the Complexity Cycle

Aim/Purpose: In this paper we propose a framework identifying many of the unintended consequences of information technology and posit that the increased complexity brought about by IT is a proximate cause for these negative effects. Background: Builds upon the three-world model that has been evolving within the informing science transdiscipline. Methodology: We separate complexity into three categories: experienced complexity, intrinsic complexity, and extrinsic complexity. With the complexity cycle in mind, we consider how increasing complexity of all three forms can lead to unintended consequences at the individual, task and system levels. Examples of these consequences are discussed at the individual level (e.g., deskilling, barriers to advancement), the task level (e.g., perpetuation of past practices), as well as broader consequences that may result from the need to function in an environment that is more extrinsically complex (e.g., erosion of predictable causality, shortened time horizons, inequality, tribalism). We conclude by reflecting on the implications of attempting to manage or limit increases of complexity. Contribution: Shows how many unintended consequences of IT could be attributed to growing complexity. Findings: We find that these three forms of complexity feed into one another resulting in a positive feedback loop that we term the Complexity Cycle. As examples, we analyze ChatGPT, blockchain and quantum computing, through the lens of the complexity cycle, speculating how experienced complexity can lead to greater intrinsic complexity in task performance through the incorporation of IT which, in turn, increases the extrinsic complexity of the economic/technological environment. Recommendations for Practitioners: Consider treating increasing task complexity as an externality that should be considered as new systems are developed and deployed. Recommendation for Researchers: Provides opportunities for empirical investigation of the proposed model. Impact on Society: Systemic risks of complexity are proposed along with some proposals regarding how they might be addressed. Future Research: Empirical investigation of the proposed model and the degree to which cognitive changes created by the proposed complexity cycle are necessarily problematic.

The Three Worlds of Task Complexity

Aim/Purpose: To provide a systematic approach to defining task complexity using a three worlds model previously introduced in informing science research. Background: The task complexity construct presents researchers with a quandary. While it appears useful on the surface, repeated attempts to define it rigorously have failed to gain traction in the broader research community. The level of inconsistency between definitions is shown to have changed little in the past 20 years. Methodology: Using a common framework that treats task complexity as a latent construct residing between sources and outcomes, moderated by both task familiarity and task discretion, separate models for each of the three worlds are developed. Contribution: Our paper proposes a potential path forward by showing how many issues in past task complexity research can be reconciled by framing the construct according to the three worlds model: the world we experience, the world of human artifacts, and the “real world.” Findings: The framework defines experienced complexity as occurring in the mind of the task performer while performing a single task instance, intrinsic complexity as a function of the internal characteristics of the problem space used to perform a bounded set of task instances, and extrinsic complexity as the ruggedness of the fitness landscape in which the task is performed. Recommendation for Researchers: It offers a path to convergence for definitions of task complexity. Future Research: The three worlds of task complexity can potentially be applied to many practical problems.

Multitask connected U-Net: automatic lung cancer segmentation from CT images using PET knowledge guidance.

Lung cancer is a predominant cause of cancer-related mortality worldwide, necessitating precise tumor segmentation of medical images for accurate diagnosis and treatment. However, the intrinsic complexity and variability of tumor morphology pose substantial challenges to segmentation tasks. To address this issue, we propose a multitask connected U-Net model with a teacher-student framework to enhance the effectiveness of lung tumor segmentation. The proposed model and framework integrate PET knowledge into the segmentation process, leveraging complementary information from both CT and PET modalities to improve segmentation performance. Additionally, we implemented a tumor area detection method to enhance tumor segmentation performance. In extensive experiments on four datasets, the average Dice coefficient of 0.56, obtained using our model, surpassed those of existing methods such as Segformer (0.51), Transformer (0.50), and UctransNet (0.43). These findings validate the efficacy of the proposed method in lung tumor segmentation tasks.

Intrinsic Complexity: Quantifying Task Complexity for Deep Learning-Based City-wide Traffic Prediction

Intrinsic Complexity: Quantifying Task Complexity for Deep Learning-Based City-wide Traffic Prediction

What can quantum information theory offer to quantum chemistry?

It is the ultimate goal of this work to foster synergy between quantum chemistry and the flourishing field of quantum information theory. For this, we first translate quantum information concepts, such as entanglement and correlation, into the context of quantum chemical systems. In particular, we establish two conceptually distinct perspectives on 'electron correlation', leading to a notion of orbital and particle correlation. We then demonstrate that particle correlation equals total orbital correlation minimized over all orbital bases. Accordingly, particle correlation resembles the minimal, thus intrinsic, complexity of many-electron wave functions, while orbital correlation quantifies their complexity relative to a basis. We illustrate these concepts of intrinsic and extrinsic correlation complexity in molecular systems, which also manifests the crucial link between the two correlation pictures. Our results provide theoretical justification for the long-favored natural orbitals for simplifying electronic structures, and open new pathways for developing more efficient approaches towards the electron correlation problem.

Gasless endoscopic transaxillary subcutaneous mastectomy and immediate reconstruction with implants (GETSMIRI) for breast cancer: Lei's five-step method

BackgroundEndoscopic nipple-sparing mastectomy (E-NSM) is a promising procedure in the treatment of breast cancer, but the limitations of endoscopic tools and intrinsic technical complexity of the technique hinder its applicability. Here, we introduce a novel surgery, gasless endoscopic transaxillary subcutaneous mastectomy and immediate reconstruction with implants (GETSMIRI), for breast cancer. and early effects. MethodsA retrospective analysis of the clinical data of 11 female patients, aged 50 (27–78) years, admitted to our hospital from January to December 2022, who underwent gasless endoscopic transaxillary subcutaneous mastectomy and immediate reconstruction with implants (GETSMIRI), was conducted. This study was designed to assess patient satisfaction before and after breast reconstruction, early complications, and breast function. ResultsThe tumors were all solitary, with a mean maximum diameter of 1.0 (0–2.0) cm and a mean distance of 2.3 (2–4) cm from the nipple, the mean intraoperative bleeding volume was 47.5 mL, and the mean hospital stay was 1.5 d. Postoperatively, 1 patient developed depigmentation of the nipple due to mild ischemia. There were no incisional complications, subcutaneous emphysema, infection, areola necrosis, skin flap necrosis, or removal of the prosthesis and/or patch. No tumor recurrence or metastasis was observed during the follow-up period. The difference between breast satisfaction and psychosocial health scores was not statistically significant (P = 0.680; P = 0.612). ConclusionGETSMIRI, immediate implantable breast reconstruction, is less invasive than other such procedures, and short-term follow-up results show good postoperative satisfaction, making it an alternative surgical method.

A standardized approach to identify nonlinearity in fighter jet noise during ground run-ups

High-intensity military sources (explosions, gunfire, fighter jet noise. . . ) fall out of the scope of linearity-based commercial software and international standards. On top of its intrinsic complexity (high temperature supersonic jet, shocks, turbulent eddies, etc), fighter jet engine noise bears additional challenges: turbulent surrounding flow, airframe interference, directionality and tonal components typical of rotating equipment. The absence of a suitable metric to determine the boundary of the nonlinear propagation region can lead to costly mispredictions in the exposure levels for noise abatement procedures and the personnel's safety. The derivative skewness of the time domain signal used as an indicator of spectral reshaping proved effective in setting a threshold to the generation of acoustic nonlinearity for seven firearms. Its application to aircraft noise is here discussed, in order to verify the claim of persistence of nonlinear behaviour at large distances and set the foundations for a common framework contemplating the peculiarities of each military noise source. The experimental data was collected during a series of static ground run-ups of an F-16 military jet aircraft. The results from five engine regimes and two propagation paths are compared with the findings from firearms, existing literature and the solution of a nonlinear acoustic propagation solver.

Coupling of Dye Analysis and Compound Specific Radiocarbon (14C) Analysis (CSRA) in Heritage Sciences

Natural organic dyes and pigments have been used for millennia to bring colour into our daily lives. Being sourced from a variety of natural sources, they form an extremely varied and large class of compounds, all of which retain the atmospheric 14CO2 of their year of growth. As such these compounds represent ideal candidates for radiocarbon (14C) dating, allowing the identification of or providing information towards the period in which the coloured artefact was created. However, up to now no such analysis has ever been conducted solely on organic colourants within an object. The complex nature of the samples and the sample size limitations with respect to precious and rare art artefacts requires innovative inter- and multidisciplinary approaches. Here we discuss preliminary results in the development of a compound-specific radiocarbon analysis (CSRA) methodology for the analysis of anthraquinone derived red dyes extracted from dyed wool yarns. The aim of this research project is to introduce new routes to date cultural heritage objects, in particular to overcome their intrinsic complexity through the development of CSRA strategies.

Exploring high-throughput synchrotron X-Ray powder diffraction for the structural analysis of pharmaceuticals

Synchrotron radiation offers a host of advanced properties, surpassing conventional laboratory sources with its high brightness, tunable phonon energy, photon beam coherence for advanced X-ray imaging, and a structured time profile, ideal for capturing dynamic atomic and molecular processes. However, these benefits come at the cost of operational complexity and expenses. Three decades ago, synchrotron radiation facilities, while technically open to all scientists, primarily served a limited community. Despite substantial accessibility improvements over the past two decades, synchrotron measurements still do not qualify as routine analyses. The intrinsic complexity of synchrotron science means experiments are pursued only when no alternatives suffice. In recent years, strides have been made in technology transfer offices, intermediate synchrotron-based analytical service companies, and the development of high-throughput synchrotron systems at various facilities, reshaping the perception of synchrotron science. This article investigates the practical application of synchrotron X-Ray Powder Diffraction (s-XRPD) techniques in pharmaceutical analysis. By utilizing concrete examples, we demonstrate how high-throughput systems have the potential to revolutionize s-XRPD applications in the pharmaceutical industry, rapidly generating XRPD patterns of comparable or superior quality to those obtained in state-of-the-art laboratory XRPD, all in less than 5 s. Additional cases featuring well-established pharmaceutical active ingredients (API) and excipients substantiate the concept of high throughput in pharmaceuticals, affirming data quality through structural refinements aligned with literature-derived unit cell parameters. Synchrotron data need not always be state-of-the-art to compete with lab-XRPD data. The key lies in ensuring user-friendliness, reproducibility, accessibility, cost-effectiveness, and the streamlined efforts associated with synchrotron instrumentation to remain highly competitive with their laboratory counterparts.

Roton-like dispersion via polarisation change for elastic wave energy control in graded delay-lines

While roton dispersion relations had been restricted to correlated quantum systems at low temperature, recent works show the possibility of obtaining this unusual dispersion in acoustic and elastic metamaterials. Such phenomenon has been demonstrated in periodic structures by means of beyond-nearest-neighbour interactions, following the formulation firstly developed by Brillouin in the ′50s. In this paper, we demonstrate both numerically and experimentally that beyond-nearest-neighbour connections are not a necessary condition to obtain this unusual dispersion relation in elasticity. Leveraging the intrinsic complexity of elastic systems supporting different types of waves, we demonstrate that mode locking can be applied to obtain roton dispersion, without the need of elastic or magnetic interactions between non nearest neighbours. Moreover, the combination of roton dispersion and rainbow physics enables spatial separation of the energy fluxes with positive and negative group velocity.

Efficacy of a lifestyle intervention for elderly in long-term care: a randomized controlled trial

Abstract Background Long term care (LTC) services represent an important element of worldwide health systems, providing medical care and social services to thousands of elderlies. In this setting inadequate food consumption and lack of physical exercise represent major causes of mortality and morbidity due to malnutrition, sarcopenia, osteoporosis, and dehydration. While it has been acknowledged that these conditions are potentially reversible with proper lifestyle medicine interventions, the latter are rarely implemented and evaluated in LTC owing to their intrinsic complexity. Methods A randomized controlled trial was conducted to assess the effectiveness of a three-months combined food-physical exercise lifestyle intervention in elderlies living in an Italian LTC facility. The diet was designed to provide high levels of energy, proteins, leucine, and calcium. The physical exercise treatment was delivered two times per week, with a moderate to high effort requested to subjects. At baseline and at the end of the intervention subjects were evaluated using the Barthel Index, Activities of Daily Living, and Tinetti scales. Results 54 participants took part to the trial. At the end of the study the intervention group showed a significant improvement in all the scales. They burned 287 Kcal/week, significantly more than the control group. In contrast to the study protocol, they introduced 11% less calories than the control group. Conclusions This intervention has been proved effective in increasing functionality, with the beneficial effect that might be primarily attributed to the physical exercise, considering the low adherence to diet in the intervention group. This evidence supports the hypothesis that these interventions, despite the effectiveness, are complex to be powerfully implemented. While our results encourage the efficacy of lifestyle interventions in LTC, more studies are needed to deeply understand barriers and facilitators for an effective implementation. Key messages • This lifestyle intervention proved effective in improving functionality in institutionalized elderlies. • The low adherence to diet highlights challenges and complexities of lifestyle interventions in LTC.

Adaptive optimal secure wind power generation control for variable speed wind turbine systems via reinforcement learning

As the utilization of wind energy continues to grow, it is crucial to prioritize the identification of vulnerabilities, raise awareness, and develop strategies for cybersecurity defense. False data injection (FDI) attacks, if targeted at the communication between the rotor speed sensor and the wind turbine (WT) controller, can potentially disrupt the normal operation of the system. These attacks have the capability to overload the drive-train and significantly reduce the power generation efficiency of the wind turbine. So, this note presents an adaptive optimal secure control strategy entailing reinforcement learning (RL) neural network (NN) using the filter error to compensate the detrimental effects of FDI attack as well as actuator fault for WT systems. The Hamilton–Jacobi–Bellman (HJB) equation is constructed and solved to obtain the optimal control policy. Since the HJB is inextricably intertwined with intrinsic nonlinearity and complexity, solving this equation is quiet challenging. To tackle this issue and also approximate the solution of the HJB, an actor–critic-based reinforcement learning (RL) strategy is used, in which actor and critic NNs are applied to execute control action and assess control performance, respectively. To detect FDI attack, an anomaly detection is developed using a nonlinear observer/estimator. Stability analysis is performed using Lyapunov theory which guarantees semi-global uniformly ultimately bounded (SGUUB) of the error signal. Finally, simulation results verify the effectiveness of the proposed control approach.

Time domain diffuse Raman spectroscopy using single pixel detection.

Diffuse Raman spectroscopy (DIRS) extends the high chemical specificity of Raman scattering to in-depth investigation of thick biological tissues. We present here a novel approach for time-domain diffuse Raman spectroscopy (TD-DIRS) based on a single-pixel detector and a digital micromirror device (DMD) within an imaging spectrometer for wavelength encoding. This overcomes the intrinsic complexity and high cost of detection arrays with ps-resolving time capability. Unlike spatially offset Raman spectroscopy (SORS) or frequency offset Raman spectroscopy (FORS), TD-DIRS exploits the time-of-flight distribution of photons to probe the depth of the Raman signal at a single wavelength with a single source-detector separation. We validated the system using a bilayer tissue-bone mimicking phantom composed of a 1 cm thick slab of silicone overlaying a calcium carbonate specimen and demonstrated a high differentiation of the two Raman signals. We reconstructed the Raman spectra of the two layers, offering the potential for improved and quantitative material analysis. Using a bilayer phantom made of porcine muscle and calcium carbonate, we proved that our system can retrieve Raman peaks even in the presence of autofluorescence typical of biomedical tissues. Overall, our novel TD-DIRS setup proposes a cost-effective and high-performance approach for in-depth Raman spectroscopy in diffusive media.

Chemo-mechanical forces modulate the topology dynamics of mesoscale DNA assemblies

The intrinsic complexity of many mesoscale (10–100 nm) cellular machineries makes it challenging to elucidate their topological arrangement and transition dynamics. Here, we exploit DNA origami nanospring as a model system to demonstrate that tens of piconewton linear force can modulate higher-order conformation dynamics of mesoscale molecular assemblies. By switching between two chemical structures (i.e., duplex and tetraplex DNA) in the junctions of adjacent origami modules, the corresponding stretching or compressing chemo-mechanical stress reversibly flips the backbone orientations of the DNA nanosprings. Both coarse-grained molecular dynamics simulations and atomic force microscopy measurements reveal that such a backbone conformational switch does not alter the right-handed chirality of the nanospring helix. This result suggests that mesoscale helical handedness may be governed by the torque, rather than the achiral orientation, of nanospring backbones. It offers a topology-based caging/uncaging concept to present chemicals in response to environmental cues in solution.

Treating disorder in introductory solid state physics

Introductory textbooks in solid state physics present solvable models for illustrating the occurrence of allowed bands and forbidden gaps in the energy spectrum of Bloch electrons. However, the quantum mechanical description of electrons in non-periodic solids, such as amorphous materials, is beyond the scope of introductory courses because of its intrinsic complexity. The tight-binding approximation can account for such a scenario by letting the atomic levels vary at random from lattice site to site. We theoretically tackle the study of the average properties of the energy spectrum by introducing a transfer matrix method that allows us to obtain closed expressions for the so-called coherent potential. The coherent potential is energy-dependent and constant in space. It replaces the actual atomic random potential, thus generating a periodic effective medium with the same average properties as the non-periodic solid. We demonstrate that the average density of states can be calculated within this framework without relying on heavy mathematical machinery. Thus, our approach is suitable for introductory courses in solid state physics and materials science.

PIXEL: Challenges of Designing a Professional Board Game for Astronomy Education

PIXEL - Picture (of) the Universe is a board game developed by INAF - Italian National Institute for Astrophysics in collaboration with GAME Science Research Center. The game simulates the astrophysics research environment, particularly emphasising the observation and study of cosmic bodies at different resolutions. ​​Image resolution is a crucial element in astrophysics, but the intrinsic complexity and challenges of making high-resolution images of the distant Universe are not easily and generally perceivable. We envisioned PIXEL driven by this challenge. Games intended to engage students with science either concentrate on the contents to foster the learning process or focus on life skills solicited by scientific practices. Game mechanics are then either a leverage of scientific knowledge or a science-like behavioural model, depending on the expected outcome of the game-based learning process. In addition to that, game-based learning in STEM (Science, Technology, Engineering, Mathematics) generally is designed by science practitioners and science communication and education experts. The design process of PIXEL has been a novel joint effort between scientists, science communicators, professional game designers, and game-market and award advisors. We produced a game in which the mechanics are the core of scientific learning, implicitly telling about science while making the player experience it. The innovation of this process is to obtain a game that encountered positive feedback both from the community of game experts and the educational context. The final output is a professional board game suitable for STEM education that promotes scientific citizenship in the audience.In this work, we discuss the game design process and describe how we included our scientific educational messages of image resolution and research dynamics as processes within the game mechanics without making them explicit during the gameplay. We also present a preliminary engagement evaluation of PIXEL and its efficacy in delivering implicit scientific messages through its mechanics.

Comparative Dosimetry for Hippocampal-Avoidant Whole Brain Radiotherapy with Helical Tomotherapy and VMAT Planning Techniques

The advent of hippocampal-avoidant whole brain radiotherapy (HA-WBRT) has allowed for substantial improvements in cognition without compromising the efficacy of palliative whole brain radiotherapy. Volumetric modulated arc therapy (VMAT), a form of rotational intensity-modulated radiation therapy (IMRT), allows for rapid treatment delivery and minimizes fractional treatment time. However, given the intrinsic complexity of HA-WBRT planning, standard VMAT techniques require significant departmental resources and often fail to achieve planning objectives. We hypothesize that treatment planning and delivery on a helical tomotherapy (HT) unit improves OAR dosimetry compared to standard VMAT techniques. Patients with multiple brain metastases who received WBRT with palliative intent were included in this single institution dosimetric study. Treatment objectives and dose constraints for HA-WBRT from NRG CC001 were utilized. Three separate plans were generated for each patient including Dual-Arc Conventional VMAT (DAC), Split-Arc Partial-Field VMAT (SAPF), and HT for dosimetric comparison. VMAT plans were generated using 6-MV photon beams with a maximum dose rate of 600 MU/min with a 120-leaf MLC. DAC plans utilized 2 coplanar arcs each with jaw tracking. SAPF plans used four partial arcs, and the field size of each beam was reduced to allow the MLC to block the centrally located hippocampus without sacrificing the whole brain PTV coverage. HT plans with a dose rate of 1000MU/min and Helical Delivery mode used a 2.5cm dynamic Jaw setting. Mean differences in target volume coverage and OAR dosimetry between planning approaches were calculated. Two-tailed, paired Student's t-tests were employed to determine statistically significant differences between DAC, SAPF, and HT plans. A total of 15 treatment plans were generated for five patients (5 DAC, 5 SAPF, and 5 HT plans). HT was seen to significantly reduce hippocampal D100% compared to both DAC (∆-114.16 cGy, p = 0.001) and SAPF (∆-125.76 cGy, p < 0.001). Moreover, HT hippocampal D0.03cc was significantly lower than DAC (∆-80.26 cGy p = 0.003) and SAPF (∆-174.40 cGy, p < 0.001). At the same time, PTV coverage as determined by D98% was significantly higher compared to both DAC (∆ +372.66 cGy, p = <0.001) and SAPF (∆ +304 cGy, p = <0.001). Compared to both DAC and SAPF, HT planning for HA-WBRT provides significant improvements in target coverage and OAR sparing. Additional research is warranted to determine whether further reductions in dose to the hippocampi provide additional clinical benefit.

Flow-Data-Based Global Spatial Autocorrelation Measurements for Evaluating Spatial Interactions

Spatial autocorrelation analysis is essential for understanding the distribution patterns of spatial flow data. Existing methods focus mainly on the origins and destinations of flow units and the relationships between them. These methods measure the autocorrelation of gravity or the positional and directional autocorrelations of flow units that are treated as objects. However, the intrinsic complexity of actual flow data necessitates the consideration of not only gravity, positional, and directional autocorrelations but also the autocorrelations of the variables of interest. This study proposes a global spatial autocorrelation method to measure the variables of interest of flow data. This method mainly consists of three steps. First, the proximity constraints of the origin and destination of a flow unit are defined to ensure similarity of flow units in terms of direction, distance, and position. This undertaking aims to determine the neighborhood of flow units and generate their adjacent matrices. Second, a spatial autocorrelation measurement model for flow data is constructed on the basis of the adjacent matrix generated. Artificial data sets are also employed to test the validity of the model. Finally, the proposed method is applied to the flow data analysis of population migration in central and eastern China to prove the practical application value of the model. The proposed method is universal and can be generalized to the global spatial autocorrelation analysis of any type of flow data.