Time Usage Research Articles

Investigation of Secondary School Students’ Social-Emotional Learning and Friendship-Making Skills in Terms of Various Variables

Social and emotional development is the child’s ability to express himself, establish relationships, recognize himself, adapt to his social environment, and restrain his emotions. Because of this situation, developing children’s social and emotional learning skills is important in increasing their academic success, improving their friendship-making skills in the social environment, developing positive peer relationships, and improving the relationships established in the family environment. This research also aims to examine the social-emotional learning abilities of secondary school students, their friendship making skills with age, gender, classroom, daily phone and computer usage time, and their ability to use digital technologies variables. A sampling of this research’s universe (n = 415) and sample (n = 380) were students studying in seventh and eighth grades at secondary schools in the Kartal district of Istanbul. In this research using the correlational survey model, the data was analyzed in three stages. İt has been determined with a descriptive relational/related model found that social and emotional learning levels increased and that male students had higher social-emotional and relationship-making skills than female students; less daily phone use was higher than students with high social-emotional and friendship-making skills. Finally, secondary school students are becoming more and more able to relate as the level of social-emotional learning increases. Research improving the status of students at a disadvantage in social and emotional learning in this regard will offer positive contributions to developing their relationship skills.

Design and deployment of a novel decisive algorithm to enable real-time optimal load scheduling within an intelligent smart energy management system based on IoT

Consumers routinely use electrical devices, leading to a disparity between consumer demand and the supply side a significant concern for the energy sector. Implementing demand-side energy management can enhance energy efficiency and mitigate substantial supply-side shortages. Current energy management practices focus on reducing power consumption during peak hours, enabling a decrease in overall electricity costs without sacrificing usage. To tackle the mentioned challenges and maintain system equilibrium, it is essential to develop a flexible and portable system. Introducing an intelligent energy management system could pre-empt power outages by implementing controlled partial load shedding based on consumer preferences. During a demand response event, the system adapts by imposing a maximum demand limit, considering various scenarios and adjusting appliance priorities. Experimental work, incorporating user comfort levels, sensor data, and usage times, is conducted using Smart Energy Management Systems (SEMS) integrated with cost-optimization algorithms.

LRPS‐GCN: A millimeter wave sparse imaging algorithm based on graph signal

AbstractAiming at the problems of slow speed and poor accuracy of traditional millimeter wave sparse imaging, a sparse imaging algorithm based on graph convolution model is proposed from the perspective of sparse signal recovery. The graph signal model is constructed by combining the low‐rank and piecewise smoothing(LRPS) regular terms, based on which the proximal operator is replaced by the denoising graph convolution network, and the graph convolution sparse reconstruction network LRPS‐GCN is constructed, and the recovered target image is obtained by iterating with the optimal non‐linear sparse variation. For the proposed algorithm, simulation experiments are carried out using synthetic datasets under different target densities, iteration times and noise environments, and compared with the traditional graph signal reconstruction algorithm and the deep compressed sensing reconstruction algorithm, and then use the measured data with varying degrees of sparsity to validate. The experimental results show that the reconstructed images by this algorithm have better performance in terms of normalised mean square error, target to background ratio, reconstruction time and memory usage.

Advantage of foreignness in a digital world: role of long tail users

PurposeThis study aims to explore the advantage of foreignness in a digital world.Design/methodology/approachUsage data for 251 days of 32 travel mobile applications installed on a major mobile phone brand in China are examined. Results support the author’s arguments.FindingsForeign mobile apps enjoy higher daily usage time than local apps. Next, the author consider how foreign apps can maximize their advantage, that is, increase daily usage time. The author argue that a multinational enterprise (MNE) can digitally enter a country that has numerous immigrants from its home country because of the high number of potential long tail users. A high level of diversity of international experience of MNEs increases the ability to understand and satisfy the specific needs of long tail users, thereby increasing daily usage time of foreign mobile apps. To maximize the advantage of foreignness in a digital world, MNEs can also carefully select business models that do not heavily rely on network effect, given the difficulty of generating network effect by long tail users.Originality/valuePrevious studies focus on the liability of foreignness or outsidership that MNEs encounter in the digital world, whereas this study argues that foreignness brings certain benefits, such as the capability to satisfy the specific needs of long tail users.

Network consumption and sports practice: influence on the risk of network addiction and basic psychological needs

The objective of the study was to identify the possibility of developing a risk of addiction to social networks and to know the satisfaction of basic psychological needs depending on network usage time, the number of networks used, and the practice hours and type of sport developed. A sample of 265 university students (Mage = 28.23; SD = 8.44; 110 men and 155 women) completed distinct self-report measures. Results revealed significant differences in the addiction-symptoms, social-use and geek-traits, being higher when the time of network consumption increases and when the number of networks used is bigger. Regarding the sports variables, collective sports are significantly associated with the risk of addiction symptoms. However, the practice of collective sports seems to satisfy basic psychological needs. In conclusion, the higher use and number of social networks seem to predict the risk of addiction to them. Single sports practice decreases the probability of network addiction and, collective and single sports help satisfy basic psychological needs.

Seraph: Towards secure and efficient multi-controller authentication with [formula omitted]-threshold signature in multi-domain SDWAN

The multi-controller scheme is widely adopted in Software-Defined Wide Area Networks (SDWANs), where a WAN is segmented into multiple domains, each controlled by one controller. These controllers communicate with each other in-band, necessitating authentication before exchanging control messages. However, relying solely on identification of a single node for authentication exposes the network to spoofing attacks, jeopardizing its security. To address this issue, we present Seraph, an innovative (t,n)-threshold signature-based authentication scheme that verifies not only the node itself but also its “endorsement” nodes to establish its identity. We have investigated the best practice for defining the “endorsement” relationships concerning security and overheads, formulating the problem as an integer programming problem. We have demonstrated the polynomial-time hardness (NP-hardness) of the problem and proposed an efficient Seraph algorithm. Through our rigorous simulation analysis, we show that Seraph can provide comparative performance with Optimal and reduce time usage by over 90%.

MethParquet: an R package for rapid and efficient DNA methylation association analysis adopting Apache Parquet.

Genome-wide DNA methylation (DNAm) profiling is indispensable for unveiling how DNAm regulates biological pathways and individual phenotypes. However, managing and analyzing extensive DNAm data generated from large cohort studies present computational obstacles. Apache Parquet is a data file format that allows for efficient data storage, retrieval, and manipulation, alleviating computational hurdles associated with conventional row-based formats. We here introduce MethParquet, the first R package leveraging the columnar Parquet format for efficient DNAm data analysis. It can be used for data extraction, methylation risk score calculation, epigenome-wide association analyses, and other standard post-quality control tasks. The package flexibly implements diverse regression models. Via a public methylation dataset, we show the efficiency of this package in reducing running time and RAM usage in large-scale EWAS. The MethParquet R package is publicly available on the GitHub repository https://github.com/ZWangTen/MethParquet. It includes a vignette and a toy dataset derived from a public resource.

Spontaneous erectile function recovery among young men with erectile dysfunction taking tadalafil 5mg once a day.

Daily (once a day [OaD]) tadalafil intake is a valuable option for men favoring spontaneous over scheduled sexual intercourse. The study sought to assess the rate of and the clinical factors associated with spontaneous, medication-free erectile function (EF) recovery after discontinuation of tadalafil 5mg OaD in a cohort of young men seeking first medical help for psychogenic erectile dysfunction (ED) as their primary complaint. Data from 96 consecutive patients <50years of age seeking first medical help for ED and prescribed tadalafil 5mg OaD were analyzed. Patients completed the International Index of Erectile Function (IIEF) and underwent baseline penile color Doppler ultrasound. Follow-up involved clinical assessments or phone interviews. Spontaneous medication-free EF recovery was defined as IIEF EF domain score >22 after tadalafil discontinuation, prompting cessation of follow-up. Descriptive statistics compared tadalafil OaD responders and nonresponders. Cox regression hazard models explored the association between baseline characteristics and EF recovery risk post-drug discontinuation. Kaplan-Meier analyses estimated EF recovery probability over time. The primary outcome was EF recovery after discontinuation of tadalafil 5mg OaD. Overall, median age was 39 (interquartile range [IQR], 32-45) years. Of all, 82 (85.4%) patients achieved EF recovery after tadalafil OaD discontinuation, while 14 (14.6%) patients were identified as nonresponders. Median tadalafil usage time (from beginning to discontinuation) was 3 (IQR, 2-11) months. The most common treatment-emergent adverse event was headache in 9 (9.4%) patients. Nonresponders were older (43 [IQR, 42-45] years vs 38 [IQR, 31-44] years; P = .03), had higher body mass index (25.5 [IQR, 23.4-29.9] kg/m2 vs 23.6 [IQR, 21.8-25.9] kg/m2; P = .04), and reported lower baseline IIEF EF domain scores (12 [IQR, 7-15] vs 15 [IQR, 10-22]; P = .02) than responders. Nonresponders and responders did not differ in terms of baseline ED severity, Charlson comorbidity index, smoking, alcohol consumption, regular physical exercise, and color Doppler ultrasound parameters. Upon Cox regression analysis, younger age (hazard ratio, 0.95; 95% confidence interval, 0.92-0.99; P = .01) was associated to EF recovery, after adjusting for baseline ED severity, body mass index, smoking, and Charlson comorbidity index ≥1. The Kaplan-Meier analysis displays the probability of EF recovery over time, indicating rates of 43%, 60%, and 72% at 3-, 6-, and 12-month follow-up intervals, respectively. Tadalafil 5mg OaD is an effective short-term treatment for psychogenic ED, allowing its discontinuation after achieving a normal medication-free EF. The main limitations are the limited number of participants and the potential neglect of confounding factors. Almost 1 out of 2 young men with primary psychogenic ED who were prescribed with tadalafil 5mg OaD recovered spontaneous medication-free EF after 3months of treatment. Overall, the younger the patient was, the higher the chance there was of spontaneous EF recovery after drug discontinuation.

METB-09. VARIANT WORKBENCH IN THE KIDS FIRST PROGRAM FACILITATES GENOMIC DISCOVERIES IN PEDIATRIC NEURO-ONCOLOGY RESEARCH

Abstract The Gabriella Miller Kids First Pediatric Research Program (Kids First) aims at facilitating researchers to uncover new insights into the biology of childhood cancer and structural birth defects, including the discovery of shared genetic pathways between these disorders. Kids First Data Resource Center developed the Kids First Data Resource Portal (KFDRP), which is a centralized data platform for both Kids First and collaborative cohorts. Currently, KFDRP facilitates data access for 40 studies with over 35,500 participants. To assist researchers and clinicians in identifying potential disease-causing germline variants in the human genome, KFDRP released the Variant WorkBench (VWB), which facilitates variant querying, manipulation, analysis, and visualization. Cavatica is a widely used bioinformatics analysis platform developed by Velsera. Compared to a previous version, the Cavatica-based VWB has better support for data import/export, more convenient sharing of notebooks and data, and easier billing details, with the same level of scalable, cloud-based computing. Additionally, Cavatica-based VWB has incorporated multiple public reference databases, including Cancer Hotspots, ClinVar, COSMIC, dbNSFP, gnomAD, TOPMed, as well as gene-phenotype links provided by OMIM, HPO, Orphanet, and the Deciphering Developmental Disorders Project. These databases have been converted to parquet files, reducing process time and memory usage compared to regular text files, thus speeding up data retrieval and querying. Furthermore, Cavatica empowers users to create and share custom analysis workflows tailored to specific research questions and datasets, enhancing data utility and analysis accuracy. Here we present a gene-based variant filtering workflow that aggregates information from dbNSFP, HGMD, TOPMed, gnomAD, and ClinVar. We identified 1202 pathogenic/likely pathogenic variants in NF1, a gene that helps regulate cell growth, across 582 pediatric brain tumor samples within 6 mins. Among the variants, there are 21 protein-altering variants. Overall, the upgraded VWB is more powerful, user-friendly, and adaptable.

Home quarantine duration and Chinese preschoolers’ sleep problems during COVID-19: child screen time as an explanatory mechanism and real interpersonal interactions in family setting as a contextualizing buffer

ABSTRACT Using data collected during the COVID-19 pandemic from 28,185 families with preschoolers living in Hubei, China, this study examined the relationship between home quarantine duration and preschoolers’ sleep problems. In particular, we tested the potential mediating role of child screen usage time and the potential moderating role of real interpersonal interactions in the family setting. Results indicated that home quarantine duration was positively associated with preschoolers’ sleep problems indirectly through both types of screen time. More importantly, a conditional indirect pathway was identified, such that home quarantine duration was linked with preschoolers’ more sleep problems through longer traditional screen time only when real interpersonal interactions were relatively low. These findings, reveal some potential intervention targets and avenues, such as setting limits on child screen time and enhancing more real family interpersonal interactions, to help parents of young children successfully navigate the challenges during home quarantine during the pandemic.

The development of patient-specific quality assurance (PSQA) for a proton wobbling nozzle using PTSim Monte Carlo code

The aim of this study is to develop a Monte Carlo-based platform for patient-specific quality assurance (PSQA) in the proton wobbling nozzle at Chang Gung Memorial Hospital. To efficiently reduce time usage and enhance simulated precision, this platform required an initial fine-tuning of the Guard volume (GV) and lateral displacement (LD) settings. Different GV sizes combined with LD modes were utilized to estimate depth dose profiles in a water phantom. The simulated central axis depth doses were then analyzed using PTSim and compared to measurement using a PTW MP3 water tank and a Markus ionization chamber type 34045. Treatment parameters for a liver case were extracted from the Eclipse DICOM RT Plan file. Simulated doses were compared to measurements using Zebra and MatriXX systems during PSQA process. Furthermore, a geometrical trigger technique was applied to assess the track positions in patient-specific components. The study found that the mean dose difference between measured and simulated values for the optimized LD/GV was below 1% at all depth positions. With passing rates of 97.4% at the middle SOBP and 90.3% at the proximal SOBP, the gamma analysis demonstrated satisfactory results. For the axial dose profile, SOBP flatness was within 2.5%. From the geometric trigger analysis, more than 95–98% of the dose was delivered through the range compensator, while approximately 2–5% originated from scattered protons from the Multi-Leaf Collimator (MLC) and block's edges. The PTSim simulation's performance in conducting PSQA demonstrated its capability and reliability.

Adolescent anterior cruciate ligament reconstruction: a decade of rising surgical cost.

The number of anterior cruciate ligament reconstruction (ACL-R) surgeries for adolescent patients has been increasing, and so are the costs for medical care services and the general cost of living. We proposed a novel economic model assessing the cost associated with adolescent ACL-R over time and how this compared with price measures in the US economy. Economic analysis. ACL-R surgeries performed from 2010 to 2022 in a single Level I trauma center were included. The trend of the total charge, charge of anesthesia, and operating room (OR) charge were normalized to 2010 (base year) and compared with the inflation in hospital services, medical care services, and the US economy measured by the Consumer Price Index (CPI). The actual reimbursements-to-charges percentage from the payers was analyzed. Comparing growth rates rather than dollar values circumvented any problematic direct-dollar comparisons across measures. Analyzing 459 qualified ACL-R cases in patients whose ages ranged from 12 to 18 years, the overall total median charge increased 70%, whereas the General CPI, Medical CPI, and Hospital CPI increased 35%, 41%, and 64%, respectively. The anesthesia and OR charges increased 52% and 92%, respectively. The annual reimbursements-to-charges percentage hovered steadily beneath 50%. All inflation measures rose sharply after 2019. The rising cost of adolescent ACL-R has been outpacing the inflation in the cost of medical services and the general economy in the US. The COVID-19 pandemic and market rigidity in medical services may have impacted these trends. Optimizing OR time usage may mitigate the rising cost.

Efficacy and Safety of Shen Fu Injection Alleviating Chemotherapy-Induced Peripheral Neurotoxicity: A Randomized Controlled Trial

Objective: To analyze the effect of Shenfu injection on Chemotherapy-Induced Peripheral Neuropathy (CIPN) at different stages of tumor chemotherapy. Method: An analysis of 153 patients who were divided into chemotherapy group and combined group was performed chemotherapy within two to six cycles with oxaliplatin or paclitaxel, and combined with or without Shenfu injection. Efficacy evaluation was divided into two phases, including the short-term incidence of CIPN and the long-term incidence of CIPN. Subgroup analysis was performed on the combined group to compare the incidence of CIPN in different usage time of Shenfu injection. Preliminary comparison of the incidence of common side effects. Results: The short-term incidence rates of CIPN in the combined group and chemotherapy group were 27.85% and 66.22%, respectively (P&lt;0.01), and the long-term incidence rates were 17.72% and 45.95%, respectively (P&lt;0.01). In the combined group of 5-6 cycles chemotherapy, divided into two groups according to the time used of Shenfu injection, greater than 3 weeks and less than 3 weeks, and the short-term incidence rates of CIPN were 28.57% and 69.23%, respectively, and the longterm incidence rates of CIPN was 14.29% and 46.15%, respectively. Adverse reactions evaluation showed that the occurrence of bone marrow suppression were 35.44% and 60.81% (P&lt;0.05) in the combined group and chemotherapy group, and there was no significant difference in digestive tract reaction, liver and kidney toxicity. Conclusion: Shenfu injection significantly reduced the incidence of CIPN and had a good security.

Implementation of User Experience (UX) Design on Library Website

The management of libraries in Indonesia is generally still done manually, leading to several issues such as inaccurate book inventory data and unclear transaction processes. The aim of this research is to design a web-based library information system using the User Experience (UX) concept, which will provide ease of use for users by focusing on effectiveness, efficiency, and satisfaction. This concept involves four stages: analysis, design, implementation, and evaluation. During the analysis stage, data collection is carried out through observation, interviews, and the distribution of questionnaires to understand the needs of the members. Next, the system is designed to meet the needs of both the members and the management. After that, usability testing is conducted to evaluate the effectiveness, efficiency, and user satisfaction with the system. The testing involved 15 members and library staff. The results showed that in terms of effectiveness, all tasks were above the average completion rate. In terms of efficiency, the product usage time was satisfactory, and in terms of satisfaction, using the UEQ (User Experience Questionnaire) showed good to very good results. Therefore, the library system can be used by library members to support their library activities.

Improving the interoperability of a Function‐as‐a‐Service platform using an orchestration framework with a cloud‐agnostic approach

AbstractFunction‐as‐a‐Service (FaaS) applications suffer from cold‐start latency owing to their high execution time and memory usage. We propose a FaaS orchestration framework based on a cloud‐agnostic approach for application and data interoperability. The framework's performance is evaluated on the web application of a student attendance system for online learning. The test system comprises 300 records from 50 students across five courses. Through optional file elimination, entry recognition, optional function generation, and function‐level rewriting, the proposed orchestration framework suitably manages the storage of the student attendance records. The framework notably contributes to the student attendance web application by ensuring scalable, reliable, and efficient operations. Various evaluation measures confirm the effectiveness of the orchestration framework. These measures include cold/warm‐start execution time, cold/warm‐start memory usage, and zip execution time. An empirical analysis reveals that our framework reduces the execution time by 2 s –15 s and memory usage by 1MB–3 MB for the evaluated application.

The Role of Automation in the Analysis of Manganese in Environmental Water Samples

Manganese is considered an emerging pollutant and it is perceived as a potential threat to human health and aquatic ecosystems. The need to determine and monitor the presence of Mn in environmental water requires increasingly precise and accurate chemical analytical techniques that provide reliable information to take timely measures in the event of potential environmental contingencies. The automation by flow analysis technique has allowed analytical procedures to isolate and preconcentrate manganese in environmental water samples. Additionally, it brings forth benefits such as greatly enhancing the sample processing capacity and a reduced time and reagent usage, leading to cost savings and minimized waste production, thereby aligning with the principles of green chemistry. In this review, a recent report of some flow analysis techniques (FIA, rFIA, SIA, MSFIA, LOV, and MPFS) is presented, highlighting the trend of automation, whose portability and miniaturization allow for complete in situ analysis. There are two remarkable analytical features from the studies evaluated here, which are sample throughput and accuracy, with a maximum processing time of 120 samples h−1 and an accuracy of 98%. The implementation of flow analysis techniques offers several advantages, such as miniaturization and portability. The discussed methodologies achieved limits of quantification as low as 0.26 µg L−1, enabling environmental monitoring that can easily detect the reference value of 0.05 mg L−1, established by the WHO and the EPA.

The relationship between social media usage and loneliness among younger and older adults: the moderating effect of shyness

Does social media alleviate or exacerbate loneliness? Past research has shown mixed results regarding the relationship between social media usage and loneliness among younger and older adults. Unlike younger individuals, older adults may decrease their loneliness through social media interactions. Additionally, previous research has indicated that the link between social media use and loneliness can vary depending on one’s shy tendency. Therefore, this study aims to explore the relationship between individuals’ social media use and loneliness while considering age and shyness tendency as moderating variables. The study employed a questionnaire survey conducted through convenience sampling, resulting in 234 valid responses from participants in Northern Taiwan. Among them, 113 were college students (aged 18 to 25, average age 19.40), and 121 were older adults (aged 50 to 82, average age 60.81). Using hierarchical regression analysis, results indicated that (1) age moderates the relationship between personal social media use and loneliness. Minimal differences were observed among younger individuals, but among older adults, increased social media usage time was associated with a significant reduction in loneliness. (2) Shyness tendency moderate the relationship between personal social media use and loneliness. Individuals with higher shyness tendency experience an increase in loneliness as their social media usage time lengthens.

TadaStride: Using time adaptive strides in audio data for effective downsampling

In this paper, we introduce a new downsampling method for audio data called TadaStride, which can adaptively adjust the downsampling ratios across an audio data instance. Unlike previous methods using a fixed downsampling ratio, TadaStride can preserve more information from task-relevant parts of a data instance by using smaller strides for those parts and larger strides for less relevant parts. Additionally, we also introduce TadaStride-F, which is developed as a more efficient version of TadaStride while maintaining minimal performance loss. In experiments, we evaluate our TadaStride, primarily focusing on a range of audio processing tasks. Firstly, in audio classification experiments, TadaStride and TadaStride-F outperform other widely used standard downsampling methods, even with comparable memory and time usage. Furthermore, through various analyses, we provide an understanding of how TadaStride learns effective adaptive strides and how it leads to improved performance. In addition, through additional experiments on automatic speech recognition and discrete speech representation learning, we demonstrate that TadaStride and TadaStride-F consistently outperform other downsampling methods and examine how the adaptive strides are learned in these tasks.

Securely Running High-Performance Workloads as Microservices in Cloud Environments

Over the past few years, the paradigm shift towards cloud computing has transformed and revolutionized how organizations manage high- performance workloads. The microservices architecture, renowned for its modularity and scalability, is increasingly being adopted to run these workloads in cloud environments. However, this transition is not without its challenges, particularly in security. This research article delves into the methods for securely running high-performance workloads as microservices in cloud environments, presenting the advantages and the challenges involved. The study aims to develop a comprehensive framework that not only addresses these security concerns but also optimizes performance, a crucial aspect in today's digital landscape. This research is a testament to our commitment to thoroughness and precision, as it combines both qualitative and quantitative approaches. Qualitative data were meticulously gathered through interviews with 15 cloud security experts, providing invaluable insights into prevalent security practices and challenges. Quantitative data, on the other hand, were collected from performance benchmarks that rigorously compared traditional monolithic applications with microservices- based applications in a cloud setting. The study employs robust statistical analysis tools such as SPSS and Grafana to analyze the collected data, ensuring the validity and reliability of our findings. Key interview findings highlighted critical security measures necessary for microservices, including service authentication, data encryption, and vulnerability management. The performance benchmarks revealed that microservices- based applications significantly outperformed monolithic applications, with notable improvements in CPU utilization, memory usage, and response time. For instance, the microservices architecture demonstrated a 21% reduction in CPU utilization and a 12% decrease in memory usage compared to its monolithic counterpart. The proposed framework integrates robust security practices, ensuring secure authentication, encrypted data transmission, and regular updates to mitigate vulnerabilities. This framework enhances security and optimizes resource allocation, leading to improved performance metrics.

Fast connectivity gradient approximation: maintaining spatially fine-grained connectivity gradients while reducing computational costs

Brain connectome analysis suffers from the high dimensionality of connectivity data, often forcing a reduced representation of the brain at a lower spatial resolution or parcellation. This is particularly true for graph-based representations, which are increasingly used to characterize connectivity gradients, capturing patterns of systematic spatial variation in the functional connectivity structure. However, maintaining a high spatial resolution is crucial for enabling fine-grained topographical analysis and preserving subtle individual differences that might otherwise be lost. Here we introduce a computationally efficient approach to establish spatially fine-grained connectivity gradients. At its core, it leverages a set of landmarks to approximate the underlying connectivity structure at the full spatial resolution without requiring a full-scale vertex-by-vertex connectivity matrix. We show that this approach reduces computational time and memory usage while preserving informative individual features and demonstrate its application in improving brain-behavior predictions. Overall, its efficiency can remove computational barriers and enable the widespread application of connectivity gradients to capture spatial signatures of the connectome. Importantly, maintaining a spatially fine-grained resolution facilitates to characterize the spatial transitions inherent in the core concept of gradients of brain organization.