Central Computer Research Articles

Advancing parcel-level hurricane regional loss assessments using open data and the regional resilience determination tool

Hurricanes are a major driver of losses in the United States and thus are the focus of risk assessment capacity building efforts in the public and private sectors, as well as in the scholarly community. Capabilities for loss modeling have been particularly advanced through the development of open-source scientific workflows that conduct site-specific, building-specific, and even component-level loss assessments across entire regions. Notable among these is the Natural Hazards Engineering Research Infrastructure's Computational Modeling and Simulation Center's (NHERI SimCenter) Regional Resilience Determination (R2D) tool. However, the modular architecture of R2D's computational scaffolding has only been described and illustrated through testbed applications thus far. This study presents the first replication and extension of the R2D tool to conduct parcel-level and component-level hurricane performance assessments outside of the SimCenter's testbed locations. The study first details how building inventories that capture time-evolving building characteristics and regional construction practices can be generated using updated heuristic rulesets that guide the integration of tax assessor data with other open data sources. These rulesets and supporting data are then utilized to generate building inventory information for a set of single family homes located in Florida's Bay County, the landfall site of Hurricane Michael in 2018. HAZUS-compatible, parcel-level damage and loss assessments are then conducted, considering Hurricane Michael's peak gust wind speeds. Finally, a set of custom fragilities, empirically-derived from multiple regional post-disaster datasets, are incorporated into R2D to conduct the first component-level damage assessment of buildings under hurricanes using the SimCenter's regional loss modeling workflows. In total, this represents an important first step in operationalizing replicable regional risk assessments down to the parcel level to provide more granular risk information to key stakeholders.

Penerapan Graf Berarah dan Berbobot untuk Mengetahui Inluencer yang Paling Berpengaruh dalam Penyebaran Informasi pada Twitter

A graph is a non-empty set whose members are vertices and edges, where the edges connect several pairs of these vertices; likewise, social media connects users with each other through interests, relationships, likes and dislikes. The rapid development of technology in the era of globalization has made social media a more effective source of information, one of them is Twitter which has been used by 280 million people in the world. This research involves 100 Twitter users who are classified as Influencers in Indonesia who have more than 10,000 followers by visualizing their relationship with other users followed by them with a directed and weighted graph. First, the data is filtered using the Twecoll script in Python software, then the data is visualized using the Gephi software in the form of a directed and weighted graph. The centrality value is calculated to determine the influential influencers in spreading information on the network. Based on the results of the study, it was found that the network pattern of 100 Influencers that had been collected in the following list of @dearmyths accounts, there were 96 points and 1883 sides with the side having the highest weight being @detikcom, followed by @ivanlanin and @ernestprakasa through the results of centrality calculations as accounts that can disseminate information on the network.

In search of behavioral and brain processes involved in honey bee dance communication.

Honey bees represent an iconic model animal for studying the underlying mechanisms affecting advanced sensory and cognitive abilities during communication among colony mates. After von Frisch discovered the functional value of the waggle dance, this complex motor pattern led ethologists and neuroscientists to study its neural mechanism, behavioral significance, and implications for a collective organization. Recent studies have revealed some of the mechanisms involved in this symbolic form of communication by using conventional behavioral and pharmacological assays, neurobiological studies, comprehensive molecular and connectome analyses, and computational models. This review summarizes several critical behavioral and brain processes and mechanisms involved in waggle dance communication. We focus on the role of neuromodulators in the dancer and the recruited follower, the interneurons and their related processing in the first mechano-processing, and the computational navigation centers of insect brains.

STATE POLICY IN THE FIELD OF COMPUTER TECHNOLOGY DEVELOPMENT IN THE 1950S: ACHIEVEMENTS AND BLOCKING FACTORS

The purpose of the publication, based on currently declassified documents, is to investigate the actual problem of the evolution of state policy in the field of computer technology development in the USSR in the 1950s. The conclusion is formulated that the «cold war», the unfolding scientific and technological revolution stimulated the implementation of their own projects in the field of information technology and hardware platforms in the USSR. A significant factor that determined the creation of various domestic computers in the early 1950s was the support at the state level of developments independent of Western analogues. The continuous growth in demand for calculating machines and the release in 1956 of a number of government decisions on the creation of new types of such machines forced the leadership of various departments to take urgent measures to accelerate the development of the mathematical engineering industry. In the period from 1955 to 1957, samples of high-performance computing and mathematical machines were created. A number of them were sent to mass production. Computer centers were created on the basis of new computer technology. However, in general, the development of computer technology in the country lagged behind the United States. The documents allow us to identify a number of factors that determined the braking of this process: the industrial management reform being carried out at that time, the departmental approach, the lack of understanding by the country's leadership of the special significance of this area of industrial and scientific and technical policy, the absence of a single center coordinating this work. The Scientific Council on Computer Technology and Control Systems of the State Committee of the USSR Academy of Sciences for Science and Technology and the Presidium of the USSR Academy of Sciences was established only in 1966.

Real-space solution to the electronic structure problem for nearly a million electrons.

We report a Kohn-Sham density functional theory calculation of a system with more than 200 000 atoms and 800 000 electrons using a real-space high-order finite-difference method to investigate the electronic structure of large spherical silicon nanoclusters. Our system of choice was a 20nm large spherical nanocluster with 202 617 silicon atoms and 13 836 hydrogen atoms used to passivate the dangling surface bonds. To speed up the convergence of the eigenspace, we utilized Chebyshev-filtered subspace iteration, and for sparse matrix-vector multiplications, we used blockwise Hilbert space-filling curves, implemented in the PARSEC code. For this calculation, we also replaced our orthonormalization + Rayleigh-Ritz step with a generalized eigenvalue problem step. We utilized all of the 8192 nodes (458 752 processors) on the Frontera machine at the Texas Advanced Computing Center. We achieved two Chebyshev-filtered subspace iterations, yielding a good approximation of the electronic density of states. Our work pushes the limits on the capabilities of the current electronic structure solvers to nearly 106 electrons and demonstrates the potential of the real-space approach to efficiently parallelize large calculations on modern high-performance computing platforms.

Planting a Lyman alpha forest on AbacusSummit

ABSTRACT The full-shape correlations of the Lyman alpha (Ly α) forest contain a wealth of cosmological information through the Alcock–Paczyński effect. However, these measurements are challenging to model without robustly testing and verifying the theoretical framework used for analysing them. Here, we leverage the accuracy and volume of the N-body simulation suite AbacusSummit to generate high-resolution Ly α skewers and quasi-stellar object (QSO) catalogues. One of the main goals of our mocks is to aid in the full-shape Ly α analysis planned by the Dark Energy Spectroscopic Instrument (DESI) team. We provide optical depth skewers for six of the fiducial cosmology base-resolution simulations ($L_{\rm box} = 2\, h^{-1}\, {\rm Gpc}$, N = 69123) at z = 2.5. We adopt a simple recipe based on the Fluctuating Gunn–Peterson Approximation (FGPA) for constructing these skewers from the matter density in an N-body simulation and calibrate it against the 1D and 3D Ly α power spectra extracted from the hydrodynamical simulation IllustrisTNG (TNG; $L_{\rm box} = 205\, h^{-1}\, {\rm Mpc}$, N = 25003). As an important application, we study the non-linear broadening of the baryon acoustic oscillation (BAO) peak and show the cross-correlation between DESI-like QSOs and our Ly α forest skewers. We find differences on small scales between the Kaiser approximation prediction and our mock measurements of the Ly α × QSO cross-correlation, which would be important to account for in upcoming analyses. The AbacusSummit Ly α forest mocks open up the possibility for improved modelling of cross-correlations between Ly α and cosmic microwave background (CMB) lensing and Ly α and QSOs, and for forecasts of the 3-point Ly α correlation function. Our catalogues and skewers are publicly available on Globus via the National Energy Research Scientific Computing Center (NERSC) (full link under the section ‘Data Availability’).

Solving the electronic structure problem for over 100 000 atoms in real space

Using a real-space high-order finite-difference approach, we investigate the electronic structure of large spherical silicon nanoclusters. Within Kohn-Sham density functional theory and using pseudopotentials, we report the self-consistent field convergence of a system with over 100 000 atoms: a ${\mathrm{Si}}_{107,641}{\mathrm{H}}_{9,084}$ nanocluster with a diameter of 16 nm. Our approach uses Chebyshev-filtered subspace iteration to speed up the convergence of the eigenspace, and blockwise Hilbert space-filling curves to speed up sparse matrix-vector multiplications, all of which are implemented in the parsec code. For the largest system, we utilized 2048 nodes (114 688 cores) on the Frontera machine in the Texas Advanced Computing Center. Our quantitative analysis of the electronic structure shows how it gradually approaches its bulk counterpart as a function of nanocluster size. The band gap is enlarged due to quantum confinement in nanoclusters, but decreases as the system size increases, as expected. Our work serves as a proof of concept for the capacity of the real-space approach in efficiently parallelizing very large calculations using high-performance computer platforms, which can straightforwardly be replicated in other systems with more than ${10}^{5}$ atoms.

Investigation of the Inhibition Mechanism of Organic Corrosion Inhibitors on the Copper Surface by DFT study and MD simulations

AbstractSupports of the National Natural Science Foundation of China (21908017 and 21902021), the Undergraduate Innovation and Entrepreneurship Training Program Dalian University of Technology (20211014110934), the Foundation of State Key Laboratory of High‐efficiency Utilization of Coal and Green Chemical Engineering (2022‐K70), the Fundamental Research Funds for the Central Universities (DUT22LK09), the Open Foundation of Key Laboratory of Industrial Ecology and Environmental Engineering, MOE (KLIEEE‐20‐01, KLIEEE‐21‐02), and the Hefei Advanced Computing Center for this work are gratefully acknowledged.

Leveraging History to Predict Infrequent Abnormal Transfers in Distributed Workflows.

Scientific computing heavily relies on data shared by the community, especially in distributed data-intensive applications. This research focuses on predicting slow connections that create bottlenecks in distributed workflows. In this study, we analyze network traffic logs collected between January 2021 and August 2022 at the National Energy Research Scientific Computing Center (NERSC). Based on the observed patterns, we define a set of features primarily based on history for identifying low-performing data transfers. Typically, there are far fewer slow connections on well-maintained networks, which creates difficulty in learning to identify these abnormally slow connections from the normal ones. We devise several stratified sampling techniques to address the class-imbalance challenge and study how they affect the machine learning approaches. Our tests show that a relatively simple technique that undersamples the normal cases to balance the number of samples in two classes (normal and slow) is very effective for model training. This model predicts slow connections with an F1 score of 0.926.

MSR57 Survival Analysis without Sharing of Individual Person Data: An Antidote to “Data Available upon Request”?

Cox regression and Kaplan-Meier estimates are often needed in post-approval clinical research which requires access to individual person data (IPD). Think about a long-term treatment-effect review or a comparative effectiveness oncology study involving the IPD owned by a competitor. Here, IPD cannot always be shared due to privacy or proprietary restrictions, which complicates the making of such estimates. I propose a method that generates pseudodata replacing the IPD by only using non-disclosive IPD aggregates which are shared with a central computer and are input parameters to a Gaussian copula (GC) generating the pseudodata, allowing analysts to access completely anonymised versions of possibly multiple datasets on which to run analyses.

Концепция построения учебных тренажеров для подготовки специалистов гражданской авиации в технических вузах

The method of equipping with training simulators for civil aviation personnel training is considered. Since not all issues of practical training can be solved by implementing a part of the educational program in the form of practical training in the specialized organization, the use of training aviation simulators can significantly reduce the cost of specialist training. The simulators presented at the market are expensive for education institutions with limited functionality, that is why one of the options is their independent production. It is proposed to reduce the cost of training simulators by using small-size microcontrollers, which are built into the device itself, and data exchange with the central computer over a wireless communication line. To check this approach, a test setup in the form of a Tу-154М flight engineer panel consisting of more than five hundred elements was assembled. The operating time of the test setup was 1300 hours, during that period of time there was not a single failure in operation, all devices, lamps and controls worked out the set values without failures. The offered variant of a method of manufacturing flight simulators is less expensive both financially and labor-consuming, which enables educational organizations to purchase it and allows to form necessary competences on operation of modern aviation technique among the future aviation specialists. In case such aviation simulator is designed and manufactured by students within the framework of project training, course works (projects) and graduate qualification works, the main goal — the highest level of practical mastering of aircraft equipment and systems — is achieved.

The Fifth Conference "Computer Algebra" in Moscow

The fifth International Conference "Computer algebra" http://www.ccas.ru/ca/conference is organized in Moscow from 26 to 28 June 2023 jointly by the Dorodnicyn Computing Centre (Federal Research Center "Computer Science and Control") of Russian Academy of Science, the Russian University of Peoples' Friendship named after Patrice Lumumba and Keldysh Institute of Applied Mathematics of Russian Academy of Sciences.

ვენახებისა და ბაღების წაყინვებისგან დაცვის მეთოდები

The article discusses the main means of protection against frost: overcrown sprinkler, undercrown sprinkler, smoke, wind turbines. Also mentioned are some protections that are more applicable in small areas. European projects were considered, within the framework of which the modernization of frost protection systems was carried out based on the use of the latest digital technologies. In areas of vineyards and orchards, sensors are placed that measure the necessary climatic parameters. The data is transmitted to computer centers, where, with the help of special prognostic models, an operational, operational frost forecast is issued. This enables farmers to organize protection in a timely manner

(489) Comparison of Penile Prostheses Outcomes in Veterans with Peyronie’s Disease: A Single-Center Analysis

Abstract Introduction Peyronie’s disease (PD) causes erectile dysfunction (ED) in at least 40% of cases. ED refractory to medical and injection therapy can be treated with implantable penile prosthesis, which may also address the penile deformities. However, prosthesis surgery has significant associated morbidity-including erosive disease and infection-and frequently requires explant or revision. Data for Veterans Affairs (VA) patients with PD is limited, especially with respect to penile prosthesis placement. More information is needed for proper counseling and perioperative planning in this high-risk population. Objective The aim of this study is to compare outcomes and revision rates in Veteran patients with and without PD after primary penile prosthesis implantation. Methods A retrospective cohort study of the xxx VA Medical Center Informatics and Computing Infrastructure database was performed. Veterans who underwent penile prosthesis surgery between January 2013 and February 2022 were identified and included in the study. Patient factors including age, race, procedure type, and relevant comorbidities were collected. Patients with and without history of PD were identified and separated into two cohorts and patient factors of these two groups were compared using chi-square and Fisher’s exact tests. Freedom from revision was analyzed using Cox regression and hazard ratios. Results A total of 229 patients underwent penile prosthesis placement with at least 4 months follow-up. 24 patients (10.48%) with history of PD were identified. The mean age at prosthesis placement of PD patients was younger than that of non-PD patients (61.3 vs 65.0 respectively, p=0.0358). Rear tip extender length was longer in the PD cohort than the non-PD cohort (3.02 cm vs 2.32 cm respectively, p=0.0313). Operative time was shorter in patients with PD than in patients without PD (91 minutes vs 111 minutes respectively, p=0.0409). Prosthesis type, hospital stay, and post-operative complication rates were not significantly different between groups. PD was not associated with significantly increased risk of prosthesis revision or removal (p>0.05). No patients in the PD cohort experienced infection or erosion; two explants were performed for component migration and supersonic transporter deformity respectively. Conclusions Veterans with PD undergoing prosthesis placement have similar revision rates and explant rates as compared to veterans without PD. Additionally, penile prosthesis implantation for men with PD is associated with low morbidity and similar complication rates compared to men without PD undergoing prosthesis placement for erectile dysfunction. Disclosure No

Using Social Network Analysis to Identify the Critical Factors Influencing Residents’ Green Consumption Behavior

Green consumption is an important tool to accelerate the circular economy and promote sustainable development. The identification of critical influencing factors for green consumption is the key to promoting green consumption behavior (GCB). Firstly, based on the joint framework of theory of planned behavior (TPB) and the attitude–behavior–context (ABC) theory, we summarized 32 influencing factors from six dimensions: consumer attitude, cognitive factors, sense of responsibility, economic factors, government regulation, and green product supply. Secondly, the Delphi method was used to modify and optimize the initial influencing factor index. Thirdly, we constructed a social network analysis (SNA) model of influencing factors to determine the causal relationships between each influencing factor. All factors were divided into driving factors and result factors via the calculation of degree centrality, and the critical influencing factors and influencing paths of residents’ GCB were ultimately determined. Finally, based on the empirical research results, corresponding countermeasures and suggestions were put forward. The results show that the top five critical influencing factors include green purchase intention, willingness to pay, risk perception, green product certification, publicity and education, green product price, and green attribute information. Among them, green product certification, publicity and education, and green product price are critical driving factors in GCB.

Replicating File Segments between Multi-Cloud Nodes in a Smart City: A Machine Learning Approach

The design and management of smart cities and the IoT is a multidimensional problem. One of those dimensions is cloud and edge computing management. Due to the complexity of the problem, resource sharing is one of the vital and major components that when enhanced, the performance of the whole system is enhanced. Research in data access and storage in multi-clouds and edge servers can broadly be classified to data centers and computational centers. The main aim of data centers is to provide services for accessing, sharing and modifying large databases. On the other hand, the aim of computational centers is to provide services for sharing resources. Present and future distributed applications need to deal with very large multi-petabyte datasets and increasing numbers of associated users and resources. The emergence of IoT-based, multi-cloud systems as a potential solution for large computational and data management problems has initiated significant research activity in the area. Due to the considerable increase in data production and data sharing within scientific communities, the need for improvements in data access and data availability cannot be overlooked. It can be argued that the current approaches of large dataset management do not solve all problems associated with big data and large datasets. The heterogeneity and veracity of big data require careful management. One of the issues for managing big data in a multi-cloud system is the scalability and expendability of the system under consideration. Data replication ensures server load balancing, data availability and improved data access time. The proposed model minimises the cost of data services through minimising a cost function that takes storage cost, host access cost and communication cost into consideration. The relative weights between different components is learned through history and it is different from a cloud to another. The model ensures that data are replicated in a way that increases availability while at the same time decreasing the overall cost of data storage and access time. Using the proposed model avoids the overheads of the traditional full replication techniques. The proposed model is mathematically proven to be sound and valid.

Automated control for investigation of the insufflation-ventilation interaction in experimental laparoscopy.

In laparoscopic surgery the abdominal cavity is insufflated with pressurized carbon dioxide gas to create workspace. This pressure is exerted through the diaphragm onto the lungs, competing with ventilation and hampering it. In clinical practice the difficulty of optimizing this balance can lead to the application of harmfully high pressures. This study set out to create a research platform for the investigation of the complex interaction between insufflation and ventilation in an animal model. The research platform was constructed to incorporate insufflation, ventilation and relevant hemodynamic monitoring devices, controlling insufflation and ventilation from a central computer. The core of the applied methodology is the fixation of physiological parameters by applying closed-loop control of specific ventilation parameters. For accurate volumetric measurements the research platform can be used in a CT scanner. An algorithm was designed to keep blood carbon dioxide and oxygen values stable, minimizing the effect of fluctuations on vascular tone and hemodynamics. This design allowed stepwise adjustment of insufflation pressure to measure the effects on ventilation and circulation. A pilot experiment in a porcine model demonstrated adequate platform performance. The developed research platform and protocol automation have the potential to increase translatability and repeatability of animal experiments on the biomechanical interactions between insufflation and ventilation.

EESD special issue: AI and data‐driven methods in earthquake engineering – (Part 1)

EESD special issue: AI and data‐driven methods in earthquake engineering – (Part 1)

Dementia Modulates the Distributed Representations of Cognitive Functions (P4-12.011)

<h3>Objective:</h3> To investigate how cognitive decline affects psychometric representations of global (Mini-Mental State Examination (MMSE) and Clinical Dementia Rating scale (CDR)) and domain-specific neuropsychological measures. To examine the association between cognitive decline and β-amyloid burden using tracer Positron Emission Tomography (PET) imaging. <h3>Background:</h3> One of the central goals of cognitive neuroscience is to understand how anatomical structure relates to function. In dementia, cognitive functions are disrupted and brain regions are selectively involved. It is unclear, however, how the anatomical distribution of pathological changes relates to cognitive functions as measured by clinical assessments. <h3>Design/Methods:</h3> OASIS-3 dataset was used to evaluate the psychometric correlates of cognitive decline in cognitively normal (n=755), and cognitively impaired subjects (n=655) with ages ranging from 42 to 95 years. Anatomical distribution of β-amyloid burden was assessed using florbetapir (AV-45) and Pittsburgh compound B (PIB) PET imaging. Analysis was limited to subjects who underwent cognitive testing and PET imaging within six months. <h3>Results:</h3> Global cognitive decline as measured with MMSE and CDR is associated with brain-wide β-amyloid deposition (randomization test, false detection rate adjusted p-values (q-values) &lt;0.001). Both PIB and AV-45 capture similar neural correlates of global cognitive measures, but show differential selectivity for individual neuropsychological measures (Pearson correlation coefficients, q-values &lt;0.05). Representational similarity analysis of β-amyloid deposition further confirmed these findings, revealing distributed patterns of global cognitive decline across the cortical and subcortical regions (q-values &lt;0.05). There is a continuum in the low-dimensional psychometric and β-amyloid deposition representation (binomial test, q-values &lt;0.001), suggesting behavioral and anatomical heterogeneity within subjects with a diagnosis of cognitive impairment. <h3>Conclusions:</h3> Global cognitive assessments are associated with distributed cortical and subcortical representation. There is a distributed rather than a localized system of cortical and subcortical regions that maintain cognitive function. Behavioral and anatomical heterogeneity exists among subjects with cognitive impairment. <b>Disclosure:</b> Dr. Verma has nothing to disclose. Dr. Kumar has received research support from Texas Advance Computing Center.

‘The internet is in the satellites!’: A systematic review of 3–15-year-olds’ conceptions about the internet

Children aged 3–15 frequently use internet-enabled technologies for leisure and educational purposes, yet they have limited knowledge about how the internet works. Literature also indicates that children possess varied and often contradictory internet-related ideas, which have not yet been systematized. This systematic review, drawing from 27 mixed-methods and qualitative studies (N = 2,214) from the last two decades (2002 – 2022), organizes these ideas through a thematic analysis with a specific focus on the age when individual child conceptions start to appear at the earliest. The findings are interpreted through the lenses of a Vygotskian framework. The results highlight 60 conceptions concerning general perceptions of the internet, internet infrastructure, and dataflow. Children appear to understand the internet primarily through their personal experiences. Perception of the internet as online activities is dominant in younger children, but also present among older ones. Children in all age groups are confused about what Wi-Fi really is; some equate it to the internet, others to the ‘Wi-Fi box’ (Wi-Fi router). The most knowledgeable older children view the internet as a global network with a complex internal, but only vaguely understood, structure. Typical reasoning among older children about the internet’s structure includes satellites, central computers or central towers. Only expert children know about distributed, server-like storage. These results imply that children at the K-8 level need to be familiarized gradually with how the internet works, but teaching them this topic may prove to be challenging. This review also highlights the limitations of existing literature and presents suggestions for future research and designing technology-based curricula.