cometadata/datacite-rtg-text-other-reclassification-records huggingface dataset:
Quantifying performance bottlenecks of stencil computations using the Execution-Cache-Memory model
Creators: name: Stengel, Holger
name: Treibig, Jan
name: Hager, Georg
name: Wellein, Gerhard
Publisher: name: arXiv
Year: 2014
Subjects: subject: Performance (cs.PF)
subject: Distributed, Parallel, and Cluster Computing (cs.DC)
subject: FOS: Computer and information sciences

description: Stencil algorithms on regular lattices appear in many fields of computational science, and much effort has been put into optimized implementations. Such activities are usually not guided by performance models that provide estimates of expected speedup. Understanding the performance properties and bottlenecks by performance modeling enables a clear view on promising optimization opportunities. In this work we refine the recently developed Execution-Cache-Memory (ECM) model and use it to quantify the performance bottlenecks of stencil algorithms on a contemporary Intel processor. This includes applying the model to arrive at single-core performance and scalability predictions for typical corner case stencil loop kernels. Guided by the ECM model we accurately quantify the significance of "layer conditions," which are required to estimate the data traffic through the memory hierarchy, and study the impact of typical optimization approaches such as spatial blocking, strength reduction, and temporal blocking for their expected benefits. We also compare the ECM model to the widely known Roofline model.
description: 10 pages, 8 figures. Added Roofline comparison and other minor improvements
Forests of the future: socio-ecological dynamics of tropical forest regeneration in the Mesoamerican Biological Corridor, Mexico
Creators: name: Rader, Alana Marie
Publisher: name: No Publisher Supplied
Year: 2022

description: Tropical forests are regenerating globally following diverse and compounding disturbances to forest cover. Understanding where, when, and why forests regenerate adds a largely unexplored dimension to the life cycle of tropical forests in human occupied landscapes which to date are largely characterized by deforestation and its acute biophysical and socio-economic impacts. Instead, going beyond deforestation to examine patterns and processes of forest regeneration speaks more accurately to the ability of tropical forests landscapes, and the ecological and human communities which inhabit them, to withstand projected increases in environmental disturbances. Examining forest regeneration dynamics is particularly pertinent in the Mexican portion of the Mesoamerican Biological Corridor (MxMBC), a region along Mexico’s southeastern Yucatán Peninsula marking the northern margin of the important Mesoamerican Biological Corridor. The MxMBC has long been deemed a hotspot for both biodiversity conservation and deforestation. At the same time, forest cover regularly experiences widespread damage from hurricanes, such as the most recent landfall of category 5 Hurricane Dean in 2007. In the MxMBC, forest cover persists following disturbances such as hurricane impacts and land use, due to the largely understudied process of regeneration, and is central to long-term tropical forest use that continually adapts to sustain specific ecosystem processes and conditions through regrowth. This dissertation characterizes the socio-ecological patterns of forest regeneration in the MxMBC that stem from the relationship between ecosystem processes and land use. Examining forest regeneration in this region contributes to a history of land system science research that has outlined the patterns and drivers of deforestation in the region (i.e. the Southern Yucatán Peninsula Region Project), as well as programs that have outlined the immediate impacts of Hurricane Dean (i.e. the Environmental Disturbances in the Greater Yucatán Project), to highlight the various pathways to and opportunities provides by forest regeneration. Together, chapters of this dissertation represent a mixed methods approach in the field of land system science to link remote sensing, ecological, and sociopolitical data analysis in the service of understanding regenerated forest’s role in an integrated land system. As a result, forest regeneration emerges as both a landcover pattern, driven by multiscale land use systems, and a process driving biophysical and socio-political patterns in the region, with implications for forest management in the face of increasing disturbances.
Machine Learning Gap-Filling AOD Models for High Resolution PM2.5 Predictions: Assessing Wildfire Impact on Air Quality in US Northeastern States
Creators: name: PHOEBE PAN
name: Anusha Srirenganathan
name: Chaowei Yang
Publisher: name: Journal of Student-Scientists' Research
Year: 2023

description: Breathing in fine particulate matter with diameters less than 2.5 µm (PM2.5) has been shown to greatly increase an individual’s risk of cardiovascular and respiratory diseases. In light of the recent Canadian Wildfires' impact on air quality in the US northeastern states, this research is focused on the influence of these wildfires on PM2.5 levels. While air quality monitoring networks can provide accurate and timely PM2.5 readings, these stations are often too sparsely located to capture the spatial and temporal variabilities of PM2.5. As a solution, satellite measured aerosol optical depth (AOD) is commonly used as a source for PM2.5 pollution assessment. AOD quantifies the amount of aerosols present in the atmosphere by measuring the extinction of a ray of light as it passes through a vertical column of air. Initially, satellite AOD products were validated against ground truth data, ensuring the accuracy of the satellite measurements. Present work centers on developing machine learning gap-filling AOD models through the fusion of multisource AOD data. This approach aims to address data gaps caused by cloud cover, providing a complete hourly AOD dataset. In future work, gap filled AOD data will be combined with meteorological information and ground based PM2.5 measurements to generate precise and localized PM2.5 predictions. These insights will significantly contribute to a better understanding of wildfire impact on air quality in the US northeastern states with the hopes of more informed public health and environmental policies.
description: Journal of Student-Scientists' Research, Vol. 5 (2023)
Utilizing PurpleAir Sensors for Real-Time Visualization and Analysis of Region-Specific PM2.5 Air Pollution Data
Creators: name: AHAAN SHAH
name: Jiakang Liu
name: Chaowei Yang
Publisher: name: Journal of Student-Scientists' Research
Year: 2023

description: Airborne particulate matter with a diameter of 2.5 micrometers or less (PM2.5) is a major health concern due to its adverse effects on human health and the environment. As air pollution worsens, understanding region-specific PM2.5 levels becomes crucial for targeted interventions. This study presents a novel approach using low-cost PurpleAir sensors that provide real-time PM2.5 data. Through the implementation of Python, a sophisticated visualization and analysis tool has been developed to map the real-time PM2.5 data on an interactive platform. Specific regions of interest can be effortlessly defined by selecting bounding boxes on the map, thereby focusing on areas that warrant immediate attention. Customizable filters, such as proximity of sensors to the selected region and the maximum allowable PM2.5 concentration, are incorporated into the tool to enhance data accuracy and streamline the data collection process. The strength of this approach lies in its ability to empower researchers and communities with timely information about region-specific PM2.5 levels, significantly advancing our understanding of air quality and facilitating a proactive approach towards a cleaner and healthier environment for all.
description: Journal of Student-Scientists' Research, Vol. 5 (2023)
Using Automated Processes Using GES DISC API to Help Users Easily Access Data of Air Quality Events
Creators: name: NIKITA RAO
name: Anusha Srirenganathan Malarvizhi
name: Chaowei Yang
Publisher: name: Journal of Student-Scientists' Research
Year: 2023

description: The Canadian wildfires have notable impacts on air quality in the US and it led to a substantial decline in air quality levels. This event releases massive amounts of harmful particulate matter and pollutants into the atmosphere, leading to long-term consequences for both human and ecological well-being. To study and analyze the consequences of these events, air quality data from different sources such as satellites, in-situ, and airborne observations must be used. Currently, the retrieval of satellite data solely relies on a manual process, wherein each day necessitates individualized retrieval. This current approach is burdened with repetitiveness and demands a significant amount of time, posing substantial challenges. In the present research, an automated process was created using NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) Application Programming Interfaces (API) and a job scheduler application. With the use of APIs, data could be easily downloaded from NASA’s server filtering by cloud cover, acquisition date, resolution, spatial extent or any other relevant parameters. This code was finalized in Python and allowed users to easily access the data to help analyze various air quality events. The users will now be able to address the above-mentioned challenge more efficiently.
description: Journal of Student-Scientists' Research, Vol. 5 (2023)
Tenebrio molitor
Creators: name: Linnaeus, Carolus
Publisher: name: Zenodo
Year: 1758
Subjects: Biodiversity
Taxonomy
Animalia
Arthropoda
Insecta
Coleoptera
Tenebrionidae
Tenebrio
Tenebrio molitor

description: Tenebrio molitor T. niger totus Fn. scev. 547. Mordella antennarum articulis lentiformibus: ultimo globoso. Frisch. ins. 4 p. 1 t.1 Habitat in Farina pistorum, Molendinis, Pane sicco, saccharato Larva pallida, 13 segmentis, glabra, Lusciniis accepta
description: Published as part of Linnaeus, Carolus, 1758, Systema naturae per regna tria naturae, secundum classes, ordines, genera, species, cum characteribus, differentiis, synonymis, locis, Laurentii Salvii, Holmiae: Impensis Direct. Laurentii Salvii, 1758 - 1759. on page 417, DOI: 10.5962/bhl.title.542
Unity and Struggle v.4 no.2
Creators: name: No Name Supplied
Publisher: name: No Publisher Supplied
Year: 1975

description: This issue of Unity and Struggle volume 4, number 2, has a publication date of January 1975 and is the second part of the January 1975 edition. Contributions of news articles, essays, illustrations, photographs, or advertisements are attributed to Afrikan Youth Movement for Liberation & Unity, IAB, and Amiri Baraka.
Robust identification of noncoding RNA from transcriptomes requires phylogenetically-informed sampling
Creators: name: Lindgreen, Stinus
name: Umu, Sinan Ugur
name: Lai, Alicia Sook-Wei
name: Eldai, Hisham
name: Liu, Wenting
name: McGimpsey, Stephanie
name: Wheeler, Nicole
name: Biggs, Patrick J.
name: Thomson, Nick R.
name: Barquist, Lars
name: Poole, Anthony M.
name: Gardner, Paul P.
Publisher: name: arXiv
Year: 2014
Subjects: subject: Genomics (q-bio.GN)
subject: FOS: Biological sciences

description: Noncoding RNAs are integral to a wide range of biological processes, including translation, gene regulation, host-pathogen interactions and environmental sensing. While genomics is now a mature field, our capacity to identify noncoding RNA elements in bacterial and archaeal genomes is hampered by the difficulty of de novo identification. The emergence of new technologies for characterizing transcriptome outputs, notably RNA-seq, are improving noncoding RNA identification and expression quantification. However, a major challenge is to robustly distinguish functional outputs from transcriptional noise. To establish whether annotation of existing transcriptome data has effectively captured all functional outputs, we analysed over 400 publicly available RNA-seq datasets spanning 37 different Archaea and Bacteria. Using comparative tools, we identify close to a thousand highly-expressed candidate noncoding RNAs. However, our analyses reveal that capacity to identify noncoding RNA outputs is strongly dependent on phylogenetic sampling. Surprisingly, and in stark contrast to protein-coding genes, the phylogenetic window for effective use of comparative methods is perversely narrow: aggregating public datasets only produced one phylogenetic cluster where these tools could be used to robustly separate unannotated noncoding RNAs from a null hypothesis of transcriptional noise. Our results show that for the full potential of transcriptomics data to be realized, a change in experimental design is paramount: effective transcriptomics requires phylogeny-aware sampling.
description: 16 pages, 5 figures
Optimal Geodesic Curvature Constrained Dubins' Path on Sphere with Free Terminal Orientation
Creators: name: Kumar, Deepak Prakash
name: Darbha, Swaroop
name: Manyam, Satyanarayana Gupta
name: Tran, Dzung
name: Casbeer, David W.
Publisher: name: arXiv
Year: 2024
Subjects: subject: Optimization and Control (math.OC)
subject: FOS: Mathematics

description: In this paper, motion planning for a vehicle moving on a unit sphere with unit speed is considered, wherein the desired terminal location is fixed, but the terminal orientation is free. The motion of the vehicle is modeled to be constrained by a maximum geodesic curvature $U_{max},$ which controls the rate of change of heading of the vehicle such that the maximum heading change occurs when the vehicle travels on a tight circular arc of radius $r = \frac{1}{\sqrt{1 + U_{max}^2}}$. Using Pontryagin's Minimum Principle, the main result of this paper shows that for $r \leq \frac{1}{2}$, the optimal path connecting a given initial configuration and a final location on the sphere belongs to a set of at most seven paths. The candidate paths are of type $CG, CC,$ and degenerate paths of the same, where $C \in \{L, R\}$ denotes a tight left or right turn, respectively, and $G$ denotes a great circular arc.
description: \c{opyright} 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works
Additional file 2 of Factors associated with breast cancer awareness and breast self-examination in Fiji and Kashmir India – a cross-sectional study
Creators: name: Rukaiya Malik
name: Vera, Numa
name: Dayal, Chandra
name: Choudhari, Abhay
name: Jyotishna Mudaliar
name: Hill, Amanda Noovao
name: Ilisapeci Kubuabola
name: Gunnarsson, Ronny
Publisher: name: figshare
Year: 2020
Subjects: subject: Medicine
subject: Cell Biology
subject: Biotechnology
subject: 59999 Environmental Sciences not elsewhere classified
subject: FOS: Earth and related environmental sciences
subject: Cancer
subject: Science Policy

description: Additional file 2.
Improving Accuracy in PM2.5 Interpolation Using AI and ML
Creators: name: ANDREW YANG
name: Anusha Srirenganathan
name: Chaowei Yang
Publisher: name: Journal of Student-Scientists' Research
Year: 2023

description: Air quality prediction is increasingly critical, especially considering recent events like the Canadian Wildfires releasing hazardous particulate matter over the US. The growing awareness of AI and machine learning have been increasingly used to facilitate applications in scientific studies, notably PM2.5 retrieval. PM2.5 retrieval uses machine learning (ML) techniques to estimate accurate PM2.5 values by considering predictors such as meteorological variables. One of the challenges in PM2.5 retrieval is dealing with different predictors with varying spatial resolutions. Prior to retrieval, predictor variables needed to be interpolated into a uniform grid, which currently lacks a standardized and validated model. Different interpolation methods (Inverse Distance Weighting (IDW), Kriging, and Natural Neighbor) offer techniques for estimating values in PM2.5 retrieval. Understanding the results involves assessing the spatial behavior of the data and validating the interpolation methods using metrics like Root Mean Squared Error (RMSE) and R-squared (R2). In this study, different interpolation models in ArcGIS Pro were used to interpolate meteorological variables. The models employed estimated values at a uniform grid with a spatial resolution of 1 km x 1 km. Interpolation methods were carefully evaluated using validation metrics to assess their effectiveness and accuracy in capturing spatial patterns and variations at this resolution.
description: Journal of Student-Scientists' Research, Vol. 5 (2023)
Emergent BCS regime of the two-dimensional fermionic Hubbard model: ground-state phase diagram
Creators: name: Deng, Youjin
name: Kozik, Evgeny
name: Prokof'ev, Nikolay V.
name: Svistunov, Boris V.
Publisher: name: arXiv
Year: 2014
Subjects: subject: Strongly Correlated Electrons (cond-mat.str-el)
subject: Statistical Mechanics (cond-mat.stat-mech)
subject: Computational Physics (physics.comp-ph)
subject: FOS: Physical sciences

description: A significant part of the phase diagram of the two-dimensional fermionic Hubbard model for moderate interactions and filling factors ($U < 4, \, n<0.7$) is governed by effective Fermi liquid physics with weak BCS-type instabilities. We access this regime in a controlled way by a combination of the bold-line diagrammatic Monte Carlo method with an additional ladder-diagram summation trick and semi-analytic treatment of the weak instability in the Cooper channel. We obtain the corresponding ground-state phase diagram in the $(n,U)$ plane describing the competition between the $p-$ and $d-$wave superfluid states. We also claim the values of the dimensionless BCS coupling constants controlling the superfluid $T_c$ at the phase boundaries, which prove to be very small up to $U=4, n = 0.6$.
description: 5 pages, 5 figures
ArcCI Development
Creators: name: PATRICK O’BRIEN
name: ABISHEK KANTHAN
name: Spanbauer, Theodore
name: Hollar, Grady
name: Chaowei Yang
Publisher: name: Journal of Student-Scientists' Research
Year: 2023

description: Sea ice is important to study as it reflects climate change and the state of the environment. ArcCI is a utility which allows users to upload images of sea ice from online databases which can be cropped into smaller resolutions, which are segmented using a variety of algorithms via borders (e.g. the border between ice and water). The user can then categorize each segment as a different property (e.g. ice or water). Most standard methods have difficulty determining the difference between melt ponds and submerged ice, but through Polygon Neighbor Analysis, the regions surrounding a body of water with ice underneath can be used to determine the feature. This method can only be implemented with HSR (high resolution images), which are much larger in size and therefore more challenging to optimally process. The user interface is being updated alongside the development of a desktop variant of the app. Additionally, an artificial intelligence model is being trained by interns and the ArcCI development team to automate the process of segment labeling with the hope that the full process could be automated. With the assistance of Abishek Kanthan, an export script was added, giving users a method to extract the local data into a zip file to be shared for training.
description: Journal of Student-Scientists' Research, Vol. 5 (2023)
Comprehensive and Macrospin-Based Magnetic Tunnel Junction Spin Torque Oscillator Model - Part I: Analytical Model of the MTJ STO
Creators: name: Chen, Tingsu
name: Eklund, Anders
name: Iacocca, Ezio
name: Rodriguez, Saul
name: Malm, Gunnar
name: Åkerman, Johan
name: Rusu, Ana
Publisher: name: arXiv
Year: 2014
Subjects: subject: Mesoscale and Nanoscale Physics (cond-mat.mes-hall)
subject: FOS: Physical sciences

description: Magnetic tunnel junction (MTJ) spin torque oscillators (STO) have shown the potential to be used in a wide range of microwave and sensing applications. To evaluate potential uses of MTJ STO technology in various applications, an analytical model that can capture MTJ STO's characteristics, while enabling system- and circuit-level designs, is of great importance. An analytical model based on macrospin approximation is necessary for these designs since it allows implementation in hardware description languages. This paper presents a new macrospin-based, comprehensive and compact MTJ STO model, which can be used for various MTJ STOs to estimate the performance of MTJ STOs together with their application-specific integrated circuits. To adequately present the complete model, this paper is divided into two parts. In Part I, the analytical model is introduced and verified by comparing it against measured data of three different MTJ STOs, varying the angle and magnitude of the magnetic field, as well as the DC biasing current. The proposed analytical model is suitable for being implemented in Verilog-A and used for efficient simulations at device-, circuit- and system-levels. In Part II, the full Verilog-A implementation of the analytical model with accurate phase noise generation is presented and verified by simulations.
description: 8 pages, 4 figures
A high-resolution and efficient system for analyzing and labeling ice images
Creators: name: ABISHEK KANTHAN
name: PATRICK O’BRIEN
name: Spanbauer, Theodore
name: Chaowei Yang
Publisher: name: Journal of Student-Scientists' Research
Year: 2023

description: A well-known issue with our environment is global warming and climate change. The Arctic region is a key indicator that can be used to measure the effects of global warming. Arctic CyberInfrastructure (ArcCI) allows researchers and scientists to study this pressing issue through autonomous classification of aerial ice image data from the Arctic regions. In addition, ArcCI aims to be user-friendly and intuitive, featuring a simple interface that allows for quick labeling of ice structures using labels such as ice, shadows, and water. ArcCI was made to improve image management and processing, specifically for ice data. ArcCI primarily uses object-based image analysis (OBIA) methods with integrated machine learning and high spatial resolution data to accurately label images. A key component of the ArcCI infrastructure is its ability to classify images autonomously due to the various data training models used and the export script which allows for the ability to easily share labeled images. ArcCI helps enhance the accuracy and consistency of ice image analysis. This makes it a valuable asset in a diverse range of applications, from climate studies to ice navigation.
description: Journal of Student-Scientists' Research, Vol. 5 (2023)
Biorisk Management Case Study: Massachusetts Institute of Technology-Broad Foundry
Creators: name: Gordon, Ben
name: Casini, Arturo
name: Salm, Melissa
name: Brink, Kathryn
Publisher: name: Stanford Digital Repository
Year: 2023
Subjects: subject: Risk management

description: The MIT-Broad Foundry is a genetic design institute that developed methods for fast and large-scale engineering of genetic systems. The Foundry began as a collaboration between a university and research institute and received support primarily from U.S. government agencies, including the Department of Defense, and industry partners. The Foundry:
• sought to identify and manage risks associated with new technologies beyond those addressed in existing legal, federal, and institutional policies.
• created a culture of responsibility among staff by integrating a self-assessment tool into its routine operations and welcoming researcher participation in expert biosecurity review meetings.
• involved a broad set of stakeholders in biosecurity reviews including law enforcement, intelligence, defense, and policy experts as well as local physical and IT security professionals.
Energy Justice Implication of Large-scale Electric Vehicle Adoption
Creators: name: VICTOR WANG
name: Xu, Jie
Publisher: name: Journal of Student-Scientists' Research
Year: 2023

description: Electric vehicle (EV) sales have been growing exponentially, and the potential energy costs to support them are reflected on the bill of numerous households. Many studies address the effectiveness of incentives for large-scale EV adoption. However, the consequences of such an event, specifically the energy burden of supporting it, are not fully explored. The energy requirements of increased EV adoption will put upward pressure on wholesale prices, which collaborators at ISO-NE have forecasted using an industry-standard wholesale market simulator. Our goal is to find the effect of such changes in wholesale prices on the retail rate charged to consumers. To do so, we must determine which factors influence the retail rate, and whether the wholesale rate is a big factor. In this study, we have synthesized consensus from existing literature to a standardized retail rate accounting method. Using this method on historical data, we first verify the credibility of the method, then calculate the percentages that purchased power from the wholesale market contributes to the retail rate in various utilities. Overall, we found that large-scale EV adoption will have a high energy burden on consumers, which underscores the need for new policies to fairly distribute electricity costs.
description: Journal of Student-Scientists' Research, Vol. 5 (2023)
From Property Rights in Data Towards a Regulatory Framework in the Data Act - Sufficient to Empower Individuals?
Creators: name: Hinrichs
Publisher: name: Zenodo
Year: 2022
Subjects: Data Act
European Strategy for Data

description: With the abandonment of the idea of property rights in data, this poster looks into the new regulatory framework introduced by the Data Act and if it might be capable of reconciling diverging interests in data.
Can vortex quantum droplets be realized experimentally?
Creators: name: Li, Guilong
name: Zhao, Zibin
name: Liu, Bin
name: Li, Yongyao
name: Kartashov, Yaroslav V.
name: Malomed, Boris A.
Publisher: name: arXiv
Year: 2024
Subjects: subject: Quantum Gases (cond-mat.quant-gas)
subject: Pattern Formation and Solitons (nlin.PS)
subject: Optics (physics.optics)
subject: FOS: Physical sciences

description: The current state of research on vortices carried by quantum droplets (QDs) has predicted their existence, in the stable form, in two- and three-dimensional free-space binary Bose-Einstein condensates (BECs) and dipolar BECs. These theoretical results suggest that QDs may be excellent carriers of self-trapped vortex states. Given that the experimental creation of QDs has already been firmly established, the observation of embedded vortices in them becomes a key question for the next phase of the development in the field.
description: 6 pages, 1 figure, and 88 references. Accepted as the View & Perspective by Frontiers of Physics (http://journal.hep.com.cn/fop/EN/10.15302/frontphys.2025.013401)
Additional file 4 of Education interventions for health professionals on falls prevention in health care settings: a 10-year scoping review
Creators: name: Shaw, L.
name: Kiegaldie, D.
name: Farlie, M. K.
Publisher: name: figshare
Year: 2020
Subjects: Medicine
Biotechnology
Science Policy

description: Additional file 4. Presage and planning elements of education interventions
Gauge covariant solution for the Schwinger-Dyson equation in three-dimensional QED with Chern-Simons term
Creators: name: Hoshino, Yuichi
name: Inagaki, Tomohiro
name: Mizutani, Yuichi
Publisher: name: arXiv
Year: 2014
Subjects: subject: High Energy Physics - Phenomenology (hep-ph)
subject: High Energy Physics - Theory (hep-th)
subject: FOS: Physical sciences

description: An Abelian gauge theory with Chern-Simons term is investigated for a four-component Dirac fermion in 1+2 dimensions. The Ball-Chiu (BC) vertex function is employed to modify the rainbow-ladder approximation for the Schwinger-Dyson (SD) equation. We numerically solve the SD equation and show the gauge dependence for the resulting phase boundary for the parity and the chiral symmetry.
description: 16 pages, 7 figures, Published version
Literature Review of Electric Heavy Duty Vehicles and Charging Standards
Creators: name: MAXIMILIAN PIECH
name: Xu, Jie
Publisher: name: Journal of Student-Scientists' Research
Year: 2023

description: Battery electric transit buses are a technology experiencing a rapid rise in popularity due to high fuel prices and the need to stop climate change. This literature review will explore the strategies and successes of the rollout of electric buses by transit agencies, different available high power charging standards, the funding for the transition to electric buses and related infrastructure, and the possibility of increased energy density for future batteries. Transit agencies have rolled out battery electric buses with varying rates of success, from one having an exclusively electric fleet to one giving up entirely on battery buses. The three primary charging methods are by cable, by an overhead port, and wirelessly with inductive charging. Transit agencies can take advantage of numerous state and federal grants to upgrade their fleets with new buses and charging stations. There is significant room for improvement in the energy density of lithium ion batteries.
description: Journal of Student-Scientists' Research, Vol. 5 (2023)
title: Ο σύνθετος κόσμος της Μηχατρονικής και οι εφαρμογές της

title: The complex world of Mechatronics and its applications

Creators: name: Σαββακης Δημοσθενης
Publisher: name: Technical University of Crete
Year: 2022

description: Η παρούσα διπλωματική εργασία, μας εισάγει στον σύνθετο "κόσμο" της μηχατρονικής δίνοντάς μας πληροφορίες για το τί είναι η μηχατρονική, ποιο είναι το αντικείμενό της, από τι αποτελείται αλλά και που τη συναντάμε στην καθημερινότητά μας.
 Αρχικά, θα μιλήσουμε γενικά για το επιστημονικό πεδίο της μηχατρονικής. Ειδικότερα θα αναφέρουμε τον ορισμό της, το πώς ξεκίνησε, τα βασικά χαρακτηριστικά της αλλά και της αναγκαιότητα της χρήσης της.
 Έπειτα, θα παρουσιαστούν τα αισθητήρια και οι ενεργοποιητές με τους ορισμούς τους αλλά και με διάφορες εφαρμογές τους. Θα αναφερθούν τα χαρακτηριστικά τους αλλά και όλα τα είδη τους με τη χρήση παραδειγμάτων.
 Αναφορά θα γίνει και για το ευθύ αλλά και για το αντίστροφο φαινόμενο του πιεζοηλεκτρισμού με τις λειτουργίες και τις εφαρμογές του.
 Στη συνέχεια, θα γίνει μία ιστορική αναδρομή για τα πνευματικά συστήματα, και θα αναφερθούν τα βασικά στοιχεία των πνευματικών συστημάτων αλλά και τα πλεονεκτήματα-μειονεκτήματα τους.
 Τέλος, θα παρουσιαστούν διάφορα παραδείγματα και εφαρμογές της Μηχατρονικής στο παρόν καθώς και μεθόδους με τις οποίες θα μπορούσαμε να την "εκμεταλλευτούμε" ώστε να διευκολύνει τη ζωή μας στο μέλλον.

description: This project, introduces us to the complex "world" of Mechatronics, giving us information on what Mechatronics is, what it is about, what it is made of, and where we encounter it in our daily lives.
First of all, we will talk generally about the scientific field of mechatronics. In particular, we will mention its definition, how it all started, its basic characteristics and the necessity of its usage.
Then, the sensors and actuators will be presented with their definitions but also with their various applications. Their main characteristics will be attributed and their various types will be recorded with the use of examples.
Reference will also be made to the direct and inverse phenomenon of piezoelectricity with its functions and applications.
Then, a historical review of pneumatic systems will be made, and the basic elements of pneumatic systems will be mentioned as well as their advantages-disadvantages.
Finally, various examples and applications of Mechatronics in the present will be presented as well as ways in which we could "harness" it to make our lives easier in the future.
title: Das Problem des positiven Tests
Creators: name: Garofalo, Luca
Year: 2021

description: Das Ziel der vorliegenden Masterarbeit war es, das Thema bedingte Wahrscheinlichkeit auf der einen Seite mathematisch und auf der anderen Seite fachdidaktisch aufzuarbeiten. Sie sollte einen Überblick über bedingte Wahrscheinlichkeiten bieten. Dabei wurden zunächst die wichtigsten mathematischen Begriffe zum Thema behandelt. Auf dieser Grundlage wurde dann ein Beispiel angeführt, welches als möglicher Einstieg zum Thema in der Schule dienen kann. Dabei wurde noch auf mögliche Lernschwierigkeiten Bezug genommen, auf welche die Lehrperson Rücksicht nehmen sollte. Abschließend wurden noch diverse stochastische Paradoxa vorgestellt, welche ebenfalls für die Schule geeignet sind.
Precise determination of Z-Z' mixing at the CERN LHC
Creators: name: Andreev, V. V.
name: Osland, P.
name: Pankov, A. A.
Publisher: name: arXiv
Year: 2014
Subjects: subject: High Energy Physics - Phenomenology (hep-ph)
subject: FOS: Physical sciences

description: We discuss the expected sensitivity to Z' boson effects in the W^\pm boson pair production process at the Large Hadron Collider (LHC). The results of a model-dependent analysis of Z' boson effects are presented as constraints on the Z-Z' mixing angle phi and Z' boson mass. The process pp\to W^+W^- + X allows to place stringent constraints on the Z-Z' mixing angle. Specifically, we find that the present LHC bounds on the mixing angle are of the order a few times 10^{-3}, what is of the same order as those derived from the electroweak data. These results were derived from analysis of W-pair production at sqrt{s}=8 TeV and integrated luminosity of 20 fb^{-1}. Further improvement on the constraining of this mixing can be achieved from the analysis of data on WW \to l nu l'nu' (l,l'=e or mu) and WW \to l nu jj final states collected at the LHC with nominal energy and luminosity, 14 TeV and 100 fb^{-1}, and should be phi \sim 10^{-4}-10^{-3}.
description: 22 pages, 7 figures. PRD version
Collision Risk Model Simulations with Data-Driven Models and Examining the Impact and Strategies of Electrical Vehicle Grid Integration
Creators: name: JULIENNE LIM
name: Xu, Jie
Publisher: name: Journal of Student-Scientists' Research
Year: 2023

description: Collision risk models (CRMs) and electric vehicle (EV) grid integration are pivotal aspects in the domain of transportation and energy management. CRMs aim to assess and predict the probability of collisions involving diverse airplane models with the ultimate goal of enhancing safety in transportation. These models consider a variety of factors, such as airplane models, environmental conditions, traffic patterns, and human behavior, providing valuable insights to implement effective safety measures and traffic management strategies. CRMs have shifted towards data-driven models, departing from traditional physics-based approaches, to attain more precise trajectory paths for airplanes, leveraging large-scale real-world data and machine learning algorithms. Multiple algorithms were investigated for the purpose of carrying out a simulation study and analyzing flight trajectories. Concurrently, with EV grid integration, a systematic screening analysis is aimed at identifying utility company executives for a focus group study, exploring the impact of large-scale EVs on the electric grid, with a specific focus on electricity price dynamics. This interdisciplinary investigation merges principles from engineering and social sciences to comprehensively examine the challenges and opportunities arising from EV integration into the grid. By leveraging this collaborative approach, valuable insights can be gained, aiding in the development of effective strategies to address grid management and pricing concerns, and ultimately fostering a sustainable and efficient EV-grid integration. In conclusion, the intersection of collision risk models and electric vehicle grid integration represents a comprehensive approach to enhance safety in transportation and promote sustainable energy management. By embracing data-driven models and interdisciplinary investigations, we gain valuable insights into collision probabilities and electricity price dynamics, enabling the development of effective strategies for safer and more efficient transportation.
description: Journal of Student-Scientists' Research, Vol. 5 (2023)
Creating a Discrete Event Simulation Model for the Allocation of Donor Hearts
Creators: name: JESSICA CHEN
name: Xu, Jie
Publisher: name: Journal of Student-Scientists' Research
Year: 2023

description: Heart transplantation surgery is a procedure performed on patients with end-stage heart disease and is sometimes life-saving. When a donor heart becomes available, end-stage heart disease patients on a waitlist are allocated through a match run that generates a priority list of patients who can receive the donor heart based on factors such as blood type, medical status, distance to donor, etc. Each patient’s doctor is then contacted according to priority, and a decision is made to either accept or reject the donor heart. Although simulations and machine learning models have been created to aid medical professionals in the matching process of other types of organ transplantation, their applications in heart transplantation remain to be explored. In this study, the framework of a discrete event computer simulation model is developed for the national heart transplant system. This simulation will handle the match run allocation, create a priority list, make a accept/reject decision, and output results. As a result, the final product will be a dependable foundation for future researchers to add more sophisticated decision-making and prediction modules.
description: Journal of Student-Scientists' Research, Vol. 5 (2023)
Additional file 1 of Professionalism in traditional Chinese medicine (TCM) practitioners: a qualitative study
Creators: name: Kwan, Yu Heng
name: Chooi, Sarah
name: Sungwon Yoon
name: Ang, Xiang Ling
name: Phang, Jie Kie
name: Hwee Ling Koh
name: Thumboo, Julian
name: Swee Cheng Ng
name: Fong, Warren
Publisher: name: figshare
Year: 2020
Subjects: subject: Medicine
subject: 69999 Biological Sciences not elsewhere classified
subject: FOS: Biological sciences
subject: Cancer
subject: Science Policy

description: Additional file 1.
Optimal Computing Budget Allocation for Monte Carlo Tree Search has been demonstrated to be a better tree policy than Upper Confidence bounds applied to Trees in the game of Othello
Creators: name: DANIEL QIU
name: Xu, Jie
Publisher: name: Journal of Student-Scientists' Research
Year: 2023

description: Through this internship, we aim to try to find better methods for selecting the best action from a set of choices using tree search. We chose to use Monte Carlo Tree Search with Optimal Computing Budget Allocation (MCTS-OCBA) tree policy as a way to find the best choice from a given set of moves from the board game Othello. Monte Carlo Tree search uses many simulations from a certain board state to generate a search tree with, and eventually choose the best move. A tree policy is the way one would choose the move to assign the next simulation given already collected information. Previously, the most widely accepted tree policy for MCTS was Upper Confidence bounds applied to Trees (MCTS-UCT). A newer algorithm, MCTS-OCBA, has recently been demonstrated to be more accurate than MCTS-UCT in solved board games, such as Tic-Tac-Toe, but has not been tested against MCTS-UCT in unsolved board games with larger board states such as Othello. We try to demonstrate that OCBA is a better tree policy than UCT for MCTS by creating an Othello game engine. From our results, MCTS-OCBA performed much better than MCTS-UCT when the number of nodes added to a tree is small, but asymptotically approaches MCTS-UCT’s success in Othello. We tried adding a heuristic, and experiment results suggested that adding a heuristic further improves MCTS-OCBA’s success over MCTS-UCT.
description: Journal of Student-Scientists' Research, Vol. 5 (2023)
All optical quantum storage based on spatial chirp of the control field
Creators: name: Zhang, Xiwen
name: Kalachev, Alexey
name: Kocharovskaya, Olga
Publisher: name: arXiv
Year: 2014
Subjects: subject: Quantum Physics (quant-ph)
subject: FOS: Physical sciences

description: We suggest an all-optical quantum memory scheme which is based on the off-resonant Raman interaction of a signal quantum field and a strong control field in a three-level atomic medium in the case, when the control field has a spatially varying frequency across the beam, called a spatial chirp. We show that the effect of such a spatial chirp is analogous to the effect of a controllable reversible inhomogeneous broadening (CRIB) of the atomic transition used in the gradient echo memory (GEM) scheme. However, the proposed scheme does not require temporal modulation of the control field or the atomic levels, and can be realized without additional electric or magnetic fields. It means that materials demonstrating neither linear Stark nor Zeeman effects can be used and/or materials which are placed in specific external fields remain undisturbed.
title: Die Auswirkungen von K-Pop Marketingmaßnahmen auf dessen internationalen Erfolg und auf das Konsumentenverhalten internationaler Fans
Creators: name: Bastug, Deniz
Year: 2021

description: Ziel der vorliegenden Forschung ist es einerseits, relevante Marketingmaßnahmen zu erläutern, die zum internationalen Erfolg von K-Pop geführt haben, und andererseits die Auswirkungen des globalen Erfolges von K-Pop auf das Konsumentenverhalten internationaler Fans zu untersuchen. Das Erhebungsinstrument stellte dabei ein standardisierter Fragebogen dar, der von 1472 internationalen K-Pop Fans beantwortet wurde. Die Auseinandersetzung mit der vorhandenen Literatur sowie die quantitative Datenerhebung ergaben, dass das Zusammenspiel verschiedener Online- und Offline-Marketingmaßnahmen den internationalen Erfolg von K-Pop fördern, und dass dieser Erfolg das Konsumentenverhalten der internationalen K-Pop Fans positiv beeinflusst.
description: The aim of this study is, on the one hand, to explain relevant marketing activities that have led to the international success of K-pop and, on the other hand, to examine the effects of the global success of K-pop on the consumer behavior of international fans. The research instrument was a standardized questionnaire that was answered by 1472 international K-pop fans. The examination of the existing literature as well as the quantitative data acquisition showed that the interaction of various online and offline marketing activities contributes to the international success of K-pop, which also has a positive influence on the consumer behavior of international K-pop fans.
Combined current control and system identification of a PMSM with neural ordinary differential equations
Creators: name: Meyer, Marvin
Publisher: name: Universität Paderborn
Year: 2022

description: This thesis deals with current control and system identification of a permanent magnet synchronous machine. To learn a data-driven controller for current control, a model of the motor is required. Such model can be constructed with the utilization of neural ordinary differential equations. Through this approach, expert knowledge can be used in combination with learnable parameters to identify the motor parameters. With the help of this model, a neural network can then be trained to control the current. The proposed approach will be compared with both model-based and model-free methods for current control.
Incidence bounds on multijoints and generic joints
Creators: name: Iliopoulou, Marina
Publisher: name: arXiv
Year: 2014
Subjects: subject: Combinatorics (math.CO)
subject: FOS: Mathematics

description: A point $x \in \mathbb{F}^n$ is a joint formed by a finite collection $\mathfrak{L}$ of lines in $\mathbb{F}^n$ if there exist at least $n$ lines in $\mathfrak{L}$ through $x$ that span $\mathbb{F}^n$. It is known that there are $\lesssim_n |\mathfrak{L}|^{\frac{n}{n-1}}$ joints formed by $\mathfrak{L}$. We say that a point $x \in \mathbb{F}^n$ is a multijoint formed by the finite collections $\mathfrak{L}_1,\ldots,\mathfrak{L}_n$ of lines in $\mathbb{F}^n$ if there exist at least $n$ lines through $x$, one from each collection, spanning $\mathbb{F}^n$. We show that there are $\lesssim_n (|\mathfrak{L}_1|\cdots |\mathfrak{L}_n|)^{\frac{1}{n-1}}$ such points for any field $\mathbb{F}$ and $n=3$, as well as for $\mathbb{F}=\mathbb{R}$ and any $n \geq 3$. Moreover, we say that a point $x \in \mathbb{F}^n$ is a generic joint formed by a finite collection $\mathfrak{L}$ of lines in $\mathbb{F}^n$ if each $n$ lines of $\mathfrak{L}$ through $x$ form a joint there. We show that, for $\mathbb{F}=\mathbb{R}$ and any $n \geq 3$, there are $\lesssim_n \frac{|\mathfrak{L}|^{\frac{n}{n-1}}}{k^{\frac{n+1}{n-1}}}+\frac{|\mathfrak{L}|}{k}$ generic joints formed by $\mathfrak{L}$, each lying in $\sim k$ lines of $\mathfrak{L}$. This result generalises, to all dimensions, a (very small) part of the main point-line incidence theorem in $\mathbb{R}^3$ in \cite{Guth_Katz_2010} by Guth and Katz. Finally, we generalise our results in $\mathbb{R}^n$ to the case of multijoints and generic joints formed by real algebraic curves.
description: Some errors corrected. Theorem 4.4 is now slightly stronger than its previous version. To appear in Discrete Comput. Geom
Advancing Collision Risk Models in Terminal Airspace using BlueSky Simulator and Gaussian Process Regression
Creators: name: ANGELA ZHANG
name: MIHIR GHAWGHAWE
name: SANA AMER
name: SANA AMER
name: Xu, Jie
Publisher: name: Journal of Student-Scientists' Research
Year: 2023

description: In recent years, with the rapid growth in air traffic and the increasing complexity of terminal airspace operations, the need for reliable collision risk models has become paramount. This research sought to address the field of collision risk models, specifically through the BlueSky simulator and Gaussian Process Regression (GPR). Existing models require high computational power and large trajectory datasets. One of the primary struggles faced was the lack of easily accessible and relevant data. Many aviation datasets are either proprietary and could not be used to validate and refine our models. Furthermore, gaining a comprehensive understanding of collision risk models was difficult. The majority of time was spent conducting literature review to contribute to a report. This research used BlueSky, a versatile, open-source tool designed for conducting simulations of air traffic. The BlueSky simulator allows for a more controlled environment for experimenting with GPR than aviation datasets available online. BlueSky was utilized to create synthetic flight trajectories and collect corresponding data on latitude, longitude, and altitude. JupyterLab and Scikit-Learn were used to experiment with GPR kernels and their hyperparameters. While valuable insights were gained in creating synthetic trajectories and selecting functions to describe aircraft data, further investigation is needed to enhance the accuracy and applicability of these models in real-world scenarios.
description: Journal of Student-Scientists' Research, Vol. 5 (2023)