cometadata/datacite-rtg-text-other-reclassification-records huggingface dataset:
sj-pdf-1-epb-10.1177_23998083211040519 - Supplemental material for A framework for delineating the scale, extent and characteristics of American retail centre agglomerations
Creators: name: Ballantyne, Patrick
name: Singleton, Alex
name: Dolega, Les
name: Credit, Kevin
Publisher: name: SAGE Journals
Year: 2021
Subjects: subject: Geography
subject: 120599 Urban and Regional Planning not elsewhere classified
subject: FOS: Social and economic geography

description: Supplemental material, sj-pdf-1-epb-10.1177_23998083211040519 for A framework for delineating the scale, extent and characteristics of American retail centre agglomerations by Patrick Ballantyne, Alex Singleton, Les Dolega and Kevin Credit in EPB: Urban Analytics and City Science
FACILITATING MANAGEMENT AND DECISION-MAKING ON PRIVATE AND PUBLIC FORESTS IN INDIANA
Creators: name: MacGowan, Brian J
Publisher: name: Purdue University Graduate School
Year: 2021
Subjects: Forestry management and environment

description: Active forest management is generally considered a desirable approach for both private and public tracts. While stakeholder collaboration and input are used on public lands, states have used several approaches to facilitate forest management on private forests including property tax-incentive programs, cost-share and technical assistant programs, and professional advice. Some researchers have studied how educational programs can facilitate woodland management on private lands. While some determined that the adoption of management practices can be influenced, in part, by attending educational programs, understanding of the factors that contribute to successful outcomes of educational programs for family forest owners is limited. Similarly, many federal and state agencies have used stakeholder input to inform natural resource management and policy in a variety of collaborative formats. In Indiana, the Indiana Forest Stewardship Coordinating Committee has provided input into private and public forest management in the state since 2010. Using a case-study approach, this dissertation, through mail surveys and interviews, examined the role of the Forest Management for the Private Woodland Owner eight-week short course in woodland owner management decisions. Findings suggest that, across behaviors, woodland owner attitudes about and reasons for owning their woodlands were the most consistent predictors of the level of influence the course had on participants. Enrollment in the Indiana Classified Forest and Wildlands Program and likelihood of attending future educational programs were also positively associated with course influence for some behaviors while contact with the instructor after the course and owning woods for privacy had negative associations. The course played a role in different stages of the decision-making process of woodland owners to harvest timber, control invasive plants, create a written management plan, and use the services of a professional forester. Compatibility and relative advantage of a practice were important factors in adoption decisions. I also interviewed members of the Indiana Forest Stewardship Coordinating Committee to investigate its perceived value to members and how they view its contributions to forest management in the state. Overall, members generally held a positive perspective of its value and thought the committee benefited Indiana’s forests although there was limited evidence to support this viewpoint. The committee followed some recommended collaborative approaches, but fell short on others. Findings inform several recommendations that could benefit the committee and its role in the future.
Degradationsmechanismen großformatiger Lithium-Ionen-Batterien für Elektrofahrzeuge
Creators: name: Lang, Michael
Publisher: name: Karlsruhe
Year: 2018
Subjects: Lithium-Ionen-Batterien
Lithium-Ionen-Zellen
Blend
NCA
NCM
NMC
LMO
Degradation
Alterung
Ermüdung
Solid-Electrolyte-Interphase
SEI
Mikrorisse
Manganauslösung
Elektromobilität
60 Ah
Zyklierung
Lagerung

description: Die Degradationsmechanismen kommerzieller 60 Ah-Lithium-Ionen-Batterien (LIBs) wurden unter dem Einfluss verschiedener Betriebsparameter untersucht und mit einer Begin-of-Life (BoL)-Zelle verglichen. Die Zellen beinhalteten einen Kathodenblend aus LiNi0,8Co0,15Al0,05O2 (NCA), LiNi0,5Co0,2Mn0,3O2 (NCM) sowie LiMn2O4 (LMO) und Graphit als Anodenmaterial. Sowohl die Zyklierung als auch die Lagerung der Zellen führten zum Verlust aktiven Lithiums, wodurch die Kapazität der Zellen abnahm. Aktives Lithium wurde hauptsächlich durch das Wachstum und die Restrukturierung der Solid Electrolyte Interphase (SEI) verbraucht. Die Erhöhung der Zykliertemperatur von 25 °C auf 40 °C verstärkte diesen Verlust deutlich, wohingegen die Erhöhung der Lade-/Entladeraten von 1C/2C auf 2C/3C eine geringfügigere Verstärkung herbeiführte. Die Erhöhung der Lagertemperatur von 40 °C auf 60 °C führte ebenfalls zu einem starken Anstieg des Aktivlithiumverlusts. Eine Ermüdung der Kathode wurde zudem im Falle aller zyklierten Zellen festgestellt. Die Schichtoxide NCA und NCM bildeten Mikrorisse aus und wiesen Oberflächenveränderungen auf. Letzterer Effekt erhöhte die Überpotentiale und senkte die Ratenbeständigkeit der Kathode, wodurch sich ratenabhängige Kapazitätsverluste der Kathode ergaben. Die Temperaturerhöhung von 25 °C auf 40 °C verstärkte die Effekte, während die Ratenerhöhung kaum Einfluss darauf nahm. Das LMO zeigte bei 25 °C keine signifikante Ermüdung, während bei 40 °C ein Verlust von Manganspezies festgestellt werden konnte, welche dem LMO zugewiesen wurden. Dadurch ergab sich für das LMO ein phasenspezifischer Kapazitätsverlust, auf welchen die Änderung der Rate nur einen sehr geringen Einfluss hatte.
title: An End-To-End Learning Framework for Supporting Green Neuromorphic Computing
title: From RRAM Design and Microfabrication to Applications
titleType: Subtitle
Creators: name: Vicenciodelmoral, Abdi  Yamil
Publisher: name: Washington State University
Year: 2025
Subjects: Deep Learning
Neural Networks
Neuromorphic Computing
Resistive Random Access Memory
Machine Learning
Materials Science

description: Conventional computing systems are commonly organized with a separate memory and CPU units, leaving them vulnerable to the von Neumann bottleneck. This stems from the data transfer rate between the CPU and memory, which is approximately one hundred times slower than the CPU processing speed \cite{pacheco}. The von Neumann bottleneck can significantly hinder computing or memory intensive executions that require processing large amounts of data, such as machine learning or deep learning algorithms. The increasing demand of data processing requirements and extensive use of computer-intensive applications has driven the research and development of energy-efficient hardware implementations for nonvolatile memory. Fabricating efficient memory devices for high-performance computing systems can be a costly and time-consuming process, particularly when relying on traditional trial-and-error methods that involve repetitive testing and modification until successful designs have been developed. The manufacturing process of optimal memory units can be potentially facilitated through the use of advanced evaluation methods and predictive analysis. Machine learning and deep Learning methods have emerged as powerful and effective tools for constructing predictive models that can be used to optimize the fabrication process for various devices and technologies,including non-volatile memory. In this research, we propose a general learning framework for predicting the behavioral properties and potential learning capabilities of memory devices used in neuromorphic computing, by employing machine learning and deep learning algorithms. This study focuses on resistive random access memory (RRAM) as a case study, however, the proposed workflow can be generally applied to other device fabrication analysis aiming to investigate variability and distributions. RRAM is of particular interest as it has demonstrated the potential for high energy and computational efficiency in computing vector-matrix multiplications, a key operation in neural network algorithms. The proposed workflow demonstrates how the application of learning models can facilitate the development of optimal devices for neuromorphic computing, ultimately leading to more efficient and cost-effective fabrication and manufacturing processes.
Understanding curvature-matter interaction in viable $f(R)$ dark energy models: A dynamical analysis approach
Creators: name: Chatterjee, Anirban
name: Gong, Yungui
Publisher: name: arXiv
Year: 2024
Subjects: subject: General Relativity and Quantum Cosmology (gr-qc)
subject: FOS: Physical sciences

description: We employ a linear stability analysis approach to explore the dynamics of matter and curvature-driven dark energy interactions within the framework of two types of viable $f(R)$ gravity models. The interaction is modeled via a source term in the continuity equations, $\mathcal{Q} = α\tildeρ_{\rm m} \Big{(}\frac{3H^3}{κ^2 ρ_{\rm curv}} + \frac{κ^2 }{3H}ρ_{\rm curv} \Big{)}$. Our results reveal significant modifications to the fixed points and their stability criteria compared to traditional $f(R)$ gravity analyses without matter-curvature coupling. We identify constraints on model and coupling parameters necessary for critical point stability, illustrating how the interaction influences cosmic dynamics within specific parameter ranges. The findings are consistent with observed cosmic evolution, supporting stable late-time acceleration. Moreover, we highlight the coupling parameter's potential role in addressing the cosmic coincidence problem.
description: 45 pages, 2 tables and 7 figures. Latest version has been accepted for publication in 'Annals of Physics'
"DEVONU LUG'OTIT TURK" ASARINING NEGIZ DIALEKTI
Creators: name: Roziqova, G.
name: Ismoiljonova, M.
name: Mahammadjonova, U.
Publisher: name: Zenodo
Year: 2025

description: Mahmud Koshg‘ariyning “Devonu lug‘otit turk” asari oddiy lug‘at emas, balki XI asr turkiy tillarining fonetikasi, leksikasi, dialektologiyasi va tarixiy taraqqiyotini chuqur ilmiy asosda aks ettirgan nodir manbadir. Ushbu maqolada asardagi qadimgi turkiy tilning turli dialekt shakllari, semantik farqlari va uslubiy boyligi yoritilgan.
Human populations in the world's mountains: Spatio-temporal patterns and potential controls
Creators: name: GEO Mountains
Publisher: name: GEO Knowledge Hub
Year: 2022
Subjects: mountains
population
urbanization
GEO Mountains

description: Supplementary Information (data, code, and figures) for "Human populations in the world's mountains: Spatio-temporal patterns and potential controls (Thornton et al. 2022; https://doi.org/10.1371/journal.pone.0271466). The project involved collaboration between GEO Mountains, GEO Human Planet, and other organisations. The code provided enables the results of the study to be replicated, and the workflow transferred or extended to other applications.
Spectral Multiplexing and Information Processing for Quantum Networks
Creators: name: Lingaraju, Navin Bhartoor
Publisher: name: Purdue University Graduate School
Year: 2021
Subjects: Quantum optics and quantum optomechanics
Quantum information, computation and communication
Photonics, optoelectronics and optical communications
Electrical engineering not elsewhere classified
Optical fibre communication systems and technologies

description: Modern fiber-optic networks leverage massive parallelization of communications channels in the spectral domain, as well as low-noise recovery of optical signals, to achieve high rates of information transfer. However, quantum information imposes additional constraints on optical transport networks – the no-cloning theorem forbids use of signal regeneration and many network protocols are premised on operations like Bell state measurements that prize spectral indistinguishability. Consequently, a key challenge for quantum networks is identifying a path to high-rate and high-fidelity quantum state transport.
To bridge this gap between the capabilities of classical and quantum networks, we developed techniques that harness spectral multiplexing of quantum channels, as well as that support frequency encoding. In relation to the former, we demonstrated reconfigurable connectivity over arbitrary subgraphs in a multi-user quantum network. In particular, through flexible provisioning of the pair source bandwidth, we adjusted the rate at which entanglement was distributed over any user-to-user link. To facilitate networking protocols compatible with both spectral multiplexing and frequency encoding, we synthesized a Bell state analyzer based on mixing outcomes that populate different spectral modes, in contrast to conventional approaches that are based on mixing outcomes that populate different spatial paths. This advance breaks the tradeoff between the fidelity of remote entanglement and the spectral distinguishability of photons participating in a joint measurement.

Finally, we take steps toward field deployment by developing photonic integrated circuits to migrate the aforementioned functionality to a chip-scale platform while also achieving the low loss transmission and high-fidelity operation needed for practical quantum networks.
Additional file 2 of Attenuation of Alzheimer’s brain pathology in 5XFAD mice by PTH1-34, a peptide of parathyroid hormone
Creators: name: Chen, Li
name: Xiong, Lei
name: Yao, Lingling
name: Pan, Jinxiu
name: Arzola, Emily
name: Zhu, Xiaojuan
name: Mei, Lin
name: Xiong, Wen-Cheng
Publisher: name: figshare
Year: 2024
Subjects: subject: Biochemistry
subject: Medicine
subject: Cell Biology
subject: Neuroscience
subject: Physiology
subject: FOS: Biological sciences
subject: Immunology
subject: FOS: Clinical medicine
subject: Cancer
subject: Hematology

description: Additional file 2: Supplemental file 1. Two-way ANOVA analysis results.
Partition Theory
Creators: name: Oueis, Yanal
Publisher: name: Purdue University Graduate School
Year: 2021
Subjects: Theoretical and computational chemistry not elsewhere classified

description: Partition Theory (PT) is a quantum chemistry method for simplifying a molecular calculation by breaking it down into fragment calculations. This “fragmentation” can lead to more efficient and/or more accurate results. The work in this thesis concerns studying fundamental aspects of PT and exact properties of energy functionals used in PT. We hope that these properties can be used for the development of feasible approximations to PT functionals.We implemented PT so that it can be solved numerically exactly for model systems in 1D. We used this implementation to study exact properties of the partition potential (a fictitious one-body potential used in PT to recover inter-fragment interactions). Our implementation can be used to study non-interacting and interacting electrons in 1D. We extended PT to systems supporting continuous electronic states (e.g., metals and metalsurfaces) and demonstrated this method using a model system in 1D. We derived an exact virial relation for fragment energies and tested it on simple diatomic molecules in 3D. Finally, we studied properties of the partition potentials obtained through numerical inversions of formic acid dimer systems in 3D.
title: Beyond the Scene of the Crime: Investigating Place in Golden Age Detective Fiction
Creators: name: Bright, Brittain
Publisher: name: Goldsmiths, University of London
Year: 2015
Subjects: subject: detective, crime, place, scene, setting, space, Golden Age, Agatha Christie, Dorothy L. Sayers, Gladys Mitchell

description: Place is both physical and conceptual; in fiction, place offers an initial basic orientation, but also fulfills many more complex roles. This thesis considers place in the Golden Age detective novels of Agatha Christie, Gladys Mitchell, and Dorothy L. Sayers to establish place as a point of critical engagement, and uses place to re-consider influential works in the genre. The exploration of place uncovers textual clues that are not necessarily detective clues, complicating these novels and dismantling deceptive assumptions about the homogeneity of the Golden Age.

The evidential place, or “the scene of the crime”, provides a physical setting for the crime itself and the clues that it generates, but it is rarely the most important or revelatory place in a detective story. Christie developed a place-typology that defined much of her work: the house, the village, London, and the holiday convey distinct meanings from early in her career. These places evolve over decades of social commentary, but each maintains a core of structural meaning. Character and place often develop in tandem, and Mitchell is particularly interested in the distortions of the relationship between the two. She rejects the rationality of the genre, and uses place and focalization to embed psychological questioning in her novels. Sayers considers place a central “artistic unity” of the novel. She presents place as a socially constructed unit, and through notions of “belonging” or being “out of place”, she interrogates structures of milieu. Place becomes a central focal point in her later novels, through which she questions contemporary values and identities.

In all of these authors’ work, the detective is a figure representative of modernity, developed through his or her relationship to place. Place also takes the investigation outside of purely plot-based channels, and into sociological and psychological areas of questioning.
title: Studies on customisation-driven digital music instruments
Creators: name: Zamborlin, Bruno
Publisher: name: Goldsmiths, University of London
Year: 2015
Subjects: subject: Computer-Human Interaction, Computer Music, Gestural Interaction, New Interfaces for Musical Expression

description: From John Cage’s Prepared Piano to the turntable, the history of musical instruments is scattered with examples of musicians who deeply customised their instruments to fit personal artistic objectives, objectives that differed from the ones the instruments have been designed for. In their digital counterpart however, musical instruments are often presented in the form of closed, finalised systems with apriori symbolic rules set by their designer that leave very little room for the artists to customise the technologies for their unique art practices; in these cases the only possibility to change the mode of interaction with digital instrument is to reprogram them, a possibility available to programmers but not to musicians.

This thesis presents two digital music instruments designed with the explicit goal of being highly customisable by musicians and to provide different modes of interactions, whilst keeping simplicity and immediateness of use. The first one leverages real-time gesture recognition to provide continuous feedback to users as guidance in defining the behaviour of the system and the gestures it recognises. The second one is a novel tangible user interface which allows to transform everyday objects into expressive digital music instruments, and whose sound generated strongly depends by the particular nature of the physical object selected.
Additional file 3 of Attenuation of Alzheimer’s brain pathology in 5XFAD mice by PTH1-34, a peptide of parathyroid hormone
Creators: name: Chen, Li
name: Xiong, Lei
name: Yao, Lingling
name: Pan, Jinxiu
name: Arzola, Emily
name: Zhu, Xiaojuan
name: Mei, Lin
name: Xiong, Wen-Cheng
Publisher: name: figshare
Year: 2024
Subjects: subject: Biochemistry
subject: Medicine
subject: Cell Biology
subject: Neuroscience
subject: Physiology
subject: FOS: Biological sciences
subject: Immunology
subject: FOS: Clinical medicine
subject: Cancer
subject: Hematology

description: Additional file 3: Supplemental file 2. Full western blots.
Constriction and contact impedance of ceramic solid electrolytes
Creators: name: Limon, Md Salman Rabbi
name: Duffee, Curtis
name: Ahmad, Zeeshan
Publisher: name: arXiv
Year: 2025
Subjects: subject: Materials Science (cond-mat.mtrl-sci)
subject: Applied Physics (physics.app-ph)
subject: FOS: Physical sciences

description: The development of solid-state batteries (SSBs) is hindered by degradation at solid-solid interfaces due to void formation and contact loss, resulting in increased impedance. Here, we systematically investigate the roles of real and unrecoverable interfacial contact areas at the electrode/Li$_6$PS$_5$Cl interface in driving the impedance rise. By controlling contact geometries and applied pressures, we identify their distinct contributions to the impedance spectra and quantify their influence on the interfacial resistance and transport. Experiments reveal that interfacial resistance varies strongly with recoverable contact area and applied pressure following power law scaling, with exponents of -1 and -0.5, respectively. Moreover, distributed contacts result in lower impedance due to smaller potential gradients and a more uniform potential distribution. Continuum simulations of the contact geometries predict interfacial resistances in agreement with experiments. Our work highlights the influence of unrecoverable and recoverable contact losses on SSB impedance while quantifying the effectiveness of mitigation strategies.
description: 19 pages, 6 figures + 17 pages of Supporting Information
Immc: I Make Meetings Carefully
Creators: name: Li, Kevin S
name: Greising, Maeve F
name: Hilton, Evan
Publisher: name: Zenodo
Year: 2017

description: In a globally connected society, international meetings are becoming increasingly common, but this takes away little of the burden in planning or attending them. Thus, when planning an international scientific or business meeting, it is exceedingly important to choose a meeting location such that attendees will be able to contribute at peak productivity. We present an algorithm to determine the best meeting location for any given group of attendees by modeling the problem as a network of interconnected optimization problems, and we developed an advanced Java program that utilizes hundreds of thousands of custom­-crafted data entries and calls to the Google API to model the impact of jet lag and climate shock on attendees.
Additional file 1 of Personal determinants of change agents’ decision-making behavior in community health promotion: a qualitative study
Creators: name: Paulsen, Lisa
name: Benz, Lea
name: Müller, Christina
name: Wallmann-Sperlich, Birgit
name: Bucksch, Jens
Publisher: name: figshare
Year: 2024
Subjects: subject: Medicine
subject: Sociology
subject: FOS: Sociology
subject: Biological Sciences not elsewhere classified
subject: Cancer
subject: Science Policy

description: Additional file 1. Interview guide: Decision-makers from local politics and government.
Additional file 1 of Association study of FLT4 and HYDIN single nucleotide polymorphisms with atrial septal defect susceptibility in the Han Chinese population of Southwest China
Creators: name: Jin, Ye
name: Zhao, Miao
name: Guo, Qiuzhe
name: Zhao, Wanyu
name: Lei, Min
name: Zhang, Yifei
name: zhang, Yunhan
name: Shen, Yan
name: Lin, Keqin
name: Yang, Zhaoqing
name: Chu, Jiayou
name: Sun, Hao
name: Luo, Zhiling
Publisher: name: figshare
Year: 2024
Subjects: subject: Genetics
subject: FOS: Biological sciences
subject: Molecular Biology
subject: Environmental Sciences not elsewhere classified
subject: Biological Sciences not elsewhere classified
subject: Science Policy

description: Supplementary Material 1
The R-matrix bootstrap
Creators: name: Murali, Harish
Publisher: name: Purdue University Graduate School
Year: 2021
Subjects: Particle physics

description: In this thesis, we extend the numerical S-matrix bootstrap program to 1+1d theories with a boundary, where we bootstrap the 1-to-1 reflection matrix (R-matrix). We review the constraints that a physical R-matrix must obey, namely unitarity, analyticiy and crossing symmetry. We then carve out the allowed space of 2d R-matrices with the O(N) nonlinear sigma model and the periodic Yang Baxter solution in the bulk. We find a variety of integrable R-matrices along the boundary of the allowed space both with and without free parameters. The integrable models without a free parameter appear at vertices of the allowed space, while those with a free parameter occupy the whole boundary. We also introduce the extended analyticity constraint where we increase the domain of analyticity beyond the physical region. In some cases, the allowed space of R-matrices shrinks drastically and we observe new vertices which correspond to integrable theories. We also find a new integrable R-matrix through our numerics, which we later obtained by solving the boundary Yang--Baxter equation. Finally, we derive the dual to the extended analyticity problem and find that the formalism allows for R-matrices which do not saturate unitarity to lie on the boundary of the allowed region.
Post-embryonic Expression of HLH-3 is Sexually Dimorphic and Affects Sexually Dimorphic Behavior in Males
Creators: name: Goodwin, Kimberly Lynn
Publisher: name: University of Illinois Chicago
Year: 2025

description: A critical stage of neuronal development is the expression of proneural bHLH genes in
the ectoderm leading to the specification of neuronal precursor cells. Expression of subsequent
identity specification genes allow these cells to mature and acquire terminal identity features
including a particular morphology, connectivity, and transcriptome. Other bHLH transcription
factors are known to have alternate, non-traditional roles in differentiation. This work
investigates the role that one such non-traditional bHLH transcription factor, hlh-3, plays in
neuronal development. The goal of this work is to characterize the post-embryonic expression
pattern of hlh-3 in males, as well as the differentiation of a subset of neurons required for male specific behaviors. Our findings show that expression of hlh-3 is sexually dimorphic in the L1, late L3/early L4, and adult stages. This work also describes the role of hlh-3 in the maturation of a subset of neurons required for male specific exploration behavior. Our findings show that in the absence of hlh-3, AWA, ASJ, and AIM neurons fail to acquire terminally differentiated features and therefore contribute to the failure of males to perform behaviors mediated by these cells. We further characterize features of another sex-shared neuron with sex-specific function, PHCs, including anterior axon length, eat-4/VGLUT relative expression, overall axon morphology, and male mating behavior to determine if hlh-3(lof) males have fully differentiated PHC neurons. Our results show that while eat-4/VGLUT levels and anterior axon length are unaltered, overall axon morphology is severely compromised, and subsequent male mating behaviors fail at multiple points. These results indicate that hlh-3(lof) male PHCs are likely to be a contributing factor to the large-scale defects observed in male mating behaviors
MECHANICS, VIBRATIONS, AND TENSION MEASUREMENT OF THIN WEBS IN ROLL-TO-ROLL MANUFACTURING FOR FLEXIBLE AND PRINTED ELECTRONICS
Creators: name: Feng, Dan
Publisher: name: Purdue University Graduate School
Year: 2021
Subjects: Mechanical engineering not elsewhere classified

description: Roll-to-roll processes provide a low-cost and high-throughput scheme for scalable flexible devices manufacturing. Multiple processes are used in roll-to-roll manufacturing, such as functional printing, evaporation/drying, UV curing, hot embossing, laser/heat annealing, laser ablation, plasma/ chemical growth, and sputtering. These processes change the web temperature field and/ or local properties. In addition, residual stresses by the process and web tension can destabilize the process and lead to wrinkling or undesirable performance of the products.This dissertation investigates three different multi-physics problems relevant to the roll-to-roll processes, which are web thermomechanics, air-coupled web vibrations, and the measuring of nonuniform web tension. First, a mathematical model for predicting the in-plane temperature and heat induced stress distributions in a flexible, axially moving web under arbitrary shape of heat flux is presented. The computational approach is validated on experiments performed on moving paper and PET webs with infrared laser heating source. Second, a closed-form, semi-analytical, universal hydrodynamic functions is developed to accurately predict the lowest symmetric and anti-symmetric transverse frequency responses for any uniaxially tensioned web of arbitrary material and aspect ratio used in roll-to-roll processes with the surrounding air acting as distributed added mass. Experimental validation is carried out by using pointwise laser measurements of acoustically excited webs with different pre-tensions, web materials, and aspect ratios. Finally, we develop and test a non-contact resonance method and a gentle contact stiffness mapping method based on the first principles mechanical models of a tensioned plate to accurately measure the average web tension and its linear variation for a wide range of web properties, web path, web tension, measurement configurations, and environmental conditions. The two methods are cross-validated on a stationary test stand and the non-contact resonance method is used to study the web tension distribution within a commercial roll-to-roll system.
Detection of IoT Botnets using Decision Trees
Creators: name: Raghavendra, Meghana
Publisher: name: Purdue University Graduate School
Year: 2021
Subjects: System and network security

description: International Data Corporation[3] (IDC) data estimates that 152,200 Internet of things (IoT) devices will be connected to the Internet every minute by the year 2025. This rapid expansion in the utilization of IoT devices in everyday life leads to an increase in the attack surface for cybercriminals. IoT devices are frequently compromised and used for the creation of botnets. However, it is difficult to apply the traditional methods to counteract IoT botnets and thus calls for finding effective and efficient methods to mitigate such threats. In this work, the network snapshots of IoT traffic infected with two botnets, i.e., Mirai and Bashlite, are studied. Specifically, the collected datasets include network traffic from 9 different IoT devices such as baby monitor, doorbells, thermostat, web cameras, and security cameras. Each dataset consists of 115 stream aggregation feature statistics like weight, mean, covariance, correlation coefficient, standard deviation, radius, and magnitude with a timeframe decay factor, along with a class label defining the traffic as benign or anomalous.The goal of the research is to identify a proper machine learning method that can detect IoT botnet traffic accurately and in real-time on IoT edge devices with low computation power, in order to form the first line of defense in an IoT network. The initial step is to identify the most important features that distinguish between benign and anomalous traffic for IoT devices. Specifically, the Input Perturbation Ranking algorithm[12] with XGBoost[26]is applied to find the 9 most important features among the 115 features. These 9 features can be collected in real time and be applied as inputs to any detection method. Next, a supervised predictive machine learning method, i.e., Decision Trees, is proposed for faster and accurate detection of botnet traffic. The advantage of using decision trees over other machine learning methodologies, is that it achieves accurate results with low computation time and power. Unlike deep learning methodologies, decision trees can provide visual representation of the decision making and detection process. This can be easily translated into explicit security policies in the IoT environment. In the experiments conducted, it can be clearly seen that decision trees can detect anomalous traffic with an accuracy of 99.997% and takes 59 seconds for training and 0.068 seconds for prediction, which is much faster than the state-of-art deep-learning based detector, i.e., Kitsune[4]. Moreover, our results show that decision trees have an extremely low false positive rate of 0.019%. Using the 9 most important features, decision trees can further reduce the processing time while maintaining the accuracy. Hence, decision trees with important features are able to accurately and efficiently detect IoT botnets in real time and on a low performance edge device such as Raspberry Pi[9].
EXPERIMENTAL STUDY OF A TRANSCRITICAL THERMOACOUSTIC ENGINE WITH POWER EXTRACTION APPLICATIONS
Creators: name: Kuras, Benjamin Gallagher
Publisher: name: Purdue University Graduate School
Year: 2021
Subjects: Aerospace engineering not elsewhere classified

description: An experimental study was performed on a low frequency transcritical thermoacoustic engine developed at Maurice J. Zucrow Laboratories. The goal of the experiment was to characterize the effects of engine geometry on the thermoacoustic production of the working fluid and to use insights gained to design a power extraction device for the transcritical thermoacoustic engine. The effects of geometry were investigated by parametrically varying the length of the resonator and the diameter of the resonator and measuring the pressure amplitude and frequency of thermoacoustic instabilities developed at varying ∆T and one bulk pressure of P Pcr = 1.1. It was found that increasing resonator length increases pres?sure amplitude, decreases frequency, and increases acoustic power developed. Increasing resonator diameter decreases pressure amplitude, increases frequency, and increases acoustic power developed. It was also experimentally proven that coiled tube sections in the res?onator attenuate the thermoacoustic pressure wave. After testing, the knowledge gained was applied to the design of a bidirectional impulse turbine for eventual integration into a scaled-up version of the current thermoacoustic engine to be used to extract power from the thermoacoustic instabilities developed in the rig.
sj-docx-1-aut-10.1177_13623613211041904 – Supplemental material for Atypicalities in the developmental trajectory of cortico-striatal functional connectivity in autism spectrum disorder
Creators: name: Ma, Zeng-Hui
name: Lu, Bin
name: Li, Xue
name: Mei, Ting
name: Guo, Yan-Qing
name: Yang, Liu
name: Wang, Hui
name: Tang, Xin-Zhou
name: Ji, Zhao-Zheng
name: Liu, Jing-Ran
name: Xu, Ling-Zi
name: Yang, Yu-Lu
name: Cao, Qing-Jiu
name: Yan, Chao-Gan
name: Liu, Jing
Publisher: name: SAGE Journals
Year: 2021
Subjects: Psychology not elsewhere classified
Psychiatry (incl. Psychotherapy)
Public Health and Health Services not elsewhere classified
Education
Special Education and Disability

description: Supplemental material, sj-docx-1-aut-10.1177_13623613211041904 for Atypicalities in the developmental trajectory of cortico-striatal functional connectivity in autism spectrum disorder by Zeng-Hui Ma, Bin Lu, Xue Li, Ting Mei, Yan-Qing Guo, Liu Yang, Hui Wang, Xin-Zhou Tang, Zhao-Zheng Ji, Jing-Ran Liu, Ling-Zi Xu, Yu-Lu Yang, Qing-Jiu Cao, Chao-Gan Yan and Jing Liu in Autism
Additional file 2 of Association study of FLT4 and HYDIN single nucleotide polymorphisms with atrial septal defect susceptibility in the Han Chinese population of Southwest China
Creators: name: Jin, Ye
name: Zhao, Miao
name: Guo, Qiuzhe
name: Zhao, Wanyu
name: Lei, Min
name: Zhang, Yifei
name: zhang, Yunhan
name: Shen, Yan
name: Lin, Keqin
name: Yang, Zhaoqing
name: Chu, Jiayou
name: Sun, Hao
name: Luo, Zhiling
Publisher: name: figshare
Year: 2024
Subjects: subject: Genetics
subject: FOS: Biological sciences
subject: Molecular Biology
subject: Environmental Sciences not elsewhere classified
subject: Biological Sciences not elsewhere classified
subject: Science Policy

description: Supplementary Material 2
Community Detection of Anomaly in Large-Scale Network Dissertation - Adefolarin Bolaji .pdf
Creators: name: Bolaji, Adefolarin Alaba
Publisher: name: Purdue University Graduate School
Year: 2021
Subjects: System and network security
Networking and communications
Applied computing not elsewhere classified
Artificial intelligence not elsewhere classified
Knowledge representation and reasoning

description: The detection of anomalies in real-world networks is applicable in different domains; the application includes, but is not limited to, credit card fraud detection, malware identification and classification, cancer detection from diagnostic reports, abnormal traffic detection, identification of fake media posts, and the like. Many ongoing and current researches are providing tools for analyzing labeled and unlabeled data; however, the challenges of finding anomalies and patterns in large-scale datasets still exist because of rapid changes in the threat landscape. In this study, I implemented a novel and robust solution that combines data science and cybersecurity to solve complex network security problems. I used Long Short-Term Memory (LSTM) model, Louvain algorithm, and PageRank algorithm to identify and group anomalies in large-scale real-world networks. The network has billions of packets. The developed model used different visualization techniques to provide further insight into how the anomalies in the network are related. Mean absolute error (MAE) and root mean square error (RMSE) was used to validate the anomaly detection models, the results obtained for both are 5.1813e-04 and 1e-03 respectively. The low loss from the training phase confirmed the low RMSE at loss: 5.1812e-04, mean absolute error: 5.1813e-04, validation loss: 3.9858e-04, validation mean absolute error: 3.9858e-04. The result from the community detection shows an overall modularity value of 0.914 which is proof of the existence of very strong communities among the anomalies. The largest sub-community of the anomalies connects 10.42% of the total nodes of the anomalies. The broader aim and impact of this study was to provide sophisticated, AI-assisted countermeasures to cyber-threats in large-scale networks. To close the existing gaps created by the shortage of skilled and experienced cybersecurity specialists and analysts in the cybersecurity field, solutions based on out-of-the-box thinking are inevitable; this research was aimed at yielding one of such solutions. It was built to detect specific and collaborating threat actors in large networks and to help speed up how the activities of anomalies in any given large-scale network can be curtailed in time.
FAST: Fast Audio Spectrogram Transformer
Creators: name: Naman, Anugunj
name: Zhang, Gaibo
Publisher: name: arXiv
Year: 2025
Subjects: subject: Sound (cs.SD)
subject: Audio and Speech Processing (eess.AS)
subject: FOS: Computer and information sciences
subject: FOS: Electrical engineering, electronic engineering, information engineering

description: In audio classification, developing efficient and robust models is critical for real-time applications. Inspired by the design principles of MobileViT, we present FAST (Fast Audio Spectrogram Transformer), a new architecture that combines convolutional neural networks (CNNs) and transformers to capitalize on the strengths of both. FAST integrates the local feature extraction efficiencies of CNNs with the global context modeling capabilities of transformers, resulting in a model that is powerful yet lightweight, well-suited to a real-time or mobile use case. Additionally, we incorporate Lipschitz continuous attention mechanisms to improve training stability and accelerate convergence. We evaluate FAST on the ADIMA dataset, a multilingual corpus towards real-time profanity and abuse detection, as well as on the more traditional AudioSet. Our results show that FAST achieves state-of-the-art performance on both the ADIMA and AudioSet classification tasks and in some cases surpasses existing benchmarks while using up to 150x fewer parameters.
description: Accepted at ICASSP 2025
Hyperkalemia in Feline Urinary Tract Emergencies
Creators: name: Tiffinger, Kornelia
Publisher: name: Washington State University
Year: 2026
Subjects: feline
hyperkalemia
urinary tract emergencies

description: Objective – The aim was to 1. Determine frequency and severity of the hyperkalemia in urinary emergencies in large cohort of cats, 2. Analyse risk factors for and determine treatment response to hyperkalemia. We hypothesized that hyperkalemia is common in feline urinary emergencies and that all hyperkalemic urinary emergencies can be resolved by a combination of fluid therapy and resolution of the underlying cause.
description: Design – Retrospective study.
description: Setting – University veterinary teaching hospital.
description: Animals – 162 client-owned cats.
description: Interventions – None.
description: Measurements and Main Results – Forty-seven of 144 cats (32%) were hyperkalemic. Of these, 38% were mildly hyperkalemic, 25% and 36% were moderately and severely hyperkalemic, respectively. Hyperkalemia severity was increased in cats with 20-29 hours duration of clinical signs. Serum BUN and creatinine concentrations were positively correlated with serum potassium (K) concentrations, and BUN > 21.1 mmol/L (59.2 mg/dl) predicted hyperkalemia with 100% sensitivity and 90% specificity. In mildly hyperkalemic cats, 83% resolved with fluid therapy and de-obstructing. Moderately and severely hyperkalemic cats undergoing medical management and deobstruction resolved in 25% and 15% of cases, respectively. However, multi-approach therapy was used in many cases. Insulin therapy showed the highest correlation with K decrease.
description: Conclusions – Only 20% of cats were moderately or severely hyperkalemic on presentation. Azotemia with elevated BUN and creatinine, and duration of clinical signs are predictors of severity of hyperkalemia. Fluid therapy alone resulted in normokalemia among most mildly hyperkalemic cats. Despite multi-therapy approach, most of the severely hyperkalemic cases remained moderately or severely hyperkalemic after initial management.
Additional file 1 of How to differentiate induced pluripotent stem cells into sensory neurons for disease modelling: a functional assessment
Creators: name: Kalia, Anil Kumar
name: Rösseler, Corinna
name: Granja-Vazquez, Rafael
name: Ahmad, Ayesha
name: Pancrazio, Joseph J.
name: Neureiter, Anika
name: Zhang, Mei
name: Sauter, Daniel
name: Vetter, Irina
name: Andersson, Asa
name: Dussor, Gregory
name: Price, Theodore J.
name: Kolber, Benedict J.
name: Truong, Vincent
name: Walsh, Patrick
name: Lampert, Angelika
Publisher: name: figshare
Year: 2024
Subjects: subject: Space Science
subject: Medicine
subject: Cell Biology
subject: Genetics
subject: FOS: Biological sciences
subject: Neuroscience
subject: Biological Sciences not elsewhere classified
subject: Developmental Biology
subject: Mental Health

description: Additional file 1. Supplementary information.
Tomo: Traffic Optimization And Merge Organization
Creators: name: Li, Kevin S.
name: Greising, Maeve F.
name: Hilton, Evan
name: Morris, Jonathan
Publisher: name: Zenodo
Year: 2015

description: We present a mathematical model to simulate the traffic congestion that occurs when a multi-lane road, such as a freeway, must end a lane due to construction or a traffic incident. We examine a number of mathematical theories in deciding how to simulate and ease congestion. In particular, we consider elements of queueing theory, congestion game theory, and three-phase traffic theory, using modern technology to boost our throughput.
sj-pdf-1-dst-10.1177_19322968211043112 – Supplemental material for Sensor Augmented Pump Therapy is Safe and Effective in Very Low Birth Weight Newborns Affected by Neonatal Diabetes Mellitus, with Poor Subcutaneous Tissue: Replacement of the Insulin Pump Infusion Set on the Arm, a Video Case Report
Creators: name: Zanfardino, Angela
name: Carpentieri, Mauro
name: Piscopo, Alessia
name: Curto, Stefano
name: Miraglia del Giudice, Emanuele
name: Inverardi, Alessia
name: Diplomatico, Mario
name: Moschella, Sabino
name: Spagnuolo, Ferdinando
name: Caredda, Elisabetta
name: Montaldo, Paolo
name: Iafusco, Dario
Publisher: name: SAGE Journals
Year: 2021
Subjects: subject: 111708 Health and Community Services
subject: FOS: Health sciences
subject: 110306 Endocrinology
subject: FOS: Clinical medicine
subject: Medicine
subject: 111199 Nutrition and Dietetics not elsewhere classified

description: Supplemental material, sj-pdf-1-dst-10.1177_19322968211043112 for Sensor Augmented Pump Therapy is Safe and Effective in Very Low Birth Weight Newborns Affected by Neonatal Diabetes Mellitus, with Poor Subcutaneous Tissue: Replacement of the Insulin Pump Infusion Set on the Arm, a Video Case Report by Angela Zanfardino, Mauro Carpentieri, Alessia Piscopo, Stefano Curto, Emanuele Miraglia del Giudice, Alessia Inverardi, Mario Diplomatico, Sabino Moschella, Ferdinando Spagnuolo, Elisabetta Caredda, Paolo Montaldo and Dario Iafusco in Journal of Diabetes Science and Technology
On the Abstract Structure of Operator Systems and Applications to Quantum Information Theory
Creators: name: Araiza, Roy M
Publisher: name: Purdue University Graduate School
Year: 2021
Subjects: Operator algebras and functional analysis

description: We introduce the notion of an abstract projection in an operator system and when a finite number of positive contractions in an operator system are all simultaneously abstract projections in that operator system. We extend this notion to Archimedean order unit spaces where we prove when a positive contraction is an abstract projection in some operator system, and furthermore when a finite number of positive contractions in an Archimedean order unit space are all simultaneously abstract projections in a single operator system. These methods are then used to provide new characterizations of both nonsignalling and quantum commuting correlations. In particular, we construct a universal Archimedean order unit space such that every quantum commuting correlation may be realized as the image of a unital linear positive map acting on the generators of that Archimedean order unit space. We also construct an Archimedean order unit space which is universal (in the same way) to nonsignalling correlations. We conclude with results concerning weak dual matrix ordered *-vector spaces and the operator systems they induce.