cometadata/datacite-rtg-text-other-reclassification-records huggingface dataset:
Vibrational modes of negatively charged silicon-vacancy centers in diamond from ab initio calculations
Creators: name: Londero, Elisa
name: Thiering, Gergő
name: Razinkovas, Lukas
name: Gali, Adam
name: Alkauskas, Audrius
Publisher: name: arXiv
Year: 2016
Subjects: subject: Quantum Physics (quant-ph)
subject: Materials Science (cond-mat.mtrl-sci)
subject: Computational Physics (physics.comp-ph)
subject: FOS: Physical sciences

description: Silicon-vacancy (SiV) center in diamond is a photoluminescence (PL) center with a characteristic zero-phonon line energy at 1.681 eV that acts as a solid-state single photon source and, potentially, as a quantum bit. The majority of the luminescence intensity appears in the zero-phonon line; nevertheless, about 30\% of the intensity manifests in the phonon sideband. Since phonons play an essential role in the operation of this system, it is of importance to understand the vibrational properties of the SiV center in detail. To this end, we carry out density functional theory calculations of dilute SiV centers by embedding the defect in supercells of a size of a few thousand atoms. We find that there exist two well-pronounced quasi-local vibrational modes (resonances) with $A_{2u}$ and $E_u$ symmetries, corresponding to the vibration of the Si atom along and perpendicular to the defect symmetry axis, respectively. Isotopic shifts of these modes explain the isotopic shifts of prominent vibronic features in the experimental SiV PL spectrum. Moreover, calculations show that the vibrational frequency of the $A_{2u}$ mode increases by about 30\% in the excited state with respect to the ground state, while the frequency of the $E_u$ mode increases by about 5\%. These changes explain experimentally observed isotopic shifts of the zero-phonon line energy. We also emphasize possible dangers of extracting isotopic shifts of vibrational resonances from finite-size supercell calculations, and instead propose a method to do this correctly.
description: 9 pages, 6 figures, 2 tables
Music Recommender System Using K-Nearest Neighbor and Particle Swarm Optimization
Creators: name: Rasyid, Randika Dwi Maulana
name: Baizal, ZK Abdurahman
Publisher: name: Indonesia Journal on Computing (Indo-JC)
Year: 2022

description: In this day, users can listen to music anytime digitally and access them through the already available applications. A music recommender system is needed to help users choose music according to their interests and find music to listen to. K-Nearest Neighbor (KNN) is a popular method used in Collaborative Filtering (CF). In many studies, CF with the KNN method has been widely used, but it does not provide good performance. Thus, in this study, we use KNN, which will be optimized using Particle Swarm Optimization (PSO), which can improve the performance of the results obtained against the method used. System testing is done by comparing the performance of the KNN algorithm with the optimization results of KNN-PSO with several variables being observed, including the Mean Squared Error (MSE) and Root Mean Squared Error (RMSE) values. The results of these recommender will predict the rating value where the KNN method gives MSE 4.48 and RMSE 2.54 while the KNN-PSO method gives MSE 1.70 and RMSE 1.30.
description: Indonesia Journal on Computing (Indo-JC), Vol. 7 No. 2 (2022): August, 2022
A memristive deep belief neural network based on silicon synapses
Creators: name: Wang, Wei
name: Danial, Loai
name: Li, Yang
name: Herbelin, Eric
name: Pikhay, Evgeny
name: Roizin, Yakov
name: Hoffer, Barak
name: Wang, Zhongrui
name: Kvatinsky, Shahar
Publisher: name: arXiv
Year: 2022
Subjects: subject: Applied Physics (physics.app-ph)
subject: Disordered Systems and Neural Networks (cond-mat.dis-nn)
subject: Materials Science (cond-mat.mtrl-sci)
subject: Emerging Technologies (cs.ET)
subject: FOS: Physical sciences
subject: FOS: Computer and information sciences

description: Memristor-based neuromorphic computing could overcome the limitations of traditional von Neumann computing architectures -- in which data are shuffled between separate memory and processing units -- and improve the performance of deep neural networks. However, this will require accurate synaptic-like device performance, and memristors typically suffer from poor yield and a limited number of reliable conductance states. Here we report floating gate memristive synaptic devices that are fabricated in a commercial complementary metal-oxide-semiconductor (CMOS) process. These silicon synapses offer analogue tunability, high endurance, long retention times, predictable cycling degradation, moderate device-to-device variations, and high yield. They also provide two orders of magnitude higher energy efficiency for multiply-accumulate operations than graphics processing units. We use two 12-by-8 arrays of the memristive devices for in-situ training of a 19-by-8 memristive restricted Boltzmann machine for pattern recognition via a gradient descent algorithm based on contrastive divergence. We then create a memristive deep belief neural network consisting of three memristive restricted Boltzmann machines. We test this on the modified National Institute of Standards and Technology (MNIST) dataset, demonstrating recognition accuracy up to 97.05%.
Pleasant and Unpleasant Feeling
Creators: name: Bramble, Ben
Publisher: name: The University of North Carolina at Chapel Hill University Libraries
Year: 2007

description: This thesis is a defence of two views about the nature of pleasant and unpleasant feeling: (1) The Fallibility Thesis, according to which we can believe we're experiencing pleasant or unpleasant feeling (or that we're not), and be wrong; and (2) The Sensation Thesis, according to which pleasant and unpleasant feeling are two particular sensations.
Hidden in the background: a local approach to CMB anomalies
Creators: name: Sanchez, Juan C. Bueno
Publisher: name: arXiv
Year: 2016
Subjects: subject: Cosmology and Nongalactic Astrophysics (astro-ph.CO)
subject: General Relativity and Quantum Cosmology (gr-qc)
subject: High Energy Physics - Phenomenology (hep-ph)
subject: High Energy Physics - Theory (hep-th)
subject: FOS: Physical sciences

description: We investigate a framework aiming to provide a common origin for the large-angle anomalies detected in the Cosmic Microwave Background (CMB), which are hypothesized as the result of the statistical inhomogeneity developed by different isocurvature fields of mass $m\sim H$ present during inflation. The inhomogeneity arises as the combined effect of $(i)$ the initial conditions for isocurvature fields (obtained after a fast-roll stage finishing many $e$-foldings before cosmological scales exit the horizon), $(ii)$ their inflationary fluctuations and $(iii)$ their coupling to other degrees of freedom. Our case of interest is when these fields (interpreted as the precursors of large-angle anomalies) leave an observable imprint only in isolated patches of the Universe. When the latter intersect the last scattering surface, such imprints arise in the CMB. Nevertheless, due to their statistically inhomogeneous nature, these imprints are difficult to detect, for they become hidden in the background similarly to the Cold Spot. We then compute the probability that a single isocurvature field becomes inhomogeneous at the end of inflation and find that, if the appropriate conditions are given (which depend exclusively on the preexisting fast-roll stage), this probability is at the percent level. Finally, we discuss several mechanisms (including the curvaton and the inhomogeneous reheating) to investigate whether an initial statistically inhomogeneous isocurvature field fluctuation might give rise to some of the observed anomalies. In particular, we focus on the Cold Spot, the power deficit at low multipoles and the breaking of statistical isotropy.
description: v2: Material reorganized and simpified to improve presentation. Comments and references added. It maches published version (49 pages 12 figures)
Dynamically Mitigating Data Discrepancy with Balanced Focal Loss for Replay Attack Detection
Creators: name: Dou, Yongqiang
name: Yang, Haocheng
name: Yang, Maolin
name: Xu, Yanyan
name: Ke, Dengfeng
Publisher: name: arXiv
Year: 2020
Subjects: subject: Computer Vision and Pattern Recognition (cs.CV)
subject: Machine Learning (cs.LG)
subject: Audio and Speech Processing (eess.AS)
subject: Machine Learning (stat.ML)
subject: FOS: Computer and information sciences
subject: FOS: Electrical engineering, electronic engineering, information engineering

description: It becomes urgent to design effective anti-spoofing algorithms for vulnerable automatic speaker verification systems due to the advancement of high-quality playback devices. Current studies mainly treat anti-spoofing as a binary classification problem between bonafide and spoofed utterances, while lack of indistinguishable samples makes it difficult to train a robust spoofing detector. In this paper, we argue that for anti-spoofing, it needs more attention for indistinguishable samples over easily-classified ones in the modeling process, to make correct discrimination a top priority. Therefore, to mitigate the data discrepancy between training and inference, we propose D3M, to leverage a balanced focal loss function as the training objective to dynamically scale the loss based on the traits of the sample itself. Besides, in the experiments, we select three kinds of features that contain both magnitude-based and phase-based information to form complementary and informative features. Experimental results on the ASVspoof2019 dataset demonstrate the superiority of the proposed methods by comparison between our systems and top-performing ones. Systems trained with the balanced focal loss perform significantly better than conventional cross-entropy loss. With complementary features, our fusion system with only three kinds of features outperforms other systems containing five or more complex single models by 22.5% for min-tDCF and 7% for EER, achieving a min-tDCF and an EER of 0.0124 and 0.55% respectively. Furthermore, we present and discuss the evaluation results on real replay data apart from the simulated ASVspoof2019 data, indicating that research for anti-spoofing still has a long way to go. Source code, analysis data, and other details are publicly available at https://github.com/asvspoof/D3M.
description: The 25th International Conference on Pattern Recognition (ICPR2020)
Feedback Regulated Turbulence, Magnetic Fields, and Star Formation Rates in Galactic Disks
Creators: name: Kim, Chang-Goo
name: Ostriker, Eve C.
Publisher: name: arXiv
Year: 2015
Subjects: subject: Astrophysics of Galaxies (astro-ph.GA)
subject: FOS: Physical sciences

description: We use three-dimensional magnetohydrodynamic (MHD) simulations to investigate the quasi-equilibrium states of galactic disks regulated by star formation feedback. We incorporate effects from massive-star feedback via time-varying heating rates and supernova (SN) explosions. We find that the disks in our simulations rapidly approach a quasi-steady state that satisfies vertical dynamical equilibrium. The star formation rate (SFR) surface density self-adjusts to provide the total momentum flux (pressure) in the vertical direction that matches the weight of the gas. We quantify feedback efficiency by measuring feedback yields, η_c\equiv P_c/Σ_SFR (in suitable units), for each pressure component. The turbulent and thermal feedback yields are the same for HD and MHD simulations, η_th~1 and η_ turb~4, consistent with the theoretical expectations. In MHD simulations, turbulent magnetic fields are rapidly generated by turbulence, and saturate at a level corresponding to η_mag,t~1. The presence of magnetic fields enhances the total feedback yield and therefore reduces the SFR, since the same vertical support can be supplied at a smaller SFR. We suggest further numerical calibrations and observational tests in terms of the feedback yields.
description: To appear in Proceedings of IAU Symposium 315, From interstellar clouds to star-forming galaxies: universal processes?, P. Jablonka, P. Andre, and F.. van der Tak, eds
Integrating Formal Methods with Model-Driven Engineering
Creators: name: Adesina, Opeyemi
Publisher: name: Université d'Ottawa / University of Ottawa
Year: 2017
Subjects: Formal Methods
Model-Driven Engineering
Model Checking
Umple
UML
Model-Driven Development

description: This thesis presents our method to integrate formal methods with model-driven engineering. Although a large amount of literature exists with the goal of facilitating the adoption of formal methods for educational and industrial practice, yet the adoption of formal methods in academia and industry is poor. The goal of this research is to improve the adoption of formal methods by automating the generation of formal methods code while maintaining scalability and bridging the gaps between formal analysis and actual implementation of the complete system. Our approach is based on generating formal representations of software abstractions expressed in a textual language, called Umple, which is derived from UML. Software abstractions of interest include class models and state machines. For state machines, we address concerns such as composite and concurrent states separately. The resulting systems are analyzable by back-end analysis engines such as Alloy and nuXmv or NuSMV for model checking. To ensure correctness of our approach, we have adopted simulation, empirical studies and rigorous test-driven development (TDD) methodologies. To guarantee correctness of state machine systems under analysis (SSUAs), we present methods to automatically generate specifications to analyze domain-independent properties such as non-determinism and reachability analysis. We apply these methods in various case studies; certify their conformance with sets of requirements and uncover certain flaws. Our contributions include a) The overall approach, involving having the developer write the system in Umple and generating both the formal system for analysis and the final code from the same model; b) a novel approach to encode SSUAs even in the presence of and-cross transitions; c) a fully automated approach to certify an SSUA to be free from nondeterminism even in the presence of unbounded domains and multiple and-cross transitions within the same enclosing orthogonal state; d) an empirical study of the impact of abstraction on some performance parameters; and e) a translator from Umple to Alloy and SMV.
Performance Analysis of PPG Signal Denoising Method Using DWT and EMD for Detection of PVC and AF Arrhytmias
Creators: name: Aniq Wafa, Muhammad
name: Mandala, Satria
name: Pramudyo, Miftah
Publisher: name: Indonesia Journal on Computing (Indo-JC)
Year: 2022

description: In the cardiac arrhythmia detection system using a Photoplethysmography (PPG) sensor, noise is often found in the PPG signal due to internal and external factors in the signal retrieval process. So it is necessary to do a denoising process to remove noise before the signal is used. This study aims to test the Discrete wavelet transform (DWT) and Empirical Mode Decomposition (EMD) methods in removing noise from the PPG signal and to test the denoising signal on the Premature Arrhythmia Verticular Contractions (PVC) and Atrial Fibrillation (AF) detection systems. The parameters used to compare the performance of the denoising method are Mean Square Error (MSE), Signal to Noise Ratio (SNR), Accuracy, F1, Precision, and Recall. The method with the highest SNR, Accuracy, F1, Precision, and Recall values ​​and the lowest MSE values ​​is the best denoising method.
description: Indonesia Journal on Computing (Indo-JC), Vol. 7 No. 2 (2022): August, 2022
Fitting a 3D Morphable Model to Edges: A Comparison Between Hard and Soft Correspondences
Creators: name: Bas, Anil
name: Smith, William A. P.
name: Bolkart, Timo
name: Wuhrer, Stefanie
Publisher: name: arXiv
Year: 2016
Subjects: subject: Computer Vision and Pattern Recognition (cs.CV)
subject: FOS: Computer and information sciences

description: We propose a fully automatic method for fitting a 3D morphable model to single face images in arbitrary pose and lighting. Our approach relies on geometric features (edges and landmarks) and, inspired by the iterated closest point algorithm, is based on computing hard correspondences between model vertices and edge pixels. We demonstrate that this is superior to previous work that uses soft correspondences to form an edge-derived cost surface that is minimised by nonlinear optimisation.
description: To appear in ACCV 2016 Workshop on Facial Informatics
title: Методологические аспекты формирования и развития предпринимательских сетей
Creators: name: Асаул А.Н.
name:  Скуматов Е.Г.
name:  Локтеева Г.Е.
Publisher: name: Институт проблем экономического возрождения, Гуманистика
Year: 2004

description: В издании широко показано развитие отечественного предпринимательства. Особое место уделено теоретико-методологическим основам и сущности предпринимательства, целеполаганию, предпринимательской культуре и интрапренерству. Научным результатом книги является классификация предпринимательских сетей и системы их параметрического описания, а разработка принципов двухуровневого управления процессом создания и функционирования предпринимательских сетей, а также экономико-организационных механизмов их реализации на основе формирования локальных и комплексных бизнес-планов и целевых программ позволяет усовершенствовать систему управления строительством с учетом положений сетевого подхода к организации производственного цикла. В качестве практической части авторами предлагается обоснованный алгоритм разработки программы формирования предпринимательской сети и методические подходы к структурной оценке эффективности ее функционирования в инновационно-строительном комплексе. Издание предназначено аспирантам, слушателям системы переподготовки и повышения квалификации специалистов, а также получения второго высшего образования, ученым-экономистам и руководителям высшего звена управления фирм.
description: The publication extensively shows the development of domestic business. Special attention is given to theoretical and methodological basics and the essence of entrepreneurship, goal setting, entrepreneurial culture and intrapreneurship. The scientific result of the book is the classification of entrepreneurial networks and their parametric descriptions, and the development of the principles of two-level control process for the establishment and functioning of business networks, and economic and organizational mechanisms for their implementation through the development of local and integrated business plans and target programs allows to improve the system of construction management, subject to the provisions of the network approach to the organization of the production cycle. As a practical part, the authors have proposed a reasonable algorithm for the development of the program of formation of the business network and methodological approaches to structural evaluation of its performance in innovation and the construction industry. The publication is intended to graduate students, listeners of system of retraining and advanced training of specialists, as well as receiving the second higher education, academic economists and senior executives of control firms.
Symmetric group characters as symmetric functions
Creators: name: Orellana, Rosa
name: Zabrocki, Mike
Publisher: name: arXiv
Year: 2016
Subjects: subject: Combinatorics (math.CO)
subject: FOS: Mathematics
subject: 05E05, 05E10, 06B15, 20C30

description: We introduce a basis of the symmetric functions that evaluates to the (irreducible) characters of the symmetric group, just as the Schur functions evaluate to the irreducible characters of $GL_n$ modules. Our main result gives three different characterizations for this basis. One of the characterizations shows that the structure coefficients for the (outer) product of these functions are the stable Kronecker coefficients. The results in this paper focus on developing the fundamental properties of this basis.
description: 35 pages; this is the more complete version of arXiv:1510.00438; v5 differs from previous versions with minor edits and the addition of an appendix about using Sagemath to do computations with these bases (this appendix does not appear in the published journal version)
The lepton flavor violating decays of vector mesons in the MRSSM
Creators: name: Sun, Ke-Sheng
name: Zhang, Wen-Hui
name: Chen, Jian-Bin
name: Zhang, Hai-Bin
Publisher: name: arXiv
Year: 2022
Subjects: subject: High Energy Physics - Phenomenology (hep-ph)
subject: FOS: Physical sciences

description: Recently several new bounds of the lepton flavor violating decays of the neutral vector mesons $J/ψ$ and $Υ(nS)$ are reported from the experiments. In the work, we analyze these processes in the scenario of the minimal R-symmetric supersymmetric standard model by means of the effective Lagrangian method. The predicted branching ratios are affected by the mass insertion parameters $δ^{ij}$ and the contributions from different parts are comparable. Taking account of the constraints on the mass insertion parameters from the experiments, the branching ratios for the most promising processes $Υ(nS)\rightarrow lτ$ are predicted to be ten orders of magnitude smaller than the present experimental bounds.
description: 18 pages, 10 figures
Energy Efficiency Analysis of Network Slicing Algorithm on WiFI Network
Creators: name: Prakoso, Dimas
name: Nuha, Hilal Hudan
name: Utomo, Rio Guntur
Publisher: name: Indonesia Journal on Computing (Indo-JC)
Year: 2022

description: The 5G network generation is a modern innovation after it was first introduced by the New Generation Mobile Network (NGMN). The rapid development of mobile devices is marked by the number of companies launching mobile devices with the latest network connection technology, namely the 5G network. In addition, the rapid development of technology has led to an increase in the number of network requirements that are increasingly current. The development of network virtualization and software network functions is proposed as Network Slicing technology. Network Slicing can integrate and distribute independent network resources so that users get services with low latency and high-reliability requirements. The Network Slicing algorithm can reduce energy wastage when used and aims to divide and allocate network resources into several parts in proportion to the expected resource ratio or priority.
description: Indonesia Journal on Computing (Indo-JC), Vol. 7 No. 2 (2022): August, 2022
LRH-Net: A Multi-Level Knowledge Distillation Approach for Low-Resource Heart Network
Creators: name: Chauhan, Ekansh
name: Guptha, Swathi
name: Reddy, Likith
name: Raju, Bapi
Publisher: name: arXiv
Year: 2022
Subjects: subject: Medical Physics (physics.med-ph)
subject: Artificial Intelligence (cs.AI)
subject: Machine Learning (cs.LG)
subject: Signal Processing (eess.SP)
subject: FOS: Physical sciences
subject: FOS: Computer and information sciences
subject: FOS: Electrical engineering, electronic engineering, information engineering

description: An electrocardiogram (ECG) monitors the electrical activity generated by the heart and is used to detect fatal cardiovascular diseases (CVDs). Conventionally, to capture the precise electrical activity, clinical experts use multiple-lead ECGs (typically 12 leads). But in recent times, large-size deep learning models have been used to detect these diseases. However, such models require heavy compute resources like huge memory and long inference time. To alleviate these shortcomings, we propose a low-parameter model, named Low Resource Heart-Network (LRH-Net), which uses fewer leads to detect ECG anomalies in a resource-constrained environment. A multi-level knowledge distillation process is used on top of that to get better generalization performance on our proposed model. The multi-level knowledge distillation process distills the knowledge to LRH-Net trained on a reduced number of leads from higher parameter (teacher) models trained on multiple leads to reduce the performance gap. The proposed model is evaluated on the PhysioNet-2020 challenge dataset with constrained input. The parameters of the LRH-Net are 106x less than our teacher model for detecting CVDs. The performance of the LRH-Net was scaled up to 3.2% and the inference time scaled down by 75% compared to the teacher model. In contrast to the compute- and parameter-intensive deep learning techniques, the proposed methodology uses a subset of ECG leads using the low resource LRH-Net, making it eminently suitable for deployment on edge devices.
title: Оценка машин, оборудования и транспортных средств
title: Учебно-методическое пособие
titleType: Subtitle
Creators: name: Асаул А.Н.
name:  Старинский В.Н.
name:  Бездудная А.Г.
name:  Ерофеев П.Ю.
Publisher: name: Институт проблем экономического возрождения, Гуманистика
Year: 2007

description: Учебное пособие подготовлено в соответствии с программой обучения по дисциплине ДС.11.4. «Оценка стоимости машин, оборудования и транспортных средств» по специализации 060821 «Оценка собственности». Рассмотрены технико-экономическое содержание, классификация и приемы идентификации машин и оборудования, виды стоимости технических устройств, принципы и технология их оценки. Раскрыто содержание физического, функционального и внешнего износа и на конкретных примерах показано, как эти виды износа влияют на изменение стоимости машин и оборудования. Особое место уделено практике определения стоимости машин и оборудования с позиций имущественного (затратного), сравнительного (рыночного) и доходного подходов, а также приемам формирования окончательного результата оценки этих объектов. Предназначено для студентов, обучающихся по специализации 060821 «Оценка собственности», а также адресовано слушателям курса «Оценка стоимости предприятия (бизнеса)» и всем, кто интересуется проблемами оценочной деятельности.
description: Manual prepared in accordance with the program of training in the discipline of DS.11.4. "Valuation of machinery, equipment and vehicles" in the field 060821 "property Valuation". Discussed technical and economic content, classification and methods of identification of machinery and equipment, the cost of technical devices, principles and technology evaluation. Disclosed the contents of the physical, functional and external obsolescence, and the specific examples shown, as these types of wear can affect the cost of machinery and equipment. Special attention is given to the practice of determining the value of machinery and equipment from the standpoint of property (expensive), comparative (market) and income approaches, and techniques for the formation of the final result of the evaluation of these objects. Designed for students enrolled in the specialization 060821 "property Valuation", and addressed to the students of the course "Valuation of enterprise (business)" and all who are interested in problems of evaluation.
Evidence for quasi-two-dimensional superconductivity in infinite-layer nickelates
Creators: name: Sun, Wenjie
name: Li, Yueying
name: Liu, Ruxin
name: Yang, Jiangfeng
name: Li, Jiayi
name: Yan, Shengjun
name: Sun, Haoying
name: Guo, Wei
name: Gu, Zhengbin
name: Deng, Yu
name: Wang, Xuefeng
name: Nie, Yuefeng
Publisher: name: arXiv
Year: 2022
Subjects: subject: Superconductivity (cond-mat.supr-con)
subject: Materials Science (cond-mat.mtrl-sci)
subject: Strongly Correlated Electrons (cond-mat.str-el)
subject: FOS: Physical sciences

description: After being expected as a promising analogue to cuprates for decades, superconductivity was recently discovered in infinite-layer nickelates, providing new opportunities to explore mechanisms of high-temperature superconductivity. However, in sharp contrast to the single-band quasi-two-dimensional superconductivity in cuprates, nickelates exhibit a multi-band electronic structure and an unexpected isotropic superconductivity as reported recently, which challenges the cuprate-like picture in nickelates. Here, we show the superconductivity in nickelates is actually anisotropic and quasi-two-dimensional in nature, as that in cuprates. By synthesizing high-quality lanthanide nickelate films with enhanced crystallinity and superconductivity ($T_{c}^{onset}$ = 18.8 K, $T_{c}^{zero}$ = 16.5 K), strong anisotropic magnetotransport behaviors have been observed. The quasi-two-dimensional nature is further confirmed by the existence of a cusp-like peak of the angle-dependent $T_{c}$, and a Berezinskii-Kosterlitz-Thouless transition near $T_{c}$. Our work thus suggests a quasi-two-dimensional superconductivity in infinite-layer nickelates, implying a single-3$d_{x^2-y^2}$-band cuprate-like picture may remain valid in these compounds.
description: 32 pages, 4 main figures, 6 extended data
Hypergeometric foundations of Fokker-Plank like equations
Creators: name: Plastino, A.
name: Rocca, M. C.
Publisher: name: arXiv
Year: 2015
Subjects: subject: Statistical Mechanics (cond-mat.stat-mech)
subject: Mathematical Physics (math-ph)
subject: Classical Physics (physics.class-ph)
subject: FOS: Physical sciences

description: We show that the Fokker Planck equation can be derived from a Hypergeometric differential equation. The same applies to a non linear generalization of such equation.
description: 9 pages. No figures
Reach for the (cloudy) Sky! Exploring cloud-to-cloud archiving of digital records
Creators: name: Arnold, Kirsten
Publisher: name: Zenodo
Year: 2024
Subjects: digital transfer
Sharepoint
Cloud
digital records
The National Archives

description: The National Archives (UK) is committed to making transfer of digital records faster and easier for our users. Or new automated digital transfer service (Transfer Digital Records or TDR) allows depositors to upload records from a network drive environment. However, an increasing number of users (c86% of UK public record bodies) are now using cloud ecosystems, mostly SharePoint Online but also Google drive. The current transfer process requires users to extract records from the cloud environment before they can be transferred (through re-upload to the cloud). This is slow, error-prone and, most importantly, can disrupt or lose metadata (particularly dates). It also introduces challenges in selecting export formats. A significant volume of records is affected – both current records and legacy data that has previously been migrated to the cloud.

The lighting talk will describe the ongoing study of work The National Archives has been undertaking to enable it’s transferring bodies to upload records directly from SharePoint to the Archive, securely and without loss of metadata or file integrity. The study engaged with external partners including Microsoft and will discuss the outcomes and next steps.
Discontinuity of Straightening in Anti-holomorphic Dynamics: I
Creators: name: Inou, Hiroyuki
name: Mukherjee, Sabyasachi
Publisher: name: arXiv
Year: 2016
Subjects: subject: Dynamical Systems (math.DS)
subject: Complex Variables (math.CV)
subject: FOS: Mathematics
subject: 37F10, 37F25, 30D05, 37F44

description: It is well known that baby Mandelbrot sets are homeomorphic to the original one. We study baby Tricorns appearing in the Tricorn, which is the connectedness locus of quadratic anti-holomorphic polynomials, and show that the dynamically natural straightening map from a baby Tricorn to the original Tricorn is discontinuous at infinitely many explicit parameters. This is the first known example of discontinuity of straightening maps on a real two-dimensional slice of an analytic family of holomorphic polynomials. The proof of discontinuity is carried out by showing that all non-real umbilical cords of the Tricorn wiggle, which settles a conjecture made by various people including Hubbard, Milnor, and Schleicher.
description: Same as published version. The original undivided version is available at: arXiv:1605.08061v3, and Part II is available at: arXiv:2010.01129. arXiv admin note: text overlap with arXiv:1209.1753 by other authors
Sentiment Analysis of University Social Media Using Support Vector Machine and Logistic Regression Methods
Creators: name: Fazainsyah Azka Wicaksono
name: Romadhony, Ade
name: Hasmawati
Publisher: name: Indonesia Journal on Computing (Indo-JC)
Year: 2022

description: Social media has become one of the most powerful platforms for information sharing. Colleges and universities now have official social media profiles to convey information about the campus and boost its branding and popularity. Instagram is a popular social networking website among college students. It is important for a university to comprehend its performance from the community's perspective, whether positive, negative, or indifferent toward the university. One solution is to examine the university's social media sentiment to establish the public's perception of the university. In this study, we will conduct a sentiment analysis on university social media based on public opinion or comments for each post on the university's Instagram to identify whether the comments are “Positive,” “Negative,” or “Neutral.” To classify posts on university Instagram, we use two methods: Support Vector Machine and Logistic Regression. The results suggest combining the Support Vector Machine approach with the TF-IDF feature yields the best F1-Score performance. In contrast, Logistic Regression with the FastText feature produces the worst performance of all models and feature extraction employed.
description: Indonesia Journal on Computing (Indo-JC), Vol. 7 No. 2 (2022): August, 2022
Concordance of spatial graphs
Creators: name: Lappo, Egor
Publisher: name: arXiv
Year: 2022
Subjects: subject: Geometric Topology (math.GT)
subject: FOS: Mathematics
subject: 57M15 (Primary), 05C10, 57K10 (Secondary)

description: We define smooth notions of concordance and sliceness for spatial graphs. We prove that sliceness of a spatial graph is equivalent to a condition on a set of linking numbers together with sliceness of a link associated to the graph. This generalizes the result of Taniyama for $θ$-curves.
description: 14 pages
The Effect of Play Type and Collision Closing Distance on Head Impact Biomechanics
Creators: name: Ocwieja, Karen Elaine
Publisher: name: University of North Carolina at Chapel Hill
Year: 2011

description: Football accounts for 55% of all concussions that collegiate athletes sustain. Kickoffs and punts have a greater risk of concussion than rushing and passing plays. The purpose of this study was to determine the effect of special team plays and closing distance of collisions on head impact biomechanics. Forty-six collegiate football players participated in the study. We used real-time data collection instrumentation to record head impact biomechanics during games for the three following play types: special teams, offense, and defense. Collisions occurring on special teams over long closing distances were the most severe impacts while collisions occurring on special teams and defense over short closing distances were the least severe impacts. Our findings indicate that impacts following long closing distances result in more severe head impacts; therefore, in order to decrease the severity of collisions in football the ability for long closing distances prior to impacts should be addressed.
Analysis of the Results of Metadynamics Simulations by metadynminer and metadynminer3d
Creators: name: Trapl, Dalibor
name: Spiwok, Vojtěch
Publisher: name: arXiv
Year: 2020
Subjects: subject: Biomolecules (q-bio.BM)
subject: Chemical Physics (physics.chem-ph)
subject: Computational Physics (physics.comp-ph)
subject: FOS: Biological sciences
subject: FOS: Physical sciences

description: The molecular simulations solve the equation of motion of molecular systems, making 3D shapes of molecules four-dimensional by adding the time coordinate. These methods have a great potential in drug discovery because they can realistically model the structures of protein molecules targeted by drugs as well as the process of binding of a potential drug to its molecular target. However, routine application of biomolecular simulations is hampered by the very high computational costs of this method. Several methods have been developed to address this problem. One of them, metadynamics, disfavors states of the simulated system that have been already visited and thus forces the system to explore new and new states. Here we present the package metadynminer and metadynminer3d to analyze and visualize results from metadynamics, in particular those produced by a popular metadynamics package Plumed.
description: 11 pages, 9 figures
STROBE Checklist for 'A comparative study to monitor drug adherence to antihypertensive drugs among preeclamptic women and to determine factors contributing to drug compliance restrictions.'
Creators: name: Agrawal, Harshita
Publisher: name: Zenodo
Year: 2023

description: 'A comparative study to monitor drug adherence to antihypertensive drugs among preeclamptic women and to determine factors contributing to drug compliance restrictions.'
Lung Cancer Prediction Model using Logistic Linear Regression with Imbalanced Dataset
Creators: name: Paelongan, Priscilia Lovita
name: Palupi, Irma
Publisher: name: Indonesia Journal on Computing (Indo-JC)
Year: 2022

description: Cancer is one of the leading causes of death worldwide. Cancer cases in Indonesia have now reached 4.8 million in 2018. Most cases are breast, cervix, and lung. Furthermore, we need to note that 43 percent of these cancer cases are preventable. This study uses a linear logistics regression model. Linear logistic regression models can be used for categoric datasets. The appropriate model is obtained after parameter assessment, test the significance of each affecting attribute, and test the suitability of the model. This is done to obtain prediction models and risk factors at the level of correlation of disease size. This method is relatively easy and conceptually practical, so it is possible to apply it to diagnose early symptoms of lung cancer. The results include a linear logistics regression model for early prediction of lung cancer patients based on symptoms, habits, and history of health diseases to see the likelihood that someone with a certain level of risk could have lung cancer. The factors that affect a person with lung cancer are difficulty swallowing, coughing, chronic diseases, fatigue, and age.
description: Indonesia Journal on Computing (Indo-JC), Vol. 7 No. 2 (2022): August, 2022
Electromechanical Oscillations in Bilayer Graphene
Creators: name: Benameur, Muhammed Malik
name: Gargiulo, Fernando
name: Manzeli, Sajedeh
name: Autes, Gabriel
name: Tosun, Mahmut
name: Yazyev, Oleg V.
name: Kis, Andras
Publisher: name: arXiv
Year: 2015
Subjects: subject: Mesoscale and Nanoscale Physics (cond-mat.mes-hall)
subject: FOS: Physical sciences

description: Nanoelectromechanical systems (NEMS) constitute a class of devices lying at the interface between fundamental research and technological applications. Integrating novel materials such as graphene into NEMS allows studying their mechanical and electromechanical characteristics at the nanoscale and addressing fundamental questions such as electron-phonon interaction and bandgap engineering. In this work, we integrate single and bilayer graphene into NEMS and probe the interplay between their mechanical and electrical properties. We show that the deflection of monolayer graphene nanoribbons results in a linear increase in their electrical resistance. Surprisingly, we observe oscillations in the electromechanical response of bilayer graphene. The proposed theoretical model suggests that these oscillations arise from quantum mechanical interference taking place due to the lateral displacement of graphene layers with respect to each other. Our work shows that bilayer graphene conceals unexpectedly rich and novel physics with promising potential in NEMS-based applications.
description: First three authors contributed equally
Concept for a Space-based Near-Solar Neutrino Detector
Creators: name: Solomey, N.
name: Folkerts, J.
name: Meyer, H.
name: Gimar, C.
name: Novak, J.
name: Doty, B.
name: English, T.
name: Buchele, L.
name: Nelsen, A.
name: McTaggart, R.
name: Christl, M.
Publisher: name: arXiv
Year: 2022
Subjects: subject: Instrumentation and Detectors (physics.ins-det)
subject: Instrumentation and Methods for Astrophysics (astro-ph.IM)
subject: High Energy Physics - Experiment (hep-ex)
subject: FOS: Physical sciences

description: The concept of putting a neutrino detector in close orbit of the sun has been unexplored until very recently. The primary scientific return is to vastly enhance our understanding of the solar interior, which is a major NASA goal. Preliminary calculations show that such a spacecraft, if properly shielded, can operate in space environments while taking data from neutrino interactions. These interactions can be distinguished from random background rates of solar electromagnetic emissions, galactic charged cosmic-rays, and gamma-rays by using a double pulsed signature. Early simulations of this project have shown this veto schema to be successful in eliminating background and identifying the neutrino interaction signal in upwards of 75% of gamma ray interactions and nearly 100% of other interactions. Hence, we propose a new instrument to explore and study our sun. Due to inverse square scaling, this instrument has the potential to outperform earth-based experiments in several domains such as making measurements not accessible from the earth's orbit.
Multistable excitonic Stark effect
Creators: name: Xiong, Ying
name: Rudner, Mark S.
name: Song, Justin C. W.
Publisher: name: arXiv
Year: 2020
Subjects: subject: Mesoscale and Nanoscale Physics (cond-mat.mes-hall)
subject: FOS: Physical sciences

description: The optical Stark effect is a tell-tale signature of coherent light-matter interaction in excitonic systems, wherein an irradiating light beam tunes exciton transition frequencies. Here we show that, when excitons are placed in a nanophotonic cavity, the excitonic Stark effect can become highly nonlinear, exhibiting multi-valued and hysteretic Stark shifts that depend on the history of the irradiating light. This multistable Stark effect (MSE) arises from feedback between the cavity mode occupation and excitonic population, mediated by the Stark-induced mutual tuning of the cavity and excitonic resonances. Strikingly, the MSE manifests even for very dilute exciton concentrations and can yield discontinuous Stark shift jumps of order meV. We expect that the MSE can be realized in readily available transition metal dichalcogenide excitonic systems placed in planar photonic cavities, at modest pump intensities. This phenomenon can provide new means to engineer coupled states of light and matter that can persist even in the single exciton limit.
description: 13 pages, 4 figures
DiviK: Divisive intelligent K-Means for hands-free unsupervised clustering in big biological data
Creators: name: Mrukwa, Grzegorz
name: Polanska, Joanna
Publisher: name: arXiv
Year: 2020
Subjects: subject: Quantitative Methods (q-bio.QM)
subject: FOS: Biological sciences

description: Investigating molecular heterogeneity provides insights about tumor origin and metabolomics. The increasing amount of data gathered makes manual analyses infeasible - therefore, automated unsupervised learning approaches are utilized for discovering heterogeneity. However, automated unsupervised analyses require a lot of experience with setting their hyperparameters and usually an upfront knowledge about the number of expected substructures. Moreover, numerous measured molecules require an additional step of feature engineering to provide valuable results. In this work, we propose DiviK: a scalable stepwise algorithm with local data-driven feature space adaptation for the segmentation of high-dimensional datasets. The combination of three quality indices: Dice Index, Rand Index and EXIMS score are used to assess the quality of unsupervised analyses in 3D space. DiviK was validated on two separate high-throughput datasets acquired by Mass Spectrometry Imaging in 2D and 3D. DiviK could be one of the default choices to consider during the initial exploration of Mass Spectrometry Imaging data. It provides a trade-off between absolute heterogeneity detection and focus on biologically plausible structures, and does not require specifying the number of expected structures before the analysis. With its unique local feature space adaptation, it is robust against dominating global patterns when focusing on the detail. Finally, due to its simplicity, DiviK is easily generalizable to an even more flexible framework, useful for other '-omics' data, or tabular data in general (including medical images after appropriate embedding). A generic implementation is freely available under Apache 2.0 license at https://github.com/gmrukwa/divik.
description: 24 pages, 11 figures
The Malgrange-Ehrenpreis theorem in distribution theory
Creators: name: Fu, Eric Chin Hooi
Publisher: name: University of North Carolina at Chapel Hill
Year: 2010

description: This thesis explores the Malgrange-Ehrenpreis Theorem in the theory of distribution via an expository approach based on the text Introduction to the Theory of Distribution by G. Friedlander and M. Joshi. I will be focusing on the understanding of the proof of the Malgrange-Ehrenpries Theorem. In many places, I have closely followed the presentation of Friedlander's and Joshi's monograph. We begin with the definition and the properties of distributions. Next, we study Fourier transforms and its properties. We look at the Schwartz space and consider its dual space. We conclude the section by investigating the Fourier transform of several notable distributions, including the Dirac-delta distribution and the signum distribution. Finally, we introduce Fourier-Laplace transforms and examine the Paley-Wiener-Schwartz estimate. This estimate describes the polynomial decay property of the Fourier-Laplace trans- form of test functions. We conclude with a special case of Malgrange-Ehrenpreis Theorem and analyze its complex proof.
Pointwise Universal Gysin formulae and Applications towards Griffiths' conjecture
Creators: name: Diverio, Simone
name: Fagioli, Filippo
Publisher: name: arXiv
Year: 2020
Subjects: subject: Differential Geometry (math.DG)
subject: Algebraic Geometry (math.AG)
subject: Complex Variables (math.CV)
subject: FOS: Mathematics
subject: Primary: 14F05, Secondary: 14M15, 57R20

description: Let $X$ be a complex manifold, $(E,h)\to X$ be a rank $r$ holomorphic hermitian vector bundle, and $ρ$ be a sequence of dimensions $0 = ρ_0 < ρ_1 < \cdots < ρ_m = r$. Let $Q_{ρ,j}$, $j=1,\dots,m$, be the tautological line bundles over the (possibly incomplete) flag bundle $\mathbb{F}_ρ(E) \to X$ associated to $ρ$, endowed with the natural metrics induced by that of $E$, with Chern curvatures $Ξ_{ρ,j}$. We show that the universal Gysin formula \textsl{à la} Darondeau--Pragacz for the push-forward of a homogeneous polynomial in the Chern classes of the $Q_{ρ,j}$'s also hold pointwise at the level of the Chern forms $Ξ_{ρ,j}$ in this hermitianized situation. As an application, we show the positivity of several polynomials in the Chern forms of a Griffiths (semi)positive vector bundle not previously known, thus giving some new evidences towards a conjecture by Griffiths, which in turn can be seen as a pointwise hermitianized version of the Fulton--Lazarsfeld Theorem on numerically positive polynomials for ample vector bundles.
description: 24 pages, no figures, comments are very welcome! v3: several minor corrections, the main application is now stated for strongly positive forms