cometadata/datacite-rtg-text-other-reclassification-records huggingface dataset:
Upregulation of human PINK1 gene expression by NFκB signalling
Creators: name: Duan, Xiaoling
name: Tong, Jade
name: Xu, Qin
name: Wu, Yili
name: Cai, Fang
name: Li, Tingyu
name: Song, Weihong
Publisher: name: BioMed Central
Year: 2015

description: Parkinson’s disease (PD) is one of the major neurodegenerative disorders. Mitochondrial malfunction is implicated in PD pathogenesis. Phosphatase and tensin homolog deleted on chromosome 10 (PTEN)-induced putative kinase 1 (PINK1), a serine/threonine kinase, plays an important role in the quality control of mitochondria and more than 70 PINK1 mutations have been identified to cause early-onset PD. However, the regulation of PINK1 gene expression remains elusive. In the present study, we identified the transcription start site (TSS) of the human PINK1 gene using switching mechanism at 5’end of RNA transcription (SMART RACE) assay. The TSS is located at 91 bp upstream of the translation start site ATG. The region with 104 bp was identified as the minimal promoter region by deletion analysis followed by dual luciferase assay. Four functional cis-acting nuclear factor kappa-light-chain-enhancer of activated B cells (NFκB)-binding sites within the PINK1 promoter were identified. NFκB overexpression led to the up-regulation of PINK1 expression in both HEK293 cells and SH-SY5Y cells. Consistently, lipopolysaccharide (LPS), a strong activator of NFκB, significantly increased PINK1 expression in SH-SY5Y cells. Taken together, our results clearly suggested that PINK1 expression is tightly regulated at its transcription level and NFκB is a positive regulator for PINK1 expression.
X.509 Information Security Certification Based on Post-Quantum Cryptography
Creators: name: Chen, Abel C. H.
Publisher: name: arXiv
Year: 2024
Subjects: subject: Cryptography and Security (cs.CR)
subject: Software Engineering (cs.SE)
subject: FOS: Computer and information sciences

description: In recent years, with the advancement of quantum computing, mainstream asymmetric cryptographic methods in the current Public Key Infrastructure (PKI) systems are gradually being threatened. Therefore, this study explores X.509 security certificates based on Post-Quantum Cryptography (PQC) and discusses implemented solutions. This study compares mainstream asymmetric cryptographic methods (including RSA and Elliptic Curve Digital Signature Algorithm (ECDSA)) with standard PQC methods (including Falcon, Dilithium, SPHINCS+), comparing the efficiency of certificate generation, signature generation, and signature verification. Finally, recommendations for a solution based on PQC for X.509 security certificates are proposed.
description: The manuscript was submitted to arXiv on 6 May 2024, but it was rejected on 11 July 2024. The appeal was submitted on 11 July 2024, and it was accepted on 2 August 2024. The manuscript is written in Chinese language
Foundations of MIMO Radar Detection Aided by Reconfigurable Intelligent Surfaces
Creators: name: Buzzi, Stefano
name: Grossi, Emanuele
name: Lops, Marco
name: Venturino, Luca
Publisher: name: arXiv
Year: 2021
Subjects: subject: Signal Processing (eess.SP)
subject: Information Theory (cs.IT)
subject: FOS: Electrical engineering, electronic engineering, information engineering
subject: FOS: Computer and information sciences

description: A reconfigurable intelligent surface (RIS) is a nearly-passive flat layer made of inexpensive elements that can add a tunable phase shift to the impinging electromagnetic wave and are controlled by a low-power electronic circuit. This paper considers the fundamental problem of target detection in a RIS-aided multiple-input multiple-output (MIMO) radar. At first, a general signal model is introduced, which includes the possibility of using up to two RISs (one close to the radar transmitter and one close to the radar receiver) and subsumes both a monostatic and a bistatic radar configuration with or without a line-of-sight view of the prospective target. Upon resorting to a generalized likelihood ratio test (GLRT), the design of the phase shifts introduced by the RIS elements is formulated as the maximization of the probability of detection in the location under inspection for a fixed probability of false alarm, and suitable optimization algorithms are proposed. The performance analysis shows the benefits granted by the presence of the RISs and shed light on the interplay among the key system parameters, such as the radar-RIS distance, the RIS size, and location of the prospective target. A major finding is that the RISs should be better deployed in the near-field of the radar arrays at both the transmit and the receive side. The paper is concluded by discussing some open problems and foreseen applications.
description: Paper submitted to IEEE Transactions on Signal Processing; revised version after first-round review
Sharing Pain: Using Pain Domain Transfer for Video Recognition of Low Grade Orthopedic Pain in Horses
Creators: name: Broomé, Sofia
name: Ask, Katrina
name: Rashid, Maheen
name: Andersen, Pia Haubro
name: Kjellström, Hedvig
Publisher: name: arXiv
Year: 2021
Subjects: subject: Computer Vision and Pattern Recognition (cs.CV)
subject: FOS: Computer and information sciences

description: Orthopedic disorders are common among horses, often leading to euthanasia, which often could have been avoided with earlier detection. These conditions often create varying degrees of subtle long-term pain. It is challenging to train a visual pain recognition method with video data depicting such pain, since the resulting pain behavior also is subtle, sparsely appearing, and varying, making it challenging for even an expert human labeller to provide accurate ground-truth for the data. We show that a model trained solely on a dataset of horses with acute experimental pain (where labeling is less ambiguous) can aid recognition of the more subtle displays of orthopedic pain. Moreover, we present a human expert baseline for the problem, as well as an extensive empirical study of various domain transfer methods and of what is detected by the pain recognition method trained on clean experimental pain in the orthopedic dataset. Finally, this is accompanied with a discussion around the challenges posed by real-world animal behavior datasets and how best practices can be established for similar fine-grained action recognition tasks. Our code is available at https://github.com/sofiabroome/painface-recognition.
Stand on the Same Side - Preventing a Second Wave of Covid-19's Outbreak
Creators: name: Corbetta, Lorenzo
Publisher: name: Substantia
Year: 2020

description: This document is the direct transcription of a Webinar organized by Prof. L. Corbetta of the University of Florence on April 19th, 2020.
description: Substantia, Vol 4 No 1 Suppl. 1 (2020) - Open Stream on Covid-19 Emergency
Electrically charged compact stars with an interacting quark equation of state
Creators: name: Panotopoulos, Grigoris
name: Tangphati, Takol
name: Banerjee, Ayan
Publisher: name: arXiv
Year: 2021
Subjects: subject: General Relativity and Quantum Cosmology (gr-qc)
subject: FOS: Physical sciences

description: We investigate the properties of non-rotating, electrically charged strange quark stars in four-dimensional Einstein-Maxwell theory. For quark matter we adopt the well-motivated quantum chromodynamics (QCD) equation-of-state, while for the charge density we assume it is proportional to the mass density. The system of coupled structure equations are integrated numerically, and we compute the mass, the radius as well as the total electric charge of the stars. Moreover, we perform a detailed numerical study of the effect of electric charge using the interacting quark equation-of-state. We find that stars as heavy as two solar masses can be supported, and that the highest radius and highest mass of the stars increase with the charge density.
description: 8 pages, 3 figures
Classical and Quantum Chaos in Chirally-Driven, Dissipative Bose-Hubbard Systems
Creators: name: Dahan, Daniel
name: Arwas, Geva
name: Grosfeld, Eytan
Publisher: name: arXiv
Year: 2021
Subjects: subject: Other Condensed Matter (cond-mat.other)
subject: FOS: Physical sciences

description: We study the dissipative Bose-Hubbard model on a small ring of sites in the presence of a chiral drive and explore its long-time dynamical structure using the mean field equations and by simulating the quantum master equation. Remarkably, for large enough drivings, we find that the system admits, in a wide range of parameters, a chaotic attractor at the mean-field level, which manifests as a complex Wigner function on the quantum level. The latter is shown to have the largest weight around the approximate region of phase space occupied by the chaotic attractor. We demonstrate that this behavior could be revealed via measurement of various bosonic correlation functions. In particular, we employ open system methods to calculate the out-of-time-ordered correlator, whose exponential growth signifies a positive quantum Lyapunov exponent in our system. This can open a pathway to the study of chaotic dynamics in interacting systems of photons.
Powered Prosthesis Locomotion on Varying Terrains: Model-Dependent Control with Real-Time Force Sensing
Creators: name: Gehlhar, Rachel
name: Yang, Je-han
name: Ames, Aaron D.
Publisher: name: arXiv
Year: 2021
Subjects: subject: Robotics (cs.RO)
subject: Systems and Control (eess.SY)
subject: FOS: Computer and information sciences
subject: FOS: Electrical engineering, electronic engineering, information engineering

description: Lower-limb prosthesis wearers are more prone to falling than non-amputees. Powered prostheses can reduce this instability of passive prostheses. While shown to be more stable in practice, powered prostheses generally use model-independent control methods that lack formal guarantees of stability and rely on heuristic tuning. Recent work overcame one of the limitations of model-based prosthesis control by developing a class of provably stable prosthesis controllers that only require the human interaction forces with the prosthesis, yet these controllers have not been realized with sensing of these forces in the control loop. Our work realizes the first model-dependent prosthesis knee controller that uses in-the-loop on-board real-time force sensing at the interface between the human and prosthesis and at the ground. The result is an optimization-based control methodology that formally guarantees stability while enabling human-prosthesis walking on a variety of terrain types. Experimental results demonstrate this force-based controller outperforms similar controllers not using force sensors, improving tracking across 4 terrain types.
description: 8 pages, 7 figures, accepted by RA-L and ICRA 2022
Unsupervised Domain Adaption Harnessing Vision-Language Pre-training
Creators: name: Zhou, Wenlve
name: Zhou, Zhiheng
Publisher: name: arXiv
Year: 2024
Subjects: subject: Computer Vision and Pattern Recognition (cs.CV)
subject: FOS: Computer and information sciences

description: This paper addresses two vital challenges in Unsupervised Domain Adaptation (UDA) with a focus on harnessing the power of Vision-Language Pre-training (VLP) models. Firstly, UDA has primarily relied on ImageNet pre-trained models. However, the potential of VLP models in UDA remains largely unexplored. The rich representation of VLP models holds significant promise for enhancing UDA tasks. To address this, we propose a novel method called Cross-Modal Knowledge Distillation (CMKD), leveraging VLP models as teacher models to guide the learning process in the target domain, resulting in state-of-the-art performance. Secondly, current UDA paradigms involve training separate models for each task, leading to significant storage overhead and impractical model deployment as the number of transfer tasks grows. To overcome this challenge, we introduce Residual Sparse Training (RST) exploiting the benefits conferred by VLP's extensive pre-training, a technique that requires minimal adjustment (approximately 0.1\%$\sim$0.5\%) of VLP model parameters to achieve performance comparable to fine-tuning. Combining CMKD and RST, we present a comprehensive solution that effectively leverages VLP models for UDA tasks while reducing storage overhead for model deployment. Furthermore, CMKD can serve as a baseline in conjunction with other methods like FixMatch, enhancing the performance of UDA. Our proposed method outperforms existing techniques on standard benchmarks. Our code will be available at: https://github.com/Wenlve-Zhou/VLP-UDA.
The surveillance outcome comparative of unsafe cosmetic products distribution in shop and salon, Sukhothai province Year 2017-2018
Creators: name: Nutsiree Nuda
Publisher: name: Faculty of Pharmaceutical Sciences KKU MSU UBU
Year: 2020
Subjects: cosmetics, cosmetics labels, prohibited substances, surveillance, outcome

description: Isan Journal ofPharmaceutical Sciences, 16, 2, 11-20
Adaptive and optimized COVID-19 vaccination strategies across geographical regions and age groups
Creators: name: Molla, Jeta
name: Chávez, Alejandro Ponce de León
name: Hiraoka, Takayuki
name: Ala-Nissila, Tapio
name: Kivelä, Mikko
name: Leskelä, Lasse
Publisher: name: arXiv
Year: 2021
Subjects: subject: Populations and Evolution (q-bio.PE)
subject: Physics and Society (physics.soc-ph)
subject: FOS: Biological sciences
subject: FOS: Physical sciences

description: We evaluate the efficiency of various heuristic strategies for allocating vaccines against COVID-19 and compare them to strategies found using optimal control theory. Our approach is based on a mathematical model which tracks the spread of disease among different age groups and across different geographical regions, and we introduce a method to combine age-specific contact data to geographical movement data. As a case study, we model the epidemic in the population of mainland Finland utilizing mobility data from a major telecom operator. Our approach allows to determine which geographical regions and age groups should be targeted first in order to minimize the number of deaths. In the scenarios that we test, we find that distributing vaccines demographically and in an age-descending order is not optimal for minimizing deaths and the burden of disease. Instead, more lives could potentially be saved by using strategies which emphasize high-incidence regions and distribute vaccines in parallel to multiple age groups. The level of emphasis that high-incidence regions should be given depends on the overall transmission rate in the population. This observation highlights the importance of updating the vaccination strategy when the effective reproduction number changes due to the general contact patterns changing and new virus variants entering.
description: Revision
Effective field theory and classical equations of motion
Creators: name: Reall, Harvey S.
name: Warnick, Claude M.
Publisher: name: arXiv
Year: 2021
Subjects: subject: High Energy Physics - Theory (hep-th)
subject: General Relativity and Quantum Cosmology (gr-qc)
subject: Analysis of PDEs (math.AP)
subject: FOS: Physical sciences
subject: FOS: Mathematics

description: Given a theory containing both heavy and light fields (the UV theory), a standard procedure is to integrate out the heavy field to obtain an effective field theory (EFT) for the light fields. Typically the EFT equations of motion consist of an expansion involving higher and higher derivatives of the fields, whose truncation at any finite order may not be well-posed. In this paper we address the question of how to make sense of the EFT equations of motion, and whether they provide a good approximation to the classical UV theory. We propose an approach to solving EFTs which leads to a well-posedness statement. For a particular choice of UV theory we rigorously derive the corresponding EFT and show that a large class of classical solutions to the UV theory are well approximated by EFT solutions. We also consider solutions of the UV theory which are not well approximated by EFT solutions and demonstrate that these are close, in an averaged sense, to solutions of a modified EFT.
description: 47 pages; references updated
A formative evaluation of the implementation of an upper limb stroke rehabilitation intervention in clinical practice: a qualitative interview study
Creators: name: Connell, Louise A
name: McMahon, Naoimh E
name: Harris, Jocelyn E
name: Watkins, Caroline L
name: Eng, Janice
Publisher: name: BioMed Central
Year: 2016

description: Background: The Graded Repetitive Arm Supplementary Program (GRASP) is a hand and arm exercise programme designed to increase the intensity of exercise achieved in inpatient stroke rehabilitation. GRASP was shown to be effective in a randomised controlled trial in 2009 and has since experienced unusually rapid uptake into clinical practice. The aim of this study was to conduct a formative evaluation of the implementation of GRASP to inform the development and implementation of a similar intervention in the United Kingdom. Methods: Semi-structured interviews were conducted with therapists who were involved in implementing GRASP at their work site, or who had experience of using GRASP. Normalisation Process Theory (NPT), a sociological theory used to explore the processes of embedding innovations in practice, was used to develop an interview guide. Intervention components outlined within the GRASP Guideline Manual were used to develop prompts to explore how therapists use GRASP in practice. Interview transcripts were analysed using a coding frame based on implementation theory. Results: Twenty interviews were conducted across eight sites in British Columbia Canada. Therapists identified informal networks and the free online availability of GRASP as key factors in finding out about the intervention. All therapists reported positive opinions about the value of GRASP. At all sites, therapists identified individuals who advocated for the use of GRASP, and in six of the eight sites this was the practice leader or senior therapist. Rehabilitation assistants were identified as instrumental in delivering GRASP in almost all sites as they were responsible for organising the GRASP equipment and assisting patients using GRASP. Almost all intervention components were found to be adapted to some degree when used in clinical practice; coverage was wider, the content adapted, and the dose, when monitored, was less. Conclusions: Although GRASP has translated into clinical practice, it is not always used in the way in which it was shown to be effective. This formative evaluation has informed the development of a novel intervention which aims to bridge this evidence-practice gap in upper limb rehabilitation after stroke.
Permutation invariance and uncertainty in multitemporal image super-resolution
Creators: name: Valsesia, Diego
name: Magli, Enrico
Publisher: name: arXiv
Year: 2021
Subjects: subject: Image and Video Processing (eess.IV)
subject: Computer Vision and Pattern Recognition (cs.CV)
subject: FOS: Electrical engineering, electronic engineering, information engineering
subject: FOS: Computer and information sciences

description: Recent advances have shown how deep neural networks can be extremely effective at super-resolving remote sensing imagery, starting from a multitemporal collection of low-resolution images. However, existing models have neglected the issue of temporal permutation, whereby the temporal ordering of the input images does not carry any relevant information for the super-resolution task and causes such models to be inefficient with the, often scarce, ground truth data that available for training. Thus, models ought not to learn feature extractors that rely on temporal ordering. In this paper, we show how building a model that is fully invariant to temporal permutation significantly improves performance and data efficiency. Moreover, we study how to quantify the uncertainty of the super-resolved image so that the final user is informed on the local quality of the product. We show how uncertainty correlates with temporal variation in the series, and how quantifying it further improves model performance. Experiments on the Proba-V challenge dataset show significant improvements over the state of the art without the need for self-ensembling, as well as improved data efficiency, reaching the performance of the challenge winner with just 25% of the training data.
Spatial distribution of the journey to work by sustainable modes in Australian cities
Creators: name: Stone, John
name: Mees, Paul
Publisher: name: Swinburne
Year: 2024

description: To understand the impacts of current policies and to guide planning for future infrastructure and services, it is important to monitor and analyse trends in transport behaviour. The ABS Census is an under-utilized source of travel behaviour data that, because of its method of collection, avoids the problems associated with other survey methodologies that rely on generalisations from small samples. This paper reports on an analysis of travel mode and destination zone for people in the labour force using data from the 2001 and 2006 censuses for the Australian state capitals and Canberra. Destination-zone data is publicly available only for these two censuses. This work builds on earlier analysis of Australian journey to work data between 1976 and 2006. We analyse the spatial distribution of recent growth in urban public transport patronage, as well as walking and cycling, to determine the extent to which inner-city workers are contributing to recent increases in travel by sustainable modes. We expected that, because services and infrastructure are principally designed for this market, work travel to the inner zones of Australian cities would account for most of the growth in the use of sustainable modes of transport. However, for public transport, the results did not follow this pattern. The proportion of work trips by public transport to destinations in the inner zones fell between 2001 and 2006 in all cities except Sydney and Canberra.
Examination of orbital evolution and gravitational waves of OJ 287 in the 4PN order
Creators: name: Kacskovics, Balázs
name: Vasúth, Matyás
Publisher: name: arXiv
Year: 2021
Subjects: subject: General Relativity and Quantum Cosmology (gr-qc)
subject: FOS: Physical sciences

description: We computed the orbital evolution and the emitted gravitational radiation of the supermassive black hole binary OJ 287. Here we used the initial data provided by the outburst structure of the system. We considered the spin-spin, spin-orbit, and the next-to-next leading order fourth post-Newtonian (4PN) corrections in our analysis. In this way, we could make an accurate examination of unstable orbits ($3M < r <6M$) of the secondary black hole. We tested the 4PN terms by analyzing the total and radiated energy, compared the post-Newtonian parameters and the separation of the two black holes for 3PN and 4PN. In conclusion, the 4PN corrections provided a significantly more accurate tool for analyzing unstable orbits than earlier 3PN terms. Furthermore, in this paper, we show the gravitational waves emitted by OJ 287 during its complete orbital evolution including unstable orbits.
description: 16 pages, 8 figure, preprint
Second moments of work and heat for a single particle stochastic heat engine in a breathing harmonic potential
Creators: name: Iida, Shinji
name: Negoro, Koki
name: Yamada, Kanta
Publisher: name: arXiv
Year: 2021
Subjects: subject: Statistical Mechanics (cond-mat.stat-mech)
subject: FOS: Physical sciences

description: We consider a simple model of a stochastic heat engine, which consists of a single Brownian particle moving in a one-dimensional periodically breathing harmonic potential. Overdamped limit is assumed. Expressions of second moments (variances and covariances ) of heat and work are obtained in the form of integrals, whose integrands contain functions satisfying certain differential equations. The results in the quasi-static limit are simple functions of temperatures of hot and cold thermal baths. The coefficient of variation of the work is suggested to give an approximate probability for the work to exceeds a certain threshold. During derivation, we get the expression of the cumulant-generating function.
Large-scale Deployment of Vision-based Tactile Sensors on Multi-fingered Grippers
Creators: name: Wang, Meng
name: Li, Wanlin
name: Liang, Hao
name: Li, Boren
name: Althoefer, Kaspar
name: Su, Yao
name: Liu, Hangxin
Publisher: name: arXiv
Year: 2024
Subjects: subject: Robotics (cs.RO)
subject: FOS: Computer and information sciences

description: Vision-based Tactile Sensors (VBTSs) show significant promise in that they can leverage image measurements to provide high-spatial-resolution human-like performance. However, current VBTS designs, typically confined to the fingertips of robotic grippers, prove somewhat inadequate, as many grasping and manipulation tasks require multiple contact points with the object. With an end goal of enabling large-scale, multi-surface tactile sensing via VBTSs, our research (i) develops a synchronized image acquisition system with minimal latency,(ii) proposes a modularized VBTS design for easy integration into finger phalanges, and (iii) devises a zero-shot calibration approach to improve data efficiency in the simultaneous calibration of multiple VBTSs. In validating the system within a miniature 3-fingered robotic gripper equipped with 7 VBTSs we demonstrate improved tactile perception performance by covering the contact surfaces of both gripper fingers and palm. Additionally, we show that our VBTS design can be seamlessly integrated into various end-effector morphologies significantly reducing the data requirements for calibration.
On the energy density of linearly polarized, plane gravitational wave
Creators: name: Yang, I-Ching
Publisher: name: arXiv
Year: 2021
Subjects: subject: General Relativity and Quantum Cosmology (gr-qc)
subject: FOS: Physical sciences

description: In this article, the energy density of plane gravitational wave is studied by using Einstein and Møller's prescription of energy-momentum pseudotensors. The linearly polarized plan gravitational wave solution of Einstein field equation, which has been defined by Bondi et al., is represented by four kinds of different coodrinates. The energy distribution of gravitational wave solution in Einstein and Møller's prescription are obtained. Particularly the energy component is zero in null coordinates.
description: 8 pages
Ten Quick Tips for Deep Learning in Biology
Creators: name: Lee, Benjamin D.
name: Gitter, Anthony
name: Greene, Casey S.
name: Raschka, Sebastian
name: Maguire, Finlay
name: Titus, Alexander J.
name: Kessler, Michael D.
name: Lee, Alexandra J.
name: Chevrette, Marc G.
name: Stewart, Paul Allen
name: Britto-Borges, Thiago
name: Cofer, Evan M.
name: Yu, Kun-Hsing
name: Carmona, Juan Jose
name: Fertig, Elana J.
name: Kalinin, Alexandr A.
name: Signal, Beth
name: Lengerich, Benjamin J.
name: Triche, Timothy J.
name: Boca, Simina M.
Publisher: name: arXiv
Year: 2021
Subjects: subject: Other Quantitative Biology (q-bio.OT)
subject: Machine Learning (cs.LG)
subject: FOS: Biological sciences
subject: FOS: Computer and information sciences

description: Machine learning is a modern approach to problem-solving and task automation. In particular, machine learning is concerned with the development and applications of algorithms that can recognize patterns in data and use them for predictive modeling. Artificial neural networks are a particular class of machine learning algorithms and models that evolved into what is now described as deep learning. Given the computational advances made in the last decade, deep learning can now be applied to massive data sets and in innumerable contexts. Therefore, deep learning has become its own subfield of machine learning. In the context of biological research, it has been increasingly used to derive novel insights from high-dimensional biological data. To make the biological applications of deep learning more accessible to scientists who have some experience with machine learning, we solicited input from a community of researchers with varied biological and deep learning interests. These individuals collaboratively contributed to this manuscript's writing using the GitHub version control platform and the Manubot manuscript generation toolset. The goal was to articulate a practical, accessible, and concise set of guidelines and suggestions to follow when using deep learning. In the course of our discussions, several themes became clear: the importance of understanding and applying machine learning fundamentals as a baseline for utilizing deep learning, the necessity for extensive model comparisons with careful evaluation, and the need for critical thought in interpreting results generated by deep learning, among others.
description: 23 pages, 2 figures
MARCO: A Memory-Augmented Reinforcement Framework for Combinatorial Optimization
Creators: name: Garmendia, Andoni I.
name: Cappart, Quentin
name: Ceberio, Josu
name: Mendiburu, Alexander
Publisher: name: arXiv
Year: 2024
Subjects: subject: Neural and Evolutionary Computing (cs.NE)
subject: Artificial Intelligence (cs.AI)
subject: FOS: Computer and information sciences

description: Neural Combinatorial Optimization (NCO) is an emerging domain where deep learning techniques are employed to address combinatorial optimization problems as a standalone solver. Despite their potential, existing NCO methods often suffer from inefficient search space exploration, frequently leading to local optima entrapment or redundant exploration of previously visited states. This paper introduces a versatile framework, referred to as Memory-Augmented Reinforcement for Combinatorial Optimization (MARCO), that can be used to enhance both constructive and improvement methods in NCO through an innovative memory module. MARCO stores data collected throughout the optimization trajectory and retrieves contextually relevant information at each state. This way, the search is guided by two competing criteria: making the best decision in terms of the quality of the solution and avoiding revisiting already explored solutions. This approach promotes a more efficient use of the available optimization budget. Moreover, thanks to the parallel nature of NCO models, several search threads can run simultaneously, all sharing the same memory module, enabling an efficient collaborative exploration. Empirical evaluations, carried out on the maximum cut, maximum independent set and travelling salesman problems, reveal that the memory module effectively increases the exploration, enabling the model to discover diverse, higher-quality solutions. MARCO achieves good performance in a low computational cost, establishing a promising new direction in the field of NCO.
Malcolm BELL III, The City Plan and Political Agora. Results of the excavations conducted by Princeton University, the University of Illinois, and the University of Virginia
Creators: name: Sielhorst, Barbara
Publisher: name: Göttinger Forum für Altertumswissenschaft
Year: 2024

description: Rezension zu: Malcolm Bell III, The City Plan and Political Agora. Results of the excava­tions conducted by Princeton University, the University of Illinois, and the University of Virginia. Morgantina Studies VII. Wiesbaden: Reichert 2022, 444 S., 60 farb. Abb., 763 s/w Abb., EUR 129,00. ISBN: 9783752000214
description: Göttinger Forum für Altertumswissenschaft, Bd. 26 (2023): Göttinger Forum für Altertumswissenschaft
Early Detection of COVID-19 Hotspots Using Spatio-Temporal Data
Creators: name: Zhu, Shixiang
name: Bukharin, Alexander
name: Xie, Liyan
name: Yamin, Khurram
name: Yang, Shihao
name: Keskinocak, Pinar
name: Xie, Yao
Publisher: name: arXiv
Year: 2021
Subjects: subject: Machine Learning (stat.ML)
subject: Machine Learning (cs.LG)
subject: Applications (stat.AP)
subject: FOS: Computer and information sciences

description: Recently, the Centers for Disease Control and Prevention (CDC) has worked with other federal agencies to identify counties with increasing coronavirus disease 2019 (COVID-19) incidence (hotspots) and offers support to local health departments to limit the spread of the disease. Understanding the spatio-temporal dynamics of hotspot events is of great importance to support policy decisions and prevent large-scale outbreaks. This paper presents a spatio-temporal Bayesian framework for early detection of COVID-19 hotspots (at the county level) in the United States. We assume both the observed number of cases and hotspots depend on a class of latent random variables, which encode the underlying spatio-temporal dynamics of the transmission of COVID-19. Such latent variables follow a zero-mean Gaussian process, whose covariance is specified by a non-stationary kernel function. The most salient feature of our kernel function is that deep neural networks are introduced to enhance the model's representative power while still enjoying the interpretability of the kernel. We derive a sparse model and fit the model using a variational learning strategy to circumvent the computational intractability for large data sets. Our model demonstrates better interpretability and superior hotspot-detection performance compared to other baseline methods.
Template induced precursor formation in heterogeneous nucleation -- Controlling polymorph selection and nucleation efficiency
Creators: name: Leines, Grisell Díaz
name: Rogal, Jutta
Publisher: name: arXiv
Year: 2021
Subjects: subject: Materials Science (cond-mat.mtrl-sci)
subject: Chemical Physics (physics.chem-ph)
subject: FOS: Physical sciences

description: We present an atomistic study of heterogeneous nucleation in Ni employing transition path sampling, which reveals a template precursor-mediated mechanism of crystallization. Most notably, we find that the ability of tiny templates to modify the structural features of the liquid and promote the formation of precursor regions with enhanced bond-orientational order is key to determine their nucleation efficiency and the polymorphs that crystallize. Our results reveal an intrinsic link between liquid heterogeneity and the nucleating ability of templates, which significantly advances our understanding towards the control of nucleation efficiency and polymorph selection.
description: Manuscript 6 pages, 3 Figures. Supplemental : 10 pages, 8 figures
Variational analysis of inextensible elastic curves
Creators: name: Bevilacqua, Giulia
name: Lussardi, Luca
name: Marzocchi, Alfredo
Publisher: name: arXiv
Year: 2021
Subjects: subject: Analysis of PDEs (math.AP)
subject: FOS: Mathematics
subject: 49J05, 46G05, 53A04, 74B20

description: We minimize elastic energies on framed curves which penalize both curvature and torsion. We also discuss critical points using the infinite dimensional version of the Lagrange multipliers' method. Finally, some examples arising from the applications are discussed and also numerical experiments are presented.
Adverse events of patients receiving rituximab, bevacizumab and omalizumab at King Chulalongkorn Memorial Hospital
Creators: name: Wirotesangthong, Mali
Publisher: name: Faculty of Pharmaceutical Sciences KKU MSU UBU
Year: 2020
Subjects: adverse events, monoclonal antibodies, rituximab, bevacizumab and omalizumab

description: Isan Journal ofPharmaceutical Sciences, 16, 2, 30-44
Development of a PET Scanner for Simultaneously Imaging Small Animals with MRI and PET
Creators: name: Thompson, Christopher J
name: Goertzen, Andrew L
name: Thiessen, Jonathan D
name: Bishop, Daryl
name: Stortz, Greg
name: Kozlowski, Piotr
name: Retière, Fabrice
name: Zhang, Xuezhu
name: Sossi, Vesna
Publisher: name: Multidisciplinary Digital Publishing Institute
Year: 2019

description: Recently, positron emission tomography (PET) is playing an increasingly important role in the diagnosis and staging of cancer. Combined PET and X-ray computed tomography (PET-CT) scanners are now the modality of choice in cancer treatment planning. More recently, the combination of PET and magnetic resonance imaging (MRI) is being explored in many sites. Combining PET and MRI has presented many challenges since the photo-multiplier tubes (PMT) in PET do not function in high magnetic fields, and conventional PET detectors distort MRI images. Solid state light sensors like avalanche photo-diodes (APDs) and more recently silicon photo-multipliers (SiPMs) are much less sensitive to magnetic fields thus easing the compatibility issues. This paper presents the results of a group of Canadian scientists who are developing a PET detector ring which fits inside a high field small animal MRI scanner with the goal of providing simultaneous PET and MRI images of small rodents used in pre-clinical medical research. We discuss the evolution of both the crystal blocks (which detect annihilation photons from positron decay) and the SiPM array performance in the last four years which together combine to deliver significant system performance in terms of speed, energy and timing resolution.
Physical and Chemical Stability of Glycerin Formulations Containing Extracts from Albizia myriophylla and Cha-Em-Thang Song
Creators: name: Puwadet Ritdet
Publisher: name: Faculty of Pharmaceutical Sciences KKU MSU UBU
Year: 2020
Subjects: Cha-Em-Thang Song, Glycerin, Stability, Traditional Thai Medicine

description: Isan Journal ofPharmaceutical Sciences, 16, 2, 45-56
Cost-outcome of Hepatocellular Carcinoma Screening at Roi-Et Hospital
Creators: name: Wittaya Roongjangram
Publisher: name: Faculty of Pharmaceutical Sciences KKU MSU UBU
Year: 2020
Subjects: Screening, Hepatocellular carcinoma, Cost

description: Isan Journal ofPharmaceutical Sciences, 16, 2, 21-29
Slurry flow, gravitational settling, and a proppant transport model for hydraulic fractures
Creators: name: Dontsov, E. V.
name: Peirce, Anthony
Publisher: name: The University of British Columbia
Year: 2014

description: The goal of this study is to analyze the steady flow of a Newtonian fluid mixed with spherical particles in a channel based on a continuum model, where the constitutive behaviour of the slurry is approximated by an empirical formula. In order to account for the gravitational settling of particles, two-dimensional flow needs to be considered as the pressure gradient and gravity may not always be collinear. It is shown that the problem under consideration features a boundary layer, whose size is on the order of the particle radius. The expressions for both the outer (i.e. outside the boundary layer) and inner (i.e. within the boundary layer) solutions are obtained in terms of the particle concentration, particle velocity, and fluid velocity. Unfortunately, these solutions require numerical solution of an integral equation, depend on the ratio between the pressure gradient and the gravity force, and the orientation of the pressure gradient relative to the gravity. Consequently, the development of a proppant transport model for hydraulic fracturing based on these results is not practical. For this reason, an approximate solution is introduced, where the effect of gravity is accounted for in an approximate fashion, reducing the complexity of the slurry flow solution. To validate the use of this approximation, the error is estimated for different regimes of flow. The approximate solution is then used to calculate the expressions for the slurry flux and the proppant flux, which are the basis for a model that can be used to account for proppant transport with gravitational settling in a fully coupled hydraulic fracturing simulator.
Evidence for a Cloud-Cloud Collision in Sh2-233 Triggering the Formation of the High-mass Protostar Object IRAS 05358+3543
Creators: name: Yamada, R. I.
name: Fukui, Y.
name: Sano, H.
name: Tachihara, K.
name: Bieging, John H.
name: Enokiya, R.
name: Nishimura, A.
name: Fujita, S.
name: Kohno, M.
name: Tsuge, Kisetsu
Publisher: name: arXiv
Year: 2021
Subjects: subject: Astrophysics of Galaxies (astro-ph.GA)
subject: FOS: Physical sciences

description: We have carried out a new kinematical analysis of the molecular gas in the Sh2-233 region by using the CO $J$ = 2-1 data taken at $\sim$0.5 pc resolution. The molecular gas consists of a filamentary cloud of 5-pc length with 1.5-pc width where two dense cloud cores are embedded. The filament lies between two clouds, which have a velocity difference of 2.6 km s$^{-1}$ and are extended over $\sim$5 pc. We frame a scenario that the two clouds are colliding with each other and compressed the gas between them to form the filament in $\sim$0.5 Myr which is perpendicular to the collision. It is likely that the collision formed not only the filamentary cloud but also the two dense cores. One of the dense cores is associated with the high-mass protostellar candidate IRAS 05358+3543, a representative high-mass protostar. In the monolithic collapse scheme of high mass star formation, a compact dense core of 100 $M_\odot$ within a volume of 0.1 pc radius is assumed as the initial condition, whereas the formation of such a core remained unexplained in the previous works. We argue that the proposed collision is a step which efficiently collects the gas of 100 $M_\odot$ into 0.1 pc radius. This lends support for that the cloud-cloud collision is an essential process in forming the compact high-mass dense core, IRAS 05358+3543.
description: 12 pages, 10 figures, two tables, submitted to Monthly Notices of Royal Astronomical Society(MNRAS)
Spin-orbit coupling effects over thermoelectric transport properties in quantum dots
Creators: name: Manya, M. A.
name: Martins, G. B.
name: Figueira, M. S.
Publisher: name: arXiv
Year: 2021
Subjects: subject: Mesoscale and Nanoscale Physics (cond-mat.mes-hall)
subject: FOS: Physical sciences

description: We study the effects caused by Rashba and Dresselhaus spin-orbit coupling over the thermoelectric transport properties of a single-electron transistor, viz., a quantum dot connected to one-dimensional leads. Using linear response theory and employing the numerical renormalization group method, we calculate the thermopower, electrical and thermal conductances, dimensionless thermoelectric figure of merit, and study the Wiedemann-Franz law, showing their temperature maps. Our results for all those properties indicate that spin-orbit coupling drives the system into the Kondo regime. We show that the thermoelectric transport properties, in the presence of spin-orbit coupling, obey the expected universality of the Kondo strong coupling fixed point. In addition, our results show a notable increase in the thermoelectric figure of merit, caused by the spin-orbit coupling in the one-dimensional quantum dot leads.
description: 12 pages, 15 figures
Efficient conversion of orbital Hall current to spin current for spin-orbit torque switching
Creators: name: Lee, Soogil
name: Kang, Min-Gu
name: Go, Dongwook
name: Kim, Dohyoung
name: Kang, Jun-Ho
name: Lee, Taekhyeon
name: Lee, Geun-Hee
name: Lee, Nyun Jong
name: Kim, Sanghoon
name: Kim, Kab-Jin
name: Lee, Kyung-Jin
name: Park, Byong-Guk
Publisher: name: arXiv
Year: 2021
Subjects: subject: Materials Science (cond-mat.mtrl-sci)
subject: Mesoscale and Nanoscale Physics (cond-mat.mes-hall)
subject: Applied Physics (physics.app-ph)
subject: FOS: Physical sciences

description: Spin Hall effect, an electric generation of spin current, allows for efficient control of magnetization. Recent theory revealed that orbital Hall effect creates orbital current, which can be much larger than spin Hall-induced spin current. However, orbital current cannot directly exert a torque on a ferromagnet, requiring a conversion process from orbital current to spin current. Here, we report two effective methods of the conversion through spin-orbit coupling engineering, which allows us to unambiguously demonstrate orbital-current-induced spin torque, or orbital Hall torque. We find that orbital Hall torque is greatly enhanced by introducing either a rare-earth ferromagnet Gd or a Pt interfacial layer with strong spin-orbit coupling in Cr/ferromagnet structures, indicating that the orbital current generated in Cr is efficiently converted into spin current in the Gd or Pt layer. Furthermore, we show that the orbital Hall torque can facilitate the reduction of switching current of perpendicular magnetization in spin-orbit-torque-based spintronic devices.
description: 19 pages, 3 figures
Authentication of Metropolitan Quantum Key Distribution Network with Post-quantum Cryptography
Creators: name: Yang, Yong-Hua
name: Li, Pei-Yuan
name: Ma, Shi-Zhao
name: Qian, Xiao-Cong
name: Zhang, Kai-Yi
name: Wang, Liu-Jun
name: Zhang, Wan-Li
name: Zhou, Fei
name: Tang, Shi-Biao
name: Wang, Jia-Yong
name: Yu, Yu
name: Zhang, Qiang
name: Pan, Jian-Wei
Publisher: name: arXiv
Year: 2021
Subjects: subject: Quantum Physics (quant-ph)
subject: FOS: Physical sciences

description: Quantum key distribution (QKD) provides information theoretically secures key exchange requiring authentication of the classic data processing channel via pre-sharing of symmetric private keys. In previous studies, the lattice-based post-quantum digital signature algorithm Aigis-Sig, combined with public-key infrastructure (PKI) was used to achieve high-efficiency quantum security authentication of QKD, and its advantages in simplifying the MAN network structure and new user entry were demonstrated. This experiment further integrates the PQC algorithm into the commercial QKD system, the Jinan field metropolitan QKD network comprised of 14 user nodes and 5 optical switching nodes. The feasibility, effectiveness and stability of the post-quantum cryptography (PQC) algorithm and advantages of replacing trusted relays with optical switching brought by PQC authentication large-scale metropolitan area QKD network were verified. QKD with PQC authentication has potential in quantum-secure communications, specifically in metropolitan QKD networks.
description: 11 pages, 3 figures
On a Set-Valued Young Integral with Applications to Differential Inclusions
Creators: name: Coutin, Laure
name: Marie, Nicolas
name: de Fitte, Paul Raynaud
Publisher: name: arXiv
Year: 2021
Subjects: subject: Probability (math.PR)
subject: FOS: Mathematics

description: We present a new Aumann-like integral for a Hölder multifunction with respect to a Hölder signal, based on the Young integral of a particular set of Hölder selections. This restricted Aumann integral has continuity properties that allow for numerical approximation as well as an existence theorem for an abstract stochastic differential inclusion. This is applied to concrete examples of first order and second order stochastic differential inclusions directed by fractional Brownian motion.
description: 25 pages
Q-dependent Collective Relaxation Dynamics of Glass-Forming Liquid Ca0.4K0.6(NO3)1.4 Investigated by Wide-Angle Neutron Spin-Echo
Creators: name: Luo, Peng
name: Zhai, Yanqin
name: Falus, Peter
name: Sakai, Victoria Garcia
name: Hartl, Monika
name: Kofu, Maiko
name: Nakajima, Kenji
name: Faraone, Antonio
name: Zhang, Yang
Publisher: name: arXiv
Year: 2021
Subjects: subject: Soft Condensed Matter (cond-mat.soft)
subject: FOS: Physical sciences

description: Employing wide-angle neutron spin echo spectroscopy, we measured the Q-dependent coherent intermediate scattering function of the prototypical ionic glass former Ca0.4K0.6(NO3)1.4, in the equilibrium and supercooled liquid states beyond the hydrodynamic regime. The data reveal a clear two-step relaxation: an exponential fast process, and a stretched exponential slow alpha process. de Gennes narrowing is observed in all characteristic variables of the alpha process: the relaxation time, amplitude, and stretching exponent. At all length scales probed, the relative amplitude of the alpha-relaxation decreases with increasing temperature and levels off in the normal liquid state. The temperature dependence of the stretching exponent and the relaxation time at different Q's indicate that modifications of the relaxation mechanisms at the local length scales, manifested as temperature independent dynamic heterogeneity and smaller deviations from Arrhenius behavior, have occurred even above the alpha-beta (Johari-Goldstein) bifurcation temperature.