Miracle-dz/UniFAR-FTUs huggingface dataset:
Supermirror neutron guide system for neutron resonance spin echo spectrometers at a pulsed neutron source

ABSTRACT A neutron guide system for neutron resonance spin echo spectrometers has been constructed at BL06 of the Japan Proton Accelerator Research Complex, Materials and Life Science Experimental Facility. The spectrometers consist of two types of neutron spin echo instruments, a modulated intensity by zero effort instrument (MIEZE) and a neutron resonance spin echo instrument (NRSE), to cover a wide energy range for various sample environments. A neutron beam from the moderator is deflected by supermirror neutron guides, split, and separately guided into the MIEZE and NRSE. The characteristic wavelengths of the neutron guide tube for the MIEZE and NRSE are 2.9 and 4.9 Å, respectively. The cross sections of the exit of the MIEZE and NRSE guides are 15 mm × 50 mm and 30 mm × 50 mm, respectively. The neutronics and shielding design were optimized by using the heavy ion transport code system (PHITS), and the absolute average neutron fluxes at the exits of the MIEZE and NRSE guides are estimated to be 2.7 × 108 and 6.9 × 108 n/cm2/s/MW, respectively. The measured fluxes of the MIEZE and NRSE neutron guides are 0.56 and 0.95 times the calculated values, respectively.
Neuronal activity and remyelination: new insights into the molecular mechanisms and therapeutic advancements

This article reviews the role of neuronal activity in myelin regeneration and the related neural signaling pathways. The article points out that neuronal activity can stimulate the formation and regeneration of myelin, significantly improve its conduction speed and neural signal processing ability, maintain axonal integrity, and support axonal nutrition. However, myelin damage is common in various clinical diseases such as multiple sclerosis, stroke, dementia, and schizophrenia. Although myelin regeneration exists in these diseases, it is often incomplete and cannot promote functional recovery. Therefore, seeking other ways to improve myelin regeneration in clinical trials in recent years is of great significance. Research has shown that controlling neuronal excitability may become a new intervention method for the clinical treatment of demyelinating diseases. The article discusses the latest research progress of neuronal activity on myelin regeneration, including direct or indirect stimulation methods, and the related neural signaling pathways, including glutamatergic, GABAergic, cholinergic, histaminergic, purinergic and voltage-gated ion channel signaling pathways, revealing that seeking treatment strategies to promote myelin regeneration through precise regulation of neuronal activity has broad prospects.
Cosmic Ray Dynamics in Galaxies and Galaxy Clusters

Author(s): Wiener, Joshua | Advisor(s): Oh, Peng | Abstract: Cosmic rays comprise a significant amount of energy in galaxy clusters, and are as energetically important in galaxies as the thermal gas. A careful treatment of cosmic ray transport is necessary to predict dynamics (such as CR driven winds) based on the radio observations which indicate their abundance. Yet the physics of cosmic ray transport are not very well understood. In this dissertation I will discuss how cosmic rays travel through and couple energetically with magnetized plasma, focusing specifically on the effects of streaming and heating in cluster and galactic environments.
Inertial microfluidic vortex cell sorter

Sorting and purification of target cells from complex cellular samples is critical for downstream cell biology research, biomedical research and clinical diagnostics. In this work, a novel microfluidic platform is developed to achieve size-based sorting of cells with high performance and systematic versatility. The platform uses inertial effect of fluid and microscale vortices in designed microfluidic units to align and sort cells. A microfluidic unit was first developed to enable bimodal sorting of cells with high sorting resolution and tunability. Microparticle mixture with only 2 μm difference was continuously sorted with > 90% efficiency. Two sorting units were then integrated into specific arrangements to enable versatile cell sorting functions. A serial sequencing arrangement enabled new multimodal sorting function. Multisized or heterogeneous microparticle mixtures were sorted continuously into three subpopulations of different sizes with > 90% efficiency. Alternative arrangement of the two units enabled new double sorting and purification function. The larger target cells can be extracted from the small non-target cells two times sequentially yielding highly purified target cell product. Spiked human cancer stem-like cells (HuSLCs) were sorted from human blood samples with enriched concentration and significantly enhanced purity. The two distinct arrangements exhibit the systematic versatility of the vortex cell sorting platform for efficient sorting of complex cellular samples which will open new opportunities for size-based cellular sample preparation in cell biology, biomedical research and clinical diagnostics.
Radar Signal Recognition Based on Dual-Channel Model With HOG Feature Extraction

Objectives: To improve the recognition accuracy of radar signals under a low signal-to-noise ratio (SNR). Technology or Method: We propose a novel radar signal recognition method based on a dual-channel model with the histogram of oriented gradients (HOG) feature extraction. Specifically, multisynchrosqueezing transform (MSST) and Choi–Williams distribution (CWD) transform are adopted individually to obtain the time–frequency distribution images of radar signals, and HOG feature extraction is performed on the preprocessed time–frequency images of each channel, respectively. Then, the features of the two channels are fused and dimensionally reduced by the principal component analysis (PCA). Finally, the compact feature parameters are fed to the support vector machine (SVM) classifier to identify radar signals. Clinical or Biological Impact: The experimental results demonstrate that the proposed model achieves a high recognition performance with a small computational complexity, especially in low SNR. When the SNR is −12 dB, the recognition accuracy can reach more than 92%, which is over 6% higher than that of single-channel models and related convolutional neural network-based models.
Rigidity Maintenance Control for Multi-Robot Systems

Rigidity of formations in multi-robot systems is important for formation control, localization, and sensor fusion. This work proposes a rigidity maintenance gradient controller for a multi-agent robot team. To develop such a controller, we first provide an alternative characterization of the rigidity matrix and use that to introduce the novel concept of the rigidity eigenvalue. We provide a necessary and sufficient condition relating the positivity of the rigidity eigenvalue to the rigidity of the formation. The rigidity maintenance controller is based on the gradient of the rigidity eigenvalue with respect to each robot position. This gradient has a naturally distributed structure, and is thus amenable to a distributed implementation. Additional requirements such as obstacle and inter-agent collision avoidance, as well as typical constraints such as limited sensing/communication ranges and line-of-sight occlusions, are also explicitly considered. Finally, we present a simulation with a group of seven quadrotor UAVs to demonstrate and validate the theoretical results.
Uncommon (in)stability properties in the numerical method of characteristic applied to hyperbolic equations

This thesis presents the stability analysis of the numerical method of characteristic (MoC) that is applied to hyperbolic partial differential equations (PDEs). Simple Euler method, Modified Euler method and Leapfrog method are used for numerical integration along the characteristics. The corresponding MoC schemes are referred to as MoC-SE, MoC-ME, and MoC-LF respectively. We discovered and explained two unusual phenomena. First, certain non-periodic boundary condition (b.c.) could eliminate the numerical instability for some schemes such as the MoC-ME, where the instability exists for periodic b.c. However, it is commonly believed that if von Neumann analysis, i.e., assuming periodic b.c., predicts numerical instability, then there must be numerical instability if one uses non-periodic b.c. Second, a symplectic method (LF), which is known to work well for energypreserving ordinary differential equations, introduces a strong numerical instability when integrating energy-preserving PDEs by the MoC. In this thesis, we worked out a new method of analyzing the numerical scheme with non-periodic boundary conditions and explained in details why the non-periodic boundary conditions could eliminate the numerical instability. We also illustrated why our result contradicts the common knowledge that von Neumann stability is necessary for numerical stability of the scheme. Table of
Assessment of Phobos gravity field determination from both near polar and near equatorial orbital flyby data

The C20 and C22 coefficients of the Phobos gravity field are key parameters to constrain the internal structure of the Martian moon, but reliable observed values of these parameters are still missing. In this paper, we demonstrate, through a combination of forward and inverse modelling of simulated Doppler spacecraft tracking data collected from the Earth, that a Phobos flyby along a near polar Mars orbit is optimal when determining the C20 coefficient, and further, that a near equatorial flyby Mars orbit is optimal for determination of the C22 coefficient. Therefore, the combination of a near polar and a near equatorial orbit is an effective way to determine the Phobos C20 and C22 gravity field coefficients. This work provides a reference for a future Chinese Mars mission.
Optimization of a thermally tuned silicon-based reconfigurable optical power splitter with thermal isolations

Abstract. In this paper, a thermally tuned silicon-based three-channel reconfigurable multimode interference (MMI) optical power splitter with four optimized thermal isolations is proposed. Specific and flexible reconfigurable functions (1×1, 1×2, and 1×3 MMI splitters) can be achieved by thermally tuning the heaters. By using a beam propagation method, the optimum geometry of the heaters, desired refractive index changes, and phase shifts of the MMI splitter are calculated at first. The temperature distributions of the devices without and with the thermal isolations are then analyzed by using the finite element method. Thermal crosstalk between adjacent heaters is observed and the influence of the thermal isolation geometry on the thermal crosstalk is examined subsequently. The geometry of the thermal isolations is optimized based on the trade-off between the thermal tuning efficiency and optical output characteristics. Finally, satisfactory improvements with the proposed structure are demonstrated with high-thermal efficiency (the maximum power dissipation decreases reach 43.7% and 55.2% for 1×1 and 1×2 MMI splitters, respectively) and good optical output quality (the maximum excess losses are as low as 0.365, 0.388, and 0.272 dB for 1×1, 1×2, and 1×3 MMI splitters, respectively; the crosstalk is less than −21.27 and −15.54 dB for 1×1 and 1×2 MMI splitters, respectively).
Optimal MDS codes for cooperative repair

Two widely studied models of multiple-node repair in distributed storage systems are centralized repair and cooperative repair. The centralized model assumes that all the failed nodes are recreated in one location, while the cooperative one stipulates that the failed nodes may communicate but are distinct, and the amount of data exchanged between them is included in the repair bandwidth. We present two families of $(n,k)$ MDS codes with optimal cooperative repair. Codes in the first family support optimal repair of any two erasures from any $d$ helper nodes for any given $k\le d\le n-2. $ Codes in the second family support optimal repair of any $h$ failed nodes, $2\le h\le n-k-1,$ from any $k+1$ helper nodes.
Three-dimensional CFD simulations of natural and forced convection solar domestic water heating systems

3 D CFD Simulations of natural and forced convection solar domestic water heating systems by Sachin Sudhakar Deshmukh Dr. Samir Moujaes, Examination Committee Chair Professor, Mechanical Engineering University of Nevada, Las Vegas The objective of the thesis is to study the thermal performance of the open loop natural convection and closed loop forced convection solar water heating system. The 3 dimensional (3D) numerical models were made in the Computer aided design (CAD) package and were simulated for the 12 hours of day time. Analysis was performed using the Computational fluid dynamics (CED) software package Star-CD. The physical system of natural convection can he used for the purpose of heating domestic hot water without the use of a circulating pump. The closed loop forced circulation system is simulated to study the numerical behavior of the system with respect to time which can further predict the performance of the system when it is connected to the water mains for actual residential applications. The solar water heater that is being simulated is a truly flat surface collector where the water is allowed to flow in a thin rectangular channel cross-section. The CFD simulations are performed to predict the velocity and temperature of the water in these
$\mathsf{HyHooVer}$: Verification and Parameter Synthesis in Stochastic Systems With Hybrid State Space Using Optimistic Optimization

This article presents a new method for model-free verification of a general class of control systems with unknown nonlinear dynamics, where the state space has both a continuum-based and a discrete component. Specifically, we focus on finding what choices of initial states or parameters maximize a given probabilistic objective function over all choices of initial states or parameters from such hybrid state space, without having exact knowledge of the system dynamics. We introduce the notion of set initialized Markov chains to represent such systems. Our method utilizes generalized techniques from multi-armed bandit theory on the continuum, in an attempt to make an efficient use of the available sampling budget. We introduce a new algorithm called the Hybrid Hierarchical Optimistic Optimization (HyHOO) algorithm, which is designed to address the problem outlined in this paper. The algorithm combines elements of the existing Hierarchical Optimistic Optimization (HOO) bandit algorithm with carefully chosen parameters to create a fresh perspective on the problem. By viewing the problem as a multi-armed bandit problem, we are able to provide theoretical regret bounds on sample efficiency of our tool, $\mathsf{HyHooVer}$. This is achieved by making assumptions about the smoothness of the underlying system. The results of experiments in formal verification and parameter synthesis of variety of scenarios, indicate that the proposed method is effective and efficient when applied to realistic-sized problems and it performs well compared to other methods, specifically PlasmaLab, BoTorch, and the baseline HOO algorithm. Specifically, it demonstrates better efficiency when employed on models with large state space and when the objective function has sharp slopes in comparison with other tools.
PCR-based gene targeting in Hanseniaspora uvarum.

Lack of gene-function analyses tools limits studying the biology of Hanseniaspora uvarum, one of the most abundant yeasts on grapes and in must. We investigated a rapid PCR-based gene targeting approach for one-step gene replacement in this diploid yeast. To this end, we generated and validated two synthetic antibiotic resistance genes, pFA-hygXL and pFA-clnXL, providing resistance against hygromycin and nourseothricin, respectively, for use with H. uvarum. Addition of short flanking-homology regions of 56‒80 bp to these selection markers via PCR was sufficient to promote gene targeting. We report here the deletion of the H. uvarum LEU2 and LYS2 genes with these marker genes via two rounds of consecutive transformations, each resulting in the generation of auxotrophic strains (leu2/leu2; lys2/lys2). The hereby constructed leucine auxotrophic leu2/leu2 strain was subsequently complemented in a targeted manner, thereby further validating this approach. PCR-based gene targeting in H. uvarum was less efficient than in Saccharomyces cerevisiae. However, this approach combined with the availability of two marker genes, provides essential tools for directed gene manipulations in H. uvarum.
China’s digital diplomacy on Twitter: The multiple reactions to the Belt and Road Initiative

This article examines three aspects of China’s digital diplomacy efforts about the Belt and Road Initiative (BRI) on Twitter between February 9th 2019 to January 3rd 2020. First, it explores the frequency and geographical distribution of tweets about the BRI. Second, it scrutinises the main topics discussed in such tweets. Finally, it describes the actors producing BRI content. Results show that Chinese digital diplomacy has been proactive on Twitter, driven by the posting practices of its main international broadcasting organisations and BRI partners. As such, China’s digital diplomacy is becoming more relational. However, the open nature of Twitter also paves the way to numerous counter narratives disseminated by other users critical of the BRI, namely, Western media, think tanks, academics, and citizens, who undermine the stories that China aims to convey. These criticisms expose the limits of China’s digital diplomacy and of the sensationalist reporting of its alleged direct effects on audiences.
Cancer 3D Models for Metallodrug Preclinical Testing

Despite being standard tools in research, the application of cellular and animal models in drug development is hindered by several limitations, such as limited translational significance, animal ethics, and inter-species physiological differences. In this regard, 3D cellular models can be presented as a step forward in biomedical research, allowing for mimicking tissue complexity more accurately than traditional 2D models, while also contributing to reducing the use of animal models. In cancer research, 3D models have the potential to replicate the tumor microenvironment, which is a key modulator of cancer cell behavior and drug response. These features make cancer 3D models prime tools for the preclinical study of anti-tumoral drugs, especially considering that there is still a need to develop effective anti-cancer drugs with high selectivity, minimal toxicity, and reduced side effects. Metallodrugs, especially transition-metal-based complexes, have been extensively studied for their therapeutic potential in cancer therapy due to their distinctive properties; however, despite the benefits of 3D models, their application in metallodrug testing is currently limited. Thus, this article reviews some of the most common types of 3D models in cancer research, as well as the application of 3D models in metallodrug preclinical studies.
The effects of assembly bias on galaxy clustering predictions

The Halo Occupation Distribution (HOD) model is frequently used in surveys to predict the mass of the dark matter haloes from the clustering of galaxies. On the other hand, semi-analytical models (SAMs) of galaxy formation are often used to populate simulations according to some physical prescriptions and merger trees. We compare galaxy bi s measured in SAMs with the bias reconstructed from the halo bias and HOD measured in the sam simulations. We find that the reconstruction underestimates the bias by 5 − 10%, which translates in 50% overestimation of the halo mass. We attribute this failure to assembly bias. The clustering of haloes with M . 3−5×10hM⊙ depends strongly on environment (number of subhaloes) and t his also reflects in different clustering for galaxies with different lumino sity but equal halo mass. Thus we need to include properties other than halo mass to do a proper HOD r econstruction.
Quantum hypothesis testing : theory and applications to quantum sensing and data readout

In this thesis we investigate the theory of quantum hypothesis testing and its potential applications for the new area of quantum technologies. We first consider the asymmetric formulation of quantum hypothesis testing where the aim is to minimize the probability of false negatives and the main tool is provided by the quantum Hoeffding bound. In this context we provide a general recipe for computing this bound in the most important scenario for continuous variable quantum information, that of Gaussian states. We then study both asymmetric and symmetric quantum hypothesis testing in the context of quantum channel discrimination. Here we show how the use of quantum-correlated light can enhance the detection of small variations of transmissivity in a sample of photodegrabable material, while a classical source of light either cannot retrieve information or would destroy the sample. This non-invasive quantum technique might be useful to realize in-vivo and real-time probing of very fragile biological samples, such as DNA or RNA. We also show that the same principle can be exploited to build next-generation memories for the confidential storage of confidential data, where information can be read only by well-tailored sources of entangled light.
Do Inclusive Workplace Policies Foster Employer Attractiveness? Comparative Evidence From an Online Employer Review Platform

Public sector employers increasingly promote inclusive workplaces, but the impact of such policies on employees’ perceptions of employer attractiveness has rarely been studied. A deeper understanding of how inclusive workplaces relate to employer attractiveness, and how this relationship differs between employment sectors, may inform recruitment policies and retention management. This study tackles this issue and provides a large-scale analysis of an online employer review platform, covering more than 16,000 Germany-based organizations as rated and recommended (or not) by more than 715,000 current and former employees. More specifically, it builds on person–organization fit theory and analyzes how employee referrals are associated with ratings in three dimensions of inclusive workplaces (i.e., inclusion of women, elderly, and disabled). The results show that inclusive workplaces are positively and significantly related to employer attractiveness, both on aggregate and across the three dimensions. The overall relationship is stronger in the case of public employers when compared with private employers, while there are no sector differences in the relationship when comparing public and nonprofit employers. The findings suggest that inclusive workplaces are advantageous in terms of employer attractiveness, not just for the beneficiaries of such policies, but even more so in the public sector.
Balinese Way of Governing Water: A Social Survey on Water Governance

The ever increasing human population demands more extraction of freshwater to fulfill our basic needs. This put more pressure to the already limited water resource. The previous studies about water governance concludes that local community needs to be actively involved in an integrated water resource management (IWRM) in order to maintain sustainability. Balinese has long been known as community which always preserve water due to their belief in their local wisdom. This article aims to investigate how Balinese local wisdom play its role in the water governance. The social survey study was conducted using descriptive analysis. The data was collected in Badung District of Bali Province with purposive sampling of 100 respondents who live in Badung for the last 10 years and of 17 years old above. The result of the study shows that Balinese may not really aware about Tri Hita Karana and Sad Kertih, but they are practising its principle in their daily life. Balinese respect water as part of nature which must be preserved.