Miracle-dz/UniFAR-FTUs huggingface dataset:
A NEW LASER COOLING METHOD FOR LITHIUM ATOM INTERFEROMETRY

Author(s): Kim, Geena | Advisor(s): Mueller, Holger | Abstract: An atom interferometer offers means to measure physical constants and physical quantities with a high precision, with relatively low cost and convenience as a table-top experiment. A precision measurement of a gravitational acceleration can test fundamental physics concepts such as Einstein equivalence principle (EEP). We identified that the two lithium isotopes (${}^{7}$Li and ${}^{6}$Li) have an advantage for the test of EEP, according to the standard model extension (SME). We aim to build the world's first lithium atom interferometer and test the Einstein equivalence principle. \We demonstrate a new laser cooling method suitable for a lithium atom interferometer. Although lithium is often used in ultra-cold atom experiments for its interesting physical properties and measurement feasibility, it is more difficult to laser cool lithium than other alkali atoms due to its unresolved hyperfine states, light mass (large recoil velocity) and high temperature from the oven. Typically, standard laser cooling techniques such as Zeeman slowers and magneto-optical traps are used to cool lithium atoms to about 1 mK, and the evaporative cooling method is used to cool lithium atoms to a few $\mu$K for Bose-Einstein condensate (BEC) experiments. However, for the atom interferometry purpose, the evaporative cooling method is not ideal for several reasons: First, its cooling efficiency is so low (0.01 \% or less) that typically only $10^4-10^5$ atoms are left after cooling when one begins with $10^9$ atoms. More atoms in an atom interferometer are needed to have a better signal to noise ratio. Second, an evaporative cooling is used to make a BEC, but we do not need a BEC to make an atom interferometer. In an atom interferometer, a high density of atoms as in a BEC should be avoided since it causes a phase shift due to atom interactions. Third, a setup for an evaporative cooling requires intricate RF generating coils or a high power laser. \With a simple optical lattice and a moderate laser power (100 mW), we achieved a sub-Doppler cooling of lithium by a new laser cooling method despite the fact that lithium has un-resolved hyperfine structure. We identified that the Sisyphus cooling and the adiabatic cooling mechanisms cooperate and give both lower temperature and higher cooling efficiency than the result that can be achieved by each alone. We cooled ${}^{7}$Li atoms to $\sim \;50\;\mu$K (about 8 times the recoil temperature) in a one dimensional lattice with cooling efficiency of $50\%$. In three dimensions the cooling temperature was limited to $90\,\mu$K due to instability of our 3D lattice, however the same principle applies and potentially a lower temperature can be achieved in 3D as well.
Radiation Pattern and Scattering Properties of Optical Antennas

When light emitting devices (e.g. LEDs) are coupled to optical antennas of the same resonance frequency, their spontaneous emission rate can be enhanced drastically. The ultimate goal is to have the rate of spontaneous emission faster than the stimulated emission so that the LEDs would be as fast as lasers and enable us to achieve energy efficient interconnects for on-chip communication[1]. In this project, we theoretically and experimentally measured the far-field radiation pattern and the light scattering spectrum of a series of as-fabricated optical antennas. These measurements enabled us to characterize and better understand the fundamental behaviors of optical antennas. Far Field Radiation Pattern Experiments:
Distribution and Recurrence of Warming‐Induced Retrogressive Thaw Slumps on the Central Qinghai‐Tibet Plateau

Retrogressive thaw slumps (RTSs) have become a dominant geomorphic event in permafrost regions due to the modern climate change. However, the roles of topographic, vegetation, and soil factors in influencing the spatial distribution and recurrence of RTSs remain not fully understood. Here, we identified the formation and recurrence of 459 RTSs during 2008–2021 using satellite images of the central Qinghai‐Tibet Plateau (Northwest of the Beiluhe Basin, 239 km2). We found that the topographic and environmental attributes of the RTSs exhibited strong correlations with the variation in the RTS density. The RTS‐affected areas had a higher slope, elevation, relative slope position, normalized difference vegetation index, soil water content, and lower soil bulk density than other landscapes. Regarding the influence of topographic and environmental attributes on the activity status of RTSs during 2018–2020, we found that the higher slope, elevation, and soil water content were advantageous for the activity of the RTSs. The RTSs with larger sizes and presenting an elongated shape were more likely to be active. Additionally, we examined the variation of the headwall shape of RTSs based on the fractal dimension and UAV‐based orthophoto. We found that the headwall shape of RTSs becomes more complicated due to the small‐scale thawing of ice‐rich permafrost, which may further induce subsequent thaw slumping. Higher air temperature triggers new RTSs, and increased precipitation may be responsible for the further activity of RTSs. Our findings can enhance our understanding of the development pattern and mechanism of RTSs in permafrost regions.
The Dynamics of Financial Markets - Mandelbrot's Cascades and Beyond

This is a short review in honor of B. Mandelbrot's 80st birthday, to appear in Wilmott magazine. We discuss how multiplicative cascades and related multifractal ideas might be relevant to model the main statistical features of financial time series, in particular the intermittent, long-memory nature of the volatility. We describe in details the Bacry-Muzy-Delour multifractal random walk. We point out some inadequacies of the current models, in particular concerning time reversal symmetry, and propose an alternative family of multi-timescale models, intermediate between GARCH models and multifractal models, that seem quite promising.
Calcium intake and osteoporosis: the inﬂuence of calcium intake from dairy products on hip bone mineral density and fracture incidence – a population-based study in women over 55 years of age

Objective: The incidence of osteoporosis increases with age and is most frequently observed in postmenopausal women. The objective of the present population-based cohort study was to assess the inﬂuence of Ca intake from dairy sources on hip bone mineral density and hip fracture incidence in a group of Polish women over 55 years of age
Learning Tomography Assessed Using Mie Theory

In Optical diffraction tomography, the multiply scattered field is a nonlinear function of the refractive index of the object. The Rytov method is a linear approximation of the forward model, and is commonly used to reconstruct images. Recently, we introduced a reconstruction method based on the Beam Propagation Method (BPM) that takes the nonlinearity into account. We refer to this method as Learning Tomography (LT). In this paper, we carry out simulations in order to assess the performance of LT over the linear iterative method. Each algorithm has been rigorously assessed for spherical objects, with synthetic data generated using the Mie theory. By varying the RI contrast and the size of the objects, we show that the LT reconstruction is more accurate and robust than the reconstruction based on the linear model. In addition, we show that LT is able to correct distortion that is evident in Rytov approximation due to limitations in phase unwrapping. More importantly, the capacity of LT in handling multiple scattering problem are demonstrated by simulations of multiple cylinders using the Mie theory and confirmed by experimental results of two spheres.
FASTdRNA: a workflow for the analysis of ONT direct RNA sequencing

Abstract Motivation Direct RNA-seq (dRNA-seq) using Oxford Nanopore Technology (ONT) has revolutionized transcript mapping by offering enhanced precision due to its long-read length. Unlike traditional techniques, dRNA-seq eliminates the need for PCR amplification, reducing the impact of GC bias, and preserving valuable base physical information, such as RNA modification and poly(A) length estimation. However, the rapid advancement of ONT devices has set higher standards for analytical software, resulting in potential challenges of software incompatibility and reduced efficiency. Results We present a novel workflow, called FASTdRNA, to manipulate dRNA-seq data efficiently. This workflow comprises two modules: a data preprocessing module and a data analysis module. The preprocessing data module, dRNAmain, encompasses basecalling, mapping, and transcript counting, which are essential for subsequent analyses. The data analysis module consists of a range of downstream analyses that facilitate the estimation of poly(A) length, prediction of RNA modifications, and assessment of alternative splicing events across different conditions with duplication. The FASTdRNA workflow is designed for the Snakemake framework and can be efficiently executed locally or in the cloud. Comparative experiments have demonstrated its superior performance compared to previous methods. This innovative workflow enhances the research capabilities of dRNA-seq data analysis pipelines by optimizing existing processes and expanding the scope of analysis. Availability and implementation The workflow is freely available at https://github.com/Tomcxf/FASTdRNA under an MIT license. Detailed install and usage guidance can be found in the GitHub repository.
Comparison of Maximum-Likelihood Estimation and Other Methods for Clutter Doppler Centroid Estimation

This paper investigates the performance of multiple approaches, including maximum likelihood estimation (MLE), for determining the Doppler frequency of radar returns from clutter scatterers. Fields backscattered from clutter are modeled as a complex stationary random process with a specified temporal correlation function received in the presence of additive thermal noise at a specified clutter-to-noise ratio. The MLE implementation is formulated, and its results are then compared through a simulation study to those obtained from traditional pulse-pair processing and other fast Fourier transform based methods in terms of error statistics and computational complexity. The methods are also compared for measurements of sea clutter from an X-band radar system. The results of the study show that the MLE approach has modest advantages over other methods in certain conditions, but that the performance gains obtained may often be insufficient to justify the extra computational cost or a-priori knowledge requirements of the method.
Inverse optimal controller based on extended Kalman filter for discrete‐time nonlinear systems

In this study, we present an inverse optimal control approach based on extended Kalman filter (EKF) algorithm to solve the optimal control problem of discrete‐time affine nonlinear systems. The main aim of inverse optimal control is to circumvent the tedious task of solving the Hamilton‐Jacobi‐Bellman equation that results from the classical solution of a nonlinear optimal control problem. Here, the inverse optimal controller is based on defining an appropriate quadratic control Lyapunov function (CLF) where the parameters of this candidate CLF were estimated by adopting the EKF equations. The root mean square error of the system states is used as the observed error in the case of classical EKF algorithm application, whereas, here, the EKF tries to eliminate the same root mean square error defined over the parameters by generating a CLF matrix with appropriate elements. The performance and the applicability of the proposed scheme is illustrated through both simulations performed on a nonlinear system model and a real‐time laboratory experiment. Simulation study demonstrate the effectiveness of the proposed method in comparison with 2 other inverse control approaches. Finally, the proposed controller is implemented on a professional control board to stabilize a DC‐DC boost converter and minimize a meaningful cost function. The experimental results show the applicability and effectiveness of the proposed EKF‐based inverse optimal control even in real‐time control systems with a very short time constant.
Gorenstein homological dimensions with respect to a semidualizing module

In this paper, let R be a commutative ring and C a semidualizing module. We investigate the (weak) C-Gorenstein global dimension of R and we get a simple formula to compute the C-Gorenstein global dimension. Moreover, we compare it with the classical (weak) global dimension of R and get the relations between them. At last, we compare the weak C-Gorenstein global dimension with the C-Gorenstein global dimension and we get that they are equal when R is Noetherian.
EKSPLORASI KONSEP GEOMETRI PADA GAME MOBILE LEGENDS

Perubahan dan perkembangan teknologi mengakibatkan berubahnya budaya dan kebiasaan manusia baik dari kalangan dewasa, remaja, bahkan anak-anak. Melihat dari peradaban sendiri sudah bergeser dengan munculnya era baru dimana pada masa ini manusia telah berdampingan dengan internet. Kata online sudah akrab terdengar di kalangan masyarakat salah satu hal yang saat ini sering menjadi perbincangan bahkan telah menjadi sebuah ajang bergengsi di televisi yaitu turnamen E-sport Mobile Legends. Penelitian ini bertujuan untuk mengeksplorasi konsep geometri yang ada pada game Mobile Legends. Teknik pengumpulan data penelitian ini adalah teknik observasi dan dokumentasi. Pemeriksaan keabsahan data dilakukan dengan triangulasi. Hasil penelitian menunjukkan bahwa pada game Mobile Legends terdapat bentuk-bentuk bangun datar seperti lingkaran, elips, persegi, persegi panjang, segitiga, segi banyak beraturan, dan segi banyak tak beraturan. Kemudian ada pula konsep geometri kesebangunan dan kekongruenan, transformasi geometri, dan bangun ruang limas. Konsep-konsep geometri ini dapat digunakan dalam pembelajaran matematika di sekolah.
GL-II-73, a Positive Allosteric Modulator of α5GABAA Receptors, Reverses Dopamine System Dysfunction Associated with Pilocarpine-Induced Temporal Lobe Epilepsy

Although seizures are a hallmark feature of temporal lobe epilepsy (TLE), psychiatric comorbidities, including psychosis, are frequently associated with TLE and contribute to decreased quality of life. Currently, there are no defined therapeutic protocols to manage psychosis in TLE patients, as antipsychotic agents may induce epileptic seizures and are associated with severe side effects and pharmacokinetic and pharmacodynamic interactions with antiepileptic drugs. Thus, novel treatment strategies are necessary. Several lines of evidence suggest that hippocampal hyperactivity is central to the pathology of both TLE and psychosis; therefore, restoring hippocampal activity back to normal levels may be a novel therapeutic approach for treating psychosis in TLE. In rodent models, increased activity in the ventral hippocampus (vHipp) results in aberrant dopamine system function, which is thought to underlie symptoms of psychosis. Indeed, we have previously demonstrated that targeting α5-containing γ-aminobutyric acid receptors (α5GABAARs), an inhibitory receptor abundant in the hippocampus, with positive allosteric modulators (PAMs), can restore dopamine system function in rodent models displaying hippocampal hyperactivity. Thus, we posited that α5-PAMs may be beneficial in a model used to study TLE. Here, we demonstrate that pilocarpine-induced TLE is associated with increased VTA dopamine neuron activity, an effect that was completely reversed by intra-vHipp administration of GL-II-73, a selective α5-PAM. Further, pilocarpine did not alter the hippocampal α5GABAAR expression or synaptic localization that may affect the efficacy of α5-PAMs. Taken together, these results suggest augmenting α5GABAAR function as a novel therapeutic modality for the treatment of psychosis in TLE.
Blind identification of under-determined mixtures based on the characteristic function: influence of the knowledge of source PDF's

When the number of inputs (sources) is larger than the number of outputs (observations), linear mixtures are referred to as Under-Determined (UDM). The algorithms proposed here aim at identifying UDM using the second characteristic function (c.f.) of observations, without any need of sparsity assumption on sources, but assuming their statistical independence. The first algorithm, already proposed by the authors in P. Comon and M. Rajih (2005), assumes that the source c.f. 's are unknown. In this paper, a variant of the algorithm is described, which allows to take into account the knowledge of source c.f. 's. Performances of both algorithms are compared based on computer simulations
Multitone PSK Modulation Design for Simultaneous Wireless Information and Power Transfer

Far-field wireless power transfer (WPT), based on radio frequency (RF) waves, came into the picture to fulfill the power need of large Internet-of-Things (IoT) networks, the backbone of the 5G and beyond era. However, RF communication signals carry both information as well as energy. Therefore, recently, simultaneous wireless information and power transfer (SWIPT) has attracted much attention in order to wirelessly charge these IoT devices. In this article, we propose a novel $N$ -tone multitone phase shift keying (PSK) modulation scheme, taking advantage of the nonlinearity of integrated receiver rectifier architecture. The main advantage of the proposed modulation scheme is the reduction in ripple voltage, introduced by the symbol transmission through phases. Achievable power conversion efficiency (PCE) and bit-error-rate (BER) at the output are considered to measure the efficacy of the proposed modulation scheme. Simulation results are verified by the measurements over the designed rectifier circuitry. The effect of symbol phase range, modulation order, and the number of tones are analyzed. In the future, this transmission scheme can be utilized to satisfy the data and power requirements of low-power IoT sensor networks.
Time-domain interpolation of head-related transfer functions with correct reproduction of notch frequencies

Realistic synthesis in virtual binaural displays requires interpolation of the complex frequency and phase responses of head-related transfer functions (HRTFs) to correctly reproduce the acoustical impact of small changes in sound source position. State-of-the-art interpolation approaches are classified into time and frequency domain interpolation. Frequency domain interpolation cannot reproduce the direction specific position of spectral notches in HRTFs leading to interpolation errors due to a flattening of filter notches, and it has difficulties reconstructing the phase. Time domain interpolation is prone to comb filter artefacts caused by incorrect temporal alignment.
Synchrotron Intensity Gradients as Tracers of Interstellar Magnetic Fields

On the basis of the modern understanding of MHD turbulence, we propose a new way of using synchrotron radiation: using synchrotron intensity gradients (SIGs) for tracing astrophysical magnetic fields. We successfully test the new technique using synthetic data obtained with 3D MHD simulations and provide the demonstration of the practical utility of the technique by comparing the directions of magnetic fields that are obtained with PLANCK synchrotron intensity data to the directions obtained with PLANCK synchrotron polarization data. We demonstrate that the SIGs can reliably trace magnetic fields in the presence of noise and can provide detailed maps of magnetic field directions. We also show that the SIGs are relatively robust for tracing magnetic fields while the low spatial frequencies of the synchrotron image are removed. This makes the SIGs applicable to the tracing of magnetic fields using interferometric data with single-dish measurement absent. We discuss the synergy of using the SIGs together with synchrotron polarization in order to find the actual direction of the magnetic fields and quantify the effects of Faraday rotation as well as with other ways of studying astrophysical magnetic fields. We test our method in the presence of noise and the resolution effects. We stress the complementary nature of the studies using the SIG technique and those employing the recently introduced velocity gradient techniques that trace magnetic fields using spectroscopic data.
Stochastic Velocity Prediction for Connected Vehicles Considering V2V Communication Interruption

Reliable and accurate velocity prediction can significantly contribute to the quality of connected vehicle control applications. Existing efforts focus on the velocity prediction without considering vehicle-to-vehicle (V2V) communication interruption. Hence, a stochastic velocity prediction method for connected vehicles considering V2V communication interruption is put forward for the first time. The missing V2V communication data are addressed by the piecewise cubic Hermite spline interpolation. Then, the processed data are used as the input variables of the best conditional linear Gaussian (CLG) prediction model. Specifically, the best CLG model is obtained by analyzing the influence of different input variables on the velocity prediction without V2V communication interruption. The results demonstrate that the prediction accuracy of CLG-based model is acceptable if the communication interruption time is less than 5 s compared to the non-interrupted V2V communication case. The sensitivity study of the best CLG model under multiple vehicles scenario indicates that choosing appropriate historical data substantially improve the prediction accuracy. Furthermore, the CLG-based predictor is proved to be an effective method to achieve higher prediction accuracy in two test road networks when compared with the Back-propagation and Long Short-Term Memory network.
A Magnetic Millirobot Walks on Slippery Biological Surfaces for Targeted Cargo Delivery

Small-scale robots hold great potential for targeted cargo delivery in minimally invasive medicine. However, current robots often face challenges in locomoting efficiently on slippery biological tissue surfaces, especially when loaded with heavy cargo. Here, we report a magnetic millirobot that can walk on rough and slippery biological tissues by anchoring itself on the soft tissue surface alternatingly with two feet and reciprocally rotating the body to move forward. We experimentally studied the locomotion, validated it with numerical simulations, and optimized the actuation parameters to fit various terrains and loading conditions. Furthermore, we developed a permanent magnet set-up to enable wireless actuation within a human-scale volume that allows precise control of the millirobot to follow complex trajectories, climb vertical walls, and carry cargo up to four times its own weight. Upon reaching the target location, it performs a deployment sequence to release the liquid drug into tissues. The robust gait of our millirobot on rough biological terrains, combined with its heavy load capacity, makes it a versatile and effective miniaturized vehicle for targeted cargo delivery.
Global Quasi Linearization (GQL) for the automatic reduction of chemical kinetics

In the present work a new approach for automatic reduction of chemical kinetics models, the so-called Global Quasi-Linearization (GQL) method is discussed. The suggested approach is a result of an analytical study of the ILDM method from the point of view of the general framework of singular perturbation theory. This method has been developed in order to overcome difficulties of the theoretical concept of slow manifolds in simulations of reacting flows. The method is implemented within the standard ILDM method and applied to a simple, but meaningful combustion chemistry model, namely, the carbon-monoxide system. The results of the simulations show a good agreement of the detailed model with reduced one and demonstrate the potential of the suggested method.