Miracle-dz/UniFAR-FTUs huggingface dataset:
Proposing new experiments to test the quantum-to-classical transition

An open problem in modern physics is why microscopic quantum objects can be at two places at once (i.e. a superposed quantum state) while macroscpoic classical object never show such a behaviour. Collapse models provides a quantitative answer for this problem and explain how macroscopic classical world emerges out of microscopic quantum world. A universal noise field is postulated in collapse models, inducing appropriate Brownian- motion corrections to standard quantum dynamics. The strength of collapse-driven Brownian fluctuations depend on: (i) the parameters characterizing the system (e.g., mass, size, density), and (ii) two phenomenological parameters defining the statistical properties of the collapse noise. The collapse-driven Brownian motion works such that microscopic systems behave quantum mechanically, while macroscopic objects are classical. At the intermediate mesocopic scale, collapse models predict deviations from standard quantum predictions. This issue has been subject of experimental tests. All experiments to date have been at the scales where collapse effects are negligible for all practical purposes. However, recent experimental progress in revealing quantum features of larger objects, increases the hope for testing at unprecedented scales where collapse models can be falsified. Current experiments are mainly focused on the preparation of macroscopic systems in a spatial quantum superposition state. The collapse effects would then manifest as loss of visibility in the observed inference pattern. However, one needs a quantum interference with single particles of mass ∼ 1010amu for a decisive test of collapse models. Creating such massive superpositionsis quite challenging, and beyond currectstate-of-the-art. Quite recently, an alternative approach has been proposed where the collapse manifests in the fluctuating properties of light interacting with the quantum system. The great advantage of this new approach is that here there is no need for the preparation of a quantum superposed state. It has been discussed that promising results can be revealed in the spectrum of light interacting with a radiation pressure-driven mechanical oscillator in a cavity optomechanics setting. Here, we review the theoretical modelling of the above optomechenical proposal. We discuss how collapse-driven Brownian motion modifies the spectrum. We quantify the collapse effect and explain how it depends on the parameters of the mechanical oscillator (e.g., mass, density, geometry).
Development and test of 60 kV coaxial fast rising pulse source

Based on ceramic pulse capacitors and high press gas switch,a 60 kV coaxial fast rising pulse source was developed.A foil capacitive divider and a resistive divider were developed for measuring the output voltage of the fast rising pulse source.The test result indicats that the rising time of the output voltage of the pulse source is less than 2.3 ns and the pulse width is about 28 ns with a 50 Ω dummy load.This result agrees with the newest EMP standard of IEC.
Data generation and separation of AM radio collisions with machine learning

A yet-unsolved problem in the Radio Frequency (RF) domain is with transmission collisions in Amplitude Modulated (AM) radio, an example of which is air traffic control radios. In a high-traffic environment like aviation, radio operators often unknowingly transmit at the same time, leading to other radios receiving both transmissions layered together. This renders both transmissions difficult – if not impossible – to understand, leading to frustration at best and, at worst, critical transmissions being completely lost. Machine learning (ML) can successfully separate multiple overlapping speakers in audio, but we extend this idea to the RF domain. Training a performant ML model for such a scenario requires ample quantities of not only the signals with the overlapping transmissions, but also each original, individual signal. This data is easier to collect for audio – and many open-source datasets for such tasks are readily available – but no such datasets exist for AM radio separation. To collect adequate volumes of such data that is sufficiently diverse would be time-consuming and expensive. To solve this problem, we turn to data generation. Using our custom data generation pipeline combined with a Deep Neural Network (DNN), we demonstrate a 98.9% increase in signal separation efficacy when using AM radio as compared to when using audio alone. AM radio collision mitigation has broad implications, especially in congested scenarios with a high likelihood of colliding transmitters like aviation communications. Successful separation of such signals enables mitigation logic, leading to a smoother and safer user experience.
Mobile Robot Navigation Strategies Through Behavioral Cloning and Generative Adversarial Imitation Learning

: The conception of robots able to navigate autonomously through several environments remains one of the main challenges to be overcome in the robotics research. The wide use of machine learning techniques as imitation learning has obtained efficient performance in this research field. The autonomous navigation is essential to carry out many kinds of task, which it can reduce the time and computational cust. One of the mechanisms to a robot be autonomous is observe the behavior of the other. Therefore, it is proposed in this research the development of a strategy of navigation based on Generative Adversarial Imitation Learning (GAIL) for the learning of the navigational behaviors of distinct mobile robots with different locomotion strategies. The CoppeliaSim simulator is used to build virtual scenarios and execute experiments to gather samples for the strategy training. Another strategy will be developed based on the behavioral cloning, which will also be trained in some environments with the same samples used in GAIL. Regression error metrics in addition with the comparison of the paths generated by the strategies in each scenario will be considered as evaluation methods. The obtained results are then discussed along with the potential future works.
Equitable distribution of perishable items in a food bank supply chain

In the United States, food banks play an important role in helping to reduce the rate of food insecurity by distributing donated food among the population in need. One of the challenges that food banks face is to equitably distribute food donations among their clients such that, ideally, each recipient receives the same amount of food. They aim to do so while minimizing waste that occurs due to spoilage and capacity limitations. Perishable food items present specific challenges since they are susceptible to spoilage and need to be distributed before their expiry dates. Based on our longstanding partnership with a large food bank located in the southeastern United States, we present a capacitated, multiperiod, multiproduct network flow model to help them equitably and effectively distribute perishable food donations among the food‐insecure population in their service region. The model is applied within the context of a case study and reveals managerial insights that would be useful to practitioners. Our findings show that although equity is one of the food bank's highest priorities, inequities cannot be eliminated completely. Given the inevitability of inequitable food allocations in practice, this paper provides food banks guidance on how to strategically control inequities using two approaches: (i) by increasing the number of periods for which equity should be satisfied or ( i i $ii$ ) by allowing deviations from a perfectly equitable distribution. The results show that modest deviations from perfect equity using either approach can lead to significant improvements in both the quality and quantity of food distributed and can also reduce food waste. While approach ( i i $ii$ ) is preferable, the most desirable outcomes occur when both are applied simultaneously. We also find that county capacities inhibit a food bank's ability to achieve balance between equity and effectiveness when distributing perishables. Our framework provides food banks the flexibility to balance the trade‐off between effectiveness and equity based on their preferences.
Coherent Power Combination in a Resonant-Tunneling-Diode Arrayed Oscillator With Simplified Structure

Coherent resonant-tunneling-diode (RTD) oscillator array is promising for high-power terahertz sources. However, it is complicated to identify the proper operation mode in an arrayed RTD oscillator. Here, we established a simple and general analytical method for operation modes in RTD arrayed oscillators. We also proposed and fabricated a terahertz slot antenna integrated RTD oscillator array coupled by a resistor for stable operation and coherent power combining. From the analysis for the resistor-coupled oscillator array, we found that the odd-mode operation, where adjacent oscillators operate in antiphase condition, is stable. Hence, we proposed an arrayed structure with a right-angle connection between adjacent oscillators for coherent power combination and validation of operation mode. In preliminary experiments, we successfully fabricated two-element resistor-coupled arrayed oscillators. Output power and oscillation spectrum measurements showed that coherent power combination was achieved in arrayed oscillators. The odd-mode operation was validated by polarization measurements. Relatively high output powers of ∼770 μW were obtained at 530 GHz in two-element arrayed oscillators with offset-fed slot antennas.
Problème d'ordonnancement multicritère dans un flowshop hybride avec recirculation

Nous presentons un programme lineaire en nombres entiers pour resoudre un probleme multicritere de typeflowshop hybride dans lequel les travaux sont autorises a repasser plusieurs fois sur un etage. Le probleme identifie est NP-difficile. Deux dates dues sont associees a chaque travail. La premiere concerne une operation de la gamme, la seconde concerne la derniere operation de la gamme. On cherche pour ce probleme un ordonnancement qui minimise un critere relativement a la premiere date due, et un autre critere relativement a la seconde.
Molecular Mechanisms of Neurogenic Lower Urinary Tract Dysfunction after Spinal Cord Injury

This article provides a synopsis of current progress made in fundamental studies of lower urinary tract dysfunction (LUTD) after spinal cord injury (SCI) above the sacral level. Animal models of SCI allowed us to examine the effects of SCI on the micturition control and the underlying neurophysiological processes of SCI-induced LUTD. Urine storage and elimination are the two primary functions of the LUT, which are governed by complicated regulatory mechanisms in the central and peripheral nervous systems. These neural systems control the action of two functional units in the LUT: the urinary bladder and an outlet consisting of the bladder neck, urethral sphincters, and pelvic-floor striated muscles. During the storage phase, the outlet is closed, and the bladder is inactive to maintain a low intravenous pressure and continence. In contrast, during the voiding phase, the outlet relaxes, and the bladder contracts to facilitate adequate urine flow and bladder emptying. SCI disrupts the normal reflex circuits that regulate co-ordinated bladder and urethral sphincter function, leading to involuntary and inefficient voiding. Following SCI, a spinal micturition reflex pathway develops to induce an overactive bladder condition following the initial areflexic phase. In addition, without proper bladder–urethral-sphincter coordination after SCI, the bladder is not emptied as effectively as in the normal condition. Previous studies using animal models of SCI have shown that hyperexcitability of C-fiber bladder afferent pathways is a fundamental pathophysiological mechanism, inducing neurogenic LUTD, especially detrusor overactivity during the storage phase. SCI also induces neurogenic LUTD during the voiding phase, known as detrusor sphincter dyssynergia, likely due to hyperexcitability of Aδ-fiber bladder afferent pathways rather than C-fiber afferents. The molecular mechanisms underlying SCI-induced LUTD are multifactorial; previous studies have identified significant changes in the expression of various molecules in the peripheral organs and afferent nerves projecting to the spinal cord, including growth factors, ion channels, receptors and neurotransmitters. These findings in animal models of SCI and neurogenic LUTD should increase our understanding of pathophysiological mechanisms of LUTD after SCI for the future development of novel therapies for SCI patients with LUTD.
Application of Lactobacillus reuteri B1/1 (Limosilactobacillus reuteri) Improves Immunological Profile of the Non-Carcinogenic Porcine-Derived Enterocytes

In our previous studies, Lactobacillus reuteri B1/1, which was renamed Limosilactobacillus reuteri (L. reuteri), was able to modulate the production of pro-inflammatory cytokines and other components of the innate immune response in vitro and in vivo. In this study, we evaluated the effect of Lactobacillus reuteri B1/1 in two concentrations (1 × 107 and 1 × 109 CFU) on the metabolic activity, adherence ability and relative gene expression of pro-inflammatory interleukins (IL-1β, IL-6, IL-8, IL-18), lumican and olfactomedin 4 produced by non-carcinogenic porcine-derived enterocytes (CLAB). CLAB cells were cultured in a 12-well cell culture plate at a concentration of 4 × 105 cells/well in DMEM medium in a controlled humidified atmosphere for 48 h. A 1 mL volume of each probiotic bacterial suspension was added to the CLAB cells. Plates were incubated for 2 h and 4 h. Our results revealed that L. reuteri B1/1 was able to adhere to CLAB cells in sufficient numbers in both concentrations. In particular, the concentration of 109 L. reuteri B1/1 allowed to modulate the gene expression of pro-inflammatory cytokines, as well as to increase the metabolic activity of the cells. In addition, administration of L. reuteri B1/1 in both concentrations significantly stimulated gene expression for both proteins in the CLAB cell line after 4 h of incubation.
Adaptive Bayesian Optimization for Fast Exploration Under Safety Constraints

The industrial field faces the problem of process optimization by finding the factors affecting the yield of the process and controlling them appropriately. However, due to limited resources such as time and money, optimization is performed using a low evaluation budget. In addition, for process stability, the lower limit of the yield is set so that the yield must be maintained above this limit during optimization. Bayesian Optimization (BO) can be an effective solution in acquiring optimal samples that satisfy a safety constraint given a low evaluation budget. However, many existing BO algorithms have some limitations such as significant performance degradation due to model misspecification, and high computational load. Thus, we propose a practical safe BO algorithm, A-SafeBO, that effectively reduces performance degradation due to model misspecification using only a limited evaluation budget. Additionally, our algorithm performs computations for a large number of observations and high-dimensional input spaces by using Ensemble Gaussian Processes and Safe Particle Swarm Optimization. Here, we also propose a new acquisition function that leads to a wider exploration even under the constraint of safety. This will help deviate from the local optimum and achieve a better recommendation. Our algorithm empirically guarantees convergence and performance through evaluations on several synthetic benchmarks and a real-world optimization problem.
Numerical Study of Flow and Heat Transfer in Rotating Microchannels

Investigation of fluid flow and heat transfer in rotating microchannels is important for centrifugal microfluidics, which has emerged as an advanced technique in biomedical applications and chemical separations. The centrifugal force and the Coriolis force, arising as a consequence of the microchannel rotation, change the flow pattern significantly from the symmetric profile of a non-rotating channel. A successful design of a centrifugal microfluidic device depends on effectively regulating these forces in rotating microchannels. Although a large number of experimental studies have been performed in order to demonstrate the applications of centrifugal microfluidics in various fields, a systematic study on the effect of rotation, channel aspect ratio, and wall boundary conditions on the fluid flow and heat transfer phenomena in rotating microchannels has not yet been conducted. During the present study, pressure-based finite volume solvers in both staggered and collocated grids were developed to solve steady and unsteady, incompressible Navier-Stokes equations. The serial solver in collocated grid was parallelized using a Message Passing Interface (MPI) library. In order to accelerate the convergence of the collocated finite volume solver, a non-linear multi-grid method was developed. The parallel performances of the single and multi-grid solvers were tested on a twodimensional lid driven cavity flow. High fidelity benchmark solution to a lid driven cavity flow problem in a 1024 × 1024 grid was presented for a range of Reynolds numbers. Parallel multigrid speedup as high as three orders of magnitude was achieved for low Reynolds number flows. In addition, the optimal multigrid efficiency was validated. The fluid flow in a rotating microchannel was modeled as a steady, laminar in-
A conjugate gradient optimization method for electronic structure calculations

In this paper, we propose a conjugate gradient method for electronic structure calculations. Three algorithms are based on different orthogonality strategies. Under some mild conditions, we prove the convergence of our algorithms. In particular, our numerical experiments show that the algorithms perform quite well even without using line search method, when the step size is chosen by our strategy.
Fenceless Collision-Free Avoidance Driven by Visual Computation for an Intelligent Cyber–Physical System Employing Both Single- and Double-S Trajectory

Toward human is always one of the critical missions for any cyber physical system (CPS). Autonomous robots perceive embarrassing behavior when treating humans as conventional obstacles. In the context of flexible manufacturing or intelligent production, smart CPSs have an important role, since they contributes to the achievement of higher productivity and greater efficiency. In this paper, for intelligent human–machine interaction, a novel approach to safety, comfortability, and anti-collision using the four strategies of emergency break (EMB), slow-down break (SLB), slow-down break then emergency break (SLEMB), and emergency break then emergency break (EM2B) based on visual computation is presented. First, a dynamic model of whole CPS consisting of a vehicle’s body and freight was established. To guarantee comfortable motion and social collaboration, an interactive framework that includes human information was integrated in order to adjust the proper actions of the robot. For the actively and highly computational method, fusing data from both sensing modules and digital cameras provides an efficient technique to estimate a human’s pose and launch reasonable behavior for the movement of the robot. Later, for more intelligent and adaptive performance, a switching mechanism considering the human state was introduced. Based on the results of computer-based simulation and experiments, our approach is valuable for socially human-aware navigation in front of humans with respect to actively safe constraints. The contributions of this work are summarized as follows: (i) dynamical analysis, including the smooth profiles, was studied to suppress residual vibration; (ii) vision-based computation of reaching humans due to the socially interactive model was implemented; and (iii) the switching mechanism provides an alternative method for choosing the proper solution.
Vernetzung und Autochthonie nördlicher Arealrandpopulationen der Westlichen Smaragdeidechse (Lacerta bilineata)

To assess the connectivity of the Western Green Lizard along the lower reaches of the Moselle river and to evaluate the origin of populations in Hesse, we used a combination of maternally inherited markers (mtDNA: cytb) and Mendelian markers (microsatellites). Our results demonstrate that the westernmost populations along the Moselle are connected and compose a management unit of high value. In contrast the gene flow towards populations at the estuary is interrupted. Estimated effective population sizes document that these remaining populations are small and highly endangered. The genetic analysis of populations in Hesse suggests that they stem from systematic introductions of L. bilineata from the Kaiserstuhl or the offspring of such introductions. Furthermore, individuals of the Eastern Green Lizard (L. viridis) have been introduced within a L. bilineata population at the Kaiserstuhl without indication of hybridisation. Likewise we found introductions of L. bilineata from Brittany at the Kaiserstuhl. Our results thus emphasise the high relevance of genetic assignments of populations for nature conservation and legislation. Reptiles – Lacertidae – Habitats Directive – Population genetics – Origin – Population management Manuskripteinreichung: 27. 2. 2015, Annahme: 12. 8. 2015 © 2 01 6 W . K oh lh am m er , S tu ttg ar t
Antibacterial Activity Against Multidrug-Resistant Clinical Isolates of Nine Plants from Chencha, Southern Ethiopia

Background The diminishing efficacy of antibiotics currently in use and the emergence of multidrug-resistant bacteria pose a grave threat to public health worldwide. Hence, new classes of antimicrobials are urgently required, and the search is continuing. Methods Nine plants were chosen for the current work, which are collected from the highlands of Chencha, Ethiopia. Plant extracts containing secondary metabolites in various organic solvents were checked for antibacterial activity against type culture bacterial pathogens and MDR clinical isolates. The broth dilution technique was used to evaluate the minimum inhibitory and minimum bactericidal concentrations of highly active plant extracts, and time-kill kinetic and cytotoxic assays were performed using the most active plant extract. Results Two plants (C. asiatica and S. marianum) were highly active against ATCC isolates. The EtOAc extract of C. asiatica produced the highest zone of inhibition ranging between 18.2±0.8–20.7±0.7 and 16.1±0.4–19.2±1.4 mm against Gram-positive and Gram-negative bacteria, respectively. The EtOH extract of S. marianum displayed zones of inhibition in the range of 19.9±1.4–20.5±0.7 mm against the type culture bacteria. The EtOAc extract of C. asiatica effectively curbed the growth of six MDR clinical isolates. The MIC values of C. asiatica against the Gram-negative bacteria tested were 2.5 mg/mL, whereas the corresponding MBC values were 5 mg/mL in each case. The MIC and MBC values were the lowest in the case of Gram-positive bacteria, ie, 0.65 and 1.25 mg/mL, respectively. A time-kill assay showed the inhibition of MRSA at 4 × MIC and 8 × MIC within 2 hours of incubation. The 24 h LD50 values of C. asiatica and S. marianum corresponding to Artemia salina were 3.05 and 2.75 mg/mL, respectively. Conclusion Overall results substantiate the inclusion of C. asiatica and S. marianum as antibacterial agents in traditional medicines.