Miracle-dz/UniFAR-FTUs huggingface dataset:
Time domain analysis of the lightning current distribution at the HV tower with GSM system

GSM base stations are often placed in the poles of power transmission lines. Such base stations are usually powered from the low-voltage network through an isolating transformer to separate the high- and low-voltage networks. The isolating transformer serves to ensure security at other customers' premises especially in case of lightning stroke at the line, which is a frequent cause of flashover of the high-voltage insulators and a subsequent phase to ground fault. To optimize such protection better knowledge of the currents and voltages in the early time of the lightning stroke is required. This paper presents simulation results for the lightning current distribution between the earth wires, grounding systems and power cable network. The analysis is applied to a practical case.
Ground-Based Astronomical Instrumentation Development in the United States: A White Paper on the Challenges Faced by the US Community

This invited white paper, submitted to the National Science Foundation in January of 2020, discusses the current challenges faced by the United States astronomical instrumentation community in the era of extremely large telescopes. Some details may have changed since submission, but the basic tenets are still very much valid. The paper summarizes the technical, funding, and personnel challenges the US community faces, provides an informal census of current instrumentation groups in the US, and compares the state-of-affairs in the US with that of the European community, which builds astronomical instruments from consortia of large hard-money funded instrument centers in a coordinated fashion. With the recent release of the Decadal Survey on Astronomy and Astrophysics 2020 (Astro2020), it is clear that strong community support exists for this next generation of large telescopes in the US. Is the US ready? Is there sufficient talent, facilities, and resources in the community today to meet the challenge of developing the complex suite of instruments envisioned for two US ELTs? These questions are addressed, along with thoughts on how the National Science Foundation can help build a more viable and stable instrumentation program in the US. These thoughts are intended to serve as a starting point for a broader discussion, with the end goal being a plan that puts the US astronomical instrumentation community on solid footing and poised to take on the challenges presented by the ambitious goals we have set in the era of ELTs.
Optimal regularizations for data generation with probabilistic graphical models

Understanding the role of regularization is a central question in statistical inference. Empirically, well-chosen regularization schemes often dramatically improve the quality of the inferred models by avoiding overfitting of the training data. We consider here the particular case of L 2 regularization in the maximum a posteriori (MAP) inference of generative pairwise graphical models. Based on analytical calculations on Gaussian multivariate distributions and numerical experiments on Gaussian and Potts models we study the likelihoods of the training, test, and ‘generated data’ (with the inferred models) sets as functions of the regularization strengths. We show in particular that, at its maximum, the test likelihood and the ‘generated’ likelihood, which quantifies the quality of the generated samples, have remarkably close values. The optimal value for the regularization strength is found to be approximately equal to the inverse sum of the squared couplings incoming on sites on the underlying network of interactions. Our results seem to be robust against changes in the structure of the ground-truth underlying interactions that generated the data, when small fluctuations of the posterior distribution around the MAP estimator are taken into account, and when L 1 regularization is considered (instead of L 2). Connections with empirical works on protein models learned from homologous sequences are discussed.
Exploring fundamental laws of classical mechanics via predicting the orbits of planets based on neural networks

Neural networks have provided powerful approaches to solve various scientific problems. Many of them are even difficult for human experts who are good at accessing the physical laws from experimental data. We investigate whether neural networks can assist us in exploring the fundamental laws of classical mechanics from data of planetary motion. Firstly, we predict the orbits of planets in the geocentric system using the gate recurrent unit, one of the common neural networks. We find that the precision of the prediction is obviously improved when the information of the Sun is included in the training set. This result implies that the Sun is particularly important in the geocentric system without any prior knowledge, which inspires us to gain Copernicus’ heliocentric theory. Secondly, we turn to the heliocentric system and make successfully mutual predictions between the position and velocity of planets. We hold that the successful prediction is due to the existence of enough conserved quantities (such as conservations of mechanical energy and angular momentum) in the system. Our research provides a new way to explore the existence of conserved quantities in mechanics system based on neural networks.
Demonstration of an imaging technique for the measurement of PSF elongation caused by Atmospheric Dispersion

Elongation of the point spread function due to atmospheric dispersion becomes a severe problem for high resolution imaging instruments, if an atmospheric dispersion corrector is not present. In this work we report on a novel technique to measure this elongation, corrected or uncorrected, from imaging data. By employing a simple diffraction mask it is possible to magnify the chromatic elongation caused by the atmosphere and thus make it easier to measure. We discuss the theory and design of such a mask and report on two proof of concept observations using the 40 cm Gratama telescope at the University of Groningen. We evaluate the acquired images using a geometric approach, a forward modelling approach and from a direct measurement of the length of the point spread function. For the first two methods we report measurements consistent with atmospheric dispersion models to within 0.5 arcsec. Direct measurements of the elongation do not prove suitable for the characterisation of atmospheric dispersion. We conclude that the addition of this type of diffraction mask can be valuable for measurements of PSF elongation. This can enable high precision correction of atmospheric dispersion on future instruments.
IRAM 30 m CO-line Observation toward the PeVatron Candidate G106.3+2.7: Direct Interaction between the Shock and the Molecular Cloud Remains Uncertain

The supernova remnant (SNR) G106.3+2.7 was recently found to be one of the few potential Galactic hadronic PeVatrons. Aiming to test the solidity of the SNR’s association with the molecular clouds (MCs) that are thought to be responsible for hadronic interaction, we performed a new CO observation with the IRAM 30 m telescope toward its “belly” region, which is coincident with the centroid of the γ-ray emission. There is a filament structure in the local standard of rest velocity interval −8 to −5 km s−1 that nicely follows the northern radio boundary of the SNR. We have seen asymmetric broad profiles of 12CO lines, with widths of a few km s−1, along the northern boundary and in the “belly” region of G106.3+2.7, but similar 12CO-line profiles are also found outside the SNR boundary. Further, the low 12CO J = 2–1/J = 1–0 line ratios suggest the MCs are cool. Therefore, it is still uncertain whether the MCs are directly disturbed by the SNR shocks, but we do find some clues that the MCs are nearby and thus can still be illuminated by the protons that escaped from the SNR. Notably, we find an expanding molecular structure with a velocity of ∼3.5 km s−1 and a velocity gradient of the MCs across the SNR from ∼−3 to −7 km s−1, which could be explained as the effect of the wind blown by the SNR’s progenitor star.
A hybrid approach for intrusion-detection based on fuzzy GNP and probabilistic classification

An intrusion detection system (IDS) inspects all inbound and outbound network activity and identifies suspicious patterns that may indicate a network or system attack from someone attempting to break into or compromise a system. Intrusion detection systems, which can effectively detect intrusion accesses, have attracted attention. Our work describes a novel fuzzy genetic network programming (GNP) and probabilistic classification for detecting network intrusions.Proposed method can be flexibly applied to both misuse and anomaly detection in network-intrusion-detection problems.Examples and experimental results using intrusion detection datasets DARPA99 from MIT Lincoln Laboratory demonstrate the potential of the approach.
Polymer stretching in laminar and random flows: Entropic characterization

Polymers in nonuniform flows undergo strong deformation, which in the presence of persistent stretching can result in the coil-stretch transition. This phenomenon has been characterized by using the formalism of nonequilibrium statistical mechanics. In particular, the entropy of the polymer extension reaches a maximum at the transition. We extend the entropic characterization of the coil-stretch transition by studying the differential entropy of the polymer fractional extension in a set of laminar and random velocity fields that are benchmarks for the study of polymer stretching in flow. In the case of random velocity fields, a suitable description of the transition is obtained by considering the entropy of the logarithm of the extension instead of the entropy of the extension itself. Entropy emerges as an effective tool for capturing the coil-stretch transition and comparing its features in different flows.
Indexed Minimum Empirical Divergence for Unimodal Bandits

We consider a multi-armed bandit problem specified by a set of one-dimensional family exponential distributions endowed with a unimodal structure. We introduce IMED-UB, a algorithm that optimally exploits the unimodal-structure, by adapting to this setting the Indexed Minimum Empirical Divergence (IMED) algorithm introduced by Honda and Takemura [2015]. Owing to our proof technique, we are able to provide a concise finite-time analysis of IMED-UB algorithm. Numerical experiments show that IMED-UB competes with the state-of-the-art algorithms.
Recent Advances of Nanomaterials in Membranes for Osmotic Energy Harvesting by Pressure Retarded Osmosis

— Energy and water issues are the two main global challenges faced by the human in the past decade. The rapid growths in global energy consumption and greenhouse gas emissions have encouraged the exploration of renewable energy sources as substitute fuels. Osmotic energy (or salinity-gradient energy) is the energy released when water with different salinities is mixed, such as rivers and oceans. By employing a semipermeable membrane to control the mixing process, the osmotic pressure gradient energy can be generated in terms of electrical power via pressure retarded osmosis (PRO) without causing adverse environmental impacts. This work presents a review of the fabrication of thin film nanocomposite (TFN) membranes which are customized to offer high flux in forward osmosis (FO) and high osmotic power in PRO. The hydraulic pressure during PRO processes is less than RO processes so membranes that are used for PRO are less likely to foul. The application of these nanomaterials incorporated with TFN membranes for power generation through PRO is still a new field to be explored. Despite some promising findings obtained from this work, there is always room for improvement.
Vehicle and object models for robust tracking in traffic scenes using laser range images

Detection and modeling of dynamic traffic scenes around a, driving passenger car is the long-term aim of the research project ARGOS at the University of Ulm. Each object close to the own car should be modeled and tracked using a specific individual dynamic model. The object classification is based on the geometric outlines and the dynamic behavior. For any sensor combinations usable to detect the environment, the velocity of the objects can be measured relatively to the movement of own vehicle. To. get the absolute velocity of the objects, the motion of the own vehicle must be measured for which the well know bicycle model is used. This ego-model is fed by sensor signals provided anyway by ABS, ASR or ESP. To eliminate the own motion from the object measurements, several coordinate transformations are required in the different stages of data processing. A proposal is given on how to solve this problem when using a laser range finder as a sensing device. Moreover, a simple object model is introduced for this task in order to save processing power. The algorithms can extended towards a multihypothesis approach which will result a more robust classification and tracking algorithm.
A fast recognition method of warhead target in boost phase using kinematic features

The radar targets number increases from one to more when the ballistic missile is in the process of separating the lower stage rocket or casting covers or other components. It is vital to identify the warhead target quickly among these multiple targets for radar tracking. A fast recognition method of the warhead target is proposed to solve this problem by using kinematic features, utilizing fuzzy comprehensive method and information fusion method. In order to weaken the influence of radar measurement noise, an extended Kalman filter with constant jerk model (CJEKF) is applied to obtain more accurate target’s motion information. The simulation shows the validity of the algorithm and the effects of the radar measurement precision upon the algorithm’s performance.
Influence of nutrient status on the response of the diatom Phaeodactylum tricornutum to oil and dispersant

Phytoplankton play a central role in our ecosystems, they are responsible for nearly 50 percent of the global primary productivity and major drivers of macro-elemental cycles in the ocean. Phytoplankton are constantly subjected to stressors, some natural such as nutrient limitation and some manmade such as oil spills. With increasing oil exploration activities in coastal zones in the Gulf of Mexico and elsewhere, an oil spill during nutrient-limited conditions for phytoplankton growth is highly likely. We performed a multifactorial study exposing the diatom Phaeodactylum tricornutum (UTEX 646) to oil and/or dispersants under nitrogen and silica limitation as well as co-limitation of both nutrients. Our study found that treatments with nitrogen limitation (-N and–N-Si) showed overall lower growth and chlorophyll a, lower photosynthetic antennae size, lower maximum photosynthetic efficiency, lower protein in exopolymeric substance (EPS), but higher connectivity between photosystems compared to non-nitrogen limited treatments (-Si and +N+Si) in almost all the conditions with oil and/or dispersants. However, certain combinations of nutrient limitation and oil and/or dispersant differed from this trend indicating strong interactive effects. When analyzed for significant interactive effects, the–N treatment impact on cellular growth in oil and oil plus dispersant conditions; and oil and oil plus dispersant conditions on cellular growth in–N-Si and–N treatments were found to be significant. Overall, we demonstrate that nitrogen limitation can affect the oil resistant trait of P. tricornutum, and oil with and without dispersants can have interactive effects with nutrient limitation on this diatom.
Efficient Neural Radiance Fields with Learned Depth-Guided Sampling

This paper aims to reduce the rendering time of generalizable radiance ﬁelds. Some recent works equip neural radiance ﬁelds with image encoders and are able to generalize across scenes, which avoids the per-scene optimization. However, their rendering process is generally very slow. A major factor is that they sample lots of points in empty space when inferring radiance ﬁelds. In this paper, we present a hybrid scene representation which combines the best of implicit radiance ﬁelds and explicit depth maps for efﬁcient rendering. Speciﬁcally, we ﬁrst build the cascade cost volume to efﬁciently predict the coarse geometry of the scene. The coarse geometry allows us to sample few points near the scene surface and signiﬁcantly improves the rendering speed. This process is fully differentiable, enabling us to jointly learn the depth prediction and radiance ﬁeld networks from only RGB images. Experiments show that the proposed approach exhibits state-of-the-art performance on the DTU, Real Forward-facing and NeRF Synthetic datasets, while being at least 50 times faster than previous generalizable radiance ﬁeld methods. We also demonstrate the capability of our method to synthesize free-viewpoint videos of dynamic human performers in real-time. The code will be available at https://zju3dv.github. io/enerf/.
Impact of bound states on non-thermal dark matter production

We explore the impact of non-perturbative effects, namely Sommerfeld enhancement and bound state formation, on the cosmological production of non-thermal dark matter. For this purpose, we focus on a class of simplified models with t-channel mediators. These naturally combine the requirements for large corrections in the early Universe, i.e. beyond the Standard Model states with long range interactions, with a sizable new physics production cross section at the LHC. We find that the dark matter yield of the superWIMP mechanism is suppressed considerably due to the non-perturbative effects under consideration in models with color-charged mediators. In models with only electrically charged mediators the impact of non-perturbative effects is less pronounced and gets eclipsed by the impact of a possible Higgs portal interaction. In both cases we find significant shifts in the cosmologically preferred parameter space of non-thermal dark matter in these models. We also revisit the implications of LHC bounds on long-lived particles associated with non-thermal dark matter and find that testing this scenario at the LHC is a bigger challenge than previously anticipated.
A pitot sensor for measuring near-surface turbulence

The authors discuss the design of a pitot-static probe intended to measure near-surface turbulence from a ship while underway at high speed. The probe was affixed to the tip of the starboard sponson of the SWATH ship Frederik G. Creed during the Shoaling Waves Experiment conducted in the late fall of 1999 off Duck NC, USA. The authors present a preliminary analysis of the performance of the sensor based on data collected during that campaign, and argue that the probe is capable of measuring turbulence dissipation rates above roughly 3/spl times/10/sup 18/ W/kg while underway at speeds ranging from 12-16 kts.
Fabrication of Periodic Microstructures on Nickel Template by Multi-Beam Laser Interference

Complex microstructures can be fabricated on nickel template directly by femtosecond laser. But the efficiency is low and much time is inevitable when large scale microstructures are fabricated. The multi-beam interference provides an effective method for fabrication of large scale microstructures. This paper mainly focuses on direct ablation of nickel template by four-beam interference and fabricating periodic microstructures by laser interference lithography. Experimental results show that submicron periodic stripes and column structures can be produced on the nickel template by laser interference, laying the foundation of making nickel molds for microfluidic chips.
Field study of construction effects in jacked and driven steel H-piles

INTRODUCTION The nuisance of noise and vibration caused by percussive piling of displacement piles has limited the use of driven piles in Hong Kong. As an alternative, pile jacking is quiet and free of strong vibration in use. Recently, pile jacking was introduced to the construction industry in Hong Kong (Chan et al., 2002; Li et al., 2003). Li et al. (2003) and Zhang et al. (2006) described termination criteria for jacked pile construction, and Yang et al. (2006) and Zhang et al. (2006) reported behaviour of several jacked piles. Jacked piles were not previously a recognised type of pile foundation (Buildings Department, 2002), local regulations required that piles be installed by jacking to their approximate founding levels and then driven by hammers to confirm that their final sets were similar to those of equivalent driven piles (Chan et al., 2002). In order to satisfy prescribed final set criteria for driven piles, usually derived from Hiley’s formula, a minimum of 7 m of pile section had to be driven after pile jacking in order to achieve the same nominal pile capacity. In other words, in identical soil conditions the length of a jacked pile is smaller than that of a driven pile to satisfy the same capacity requirement. Several questions on the past practice can be asked by engineers. What are the differences between the stress conditions around a jacked pile and a driven pile? What are the differences between the load-carrying behaviour of jacked and driven piles? Why does final driving on a jacked pile cause a considerable change in the pile behaviour? The objective of this note is, through field tests, to study and compare the construction processes, the stress conditions caused by construction, and the load-transfer behaviour of jacked and driven piles.
The complete chloroplast genome sequence of Platanus × hispanica from Sichuan province, China, a medicinal plant and phylogenetic analysis

Abstract Platanus × hispanica is a tree species with high ornamental value, which complete chloroplast(cp) genome was sequenced, assembled and annotated. The chloroplast genome of P. hispanica was 161,717 bp in length, including a large single copy (LSC) region of 92,106, a small single copy (SSC) region of 19,449 bp, and two inverted repeat (IR) regions of 25,081 bp. The GC contents of LSC, SSC, IR, and whole genome are 36.2, 33.0, 43.4, and 38.0%, respectively. There are 131 genes annotated, including 86 protein-coding genes, 37 tRNA genes, and 8 rRNA genes. The phylogenetic analysis revealed that P. hispanica was most related to Platanus occidentalis as a sister group with 100% bootstrap support. The complete chloroplast genome sequences of P. hispanica will provide valuable genomic information to further illuminate phylogenetic classification of Platanus genus.
A posteriori assessment of consumption speed correction for LES with tabulated methods

Large eddy simulation of propane/air jet flame in the wrinkled flamelets regime of the Borghi diagram is used to assess the performance of a recently developed consumption speed correction model in premixed combustion. The combustion is modelled using flamelet tabulation with a presumed probability density function. The investigated flame does not lie in the shear layer and is subjected to self-driven oscillations, which is ideal to test the model performance. The flame behaviour is first discussed using an accurate simulation performed on a refined mesh requiring no correction. The same modelling framework used on a coarser mesh is observed to overestimate the consumption speed, leading to a shorter flame. The application of the consumption speed correction leads to the recovery of the flame length and width observed for the refined mesh, demonstrating its effectiveness. An extended model for partially-premixed combustion is also proposed and preliminarily tested on a high-pressure combustor.