Miracle-dz/UniFAR-FTUs huggingface dataset:
Geographically convolutional neural network weighted regression: a method for modeling spatially non-stationary relationships based on a global spatial proximity grid

Abstract Geographically weighted regression (GWR) is a classical method of modeling spatially non-stationary relationships. The geographically neural network weighted regression (GNNWR) model solves the problem of the inaccurate construction of spatial weight kernels using a spatially weighted neural network. However, when the spatial distribution of observations is uneven, the spatial proximity expression in the input of GWR and GNNWR models does not fully represent the impact of the whole research space on the estimating point. Therefore, we established a global spatial proximity grid (GSPG) to express the spatial proximity of each estimating point and proposed a spatially weighted convolutional neural network (SWCNN) to extract the relationship between the GSPG and spatial weights. Finally, we proposed a geographically convolutional neural network weighted regression (GCNNWR) model combining SWCNN and ordinary linear regression (OLR) model to estimate spatial non-stationarity. We used two case studies of simulated data and real environment data to demonstrate the advancements of the GCNNWR model. The GCNNWR model achieved higher estimation accuracy and greater predictive power than the OLR, GWR, multi-scale GWR (MGWR), and GNNWR models. Moreover, the GCNNWR model maintained its better stability and accuracy in estimating spatially non-stationary relationships when the distribution of observations was uneven.
A Mixed-Integer Solution for TDOA Based Direct Positioning of Digital Modulation Signal

This paper proposes a direct position determination (DPD) method for a digital modulation signal based on time difference of arrival (TDOA) measurements. Unlike the two-step positioning process, the measurements are used to directly estimate the source position. Fully utilizing information in a transmitted waveform can improve the accuracy of source localization in a single-step method. Based on maximum likelihood (ML) estimates, when the digital modulation scheme is known to the location system, an alternating iterative DPD method is developed to locate the emitter. The objective function of the proposed algorithm takes into account the source position and transmitted symbol sequence, which makes it a mixed-integer optimization problem. In particular, ML sequence estimation is adopted and the complex envelope is restored using a genetic algorithm. Then, based on Newton’s method, an alternating iterative algorithm is proposed to update the position and symbol sequence results. Compared with the existing DPD method, the proposed algorithm gives more accurate location results for unknown waveforms. In addition, the proposed algorithm can reach the Cramér-Rao bound (CRB) for known signal waveforms, as verified using comprehensive simulations.
HIGH-n HYDROGEN RECOMBINATION LINES FROM THE FIRST GALAXIES

We investigate the prospects of blind and targeted searches in the radio domain (10 MHz to 1 THz) for high-n hydrogen recombination lines from the first generation of galaxies, at z ≲ 10. The expected optically thin spontaneous α-line luminosities are calculated as a function of the absolute AB magnitude of a galaxy at 1500 Å. For a blind search, semi-empirical luminosity functions are used to calculate the number of galaxies whose expected flux densities exceed an assumed detectability threshold. Plots of the minimum sky area, within which at least one detectable galaxy is expected at a given observing frequency, in the fiducial instantaneous passband of 104 km s−1, allow us to assess the blind search time necessary for detection by a given facility. We show that the chances for detection are the highest in the millimeter and submillimeter domains, but finding spontaneous emission in a blind search, especially from redshifts z ≫ 1, is a challenge even with powerful facilities, such as the Actama Large Millimeter/Submillimeter Array and Square Kilometre Array. The probability of success is higher for a targeted search of lines with principal quantum number n ∼ 10 in Lyman-break galaxies amplified by gravitational lensing. Detection of more than one hydrogen line in such a galaxy will allow for line identification and a precise determination of the galaxy's redshift.
Assessing the Impact of Movie Plot Summaries on Box Office Sales

In this paper, we evaluate the impact of movie summaries on box office sales. These summaries are provided by studios as one of the many artifacts used to market a movie to the public. We acquired a set of nearly 74 thousand summaries from English-language films released between 1960 and 2019. We analyzed summary sentiment, length, and vocabulary and compared these metrics to box office sales, studying trends across genres. We observed that movies with negative or neutral summaries achieved greater box office sales than those with positive summaries. While initially surprising, these results correlate to endorphin production caused by negative or traumatic experiences. We also noted that summaries with an average length of 30 words performed better than those with fewer or more words. Finally, we noted that movies with summaries that have a vocabulary level of a college graduate performed better than others.
Evaluation of pedodiversity and land use diversity in terms of the Shannon Entropy

Recently, the Shannon entropy, which was introduced originally as a measure of information amount, has been widely used as a useful index of various diversities such as biodiversity and geodiversity. In this work we have evaluated the diversity of soil and land use, in both composition distributions and spatial distributions, in terms of the Shanonn entropy. Moreover we have also proposed how to estimate the connection between the diversity of soil and land use in the spatial distribution using mutual entropy, and carried out the estimation of its connection.
A TALE OF TWO ANOMALIES: DEPLETION, DISPERSION, AND THE CONNECTION BETWEEN THE STELLAR LITHIUM SPREAD AND INFLATED RADII ON THE PRE-MAIN SEQUENCE

We investigate lithium depletion in standard stellar models (SSMs) and main sequence (MS) open clusters, and explore the origin of the Li dispersion in young, cool stars of equal mass, age, and composition. We first demonstrate that SSMs accurately predict the Li abundances of solar analogs at the zero-age main sequence (ZAMS) within theoretical uncertainties. We then measure the rate of MS Li depletion by removing the [Fe/H]-dependent ZAMS Li pattern from three well-studied clusters, and comparing the detrended data. MS depletion is found to be mass-dependent, in the sense of more depletion at low mass. A dispersion in Li abundance at fixed Teff is nearly universal, and sets in by ∼200 Myr. We discuss mass and age dispersion trends, and the pattern is mixed. We argue that metallicity impacts the ZAMS Li pattern, in agreement with theoretical expectations but contrary to the findings of some previous studies, and suggest Li as a test of cluster metallicity. Finally, we argue that a radius dispersion in stars of fixed mass and age, during the epoch of pre-MS Li destruction, is responsible for the spread in Li abundances and the correlation between rotation and Li in young cool stars, most well known in the Pleiades. We calculate stellar models, inflated to match observed radius anomalies in magnetically active systems, and the resulting range of Li abundances reproduces the observed patterns of young clusters. We discuss ramifications for pre-MS evolutionary tracks and age measurements of young clusters, and suggest an observational test.
Catalytic mechanism and activity of N2 reduction on boron-decorated crystalline carbon nitride

The development of efficient, low-cost, and eco-friendly catalysts for nitrogen fixation is essential and provides an alternative method to the traditional Haber–Bosch process. However, studies on thermal catalyst of nitrogen fixation mainly focus on metal-containing, and the microscopic mechanism of thermal reduction process is still limited. Herein, we explored an economic metal-free boron atom decorated poly(triazine imide) (B/PTI), a crystalline carbon nitride, as an excellent thermal catalyst of nitrogen fixation and proposed a substrate-hydrogen mechanism for the N2 thermal reduction reaction (NTRR). Our results reveal that the substrate hydrogen as the hydrogen source can promote the hydrogenation process with activation barrier of 0.56 eV, significantly lower than that of reported NTRR catalysts. Importantly, the B/PTI exhibits high turnover frequency, which is comparable to Fe, Ru, and Ti catalysts. Our work offers new insights into NTRR mechanism and provides an alternative solution for the sustainable ammonia synthesis.
Quantum-limited metrology with product states

We study the performance of initial product states of n-body systems in generalized quantum metrology protocols that involve estimating an unknown coupling constant in a nonlinear k-body (kn) Hamiltonian. We obtain the theoretical lower bound on the uncertainty in the estimate of the parameter. For arbitrary initial states, the lower bound scales as 1/nk, and for initial product states, it scales as 1/nk−1/2. We show that the latter scaling can be achieved using simple, separable measurements. We analyze in detail the case of a quadratic Hamiltonian (k=2), implementable with Bose-Einstein condensates. We formulate a simple model, based on the evolution of angular-momentum coherent states, which explains the O(n−3/2) scaling for k=2; the model shows that the entanglement generated by the quadratic Hamiltonian does not play a role in the enhanced sensitivity scaling. We show that phase decoherence does not affect the O(n−3/2) sensitivity scaling for initial product states.
A fast non-LTE code for expanding atmospheres: a test of the validity of the Sobolev approximation

We present a new non-LTE atmosphere code to calculate the continuum energy distribution and line profiles from stellar atmospheres with extended outflowing envelopes. The code is fast, which makes it suited for empirical modelling. The statistical equilibrium equations and the radiative transfer in the continuum are solved with an efficient approximate lambda iteration method. The line transfer is treated using the Sobolev approximation, including the effects of the diffuse radiation field, and the continuous opacity inside the line resonance zone. We investigate the validity of the Sobolev approximation by comparing our code with one that solves the line transfer using the co-moving frame method
Improved model for the thermal conductivity of binary metallic systems

We extended and corrected Mott's two-band model for the composition-dependence of thermal and electrical conductivity in binary metal alloys based on high-throughput time-domain thermoreflectance (TDTR) measurements on diffusion multiples and scatterer-density calculations from first principles. Examining PdAg, PtRh, AuAg, AuCu, PdCu, PdPt, and NiRh binary alloys, we found that the nature of the two dominant scatterer-bands considered in the Mott model changes with the alloys, and should be interpreted as a combination of the dominant element-specific s- and/or d-orbitals. Using calculated orbital and element-resolved density-of-states values calculated with density functional theory as input, we determined the correct orbital mix that dominates electron scattering for all examined alloys and find excellent agreement between fitted models and experiments. The proposed description of the composition dependence of the resistivity can be readily implemented into the CALPHAD framework.
Soil Moisture Monitoring Through UAS-Assisted Internet of Things LoRaWAN Wireless Underground Sensors

With growing usage and demand for the global freshwater supply, there is an increasing need for technologies that facilitate water conservation and environmental stewardship in irrigated agriculture. Toward this end, recent demonstrations of Internet of Things (IoT) sensors have revealed the value of wireless soil moisture content sensors. However, existing wireless solutions often employ above-ground wireless communication modules that physically interfere with routine farming operations. Underground wireless network solutions are severely challenged by the large radio-frequency (RF) propagation loss through soil. This paper presents a method that overcomes both problems by employing completely buried underground IoT sensors and communication modules with UAS (uncrewed aircraft system) mounted LoRaWAN gateways. The UAS mounted LoRaWAN gateway eliminates the need for any in-field base stations and also allows the LoRa enabled sensors to transmit data over short distances with very low energy. Field tests were carried out using this approach to serve as a proof of concept. The RSSI (received signal strength indicator) demonstrates that the proposed solution has good communication link margin and a significantly larger communication range than is necessary for reliable operation. Moreover, this solution is easy to build, scalable, cost-effective, and can be implemented in a highly power efficient fashion.
Quantum Circuit for Calculating Symmetrized Functions Via Grover-like Algorithm

In this paper, we give a quantum circuit that calculates symmetrized functions. Our algorithm applies the original Grover's algorithm or a variant thereof such as AFGA (adaptive fixed point Grover's algorithm). Our algorithm uses AFGA in conjunction with two new techniques we call "targeting two hypotheses" and "blind targeting". Suppose AFGA drives the starting state $|s\rangle$ to the target state $|t\rangle$. When targeting two hypotheses, $|t\rangle$ is a superposition $a_0|0\rangle + a_1|1\rangle$ of two orthonormal states or hypotheses $|0\rangle$ and $|1\rangle$. When targeting blindly, the value of $\langle t| s\rangle$ is not known a priori.
A quantum measure of the multiverse

It has been recently suggested that probabilities of different events in the multiverse are given by the frequencies at which these events are encountered along the worldline of a geodesic observer (the ``watcher''). Here I discuss an extension of this probability measure to quantum theory. The proposed extension is gauge-invariant, as is the classical version of this measure. Observations of the watcher are described by a reduced density matrix, and the frequencies of events can be found using the decoherent histories formalism of Quantum Mechanics (adapted to open systems). The quantum watcher measure makes predictions in agreement with the standard Born rule of QM.
Considering musicians’ health and wellness literature through the lens of the Behaviour Change Wheel

Performing Arts Medicine (PAM) specialists have identified a variety of health conditions that interfere with musicians’ careers and leisure activities. To date, health promotion initiatives have emphasised education and training to try and help musicians understand their bodies and persuade them to engage in health-promoting behaviours: such initiatives often focus on isolated bodily systems (e.g. musculoskeletal, vocal or hearing health, or psychological wellness). Outcomes of interventions have been mixed and the prevalence of performance-related conditions remains persistently high. PAM specialists have started to recognise that effective health promotion requires a sound theoretical framework that accounts for the interplay between myriad factors that influence musicians’ lives. Behaviour change specialists have made significant advances in establishing frameworks synthesising influences on behaviour and what can be done to change behaviour. The Behaviour Change Wheel (BCW) revolves around the idea that an individual’s behaviour is influenced by their physical and psychological capabilities , physical and social opportunities , and motivation (the ‘COM-B’ model). This framework places individual factors into a societal context and fosters consideration of the body as an integrated system. The current review focuses on considering PAM literature through the lens of the COM-B model to determine what has been achieved, identify research gaps, and provide information to support the behavioural diagnosis phase of new interventions. Readers will also be introduced to subsequent phases of the BCW including nine strategies (‘intervention functions’) for changing behaviour known as (‘Education’, ‘Training’, restructuring’, ‘Modelling’, ‘Enablement’, ‘Restriction’, ‘Coercion’, and ‘Incentivisation’) and criteria for selection of the smallest building blocks that combine to form BCW interventions (‘behaviour change techniques’). This review will be of interest to performers,
Influencers Detection Algorithm to Combat Rumors in Social Networks

Although online social networks can provide a potential opportunity for interchanging information among individuals, rumor is still a big challenge. It is a harmful social phenomenon that needs to be paid attention to. Therefore, several researchers have focused on this research direction. This paper is going to combat negative rumors on online social networks by involving trusted influencers. They are members of online social networks (OSNs) who have a high degree of influence than the others. They can play an important role to minimize the effect of rumors. The process of detecting influencers is the first step in this paper. The proposed model uses some criteria to achieve this task. The next step after the detection process is to employ those influencers to combat rumors. To evaluate the proposed model, we used a tweet dataset; this demonstrates that the model can identify influencers with a high influence score who disseminate anti-rumor in social networks. The results emphasize that the model has a good performance in discovering influencers as well as spreading anti-rumor compared with others.
Inflation and alternatives with blue tensor spectra

We study the tilt of the primordial gravitational waves spectrum. A hint of blue tilt is shown from analyzing the BICEP2 and POLARBEAR data. Motivated by this, we explore the possibilities of blue tensor spectra from the very early universe cosmology models, including null energy condition violating inflation, inflation with general initial conditions, and string gas cosmology, etc. For the simplest G-inflation, blue tensor spectrum also implies blue scalar spectrum. In general, the inflation models with blue tensor spectra indicate large non-Gaussianities. On the other hand, string gas cosmology predicts blue tensor spectrum with highly Gaussian fluctuations. If further experiments do confirm the blue tensor spectrum, non-Gaussianity becomes a distinguishing test between inflation and alternatives.
Dynamical formation of detached trans-Neptunian objects close to the 2:5 and 1:3 mean motion resonances with Neptune

Aims. It is widely accepted that the past dynamical history of the solar system included a scattering of planetesimals from a primordial disk by the major planets. The primordial scattered population is likely the origin of the current scaterring disk and possibly the detached objects. In particular, an important argument has been presented for the case of 2004XR190 as having an origin in the primordial scattered disk through a mechanism including the 3:8 mean motion resonance (MMR) with Neptune. Here we aim at developing a similar study for the cases of the 1:3 and 2:5 resonances that are stronger than the 3:8 resonance. Methods. Through a semi-analytic approach of the Kozai resonance inside an MMR, we show phase diagrams (e ,ω ) that suggest the possibility of a scattered particle, after being captured in an MMR with Neptune, to become a detached object. We ran several numerical integrations with thousands of particles perturbed by the four major planets, and there are cases with and without Neptune’s residual migration. These were developed to check the semi-analytic approach and to better understand the dynamical mechanisms that produce the detached objects close to an MMR. Results. The numerical simulations with and without a residual migration for Neptune stress the importance of a particular resonance mode, which we name the hibernating mode, on the formation of fossilized detached objects close to MMRs. When considering Neptune’s residual migration we are able to show the formation of detached orbits. These objects are fossilized and cannot be trapped in the MMRs again. We find a ratio of the number of fossilized objects with moderate perihelion distance (35 40 au) as 3.0/1 for objects close to the 2:5, and 1.7/1 for objects close to the 1:3 resonance. We estimate that the two fossilized population have a total mass between 0. 1a nd 0.3 Pluto’s mass.
“LEADING BLOB” MODEL IN A STOCHASTIC ACCELERATION SCENARIO: THE CASE OF THE 2009 FLARE OF Mkn 501

Evidence for very hard, intrinsic γ-ray source spectra, as inferred after correction for absorption in the extragalactic background light (EBL), has interesting implications for the acceleration and radiation mechanisms acting in blazars. A key issue so far has been the dependence of the hardness of the γ-ray spectrum on different existing EBL models. The recent Fermi observations of Mkn 501 now provide additional evidence for the presence of hard intrinsic γ-ray spectra independent of EBL uncertainties. Relativistic Maxwellian-type electron energy distributions that are formed in stochastic acceleration scenarios offer a plausible interpretation for such hard source spectra. Here, we show that the combined emission from different components with Maxwellian-type distributions could in principle also account for much softer and broader power-law-like emission spectra. We introduce a “leading blob” scenario, applicable to active flaring episodes, when one (or a few) of these components become distinct over the “background” emission, producing hard spectral features and/or hardening of the observed spectra. We show that this model can explain the peculiar high-energy characteristics of Mkn 501 in 2009, with evidence for flaring activity and strong spectral hardening at the highest γ-ray energies.
Sperm length variation is linked to sexual ornamentation in male paper wasps

Diversification of sperm design is a common feature in animals. Considerable intra-individual variation has been detected even in species whose males produce a monomorphic sperm. The evolutionary forces that shape the variation in the gross morphology of these gametic cells are still not completely understood. Previous studies suggest that the intra-individual variation in sperm size reduces as a result of post-copulatory sexual selection. To our knowledge, for the first time, we provide evidence here that pre-copulatory sexual selection can also play a role. By studying the Neotropical paper wasp, Polistes simillimus, a monandrous species, we found reduced variation in sperm length in males bearing sexual ornamentation preferred by females. Besides, the female spermatheca contains a less variable sperm compared to that in the male seminal vesicles. Thus, the scope of selection, acting on this sperm trait, seems broader than previously acknowledged.
Tool Path Planning Method for Industrial Manipulators Based on 3D-Model Obtained From Computer Vision Systems

The paper proposes the method for tool path planning based on the use of a workpiece 3D-model obtained from a computer vision system. The main feature of the proposed method is the automatic separation of elementary paths described by lines or arcs of circles from the initial trajectory passed along the 3D-model surface. This separation is implemented by means of the RANSAC algorithm. The proposed method allows to reduce the number of commands in the generated motion program of the industrial manipulator and increase operations performance since the generated paths will not contain noise from the computer vision system. Preliminary studies performed have shown the efficiency and workability of the proposed method.