Miracle-dz/UniFAR-FTUs huggingface dataset:
Geochemistry and paleoenvironment of the phosphorites from the Ameki Formation, Niger delta, Nigeria

The phosphorites of the Ameki Formation occur as nodules, pellets as well as primary phosphatic shales and siltstones. Geochemical analysis of the phosphate samples was carried out to determine its chemical composition as well as its depositional environment. The methodology applied include XRF, INAA, XRD and thin section petrography using Polarizing Microscope. The XRF result identified CaO- P2O5- F as the major mineral group, SiO2, Al2O3, Fe2O3, MgO and TiO2, which show minor occurrences and Cr, U, Pb, V, Cu, Zn, Se and Cd that occur in trace amounts. The nodules and pellets are of medium to high grade (25- 34wt% P2O5) whereas the primary phosphatic shales and siltstones are of low to medium grade (4.5– 22wt% P2O5). The phosphorites comprise mostly of francolites. The mean index of refraction estimated by Becke-line method using Standard Polarizing Microscope gave 1.634 and1.636. XRD analysis yielded an average values of 9.243 (± 0.002) A° and 6.715 (± 0.002) A° for a and c crystallographic axes respectively with an axial ratio (c/a) of 0.726for unit cell parameter, suggestive of low degree of carbonate substitution. An increase in P2O5 content is found to be accompanied by increase in CaO, CO2 and F contents, but by a decrease in H2O, organic carbon, SiO2 and Fe contents indicative of amorphous solid phase of calcium phosphate. The phosphorite is interpreted to form under high biologic productive, shelf setting. High nutrient availability in the ancient sea is linked to upwelling along the West African Coastline during the Eocene. Keywords: Phosphorites; Geochemistry; Paleoenvironment; Ameki; Francolites; Nodules
Signing Information in the Quantum Era

Signatures are primarily used as a mark of authenticity, to demonstrate that the sender of a message is who they claim to be. In the current digital age, signatures underpin trust in the vast majority of information that we exchange, particularly on public networks such as the internet. However, schemes for signing digital information which are based on assumptions of computational complexity are facing challenges from advances in mathematics, the capability of computers, and the advent of the quantum era. Here we present a review of digital signature schemes, looking at their origins and where they are under threat. Next, we introduce post-quantum digital schemes, which are being developed with the specific intent of mitigating against threats from quantum algorithms whilst still relying on digital processes and infrastructure. Finally, we review schemes for signing information carried on quantum channels, which promise provable security metrics. Signatures were invented as a practical means of authenticating communications and it is important that the practicality of novel signature schemes is considered carefully, which is kept as a common theme of interest throughout this review.
Survey of ortho-H2D+ in high-mass star-forming regions

Context. Deuteration has been suggested to be a reliable chemical clock of star-forming regions due to its strong dependence on density and temperature changes during cloud contraction. In particular, the H3+ isotopologues (e.g. ortho-H2D+) seem to act as good proxies of the evolutionary stages of the star formation process. While this has been widely explored in low-mass star-forming regions, in the high-mass counterparts only a few studies have been pursued, and the reliability of deuteration as a chemical clock remains inconclusive. Aims. We present a large sample of o-H2D+ observations in high-mass star-forming regions and discuss possible empirical correlations with relevant physical quantities to assess its role as a chronometer of star-forming regions through different evolutionary stages. Methods. APEX observations of the ground-state transition of o-H2D+ were analysed in a large sample of high-mass clumps selected from the ATLASGAL survey at different evolutionary stages. Column densities and beam-averaged abundances of o-H2D+ with respect to H2, X(o-H2D+), were obtained by modelling the spectra under the assumption of local thermodynamic equilibrium. Results. We detect 16 sources in o-H2D+ and find clear correlations between X(o-H2D+) and the clump bolometric luminosity and the dust temperature, while only a mild correlation is found with the CO-depletion factor. In addition, we see a clear correlation with the luminosity-to-mass ratio, which is known to trace the evolution of the star formation process. This would indicate that the deuterated forms of H3+ are more abundant in the very early stages of the star formation process and that deuteration is influenced by the time evolution of the clumps. In this respect, our findings would suggest that the X(o-H2D+) abundance is mainly affected by the thermal changes rather than density changes in the gas. We have employed these findings together with observations of H13CO+, DCO+, and C17O to provide an estimate of the cosmic-ray ionisation rate in a sub-sample of eight clumps based on recent analytical work. Conclusions. Our study presents the largest sample of o-H2D+ in star-forming regions to date. The results confirm that the deuteration process is strongly affected by temperature and suggests that o-H2D+ can be considered a reliable chemical clock during the star formation processes, as proved by its strong temporal dependence.
Observer-Based Event-Triggered Boundary Control of a Class of Reaction–Diffusion PDEs

This article presents an observer-based event-triggered boundary control strategy for a class of reaction–diffusion partial differential equations with Robin actuation. The observer only requires boundary measurements. The control approach consists of a backstepping output feedback boundary controller, derived using estimated states, and a dynamic triggering condition, which determines the time instants at which the control input needs to be updated. It is shown that under the proposed observer-based event-triggered boundary control approach, there is a minimal dwell time between two triggering instants independent of initial conditions. Furthermore, the well-posedness and the global exponential convergence of the closed-loop system to the equilibrium point are established. A simulation example is provided to validate the theoretical developments.
Broadband Frequency and Spatial On-Demand Tailoring of Topological Wave Propagation Harnessing Piezoelectric Metamaterials

Many engineering applications leverage metamaterials to achieve elastic wave control. To enhance the performance and expand the functionalities of elastic waveguides, the concepts of electronic transport in topological insulators have been applied to elastic metamaterials. Initial studies showed that topologically protected elastic wave transmission in mechanical metamaterials could be realized that is immune to backscattering and undesired localization in the presence of defects or disorder. Recent studies have developed tunable topological elastic metamaterials to maximize performance in the presence of varying external conditions, adapt to changing operating requirements, and enable new functionalities such as a programmable wave path. However, a challenge remains to achieve a tunable topological metamaterial that is comprehensively adaptable in both the frequency and spatial domains and is effective over a broad frequency bandwidth that includes a subwavelength regime. To advance the state of the art, this research presents a piezoelectric metamaterial with the capability to concurrently tailor the frequency, path, and mode shape of topological waves using resonant circuitry. In the research presented in this manuscript, the plane wave expansion method is used to detect a frequency tunable subwavelength Dirac point in the band structure of the periodic unit cell and discover an operating region over which topological wave propagation can exist. Dispersion analyses for a finite strip illuminate how circuit parameters can be utilized to adjust mode shapes corresponding to topological edge states. A further evaluation provides insight into how increased electromechanical coupling and lattice reconfiguration can be exploited to enhance the frequency range for topological wave propagation, increase achievable mode localization, and attain additional edge states. Topological guided wave propagation that is subwavelength in nature and adaptive in path, localization, and frequency is illustrated in numerical simulations of thin plate structures. Outcomes from the presented work indicate that the easily integrable and comprehensively tunable proposed metamaterial could be employed in applications requiring a multitude of functions over a broad frequency bandwidth.
Type B Reflexivization as an Unambiguous Testbed for Multilingual Multi-Task Gender Bias

The one-sided focus on English in previous studies of gender bias in NLP misses out on opportunities in other languages: English challenge datasets such as GAP and WinoGender highlight model preferences that are "hallucinatory", e.g., disambiguating gender-ambiguous occurrences of 'doctor' as male doctors. We show that for languages with type B reflexivization, e.g., Swedish and Russian, we can construct multi-task challenge datasets for detecting gender bias that lead to unambiguously wrong model predictions: In these languages, the direct translation of 'the doctor removed his mask' is not ambiguous between a coreferential reading and a disjoint reading. Instead, the coreferential reading requires a non-gendered pronoun, and the gendered, possessive pronouns are anti-reflexive. We present a multilingual, multi-task challenge dataset, which spans four languages and four NLP tasks and focuses only on this phenomenon. We find evidence for gender bias across all task-language combinations and correlate model bias with national labor market statistics.
A Computer Vision Approach to Combat Lyme Disease

Lyme disease is an infectious disease transmitted to humans by a bite from an infected Ixodes species (blacklegged ticks). It is one of the fastest growing vector-borne illness in North America and is expanding its geographic footprint. Lyme disease treatment is time-sensitive, and can be cured by administering an antibiotic (prophylaxis) to the patient within 72 hours after a tick bite by the Ixodes species. However, the laboratory-based identification of each tick that might carry the bacteria is time-consuming and labour intensive and cannot meet the maximum turn-around-time of 72 hours for an effective treatment. Early identification of blacklegged ticks using computer vision technologies is a potential solution in promptly identifying a tick and administering prophylaxis within a crucial window period. In this work, we build an automated detection tool that can differentiate blacklegged ticks from other ticks species using advanced deep learning and computer vision approaches. We demonstrate the classification of tick species using Convolution Neural Network (CNN) models, trained end-to-end from tick images directly. Advanced knowledge transfer techniques within teacher-student learning frameworks are adopted to improve the performance of classification of tick species. Our best CNN model achieves 92% accuracy on test set. The tool can be integrated with the geography of exposure to determine the risk of Lyme disease infection and need for prophylaxis treatment.
A New Approach for Tactical Decision Making in Lane Changing: Sample Efficient Deep Q Learning with a Safety Feedback Reward

Automated lane change is one of the most challenging task to be solved of highly automated vehicles due to its safety-critical, uncertain and multi-agent nature. This paper presents the novel deployment of the state of art $\mathbf{Q}$ learning method, namely Rainbow DQN, that uses a new safety driven rewarding scheme to tackle the issues in an dynamic and uncertain simulation environment. We present various comparative results to show that our novel approach of having reward feedback from the safety layer dramatically increases both the agent's performance and sample efficiency. Furthermore, through the novel deployment of Rainbow DQN, it is shown that more intuition about the agent's actions is extracted by examining the distributions of generated $\mathbf{Q}$ values of the agents. The proposed algorithm shows superior performance to the baseline algorithm in the challenging scenarios with only 200000 training steps (i.e. equivalent to 55 hours driving).
Multitracer Cosmological Line Intensity Mapping Mock Light-cone Simulation

Submillimeter emission lines are important tracers of the cold gas and ionized environments of galaxies and the targets for future line intensity mapping surveys. Physics-based simulations that predict multiple emission lines arising from different phases of the interstellar medium are crucial for constraining the global physical conditions of galaxies with upcoming line intensity mapping observations. In this work, we present a general framework for creating multitracer mock submillimeter line intensity maps based on physically grounded galaxy formation and submillimeter line emission models. We simulate a mock light cone of 2 deg2 over a redshift range 0≤z≤10 comprising discrete galaxies and galaxy [C ii], CO, and [C i] emission. We present simulated line intensity maps for two fiducial surveys with resolution and observational frequency windows representative of COMAP and EXCLAIM. We show that the star formation rate and line emission scaling relations predicted by our simulation significantly differ at low halo masses from widely used empirical relations, which are often calibrated to observations of luminous galaxies at lower redshifts. We show that these differences lead to significant changes in key summary statistics used in intensity mapping, such as the one-point intensity probability density function and the power spectrum. It will be critical to use more realistic and complex models to forecast the ability of future line intensity mapping surveys to measure observables such as the cosmic star formation rate density.
A review of metadata fields associated with podcast RSS feeds

Podcasts are traditionally shared through RSS feeds. As well as pointing to the audio files, RSS gives a creator a way of providing metadata about the podcast shows and episodes. We investigate how certain metadata fields associated with podcasts are currently being used and comment on their applicability to recommendations. Specifically, we find that many creators are not using the itunes:type field in the expected fashion, and that using this field for recommendations might not lead to an optimal user experience. We perform similar explorations for the season number and the category associated with a podcast, and also find that the fields aren't being used in the expected fashion. Finally, we examine the notion that a single podcast show is the same as a single RSS feed. This also turns out to not be strictly true in all cases. In short, the metadata associated with many podcasts isn't always reflective of the show and should be used with caution.
CARF Working Paper

This paper examines an impact of Bank of Japan (BOJ)’s outright purchase on the JGB (Japanese government bond) yield curve. Particularly, we develop a simple state space model, which incorporates new factors regarding the BOJ’s announcement for its outright purchase and the current market outstanding with standard level and spread factors. Based on the model with a filtering method, we also implement an empirical analysis with time series of the BOJ’s announcement records during 2014/10/22-2017/8/3 in the quantitative-qualitative easing(QQE) period to estimate the sensitivities of interest rates against the changes in the market expectation for the net supply with each sector of JGB. We expect the current work provides a basis for considering quantitative effects on the term structure by BOJ’s policy changes such as termination or significant reduction of the BOJ’s outright purchase. For instance, our scenario analysis shows substantial increase in the 30 year yield with widening of 20-30 year spread.
Are Scene Graphs Good Enough to Improve Image Captioning?

Many top-performing image captioning models rely solely on object features computed with an object detection model to generate image descriptions. However, recent studies propose to directly use scene graphs to introduce information about object relations into captioning, hoping to better describe interactions between objects. In this work, we thoroughly investigate the use of scene graphs in image captioning. We empirically study whether using additional scene graph encoders can lead to better image descriptions and propose a conditional graph attention network (C-GAT), where the image captioning decoder state is used to condition the graph updates. Finally, we determine to what extent noise in the predicted scene graphs influence caption quality. Overall, we find no significant difference between models that use scene graph features and models that only use object detection features across different captioning metrics, which suggests that existing scene graph generation models are still too noisy to be useful in image captioning. Moreover, although the quality of predicted scene graphs is very low in general, when using high quality scene graphs we obtain gains of up to 3.3 CIDEr compared to a strong Bottom-Up Top-Down baseline.
The First Extensive Spectroscopic Study of Young Stars in the North America and Pelican Nebulae

We present a spectroscopic survey of over 3400 potential members in the North America and Pelican Nebulae (NAP) using several low-resolution (R ≈ 1300–2000) spectrographs: Palomar/Norris, WIYN/Hydra, Keck/DEep Imaging Multi-Object Spectrograph (DEIMOS), and the Multiple Mirror Telescope (MMT)/Hectospec. We identify 580 young stars as likely members of the NAP region based on criteria involving infrared excess, Li I 6708 Å absorption, X-ray emission, parallax, and proper motions. The spectral types of individual spectra are derived by fitting them with templates that are either empirical spectra of pre-main-sequence stars or model atmospheres. The templates are artificially veiled, and a best-fit combination of spectral type and veiling parameter is derived for each star. We use the spectral types with archival photometry to derive V-band extinction and stellar luminosity. From the Hertzsprung–Russell diagram, the median age of the young stars is about 1 Myr, with a luminosity dispersion of ∼0.3–0.4 dex. We investigate the photometric variability of the spectroscopic member sample using Zwicky Transient Facility data and conclude that photometric variability, while present, does not significantly contribute to the luminosity dispersion. While larger than the formal errors, the luminosity dispersion is smaller than if veiling were not taken into account in our spectral typing process. The measured ages of the stellar kinematic groups, combined with the inferred ages for embedded stellar populations revealed by Spitzer, suggest a sequential history of star formation in the NAP region.
Frequency fluctuations in nanomechanical silicon nitride string resonators

High quality factor ($Q$) nanomechanical resonators have received a lot of attention for sensor applications with unprecedented sensitivity. Despite the large interest, few investigations into the frequency stability of high-$Q$ resonators have been reported. Such resonators are characterized by a linewidth significantly smaller than typically employed measurement bandwidths, which is the opposite regime to what is normally considered for sensors. Here, the frequency stability of high-$Q$ silicon nitride string resonators is investigated both in open-loop and closed-loop configurations. The stability is here characterized using the Allan deviation. For open-loop tracking, it is found that the Allan deviation gets separated into two regimes, one limited by the thermomechanical noise of the resonator and the other by the detection noise of the optical transduction system. The point of transition between the two regimes is the resonator response time, which can be shown to have a linear dependence on $Q$. Laser power fluctuations from the optical readout is found to present a fundamental limit to the frequency stability. Finally, for closed-loop measurements, the response time is shown to no longer be intrinsically limited but instead given by the bandwidth of the closed-loop tracking system. Computed Allan deviations based on theory are given as well and found to agree well with the measurements. These results are of importance for the understanding of fundamental limitations of high-$Q$ resonators and their application as high performance sensors.
AMReX: Block-structured adaptive mesh refinement for multiphysics applications

Block-structured adaptive mesh refinement (AMR) provides the basis for the temporal and spatial discretization strategy for a number of Exascale Computing Project applications in the areas of accelerator design, additive manufacturing, astrophysics, combustion, cosmology, multiphase flow, and wind plant modeling. AMReX is a software framework that provides a unified infrastructure with the functionality needed for these and other AMR applications to be able to effectively and efficiently utilize machines from laptops to exascale architectures. AMR reduces the computational cost and memory footprint compared to a uniform mesh while preserving accurate descriptions of different physical processes in complex multiphysics algorithms. AMReX supports algorithms that solve systems of partial differential equations in simple or complex geometries and those that use particles and/or particle–mesh operations to represent component physical processes. In this article, we will discuss the core elements of the AMReX framework such as data containers and iterators as well as several specialized operations to meet the needs of the application projects. In addition, we will highlight the strategy that the AMReX team is pursuing to achieve highly performant code across a range of accelerator-based architectures for a variety of different applications.
LARVAE OF EIGHT EASTERN NORTH AMERICAN SWELTSA (PLECOPTERA: CHLOROPERLIDAE)

Larval descriptions are provided for eight eastern Nearctic species of Sweltsa. Larvae of Sweltsa hoffmani Kondratieff & Kirchner, S. lateralis (Banks), S. mediana (Banks), S. naica (Provancher), S. palearata Surdick, S. pocahontas Kirchner & Kondratieff and S. urticae (Ricker) are described for the first time and compared with S. onkos (Ricker). A provisional key is presented for larvae of these eastern Nearctic species.
The familial aggregation of obstructive sleep apnea

An inherited basis for sleep-disordered breathing (SDB) has been suggested by reports of families with multiple affected members and by a previous study of the familial aggregation of symptoms of SDB. In this study, we quantify and characterize the aggregation of SDB and assess the degree to which familial similarities may be independent of obesity. This was a genetic-epidemiologic study that assessed the distribution of SDB in families identified through a proband with diagnosed sleep apnea and among families in the same community with no relative with known sleep apnea. SDB was assessed with overnight in-home monitoring of airflow, oxygen saturation, chest wall impedance, heart rate, and body movement. Standardized questionnaires were used to assess symptoms, and weight, height, and neck circumference were measured directly. Intergenerational and intragenerational correlation coefficients and pairwise odds ratios (ORs) were calculated with adjustment for proband sampling. In toto, 561 members of 91 fami.