Miracle-dz/UniFAR-FTUs huggingface dataset:
Construction of a composite pressure–temperature path: revealing the synorogenic burial and exhumation history of the Sevier hinterland, USA

Metamorphic pressure–temperature (P–T) paths derived from 16 growth‐zoned garnets, nine from this study and seven from a previous study, have been combined to construct a detailed composite path for an area in the hinterland of the Cretaceous to early Tertiary Sevier orogenic belt in southern Idaho and north‐west Utah. Samples are from two Proterozoic units in the footwall of the Basin‐Elba thrust: the schist of Mahogany Peaks in the central Albion Mountains, Idaho, and the schist of Stevens Spring in the Basin Creek area of the Grouse Creek Mountains, Utah, ∼40 km to the south. The simulated portions of the garnets analysed in this study grew from reactions involving the breakdown of chlorite in the upper greenschist to lower amphibolite facies. Multiple garnets were analysed from three samples. Overlapping segments of P–T paths from different garnets in the same sample correlate with respect to slope and garnet Mn concentration. The composite P–T path documents three episodes of sharply increasing pressures separated by two episodes of pressure decrease, all during progressively increasing temperatures. The path is interpreted to represent alternating episodes of synconvergent thrusting and extensional exhumation in the hinterland of the Sevier orogen. Burial was probably caused by the Basin‐Elba fault, the only major thrust exposed in the region. Extensional exhumation may have occurred along the Mahogany Peaks or Emigrant Spring faults, or by extensional reactivation of the Basin‐Elba fault. This method of correlating partial P–T paths to reveal a more complete composite path provides a powerful tool in unveiling orogenic histories in metamorphic terranes, where evidence of major structures responsible for burial and exhumation is commonly obscured by later events.
BIRD: Engineering an Efficient CNF-XOR SAT Solver and Its Applications to Approximate Model Counting

Given a Boolean formula φ, the problem of model counting, also referred to as #SAT is to compute the number of solutions of φ. Model counting is a fundamental problem in artificial intelligence with a wide range of applications including probabilistic reasoning, decision making under uncertainty, quantified information flow, and the like. Motivated by the success of SAT solvers, there has been surge of interest in the design of hashing-based techniques for approximate model counting for the past decade. We profiled the state of the art approximate model counter ApproxMC2 and observed that over 99.99% of time is consumed by the underlying SAT solver, CryptoMiniSat. This observation motivated us to ask: Can we design an efficient underlying CNF-XOR SAT solver that can take advantage of the structure of hashing-based algorithms and would this lead to an efficient approximate model counter? The primary contribution of this paper is an affirmative answer to the above question. We present a novel architecture, called BIRD, to handle CNF-XOR formulas arising from hashingbased techniques. The resulting hashing-based approximate model counter, called ApproxMC3, employs the BIRD framework in its underlying SAT solver, CryptoMiniSat. To the best of our knowledge, we conducted the most comprehensive study of evaluation performance of counting algorithms involving 1896 benchmarks with computational effort totaling 86400 computational hours. Our experimental evaluation demonstrates significant runtime performance improvement for ApproxMC3 over ApproxMC2. In particular, we solve 648 benchmarks more than ApproxMC2, the state of the art approximate model counter and for all the formulas where both ApproxMC2 and ApproxMC3 did not timeout and took more than 1 seconds, the mean speedup is 284.40 – more than two orders of magnitude.
The In ﬂ uence of Climate Fiction An Empirical Survey of Readers

Climate ﬁ ction — literature explicitly focused on climate change — has exploded over the last decade, and is often assumed to have a positive ecopolitical in ﬂ uence by enabling readers to imagine potential climate futures and persuading them of the gravity and urgency of climate change. Does it succeed? And whom does it reach? A qualitative survey of 161 American readers of 19 works of climate ﬁ ction ﬁ nds that these readers are younger, more liberal, and more concerned about climate change than nonreaders of climate ﬁ ction. Drawing on concepts from ecocriticism, environmental psychology, and environmental communication, this article suggests that “ cli- ﬁ ” reminds concerned readers of the severity of climate change while impelling them to imagine environmental futures and consider the impact of climate change on human and nonhuman life. However, the actions that resulted from readers ’ heightened consciousness reveal that awareness is only as valuable as the cultural messages about ef ﬁ cacious action that are in circulation. Moreover, the affective responses of many readers suggest that most works of climate ﬁ ction are leading readers to associate climate change with intensely negative emotions, which could prove counterpro-ductive to efforts at environmental engagement or persuasion. Based on one of the ﬁ rst studies to empirically examine the reception of environmental literature, this article demonstrates a novel interdisciplinary approach to environmental literature (empirical ecocriticism) and points the way to future research in this vein.
Satellite thermal microwave sea ice concentration algorithm comparison

Seven of the most common radiometer algorithms, used to compute the sea ice concentration, are compared to ScanSAR data estimates of ice concentration. Our focus is on the near 100% ice cover in winter. The sensitivity of the algorithms to the variable sea ice surface emissivity and temperature is the most significant hindrance for correct estimates of ice concentration in this ice regime. The skill of the best radiometer algorithms is significantly better than the worst set, but all correlate poorly to and display higher variability than the SAR data at high ice concentrations. On a climatological time scale the differences between algorithms amounts to 14% and 22% of the down-going trend in winter Arctic sea ice extent and area, respectively. The climatological changes in atmospheric and water surface emissivity primarily affects the extent trend while the changes in sea ice surface emissivity affects the sea ice area trend.
S speciation in submarine basaltic glasses as determined by measurements of SKc X-ray wavelength shifts

S occurs in both oxidized (36* ) and reduced (S'z-) forms in natural silicate liquids. The wavelength ofSKa radiation changes as a function ofthe oxidation state ofS and can be used to determine the proportions of sulfide and sulfate in unknown samples by comparison with reference standards of a known valence state. We have measured the wavelength of SKa X-rays in a variety of glassy submarine lavas from spreading centers (Juan de Fuca, Gal6pagos, Kane, and Southeast Indian Ridge), seamounts (Loihi and Lamont seamounts), and back-arc basins (Lau Basin). The relative /o, values of these glasses are known from wet-chemical determinations of FeO and FerO. and vary from slightly above the Ni + NiO buffer (NNO) Io 3.2 log units below NNO. Measured values of sulfate/S,", (56*/5.",) vary from 0.02 to 0.25 and increase with increasing relative /o,. Our results demonstrate that the dissolved S in these samples occurs predominately as 52 . Large variations in HrO content have no measurable effect on the redox state of S, suggesting that HrS or HSare not abundant S species in solution in silicate liquids. Thermodynamic calculations show that the speciation of S in coexisting gas during submarine eruptions of basaltic magma is also dependent on relative /o,. Many lavas from seamounts and backarc basins are predicted to have S present mainly as SO, in coexisting magmatic gas, whereas the lower f, of midocean ridge basalts favor HrS as the dominant form of gaseous S.
Mach 5 bow shock control by a nanosecond pulse surface dielectric barrier discharge

Bow shock perturbations in a Mach 5 air flow, produced by low-temperature, nanosecond pulse, and surface dielectric barrier discharge (DBD), are detected by phase-locked schlieren imaging. A diffuse nanosecond pulse discharge is generated in a DBD plasma actuator on a surface of a cylinder model placed in air flow in a small scale blow-down supersonic wind tunnel. Discharge energy coupled to the actuator is 7.3–7.8 mJ/pulse. Plasma temperature inferred from nitrogen emission spectra is a few tens of degrees higher than flow stagnation temperature, T = 340 ± 30 K. Phase-locked Schlieren images are used to detect compression waves generated by individual nanosecond discharge pulses near the actuator surface. The compression wave propagates upstream toward the baseline bow shock standing in front of the cylinder model. Interaction of the compression wave and the bow shock causes its displacement in the upstream direction, increasing shock stand-off distance by up to 25%. The compression wave speed behind the.
Two-Timescale Networks for Nonlinear Value Function Approximation

A key component for many reinforcement learning agents is to learn a value function, either for policy evaluation or control. Many of the algorithms for learning values, however, are designed for linear function approximation—with a fixed basis or fixed representation. Though there have been a few sound extensions to nonlinear function approximation, such as nonlinear gradient temporal difference learning, these methods have largely not been adopted, eschewed in favour of simpler but not sound methods like temporal difference learning and Q-learning. In this work, we provide a two-timescale network (TTN) architecture that enables linear methods to be used to learn values, with a nonlinear representation learned at a slower timescale. The approach facilitates the use of algorithms developed for the linear setting, such as data-efficient least-squares methods, eligibility traces and the myriad of recently developed linear policy evaluation algorithms, to provide nonlinear value estimates. We prove convergence for TTNs, with particular care given to ensure convergence of the fast linear component under potentially dependent features provided by the learned representation. We empirically demonstrate the benefits of TTNs, compared to other nonlinear value function approximation algorithms, both for policy evaluation and control.
Personalisation in Location-based Advertising: The Moderating Effect of Brand Familiarity

The increasing adoption of location-based services and smart devices have propelled optimistic forecasts for location-based advertising as a unique and effective tool to improve consumers’ attitude and purchase intention towards goods and services. While so, concerns regarding over the use of personalisation in a LBA context is prevalent. Given so, this study examines the influence of personalisation tactics on attitudes and purchase intention towards a focal product, with brand familiarity as a moderating factor, in the context of location-based advertising. It is hypothesized that high personalisation improves attitude towards a focal product and secondly, that high brand familiarity aids the resulting outcome of personalisation. Finally, it is hypothesized that attitude is positively related to purchase intention. As a central part of the study, an experiment involving 100 participants was conducted. The experiment’s stimuli involved the presence and absence of personalisation and brand familiarity respectively, forming a total of four equal participant groups. It was found that personalisation positively affects the effects of location-based advertising; while brand familiarity indeed moderates the effects of personalisation on attitudes. Specifically, high brand familiarity allows for heightened effects of personalisation on attitudes, while in low brand familiarity situations, the effects of personalisation in a location-based ad is negligible. Since so, brand familiarity is an evidenced boundary condition for the effective application of location-based advertising. The study supports past research in establishing that brand familiarity lowers perceived risks and increases trust for location-based advertising, and that personalisation allows for more effective marketing messages. From a practical perspective, marketers of well-known brands should look to personalisation in location-based marketing opportunities to exploit their inherent brand value. On the other hand, less-known brands should look to improve their brand familiarity before applying personalisation in locationbased ads.
The Rise of German Protectionism in the 1870s: A Macroeconomic Perspective∗

The 1879 German ‘iron and rye’ tariff marked a turning point in nineteenth-century European tariff history. This paper challenges the leading political-economy explanations for the adoption of the tariff that focus on the effects of a decline in European grain prices on Germany’s income distribution. Instead it claims that severe macroeconomic imbalances caused by the Franco-Prussian War indemnity played the crucial role in the rise of protectionism in Germany in the 1870s and in the eventual adoption
A Neural Framework for Low-Shot Learning

There has been a growing interest in developing machine learning models that are capable of low-shot learning, the machine learning problem of learning from little data. Progress on low-shot learning has important practical applications to domains in which data for training state-of-the-art algorithms are scarce, for example in identifying rare diseases in medical images or personalizing online services to a user’s activity. Improvements on this task would also have important theoretical implications, as a successful solution in low-shot learning would likely also push the boundary in representation learning, natural language or image understanding, etc. Matching networks are a recently proposed model for low-shot learning that combine neural networks with nonparametric models. They were shown to perform well on benchmark low-shot learning tasks, highlighting the potential of this approach. To better understand the strengths and shortcomings of this family of models, in this work, we compare matching networks and several variants, against a strong baseline when applied to a diverse set of tasks. We find that on relatively simple low-shot learning tasks such as character recognition, specialized low-shot models are not necessary to do well. On more complex tasks such as facial recognition, we see significant improvements in accuracy when using matching networks.
Prohexadione-Calcium Application during Vegetative Growth Affects Growth of Mother Plants, Runners, and Runner Plants of Maehyang Strawberry

Strawberry (Fragaria × ananassa Duch.) is an important horticultural crop that is vegetatively propagated using runner plants. To achieve massive production of runner plants, it is important to transfer the assimilation products of the mother plant to the runner plants, and not to the runner itself. Application of prohexadione–calcium (Pro–Ca), a plant growth retardant with few side effects, to strawberry is effective in inhibiting transport of assimilates to runners. This study aimed to determine the optimum application method and concentration of Pro–Ca on the growth characteristics of mother plants, runners, and runner plants for the propagation of strawberry in nurseries. Pro–Ca was applied at the rate of 0, 50, 100, 150, or 200 mg·L−1 (35 mL per plant) to plants via foliar spray or drenching under greenhouse conditions at 30 days after transplantation. Petiole lengths of mother plants were measured 15 weeks after treatment; growth was suppressed at the higher concentrations of Pro–Ca regardless of the application method. However, the crown diameter was not significantly affected by the application method or Pro–Ca concentration. The number of runners was 7.0 to 8.2, with no significant difference across treatments. Runner length was shorter at higher concentrations of Pro–Ca, especially in the 200 mg·L−1 drench treatment. However, fresh weight (FW) and dry weights (DW) of runners in the 50 mg·L−1 Pro–Ca drench treatments were higher than controls. Foliar spray and drench treatments were more effective for runner plant production than the control; a greater number of runner plants were produced with the 100 and 150 mg·L−1 Pro–Ca foliar spray treatment and the 50 and 100 mg·L−1 drench treatment. The FW and DW of the first runner plant was not significantly different in all treatments, but DW of the second runner plant, and FW and DW of the third runner plant were greatest in the 50 mg·L−1 Pro–Ca drench treatment. These results suggested that growth and production of runner plants of Maehyang strawberry were greatest under the 50 mg·L−1 Pro–Ca drench treatment.
Effects of Javan Rusa Deer (Cervus timorensis) on Native Plant Species in the Jibbon-Bundeena Area, Royal National Park, New South Wales

A reconnaissance survey and exclosure experiment were carried out to examine the effects of Javan rusa deer on native flora and vegetation in Royal National Park on the southern outskirts of Sydney, Australia. Of 78 native plant species examined during the survey, only nine showed no evidence of vertebrate herbivory or physical damage and the majority of these plants were ferns and sedges. The other 69 species showed effects that included defoliation (young and/or old leaves), removal of shoots, bark-stripping, stem breakages and destruction or consumption of reproductive material. These effects varied in severity between species and from place to place, and were inferred to have been caused by deer based on the local abundance of deer droppings, footprints and the scarcity of other vertebrate herbivores in the area. The survey also revealed localised soil erosion associated with high densities of deer footprints and droppings. An unreplicated exclosure experiment showed that planted saplings of Syzygium paniculatum, a threatened rainforest tree, suffered major defoliation, bark stripping, stem breakages and some mortality when exposed to deer for several months. Many of the surviving plants showed signs of recovery when deer were subsequently excluded, although full recovery of their leaf canopies could take several seasons. The observed effects on vegetation and individual plant species are consistent with studies on several other deer species in a range of ecosystems overseas. A model of the effects of deer herbivory based on plant life-history suggests that curtailment of seed production and seedling recruitment are likely to be the major impacts of deer on plant population viability. Reductions in net growth and survival of established plants and possibly post-dispersal predation of seeds are less likely to be significant influences.
Experimental methodologies and diagnostic procedures for acute hepatopancreatic necrosis disease ( AHPND )

Acute hepatopancreatic necrosis disease (AHPND) is an emerging disease that has caused mass mortality in shrimp in many countries in Asia and South America. A new strain of Vibrio parahaemolyticus (VpAHPND), carrying one or more extrachromosomal ~70 kbp plasmids that encode homologues of the Photorhabdus insect-related (Pir) binary toxins (PirAvp and PirBvp) is the causative agent of AHPND. Bioassay challenges using immersion, reverse gavage and per os (feeding) treatments have been shown to induce the pathology characteristics of AHPND in experimentally infected shrimp. Moreover, a number of polymerase chain reaction (PCR) methods have been found to facilitate early detection of the disease. However, non-V. parahaemolyticus species close to Vibrio harveyi, Vibrio owensii and Vibrio campbellii have recently been identified as carrying pVA1-like plasmids, signifying that these plasmids are capable of being transmitted to different Vibrio species. AHPND is thus a threat and a serious concern for the aquaculture industry. Against this background, this paper presents an overview of experimental methodologies and diagnostic procedures for AHPND. It also includes fundamental findings related to the disease as guidelines which may be useful for further experimental work on AHPND and other similar shrimp diseases.
Observations of low-energy electrons upstream of the Earth's bow shock

Observations of electron fluxes with a lunar-based electron spectrometer when the moon was upstream of the earth have shown that a subset of observed fluxes are strongly controlled by the interplanetary magnetic field (IMF) direction. The fluxes occur only when the IMF lines connect back to the earth's bow shock. Observed densities and temperatures were in the ranges 0.002 to 0.004 per cu cm and 1,700,000 to 2,800,000 K. It is shown that these electrons can account for increases in effective solar wind electron temperatures on bow shock connected field lines, which have been observed previously by other investigators. It is further shown that if a model of the bow shock with an electrostatic potential barrier is assumed, the potential can be estimated to be 500 V.
Unmasking Anxiety in Autism: Explicit and Implicit Threat Dissociate Amygdala-centered Functional Connectivity

Background Anxiety is the most prevalent comorbidity in individuals diagnosed with autism spectrum disorder (ASD). Amygdala reactivity to explicit and implicit threat processing offers a platform to assess anxiety. The neural mechanisms underlying the link between anxiety and ASD remains elusive.Methods In this fMRI study, we recruited young adults with ASD (N = 31) and matched them with controls, then proceeded to assess their autistic and anxiety traits by the use of the Autism-Spectrum Quotient (AQ) and the State-Trait Anxiety Inventory (STAI-S), respectively; and scanned their amygdala reactivity in response to explicit and implicit (backward masking) perception of threatening faces.Results As compared to controls, the amygdala reactivity in ASD subjects was significantly reduced to explicit threat, but comparable to implicit threat. The correlations of the amygdala reactivity with the AQ and STAI-S were dissociated depending on threat processing (explicit or implicit). Furthermore, the amygdala in ASD relative to controls had a more negative functional connectivity with the superior parietal cortex, fusiform gyrus, and hippocampus for explicit threat, whereas a more positive connectivity with the medial prefrontal cortex, temporal pole, and hippocampus for implicit threat.Conclusion In ASD, the transmission of socially relevant information along dorsal and ventral neural pathways centered on the amygdala is dissociated depending on explicit and implicit threat processing. This dissociation, ascribed to their failure to compromise pre-existing hyperarousal, might contribute to anxiety in ASD.