The top quark plays an important role in a number of new physics models, some of which introduce violations to some of the accidental symmetries of the SM, such as the lepton number conservation or introduce additional sources of others already broken, such as the CP symmetry. A set of measurements is presented that probe violation of these symmetries in processes involving the top quark, in association with additional particles.
Cotton is a leading cash crop and ranks first in value-added crops in the United States of America. Timely and accurate information on the spatial distribution of cotton fields is vital for cotton management and production prediction. In this study, we combined hourly PhenoCam pictures and time series Sentinel-2 images and identified the unique white feature in the cotton open-boll period from spectroscopy analysis. We then developed a color-based algorithm to automatically identify and map open-boll cotton fields at the 10-m spatial resolution in the southeastern United States using time series Sentinel-2 and Sentinel-1 images in 2019. We also generated the starting date map of the open-boll period. The area of the open-boll cotton fields was 17.90 (± 1.08) × 103 km2, with the largest area in Georgia of 4.05 × 103 km2, about 23 % of the total open-boll cotton fields. Based on the stratified random sampling ground references, the open-boll cotton field map had a high overall accuracy of 95 % (± 1 %). The starting dates of the open-boll period varied across the southeastern United States, mainly ranging from the day of the year (DOY) 244 to 304 (September and October). The color-based algorithm performed well in multiple years and different regions, demonstrating the algorithm’s robustness and potential for regional application. This study could provide data and methodological support for the management of cotton fields and cotton supply chain management to achieve the No Poverty and No Hunger Sustainable Development Goals of the United Nations.
The limited whole-rock geochemical data of the granitoids exposed in the southern domain of the South Delhi Terrane, Aravalli orogen, northwestern India characterised these rocks as subduction-related continental arc I-type granites. The new comprehensive mineralogical and geochemical data of these Tonian (975–965 Ma) granitoids, particularly those exposed around the Bekariya region, reveal that they are not continental arc I-type granites. These granitoids are rather high-K, I-type, weakly peraluminous to metaluminous, magnesian to ferroan, calc-alkalic to calcic and emplaced in a post-collisional extension regime. They comprise predominantly high-temperature (764–845°C) granitoids, along with a subordinate volume of low-temperature (669–776°C) granitoids. The nearly flat to variably inclined [(Gd/Yb)N = 1.0–4.8)] and depleted [(Gd/Yb)N = 2.8–3.0)] HREE patterns of the granitoids with notable negative (Eu/Eu* = 0.21–0.71) and insignificant (Eu/Eu* = 0.83–0.85) Eu anomalies, respectively and variable Sr/Y ratios (0.6–93.9), imply variation in the depth of their magma generation. Taken together, these data suggest that the high-temperature I-type Bekariya granitoids most likely originated from dehydration partial melting of metabasaltic-metandesitic crust that required a significant influx of heat in a post-collisional or post-orogenic setting. In contrast, the minor low-temperature I-type granitoids probably resulted from partial melting of a similar source by the infiltration of a water-rich fluid phase in a subduction-related setting. Furthermore, the study signifies that I-type granitoids are more voluminous than A-type granitoids in the South Delhi Terrane and were emplaced coevally in a post-collisional extension regime during the Tonian period.
Abstract Silurian strata are well-developed in the northwest margin of Yangtze Platform. A total of 117 densely spaced argillaceous samples were taken from the Shenxuanyi Member, upper Ningqiang Formation to the lowermost Chejiaba Formation of the Majia section in northern Sichuan Province. The main aim of this study is to obtain chitinozoans to test whether Wenlock deposits are preserved here. A highly diverse and abundant chitinozoan assemblage is documented, including 21 species from six genera. This assemblage was then compared to contemporaneous chitinozoan assemblages reported from adjacent areas. This study proposes that Eisenackitina venusta (corresponds to the Pterospathodus celloni conodont Biozone) is of chronostratigraphical significance for discussing the Telychian of the Yangtze region. It is suggested that the Silurian upper red bed (lower part of the Shenxuanyi Member) in the study area is younger than the Xiushan Formation and can be correlated with the Huixingshao Formation of the Central Yangtze Platform. There are no index chitinozoan species near the Llandovery–Wenlock boundary that have been found in the upper part of the Shenxuanyi Member, and the updated chronostratigraphic framework suggests that it is Telychian-aged deposits.
Study region: This study focuses on the Yulong Snow Mountain (YLSM), a glacier region in the southeastern edge of the Qinghai-Tibet Plateau. Study focus: Stable isotopes were used to study transformation processes in different water bodies. HYSPLIT model was employed to analyze the trajectory paths and calculate the moisture flux. Finally, we used a binary linear mixed model to estimate the contribution of the artificial lake to precipitation in the glacial region. New hydrological insights for the region: Isotopic analysis of the hydrological system in YLSM has revealed distinct altitude-dependent and seasonal patterns. The moisture sources of YLSM exhibit pronounced seasonality, dominated by the Indian Ocean monsoon in summer and the westerly jet in winter, with the South Asian continental air mass as a persistent year-round contributor. Our findings demonstrate that vapor derived from artificial lakes contributes 8 %–42 % of the total snowfall in the glacial region of YLSM during the snowfall period, with a notable contribution of 8 %–16 % during the primary glacial accumulation period. This additional moisture input significantly decelerates local glacial retreat. In previous calculations of the local water cycle, the impact of artificial lakes has been underestimated. This study further expands local glacier protection technologies and deepens the understanding of the water cycle processes in high-altitude mountainous regions.
ABSTRACT High‐Arctic environments are facing an elevated pace of warming and increasing human activities, making them more susceptible to the introduction and spread of alien species. We investigated the role of human disturbance in facilitating the spread of a native plant (Papaver dahlianum) in a high‐Arctic natural environment close to Isfjord Radio station and along adjacent hiking trails at Kapp Linné, Svalbard. We reconstructed the spatial pattern of the arrival and spread of P. dahlianum at Kapp Linné by combining historical records of the species occurrence (1928–2018) with a contemporary survey of the plant abundance along the main hiking trail (2023 survey) and tested the relative effects of altitude and proximity to hiking trails on the species density via a generalised linear model (GLM). We then compared historical records with the simulated annual spread of the species by assuming either only local spread or local spread plus spread from hiking trails. Finally, we used a fine‐scale UAV‐derived brightness index to test for terrain preference by applying a randomisation test. Distance from the station (56% explained variation) and minimum distance from the trail (28%) significantly explained the species density across the research area (best GLM R2 = 0.755). The modelled species spread including the trail effect (fitted spread ~30 m yr.−1) managed to capture the maximum extent of the occupied area, whereas simulations assuming only local spread (~2 m yr.−1) underestimated the historical extent. A randomisation test showed that P. dahlianum has a significant preference for gravel soils with low vegetation cover due to either trail trampling and/or natural processes. Along with climate warming, human activities can increase the rate of species range shift by providing hot spots of introduction (human settlements) and spreading corridors (hiking trails). Our results show that spatially explicit models can be applied to accurately predict the potential spread of species, leading to a more efficient monitoring plan. Systematic monitoring of alien species and sanitisation measures should be prioritised in polar habitats with a high incidence of human disturbances.
Lucas T. Fromm, Laurence C. Smith, Ethan D. Kyzivat
Accurate remote sensing of wetland vegetation is challenging due to heterogeneous land cover, dynamic water reflectance and extent, and spectrally similar plant types. The high spatiotemporal resolution of nanosatellite constellations enables ‘phenological leveraging’ (PL)—identification and tracking of spectrally distinct phenological events to help differentiate wetland vegetation. We use PlanetScope Dove-R images, field training data, and PL to map wetland landcover in a complex riverine wetland in Rhode Island, USA. Maximum Likelihood (MLC), Support Vector Machine (SVM), and Artificial Neural Network (ANN) classification algorithms are tested on individual, monthly- and multi-seasonal composite images. The greatest improvements in classification accuracy derive from targeting optimal months of maximum phenological contrast for each landcover class, and then compositing these optimized classifications into a single map. We conclude that nanosatellite constellations offer a powerful new approach for mapping wetland vegetation classes at fine spatial scales.
ABSTRACT Technological modes of urbanism continue to transform and expand with new technologies, new actors, and new developments that are ripe for critical geographical analysis. This series of interventions focuses on capturing and understanding a still evolving movement called platform urbanism, which is centered around the growing presence and power of digital platforms in cities. This different mixture of capital-technology-cities tends to be more directly connected to consumers, more intent on rapid scaling, and more antagonistic to governments and incumbent industries. This series lays out how the emergence of platform urbanism is already provoking serious issues related to the oversight, operation, and ownership of urban services and spaces. Thematically, the series is organized around making sense of different geographical relationships at the center of platform urbanism. This contribution focuses on the dual production of space (digital/physical) and value (data/money) within cities.
Francesc Pérez-Peris, Jonathan M. Adrain, Allison C. Daley
Abstract Cheiruridae is one of the most diverse families of trilobites known from the Ordovician with 453 species assigned. Within Cheiruridae eight subfamilies (Acanthoparyphinae, Cheirurinae, “Cyrtometopinae”, Deiphoninae, Eccoptochilinae, Heliomerinae, Pilekiinae, and Sphaerexochinae) have historically been recognised. Insights about the evolution of the family and the relationships within and between subfamilies have been published. However larger scale phylogenetic hypotheses are needed in order to explore the monophyly, the basal structure, the deep nodes and the relationships of the subfamilies. Cheirurinae, Deiphoninae and “Cyrtometopinae” have historically been defined by various morphological features (e.g., anteroposterior constriction of the thoracic pleura, pleural furrow morphology, pygidial morphology) that differentiate them from the rest of Cheiruridae. However, the phylogenetic status of “Cyrtometopinae” is unclear owing to a lack of obvious synapomorphies. Here, we present phylogenetic analyses of Cheirurinae, Deiphoninae, and “Cyrtometopinae”. The results indicate that both Cheirurinae and Deiphoninae are monophyletic. “Cyrtometopines” are resolved as a paraphyletic grade at the base of Deiphoninae and Cyrtometopinae should be considered a junior subjective synonym of Deiphoninae. The new phylogenetic hypothesis reveals that paedomorphosis plays an important role in the evolution of Deiphoninae. Within Cheirurinae two major clades are identified, the ‘Ceraurus-like’ clade and the ‘Ceraurinella-like’ clade.
The present study reports a novel physical model for simulating Pulsating Heat Pipes (PHP). Their high heat performance is due to the phase change over thin liquid films. The simulation of physically correct film behavior is thus crucial. The model adopts the one-dimensional approach, which is computationally efficient yet still capable of capturing major physical phenomena. The model assumes a spatially uniform film thickness, whereas both the film thickness and length can vary over time; therefore, we call it the oscillating film thickness model. It is based on the physical analysis of liquid film deposition by the receding menisci of Taylor bubbles and of contact line dynamics. Three key phenomena are addressed: (i) film deposition, (ii) contact line receding due to dewetting acceleration by evaporation, and (iii) mass exchange over films and contact lines. The model is evaluated by simulating the simplest, single-branch PHP, for which detailed experimental data are available. A quantitative agreement is reached. As the model includes the wetting properties, their impact on oscillations is analyzed; a qualitative agreement with the experiment is demonstrated.
Laura Gustafson, Megan Richards, Melissa Hall
et al.
Despite impressive advances in object-recognition, deep learning systems' performance degrades significantly across geographies and lower income levels raising pressing concerns of inequity. Addressing such performance gaps remains a challenge, as little is understood about why performance degrades across incomes or geographies. We take a step in this direction by annotating images from Dollar Street, a popular benchmark of geographically and economically diverse images, labeling each image with factors such as color, shape, and background. These annotations unlock a new granular view into how objects differ across incomes and regions. We then use these object differences to pinpoint model vulnerabilities across incomes and regions. We study a range of modern vision models, finding that performance disparities are most associated with differences in texture, occlusion, and images with darker lighting. We illustrate how insights from our factor labels can surface mitigations to improve models' performance disparities. As an example, we show that mitigating a model's vulnerability to texture can improve performance on the lower income level. We release all the factor annotations along with an interactive dashboard to facilitate research into more equitable vision systems.
In this brief contribution I will highlight some directions where the developments in the frontier of (quantum) metrology may be key for fundamental high energy physics (HEP). I will focus on the detection of dark matter and gravitational waves, and introduce ideas from atomic clocks and magnetometers, large atomic interferometers and detection of small fields in electromagnetic cavities. Far from being comprehensive, this contribution is an invitation to everyone in the HEP and quantum technologies communities to explore this fascinating topic.
Meagan Sundstrom, Rebeckah K. Fussell, Anna McLean Phillips
et al.
Research on nontraditional laboratory (lab) activities in physics shows that students often expect to verify predetermined results, as takes place in traditional activities. This understanding of what is taking place, or epistemic framing, may impact their behaviors in the lab, either productively or unproductively. In this paper, we present an analysis of student epistemic framing in a nontraditional lab to understand how instructional context, specifically instructor behaviors, may shape student framing. We present video data from a lab section taught by an experienced teaching assistant (TA), with 19 students working in seven groups. We argue that student framing in this lab is evidenced by whether or not students articulate experimental predictions and by the extent to which they take up opportunities to construct knowledge (epistemic agency). We show that the TA's attempts to shift student frames generally succeed with respect to experimental predictions but are less successful with respect to epistemic agency. In part, we suggest, the success of the TA's attempts reflects whether and how they are responsive to students' current framing. This work offers evidence that instructors can shift students' frames in nontraditional labs, while also illuminating the complexities of both student framing and the role of the instructor in shifting that framing in this context.
Floian, Early Ordovician trilobites are systematically described and revised based on new material from the middle part
of the Duoquanshan Formation of the Shihuigou area, northern Qinghai Province, northwest China. The fauna that lived
on the shallow-water carbonate platform comprises three species belonging to two families, i.e., Tsaidamaspis diarmatus,
Zhiyia tsinghaiensis, and Liexiaspis sp. indeterminate. It exhibits a strong endemicity to the Olongbluk terrane. The new
isoteline genus Zhiyia is established on the basis of the material from the Olongbluk terrane and South China palaeoplate,
and is characterized by its: (i) almost obsolete cephalic and pygidial axial furrows; (ii) flattened anterior border
and narrow (sag., exsag.) occipital ring; (iii) bilobed hypostome with a shallow median notch and a small triangular
median projection; (iv) subsemicircular pygidium with wide pygidial axis and border. Faunal evidence indicates that the
palaeogeographic position of the Olongbluk terrane may have been situated closer to the South China palaeoplate rather
than the North China palaeoplate during the Floian.
The Hydrosocial Cycle (HSC) has been widely applied and discussed as a consolidated research line to rethink the contemporary challenges that condition the urban and agroecosystem nexus. However, additional research directions are still open to guide policy and decision-makers in reinforcing stakeholders’ engagement and interaction to resolve tensions between water demands. This perspective paper suggests updating the HSC approach to improve the analysis of stakeholder interaction when addressing water scarcity in waterscapes. After briefly review the most relevant contributions of the HSC approach in the last two decades, we develop a preliminary framework to reinforce stakeholders’ interdependence analysis by designing a questionnaire to synthesize five main behavioral patterns conditioning stakeholders’ interactions: relevance, representativeness, recognition, assessment, and collaboration. Then, each pattern is organized in a triple-loop approach: to be, to do, and to share to characterize the mutual (mis)understanding of the stakeholders. The results of its application to Benidorm (south of Spain), a mass-tourism destination coexisting with rural development in tension for water supply, exemplified how 1) most stakeholders consider themselves important, but some of them are unaware of the role of others, 2) all stakeholders receive a higher punctuation in terms of functions rather than actions, and 3) all stakeholders agree on the benefits of the predisposition of parties (willingness) to achieve agreements in the short or medium term. Future research should consider how to address the lack of representativeness and power imbalance together with mechanisms to reinforce longitudinal studies in which actions from stakeholders could be contrasted.
Searches for new physics often face unknown backgrounds, causing false detections or weakened upper limits. This paper introduces the deficit hawk technique, which mitigates unknown backgrounds by testing multiple options for data cuts, such as fiducial volumes or energy thresholds. Combining the power of likelihood ratios with the robustness of the interval-searching techniques, deficit hawks could improve mean upper limits on new physics by a factor two for experiments with partial or speculative background knowledge. Deficit hawks are well-suited to analyses that use machine learning or other multidimensional discrimination techniques, and can be extended to permit discoveries in regions without unknown background.
Pre-trained models (PTMs) have become a fundamental backbone for downstream tasks in natural language processing and computer vision. Despite initial gains that were obtained by applying generic PTMs to geo-related tasks at Baidu Maps, a clear performance plateau over time was observed. One of the main reasons for this plateau is the lack of readily available geographic knowledge in generic PTMs. To address this problem, in this paper, we present ERNIE-GeoL, which is a geography-and-language pre-trained model designed and developed for improving the geo-related tasks at Baidu Maps. ERNIE-GeoL is elaborately designed to learn a universal representation of geography-language by pre-training on large-scale data generated from a heterogeneous graph that contains abundant geographic knowledge. Extensive quantitative and qualitative experiments conducted on large-scale real-world datasets demonstrate the superiority and effectiveness of ERNIE-GeoL. ERNIE-GeoL has already been deployed in production at Baidu Maps since April 2021, which significantly benefits the performance of various downstream tasks. This demonstrates that ERNIE-GeoL can serve as a fundamental backbone for a wide range of geo-related tasks.
John A. Knaff, Charles R. Sampson, Matthew E. Kucas
et al.
This article provides a review of tropical cyclone (TC) surface wind estimation from an operational forecasting perspective. First, we provide a summary of operational forecast center practices and historical databases. Next, we discuss current and emerging objective estimates of TC surface winds, including algorithms, archive datasets, and individual algorithm strengths and weaknesses as applied to operational TC surface wind forecast parameters. Our review leads to recommendations about required surface coverage – an area covering at least 1100 km from center of TC at a 2-km resolution in the inner-core, and at a frequency of at least once every 6 h. This is enough coverage to support a complete analysis of the TC surface wind field from center to the extent of the 34-kt (17 m s−1) winds at 6-h intervals. We also suggest future designs of TC surface wind capabilities include funding to ensure near real-time data delivery to operators so that operational evaluation and use are feasible within proposed budgets. Finally, we suggest that users of archived operational wind radii datasets contact operational organizations to ensure these datasets are appropriate for their needs as the datasets vary in quality through time and space, even from a single organisation.
Carol P Harden, Sheryl Luzzadder-Beach, Glen M MacDonald
et al.
Physical geography is a process, conducted by people, of integration and synthesis of ideas and observations to advance scientific understanding of Earth’s surface and atmosphere and to apply this knowledge to the greater good of the planet and its people. Therefore, physical geography matters; that is, physical geography makes a difference to people and contributes to environmental decision making at various scales. Based upon presentations and discussion at the 2019 AAG Annual Meeting (see editorial above in this issue), we provide here a historical perspective and distillation of how and why, in our opinions, physical geography matters. Although we provide several specific examples, these represent only a small portion of the large body of excellent and relevant physical geography research.
Contrastive learning methods have significantly narrowed the gap between supervised and unsupervised learning on computer vision tasks. In this paper, we explore their application to geo-located datasets, e.g. remote sensing, where unlabeled data is often abundant but labeled data is scarce. We first show that due to their different characteristics, a non-trivial gap persists between contrastive and supervised learning on standard benchmarks. To close the gap, we propose novel training methods that exploit the spatio-temporal structure of remote sensing data. We leverage spatially aligned images over time to construct temporal positive pairs in contrastive learning and geo-location to design pre-text tasks. Our experiments show that our proposed method closes the gap between contrastive and supervised learning on image classification, object detection and semantic segmentation for remote sensing. Moreover, we demonstrate that the proposed method can also be applied to geo-tagged ImageNet images, improving downstream performance on various tasks. Project Webpage can be found at this link geography-aware-ssl.github.io.