Miracle-dz/UniFAR-FTUs huggingface dataset:
The role of minority language bilingualism in spotting agreement attraction errors: Evidence from Italian varieties

Bilingual adaptations remain a subject of ongoing debate, with varying results reported across cognitive domains. A possible way to disentangle the apparent inconsistency of results is to focus on the domain of language processing, which is what the bilingual experience boils down to. This study delves into the role of the bilingual experience on the processing of agreement mismatches. Given the underrepresentation of minority bilingual speakers of non-standard varieties, we advance a unique comparative perspective that includes monolinguals, standard language bilinguals, and different groups of minority language bilinguals, taking advantage of the rich linguistic diversity of the Italian peninsula. This comparative approach can reveal the impact of various sociolinguistic aspects of the bilingual experience across different bilingual trajectories. We developed an auditory acceptability judgement task in Italian, featuring Subject-Verb agreement mismatches. Participants evaluated the stimuli on a 5-point Likert scale and reaction times were recorded. The results do not reveal significant differences between the speakers of standard languages: Italian monolinguals and Italian-Spanish bilinguals. Instead, significant differences are found between monolinguals and the two groups of minority language bidialectals, as well as between the bidialectal groups themselves: Italian-Pavese bidialectals were faster than both Italian-Agrigentino bidialectals and Italian monolinguals, while Italian-Agrigentino bidialectals were less accurate than both Italian-Pavese bidialectals and Italian monolinguals. This intricate picture is explained through variables associated with second language use and language switching. Our findings suggest that if bilingualism is viewed as a yes/no phenotype, it is unavoidable that the bilingual experience will remain a mystery linked to intensely debated results. If, however, one accepts that bilingual adaptations are shaped by the environmental ecology of each trajectory, variation across bilingual processing outcomes is unsurprising. Overall, we argue that specific sociolinguistic factors behind each bilingual experience can reveal where bilingual adaptations on language and cognition stem from.
Frequent and intense human-bat interactions occur in buildings of rural Kenya

Simultaneous use of domestic spaces by humans and wildlife is little understood, despite global ubiquity, and can create an interface for human exposure to wildlife pathogens. Bats are a pervasive synanthropic taxon and are associated with several pathogens that can spill over and cause disease in humans. Urbanization has destroyed much natural bat habitat and, in response, many species increasingly use buildings as roosts. The purpose of this study was to characterize human interactions with bats in shared buildings to assess potential for human exposure to and spillover of bat-borne pathogens. We surveyed 102 people living and working in buildings used as bat roosts in Taita-Taveta county, Kenya between 2021 and 2023. We characterized and quantified the duration, intensity, and frequency of human-bat interactions occurring in this common domestic setting. Survey respondents reported living with bats in buildings year-round, with cohabitation occurring consistently for at least 10 years in 38% of cases. Human contact with bats occurred primarily through direct and indirect routes, including exposure to excrement (90% of respondents), and direct touching of bats (39% of respondents). Indirect contacts most often occurred daily, and direct contacts most often occurred yearly. Domestic animal consumption of bats was also reported (16% of respondents). We demonstrate that shared building use by bats and humans in rural Kenya leads to prolonged, frequent, and sometimes intense interactions between bats and humans, consistent with interfaces that can facilitate exposure to bat pathogens and subsequent spillover. Identifying and understanding the settings and practices that may lead to zoonotic pathogen spillover is of great global importance for developing countermeasures, and this study establishes bat roosts in buildings as such a setting.
Mating strategies of Vitex negundo L. var. heterophylla (Franch.) Rehder (Lamiaceae): A mixed mating system with inbreeding depression

Abstract Plant reproductive ecology is one of the research hotspots in ecology. With the increasing attention paid to the conservation of plant diversity, the research on reproductive characteristics and flowering biological characteristics of more species has attracted more attention. However, plant reproduction is affected by multiple interacting factors such as pollen limitation and resource availability. Vitex negundo var. heterophylla (Franch.) Rehder (Lamiaceae) is a significant species for water and soil conservation. Previous studies have revealed its mating system by the biological characteristics of flowering and SSR markers, but its reproductive strategies remain to be further studied. We evaluated reproductive success through artificial pollination to explore the reproductive characteristics of V. negundo var. heterophylla for the first time. From the results of fruit set, there is a mixed mating system dominated by outcrossing in V. negundo var. heterophylla accompanied by self‐compatibility, and it cannot carry out autonomous selfing. Our data show the pollinator‐mediated interaction in the success of reproduction, whereas the effect of anemophily is very weak. And the seed germination rate of inbred line progenies was lower than that of hybrid progenies, which is suspected to be caused by inbreeding depression. The research will provide scientific information for the protection and conservation of V. negundo var. heterophylla from the point of view of reproduction. In sum, the results are necessary to protect animal vectors in the background of insect decline.
Multiyear Shallow Conduit Changes Observed With Lava Lake Eruption Seismograms at Erebus Volcano, Antarctica

We analyze near‐repeating broadband seismograms from nearly 3,000 eruptions (2003–2011) from the Erebus volcano lava lake to investigate temporal changes in the shallow eruptive dynamics of an open conduit volcano. Cross‐correlation analysis reveals progressive variable time lags between correlation‐aligned short period (SP) and very long period (VLP) seismogram components ranging over approximately ±1 s and evolving over weeks to months. Lava lake eruptions both excite an SP explosion seismic signal and gravitationally unload the conduit. After a delay of several seconds, this unloading excites a posteruptive, minute‐long VLP seismic signal that persist for several minutes until the lava lake is refilled. VLP‐SP lag variations are consistent across multiple seismic stations and are independent of eruption size, spectral characteristics, eruption frequency, and lava lake morphology changes. Lag changes are interpreted in terms of variable communication time between eruptions and the subsequent elastic and gravitational response of a tomographically imaged near‐summit magma storage and VLP source region several hundred meters below the lava lake. Tomographic and VLP moment tensor studies, combined with modeling, suggest that the elastodynamic communication time between the distinct SP and VLP source regions is mediated by conduit‐guided Stoneley waves within the uppermost magma‐filled conduit system that are sensitive to small shallow conduit geometry changes. Conduit geometry changes may be driven by internal or external processes, including conduit wall melting and refreezing, repeated eruptive slug erosion, and deformation from inner crater inflation or collapse.
Preliminary considerations about costs and potential market of remote sensing from UAV in the Italian viticulture context

ABSTRACT UAVs have already demonstrated to be effective in many fields. Nevertheless, at the moment, it is not still clear the type and the value of benefits they can provide for remote sensing purposes in agriculture. In particular, in the Italian context, this technique has still to demonstrate that derivable information can improve ordinary crop management. Furthermore, it is not still clear if costs are consistent with the ones of the agricultural sector and if any actual benefit can be really obtained. Some basic questions have to be answered: (a) are costs consistent with sector incomes? and (b) which is the related economic/environmental value? In this work reference values for UAV costs and productivity are proposed. A cost simulating model, based on both technical and economic considerations, and parameterized in respect of the size of the imaged area is proposed. Different UAV company paradigms are considered demonstrating that sustainable costs can be obtained only by making remote sensing skills internal to company. A brief discussion is also given, concerning (a) UAV potential market in the Italian viticulture context and (b) expected minimal composition that a company, basing its business on this type of service, should have.
Path-BigBird: An AI-Driven Transformer Approach to Classification of Cancer Pathology Reports

PURPOSE Surgical pathology reports are critical for cancer diagnosis and management. To accurately extract information about tumor characteristics from pathology reports in near real time, we explore the impact of using domain-specific transformer models that understand cancer pathology reports. METHODS We built a pathology transformer model, Path-BigBird, by using 2.7 million pathology reports from six SEER cancer registries. We then compare different variations of Path-BigBird with two less computationally intensive methods: Hierarchical Self-Attention Network (HiSAN) classification model and an off-the-shelf clinical transformer model (Clinical BigBird). We use five pathology information extraction tasks for evaluation: site, subsite, laterality, histology, and behavior. Model performance is evaluated by using macro and micro F1 scores. RESULTS We found that Path-BigBird and Clinical BigBird outperformed the HiSAN in all tasks. Clinical BigBird performed better on the site and laterality tasks. Versions of the Path-BigBird model performed best on the two most difficult tasks: subsite (micro F1 score of 72.53, macro F1 score of 35.76) and histology (micro F1 score of 80.96, macro F1 score of 37.94). The largest performance gains over the HiSAN model were for histology, for which a Path-BigBird model increased the micro F1 score by 1.44 points and the macro F1 score by 3.55 points. Overall, the results suggest that a Path-BigBird model with a vocabulary derived from well-curated and deidentified data is the best-performing model. CONCLUSION The Path-BigBird pathology transformer model improves automated information extraction from pathology reports. Although Path-BigBird outperforms Clinical BigBird and HiSAN, these less computationally expensive models still have utility when resources are constrained.
Antioxidant and anti-inflammatory injectable hydrogel microspheres for in situ treatment of tendinopathy

Abstract Tendinopathy is a common disorder that causes local dysfunction and reduces quality of life. Recent research has indicated that alterations in the inflammatory microenvironment play a vital role in the pathogenesis of tendinopathy. Herein, injectable methacrylate gelatin (GelMA) microspheres (GM) were fabricated and loaded with heparin-dopamine conjugate (HDC) and hepatocyte growth factor (HGF). GM@HDC@HGF were designed to balance the inflammatory microenvironment by inhibiting oxidative stress and inflammation, thereby regulating extracellular matrix (ECM) metabolism and halting tendon degeneration. Combining growth factors with heparin was expected to improve the encapsulation rate and maintain the long-term efficacy of HGF. In addition, the catechol groups on dopamine have adhesion and antioxidant properties, allowing potential attachment at the injured site, and better function synergized with HGF. GM@HDC@HGF injected in situ in rat Achilles tendinopathy (AT) models significantly down-regulated oxidative stress and inflammation, and ameliorated ECM degradation. In conclusion, the multifunctional platform developed presents a promising alternative for the treatment of tendinopathy.
Supervised classification of electric power transmission line nominal voltage from high-resolution aerial imagery

For many researchers, government agencies, and emergency responders, access to the geospatial data of US electric power infrastructure is invaluable for analysis, planning, and disaster recovery. Historically, however, access to high quality geospatial energy data has been limited to few agencies because of commercial licenses restrictions, and those resources which are widely accessible have been of poor quality, particularly with respect to reliability. Recent efforts to develop a highly reliable and publicly accessible alternative to the existing datasets were met with numerous challenges – not the least of which was filling the gaps in power transmission line voltage ratings. To address the line voltage rating problem, we developed and tested a basic methodology that fuses knowledge and techniques from power systems, geography, and machine learning domains. Specifically, we identified predictors of nominal voltage that could be extracted from aerial imagery and developed a tree-based classifier to classify nominal line voltage ratings. Overall, we found that line support height, support span, and conductor spacing are the best predictors of voltage ratings, and that the classifier built with these predictors had a reliable predictive accuracy (that is, within one voltage class for four out of the five classes sampled). We applied our approach to a study area in Minnesota.
Improving mesoscale observations from satellite altimetry using bottom pressure and tide gauge measurements in the Japan Sea

ABSTRACT In the Japan/East Sea (Sea of Japan), the basin-scale barotropic high-frequency signals cause aliasing error in the gridded sea level anomaly (SLA) product of the satellite altimeters. The aliasing errors can produce false mesoscale eddies and alter the dynamical explanation of ocean circulation. In this article, we corrected non-tidal aliasing errors in gridded SLA product using bottom pressure (BP) data and tide gauge (TG) data. The root mean square (RMS) of the aliasing induced SLA is about 3 cm in the Sea of Japan, which accounts for about 20% of the total energy. We found that, after BP correction, the percentage of error variance (PEV) is reduced from 43% to 34% for satellite-derived velocity, and from 22% to14% for 70-day low-pass filtered gridded SLA product. However, the improvement for TG correction is not notable. The basin-scale barotropic high-frequency signals are likely to be found in other nearly enclosed marginal seas. We suggested that more BP measurements should be conducted in the marginal seas for aliasing correction. The work in this article offers a useful reference for suppressing non-tidal alias errors in other marginal seas.
Engineered Barrier Systems (EBS) in the Safety Case

In the deep disposal of radioactive waste, the presence of several barriers serving complementary safety functions enhances confidence that the waste will be isolated and contained to protect human health and the environment. The barriers include the natural geological barrier and the engineered barrier system (EBS). The EBS itself may comprise a variety of sub-systems or components, such as the waste form, container, buffer, backfill, seals and plugs. These proceedings include the main findings and presented papers from the third NEA-EC workshop on engineered barrier systems, which focused on the role of EBS modelling in the safety case for deep disposal. The workshop examined the modelling tools currently available and identified complex areas of assessment in which further dialogue is needed.
Experiences of physiotherapists considering virtual reality for shoulder rehabilitation: A focus group study

Introduction Shoulder pain is common and associated with substantial morbidity. Different treatment strategies are being prescribed with equivocal results. Virtual reality (VR) is a novel technology and emerging research suggests that VR may be a promising alternative to current treatments. Prior to effectiveness research or any large-scale introduction, VR-applications require appropriate scrutiny including feasibility- and acceptability of clinicians and patients. Therefore, the aim of this study was to collect experiences of physiotherapists after using immersive VR. Methods A qualitative interpretive design was used to explore physiotherapists’ experiences related to the use of VR for people with shoulder symptoms. 17 physiotherapists were asked to use VR at home for five days prior to a focus group interview. Data from the focus group interviews were analyzed using a six-phase process of thematic analysis. Results Three main themes were identified, each divided into subthemes. The main themes were: 1. VR as an extension of contemporary physiotherapy care: physiotherapists were positive about the potential of VR and its applicability in daily care. 2. Physiotherapist uncertainties of future care using VR: participants expressed concerns about their professional identity, particularly as patients engage in independent home exercises. 3. Physiotherapist's requirements for implementation of VR: participants shared their needs for evidence regarding the effectiveness and parameters such as frequency, dosage and intensity of the VR intervention. Conclusion Physiotherapists were positive about VR as an intervention tool. However, they felt more knowledge is needed about parameters of VR. The findings of this study inform researchers and technology developers about optimal design of interventions and applications using VR.
Early prediction of end-stage kidney disease using electronic health record data: a machine learning approach with a 2-year horizon

Abstract Objectives In the United States, end-stage kidney disease (ESKD) is responsible for high mortality and significant healthcare costs, with the number of cases sharply increasing in the past 2 decades. In this study, we aimed to reduce these impacts by developing an ESKD model for predicting its occurrence in a 2-year period. Materials and Methods We developed a machine learning (ML) pipeline to test different models for the prediction of ESKD. The electronic health record was used to capture several kidney disease-related variables. Various imputation methods, feature selection, and sampling approaches were tested. We compared the performance of multiple ML models using area under the ROC curve (AUCROC), area under the Precision-Recall curve (PR-AUC), and Brier scores for discrimination, precision, and calibration, respectively. Explainability methods were applied to the final model. Results Our best model was a gradient-boosting machine with feature selection and imputation methods as additional components. The model exhibited an AUCROC of 0.97, a PR-AUC of 0.33, and a Brier score of 0.002 on a holdout test set. A chart review analysis by expert physicians indicated clinical utility. Discussion and Conclusion An ESKD prediction model can identify individuals at risk for ESKD and has been successfully deployed within our health system.
Structural and Tectonic History of the Eastern San Juan Islands, Washington

In order to address the heterogeneous character of the Decatur terrane, the rocks that occur within the easternmost San Juan Islands, Washington, are described and compared with respect to lithology, metamorphism, and structure. Based on these observations, a local structural and tectonic history is proposed. The exposed bedrock in the south part of the study area (Guemes, Huckleberry, Hat, Dot, and Saddlebag Islands) consists primarily of an arc-volcanic intrusive complex (diorite with crosscutting mafic to felsic dikes) as well as ultramafic cumulates of dunite, Iherzolite, and wehrlite. Most of the igneous rocks have no deformational fabric and are relatively unmetamorphosed, containing only very low-grade veins of quartz, calcite, and prehnite. These intrusive and ultramafic rocks are probably correlative with the Fidalgo Igneous Complex of Brown (1977). Highly deformed oceanic turbidites occur in the central and north part of the study area (Jack, Eliza, and Samish Islands). These rocks consist of chert-rich lithicquartzofeldspathic metagraywacke with interbedded metasiltstone and phyllite, along with minor intercalated metatuff. The metasedimentary rocks are all distinguished by the presence of at least one well-developed deformational fabric, with textural zones ranging from TZ 2A to TZ 3A-. Metamorphic minerals include abundant white mica, pumpellyite, prehnite, and lesser actinolite. Ar/Ar ages of two white mica samples indicate a Late Jurassic to Early Cretaceous age for the metamorphic fabric (-137 to -154 Ma). The Ar/Ar spectrum of white mica from a third sample is interpreted to indicate a Carboniferous detrital age. Based on their overall similarities in lithology, geochemistry, metamorphic minerals, metamorphic age, and structure, the metasedimentary rocks are interpreted to represent part of a single terrane, and the apparent age of the metamorphic fabric suggests that they may be equivalent to the
Preliminary results of the High Energetic Particle Package on‐board the China Seismo‐Electromagnetic Satellite

The high energetic particle package (HEPP) on‐board the China Seismo‐Electromagnetic Satellite (CSES) was launched on February 2, 2018. This package includes three independent detectors: HEPP‐H, HEPP‐L, and HEPP‐X. HEPP‐H and HEPP‐L can detect energetic electrons from 100 keV to approximately 50 MeV and protons from 2 MeV to approximately 200 MeV. HEPP‐X can measure solar X‐rays in the energy range from 1 keV to approximately 20 keV. The objective of the HEPP payload was to provide a survey of energetic particles with high energy, pitch angle, and time resolutions in order to gain new insight into the space radiation environments of the near‐Earth system. Particularly, the HEPP can provide new measurements of the magnetic storm related precipitation of electrons in the slot region, and the dynamics of radiation belts. In this paper, the HEPP scientific data sets are described and initial results are provided. The scientific data can show variations in the flux of energetic particles during magnetic storms.