Miracle-dz/UniFAR-FTUs huggingface dataset:
Spanish Pre-trained BERT Model and Evaluation Data

The Spanish language is one of the top 5 spoken languages in the world. Nevertheless, finding resources to train or evaluate Spanish language models is not an easy task. In this paper we help bridge this gap by presenting a BERT-based language model pre-trained exclusively on Spanish data. As a second contribution, we also compiled several tasks specifically for the Spanish language in a single repository much in the spirit of the GLUE benchmark. By fine-tuning our pre-trained Spanish model, we obtain better results compared to other BERT-based models pre-trained on multilingual corpora for most of the tasks, even achieving a new state-of-the-art on some of them. We have publicly released our model, the pre-training data, and the compilation of the Spanish benchmarks.
Access to Health Care for Transgender and Gender-Diverse Adults in Urban and Rural Areas in the United States

The objective of this study is to examine access to care based on gender identity in urban and rural areas, focusing on transgender and gender diverse (TGD) populations. Data on TGD (n = 1,678) and cisgender adults (n = 403,414) from the 2019 to 2020 Behavioral Risk Factor Surveillance System were used. Outcome measures were four barriers to care. We conducted bivariate and multivariable logistic regressions to assess associations between access, rurality, and gender identity. Bivariate results show that TGD adults were significantly more likely to experience three barriers to care. In multivariable models, TGD adults were more likely to delay care due to cost in the full sample (adjusted odds ratio [AOR]: 2.00, p < .001), rural subsample (AOR: 2.14, p < .01), and urban subsample (AOR: 1.97, p < .01). This study revealed greater barriers to care for TGD adults, with the most frequent barriers found among rural TGD adults. Increased provider awareness and structural policy changes are needed to achieve health equity for rural TGD populations.
A cosmic string solution to the radio synchrotron background

We investigate the low-frequency spectral emission from a network of superconducting cosmic string loops in hopes of explaining the observed radio synchrotron background. After considering constraints from a variety of astrophysical and cosmological measurements, we identify a best-fit solution with string tension $G\mu \simeq 6.5 \times 10^{-12}$ and current $\mathcal{I} \simeq 2.5 \times 10^6$ GeV. This model yields a convincing fit to the data and may be testable in the near future by spectral distortion (TMS, BISOU) and 21 cm experiments (HERA, SKA, REACH). We also find that soft photon heating protects us against current constraints from global $21$ cm experiments.
PERCEPCIONES Y CONOCIMIENTO POPULAR SOBRE COCODRILOS (CROCODYLUS ACUTUS) EN LAS ZONAS ALEDAÑAS AL RÍO TEMPISQUE, COSTA RICA

The study was conducted in the communities of Rosario, Puerto Humo, Pozo de Agua and Corral de Piedra, adjacent to the western margin of Tempisque river, in order to determine what is the popular perception and knowledge of the inhabitants of these four villages with respect to the presence of crocodiles (C. acutus). 33 surveys were conducted between January and February 2010. The interviewees responded that crocodiles feed on fish (87,87%) and small mammals (72,7%), 81,8% do not know how is the courtship in this species; 57,5% do not know when is their reproductive time. They believe nests are in caves (39,3%), out of water (48,5%) or that are holes (39,3%). The residents of these villages know that the river has crocodiles (75,75%), believe that this population has increased in recent years (93,9%). They also believe that crocodiles are dangerous and a threat to people (87,9%) and that species is not considered endangered (87,9%). In turn, they think that a crocodile can attack anytime and attacks have remained the same for several years (51,5%). They propose that attacks on humans have occurred because they invade the habitat of the animal (48,5%). As a conclusion, the author proposes a process of continuing education in the communities that share ecosystems with wildlife, as this knowledge will be key to their overall development and of the species that coexist with them.
Effects of pre-sleep protein supplementation on plasma markers of muscle damage and inflammatory cytokines resulting from sprint interval training in trained swimmers

ABSTRACT Background Pre-sleep protein has been shown to improve muscle recovery overnight following exercise-induced muscle damage. Whether such an approach affects recovery from sprint interval training (SIT) has yet to be elucidated. This study examined the effects of protein supplementation every night before sleep on early (45 min post-SIT) and late (24 and 48 h after SIT) responses of creatine kinase (CK) and inflammatory cytokines, including interleukin-6 and 10 (IL-6 and IL-10) and tumor necrosis factor-alpha (TNFα). Methods Twenty trained swimmers underwent a 2-week in-water swimming SIT (two sets of 12 × 50-m all-out swims, interspersed by 1:1 recovery between each sprint and 3 min of rest between sets) and were randomized to two intervention groups receiving either 0.5 g kg−1 day−1 protein beverage (PRO) or the same amount of carbohydrate (CHO) preceding going to bed every night. For initial and final training sessions, CK and cytokine responses were analyzed at different time points, including resting, immediately after completion, 45 min post-SIT, and 24 and 48 h after SIT. Results CK concentrations elevated from resting point to 24 and 48 h post-SIT for both PRO and CHO groups (p < 0.05). In both training groups, the peak levels of IL-6 and 10 were observed 45 min post-SIT on both occasions. TNFα levels significantly elevated from rest to immediately after SIT (p < 0.001) and returned to values equivalent to the baseline afterward in both groups and on both occasions. In both groups, swimming SIT also switched the cytokine response 48 hours after exercise to an anti-inflammatory status by decreasing the ratio of IL-6 to IL-10 (p < 0.04) in the last training session. Conclusions Pre-sleep protein ingestion failed to ameliorate blood markers of muscle damage. The late anti-inflammatory profile of cytokines and exercise-induced muscle damage improved after two weeks of swimming SIT with either protein or carbohydrate ingestion before sleep.
Telomere Shortening of Barrett’s Esophagus and Esophageal Adenocarcinoma in Japanese Patients

Abstract Telomere shortening is deeply involved in many types of cancer. Telomere length of esophageal adenocarcinoma (EAC) and Barrett’s esophagus (BE) was examined in Japanese patients. Among BE from cancer free patients (Cancer free), BE from patients with EAC (Adjacent) and EAC tissue (Cancer), Cancer free group presented the longest telomeres, while Cancer group presented the shortest telomeres and Adjacent group presented intermediate telomeres. Direction of endoscopic biopsy, 2 o‘clock direction was also significantly associated with shorter telomere length in non-neoplastic BE (p = 0.027). Shortened telomere highlighted the impact of this molecular change in early carcinogenesis in EAC.
Distribution-Free Consistency Results in Nonparametric Discrimination and Regression Function Estimation

first proposed by Watson (1964) and Nadaraya (1964) . In (1) k is a nonnegative function on R" and {h} n is a sequence of positive numbers . The pointwise consistency of (1) is discussed by Watson (1964), Nadaraya (1964, 1965), Rosenblatt (1969), Schuster (1972), Greblicki (1974) and Noda (1976) . The uniform consistency is treated in the papers by Nadaraya (1965, 1970), Greblicki (1974) and Devroye (1978a) .
Extractable information capacity in sequential measurements metrology

The conventional formulation of quantum sensing is based on the assumption that the probe is reset to its initial state after each measurement. In a very distinct approach, one can also pursue a sequential measurement scheme in which time-consuming resetting is avoided. In this situation, every measurement outcome effectively comes from a different probe, yet correlated with other data samples. Finding a proper description for the precision of sequential measurement sensing is very challenging as it requires the analysis of long sequences with exponentially large outcomes. Here, we develop a recursive formula and an efficient Monte-Carlo approach to calculate the Fisher information, as a figure of merit for sensing precision, for arbitrary lengths of sequential measurements. Our results show that Fisher information initially scales non-linearly with the number of measurements and then asymptotically saturates to linear scaling. Such transition, which fundamentally constrains the extractable information about the parameter of interest, is directly linked to the finite memory of the probe when undergoes multiple sequential measurements. Based on these, we establish a figure of merit to determine the optimal measurement sequence length and exemplify our results in three different physical systems.
NeRFs: The Search for the Best 3D Representation

Neural Radiance Fields or NeRFs have become the representation of choice for problems in view synthesis or image-based rendering, as well as in many other applications across computer graphics and vision, and beyond. At their core, NeRFs describe a new representation of 3D scenes or 3D geometry. Instead of meshes, disparity maps, multiplane images or even voxel grids, they represent the scene as a continuous volume, with volumetric parameters like view-dependent radiance and volume density obtained by querying a neural network. The NeRF representation has now been widely used, with thousands of papers extending or building on it every year, multiple authors and websites providing overviews and surveys, and numerous industrial applications and startup companies. In this article, we briefly review the NeRF representation, and describe the three decades-long quest to find the best 3D representation for view synthesis and related problems, culminating in the NeRF papers. We then describe new developments in terms of NeRF representations and make some observations and insights regarding the future of 3D representations.
Empathy deficits, callous‐unemotional traits and structural underpinnings in autism spectrum disorder and conduct disorder youth

Distinct empathy deficits are often described in patients with conduct disorder (CD) and autism spectrum disorder (ASD) yet their neural underpinnings and the influence of comorbid Callous‐Unemotional (CU) traits are unclear. This study compares the cognitive (CE) and affective empathy (AE) abilities of youth with CD and ASD, their potential neuroanatomical correlates, and the influence of CU traits on empathy. Adolescents and parents/caregivers completed empathy questionnaires (N = 148 adolescents, mean age = 15.16 years) and T1 weighted images were obtained from a subsample (N = 130). Group differences in empathy and the influence of CU traits were investigated using Bayesian analyses and Voxel‐Based Morphometry with Threshold‐Free Cluster Enhancement focusing on regions involved in AE (insula, amygdala, inferior frontal gyrus and cingulate cortex) and CE processes (ventromedial prefrontal cortex, temporoparietal junction, superior temporal gyrus, and precuneus). The ASD group showed lower parent‐reported AE and CE scores and lower self‐reported CE scores while the CD group showed lower parent‐reported CE scores than controls. When accounting for the influence of CU traits no AE deficits in ASD and CE deficits in CD were found, but CE deficits in ASD remained. Across all participants, CU traits were negatively associated with gray matter volumes in anterior cingulate which extends into the mid cingulate, ventromedial prefrontal cortex, and precuneus. Thus, although co‐occurring CU traits have been linked to global empathy deficits in reports and underlying brain structures, its influence on empathy aspects might be disorder‐specific. Investigating the subdimensions of empathy may therefore help to identify disorder‐specific empathy deficits.
Dynamic passive pressure on abutments and pile caps.

This study investigated the lateral load response of a full-scale pile cap with nine different backfill conditions, more specifically being: 1) no backfill present (baseline response), 2) densely compacted clean sand, 3) loosely compacted clean sand, 4) densely compacted fine gravel, 5) loosely compacted fine gravel, 6) densely compacted coarse gravel, 7) loosely compacted coarse gravel, 8) a 3-ft wide densely compacted fine gravel zone with loosely compacted clean sand backfill, and 9) a 6-ft wide densely compacted fine gravel zone with loosely compacted clean sand backfill. The pile cap was loaded using a combination of hydraulic load actuators and an eccentric mass shaker. The actuators were used to slowly push (statically load) the pile cap to incrementally larger target displacement levels. At each displacement level, the actuators were used to cyclically displace the pile cap a small distance, and the shaker was used to apply a dynamic loading on top of the static holding force from the actuators. Hence, the results presented in this report address static, cyclic, and dynamic loadings. The results of this study include horizontal load versus displacement relationships for the pile cap with differing backfill conditions and earth pressure distributions along the pile cap face. The results also include comparisons between measured and theoretically-based or calculated values. Additional results include descriptions of vertical displacement, horizontal displacement and cracking of the backfill. The stiffness and damping for the pile cap with the different backfill conditions were also determined.
Predicting Relative Populations of Protein Conformations without a Physics Engine Using AlphaFold 2

This paper presents a novel approach for predicting the relative populations of protein conformations using AlphaFold 2, an AI-powered method that has revolutionized biology by enabling the accurate prediction of protein structures. While AlphaFold 2 has shown exceptional accuracy and speed, it is designed to predict proteins’ single ground state conformations and is limited in its ability to predict fold switching and the effects of mutations on conformational landscapes. Here, we demonstrate how AlphaFold 2 can directly predict the relative populations of different conformations of proteins and even accurately predict changes in those populations induced by mutations by subsampling multiple sequence alignments. We tested our method against NMR experiments on two proteins with drastically different amounts of available sequence data, Abl1 kinase and the granulocyte-macrophage colony-stimulating factor, and predicted their relative state populations with accuracies in excess of 80%. Our method offers a fast and cost-effective way to predict protein conformations and their relative populations at even single point mutation resolution, making it a useful tool for pharmacology, analyzing NMR data, and studying the effects of evolution.
Role of tixagevimab‐cilgavimab in preventing SARS‐CoV‐2 in hematopoietic stem cell transplant and chimeric antigen receptor T‐cell therapy recipients

Patients who have undergone hematopoietic stem cell transplantation (HSCT) or chimeric antigen receptor T ‐ cell therapy (CAR T) and subsequently become infected with severe acute respiratory syndrome coronavirus 2 (SARS ‐ CoV ‐ 2) have increased morbidity and mortality compared with the general population. 1 In 2020, an analysis by the American Society of Hematology Consortium revealed a 19% coronavirus 2019 (COVID ‐ 19) ‐ related mortality within 30 days of infection in patients who had received cellular therapy in the previous year. 2 This is attributed to severe immunosuppression, conditioning, or lymphodepleting chemotherapy, and myelosuppression. Patients with hematologic malignancies are also believed to have lower B ‐ and T ‐ cell immunogenicity partly due to lymphodepleting therapy, failing to develop adequate anti ‐ SARS ‐ CoV ‐ 2 spike antibodies despite vaccination. 3
The impact of COVID-19 on acute psychiatric admissions for first and repeated episode psychosis

Background: There is limited evidence of the longer-term impact of the COVID-19 pandemic on acute admissions for psychosis in the UK. Aims: We examined the impact of COVID-19 on rates of admissions for first and repeated episode psychosis, and changes in patient profile and seasonal patterns, over a period of 12 months. Method: We conducted a retrospective case note review of all patients admitted with a primary psychosis (F20-29 ICD 10 diagnosis) to an NHS psychiatric inpatient unit. We compared the 12 months pre-COVID-19 period between 1 March 2019 and 28 February 2020, and the 12 months post-COVID-19 period between 1 March 2020 and 28 February 2021. Results: The results showed increase rates of admissions post-COVID-19 in both first and repeated episode psychosis, the patient profile had more females and older age in the repeated episode group, with increased employment rates. Combined group data for both pre- and post-COVID-19 periods showed an increased trend in spring and summer admissions, and even though not statistically significant, more pronounced post-COVID-19. Conclusions: Our findings highlight the effect of the COVID-19 pandemic on acute psychosis admissions over a 12-month period. The results provide evidence for the ‘stress-pathogenesis’ in the context of genetic vulnerability in psychosis. Preventative strategies in the context of the ‘stress-pathogenesis model’, improved access to and responsiveness within NHS transformation efforts needs to be adjusted to fit local need and environmental changes.
hGRAD – a versatile ʹone-fits-allʹ system for the acute depletion of RNA binding proteins in nuclear condensates

Nuclear RNA binding proteins (RBPs) are difficult to study because they often belong to large protein families and form extensive networks of auto- and cross- regulation. They are highly abundant and often localize to condensates with a slow turnover, requiring long depletion times or knockouts that cannot distinguish between direct and indirect or compensatory effects. Here, we developed a system that is optimized for the rapid degradation of nuclear RBPs, called hGRAD. It comes as a ʹone-fits-allʹ plasmid, and integration into any cell line that expresses endogenously GFP-tagged proteins allows an inducible, rapid and complete knockdown. We show that the nuclear RBPs SRSF3, SRSF5, SRRM2 and NONO are completely cleared from nuclear speckles and paraspeckles within two hours. hGRAD works in various cell types, is more efficient than other methods and does not require the expression of exogenous ubiquitin ligases. Combining SRSF5 hGRAD degradation with Nascent-seq uncovered highly dynamic transient transcript changes, compensatory mechanisms and that SRSF5 promotes transcript stability.
EDI: ESKF-based Disjoint Initialization for Visual-Inertial SLAM Systems

Visual-inertial initialization can be classified into joint and disjoint approaches. Joint approaches tackle both the visual and the inertial parameters together by aligning observations from feature-bearing points based on IMU integration then use a closed-form solution with visual and acceleration observations to find initial velocity and gravity. In contrast, disjoint approaches independently solve the Structure from Motion (SFM) problem and determine inertial parameters from up-to-scale camera poses obtained from pure monocular SLAM. However, previous disjoint methods have limitations, like assuming negligible acceleration bias impact or accurate rotation estimation by pure monocular SLAM. To address these issues, we propose EDI, a novel approach for fast, accurate, and robust visual-inertial initialization. Our method incorporates an Error-state Kalman Filter (ESKF) to estimate gyroscope bias and correct rotation estimates from monocular SLAM, overcoming dependence on pure monocular SLAM for rotation estimation. To estimate the scale factor without prior information, we offer a closed-form solution for initial velocity, scale, gravity, and acceleration bias estimation. To address gravity and acceleration bias coupling, we introduce weights in the linear least-squares equations, ensuring acceleration bias observability and handling outliers. Extensive evaluation on the EuRoC dataset shows that our method achieves an average scale error of 5.8% in less than 3 seconds, outperforming other state-of-the-art disjoint visual-inertial initialization approaches, even in challenging environments and with artificial noise corruption.
Learning from Topology: Cosmological Parameter Estimation from the Large-scale Structure

The topology of the large-scale structure of the universe contains valuable information on the underlying cosmological parameters. While persistent homology can extract this topological information, the optimal method for parameter estimation from the tool remains an open question. To address this, we propose a neural network model to map persistence images to cosmological parameters. Through a parameter recovery test, we demonstrate that our model makes accurate and precise estimates, considerably outperforming conventional Bayesian inference approaches.
Magnetic Field Draping in Induced Magnetospheres: Evidence From the MAVEN Mission to Mars

The Mars Atmosphere and Volatile EvolutioN (MAVEN) mission has been orbiting Mars since 2014 and now has over 10,000 orbits which we use to characterize Mars' dynamic space environment. Through global field line tracing with MAVEN magnetic field data we find an altitude dependent draping morphology that differs from expectations of induced magnetospheres in the vertical ( Z^ $\hat{Z}$ Mars Sun‐state, MSO) direction. We quantify this difference from the classical picture of induced magnetospheres with a Bayesian multiple linear regression model to predict the draped field as a function of the upstream interplanetary magnetic field (IMF), remanent crustal fields, and a previously underestimated induced effect. From our model we conclude that unexpected twists in high altitude dayside draping (>800 km) are a result of the IMF component in the ±X^ $\pm \hat{X}$ MSO direction. We propose that this is a natural outcome of current theories of induced magnetospheres but has been underestimated due to approximations of the IMF as solely ±Y^ $\pm \hat{Y}$ directed. We additionally estimate that distortions in low altitude (<800 km) dayside draping along Z^ $\hat{Z}$ are directly related to remanent crustal fields. We show dayside draping traces down tail and previously reported inner magnetotail twists are likely caused by the crustal field of Mars, while the outer tail morphology is governed by an induced response to the IMF direction. We conclude with an updated understanding of induced magnetospheres which details dayside draping for multiple directions of the incoming IMF and discuss the repercussions of this draping for magnetotail morphology.