Miracle-dz/UniFAR-FTUs huggingface dataset:
Perception and knowledge of child abuse among dental students in Paraná, Brazil

Child abuse (CA) has a negative impact on a child’s development, and health care professionals have a legal obligation to report suspected cases. Therefore, knowledge regarding the diagnosis of CA and the appropriate professional’s actions to address CA is necessary. The aim of this cross-sectional study was to evaluate the knowledge and perceptions of dental students in Paraná, Brazil, regarding CA. A semi-structured questionnaire addressing participants’ demographic characteristics, perceptions, and knowledge about CA was administered using Google Forms. Knowledge score was calculated as the sum of correct responses, ranging from 0 to 14 points. Data were analyzed using descriptive and inferential statistical methods. Knowledge score was analyzed in terms of participant characteristics using the Mann Whitney U test or Spearman correlation test; the level of significance was 5%. A total of 146 dental students (30.41% response rate) participated in the study. The median knowledge score was 10 (range, 6–14). Of these dental students, 98.6% reported knowing the definition of CA, and 54.3% (n=75) reported having received information about the topic in classes. Regarding professional’s actions, 49% (n=71) reported not knowing what measures to take in a suspected case of CA. A significant positive correlation was observed between knowledge scores and curricular period. It was concluded that students had adequate knowledge to diagnose CA; however, aspects related to appropriate professional’s actions remain unclear. Furthermore, knowledge scores were higher in the advanced stages of the dental curricula. Regarding perceptions, dental students appeared to be insecure with taking action in a case of suspected CA. Descriptors: Child abuse. Education, Dental. Diagnostic. Perception and knowledge of child abuse among dental students in Paraná, Brazil Revista da ABENO • 21(1):1254, 2021 – DOI: 10.30979/revabeno.v21i1. 1254 2
Efectos de la orientación de la atención endógena y exógena en la memoria de contexto

The aim of this study was to determine the effects of endogenous and exogenous orienting of attention on episodic memory. Thirty healthy participants performed a cueing attention paradigm during encoding, in which images of common objects were presented either to the left or to the right of the center of the screen. Before the presentation of each image, three types of symbolic cues were displayed to indicate the location in which the stimuli would appear: valid cues to elicit endogenous orientation, invalid cues to prompt exogenous orientation and neutral or uncued trials. The participants’ task was to discriminate whether the images were symmetrical or not while fixating on the center of the screen to assure the manifestation of only covert attention mechanisms. Covert attention refers to the ability to orient attention by means of central control mechanisms alone, without head and eye movements. Trials with eye movements were excluded after inspection of eye-tracker recordings that were conducted throughout the task. During retrieval, participants conducted a source memory task in which they indicated the location where the images were presented during encoding. Memory for spatial context was superior during endogenous orientation than during exogenous orientation, whereas exogenous orientation was associated with a greater number of missed responses compared to the neutral trials. The formation of episodic memory representations with contextual details benefits from endogenous attention.
Cervical Pap smear study and its utility in cancer screening in patients attending out-patient department in a tertiary care hospital

Background: Cervical cancer is one of the major causes of mortality among women worldwide. By simple pap screening test cervical cancer and its precursor lesions can be detected and treated early. The aim of the study was to determine and analyze Pap smear reports from women presenting with various gynaecological indications in a tertiary care hospital.Methods: This retrospective study was conducted in the department of obstetrics and gynaecology at Rama Medical College Hospital and Research Centre, Hapur over a period of 6 months. Patients with various complaints between ages 21 to 70 years were screened during August 2020 to January 2021 by taking Pap smear using Ayres spatula. Total 330 patients were studied. Slides were reported according to the 2014 Bethesda system.Results: Maximum number of cases were in the age group 31-40 years constituting 32.72% of the total cases followed by age group 41-50 years. Vaginal discharge was the commonest chief complaint seen in 32.12% cases followed by menorrhagia. Maximum number of cases reported as non-specific inflammatory smears (64.54%). Among epithelial cell abnormalities incidence of LSIL was 2.42% followed by ASCUS (1.82%). Conclusions: Pap smear testing is an economical, non-invasive and simple OPD procedure to detect potentially precancerous and cancerous lesions of cervix. It should be established as a routine screening procedure to reduce the treatment burden, morbidity and mortality.
Effects of rumen-protected arginine supplementation and arginine-HCl injection on site and extent of digestion and small intestinal amino acid disappearance in forage-fed steers

Abstract Four ruminally and intestinally cannulated steers were used in a 4 × 4 Latin square to evaluate effects of rumen-protected Arg supplementation or intravenous Arg injection on small intestinal delivery of AA, site and extent of digestion, and ruminal fermentation. Steers were fed grass hay (7.2% CP, 67.6% NDF, 0.29% Arg) for ad libitum intake with no additional Arg (CON), 54-mg L-Arg/kg BW injected intravenously (Arg-INJ), 180-mg rumen-protected L-Arg/kg BW daily (Arg-RP180), or 360-mg rumen-protected L-Arg/kg BW daily (Arg-RP360). Half of each treatment dose was administered twice daily. Each period had a 7-d washout of hay only followed by a 14-d treatment and collection period. Ruminal disappearance (%) of Arg was greater (P < 0.001) for both Arg-RP treatments than CON and Arg-INJ, although the amount of Arg disappearing was greatest in Arg-RP360, followed by Arg-RP180, and least in CON and Arg-INJ (P < 0.001). Duodenal flow and small intestinal disappearance (g/d) of Arg was greatest in Arg-RP360, followed by Arg-RP180, and least in CON and Arg-INJ (P < 0.004). Ileal flow of Arg was greatest in Arg-RP360, intermediate in Arg-RP180, and least in CON (P = 0.01) because the proportional small intestinal disappearance of Arg was not different (P = 0.96). Steers fed Arg-RP360 had greater (P = 0.01) ileal flow of Orn and tended to have greater (P = 0.09) ileal flow of Glu than all other treatments. There were no differences in hay or total DMI, microbial efficiency, or OM, NDF, or ADF digestibility (P ≥ 0.10). Total N intake and duodenal N flow were greater in Arg-RP360 than all other treatments (P ≤ 0.02). Total tract N digestibility was greatest in Arg-RP360, followed by Arg-RP180, and least in CON and Arg-INJ (P = 0.003). Ruminal ammonia was greater (P = 0.004) in Arg-RP360 compared with CON and Arg-INJ and greater (P = 0.06) in Arg-RP180 than CON. There was no effect of treatment (P ≥ 0.37) on total VFA, acetate, propionate, or butyrate concentrations. Results indicate that feeding rumen-protected Arg increases small intestinal Arg flow with minimal effects on ruminal fermentation and total tract digestibility of OM and fiber.
Describing W2000 Using RDF When the Meaning Is Essential

A powerful methodology for the conceptual modeling of hypermedia and Web applications is a must for designers. In addition to the advantages of easily and fully expressing an idea and of discussing it with the customer, to better understand what he needs, a conceptual design helps the designers managing the complexity and letting them completely describe how the application will be and how it will appear to different users and on different devices. Every schema they produce will be precious for people who will develop the application, using any language or in any environment, for anyone who will work on it. But, in order to get the best result and to be sure that every effort will give what the designers expect, we must be sure that the model is fully understood by everyone. The meaning of each schema must be absolutely clear. This is even a bigger problem when the output of the modeling activity is used to feed a prototyping system or a development framework: the meaning must not be lost in each step. That’s why we use RDF as a common language to describe every piece of the application. The W2000 model itself has been translated in RDF schemas with all the stereotypes fully described and ready to be directly referenced while building an application. We are persuaded that our RDF meta-description of W2000 will let us completely take advantage of the object oriented nature of the model itself and that this one can be the right choice, in this phase of W2000’s research, in which we plan to get the methodology closer to a development-oriented point of view.
Use of Red Cactus Pear (Opuntia ficus-indica) Encapsulated Powder to Pigment Extruded Cereal

Encapsulated powder of the red cactus pear is a potential natural dye for the food industry and a known antioxidant. Although the use of this powder is possible, it is not clear how it alters food properties, thus ensuing commercial acceptability. The aim of this study was to evaluate the effect of encapsulated powder of the red cactus pear on the physicochemical properties of extruded cereals. The powder was mixed (2.5, 5.0, and 7.5% w/w) with maize grits and extruded (mix moisture 22%, temperature 100°C, and screw speed 325 rpm). The physical, chemical, and sensory characteristics of the extruded cereal were evaluated; extruded cereal without encapsulated powder was used as a control. All cereal extrudates pigmented with the encapsulated powder showed statistically significant differences in expansion, water absorption, color, density, and texture compared to the control. The encapsulated powder had a positive effect on expansion and water absorption indices, as well as color parameters, but a negative effect on density and texture. Extruded cereal properties were significantly correlated. Sensorially, consumers accepted the extruded cereal with a lower red cactus pear powder content (2.5% w/w), because this presented characteristics similar to extruded cereal lacking pigment.
Are Women More Resilient? Gender Differences in the Reaction to Negative Feedback

Although the gender gap in labor markets is steadily narrowing, there is a persistent shortage of women in competitive high-ranking positions. A large body of literature suggests that gender differences in preference for and reaction to competition are potential explanations for the scarcity of women available for leadership positions. Recent studies indicate through laboratory experiments that positive feedback eliminates gender differences in competitiveness and self-confidence, whereas negative feedback and bad experiences cause women to be more likely to withdraw from competition and reduce performance. Our study reveals a new facet of this phenomenon: Women who voluntarily participate in competitive settings are more likely to return to competition after a negative experience than men. While this underscores that feedback indeed causes different reactions in men and women, it suggests that the characteristics of the feedback is decisive: Men tend to avoid competitive situations after receiving implicit negative feedback and increasingly compete after positive experiences. Women, by contrast, re-enter a competition regardless of the nature of the previous experience.
Locating Ruelle–Pollicott resonances

We study the spectrum of transfer operators associated to various dynamical systems. Our aim is to obtain precise information on the discrete spectrum. To this end we propose a unitary approach. We consider various settings where new information can be obtained following different branches along the proposed path. These settings include affine expanding Markov maps, uniformly expanding Markov maps, non-uniformly expanding or simply monotone maps, hyperbolic diffeomorphisms. We believe this approach could be greatly generalised.
Treatment Effects in Market Equilibrium

When randomized trials are run in a marketplace equilibriated by prices, interference arises. To analyze this, we build a stochastic model of treatment effects in equilibrium. We characterize the average direct (ADE) and indirect treatment effect (AIE) asymptotically. A standard RCT can consistently estimate the ADE, but confidence intervals and AIE estimation require price elasticity estimates, which we provide using a novel experimental design. We define heterogeneous treatment effects and derive an optimal targeting rule that meets an equilibrium stability condition. We illustrate our results using a freelance labor market simulation and data from a cash transfer experiment.
Broccoli: Bug localization with the help of text search engines

Bug localization is a tedious activity in the bug fixing process in which a software developer tries to locate bugs in the source code described in a bug report. Since this process is time-consuming and requires additional knowledge about the software project, information retrieval techniques can aid the bug localization process. In this paper, we investigate if normal text search engines can improve existing bug localization approaches. In a case study, we evaluate the performance of our search engine approach Broccoli against seven state-of-the-art bug localization algorithms on 82 open source projects in two data sets. Our results show that including a search engine can increase the performance of the bug localization and that it is a useful extension to existing approaches. As part of our analysis we also exposed a flaw in a commonly used benchmark strategy, i.e., that files of a single release are considered. To increase the number of detectable files, we mitigate this flaw by considering the state of the software repository at the time of the bug report. Our results show that using single releases may lead to an underestimation of the the prediction performance.
Weakly-Supervised Monocular Depth Estimationwith Resolution-Mismatched Data

Depth estimation from a single image is an active research topic in computer vision. The most accurate approaches are based on fully supervised learning models, which rely on a large amount of dense and high-resolution (HR) ground-truth depth maps. However, in practice, color images are usually captured with much higher resolution than depth maps, leading to the resolution-mismatched effect. In this paper, we propose a novel weakly-supervised framework to train a monocular depth estimation network to generate HR depth maps with resolution-mismatched supervision, i.e., the inputs are HR color images and the ground-truth are low-resolution (LR) depth maps. The proposed weakly supervised framework is composed of a sharing weight monocular depth estimation network and a depth reconstruction network for distillation. Specifically, for the monocular depth estimation network the input color image is first downsampled to obtain its LR version with the same resolution as the ground-truth depth. Then, both HR and LR color images are fed into the proposed monocular depth estimation network to obtain the corresponding estimated depth maps. We introduce three losses to train the network: 1) reconstruction loss between the estimated LR depth and the ground-truth LR depth; 2) reconstruction loss between the downsampled estimated HR depth and the ground-truth LR depth; 3) consistency loss between the estimated LR depth and the downsampled estimated HR depth. In addition, we design a depth reconstruction network from depth to depth. Through distillation loss, features between two networks maintain the structural consistency in affinity space, and finally improving the estimation network performance. Experimental results demonstrate that our method achieves superior performance than unsupervised and semi-supervised learning based schemes, and is competitive or even better compared to supervised ones.
Revisiting the Uniform Information Density Hypothesis

The uniform information density (UID) hypothesis posits a preference among language users for utterances structured such that information is distributed uniformly across a signal. While its implications on language production have been well explored, the hypothesis potentially makes predictions about language comprehension and linguistic acceptability as well. Further, it is unclear how uniformity in a linguistic signal—or lack thereof—should be measured, and over which linguistic unit, e.g., the sentence or language level, this uniformity should hold. Here we investigate these facets of the UID hypothesis using reading time and acceptability data. While our reading time results are generally consistent with previous work, they are also consistent with a weakly super-linear effect of surprisal, which would be compatible with UID’s predictions. For acceptability judgments, we find clearer evidence that non-uniformity in information density is predictive of lower acceptability. We then explore multiple operationalizations of UID, motivated by different interpretations of the original hypothesis, and analyze the scope over which the pressure towards uniformity is exerted. The explanatory power of a subset of the proposed operationalizations suggests that the strongest trend may be a regression towards a mean surprisal across the language, rather than the phrase, sentence, or document—a finding that supports a typical interpretation of UID, namely that it is the byproduct of language users maximizing the use of a (hypothetical) communication channel.
Revised phase diagram of a high-Tc cuprate superconductor revealed by anisotropic transport measurements

Keiichi Harada,1 Yuki Teramoto,1 Tomohiro Usui,1 Kenji Itaka,2 Takenori Fujii,3 Takashi Noji,4 Haruka Taniguchi,5 Michiaki Matsukawa,5 Hajime Ishikawa,6 Koichi Kindo,6 Daniel S. Dessau,7 and Takao Watanabe1, ∗ 1Graduate School of Science and Technology, Hirosaki University, Hirosaki, Aomori, 036-8561 Japan 2Institute of Regional Innovation, Hirosaki University, Aomori, Aomori, 036-8561 Japan 3Cryogenic Research Center, University of Tokyo, Bunkyo, Tokyo 113-0032, Japan 4Graduate School of Engineering, Tohoku University, Sendai 980-8579, Japan 5Graduate School of Engineering, Iwate University, Morioka 020-8551, Japan 6Institute for Solid State Physics, University of Tokyo, Kashiwa, Chiba 277-8581, Japan 7Department of Physics, University of Colorado at Boulder, Boulder, CO 80309, USA (Dated: December 30, 2021)
Rethinking Crowd Sourcing for Semantic Similarity

Estimation of semantic similarity is crucial for a variety of natural language processing (NLP) tasks. In the absence of a general theory of semantic information, many papers rely on human annotators as the source of ground truth for semantic similarity estimation. This paper investigates the ambiguities inherent in crowd-sourced semantic labeling. It shows that annotators that treat semantic similarity as a binary category (two sentences are either similar or not similar and there is no middle ground) play the most important role in the labeling. The paper offers heuristics to filter out unreliable annotators and stimulates further discussions on human perception of semantic similarity.
Linear panel regressions with two-way unobserved heterogeneity

We study linear panel regression models in which the unobserved error term is an unknown smooth function of two-way unobserved fixed effects. In standard additive or interactive fixed effect models the individual specific and time specific effects are assumed to enter with a known functional form (additive or multiplicative). In this paper, we allow for this functional form to be more general and unknown. We discuss two different estimation approaches that allow consistent estimation of the regression parameters in this setting as the number of individuals and the number of time periods grow to infinity. The first approach uses the interactive fixed effect estimator in Bai (2009), which is still applicable here, as long as the number of factors in the estimation grows asymptotically. The second approach first discretizes the two-way unobserved heterogeneity (similar to what Bonhomme, Lamadon and Manresa 2021 are doing for one-way heterogeneity) and then estimates a simple linear fixed effect model with additive two-way grouped fixed effects. For both estimation methods we obtain asymptotic convergence results, perform Monte Carlo simulations, and employ the estimators in an empirical application to UK house price data.
Planar spider theorem and asymmetric Frobenius algebras

Abstract. We prove a ‘spider theorem’ for general Frobenius algebras A, where the algebra can be noncommutative and the Frobenius form can be asymmetric. In a diagrammatic notation for the product and an associated coproduct, the statement in the case of a special Frobenius algebra is that any map A⊗m → A⊗n corresponding to a connected planar diagram with m inputs and n outputs is equivalent to a m− 1-fold product followed by a n− 1fold coproduct. Examples include asymmetric special Frobenius structures on matrix algebras A =Md(k) and on group algebras kG.
When Hot Meets Cold: Post-flare Coronal Rain

Most solar flares demonstrate a prolonged, hour-long post-flare (or gradual) phase, characterized by arcade-like, post-flare loops (PFLs) visible in many extreme ultraviolet (EUV) passbands. These coronal loops are filled with hot (∼30 MK) and dense plasma that evaporated from the chromosphere during the impulsive phase of the flare, and they very gradually recover to normal coronal density and temperature conditions. During this gradual cooling down to ∼1 MK regimes, much cooler (∼0.01 MK) and denser coronal rain is frequently observed inside PFLs. Understanding PFL dynamics in this long-duration, gradual phase is crucial to the entire corona–chromosphere mass and energy cycle. Here we report a simulation in which a solar flare evolves from pre-flare, over the impulsive phase all the way into its gradual phase, which successfully reproduces post-flare coronal rain. This rain results from catastrophic cooling caused by thermal instability, and we analyze the entire mass and energy budget evolution driving this sudden condensation phenomenon. We find that the runaway cooling and rain formation also induces the appearance of dark post-flare loop systems, as observed in EUV channels. We confirm and augment earlier observational findings, suggesting that thermal conduction and radiative losses alternately dominate the cooling of PFLs.
DACT-BERT: Differentiable Adaptive Computation Time for an Efficient BERT Inference

Large-scale pre-trained language models have shown remarkable results in diverse NLP applications. However, these performance gains have been accompanied by a significant increase in computation time and model size, stressing the need to develop new or complementary strategies to increase the efficiency of these models. This paper proposes DACT-BERT, a differentiable adaptive computation time strategy for BERT-like models. DACT-BERT adds an adaptive computational mechanism to BERT’s regular processing pipeline, which controls the number of Transformer blocks that need to be executed at inference time. By doing this, the model learns to combine the most appropriate intermediate representations for the task at hand. Our experiments demonstrate that our approach, when compared to the baselines, excels on a reduced computational regime and is competitive in other less restrictive ones. Code available at https://github.com/ceyzaguirre4/dact_bert.