Miracle-dz/UniFAR-FTUs huggingface dataset:
Efeito preemptivo da morfina por via venosa na analgesia pós-operatória e na resposta ao trauma cirúrgico

JUSTIFICATIVA E OBJETIVOS: Embora os primeiros estudos sobre analgesia preemptiva tenham demonstrado que o bloqueio pre-operatorio com anestesicos locais ou a medicacao pre-anestesica com opioides sistemicos eram mais eficazes no alivio da dor pos-operatoria do que qualquer outro tratamento, o resultado de outros estudos comparando os efeitos do tratamento pre operatorio ao mesmo tratamento iniciado apos a cirurgia, produziram efeitos inconsistentes. As razoes para essa falta de consistencia nao sao claras. Sao poucos os estudos sobre a relacao entre analgesia preemptiva e o consumo de analgesicos e a resposta ao trauma cirurgico. O objetivo deste estudo foi avaliar o efeito preemptivo da morfina por via venosa preemptiva no consumo pos-operatorio de analgesicos e na resposta ao trauma cirurgico. METODO: Participaram deste estudo 60 pacientes, estado fisico ASA I ou II, com idades entre 20 e 60 anos, escalados para histerectomia abdominal total e salpingo-ooferectomia bilateral, que foram aleatoriamente distribuidos em tres grupos de 20 pacientes. Grupo I (n=20) - 0,15 mg.kg-1 de morfina apos a inducao anestesica e soro fisiologico durante o fechamento do peritonio. Grupo II (n=20) - soro fisiologico apos a inducao e 0,15 mg.kg-1 de morfina durante o fechamento do peritonio. Grupo III (n=20) soro fisiologico durante a inducao e o fechamento do peritonio. Foram medidos os niveis sanguineos de cortisol e de glicose e feita a contagem de leucocitos nos periodos pre e pos-operatorios. RESULTADOS: O consumo total de morfina pos-operatoria foi significativamente mais baixo no grupo I comparado ao grupo III (p < 0,001). Os niveis de cortisol aumentaram significativamente em todos os grupos 4 horas apos a cirurgia, quando comparados aos valores pre-operatorios (p < 0,001). Os niveis de glicose plasmatica tambem aumentaram significativamente em todos os grupos 30 minutos e 8 horas apos a cirurgia (p < 0,01). Todos os grupos apresentaram leucocitose pos-operatoria e a contagem de leucocitos foi significativamente mais alta no periodo pos-operatorio do que no pre-operatorio (p < 0,01). CONCLUSOES: Morfina preemptiva por via venosa, na dose de 0,15 mg.kg-1 diminuiu o consumo total de morfina mas nao conseguiu suprimir a resposta ao trauma cirurgico.
Risk Bounds for Quantile Trend Filtering

We study quantile trend filtering, a recently proposed method for nonparametric quantile regression, with the goal of generalizing existing risk bounds known for the usual trend filtering estimators which perform mean regression. We study both the penalized and the constrained version, of order r ≥ 1, of univariate quantile trend filtering. Our results show that both the constrained and the penalized version, of order r ≥ 1, attain the minimax rate up to log factors, when the (r - 1)th discrete derivative of the true vector of quantiles belongs to the class of bounded variation signals. Moreover, we also show that if the true vector of quantiles is a discrete spline with a few polynomial pieces then both versions attain a near parametric rate of convergence. Corresponding results for the usual trend filtering estimators are known to hold only when the errors are sub-Gaussian. In contrast, our risk bounds are shown to hold under minimal assumptions on the error variables. In particular, no moment assumptions are needed and our results hold under heavy-tailed errors. Our proof techniques are general and thus can potentially be used to study other nonparametric quantile regression methods. To illustrate this generality we also employ our proof techniques to obtain new results for multivariate quantile total variation denoising and high dimensional quantile linear regression.
Nonparametric Compositional Stochastic Optimization for Risk-Sensitive Kernel Learning

In this work, we address optimization problems where the objective function is a nonlinear function of an expected value, i.e., compositional stochastic programs. We consider the case where the decision variable is not vector-valued but instead belongs to a Reproducing Kernel Hilbert Space (RKHS), motivated by risk-aware formulations of supervised learning. We develop the first memory-efficient stochastic algorithm for this setting, which we call Compositional Online Learning with Kernels (COLK). COLK, at its core a two time-scale stochastic approximation method, addresses the facts that (i) compositions of expected value problems cannot be addressed by stochastic gradient method due to the presence of an inner expectation; and (ii) the RKHS-induced parameterization has complexity which is proportional to the iteration index which is mitigated through greedily constructed subspace projections. We provide, for the first time, a non-asymptotic tradeoff between the complexity of a function parameterization and its required convergence accuracy for both strongly convex and non-convex objectives under constant step-sizes. Experiments with risk-sensitive supervised learning demonstrate that COLK consistently converges and performs reliably even when data is full of outliers, and thus marks a step towards overfitting. Specifically, we observe a favorable tradeoff between model complexity, consistent convergence, and statistical accuracy for data associated with heavy-tailed distributions.
Optical activity in weakly coupled nonorods.

We introduce a matrix method and we derive a formula for phase retardation effects in plasmonic systems. We analyze the circular dichroic response (CD) of two orthogonal Au nanorods in detail and we show that, although, theoretically, circular dichroism for forward scattering is directly proportional to the dipole-dipole interaction between the particles, CD response of the system can be much greater in weak coupling due to the trade off between two different types of phases.
Domain Adaptive Knowledge Distillation for Driving Scene Semantic Segmentation

Practical autonomous driving systems face two crucial challenges: memory constraints and domain gap issues. In this paper, we present a novel approach to learn domain adaptive knowledge in models with limited memory, thus bestowing the model with the ability to deal with these issues in a comprehensive manner. We term this as “Domain Adaptive Knowledge Distillation ” and address the same in the context of unsupervised domain-adaptive semantic segmentation by proposing a multi-level distillation strategy to effectively distil knowledge at different levels. Further, we introduce a novel cross entropy loss that leverages pseudo labels from the teacher. These pseudo teacher labels play a multifaceted role towards: (i) knowledge distillation from the teacher network to the student network & (ii) serving as a proxy for the ground truth for target domain images, where the problem is completely unsupervised. We introduce four paradigms for distilling domain adaptive knowledge and carry out extensive experiments and ablation studies on real-to-real as well as synthetic-to-real scenarios. Our experiments demonstrate the profound success of our proposed method.
Succeeding against the odds: An examination of familial influences on the career development of professional African American women.

In spite of racism, African American women have pursued career goals, entered the workplace, and maintained successful careers. This persistence by African American women can be connected theoretically to several phenomena-the most notable being the family experience. The purpose of this study was to describe how 14 African American women in the midpoint of their careers perceived their family's influence on their career development. Consensual qualitative research (C. E. Hill, B. J. Thompson, & E. Nutt-Williams, 1997) was used to analyze the interview responses of these women. The most salient variables related to career development included family emphasis on education, relationships with family members, and family's social and economic resources. Other variables that shaped the career development of this sample included family gender role socialization and values toward work.
Regional hemostatic status and blood requirements after total knee arthroplasty with and without tranexamic acid or aprotinin.

Antifibrinolytics seem to reduce postoperative blood loss after total knee arthroplasty. Few studies have shown the impact of these drugs on the mechanisms of coagulation. The purpose of this study was to examine coagulation/fibrinolysis variables as well as blood loss after total knee arthroplasty with and without antifibrinolytics in the operated limb on a regional level. Thirty-six patients were randomized into one of three groups to receive aprotinin, tranexamic acid, or no medication. We took blood samples of the femoral vein before deflating the tourniquet and after 5, 10, 30, 60, 120 min and on the first postoperative day. The implantation of a knee prosthesis in artificial ischemia caused a significant activation of coagulation and fibrinolysis in the regional circulation. Tranexamic acid and aprotinin did not cause a significant modulation of fibrinolysis variables or a significant reduction of postoperative bleeding and transfusion requirements. One of the differences in comparison to other studies was the decreased total blood loss. The use of bone cement as well as surgical hemostasis before wound closure may be regarded as reasons for this. Therefore, primarily these methods should be used because there is no increased risk of adverse drug effects.
Data-model comparison of the Younger Dryas event: discussion.

Rutter et al. (2000) present an interesting overview of global evidence for the Younger Dryas event (YD, ∼11 500 – 13 000 calendar years ago) as inferred from various kinds of proxy data. Such an overview is important for a better understanding of mechanisms behind rapid climate change. Moreover, Rutter et al. make an effort to compare these data with a coupled atmosphere–ocean model experiment on the YD performed by Fanning and Weaver (1997). In this experiment the production of North Atlantic Deep Water (NADW) collapses after the release of a large amount of fresh water in the North Atlantic. Based on the data-model comparison, Rutter et al. conclude that “the model results reveal a global pattern and regional magnitude which generally agree with temperature changes interpreted from paleoclimatic reconstructions” (Abstract, p. 811). This implies that the YD temperature change is …
Foam extrusion of thermoplastic polyurethanes (TPU) using CO2 as a blowing agent

The foaming of thermoplastic poluyrethanes (TPU) with CO 2 as a blowing agent reduces material input for existing applications and also leads to improced material properties for new applications. Therefore the correlations between process parameters and the resulting foam quality are examined in this paper. The solubility behaviour of CO 2 in the polymer melt is analysed by means of a high pressure sorption balance. For the foam extrusion of the temperature and shear sensitive polymer, the influence of the screw geometry on the extrusion process is examined. First extrusion experiments have resulted in TPU foams with a density below O,4 g/cm 3 .
A Novel Sentiment Analysis Engine for Preliminary Depression Status Estimation on Social Media

Text sentiment analysis for preliminary depression status estimation of users on social media is a widely exercised and feasible method, However, the immense variety of users accessing the social media websites and their ample mix of vocabularies makes it difficult for commonly applied deep learning-based classifiers to perform. To add to the situation, the lack of adaptability of traditional supervised machine learning could hurt at many levels. We propose a cloud-based smartphone application, with a deep learning-based backend to primarily perform depression detection on Twitter social media. The backend model consists of a RoBERTa based siamese sentence classifier that compares a given tweet (Query) with a labeled set of tweets with known sentiment ( Standard Corpus ). The standard corpus is varied over time with expert opinion so as to improve the model's reliability. A psychologist ( with the patient's permission ) could leverage the application to assess the patient's depression status prior to counseling, which provides better insight into the mental health status of a patient. In addition, to the same, the psychologist could be referred to cases of similar characteristics, which could in turn help in more effective treatment. We evaluate our backend model after fine-tuning it on a publicly available dataset. The find tuned model is made to predict depression on a large set of tweet samples with random noise factors. The model achieved pinnacle results, with a testing accuracy of 87.23% and an AUC of 0.8621.
Wetting Behavior of a Three-Phase System in Contact with a Surface

We extend the Cahn-Landau-de Gennes mean field theory of wetting in binary mixtures to understand the wetting thermodynamics of a three phase system (e.g., polymer dispersed liquid crystals or polymer-colloid mixtures) that is in contact with an external surface, which prefers one of the phases. Using a model free-energy, which has three minima in its landscape, we show that as the central minimum becomes more stable compared to the remaining ones, the bulk phase diagram encounters a triple point and then bifurcates and we observe a novel non-monotonic dependence of the surface tension as a function of the stability of the central minimum. We show that this non-monotonicity in surface tension is associated with a complete to partial wetting transition. We obtain the complete wetting phase behavior as a function of phase stability and the surface interaction parameters when the system is close to the bulk triple point. The model free-energy that we use is qualitatively similar to that of a renormalized free energy, which arises in the context of polymer-liquid crystal mixtures. Finally, we study the thermodynamics of wetting for an explicit polymer-liquid crystal mixture and show that its thermodynamics is similar to that of our model free-energy.
UVid-Net: Enhanced Semantic Segmentation of UAV Aerial Videos by Embedding Temporal Information

Semantic segmentation of aerial videos has been extensively used for decision making in monitoring environmental changes, urban planning, and disaster management. The reliability of these decision support systems is dependent on the accuracy of the video semantic segmentation algorithms. The existing CNN-based video semantic segmentation methods have enhanced the image semantic segmentation methods by incorporating an additional module such as LSTM or optical flow for computing temporal dynamics of the video which is a computational overhead. The proposed research work modifies the CNN architecture by incorporating temporal information to improve the efficiency of video semantic segmentation. In this work, an enhanced encoder–decoder based CNN architecture (UVid-Net) is proposed for unmanned aerial vehicle (UAV) video semantic segmentation. The encoder of the proposed architecture embeds temporal information for temporally consistent labeling. The decoder is enhanced by introducing the feature-refiner module, which aids in accurate localization of the class labels. The proposed UVid-Net architecture for UAV video semantic segmentation is quantitatively evaluated on extended ManipalUAVid dataset. The performance metric mean Intersection over Union of 0.79 has been observed which is significantly greater than the other state-of-the-art algorithms. Further, the proposed work produced promising results even for the pretrained model of UVid-Net on urban street scene by fine tuning the final layer on UAV aerial videos.
Laser scattering by submicron droplets originated during the electrical explosion of thin metal wires.

This paper presents the results of studying of dispersed media formation during the electrical explosion of thin metal wires in vacuum by using low-current generators ($\sim 1$-$10$~kA). Particular attention is paid to the analysis of the composition and structure of the corresponding explosion products as well as to the problem of their visualization using simultaneous laser interferometry and shadow imaging at two wavelengths (1.064~$\mu$m and 0.532~$\mu$m). Our findings point to the fact that the important role in the visualization of the explosion products belongs to multiple scattering by submicron droplets of dense condensed matter, which are mixed with metal vapor. The hypothesis on the existence of submicron droplets in the products of exploding metal wires correlates with the results obtained by soft x-ray radiography combined with a laser probing technique. Taking into account the multiple scattering by submicron droplets, it is possible to significantly clarify the parameters of the explosion products visualized via laser probing techniques as well as to gain a deeper insight into the physics behind the electrical wire explosion.
Improved Optimistic Algorithm For The Multinomial Logit Contextual Bandit

We consider a dynamic assortment selection problem where the goal is to offer a sequence of assortments of cardinality at most $K$, out of $N$ items, to minimize the expected cumulative regret (loss of revenue). The feedback is given by a multinomial logit (MNL) choice model. This sequential decision making problem is studied under the MNL contextual bandit framework. The existing algorithms for MNL contexual bandit have frequentist regret guarantees as $\tilde{\mathrm{O}}(\kappa\sqrt{T})$, where $\kappa$ is an instance dependent constant. $\kappa$ could be arbitrarily large, e.g. exponentially dependent on the model parameters, causing the existing regret guarantees to be substantially loose. We propose an optimistic algorithm with a carefully designed exploration bonus term and show that it enjoys $\tilde{\mathrm{O}}(\sqrt{T})$ regret. In our bounds, the $\kappa$ factor only affects the poly-log term and not the leading term of the regret bounds.
Pb(Yb½Nb½)O₃-PbTiO₃ : a model solid solution for the study of the different polar orders

Les materiaux piezoelectriques ont ete etudies en details du fait de la versatilite des applications industrielles possibles (accelerometres, gyroscopes ou transducteurs). Les bonnes proprietes piezoelectriques (d33=510pC/N) de Pb(Yb½Nb½)O₃-PbTiO₃ (PYN-PT) et sa haute temperature de Curie (~370°C a la MPB). Cette solution solide entre une double perovskite (ordonne sur le site B) et le titanate de plomb est remarquable, du fait qu'elle presente tous les ordres polaires a temperature ambiante: antiferroelectricite, ferroelectricite et des proprietes relaxeurs.Dans le cadre de ce travail de these, je presente les resultats obtenus sur des ceramiques de PYN-PT de diverses compositions a travers le diagramme de phase. A partir des mesures de diffractions de rayons X et de diffusion neutronique, de spectroscopie dielectrique ainsi que des mesures piezoelectriques et ferroelectriques, un nouveau diagramme de phase sera propose.Cette etude minutieuse du diagramme de phase a montre que celui-ci est plus complique que ce que laissait apparaitre la litterature. En particulier, la structure de l'antiferroelectrique PYN est particuliere en comparaison des autres perovskites antiferroelectriques au plomb. En effet, dans PYN, les atomes de plomb sont deplace suivant la direction du vecteur de modulation et les cations B sont en dehors de leurs positions prototypiques et participe a l'ordre antipolaire observe.De plus, la zone morphotropique (x _0.50) s'etale sur une zone en compositions beaucoup plus grande que ce qui a ete observe dans d'autres solutions solides a base de plomb. Dans la zone pauvre en PT de la zone morphtropique, l'absence de phase rhomboedrique (attendue par analogie avec les autres systemes au plomb) a ete demontre.D'autre part, parmi les compositions presentant des proprietes relaxeurs, des differences sont apparues et il est propose que, dans la solution solide PYN-PT, plusieurs types de relaxeurs existent.Finalement, je propose un modele expliquant continument le changement d'ordre polaire dans le diagramme de phase. Ce modele est basee sur la correlation des deplacements de plomb induite par la nature chimique et l'arrangement cationique du site B.
Final Compact Remnants in Core-collapse Supernovae from 20 to 40 M ⊙: The Lower Mass Gap

A mass paucity of compact objects in the range of ∼2–5 M ⊙ has been suggested by X-ray binary observations, namely, the “lower mass gap. ” Gravitational wave detections have unlocked another mass measurement method, and aLIGO/Virgo has observed some candidates in the gap. We revisit the numerical simulations on the core-collapse supernovae (CCSNe) for ∼20–40 M ⊙ progenitor stars with different initial explosion energies. As a result, the lower explosion energy naturally causes more efficient fallback accretion for low-metallicity progenitors, and then the newborn black holes (BHs) in the center of the CCSNe can escape from the gap, but neutron stars cannot easily collapse into BHs in the gap; nevertheless, the final remnants of the solar-metallicity progenitors stick to the gap. If we consider that only drastic CCSNe can be observed and that those with lower explosion energies are universal, the lower mass gap can be reasonably built. The width and depth of the gap are mainly determined by the typical CCSN initial explosion energy and metallicity. One can expect that the future multimessenger observations of compact objects delineate the shape of the gap, which might constrain the properties of the CCSNe and their progenitors.
High‐Performance Transition Metal Dichalcogenide Photodetectors Enhanced by Self‐Assembled Monolayer Doping

Most doping research into transition metal dichalcogenides (TMDs) has been mainly focused on the improvement of electronic device performance. Here, the effect of self‐assembled monolayer (SAM)‐based doping on the performance of WSe2‐ and MoS2‐based transistors and photodetectors is investigated. The achieved doping concentrations are ≈1.4 × 1011 for octadecyltrichlorosilane (OTS) p‐doping and ≈1011 for aminopropyltriethoxysilane (APTES) n‐doping (nondegenerate). Using this SAM doping technique, the field‐effect mobility is increased from 32.58 to 168.9 cm2 V−1 s in OTS/WSe2 transistors and from 28.75 to 142.2 cm2 V−1 s in APTES/MoS2 transistors. For the photodetectors, the responsivity is improved by a factor of ≈28.2 (from 517.2 to 1.45 × 104 A W−1) in the OTS/WSe2 devices and by a factor of ≈26.4 (from 219 to 5.75 × 103 A W−1) in the APTES/MoS2 devices. The enhanced photoresponsivity values are much higher than that of the previously reported TMD photodetectors. The detectivity enhancement is ≈26.6‐fold in the OTS/WSe2 devices and ≈24.5‐fold in the APTES/MoS2 devices and is caused by the increased photocurrent and maintained dark current after doping. The optoelectronic performance is also investigated with different optical powers and the air‐exposure times. This doping study performed on TMD devices will play a significant role for optimizing the performance of future TMD‐based electronic/optoelectronic applications.
STEEL’S PROGRAMME: EVIDENTIAL FRAMEWORK, THE CORE AND ULTIMATE-L

Abstract We address Steel’s Programme to identify a ‘preferred’ universe of set theory and the best axioms extending $\mathsf {ZFC}$ by using his multiverse axioms $\mathsf {MV}$ and the ‘core hypothesis’. In the first part, we examine the evidential framework for $\mathsf {MV}$ , in particular the use of large cardinals and of ‘worlds’ obtained through forcing to ‘represent’ alternative extensions of $\mathsf {ZFC}$ . In the second part, we address the existence and the possible features of the core of $\mathsf {MV}_T$ (where T is $\mathsf {ZFC}$ +Large Cardinals). In the last part, we discuss the hypothesis that the core is Ultimate-L, and examine whether and how, based on this fact, the Core Universist can justify V=Ultimate-L as the best (and ultimate) extension of $\mathsf {ZFC}$ . To this end, we take into account several strategies, and assess their prospects in the light of $\mathsf {MV}$ ’s evidential framework.