Miracle-dz/UniFAR-FTUs huggingface dataset:
Overview of Pain Interventions for Hospital and Community Care Nurses: A Systematic Scoping Review

Objective: Identifying the scope of pain interventions executed by nurses for adult patients in hospital and community care settings. This endeavour should help to formulate evidence-based recommendations for this nursing-sensitive outcome. Background: In health care settings, patients are prone to experience pain. Nurses play a vital role in pain prevention and treatment and make patients feel comfortable. Although nursing care is the most provided care, it is the least evidence based, resulting in overor under-treatment. Identifying the scope of effective nursing pain interventions can contribute to promote a better quality of care and use of evidence-based practice. Design: Systematic scoping review (in accordance with PRISMAScr). Methods: Medline, CINAHL, EMBASE, PsycINFO, Cochrane and Web of Science were searched up to November 2019. Western, controlled intervention studies executed by nurses involving adult patients in the hospital and community care setting were eligible for inclusion. The reviewers independently screened the title/abstract and full-text and performed a structured data extraction. In addition, they methodologically assessed the quality of the studies with the Cochrane Risk of Bias 2.0 tool. Results: Out of 5,697 studies, 47 were included. All studies had a (quasi)experimental design and were performed in a hospital or community care setting. Selected interventions were divided into three subcategories: (a) distraction interventions, like listening to music; (b) health education interventions, for example, improving self-management; and (c) pain prevention interventions, like numbing sprays, cold or hot application, specific positioning and pain-preventing devices. Risk of bias assessment resulted in two studies with a high score, 28 studies with a moderate score and 17 with a low score on methodological quality. Conclusion: This systematic scoping review provides an overview of the scope of pain interventions carried out by nurses in daily practice. More research is necessary to determine the full value these interventions. Citation: Giesen JH, Bakker-Jacobs A, van Vught A, Vermeulen H, Huisman-de Waal G (2021) Overview of Pain Interventions for Hospital and Community Care Nurses: a Systematic Scoping Review. Int J Nurs Health Care Res 4: 1265. DOI: 10.29011/2688-9501.101265 2 Volume 4; Issue 10 Int J Nurs Health Care Res, an open access journal ISSN: 2688-9501
SEM study of crystal morphology in the Zn 4 ( OH )

Мinerals with the composition Zn4(OH)6SO4.nH2O are among the rare cases of reversible mutual conversion under air relative humidity changes at ordinary temperatures. The group includes minerals osakaite (with 5 H2O per formula unit), namuwite (with 4 H2O), lahnsteinite (with 3 H2O), as well as the monohydrate, which is not found in nature, but it is obtained from the others minerals already mentioned at extremely low humidity (Stanimirova et al., 2017). All they have a layered structure composed of decorated interrupted hydroxide sheets (Hawthorne, Schindler, 2000; Hawthorne, Sokolova, 2002) and form tabular to flaky crystals with trigonal or pseudo-trigonal triclinic symmetry. In natural conditions, they are formed as alteration products of zinc ores and slags. Also, osakaite was found in samples immediately after taking them in the mine, namuwite – in a sample stored in the National Museum of Wales, and lahnsteinite – in a sample from a museum in Germany, i.e., in samples stored in an atmosphere with different relative humidity. Bear et al. (1987) found their mutual transformations in the study of hydrometallurgy of zinc and lead, and Stanimirova et al. (2017) confirm and clarify these results and propose structural schemes of conversions. It is shown that during the transformations the lattice parameter a, which depends on the hydroxide layer, remains unchanged, while the parameter c, depending on the changes in the composition and structure of the interlayer, changes significantly – from 11.027 Å in osakaite to 7.23 Å in the monohydrate. This shift associate with a change in the edge angle between the faces of the crystals. The question arises, do the crystals change morphologically under the conditions of the deep vacuum in the column of a scanning electron microscope (SEM) and the image of which modification we see in the photos after we have placed a mineral type determined by diffraction? In the present work, we seek answers to these questions using a previously described method (Kirov, Dencheva, 2016) for indexing of crystal faces of microand nano-sized crystals.
Mitotically active cellular fibroma of the ovary diagnosis and treatment

Mitotically active cellular fibroma (MACF) of the ovary is a relatively newly recognized histological disease entity which explains its scarce reporting in literature and unknown prognosis [1]. In this tumor type, high mitotic activity is noticed without severe atypia. These tumors are categorized as benign ovarian tumors with late recurrence, if any. However, we herein report an unusual case of an ovarian mitotically active atypical fibrous tumor case which presented as recurrence within six months of being operated thereby raising suspicion of an element of malignancy. On presentation, the patient suffered from abdominal pain and abdomino-pelvic mass. After imaging confirmed an ovarian neoplastic lesion patient underwent bilateral salpingo-oophorectomy and hysterectomy. Histopathology defined the lesion as “ovarian mitotically active atypical fibrous tumor”. Six months later, abdominal pain recurred for which imagining was done and confirmed a newly developed well defined irregular complex solid cystic mass causing intestinal obstruction giving an impression of a malignant neoplasm, probably ovarian carcinoma. However, histopathology for the new lesion remained the same as was for the previous mass, i.e. mitotically active ovarian fibroma, but with lung and mesenteric lymph nodes metastases. Patient couldn’t be operated on due to her co-morbid conditions, and the mass was vascular. She was given supportive care with consideration to start hormonal therapy and during this period died due to sepsis. This case highlights the importance of having a high suspicion of the possibility of malignancy when mitotically active cellular fibroma manifests as a recurrence of mass as this tumor may tend to have an uncertain malignant potential. Thereby, stressing the importance of long term follow up even after the primary tumor is surgically treated without any surgical difficulty or tumor rupture [2]. Such tumors need to be followed and reported more often to help understanding the way they behave and their management.
Properties of Type Ibn Supernovae: Implications for the Progenitor Evolution and the Origin of a Population of Rapid Transients

Type Ibn supernovae (SNe Ibn) show signatures of strong interaction between the SN ejecta and hydrogen-poor circumstellar matter (CSM). Deriving the ejecta and CSM properties of SNe Ibn provides a great opportunity to study the final evolution of massive stars. In the present work, we present a light-curve (LC) model for the ejecta–CSM interaction, taking into account the processes in which the high-energy photons originally created at the forward and reverse shocks are converted to the observed emission in the optical. The model is applied to a sample of SNe Ibn and “SN Ibn” rapidly evolving transients. We show that the characteristic post-peak behavior commonly seen in the SN Ibn LCs, where a slow decay is followed by a rapid decay, is naturally explained by the transition of the forward-shock property from cooling to adiabatic regime without introducing a change in the CSM density distribution. The (commonly found) slope in the rapid-decay phase indicates a steep CSM density gradient (ρ CSM ∝ r −3), inferring a rapid increase in the mass-loss rate toward the SN as a generic property of the SN Ibn progenitors. From the derived ejecta and CSM properties, we argue that massive Wolf–Rayet stars with an initial mass of ≳18 M ⊙ can be a potential class of the progenitors. The present work also indicates the existence of a currently missing population of UV-bright rapid transients for which the final mass-loss rate is lower than the optical SNe Ibn, which can be efficiently probed by future UV missions.
Fibrational linguistics: First concepts

We define a general mathematical framework for linguistics based on the theory of fibrations, called FibLang. We start by modelling the interaction between linguistics and cognition in the most general way possible, with a heavy focus on conceptually motivating any assumption we make. The advantage is that FibLang remains agnostic with respect to any particular axiomatization of grammar one may choose. As such, it is compatible with already existing categorical models of language (such as for example, DisCoCat), providing a formally sound framework to apply mathematical tools developed in the context of category theory, mainly categorical logic, to the study of language
New RED-type TCP-AQM algorithms based on beta distribution drop functions

In recent years, Active Queue Management (AQM) mechanisms to improve the performance of TCP/IP networks have acquired a relevant role. In this paper, we present a simple and robust RED-type algorithm together with a couple of dynamical variants with the ability to adapt to the specific characteristics of different network environments, as well as to the user’s needs. We first present a basic version called Beta RED (BetaRED), where the parameters can be tuned according to the specific network conditions. The aim is to introduce control parameters that are easy to interpret and provide a good performance over a wide range of values. Secondly, BetaRED is used as a framework to design two dynamic algorithms, which we will call Adaptive Beta RED (ABetaRED) and Dynamic Beta RED (DBetaRED). In those new algorithms, certain parameters are dynamically adjusted so that the queue length remains stable around a predetermined reference value and according to changing network traffic conditions. Finally, we present a battery of simulations using the Network Simulator 3 (ns-3) software with a two-fold objective: to guide the user on how to adjust the parameters of the BetaRED mechanism, and to show a performance comparison of ABetaRED and DBetaRED with other representative algorithms that pursue a similar objective.
Theoretical model of efficient phagocytosis driven by curved membrane proteins and active cytoskeleton forces

Phagocytosis is the process of engulfment and internalization of comparatively large particles by the cell, that plays a central role in the functioning of our immune system. We study the process of phagocytosis by considering a simplified coarse grained model of a three-dimensional vesicle, having uniform adhesion interaction with a rigid particle, in the presence of curved membrane proteins and active cytoskeletal forces. Complete engulfment is achieved when the bending energy cost of the vesicle is balanced by the gain in the adhesion energy. The presence of curved (convex) proteins reduces the bending energy cost by self-organizing with higher density at the highly curved leading edge of the engulfing membrane, which forms the circular rim of the phagocytic cup that wraps around the particle. This allows the engulfment to occur at much smaller adhesion strength. When the curved proteins exert outwards protrusive forces, representing actin polymerization, at the leading edge, we find that engulfment is achieved more quickly and at lower protein density. We consider spherical as well as non-spherical particles, and find that non-spherical particles are more difficult to engulf in comparison to the spherical particles of the same surface area. For non-spherical particles, the engulfment time crucially depends upon the initial orientation of the particles with respect to the vesicle. Our model offers a mechanism for the spontaneous self-organization of the actin cytoskeleton at the phagocytic cup, in good agreement with recent high-resolution experimental observations. Significance Statement Phagocytosis is an important process that plays a central role in our immune system, and also during nutrient uptake, drug delivery and pathogen invasion. Despite its biological importance, it is still not understood how the actin cytoskeleton is coordinated spatio-temporally during the phagocytosis process. We present a simple model that explains the dynamics and self-organization of the membrane and the actin cytoskeleton during the engulfment process, based on curved membrane activators of actin polymerization.
On reduced G-perfection and horizontal linkage relative to a semidualizing module

In their investigation of horizontal linkage of modules of finite Gorenstein dimension over a commutative, Noetherian, semiperfect (e.g., local) ring, Dibaei and Sadeghi introduced the class of reduced G-perfect modules, making use of Bass’ concept of reduced grade. A few years later, the same authors extended this class by considering the relative property of reduced GC-perfection, where C is a semidualizing module, and studied linkage even further. In the present paper, we contribute to their theory and also generalize results of Auslander and Bridger as well as of Martsinkovsky and Strooker. Our investigation includes, for example, when reduced GC-perfection is preserved by relative Auslander transpose, and how to numerically characterize horizontally linked modules under suitable conditions. Along the way, we show how to produce reduced GC-perfect modules that are also C-k-torsionless (for a given integer k ≥ 0) but fail to be GC-perfect, and moreover we illustrate that, in contrast to the usual grade, the relative reduced grade does depend on the choice of C.
Effects of ultrafast free-carrier dynamics on frequency comb generation in graphene-based microresonators

Manipulation of the dynamics of cavity solitons, precise control of frequency comb spectra and nonlinear response of microresonators through exploitation of the ultrafast optical properties of graphene can have an immense impact on the technological advancement of on-chip photonic devices. Here, we report that an efficient self-frequency blueshifted frequency comb at optical and near-infrared wavelengths can be achieved owing to the near-instantaneous free-carrier dynamics of graphene in a realistic graphene-covered silicon nitride microresonator. We perform a stability analysis to find the region of stable cavity soliton excitation, which reveals that the nonlinearity of graphene helps in improving the performance of the devices.
Hydrothermal Activities on C-Complex Asteroids Induced by Radioactivity

C-complex asteroids, rich in carbonaceous materials, are potential sources of Earth’s volatile inventories. They are spectrally dark resembling primitive carbonaceous meteorites, and thus, C-complex asteroids are thought to be potential parent bodies of carbonaceous meteorites. However, the substantial number of C-complex asteroids exhibits surface spectra with weaker hydroxyl absorption than water-rich carbonaceous meteorites. Rather, they best correspond to meteorites showing evidence for dehydration, commonly attributed to impact heating. Here, we report an old radiometric age of 4564.7 million years ago for Ca carbonates from the Jbilet Winselwan meteorite analogous to dehydrated C-complex asteroids. The carbonates are enclosed by a high-temperature polymorph of Ca sulfates, suggesting thermal metamorphism at >300°C subsequently after aqueous alteration. This old age indicates the early onset of aqueous alteration and subsequent thermal metamorphism driven by the decay of short-lived radionuclides rather than impact heating. The breakup of original asteroids internally heated by radioactivity should result in asteroid families predominantly consisting of thermally metamorphosed materials. This explains the common occurrence of dehydrated C-complex asteroids.
Expected FU Ori Outburst Amplitudes from the Optical to the Mid-infrared

Disks around young stellar objects (YSOs) consist of material that thermally emits the energy provided by a combination of passive heating from the central star, and active, viscous heating due to mass accretion. FU Ori stars are YSOs with substantially enhanced accretion rates in their inner disk regions. As a disk transitions from standard low-state, to FU Ori-like high-state accretion, the outburst manifests through photometric brightening over a broad range of wavelengths. We present results for the expected amplitudes of the brightening between ∼4000 Å and 8 μm—the wavelength range where FU Ori type outburst events are most commonly detected. Our model consists of an optically thick passive + active steady-state accretion disk with low and high accretion states.
Gaussian-Hermite Moment Invariants of General Vector Functions to Rotation-Affine Transform

—With the development of data acquisition technology, multi-channel data is collected and widely used in many ﬁelds. Most of them can be expressed as various types of vector functions. Feature extraction of vector functions for identifying certain patterns of interest is a critical but challenging task. In this paper, we focus on constructing moment invariants of general vector functions. Speciﬁcally, we deﬁne rotation-afﬁne transform to describe real deformations of general vector functions, and then design a structural frame to systematically generate Gaussian-Hermite moment invariants to this transform model. This is the ﬁrst time that a uniform frame has been proposed in the literature to construct orthogonal moment invariants of general vector functions. Given a certain type of multi-channel data, we demonstrate how to utilize the new method to derive all possible invariants and to eliminate various dependences among them. For RGB images, 2D and 3D ﬂow ﬁelds, we obtain the complete and independent sets of the invariants with low orders and low degrees. Based on synthetic and popular datasets of vector-valued data, the experiments are carried out to evaluate the stability and discriminability of these invariants, and also their robustness to noise. The results clearly show that the moment invariants proposed in our paper have better performance than other previously used moment invariants of vector functions in RGB image classiﬁcation, vortex detection in 2D vector ﬁelds and template matching for 3D ﬂow ﬁelds.
A Transformer-Based Siamese Network for Change Detection

This paper presents a transformer-based Siamese network architecture (abbreviated by ChangeFormer) for Change Detection (CD) from a pair of co-registered remote sensing images. Different from recent CD frameworks, which are based on fully convolutional networks (ConvNets), the proposed method unifies hierarchically structured transformer encoder with Multi-Layer Perception (MLP) decoder in a Siamese network architecture to efficiently render multi-scale long-range details required for accurate CD. Experiments on two CD datasets show that the proposed end-to-end trainable ChangeFormer architecture achieves better CD performance than previous counterparts. Our code and pre-trained models are available at github.com/wgcban/ChangeFormer.
Applications of the fibration method for zero-cycles to the Brauer-Manin obstruction to the existence of zero-cycles on certain varieties

We study the Brauer-Manin obstruction to the existence of zero-cycles of degree d on certain classes of varieties over number ﬁelds. We generalize existing results in the literature and prove some results about ﬁbrations over the projective line, where the geometric Brauer group of the generic ﬁbre is not assumed to be ﬁnite. The idea is to assume that the Brauer-Manin obstruction to the Hasse principle is the only one for certain ﬁbres and then deduce analogous results for zero-cycles.
Rank-one strange attractors versus heteroclinic tangles

We present two different mechanisms for the emergence of strange attractors (observable chaos) in a two-parameter periodically-perturbed family of differential equations on the plane. The two parameters are independent and act on different ways in the invariant manifolds of consecutive saddles in the cycle. When both parameters are zero, the flow exhibits an attracting heteroclinic cycle associated to two equilibria. The first parameter makes the two-dimensional invariant manifolds of consecutive saddles in the cycle to pull apart; the second forces transverse intersection. The unfolding of each parameter is associated to the emergence of different dynamical scenarios (rank-one attractors and heteroclinic tangles). These relative positions may be determined using the Melnikov method.Extending the previous theory on the field, we prove the existence of many complicated dynamical objects in the two-parameter family, ranging from "lar-ge" strange attractors supporting SRB (Sinai-Ruelle-Bowen) measures to superstable sinks and non-uniformly hyperbolic attractors. We draw a plausible bifurcation diagram associated to the problem under consideration and we show that the occurrence of heteroclinic tangles is a prevalent phenomenon.
Lattice simulations of the QCD chiral transition at real $\mu_B$

Most lattice studies of hot and dense QCD matter rely on extrapolation from zero or imaginary chemical potentials. The ill-posedness of numerical analytic continuation puts severe limitations on the reliability of such methods. We studied the QCD chiral transition at finite real baryon density with the more direct sign reweighting approach. We simulate up to a baryochemical potential-temperature ratio of $\mu_B/T=2.7$, covering the RHIC Beam Energy Scan range, and penetrating the region where methods based on analytic continuation are unpredictive.This opens up a new window to study QCD matter at finite $\mu_B$ from first principles.
Learning to Generate Novel Classes for Deep Metric Learning

Deep metric learning aims to learn an embedding space where the distance between data reflects their class equivalence, even when their classes are unseen during training. However, the limited number of classes available in training precludes generalization of the learned embedding space. Motivated by this, we introduce a new data augmentation approach that synthesizes novel classes and their embedding vectors. Our approach can provide rich semantic information to an embedding model and improve its generalization by augmenting training data with novel classes unavailable in the original data. We implement this idea by learning and exploiting a conditional generative model, which, given a class label and a noise, produces a random embedding vector of the class. Our proposed generator allows the loss to use richer class relations by augmenting realistic and diverse classes, resulting in better generalization to unseen samples. Experimental results on public benchmark datasets demonstrate that our method clearly enhances the performance of proxy-based losses.