Miracle-dz/UniFAR-FTUs huggingface dataset:
Acute triage of childhood stroke in Denmark

Objective: This 2-year observational study aimed to test the feasibility of implementing a pediatric stroke triage-setup that connected frontline providers with vascular neurologists and to examine final diagnoses in children triaged for suspected stroke. Methods: Prospective, consecutive registration of children with suspected stroke triaged by a team of vascular neurologists from Jan 1st, 2020 and through Dec 2021, Eastern Denmark (census 530,000 children). Based on the provided clinical information, the children were triaged to either assessment at the Comprehensive Stroke Center (CSC) in Copenhagen or to a pediatric department. All included children were retrospectively followed-up for clinical presentations and final diagnosis. Results: A total of 163 children with 166 suspected stroke events were triaged by the vascular neurologists. Cerebrovascular disease was present in 15 (9.0%) suspected stroke events; one child had intracerebral hemorrhage, one had subarachnoid hemorrhage, two children presented with three TIA events and nine children presented with 10 ischemic stroke events. Two children with ischemic stroke were eligible for acute revascularization treatment of which both were triaged to the CSC. The sensitivity of the triage by acute revascularization indication was 1.00 (95% confidence interval (95% CI): 0.15–1.00) and specificity 0.65 (95% CI: 0.57–0.73). Non-stroke neurological emergencies were present in 34 (20.5%) children, including seizures in 18 (10.8%) and acute demyelinating disorders in 7 (4.2%). Conclusion: Implementing regional triage-setup that connected frontline providers to vascular neurologists was feasible; this system was activated for the majority of children with ischemic stroke according to an expected incidence and led to identification of children eligible for revascularization treatments.
Physicochemical Quality and Fatty Acid Profile in the Meat of Goats Fed Forage Cactus as a Substitute for Tifton 85 Hay

Simple Summary The use of cacti, such as forage cactus, in goat feeding is widely practised in Northeast Brazil due to adaptation to climatic conditions, mainly in arid and semi-arid regions. During dry periods, when water is the main limiting factor for the development of most plant species, the growth of forage cactus is not compromised due to crassulacean acid metabolism. However, little is known about the effects of forage cactus on goats’ diet in relation to meat quality. In this study, we evaluated the inclusion of 0, 25 and 55% of forage cactus replacing Tifton 85 hay in the diet of goats and its effects on meat quality. Meat from kids fed 55% of forage cactus showed greater acceptance by consumers. Therefore, it is recommended that Tifton 85 hay be replaced with 55% forage cactus, as it provides lower lipid content and higher monounsaturated fatty acid content in goat meat. Abstract Low rainfall in Northeast Brazil is a limiting factor for animal production. Forages that present crassulacean acid metabolism, such as forage cactus, are adapted to the edaphoclimatic conditions of this region, as they lose little water through the stomata. Thus, the objective was to evaluate the physical and chemical quality, fatty acid profile and sensory acceptance of the meat from goats fed forage cactus as a substitute for Tifton 85 hay. Twenty-one uncastrated mixed-breed goats with a mean body weight of 18 ± 0.86 kg and 7 ± 1 months of age were used. A completely randomized design with three treatments and seven replications per treatment was performed. The inclusion of 0 (control), 25 and 55% of forage cactus in substitution of Tifton 85 hay in the diet of the goats was evaluated. The lipid content in the meat of animals fed 25 and 55% of forage cactus was 1.33% and 1.26%, respectively, and was lower (p < 0.05) in relation to the meat of animals that received the control diet (1.56%). The inclusion of 55% of forage cactus provided an increase (p < 0.05) in the content of monounsaturated fatty acids in the meat (52.71%) in relation to the control meat (37.75%). Sensory analysis differed (p < 0.05) between treatments. We recommend replacing Tifton 85 hay with 55% forage cactus, as it presents greater sensory acceptance, and provides lower lipid content and higher content of monounsaturated fatty acids in goat meat.
DOPPLER IMAGING OF SPOTTED STARS : APPLICATION TO THE RS CANUM VENATICORUM STAR HR 1099.

A technique for imaging the surfaces of certain rapidly rotating spotted stars is discussed. The method exploits the correspondence between wavelength position across a rotationally broadened spectral line and spatial position across the stellar disk. Preliminary Doppler Images of the RS CVn star HR 1099 show spots which exhibit a striking similarity in shape and location to X ray images of solar coronal holes. It is suggested that the large star spots on RS CVn's and other active late-type stars emerge at low latitude as scaled-up analogs of solar complexes, but as they migrate poleward, they more closely resemble photospheric analogs of solar coronal holes. The evolution of starspots appears remarkably similar to that of large-scale magnetic fields of the sun.
On the Growth of the Hurricane Depression

Abstract Why do cyclones form in a conditionally unstable tropical atmosphere whose vertical thermal structure is apparently more favorable to small-scale cumulus convection than to convective circulations of tropical cyclone scale? It is proposed that the cyclone develops by a kind of secondary instability in which existing cumulus convection is augmented in regions of low-level horizontal convergence and quenched in regions of low-level divergence. The cumulus- and cyclone-scale motions are thus to be regarded as cooperating rather than as competing–the clouds supplying latent heat energy to the cyclone, and the cyclone supplying the fuel, in the form of moisture, to the clouds. A scale-analysis indicates that it is appropriate to use the balance equations of Eliassen for the macro-motion; in this case the effect of friction in the boundary-layer may be incorporated as a condition on the vertical velocity at the top of the boundary layer. It is argued that the mean humidity in a system of convecting cum.
Ensemble Learning, Deep Learning-Based and Molecular Descriptor-Based Quantitative Structure–Activity Relationships

A deep learning-based quantitative structure–activity relationship analysis, namely the molecular image-based DeepSNAP–deep learning method, can successfully and automatically capture the spatial and temporal features in an image generated from a three-dimensional (3D) structure of a chemical compound. It allows building high-performance prediction models without extracting and selecting features because of its powerful feature discrimination capability. Deep learning (DL) is based on a neural network with multiple intermediate layers that makes it possible to solve highly complex problems and improve the prediction accuracy by increasing the number of hidden layers. However, DL models are too complex when it comes to understanding the derivation of predictions. Instead, molecular descriptor-based machine learning has clear features owing to the selection and analysis of features. However, molecular descriptor-based machine learning has some limitations in terms of prediction performance, calculation cost, feature selection, etc., while the DeepSNAP–deep learning method outperforms molecular descriptor-based machine learning due to the utilization of 3D structure information and the advanced computer processing power of DL.
A Commentary on "Radical Behaviorism"

B. F. Skinner is perhaps even more widely known for his views on science than for his experimental work. His comments on the role of theory in science have been labeled "anti-theoretical," "ultra-empirical", "non-theoretical," "radical," and worse. His position appears to be both extreme and untenable. Scriven [1] has given us a critique of Skinner that goes beyond mere labeling; it is an examination of the assumptions and implications of such a position. In some instances, however, Scriven's analysis is not entirely correct or is misleading. There are different interpretations of Skinner from those offered by Scriven and perhaps "something more" in Skinner's point of view than has been caught by Scriven's analytic "net. " In general I shall simply comment on seven problems commonly posed by Skinner's critics, paying special attention to Scriven's discussion of these questions. There is some tendency among Skinner's critics to intermingle and juxtapose problems in a rather devastating way. By discussing the matter of whether or not Skinner really has a theory, they side-step the question of whether or not theories are necessary. Or, the logical necessity of theories in science is discussed as though this answers the question of whether or not theories are heuristically "helpful" in the context of discovery. I shall try to delimit these problems as clearly as possible. There are two recurrent themes in my commentary. One is the distinction between analysis of terms for their ordinary meaning and analysis of terms for their explanatory value, and the second is the question of the best way for the scientist to arrive at creative and fruitful hypotheses.
APPLICATION OF A NEW CLASS OF SYMPLECTIC INTEGRATORS TO ACCELERATOR TRACKING

The dynamics of particle accelerator beams is commonly described by a Hamiltonian of the form H = A+�B where A and B are integrable. Using Lie formalism, we give an overview of a new class of symplectic integrator (1) par- ticularly well adapted whenB is viewed as a perturbation of A. These integrators with positive step size can be con- structed with a remainder of arbitrary order n in A and or- der 2i nB . Moreover a corrector step can be added to the integration scheme in many cases such that the remain- der becomes actually of order 4 inB . A comparison with the fourth-order standard Forest and Ruth integrator (2) is performed showing in general one order of magnitude im- provement in computation precision for the same cost. The construction of these integrators is given for the main mag- netic elements of an electron storage ring.
Temperature and pressure effects on the thermal conductivity and heat capacity of CsCl, CsBr and CsI

The thermal conductivity and the heat capacity per unit volume of CsCl, CsBr and CsI have been measured as a function of temperature and pressure over the ranges 100-400K and 0-2.5 GPa. For CsCl and CsBr most of the contribution to the thermal conductivity comes from acoustical phonons, while in the case of CsI there is an appreciable contribution from optical phonons. The part of the thermal conductivity due to propagating acoustic phonons has essentially a T-1 temperature dependence. The heat capacity is found to be essentially constant over the measured temperature and pressure range for all three materials. The pressure dependence of the Gruneisen constant, derived from the change in the thermal conductivity under pressure, is correlated with the same quantity obtained by other methods, and the reasons for the discrepancies are discussed.
A Real Time Multi-focus Image Fusion Framework ⋆

In this paper, we proposed a new image fusion scheme on spatial domain. The interest of the scheme is its real time. The framework contains two steps: saliency detection and coefficient selection based on the principle of maximum saliency preservation. Mean Square Error, Average Gradient and Spectral Residual Approach are adopted to detect the saliency of original images. Two group of experimental data are shown, and results shown that the image fusion framework works well, and Spectral Residual Approach base fusion scheme performs best among the three schemes.
Stratification of surgical margin distances by the millimeter on local recurrence in oral cavity cancer: A systematic review and meta‐analysis

There are limited data supporting the commonly suggested 5 mm margin cutoff as the optimum value in defining clear margins in oral cancer. A database search of Pubmed/Medline, Web of Science, and EBSCOhost was performed from inception to June 2022. A random‐effects model was chosen for this meta‐analysis. The Preferred Reporting Items for Systematic Reviews and Meta‐analyses (PRISMA) guidelines were followed throughout this study. Seven studies met study criteria (2215 patients). The risk ratio was significantly higher for margins <5 mm when compared to those ≥5 mm (2.09 (95%CI: 1.53–2.86, I2 = 0.47)). Subgroup analysis (I2 = 0.15) of margin distances of 0.0–0.9, 1.0–1.9, 2.0–2.9, 3.0–3.9, and 4.0–4.9 mm calculated risk ratios for local recurrence of 2.96, 2.01, 2.17, 1.8, and 0.98, respectively. Margins between 4.0 and 4.9 mm had similar risk ratios for local recurrence compared to ≥5 mm, while margins <4.0 were significantly higher.
Multi-analyte optical chemical sensor employing a plastic substrate

A dual-analyte optical chemical sensor platform based on the surface patterning of fluorescent dyes immobilized in sol-gel thin films is demonstrated as a proof of principle for a potential multi-analyte detection system with implications for lab-on-a-chip technology. A combination of hot embossing and an eccentric spin-coating technique was used to achieve discrete deposition of oxygen and carbon dioxide sensitive zones on a single waveguiding platform. Imaging of fluorescence from the oxygen and carbon dioxide sensing areas was performed using a low-cost CCD camera and fluorescence quenching on analyte exposure was characterized.
Mixed Graphical Models with Missing Data and the Partial Imputation EM Algorithm

In this paper we discuss graphical models for mixed types of continuous and discrete variables with incomplete data. We use a set of hyperedges to represent an observed data pattern. A hyperedge is a set of variables observed for a group of individuals. In a mixed graph with two types of vertices and two types of edges, dots and circles represent discrete and continuous variables respectively. A normal graph represents a graphical model and a hypergraph represents an observed data pattern. In terms of the mixed graph, we discuss decomposition of mixed graphical models with incomplete data, and we present a partial imputation method which can be used in the EM algorithm and the Gibbs sampler to speed their convergence. For a given mixed graphical model and an observed data pattern, we try to decompose a large graph into several small ones so that the original likelihood can be factored into a product of likelihoods with distinct parameters for small graphs. For the case that a graph cannot be decomposed due to its observed data pattern, we can impute missing data partially so that the graph can be decomposed.
Spin-polarized two-dimensional electron gas through electrostatic doping in LaAlO 3 /EuO heterostructures

We carry out a first-principles study of stoichiometric heterostructures composed of polar oxide LaAlO3 and ferromagnetic semiconductor EuO. We show that electrostatic doping achieved by an electric field in the polar oxide leads to a fully spin-polarized two dimensional electron gas at the interface. This mechanism contrasts with a previous calculation of the LaAlO3 /EuO interface in which electron doping is introduced through a nonstoichiometric LaAlO3 layer. Our system allows a low level of doping in EuO that is comparable to the Gd-doped EuO found in recently reported experiment, and is thickness controllable. We predict a change of magnetic moment of Eu and increase of the Curie temperature in the doped layers of EuO.
Molecular and cellular level characterization of cytoskeletal mechanics using a quartz crystal microbalance

A quartz crystal microbalance (QCM) is an instrument that has the ability to measure nanogram‐level changes in mass on a quartz sensor and is traditionally used to probe surface interactions and assembly kinetics of synthetic systems. The addition of dissipation monitoring (QCM‐D) facilitates the study of viscoelastic systems, such as those relevant to molecular and cellular mechanics. Due to real‐time recording of frequency and dissipation changes and single protein‐level precision, the QCM‐D is effective in interrogating the viscoelastic properties of cell surfaces and in vitro cellular components. However, few studies focus on the application of this instrument to cytoskeletal systems, whose dynamic parts create interesting emergent mechanics as ensembles that drive essential tasks, such as division and motility. Here, we review the ability of the QCM‐D to characterize key kinetic and mechanical features of the cytoskeleton through in vitro reconstitution and cellular assays and outline how QCM‐D studies can yield insightful mechanical data alone and in tandem with other biophysical characterization techniques.
Airway Complications After Anterior Cervical Spine Surgery: Etiology and Risk Factors

Study Design Narrative Review Objective To provide an overview of etiology and risk factors of airway complications after anterior cervical spine surgery (ACSS). Methods A search was performed in PubMed and adapted for use in other databases, including Embase, Cochrane Library, Cochrane Register of Controlled Trials, Health Technology Assessment database, and NHS Economic Evaluation Database. Results 81 full-text studies were reviewed. A total of 53 papers were included were included in the review and an additional four references were extracted from other references. 39 papers were categorized as etiology and 42 as risk factors. Conclusions Most of the literature on airway compromise after ACSS is level III or IV evidence. Currently, there are no systems in place to risk-stratify patients undergoing ACSS regarding airway compromise or guidelines on how to manage patients when these complications do occur. This review focused on theory, primarily etiology and risk factors.
Subjective Complaints are Similar in Subjective Cognitive Decline and Early-Stage Alzheimer’s Disease when Assessed in a Memory Clinic Setting

Background Subjective cognitive complaints are generally poorly associated with objective memory functioning in older persons. Subjective cognitive decline (SCD) is a key feature in SCD and amnestic mild cognitive impairment (aMCI) which both can represent early Alzheimer’s disease (AD). The aim of this study was to assess how memory clinic patients with SCD, MCI and mild AD dementia scored on 3 different complaint measures and if the format of assessment had an impact on the association with cognitive functioning, age, and depressive symptoms. Methods We included 17 SCD patients, 17 aMCI patients, 17 patients with mild AD, and 30 controls. Complaints were assessed with the Cognitive Change Index (CCI), the Subjective Memory Complaints (SMC) scale, and the Memory Complaint Questionnaire (MAC-Q). Results There were no significant differences between the total scores in the patient groups on the questionnaires. However, significant differences were found in the number of patients classified with impairment when using the CCI, the SMC, and the MAC-Q. Scores on all questionnaires were significantly associated with depressive symptoms, and significant associations with age, gender, and Addenbrookes Cognitive Examination score were found for the SMC. In patients with cognitive dysfunction, lower memory awareness significantly predicted fewer cognitive complaints. Conclusions SCD patients in a memory clinic setting report the same degree of cognitive impairment as patients with aMCI and mild dementia, and in a hospital-based cohort we extend previous findings from healthy controls, that definition of SCD may depend on the format of assessment.
Redundancy-aware unsupervised ranking based on game theory: Ranking pathways in collections of gene sets

In Genetics, gene sets are grouped in collections concerning their biological function. This often leads to high-dimensional, overlapping, and redundant families of sets, thus precluding a straightforward interpretation of their biological meaning. In Data Mining, it is often argued that techniques to reduce the dimensionality of data could increase the maneuverability and consequently the interpretability of large data. In the past years, moreover, we witnessed an increasing consciousness of the importance of understanding data and interpretable models in the machine learning and bioinformatics communities. On the one hand, there exist techniques aiming to aggregate overlapping gene sets to create larger pathways. While these methods could partly solve the large size of the collections’ problem, modifying biological pathways is hardly justifiable in this biological context. On the other hand, the representation methods to increase interpretability of collections of gene sets that have been proposed so far have proved to be insufficient. Inspired by this Bioinformatics context, we propose a method to rank sets within a family of sets based on the distribution of the singletons and their size. We obtain sets’ importance scores by computing Shapley values; Making use of microarray games, we do not incur the typical exponential computational complexity. Moreover, we address the challenge of constructing redundancy-aware rankings where, in our case, redundancy is a quantity proportional to the size of intersections among the sets in the collections. We use the obtained rankings to reduce the dimension of the families, therefore showing lower redundancy among sets while still preserving a high coverage of their elements. We finally evaluate our approach for collections of gene sets and apply Gene Sets Enrichment Analysis techniques to the now smaller collections: As expected, the unsupervised nature of the proposed rankings allows for unremarkable differences in the number of significant gene sets for specific phenotypic traits. In contrast, the number of performed statistical tests can be drastically reduced. The proposed rankings show a practical utility in bioinformatics to increase interpretability of the collections of gene sets and a step forward to include redundancy-awareness into Shapley values computations.
Occupational Risk Factors for SARS-CoV-2 Seropositivity in Healthcare Workers

Physicians with the least clinical training exhibited the highest odds of COVID-19 antibodies early in the pandemic. Prior to COVID-19 vaccine distribution, standard occupational health interventions including increased training and access to personal protective equipment eliminated the excess risk of COVID-19 among vulnerable healthcare workers. Objective The aim of the study is to evaluate COVID-19 risk factors among healthcare workers (HCWs) before vaccine-induced immunity. Methods We conducted a longitudinal cohort study of HCWs (N = 1233) with SARS-CoV-2 immunoglobulin G quantification by ELISA and repeated surveys over 9 months. Risk factors were assessed by multivariable-adjusted logistic regression and Cox proportional hazards models. Results SARS-CoV-2 immunoglobulin G was associated with work in internal medicine (odds ratio [OR], 2.77; 95% confidence interval [CI], 1.05–8.26) and role of physician-in-training (OR, 2.55; 95% CI, 1.08–6.43), including interns (OR, 4.22; 95% CI, 1.20–14.00) and resident physicians (OR, 3.14; 95% CI, 1.24–8.33). Odds were lower among staff confident in N95 use (OR, 0.55; 95% CI, 0.31–0.96) and decreased over the follow-up. Conclusions Excess COVID-19 risk observed among physicians-in-training early in the COVID-19 pandemic was reduced with improved occupational health interventions before vaccinations.