Miracle-dz/UniFAR-FTUs huggingface dataset:
Non-Surgical Management of Ectopic Pregnancies

Ectopic pregnancy is a serious medical condition that can affect the patient’s fertility and even be life threatening in the most severe cases. The frequency of this condition is increasing on par with sexually transmitted diseases and medically assisted procreation techniques. This is a retrospective study concerning 91 cases of ectopic pregnancies among which 56 were treated medically (61.5% of cases) by 1mg of Methotrexate/Kg of body weight. The success rate was 62.5%. The best success predictive factor of medical treatment was HCG level below 1000mUI/ml. The average HCG negativation time was 21 days. 21 ectopic pregnancies didn’t respond to MTX (37.5%). The main fail criteria was the persistence of an HCG level above 15%, (52.3% of case). Fertility was preserved in 53% of cases during 5 years of observation.
Hot disk of the Swift J0243.6+6124 revealed by Insight-HXMT

We report on analysis of observations of the bright transient X-ray pulsar Swift J0243.6+6124 obtained during its 2017-2018 giant outburst with Insight-HXMT, NuSTAR, and Swift observatories. We focus on the discovery of a sharp state transition of the timing and spectral properties of the source at super-Eddington accretion rates, which we associate with the transition of the accretion disk to a radiation pressure dominated (RPD) state, the first ever directly observed for magnetized neutron star. This transition occurs at slightly higher luminosity compared to already reported transition of the source from sub- to super-critical accretion regime associate with onset of an accretion column. We argue that this scenario can only be realized for comparatively weakly magnetized neutron star, not dissimilar to other ultra-luminous X-ray pulsars (ULPs), which accrete at similar rates. Further evidence for this conclusion is provided by the non-detection of the transition to the propeller state in quiescence which strongly implies compact magnetosphere and thus rules out magnetar-like fields.
Modeling population dynamics based on experimental trials with genetically modified mosquitoes

Recently, the RIDL-SIT technology has been field-tested for control of \emph{Aedes aegypti}. The technique consists of releasing genetically modified mosquitoes carrying a "lethal gene". In 2016 the World Health Organisation (WHO) and the Pan-American Health Organization (PAHO) recommend to their constituent countries to test the new technologies proposed to control \emph{Aedes aegypti} populations. However, issues concerning effectiveness and ecological impact have not been thoroughly studied so far. In order to study these issues, we develop an ecological model compatible with the information available. It presents an interdependent dynamics of mosquito populations and food in an homogeneous setting. Mosquito populations are described in an stochastic compartmental setup in terms of reaction norms depending on the available food in the environment. The development of the model allow us to indicate some critical biological knowledge that is missing and could (should) be produced. Considering the model results we show how the releases proposed could contribute to the increase of epidemic risk after they have concluded. Hybridisation levels and release numbers of mosquitoes as a function of intervention duration and target are calculated.
Dust emissivity and absorption cross section in DustPedia late-type galaxies

Aims. We compare the far-infrared to sub-millimetre dust emission properties measured in high Galactic latitude cirrus with those determined in a sample of 204 late-type DustPedia galaxies. The aim is to verify if it is appropriate to use Milky Way dust properties to derive dust masses in external galaxies. Methods. We used Herschel observations and atomic and molecular gas masses to estimate ϵ(250 μm), the disc-averaged dust emissivity at 250 μm, and from this, the absorption cross section per H atom σ(250 μm) and per dust mass κ(250 μm). The emissivity ϵ(250 μm) requires one assumption, which is the CO-to-H2 conversion factor, and the dust temperature is additionally required for σ(250 μm); yet another constraint on the dust-to-hydrogen ratio D/H, depending on metallicity, is required for κ(250 μm). Results. We find ϵ(250 μm) = 0.82 ± 0.07 MJy sr−1 (1020 H cm−2)−1 for galaxies with 4 < F(250 μm)/F(500 μm) < 5. This depends only weakly on the adopted CO-to-H2 conversion factor. The value is almost the same as that for the Milky Way at the same colour ratio. Instead, for F(250 μm)/F(500 μm) > 6, ϵ(250 μm) is lower than predicted by its dependence on the heating conditions. The reduction suggests a variation in dust emission properties for spirals of earlier type, higher metallicity, and with a higher fraction of molecular gas. When the standard emission properties of Galactic cirrus are used for these galaxies, their dust masses might be underestimated by up to a factor of two. Values for σ(250 μm) and κ(250 μm) at the Milky Way metallicity are also close to those of the cirrus. Mild trends of the absorption cross sections with metallicity are found, although the results depend on the assumptions made.
Toy Models of Top Down Causation

Models in which causation arises from higher level structures as well as from microdynamics may be relevant to unifying quantum theory with classical physics or general relativity. They also give a way of defining a form of panprotopsychist property dualism, in which consciousness and material physics causally affect one another. I describe probabilistic toy models based on cellular automata that illustrate possibilities and difficulties with these ideas.
Predicting Bike-Sharing Traffic Flow using Machine Learning

Bike-Sharing Systems (BSSs) have rapidly grown in popularity worldwide in recent years. The driving forces of this explosive growth are attributed to access to modern ubiquitous technology, increased urbanization, a desire to decrease pollution, and the need for flexible and integrated mobility in city environments. However, in order to keep BSSs in a balanced state where bikes and stations are readily available for users, companies are seeking ways to accurately predict future demand. This project aims to objectively compare and evaluate various machine learning algorithms for the problem of predicting cluster-level BSS traffic flow. All models are evaluated using two different station clustering techniques, zone-based and grid-based, representing ways to group stations both with and without expert knowledge of the system. Furthermore, this thesis presents a rigorous state-of-the-art review of current research on demand prediction in BSSs and other on-demand transport services. Random Forest (RF), Feed-Forward Neural Network (FFNN) and Deep Residual Network (ResNet) emerged as the most promising models from this review, and were therefore implemented. Additionally, this thesis presents the first evaluation of using Recurrent Neural Networks within the context of BSSs demand prediction. FFNN proved to be the most successful model, reaching 21.1% and 36.65% improvements over the best baseline using grid-basedand zone-based clustering respectively. The developed system is designed to run in a cloud production environment, and elaborations are made as to how it can be extended to handle real-time streaming data from Oslo City Bike users.
University of Southern Denmark The Cost-Effectiveness of Conventional Discectomy Compared to Other Surgical Techniques for Lumbar Disk Herniation

Background: The current study reviews the literature on the cost-effectiveness of conventional diskectomy compared to other surgical techniques, by assessing studies with economical evaluation and studies using proxy measures of cost-effectiveness. Methods: In April 2016, a comprehensive search was conducted in Medline, Embase and the Cochrane Database. Reference lists of retrieved articles were perused for further relevant publications. Randomized controlled trials and comparison studies, comparing conventional diskectomy to other surgical interventions for patients with lumbar disk herniation, were included and reviewed by the authors. Data were gathered on the methodology of the studies, including study design, randomization, follow-up period, cost-estimation, etc. and the quality of the published studies was quantified using a modified version of the Drummond checklist. Results: Twenty-four articles were included in the review, 9 retrieved from the original search, and an additional 15 from reference lists. Four studies included an economical evaluation and 20 reported proxy measures of cost-effectiveness. The quality of studies varied considerably and results were ambiguous; the four economic studies favored conventional diskectomy, but none were randomized trials. Of the twenty proxy studies some favored the alternatives, and some reported no clear difference. Conclusions: The available literature does not allow for strong conclusions due to the sparsity of high quality economic studies. The available evidence, however, suggests that any cost-effectiveness difference between conventional diskectomy and the alternatives is unlikely to be great. Correspondence to: Thorsen MTH, Faculty of Health Sciences, University of Southern Denmark, Campusvej 55, 5000 Odense M, Denmark, Tel: +47 936 18 222; E-mail: Mayt101@yahoo.no
Effects of earthworms and white-tailed deer on roots, arbuscular mycorrhizae, and forest seedling performance.

Changes in understory plant composition and biodiversity declines in northeastern North American forests are widespread. Preserving species and ecosystem function requires appropriate identification and management of important stressors. Co-existence of stressors, among them earthworm invasions and white-tailed deer, make correct identification of mechanisms that cause diversity declines challenging. We used an established factorial experiment to assess survival and growth of native seedlings (Actaea pachypoda, Aquilegia canadensis, Cornus racemosa, Quercus rubra and Prenanthes alba) in response to presence/absence of deer and earthworms. We expected deer and earthworms to reduce seedling survival and biomass, and we evaluated potential pathways to explain this impact (soil N and P concentrations and pools, root architecture, and arbuscular mycorrhizal fungi [AMF] colonization). We developed structural equation models (SEM) to identify specific pathways through which earthworms and deer were impacting plant species with different life histories. Seedling survival was not affected by our treatments nor the plant and soil variables we tested. Actaea biomass was smaller in earthworm-invaded plots, and with larger total N pools. In contrast, both deer and earthworm treatments were associated with lower soil nutrient concentrations, and earthworm invaded plots had smaller N and extractable P pools. Actaea, Cornus, Prenanthes and Quercus seedlings had a lower proportion of fine roots in earthworm-invaded plots, while fine roots in Aquilegia made up a higher proportion of the root system. AMF colonization in Quercus was reduced in sites colonized by earthworms, but AMF in other species were unaffected. Our SEMs showed high correlation among soil variables, but because we do not know which variables are drivers of this change and which are the passengers, we can only conclude that they are changing together as deer and earthworms exert their respective influence. Different plant species responded in idiosyncratic ways to earthworm and deer effects on soil fertility, root architecture and limited effects on AMF colonization. While earthworm and deer-mediated changes to fine roots, soil nutrients, and AMF may lead to changes in plant performance over time, these changes rarely translated to lower plant performance in our seedlings.
Fire affects the taxonomic and functional composition of soil microbial communities, with cascading effects on grassland ecosystem functioning

Fire is a crucial event regulating the structure and functioning of many ecosystems. Yet few studies have focused on how fire affects taxonomic and functional diversities of soil microbial communities, along with changes in plant communities and soil carbon (C) and nitrogen (N) dynamics. Here, we analyze these effects in a grassland ecosystem 9 months after an experimental fire at the Jasper Ridge Global Change Experiment site in California, USA. Fire altered soil microbial communities considerably, with community assembly process analysis showing that environmental selection pressure was higher in burned sites. However, a small subset of highly connected taxa was able to withstand the disturbance. In addition, fire decreased the relative abundances of most functional genes associated with C degradation and N cycling, implicating a slowdown of microbial processes linked to soil C and N dynamics. In contrast, fire stimulated above‐ and belowground plant growth, likely enhancing plant–microbe competition for soil inorganic N, which was reduced by a factor of about 2. To synthesize those findings, we performed structural equation modeling, which showed that plants but not microbial communities were responsible for significantly higher soil respiration rates in burned sites. Together, our results demonstrate that fire ‘reboots’ the grassland ecosystem by differentially regulating plant and soil microbial communities, leading to significant changes in soil C and N dynamics.
Prediction of adverse outcomes in nursing home residents according to intrinsic capacity proposed by the World Health Organization.

BACKGROUND This study aimed to evaluate the predictive value of the domains of intrinsic capacity (i.e. cognition, locomotion, sensory, vitality and psychosocial) proposed by the WHO on the 3-year adverse health outcomes of nursing home residents. METHODS A 3-year incidence of mortality, falls, repeated falls and autonomy decline (i.e. a one-unit increase in the Katz score) was assessed in a cohort of Belgian nursing home residents. Cognition was assessed using the MMSE. For locomotion, balance, gait speed and chair stand performance were evaluated by the SPPB test. The sensory domain was measured using the Strawbridge questionnaire for audition and vision. For vitality, abdominal circumference, BMI, nutritional status (by MNA) and handgrip strength were assessed. Psychosocial status was evaluated by the EQ-5D and the CES-D scale. Missing data were handled by multiple imputations. Cox proportional hazard models, logistic regressions and ANOVA were used for the analyses. RESULTS In the multivariable model, a one-unit increase in balance performance and in the nutrition score decreased the probability of death by 12% (HR=0.88; 95% CI 0.78-0.99) and 4% (HR=0.96; 95% CI 0.93-0.99), respectively. The risk of falling decreased when there was a one-unit increase in balance performance (HR=0.87, 95% CI 0.79-0.96) and in the nutrition score (HR=0.96, 95% CI 0.93-0.98). No association was found for intrinsic capacity and repeated falls. Low scores in nutrition (OR=0.86, 95% CI 0.77-0.96) were associated with a higher probability of autonomy decline. CONCLUSION Some domains of intrinsic capacity predicted health outcomes among nursing home residents. Nutrition and balance should be regularly checked among this population.
Effects of Carbohydrate Mouth Rinsing on Upper Body Resistance Exercise Performance.

Carbohydrate mouth rinsing has been shown to enhance aerobic exercise performance, but there is limited research with resistance exercise (RE). Therefore, the purpose of this investigation was to examine the effects of carbohydrate mouth rinsing during a high-volume upper body RE protocol on performance, heart rate responses, ratings of perceived exertion, and felt arousal. Recreationally experienced resistance-trained males (N = 17, age: 21 ± 1 years, height: 177.3 ± 5.2 cm, mass: 83.5 ± 9.3 kg) completed three experimental sessions, with the first serving as familiarization to the RE protocol. During the final two trials, the participants rinsed a 25-ml solution containing either a 6% carbohydrate solution or an artificially flavored placebo in a randomized, counterbalanced, and double-blinded fashion. The participants rinsed a total of nine times immediately before beginning the protocol and 20 s before repetitions to failure with the exercises bench press, bent-over row, incline bench press, close-grip row, hammer curls, skull crushers (all completed at 70% one-repetition maximum), push-ups, and pull-ups. Heart rate, ratings of perceived exertion, and felt arousal were measured at the baseline and immediately after each set of repetitions to failure. There were no differences for the total repetitions completed (carbohydrate = 203 ± 25 repetitions vs. placebo = 201 ± 23 repetitions, p = .46, Cohen's d = 0.10). No treatment differences were observed for heart rate, ratings of perceived exertion, or felt arousal (p > .05). Although carbohydrate mouth rinsing has been shown to be effective in increasing aerobic performance, the results from this investigation show no benefit in RE performance in resistance-trained males.
Neuropsychological, Psychiatric, and Functional Correlates of Clinical Trial Enrollment

Screen failure rates in Alzheimer’s disease (AD) clinical trial research are unsustainable, with participant recruitment being a top barrier to AD research progress. The purpose of this project was to understand the neuropsychological, psychiatric, and functional features of individuals who failed screening measures for AD trials. Previously collected clinical data from 38 patients (aged 50–83) screened for a specific industry-sponsored clinical trial of MCI/early AD (Biogen 221AD302, [EMERGE]) were analyzed to identify predictors of AD trial screen pass/fail status. Worse performance on non-memory cognitive domains like crystalized knowledge, executive functioning, and attention, and higher self-reported anxiety, was associated with failing the screening visit for the EMERGE AD clinical trial, whereas we were not able to detect a relationship between screening status and memory performance, self-reported depression, or self-reported daily functioning. By identifying predictors of AD trial screen passing/failure, this research may influence decision-making about which patients are most likely to successfully enroll in a trial, thereby potentially lowering participant burden, maximizing study resources, and reducing costs.
Cognitive Distance and Research Output in Computing Education: A Case-Study

Contribution: This paper quantifies the phenomenon of more versus better research output in computing research education and elaborates on how the organizational variable known as cognitive distance plays a fundamental role in mediating such more versus better research output relation. Background: To improve the current educational system, investigation and quantification is needed of the “silos. ” Cognitive distance—a measure of the differences in background, culture, and expertise between collaborators—may be a factor influencing the lack of quality and variety in research outputs. Addressing this is a key enabler for fruitful collaboration. Research Question: Does collaboration with similarly expert researchers yield better research? Methodology: A quantitative survey provides baseline data for cognitive distance while publication data allowed creation of a co-authorship network between 123 researchers in a European computing research department. The network was analyzed through quantitative and qualitative research methods. Findings: Increased expertise overlaps across sub-fields of computing is a strong predictor for further collaboration (quantity), but research impact (quality) decreases with larger overlaps. This reveals an educational silo effect in doctoral computing education and, consequently, a flaw in the connected research output. The lack of a single, agreed way to evaluate research impact across sub-fields further hinders cross-departmental collaboration among doctoral students. Conclusion: Three recommendations emerge for policy makers and educational leaders: 1) departments should be cross-functional and focused on societal interests; 2) communities of practice should be created at the level of doctoral education and upward; and 3) departments should hold matchmaking and speed-meeting events regularly within and across institutions.
Robust Data Association for Object-level Semantic SLAM

Simultaneous mapping and localization (SLAM) in an real indoor environment is still a challenging task. Traditional SLAM approaches rely heavily on low-level geometric constraints like corners or lines, which may lead to tracking failure in textureless surroundings or cluttered world with dynamic objects. In this paper, a compact semantic SLAM framework is proposed, with utilization of both geometric and object-level semantic constraints jointly, a more consistent mapping result, and more accurate pose estimation can be obtained. Two main contributions are presented int the paper, a) a robust and efficient SLAM data association and optimization framework is proposed, it models both discrete semantic labeling and continuous pose. b) a compact map representation, combining 2D Lidar map with object detection is presented. Experiments on public indoor datasets, TUM-RGBD, ICL-NUIM, and our own collected datasets prove the improving of SLAM robustness and accuracy compared to other popular SLAM systems, meanwhile a map maintenance efficiency can be achieved.
Free space transmission lines in receiving antenna operation

This work derives exact expressions for the voltage and current induced into a two conductors non isolated transmission lines by an incident plane wave. The methodology is to use the transmission line radiating properties to derive scattering matrices and make use of reciprocity to derive the response to the incident wave. The analysis is in the frequency domain and it considers transmission lines of any small electric cross section, incident by a plane wave from any incident direction and any polarisation. The analytic results are validated by successful comparison with ANSYS commercial software simulation results, and compatible with other published results.
Learning Compact Models for Planning with Exogenous Processes

We address the problem of approximate model minimization for MDPs in which the state is partitioned into endogenous and (much larger) exogenous components. An exogenous state variable is one whose dynamics are independent of the agent's actions. We formalize the mask-learning problem, in which the agent must choose a subset of exogenous state variables to reason about when planning; doing planning in such a reduced state space can often be significantly more efficient than planning in the full model. We then explore the various value functions at play within this setting, and describe conditions under which a policy for a reduced model will be optimal for the full MDP. The analysis leads us to a tractable approximate algorithm that draws upon the notion of mutual information among exogenous state variables. We validate our approach in simulated robotic manipulation domains where a robot is placed in a busy environment, in which there are many other agents also interacting with the objects. Visit this http URL for a supplementary video.