Miracle-dz/UniFAR-FTUs huggingface dataset:
Large scale brain network dynamics in very preterm children and relationship with socio-emotional outcomes

Children born very preterm (VPT; < 32 completed weeks of gestation) are at high risk of neurodevelopmental and neurobehavioral difficulties associated with atypical brain maturation. The analysis of large-scale brain network dynamics during rest allows to investigate brain functional connectivity and their association with behavioural outcomes. Of interest, prematurity has been associated with atypical socio-emotional development with significant implications for the forming of peer relationships, adaptive functioning, academic achievement and mental health. In this study, we extracted dynamic functional connectivity by using the innovation-driven co-activation patterns (iCAPs) framework in preterm and full-term children aged 6 to 9 to explore changes in spatial organisation, laterality and temporal dynamics of spontaneous large-scale brain activity. Multivariate pattern analysis was used to explore potential biomarkers for socio-emotional difficulties in preterm children. Results show a spatial organisation of 13 networks retrieved comparable to full-term controls. Dynamic features and lateralisation of network brain activity were also comparable across groups for all large-scale brain networks. Despite apparent similarities in terms of dynamical functional connectivity parameters, multivariate pattern analysis unveiled group differences in their associations with socio-emotional abilities. While a pattern of decreased engagement in certain brain networks were associated with better socio-emotional abilities in full-term controls; in the VPT group, better socio-emotional abilities were associated with coordination of activity across different networks, i.e., coupling duration between different pairs of networks. It is possible that group differences reflect reduced degree of maturation of functional architecture in the VPT group for socio-emotional abilities.
Application of Locally Developed Smart Learning Environments in the Teaching of Mathematics in Public Secondary Schools in Osun State, Nigeria

Challenges of teaching Mathematics include inadequate teachers, over reliance on the talk and chalk method of teaching and inadequate use of instructional materials. These resulted in poor academic performance among secondary school students in Osun State, Nigeria. This study therefore determined the effect of locally developed smart learning environments on secondary school students’ academic achievement in Mathematics and if there is significant interaction between sex and the modes of teaching. The study employed pretest posttest control nonequivalent group design. Seventy five (75) students were selected across a randomly selected senatorial district in the state using a multistage sampling procedure. A Mathematics Achievement Test (MAT) was used at the pretest and the posttest. Items with IDI > 0.3 were removed during validation. Content Validity Ratio (α = 1) was also obtained for the remaining 20 items in the achievement test. Analysis of data showed no significant difference in the academic achievement of students exposed to the SLE and those taught with the talk and chalk method (F (1,74) = 0.05 ; p = 0.83). Results also showed that the interaction between sex and the mode of instruction is not significant (F (1,74) = 0.21 ; p = 0.65).
Semi Supervised NCC: Introducing Prior Knowledge To Normalized Cut Clustering

Clustering plays a pivotal role in exploratory data analysis, especially in scenarios where prior knowledge about a subset of samples is available, prompting a rapid development of Semi-supervised clustering approaches. In this work, we introduce a novel method for seamlessly integrating prior knowledge into the widely recognized Normalized Cut Clustering (NCC) algorithm, thereby oﬀering a natural extension within the realm of semi-supervised clustering. Similarly to NCC, the solution of the proposed method is spectral-based in the form of an inhomogeneous eigenvalue problem. Also, we show that the proposed method can be seen as a generalization of NCC, enhancing its applicability in scenarios where prior information is available. In addition, we design an adequate and comprehensive experimental setup. This setup not only tests the competitiveness of our approach but also showcases its superiority in terms of performance metrics.
Impact of first-line infliximab on the pharmacokinetics of second-line vedolizumab in inflammatory bowel diseases

Background Very little is known about the impact of the wash-out period on the pharmacokinetics of a second-line biologic. Objective The objective of this article is to explore the impact of two different wash-out periods on the pharmacokinetics of vedolizumab and infliximab. Methods Patients switching from infliximab to vedolizumab were retrospectively identified. The population was divided into two groups according to wash-out period: <6 weeks or >6 weeks. Vedolizumab and infliximab trough levels (TLs) were determined and correlated with clinical and biological outcomes. Results A total of 71 inflammatory bowel disease patients were included. At week 6, in patients previously treated with infliximab, median vedolizumab TLs were 21.9 µg/ml and 24.9 µg/ml for the <6 weeks and >6 weeks wash-out period, respectively (p = 0.31), whereas median residual infliximab TLs were 0.5 µg/ml and 0 µg/ml (p = 0.034). The rate of treatment discontinuation was similar (p = 0.64), and the infectious events were six and two for the <6 weeks and >6 weeks wash-out period, respectively (p = 0.12) by week 30. Conclusions This study suggests clinicians may not need to be concerned about the impact of wash-out period on the pharmacokinetics of the second-line biologic when switching infliximab to vedolizumab. More data are required on the impact of wash-out period on safety.
Microﬂuidic elongation of viscous droplets at vanishing interfacial tension

The microﬂow behavior of liquid-liquid dispersions is experimentally investigated in the presence of miscible ﬂuid additives. Original microﬂuidic methods are developed to characterize the dynamic response of mobile droplets to a local change of interfacial tension with the external phase using sequential injections and stratiﬁed ﬂows. Various oil-alcohol combinations are examined to unravel out-of-equilibrium ﬂuid interactions at short timescales and clarify the role of ﬂow rates and ﬂuid properties on individual droplet deformations. Functional relationships are developed to characterize the initial droplet strain as well as rates of elongation during immersion and submersion stages in hydrodynamic focusing junctions. It is shown, in particular, that the droplet deformation process is highly nonlinear with the initial droplet size and that droplet growth coefﬁcients remain constant for ﬂuid additives having ultralow interfacial tension. Overall, this study shows the possibility to manipulate the morphology of strongly elongated droplets to enhance oil interfacial area in miscible organic solvents using microchannels.
How Can We Increase the Nutrition-Related Knowledge in Children Aged 7–12 Years: Results of Focus Groups Interviews with Parents—Junior-Edu-Żywienie (JEŻ) Project

Nutrition education is a long-term process that should cover various population groups. A special focus should be placed on children, adolescents and their parents. The aim of this research was to find out the opinions of parents of primary school pupils aged 7–12 on their expectations towards school education in the areas of food and nutrition, addressed to both pupils and their parents. The research was conducted among 101 parents of primary school pupils with the use of the Focus Group Interview (FGI) method. It demonstrated that what is most needed are hands-on activities relating to basic theoretical issues. While parents see the need for nutrition education for their children, educating pupils in this area is of interest to only some of the respondents for whom nutrition aspects are quite important. All parents would like formal nutrition education at school, but at the same time, they do not want classes to take up too much of their children’s time, due to the already excessive number of school subjects. It seems appropriate to include everyone in regard to nutrition education, regardless of their declared interest in this issue. The need for consistent presentation of educational content addressed to teachers and parents is very important, so that they can, in a uniform way, shape the attitudes towards food and nutrition of children and adolescents.
Quantifying evaporation and its decadal change for Lake Nam Co, central Tibetan Plateau

Most lakes in the interior Tibetan Plateau have expanded rapidly since the late 1990s. Because of a lack of observations, lake water balances and their changes are far from well understood. Evaporation is a component of the lake water balance, and this study quantifies its magnitude, decadal change, and its contribution to the water balance changes in Lake Nam Co, one of the largest lakes on the Tibetan Plateau (with an area of approximately 2000 km2 and a mean depth of approximately 40 m). The lake temperature and the evaporation are simulated by the Flake model. The simulation results are validated against observed lake temperature profile from 2013 and Moderate Resolution Imaging Spectroradiometer lake surface temperature data from 2000 to 2014. The simulated latent heat flux and sensible heat flux are validated against Bowen ratio‐derived estimates for 2013. Based on the validated simulation results, the long‐term mean annual evaporation is approximately 832 ± 69 mm, and this value is much less than the potential evaporation estimated using the Penman‐Monteith equation. The annual evaporation from 1980 to 2014 displays a complex decadal oscillation, mainly due to the changes in energy‐related terms (air temperature and radiation). The mean lake evaporation since the late 1990s is greater than previous periods; thus, this change in evaporation has suppressed the recent expansion of Nam Co.
Measuring Policy Performance in Online Pricing with Offline Data

The problems of online pricing with offline data, or other similar general online decision making with offline data problems, have observed increasing interests especially in operational research. To evaluate pricing policies when offline data are available, the decision maker can either position herself at the time point when the offline data are already observed and viewed as deterministic, or at the time point before the offline data are generated. We specifically discuss how and why these two positions are relevant to policy evaluations, from a worst-case perspective and a Bayesian perspective. We then use a simple online pricing with offline data setting to illustrate the constructions of optimal policies for these two approaches and discuss their differences.
Fully Automated Closed-Loop Insulin Delivery vs. Semi-Automated Hybrid Control in Pediatric Patients with Type 1 Diabetes using an Artificial Pancreas

Objective: The most promising beta-cell replacement therapy for children with type 1 diabetes is a “closed-loop” (CL) artificial pancreas incorporating continuous glucose sensors and insulin pumps. The Medtronic MiniMed ePID System combines an external pump and sensor with a variable insulin infusion rate algorithm designed to emulate the physiological characteristics of the β -cell. However, delays in insulin absorption associated with subcutaneous route of delivery inevitably lead to large post-prandial glucose excursions. Research Design and Methods: We studied the feasibility of the Medtronic ePID system in youth with type 1 diabetes and hypothesized that small manual pre-meal “priming” boluses would reduce post-prandial excursions during CL control. 17 adolescents (age 15.9 ± 1.6 y, A1c 7.1 ± 0.8%) underwent 34 hours of closed-loop (CL) control; 8 with full CL control (FCL), and 9 with “hybrid” CL (pre-meal priming bolus, HCL). Results: Mean glucose levels were 135 ± 45 mg/dL in the HCL group vs. 141 ± 55 mg/dL in the FCL group (p=0.09); day-time glucose levels averaged 149 ± 47 mg/dL in the HCL group vs. 159 ± 59 mg/dL in the FCL group (p=0.03). Peak post-prandial glucose levels averaged 194 ± 47 mg/dL in the HCL group, vs. 226 ± 51 mg/dL in the FCL group (p=0.04). Night-time control was similar in both groups (111 ± 27 vs. 112 ± 28 mg/dL). Conclusions: CL glucose control using an external sensor and insulin pump provides a means to achieve near normal glucose concentrations in youth with type 1 diabetes during the overnight period. The addition of small manual “priming” bolus doses of insulin, given 15 min before meals, improves post-prandial glycemic excursions.
A Fast Iterative Solution of the Time-harmonic Wave Equation with MSSS-preconditioned IDR(s)

For the Full Waveform Inversion in frequency-domain, the fast numerical solution of the time-harmonic wave equation is required. For large three-dimensional problems, the problem size exceeds several million of unknowns, and a short-recurrence Krylov method such as IDR(s) is used to solve linear systems of this size. Especially for high-frequency simulations, an efficient preconditioner needs to be applied in order to speed-up convergence. In our presentation, we introduce a new preconditioner for the time-harmonic wave equation that exploits the hierarchical structure of the discretized problem. We use multilevel sequentially semiseparable (MSSS) matrix computations for the approximate inversion of the preconditioner. For large three-dimensional problems, we present a memory-efficient modification of the MSSS preconditioner that resembles the approximate solution of a sequence of two-dimensional problems. We conclude our presentation with numerical examples for the time-harmonic wave equation in both acoustic and elastic media, and in two and three spatial dimensions.
networks Græmlin : General and robust alignment of multiple large interaction data

data Supplementary http://www.genome. org/cgi/content/full/gr.5235706/DC1 "Supplemental Research Data" P<P Published online August 9, 2006 in advance of the print journal. IOA Freely available online through the Genome Research Open Access option. service Email alerting click here top right corner of the article or Receive free email alerts when new articles cite this article sign up in the box at the Notes
The Role of Facial and Speech Features in Emotion Classification

In this study, we investigate the role of facial and speech features in improving the accuracy of emotion classification methods. First, we evaluate the performance of state-of-the-art models in speech and facial emotion classification, ranging from computationally intensive ones to those employing efficient feature extraction techniques. We also evaluate the utility of partial facial features (eyes and mouth) when a complete video feed is not feasible. Our empirical results reveal that incorporating both modalities consistently improves emotion classification accuracy, surpassing single-modality benchmarks. In particular, for efficient models, we observe the most significant improvement, with nearly a 10% increase in multi-modal accuracy. This insight is especially useful for devices with limited video feed and computing power, like head-mounted displays (HMDs). Interestingly, our findings indicate that speech is more adept at classifying certain emotions, whereas facial features excel in others. This also highlights the intrinsic advantages of a multi-modal approach, offering a more comprehensive understanding of emotion classification.
Detection of aircraft traces in nighttime all-sky camera images using deep learning

All-sky cameras imagery is employed in Satellite Laser Ranging (SLR) stations during operations to gather information about the observing conditions, typically as an sky awareness tool for operators. Due to the emission of laser light towards the sky in the SLR technique, it is a priority to ensure aerial safety prior to and during operations. For this purpose, a range of techniques are employed, such as active radars, cameras, airplane spotters operating kill-switches, and Automatic Dependent Surveillance-Broadcast (ADS-B) receivers. Thanks to the aviation regulatory environment in many parts of the world, which mandates the equipment of ADS-B for a broad set of aircraft, these devices are nowadays very popular in SLR stations. ADS-B is a cooperative surveillance technology wherein an aircraft determines its position through satellite navigation and transmits it periodically, enabling its precise tracking. Currently, the primary limitation with this technology is that not all aircraft are required to equip it, which calls for alternative detection systems. In this work we demonstrate the automatic detection of aircraft using neural networks to analyse nighttime images from an all-sky camera, and propose that such a system can provide complementary information to that obtained with ADS-B, therefore increasing the safety of the operations.
Afﬁnity-based measures of biomarker performance evaluation

We propose new summary measures of biomarker accuracy which can be used as companions to existing diagnostic accuracy measures. Conceptually, our summary measures are tantamount to the so-called Hellinger afﬁnity and we show that they can be regarded as measures of agreement constructed from similar geometrical principles as Pearson correlation. We develop a covariate-speciﬁc version of our summary index, which practitioners can use to assess the discrimination performance of a biomarker, conditionally on the value of a predictor. We devise nonparametric Bayes estimators for the proposed indexes, derive theoretical properties of the corresponding priors, and assess the performance of our methods through a simulation study. The proposed methods are illustrated using data from a prostate cancer diagnosis study.
Nutritional status assessment – a professional responsibility in community nursing It is challenging for community nurses to screen their patients * nutritional risk because the guidelines fail to take sufficient account of the domestic arena

Results: Management support is important for the implementation of systematic nutritional screening. The nurses suggested that their familiarity with the patients and their nutritional needs is an important factor with respect to organising the practical arrangements in the home. The nurses felt it was challenging to assess the patient’s intake of food and drink around the clock. They found themselves in the field of tension between preserving the home dweller’s autonomy, complying with the recommendations for systematic nutritional screening and coping with
The permissible and the forbidden ✩

In many economic situations, neither prices nor authority rules. Rather, individual behavior is governed by social norms that specify what is allowed (socially acceptable) and what is forbidden (socially unacceptable). These norms can emerge in a decentralized way and can serve as a method to bring order to economic situations. The key component of our solution concept is a uniform permissible set which plays a role parallel to that of a price system in competitive equilibrium. The concept is analyzed and applied to a variety of economic and social settings. © 2020 Elsevier Inc. All rights reserved.
Eye Tracker Experiment Buying Decision-Making Process with a Focus on Sustainable Consumption - Case Study

Today's environmentally damaging activities pose global challenges for companies, environmentalists and governments alike, but these activities are also reflected at the level of the individual. The aim of the study is to investigate the decision-making processes of Hungarian consumers regarding sustainable products and to validate the eye-trackers methodology to measure this. Two groups (n=10), one educated on sustainable products and one without prior education, were observed using Tobii Glasses 3 eye trackers while purchasing sustainable items in a local supermarket. The research uses a mixed-methods approach combining qualitative and quantitative methods. Participants completed pre-shopping questionnaires to gauge their attitudes toward ecologically responsible consumption. Post-shopping interviews provided insights into their decision-making processes. As a result of the research, Hungarian consumers are not aware of sustainable products overall, and based on the interviews, they only buy a small proportion of them. Members of the experimental group (5.03 min) were much quicker to find sustainable products than members of the control group (8.03 min). Logos suggesting sustainability are misleading to consumers, and they are most easily able to identify
Implicit learning and tacit knowledge : an essay on the cognitive unconscious

In this new volume in the Oxford Psychology Series, the author presents a highly readable account of the cognitive unconscious, focusing in particular on the problem of implicit learning. Implicit learning is defined as the acquisition of knowledge that takes place independently of the conscious attempts to learn and largely in the absence of explicit knowledge about what was acquired. One of the core assumptions of this argument is that implicit learning is a fundamental, "root" process, one that lies at the very heart of the adaptive behavioral repertoire of every complex organism. The author's goals are to outline the essential features of implicit learning that have emerged from the many studies that have been carried out in a variety of experimental laboratories over the past several decades; to present the various alternative perspectives on this issue that have been proposed by other researchers and to try to accommodate these views with his own; to structure the literature so that it can be seen in the context of standard heuristics of evolutionary biology; to present the material within a functionalist approach and to try to show why the experimental data should be seen as entailing particular epistemological perspectives; and to present implicit processing as encompassing a general and ubiquitous set of operations that have wide currency and several possible applications. Chapter 1 begins with the core problem under consideration in this book, a characterization of "implicit learning" as it has come to be used in the literature. Reber puts this seemingly specialized topic into a general framework and suggests a theoretical model based on standard heuristics of evolutionary biology. In his account, Reber weaves a capsule history of interest in and work on the cognitive unconscious. Chapter 2 turns to a detailed overview of the experimental work on the acquisition of implicit knowledge, which currently is of great interest. Chapter 3 develops the evolutionary model within which one can see learning and cognition as richly intertwining issues and not as two distinct fields with one dominating the other. Finally, Chapter 4 explores a variety of entailments and speculations concerning implicit cognitive processes and their general role in the larger scope of human performance