Miracle-dz/UniFAR-FTUs huggingface dataset:
Observing the behavioural effects of methylphenidate in children and adolescents with ASD-ADHD dual diagnosis: A mini review

Research aim The aim of this study is to focus on the main neurophysiological aspects of attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) and the current pharmacological treatment used for the management of hyperactivity and attention deficits in children aged 6-20 years with a diagnosis of ASD, not associated with other genetic or epileptic disorders, such as Fragile X Syndrome (FXS), Tuberous Sclerosis, Kleefstra Syndrome or Angelman Syndrome. Methods This mini review was conducted according to the P.I. C.O. model and according to the PRISMA guidelines. The keywords used were: autism spectrum disorder; attention deficit hyperactivity disorder; attention deficit disorder; methylphenidate; ritalin; ADHD; youth autism; childhood autism; childhood autism spectrum disorder; adolescent autism. The strings produced were compared and selected by a third independent clinician. The PubMed and PsycArticles search yielded a total of 3,200 articles. For their inclusion, the 3,200 articles were examined by two clinicians who ultimately selected 28 (15 clinical trials and 13 reviews/meta-analyses) articles analysed according to their consistency with the inclusion and exclusion criteria. Conclusions Three main aspects emerged from the review: (1) According to the existing literature, new randomized controlled trials are needed to ensure a better understanding of the most effective drug treatments for dual-diagnosed ASD-ADHD patients and of the related behavioural effects. Currently, the use of drugs varies depending on psychiatric comorbidity, symptoms, age and gender and there is no univocal reference therapy; (2) Methylphenidate (MPH) has currently been shown to be the most suitable drug for the treatment of hyperactivity and inattention in individuals diagnosed with ASD and ADHD; (3) There is a need to create and evaluate appropriate tests to analyse more specific patterns of behaviour presented in the two conditions.
A Generalized Model for Curved Nanobeams Incorporating Surface Energy

This work presents a comprehensive model for nanobeams, incorporating beam curvature and surface energy. Gurtin–Murdoch surface stress theory is used, in conjunction with Euler–Bernoulli beam theory, to model the beams and take surface energy effects into consideration. The model was validated by contrasting its outcomes with experimental data published in the literature on the static bending of fixed–fixed and fixed–free nanobeams. The outcomes demonstrated that surface stress alters the stiffness of both fixed–fixed and fixed–free nanobeams with different behaviors in each case.
Exact Solutions Of The Self-Duality Equations On The Minkowski Space-Time

A SU(2) Gauge Theory with spherical symmetry over the Minkowski space-time is considered. The self-duality equation of the gauge fields are written and their solutions are obtained. Two exact solutions, one of which is statical and another of dynamical type are given. All the calculations are performed using an analytical program written in GRTensor computer algebra package, which runs on the MapleV platform.
The problem of automatic classification of pictures using an intelligent decision-making system based on the knowledge graph and fine-grained image analysis

In order to prevent the illegal export of paintings abroad, a museum examination using various methods for studying a work of art is carried out. At the same time, an analysis is also made of historical, art history, financial and other information and documents confirming the painting’s authenticity — provenance. Automation of such examination is hampered by the need to take into account numerical values of visual features, quality indicators, and verbal descriptions from provenance. In this paper, we consider the problem of automatic multi-task classification of paintings for museum expertise. A system architecture is proposed that checks provenance, implements a fine-grained image analysis (FGIA) of visual image features, and automatically classifies a painting by authorship, genre, and time of creation. Provenance is contained in a knowledge graph; for its vectorization, it is proposed to use a graph2vec type encoder with an attention mechanism. Fine-grained image analysis is proposed to be performed using searching discriminative regions (SDR) and learning discriminative regions (LDR) allocated by convolutional neural networks. To train the classifier, a generalized loss function is proposed. A data set is also proposed, including provenance and images of paintings by European and Ukrainian artists.
An efficient algorithm for computing the triple correlation

The triple correlation C[k,m] is of the class of higher-order statistics and is used in a number of signal processing applications. Its computational requirements are of the order of K.M. N (the maximum lags and the number of data points respectively) and in any practical situation this amounts to a significant burden. The algorithm we present in this paper exploits the redundancy of the product terms to derive a factored expression for C[k,m] that results in a reduced number of multiplications (and overall operations). The savings depend on the relationships between the 2 lags and the number of data samples. Details for each case are provided and numerical examples illustrate the algorithm's effectiveness.
Collective Relational Clustering

In many clustering problems, in addition to attribute data, we have relational information, linking different data points. In this chapter, we focus on the problem of collective relational clustering that makes use of both attribute and relational information. The approach is collective in that clustering decisions are not taken in an independent fashion for each pair of data points. Instead, the different pairwise decisions depend on each other. The first set of dependencies is among multiple decisions involving the same data point. The other set of dependencies come from the relationships. Decisions for any two references that are related in the data are also dependent on each other. Hence, the approach is collective as well as relational. We focus on the entity resolution problem as an application of the clustering problem, and we survey different proposed approaches that are collective or make use of relationships. One of the approaches is an agglomerative greedy clustering algorithm where the cluster similarity measure combines both attributes and relationships in a collective way. We discuss the algorithmic details of this approach and identifying data characteristics that influence its correctness. We also present experimental results on multiple real-world and synthetic data sets.
Assessment of the Pharmacokinetics, Disposition, and Duration of Action of the Tumour-Targeting Peptide CEND-1

CEND-1 (iRGD) is a bifunctional cyclic peptide that can modulate the solid tumour microenvironment, enhancing the delivery and therapeutic index of co-administered anti-cancer agents. This study explored CEND-1’s pharmacokinetic (PK) properties pre-clinically and clinically, and assessed CEND-1 distribution, tumour selectivity and duration of action in pre-clinical tumour models. Its PK properties were assessed after intravenous infusion of CEND-1 at various doses in animals (mice, rats, dogs and monkeys) and patients with metastatic pancreatic cancer. To assess tissue disposition, [3H]-CEND-1 radioligand was administered intravenously to mice bearing orthotopic 4T1 mammary carcinoma, followed by tissue measurement using quantitative whole-body autoradiography or quantitative radioactivity analysis. The duration of the tumour-penetrating effect of CEND-1 was evaluated by assessing tumour accumulation of Evans blue and gadolinium-based contrast agents in hepatocellular carcinoma (HCC) mouse models. The plasma half-life was approximately 25 min in mice and 2 h in patients following intravenous administration of CEND-1. [3H]-CEND-1 localised to the tumour and several healthy tissues shortly after administration but was cleared from most healthy tissues by 3 h. Despite the rapid systemic clearance, tumours retained significant [3H]-CEND-1 several hours post-administration. In mice with HCC, the tumour penetration activity remained elevated for at least 24 h after the injection of a single dose of CEND-1. These results indicate a favourable in vivo PK profile of CEND-1 and a specific and sustained tumour homing and tumour penetrability. Taken together, these data suggest that even single injections of CEND-1 may elicit long-lasting tumour PK improvements for co-administered anti-cancer agents.
Multiple Structures and Hartshorne's Conjecture

The purpose of this article is to develop tools for producing multiple structures on smooth varieties, based on the theory for curves by Bǎnicǎ and Forster [1, 2]. By recursively extending schemes, we show how all Cohen–Macaulay scheme structures of this kind can be found. Similar results have been obtained by Manolache [12, 15-17], using a different recursive construction. The construction in this article complements Manolache's methods, and for some of the applications we have in mind, our construction gives more flexibility [18, 19]. As an application of the theory, we reformulate Hartshorne's Conjecture on complete intersections in codimension two in terms of multiple schemes of degrees two and three.
Photonic crystal fibres with large nonlinear coefficients

We investigate the upper limits on the nonlinear coefficients obtainable in various silica-based photonic crystal fibre designs. For a fixed wavelength, the highest nonlinearities are found to occur when a substantial part of the field energy resides in air. The case of a silica strand in air is found to constitute an upper bound on the nonlinear coefficients obtained; however, all the designs investigated allow nonlinear coefficients larger than 50% of this limiting value. On the other hand, the choice of fibre design is found to have a significant influence on the dispersion properties.
Understanding Software‐centered Evolutive Ecosystems through Activity Theory

This paper proposes an interdisciplinary approach aimed to bring into practice some novel Software Engineering theoretical paradigms. The premise of these news paradigms is based on the idea of “ecologies” as realities that take place in the environment of a Software product. These “ecologies” are understood as tight but flexible interactions between the human, social, and technical components involved, where Software is just another component. However, the theoretical paradigms discussed do not offer a viable way to make sense of these ecologies into the practice of Software design and development. Thus, as a more operationalized approach, this paper proposes a framework based on Networks of Activities, a concept derived from Activity Theory, as a resource to help in the design, development, and evolution of these new emergent complex socio‐technical ecologies. This framework has been conceived as a tool for the design, capture, and, especially, to analyze the evolution of these ecologies. The concepts and notations used by the proposed approach are illustrated through a proof of concept that shows the essential ideas and their use in real scenarios. In this way, the concepts discussed contribute to the improvement of related fields like Requirements Engineering, Human‐Computer Interaction, or Software Architecture, among others.
Mechanical properties of polyimide coated optical fibers at elevated temperatures

High temperature mechanical strength and reliability of optical fibers have become important subjects as optical fibers are increasingly used for harsher environments. Theories and models of fiber mechanical properties established for traditional telecommunications applications may need to be validated for applications at elevated temperatures. In this paper, we describe the test setup for high temperature tensile strength of fiber and report initial results of dynamic tensile strength of polyimide coated optical fiber at 300 and 350ºC for different heating time intervals. The results are compared with room temperature strength data, data available in the literature, and our earlier work on thermogravimetric analysis (TGA) weight loss of the polyimide coating and the observations on surface morphology at elevated temperatures. Interesting observations are discussed and possible explanations are proposed.
Rallying around the unwaved flag: national identity and Sweden’s controversial Covid strategy

Abstract During the Covid-19 pandemic, Sweden soon found itself alone and heavily criticised for its internationally deviant strategy. Why did this approach nevertheless receive widespread public support in Sweden? This article develops and tests a novel rally around the flag (RRTF) theory, which places national identity centre stage. In contrast to previous work, the article differentiates between national pride, national chauvinism, uncritical patriotism, national attachment, and ethnic nationhood conception – expecting only the first three of these to be related to supporting the Swedish Covid approach. Survey data from a politically representative sample of Swedes support the expectations. It is concluded that the popular support for the ‘Swedish experiment’ is to be understood as an RRTF – although in this case the flag was ‘unwaved’. This suggests that even national identities that draw their pride from institutional rather than cultural superiority lend themselves to RRTF processes.
Co-regulation of Sox9 and TGFβ1 transcription factors in mesenchymal stem cells regenerated the intervertebral disc degeneration

Background Intervertebral disc (IVD) shows aging and degenerative changes earlier than any other body connective tissue. Its repair and regeneration provide a considerable challenge in regenerative medicine due to its high degree of infrastructure and mechanical complexity. Mesenchymal stem cells, due to their tissue resurfacing potential, represent many explanatory pathways to regenerate a tissue breakdown. Methods This study was undertaken to evaluate the co-regulation of Sox9 and TGFβ1 in differentiating human umbilical cord mesenchymal stem cells (hUC-MSC) into chondrocytes. The combinatorial impact of Sox9 and TGFβ1 on hUC-MSCs was examined in vitro by gene expression and immunocytochemical staining. In in vivo, an animal model of IVD degeneration was established under a fluoroscopic guided system through needle puncture of the caudal disc. Normal and transfected MSCs were transplanted. Oxidative stress, pain, and inflammatory markers were evaluated by qPCR. Disc height index (DHI), water content, and gag content were analyzed. Histological examinations were performed to evaluate the degree of regeneration. Results hUC-MSC transfected with Sox9+TGFβ1 showed a noticeable morphological appearance of a chondrocyte, and highly expressed chondrogenic markers (aggrecan, Sox9, TGFβ1, TGFβ2, and type II collagens) after transfection. Histological observation demonstrated that cartilage regeneration, extracellular matrix synthesis, and collagen remodeling were significant upon staining with H&E, Alcian blue, and Masson's trichrome stain on day 14. Additionally, oxidative stress, pain, and inflammatory markers were positively downregulated in the animals transplanted with Sox9 and TGFβ1 transfected MSCs. Conclusion These findings indicate that the combinatorial effect of Sox9 and TGFβ1 substantially accelerates the chondrogenesis in hUC-MSCs. Cartilage regeneration and matrix synthesis were significantly enhanced. Therefore, a synergistic effect of Sox9 and TGFβ1 could be an immense therapeutic combination in the tissue engineering of cartilaginous joint bio-prostheses and a novel candidate for cartilage stabilization.
Using hybrid integrated InP-Si3N4 diode lasers for the generation of sub-GHz repetition rate frequency combs

Optical frequency combs based on broadband-gain bulk lasers, due to the low intrinsic linewidth and sub-GHz repetition rates, have gained tremendous interest for applications such as high-resolution spectroscopy, dual-comb spectroscopy or LIDAR. However, susceptibility to mechanical and acoustic perturbations, the complexity of optical pumping and the larger physical size of these lasers has motivated research toward chip-based integrated extended cavity diode lasers with low-loss Si3N4 waveguide feedback circuits for low repetition rates. In diode lasers, mode-locking via saturable absorbers is generally used for generating frequency combs, however, the short upper-state carrier lifetime results in repetition rates of at least a few GHz. Here, we demonstrate absorber-free, passive mode-locking as well as hybrid mode-locking at sub-GHz repetition rates using a long Si3N4 feedback circuit with three highly frequency-selective microring resonators for extending the cavity roundtrip length to more than 0.6 m. This enables frequency-domain mode-locking in the form of a continuous wave, with a line spacing of around 500 MHz. Hybrid mode-locking, in addition to passive mode-locking, is demonstrated by adding a weak AC drive current with a frequency close to 500 MHz. This stabilizes the repetition rate and reduces the Gaussian component of the laser’s RF linewidth attaining a negligible Lorentzian component. Our numerical simulations predict that further lowering of the repetition rate and line spacings might be achievable with further cavity length extension.
The Stressed Heart: A Case Report of Takotsubo Cardiomyopathy in a Patient With Known Coronary Artery Disease

Takotsubo cardiomyopathy and acute coronary syndrome are often clinically indistinguishable, making their differentiation challenging for physicians. We present a case of a 65-year-old female who presented with acute chest pain, shortness of breath, and a recent psychosocial stressor. This is a unique case in which our patient, with known history of coronary artery disease and recent percutaneous intervention, favored a misleading initial diagnosis of non-ST elevation myocardial infarction.
Acceleration of Bi-Objective Optimization of Data-Parallel Applications for Performance and Energy on Heterogeneous Hybrid Platforms

Accelerating the bi-objective optimization of applications for performance and energy is crucial to achieving energy efficiency objectives and meeting quality-of-service requirements in modern high-performance computing platforms and cloud computing infrastructures. In this work, we highlight the crucial challenges to accelerate model-based methods proposed for the bi-objective optimization of data-parallel applications for performance and energy that employ workload distribution between the executing processors as the decision variable. The methods solve unconstrained bi-objective optimization problems and take input, the processors’ performance and energy profiles in the form of discrete functions of workload size, and output Pareto-optimal solutions (workload distributions), minimizing the execution time and the total energy consumption of computations during the parallel execution of the application. One of the challenges is the fast computation of Pareto-optimal solutions. We then formulate the bi-objective optimization problem of data-parallel applications for performance and energy through workload distribution on a cluster of <inline-formula> <tex-math notation="LaTeX">$p$ </tex-math></inline-formula> identical hybrid nodes, each containing <inline-formula> <tex-math notation="LaTeX">$h$ </tex-math></inline-formula> heterogeneous processors. The state-of-the-art algorithm for solving the problem is sequential and takes exorbitant execution times to find Pareto-optimal solutions for even moderate numbers of processors. We propose two algorithms that address this shortcoming. The first algorithm is an exact sequential algorithm that is more efficient and amenable to parallelization and achieves a complexity reduction of <inline-formula> <tex-math notation="LaTeX">$\mathcal {O}(m \times h)$ </tex-math></inline-formula> over the state-of-the-art sequential algorithm where <inline-formula> <tex-math notation="LaTeX">$m$ </tex-math></inline-formula> is the cardinality of the input discrete execution time and dynamic energy functions. The second algorithm is a parallel algorithm executed by <inline-formula> <tex-math notation="LaTeX">$q$ </tex-math></inline-formula> identical parallel processes that reduces the complexity of our proposed sequential algorithm by <inline-formula> <tex-math notation="LaTeX">$\mathcal {O}(q)$ </tex-math></inline-formula>. It, therefore, achieves a complexity reduction of <inline-formula> <tex-math notation="LaTeX">$\mathcal {O}(m \times h \times q)$ </tex-math></inline-formula> over the state-of-the-art sequential algorithm. Finally, we experimentally analyze the practical efficacy of our proposed algorithms for two data-parallel applications, matrix multiplication and fast Fourier transform, on a heterogeneous hybrid node containing an Intel Haswell multicore CPU, an Nvidia k40c GPU, and an Nvidia P100 GPU and simulations of clusters of such hybrid nodes. The experiments demonstrate that our proposed algorithms provide tremendous speedups over state-of-the-art solutions.
Spaceflight alters reaction time and duration judgment of astronauts

We report a study on astronauts aimed at characterizing duration judgment before, during, and after long-duration stays on board the International Space Station. Ten astronauts and a control group of 15 healthy (non-astronaut) participants performed a duration reproduction task and a duration production task using a visual target duration ranging from 2 to 38 s. Participants also performed a reaction time test for assessing attention. Compared to control participants and preflight responses, the astronauts’ reaction time increased during spaceflight. Also, during spaceflight, time intervals were under-produced while counting aloud and under-reproduced when there was a concurrent reading task. We hypothesize that time perception during spaceflight is altered by two mechanisms: (a) an acceleration of the internal clock through the changes in vestibular inputs in microgravity, and (b) difficulties in attention and working memory when a concurrent reading task is present. Prolonged isolation in confined areas, weightlessness, stress related to workload, and high-performance expectations could account for these cognitive impairments.