Miracle-dz/UniFAR-FTUs huggingface dataset:
Activity Mapping of Children in Play Using Multivariate Analysis of Movement Events

Supplemental digital content is available in the text. ABSTRACT Purpose (i) To develop an automated measurement technique for the assessment of both the form and intensity of physical activity undertaken by children during play. (ii) To profile the varying activity across a cohort of children using a multivariate analysis of their movement patterns. Methods Ankle-worn accelerometers were used to record 40 min of activity during a school recess, for 24 children over five consecutive days. Activity events of 1.1 s duration were identified within the acceleration time trace and compared with a reference motif, consisting of a single walking stride acceleration trace, obtained on a treadmill operating at a speed of 4 km h−1. Dynamic time warping of motif and activity events provided metrics of comparative movement duration and intensity, which formed the data set for multivariate mapping of the cohort activity using a principal component analysis (PCA). Results The two-dimensional PCA plot provided clear differentiation of children displaying diverse activity profiles and clustering of those with similar movement patterns. The first component of the PCA correlated to the integrated intensity of movement over the 40-min period, whereas the second component informed on the temporal phasing of activity. Conclusions By defining movement events and then quantifying them by reference to a motion-standard, meaningful assessment of highly varied activity within free play can be obtained. This allows detailed profiling of individual children’s activity and provides an insight on social aspects of play through identification of matched activity time profiles for children participating in conjoined play.
Emetine exhibits anticancer activity in breast cancer cells as an antagonist of Wnt/β-catenin signaling

Emetine, an amoebicidal drug, exerts potent anticancer activity against various solid tumors, however, the underlying molecular mechanism remains unclear. In the present study, the effects of emetine were investigated on various proteins involved in the Wnt/β-catenin signaling pathway, which has been linked to various human cancers. It was revealed that emetine blocked Wnt/β-catenin signaling by targeting components of this pathway, including the low-density lipoprotein-receptor-related protein 6 (LRP6) and disheveled (DVL). Moreover, nanomolar concentrations of emetine decreased phosphorylation of these proteins and suppressed the expression of Wnt target genes, including fibronectin, frizzled-7 (Fzd7), c-Myc, Nanog and CD133 in MDA-MB-231 and MDA-MB-468 breast cancer cells. Additionally, emetine treatment induced apoptosis and suppressed the viability, migration, invasion, and sphere formation of breast cancer cells. Collectively the present results indicated that emetine antagonizes Wnt/β-catenin signaling, providing insight into the molecular mechanism underlying the anticancer activity of emetine.
Crystal structure of dl-dimethyl 2,3-dibenzamido-2,3-dimethylbutanedioate, C22H24N2O6

C22H24N2O6, monoclinic, P12 i / c l (No. 14), a = 10.982(2) Â, b = 9.440(1)À, c = 10.375(3)À, β = 111.06(1)°, V = 1003. 7Â , Z= 2, Rgl(F) = 0.074, wRTei(F) = 0.222, Τ =293 Κ. Source of material The title compound, as a mixture of isomers, was prepared from the reaction between di-fert-butyl peroxide and TV-benzoylalanine methyl ester in accord with literature methods [1,2], These were separated [3] and the analysed crystallographically to determine the structure of the particular isomer. Colourless crystals of the ^-isomer were obtained from the crystallisation of an ethyl acetate/hexane solution of the compound (mp 421.5 Κ 424 Κ). Discussion The molecule is centrosymmetric about the C2—C2' bond with d(C2—C2') = 1.566(4) A; i: -x, l-y, l-z. Significant elongation of the central bond was sought as a result of strain and stability of the product radicals that would form through bond scission but, this was not found in this structure nor in that of the meso isomer [4]· Table 1. Data collection and handling. Crystal: colourless cube, size 0.57 χ 0.57 χ 0.57 mm Wavelength: Mo Ka radiation (0.71069 A) μ: 1.00 cm" Diffractometer, scan mode: Rigaku AFC6R, ω/2θ 20max: 55 . 8° N(hkl)measured, N(hkl)unique: 2526 , 2 3 9 3 Criterion for I0bs, N(hkl)gt: U s > 2 a(Iobs), 1767 N(parani) refined: 137 Programs: teXsan [5], SHELXS-86 [6], SHELXL-97 [7], DIFABS [8], ORTEPII [9] o 9 Table 2. Atomic coordinates and displacement parameters (in A"). Atom Site X y ζ Ui so H(3) Ae 0 . 1 7 5 9 0 . 4 2 5 8 0 . 5084 0 . 057 H(lla) Ae 0 . 1 4 1 0 0 . 0466 0 . 6419 0 . 0 9 8 H(llb) Ae 0 . 2445 0 . 1586 0 . 6 3 6 9 0 . 0 9 8 H(llc) Ae 0 . 1 6 4 4 0 . 0736 0 . 5035 0 . 0 9 8 H ( 2 1 a ) Ae 0 . 1 1 8 9 0 . 5 7 6 3 0 . 2 7 9 4 0 . 0 7 8 H ( 2 1 b ) Ae 0 . 0 8 2 6 0 . 4 3 0 4 0 . 2305 0 . 078 H(21c) Ae 0 . 0 2 5 8 0 . 5 4 4 9 0 . 2945 0 . 078 H ( 4 2 ) Ae 0 . 3 4 9 0 0 . 3 9 0 5 0 . 5160 0 . 100 H ( 4 3 ) Ae 0 . 5 5 1 4 0 . 3 3 2 8 0 . 5141 0 . 115 H ( 4 4 ) Ae 0 . 6 6 1 2 0 . 1467 0 . 3 8 8 8 0 . 094 H ( 4 5 ) Ae 0 . 5 6 4 8 0 . 0 0 9 4 0 . 2729 0 . 097 H ( 4 6 ) Ae 0 . 3 6 7 4 0 . 0 7 2 3 0 . 2 6 2 3 0 . 079 * Correspondence author (e-mail: chmtert@nus.edu.sg) Current address: The National University of Singapore, Department of Chemistry, Singapore 117543
Early stages of sensorimotor map acquisition: learning with free exploration, without active movement or global structure.

One of the puzzles of learning to talk or play a musical instrument is how we learn which movement produces a particular sound: an audiomotor map. The initial stages of map acquisition can be studied by having participants learn arm movements to auditory targets. The key question is what mechanism drives this early learning. Three learning processes from previous literature were tested: map learning may rely on active motor outflow, (target) error correction and on the correspondence between sensory and motor distances (i.e. that similar movements map to similar sounds). Alternatively, we hypothesized that map learning can proceed without these. Participants made movements which were mapped to sounds in a number of different conditions that each precluded one of the potential learning processes. We tested whether map learning relies on assumptions about topological continuity by exposing participants to a permuted map that did not preserve distances in auditory and motor space. Further groups were tested who passively experienced the targets, kinematic trajectories produced by a robot arm, and auditory feedback as a yoked active participant (hence without active motor outflow). Another group made movements without receiving targets (thus without experiencing errors). In each case we observed substantial learning, therefore none of the three hypothesized processes is required for learning. Instead early map acquisition can occur with free exploration without target error correction, is based on sensory-to-sensory correspondences, and possible even for discontinuous maps. The findings are consistent with the idea that early sensorimotor map formation can involve instance-specific learning.
Septic Meningitis and Liver Abscess due to Hypermucoviscous Klebsiella pneumoniae Complicated with Chronic Strongyloidiasis in a Human T-lymphotropic Virus 1 Carrier

Recently, severe cases of infection due to hypermucoviscous Klebsiella pneumonia (hmKP) have been reported in Japan. The Amami Islands in Japan are also endemic regions for Strongyloides stercoralis. Disseminated strongyloidiasis strain often causes severe enterobacteria infection; however, whether or not chronic strongyloidiasis induces it remains unclear. We herein report a 71-year-old man who developed meningitis and liver abscess due to hmKP complicated with chronic strongyloidiasis. He died on the seventh hospital day. Strongyloides stercoralis were only found around the polyp in the cecum. Chronic strongyloidiasis can also induce severe infection due to enterobacteria, especially hypervirulent pathogens like hmKP, through the induction of mucosal rupture.
Learning Disorder Confers Setting-Specific Treatment Resistance for Children with ADHD, Predominantly Inattentive Presentation

Attention deficit/hyperactivity disorder–predominantly inattentive presentation (ADHD-I) and specific learning disorder (SLD) are commonly co-occurring conditions. Despite the considerable diagnostic overlap, the effect of SLD comorbidity on outcomes of behavioral interventions for ADHD-I remains critically understudied. The current study examines the effect of reading or math SLD comorbidity in 35 children with comorbid ADHD-I+SLD and 39 children with ADHD-I only following a behavioral treatment integrated across home and school (Child Life and Attention Skills [CLAS]). Pre- and posttreatment outcome measures included teacher-rated inattention, organizational deficits, and study skills and parent-rated inattention, organizational deficits, and homework problems. A similar pattern emerged across all teacher-rated measures: Children with ADHD-I and comorbid ADHD-I+SLD did not differ significantly at baseline, but between-group differences were evident following the CLAS intervention. Specifically, children with ADHD-I and comorbid ADHD-I+SLD improved on teacher-rated measures following the CLAS intervention, but children with ADHD-I only experienced greater improvement relative to those with a comorbid SLD. No significant interactions were observed on parent-rated measures—all children improved following the CLAS intervention on parent-rated measures, regardless of SLD status. The current results reveal that children with ADHD-I+SLD comorbidity benefit significantly from multimodal behavioral interventions, although improvements in the school setting are attenuated significantly. A treatment-resistant fraction of inattention was identified only in the SLD group, implying that this fraction is related to SLD and becomes apparent only when behavioral intervention for ADHD is administered.
Contrasting resistance and resilience to extreme drought and late spring frost in five major European tree species

Extreme climate events (ECEs) such as severe droughts, heat waves, and late spring frosts are rare but exert a paramount role in shaping tree species distributions. The frequency of such ECEs is expected to increase with climate warming, threatening the sustainability of temperate forests. Here, we analyzed 2,844 tree‐ring width series of five dominant European tree species from 104 Swiss sites ranging from 400 to 2,200 m a.s. l. for the period 1930–2016. We found that (a) the broadleaved oak and beech are sensitive to late frosts that strongly reduce current year growth; however, tree growth is highly resilient and fully recovers within 2 years; (b) radial growth of the conifers larch and spruce is strongly and enduringly reduced by spring droughts—these species are the least resistant and resilient to droughts; (c) oak, silver fir, and to a lower extent beech, show higher resistance and resilience to spring droughts and seem therefore better adapted to the future climate. Our results allow a robust comparison of the tree growth responses to drought and spring frost across large climatic gradients and provide striking evidence that the growth of some of the most abundant and economically important European tree species will be increasingly limited by climate warming. These results could serve for supporting species selection to maintain the sustainability of forest ecosystem services under the expected increase in ECEs.
The Impact of Public Health Expenditure on Health Outcomes in South Africa

Health holds an important position in maintaining economic development since it is both a prerequisite for and an outcome of economic development. This means that health contributes greatly to the attainment of sustainable development and health outcomes. The importance of health is demonstrated in the Millennium Development Goals (MDGs) where three of the eight goals are aimed at improving health outcomes. Despite progress made by other middle-income countries in achieving health-related MDGs, South Africa is still worse off in respect of health outcomes and experiences a challenge in attaining positive outcomes for these goals. This study’s main focus was to identify the association between public health expenditure and health outcomes in South Africa’s nine provinces from 2002 to 2016. The study implemented fixed effects and a random effects panel data estimation technique to control for time effects and individual provincial heterogeneity. This was followed by employing the Hausman specification test to identify the fixed effects model as the appropriate estimator for the study. The study also employed the seemingly unrelated regression (SUR) model and the least squares dummy variable (LSDV) model to examine the impact of public health expenditure on each province separately. The findings elucidated that the relationship between public health expenditure and health outcomes in South Africa varied across provinces depending on provincial management and infrastructure availability.
Untargeted metabolomics with multivariate analysis to discriminate hazelnut (Corylus avellana L.) cultivars and their geographical origin.

BACKGROUND In the present study, a metabolomic-based approach was used to discriminate different hazelnut cultivars as well as to trace their geographical origin. On this basis, ultra-high-pressure liquid chromatography coupled to quadrupole-time-of-flight mass spectrometry (UHPLC-ESI/QTOF-MS), able to profile phenolic and sterolic compounds, was set up. RESULTS Compounds identification was achieved thanks to accurate monoisotopic mass and isotopic pattern, against an in-house database. The screening approach was designed to discern 15 hazelnut cultivars and to discriminate the geographical origin of 6 cultivars originating from the four main growing regions (namely Chile, Georgia, Italy and Turkey). This approach allowed annotating more than 1000 compounds among polyphenols and sterols. The metabolomics data were elaborated with both unsupervised (hierarchical clustering) and supervised (Orthogonal Projections to Latent Structures Discriminant Analysis, OPLS-DA) statistics. These multivariate statistical tools allowed to discriminate hazelnut samples considering both 'cultivar-type' and 'geographical origin'. In particular, flavonoids (anthocyanins, flavanols and flavonols - VIP scores 1.34-1.49), phenolic acids (mainly hydroxycinnamics - VIP scores 1.35-1.55) together with cholesterol, ergosterol and stigmasterol derivatives (VIP scores 1.34-1.49) were the best markers to discriminate samples according to the geographical origin. CONCLUSIONS This work outlines the potential of untargeted profiling of phenolics and sterols based on UHPLC-ESI/QTOF mass spectrometry to discriminate hazelnut and support authenticity and origin. This article is protected by copyright. All rights reserved.
Analyzing Knowledge Structure Research with LDA Model

: [ Objective ] This paper aims to comprehensively explore the knowledge structure and hotspot distribution of different disciplines, with the help of topic extraction and distribution analysis using LDA (Latent Dirichlet Allocation) model from the perspective of subject classification. [ Methods ] We collected data from the domestic knowledge flow (KF) field and KF related literature from CNKI and Wangfang database, then grouped these data into 11 categories by Chinese Library Classification. Finally, we extracted 20 hot subjects from documents in 11 disciplines with the help of the LDA topic model. [ Results ] The content and knowledge points in 11 disciplines were obtained from the analysis of 20 extracted hot topics. [ Limitations ] We did not compare the proposed method with topic mining research in other fields. The domestic KF hotspots found by our study were not compared to the previous findings. [ Conclusions ] The proposed method can help us explore the knowledge structure and research trends more comprehensively.
The Elusive Path Toward Measuring Health Outcomes: Lessons Learned From a Pseudo-Randomized Controlled Trial of a Large-Scale Mobile Health Initiative

Mobile health (mHealth) offers new opportunities to improve access to health services and health information. It also presents new challenges in evaluating its impact, particularly in linking the use of a technology intervention that aims to improve health behaviors with the health outcomes that are impacted by changed behaviors. The availability of data from a multitude of sources (paper-based and electronic) provides the conditions to facilitate making stronger connections between self-reported data and clinical outcomes. This commentary shares lessons and important considerations based on the experience of applying new research frameworks and incorporating maternal and child health records data into a pseudo-randomized controlled trial to evaluate the impact of mMitra, a stage-based voice messaging program to improve maternal, newborn, and child health outcomes in urban slums in India.
Matrix product state decomposition in machine learning and signal processing

There has been a surge of interest in the study of multidimensional arrays, known as tensors. This is due to the fact that many real-world datasets can be represented as tensors. For example, colour images are naturally third-order tensors, which include two indices (or modes) for their spatial index, and one mode for colour. Also, a colour video is a fourth-order tensor comprised of frames, which are colour images, and an additional temporal index. Traditional tools for matrix analysis does not generalise so well in tensor analysis. The main issue is that tensors prescribe a natural structure, which is destroyed when they are vectorised. Many mathematical techniques such as principal component analysis (PCA) or linear discriminant analysis (LDA) used extensively in machine learning rely on vectorised samples of data. Additionally, since tensors may often be large in dimensionality and size, vectorising these samples and applying them to PCA or LDA may not lead to the most efficient results, and the computational time of the algorithms can increase significantly. This problem is known as the so-called curse of dimensionality. Tensor decompositions and their interesting properties are needed to circumvent this problem. The Tucker (TD) or CANDECOMP/PARAFAC (CP) decompositions have been predominantly used for tensor-based machine learning and signal processing. Both utilise common factor matrices and a core tensor, which retains the dimensionality of the original tensor. A main problem with these type of decompositions is that they essentially rely on an unbalanced matricization scheme, which potentially converts a tensor to a highly unbalanced matrix, where the row size is attributed to always one mode and the column size is the product of the remaining modes. This method is not optimal for problems that rely on retaining as much correlations within the data, which is very important for tensor-based machine learning and signal processing. In this thesis, we are interested in utilising the matrix product state (MPS) decomposition. MPS has the property that it can retain much of the correlations xvii within a tensor because it is based on a balanced matricization scheme, which consists of permutations of matrix sizes that can investigate the different correlations amongst all modes of a tensor. Several new algorithms are proposed for tensor object classification, which demonstrate an MPS-based approach as an efficient method against other tensor-based approaches. Additionally, new methods for colour image and video completion are introduced, which outperform the current state-of-the-art tensor completion algorithms.
Downregulation of microRNA‐129‐5p increases the risk of intervertebral disc degeneration by promoting the apoptosis of nucleus pulposus cells via targeting BMP2

miR‐129‐5p is implicated in many diseases, such as laryngeal cancer and breast cancer. In this study, we studied the mechanism underlying the role of BMP2 in intervertebral disc degeneration (IDD). We used a luciferase assay system to determine the relationship between BMP2 and miR‐129‐5 expression. In addition, Western blot and real‐time PCR were used to confirm the regulatory relationship between miR‐129‐5p and its targets, while flow cytometry was used to evaluate the effect of miR‐129‐5p on the apoptosis of neural progenitor cells (NPCs). BMP2 was confirmed as a direct target of miR‐129‐5p. Furthermore, the expression of miR‐129 was downregulated along with upregulated BMP2 expression in IDD patients. Meanwhile, BMP2 was validated as the target of miR‐129‐5p in cells transfected with miR‐129‐5p and BMP2 siRNA. Also, compared with NPCs transfected with blank/scramble controls or miR‐129‐5p inhibitors, the NPCs treated with miR‐129‐5p mimics or BMP2 siRNA exhibited evidently elevated viability and inhibited apoptosis. The data demonstrated that miR‐129‐5p was poorly expressed in IDD patients, and the dysregulation of miR‐129‐5p might contribute to the development of IDD by targeting BMP2 expression.
eBay's Buy-It-Now Function: Who, When, and How

This paper utilizes field experiment methodology and market data to study the “Buy-it-Now” (BIN) function in a series of eBay coin auctions. BIN auctions are typically listed by sellers with higher reputations. The probability an auction will end BIN increases with seller reputation and is not significantly affected by negative comments. Auctions listed by new sellers average lower prices and are less likely to end BIN. Buyer use of the BIN option increases as the BIN price decreases. We find that price is directly related to seller reputation, though not affected by negative comments, and is negatively related to buyer reputation. This result is driven by those auctions that start with a BIN price.
Biomolecules extraction from coffee and cocoa by- and co-products using Deep Eutectic Solvents.

BACKGROUND Coffee pulp (CP), cocoa husk (CH), and pod husk (CPH) are the main agro-residues from coffee and cocoa industries. They are sources of useful biomolecules, such as phenolic compounds, fibers, and alkaloids, among others. In this study, different compositions of deep eutectic solvents (DES) were investigated as a green and sustainable extraction media, with respect to their extraction capacity. The extraction yields were evaluated using heat stirring assisted extraction (HSE) or ultrasound-probe assisted extraction (UPAE). RESULTS The results showed an important effect of the DES composition. Choline chloride (ChCl) based-DES were the most effective, specifically lactic acid:ChCl (2:1 mole ratio), and the extraction capacity of DES was higher with UPAE (3 min/constant duty cycle (200 W)), in comparison with HSE (1h / 30 min). Chlorogenic acid, caffeine, and theobromine were identified as the main bioactive compounds. Interestingly, under specific conditions, DES allowed the formation of a molecule, identified as furfural by UPLC-MS, which could not be obtained using conventional extraction solvent (EtOH 70 % v/v). CONCLUSION DES showed a sustainability and high extraction capacity of biomolecules. In addition, their use as extraction solvents could lead to the formation and production of valuable building block molecules from plant biomass. This article is protected by copyright. All rights reserved.