Miracle-dz/UniFAR-FTUs huggingface dataset:
The feasibility, acceptability and preliminary efficacy of a low-cost, virtual-reality based, upper-limb stroke rehabilitation device: a mixed methods study

Abstract Purpose: To establish feasibility, acceptability, and preliminary efficacy of an adapted version of a commercially available, virtual-reality gaming system (the Personalised Stroke Therapy system) for upper-limb rehabilitation with community dwelling stroke-survivors. Method: Twelve stroke-survivors (nine females, mean age 58 years, [standard deviation 7.1], median stroke chronicity 42 months [interquartile range 34.7], Motricity index 14–25 for shoulder and elbow) were asked to complete nine, 40-min intervention sessions using two activities on the system over 3 weeks. Feasibility and acceptability were assessed through a semi-structured interview, recording of adverse effects, adherence, enjoyment (using an 11-point Likert scale), and perceived exertion (using the BORG scale). Assessments of impairment (Fugl–Meyer Assessment Upper extremity), activity (ABILHAND, Action Research Arm Test, Motor Activity Log-28), and participation (Subjective Index of Physical and Social Outcome) were completed at baseline, following intervention, and at 4-week follow-up. Data were analysed using Thematic Analysis of interview and intervention field-notes and Wilcoxon Signed Ranks. Side-by-side displays were used to integrate findings. Results: Participants received between 175 and 336 min of intervention. Thirteen non-serious adverse effects were reported by five participants. Participants reported a high level of enjoyment (8.1 and 6.8 out of 10) and rated exertion between 11.6 and 12.9 out of 20. Themes of improvements in impairments and increased spontaneous use in functional activities were identified and supported by improvements in all outcome measures between baseline and post-intervention (p < 0.05 for all measures). Conclusions: Integrated findings suggested that the system is feasible and acceptable for use with a group of community-dwelling stroke-survivors including those with moderately-severe disability. Implications for rehabilitation To ensure feasibility of use and maintenance of an appropriate level of challenge, gaming technologies for use in upper-limb stroke rehabilitation should be personalised, dependent on individual need. Through the use of hands-free systems and personalisation, stroke survivors with moderate and moderately-severe levels of upper-limb impairment following stroke are able to use gaming technologies as a means of delivering upper-limb rehabilitation. Future studies should address issues of acceptability, feasibility, and efficacy of personalised gaming technologies for delivery of upper-limb stroke rehabilitation in the home environment. Findings from this study can be used to develop future games and activities suitable for use in stroke rehabilitation.
Effect of Lactobacillus salivarius on growth performance, diarrhea incidence, fecal bacterial population and intestinal morphology of suckling pigs challenged with F4+ enterotoxigenic Escherichia coli

Objective Gut health improvements were monitored with respect to growth performance, diarrhea incidence, fecal bacterial population and intestinal morphology of suckling pigs orally supplemented with live Lactobacillus salivarius (L. salivarius) oral suspensions and challenged with F4+ enterotoxigenic Escherichia coli (ETEC). Methods Two groups of newborn pigs from 18 multiparous sows were randomly designated as non-supplemented (control: n = 114 piglets) and L. salivarius supplemented groups (treatment: n = 87 piglets). Treatment pigs were orally administered with 2 mL of 109 colony-forming unit (CFU)/mL L. salivarius on days 1 to 3, then they were orally administered with 5 mL of 109 CFU/mL L. salivarius on days 4 to 10, while those in control group received an equal amount of phosphate buffered saline solution. On day 24 (2 weeks post supplementation), one pig per replicate of both groups was orally administered with 108 CFU/mL F4+ ETEC, then they were euthanized on day 29 of experiment. Results Results revealed that pigs in treatment group had a statistically significant increase in average daily gain, body weight and weight gain, and tended to lower diarrhea throughout the study. Numbers of Lactobacillus population in feces of treatment pigs were higher than control pigs, especially on day 10 of study. Numbers of total bacteria in intestinal contents of control pigs were also increased, but not Coliform and Lactobacillus populations. Histological examination revealed statistically significant improvements of villous height and villous/crypt ratio of duodenum, proximal jejunum and distal jejunum parts of treatment pigs compared with controls. Duodenal pH of treatment group was significantly decreased. Conclusion Oral supplementation of live L. salivarius during the first 10 days of suckling pig promoted growth performance and gut health, reduced diarrhea incidence, increased fecal Lactobacillus populations and improved intestinal morphology.
Improvement of Moderate Resolution Land Use and Land Cover Classification by Introducing Adjacent Region Features

Landsat-like moderate resolution remote sensing images are widely used in land use and land cover (LULC) classification. Limited by coarser resolutions, most of the traditional LULC classifications that are based on moderate resolution remote sensing images focus on the spectral features of a single pixel. Inspired by the spatial evaluation methods in landscape ecology, this study proposed a new method to extract neighborhood characteristics around a pixel for moderate resolution images. 3 landscape-metric-like indexes, i.e., mean index, standard deviation index, and distance weighted value index, were defined as adjacent region features to include the surrounding environmental characteristics. The effects of the adjacent region features and the different feature set configurations on improving the LULC classification were evaluated by a series of well-controlled LULC classification experiments using K nearest neighbor (KNN) and support vector machine (SVM) classifiers on a Landsat 8 Operational Land Imager (OLI) image. When the adjacent region features were added, the overall accuracies of both the classifiers were higher than when only spectral features were used. For the KNN and SVM classifiers that used only spectral features, the overall accuracies of the LULC classification were 85.45% and 88.87%, respectively, and the accuracies were improved to 94.52% and 96.97%. The classification accuracies of all the LULC types improved. Highly heterogeneous LULC types that are easily misclassified achieved greater improvements. As comparisons, the grey-level co-occurrence matrix (GLCM) and convolutional neural network (CNN) approaches were also implemented on the same dataset. The results revealed that the new method outperformed GLCM and CNN approaches and can significantly improve the classification performance that is based on moderate resolution data.
The a´ velocity in the tissue Doppler predicts S/D ratio <1 in patients with a normal ejection fraction

Abstract Objectives. To compare the ability of the a´ velocity and the e´ velocity in predicting a dominant diastolic pulmonary vein flow (S/D ratio <1) in patients with normal ejection fraction. Design. We retrospectively evaluated the diastolic function according to the ASE/EACVI guidelines, the S/D ratio and the septal, lateral and average a´ velocity in 293 unselected in-hospital patients, aged 39–86 years, in sinus rhythm and with no or mild valve disease, having a normal systolic function (EF >50%). Results. There was a good linear correlation between the S/D ratio and the a´ velocity, but a tendency towards a negative correlation between the S/D ratio and the e´ velocity. S/D ratio <1 was seen in 43 patients. These patients had a significantly lower a´ velocity compared to those with S/D-ratio ≥1, septal (6,1 ± 2,4 v 8,8 ± 2,1 cm/s; p < .001) and lateral (6,0 ± 2,6 v 9,3 ± 2,5 cm/s; p < .001) No significant difference was seen in the septal e´ velocity (6,8 ± 2,4 v 6,8 ± 2,1 cm/s), lateral e´ velocity (9,4 ± 2,6 v 9,1 ± 2,8 cm/s) or in the ejection fraction (58,6 ± 4,4% v 58,7 ± 4,0%). A diastolic dysfunction was present in 62 patients, normal diastolic function in 231 patients. The a´ velocity was significantly lower in patients with S/D ratio <1 in both groups (p < .01). Conclusion. The a´ velocity is superior to the e´ velocity in predicting S/D ratio <1 in patients with normal ejection fraction regardless the ASE/EACVI diastolic classification. A failing left atrium seems to be the explanation.
Uma importante revisão sobre o impacto de agroquímicos da cultura de arroz em peixes

Na lavoura arrozeira, o uso de agroquimicos no controle de plantas daninhas e insetos e recomendado para garantir maior produtividade. Entretanto, sua utilizacao pode acarretar uma serie de efeitos em organismos nao alvos, como os peixes. Deste modo, esta revisao tem como objetivo analisar os dados existentes sobre os efeitos dos agroquimicos utilizados no cultivo de arroz em peixes, de modo a propor estrategias que minimizem seu impacto. Existe grande variacao entre os agroquimicos testados quanto a toxicidade, sendo a determinacao da concentracao letal mediana em 96 horas apenas uma estimativa inicial para estudos adicionais, uma vez que para muitos deles concentracoes inferiores podem provocar alteracoes bioquimicas nos tecidos dos peixes, as quais se mostram mais efetivas como biomarcadores. Para minimizar o impacto dos agroquimicos deve-se utilizar sempre a dose minima recomendada, e manter estatica a lâmina de agua do cultivo por um periodo minimo de duas semanas apos a aplicacao, de modo que o principio ativo seja degradado, reduzindo a toxicidade. Alem disso, o manejo integrado de pragas e recomendando, bem como a rizipiscicultura, a qual evita a utilizacao dos agroquimicos e em alguns casos pode promover um rendimento semelhante.
Implications of possible interpretations of ‘greenhouse gas balance’ in the Paris Agreement

The main goal of the Paris Agreement as stated in Article 2 is ‘holding the increase in the global average temperature to well below 2°C above pre-industrial levels and pursuing efforts to limit the temperature increase to 1.5°C’. Article 4 points to this long-term goal and the need to achieve ‘balance between anthropogenic emissions by sources and removals by sinks of greenhouse gases'. This statement on ‘greenhouse gas balance’ is subject to interpretation, and clarifications are needed to make it operational for national and international climate policies. We study possible interpretations from a scientific perspective and analyse their climatic implications. We clarify how the implications for individual gases depend on the metrics used to relate them. We show that the way in which balance is interpreted, achieved and maintained influences temperature outcomes. Achieving and maintaining net-zero CO2-equivalent emissions conventionally calculated using GWP100 (100-year global warming potential) and including substantial positive contributions from short-lived climate-forcing agents such as methane would result in a sustained decline in global temperature. A modified approach to the use of GWP100 (that equates constant emissions of short-lived climate forcers with zero sustained emission of CO2) results in global temperatures remaining approximately constant once net-zero CO2-equivalent emissions are achieved and maintained. Our paper provides policymakers with an overview of issues and choices that are important to determine which approach is most appropriate in the context of the Paris Agreement. This article is part of the theme issue ‘The Paris Agreement: understanding the physical and social challenges for a warming world of 1.5°C above pre-industrial levels'.
Structure, variation, and assembly of the root-associated microbiomes of rice

Significance Land plants continuously contact beneficial, commensal, and pathogenic microbes in soil via their roots. There is limited knowledge as to how the totality of root-associated microbes (i.e., the microbiome) is shaped by various factors or its pattern of acquisition in the root. Using rice as a model, we show that there exist three different root niches hosting different microbial communities of eubacteria and methanogenic archaea. These microbial communities are affected by geographical location, soil source, host genotype, and cultivation practice. Dynamics of the colonization pattern for the root-associated microbiome across the three root niches provide evidence for rapid acquisition of root-associated microbiomes from soil, and support a multistep model wherein each root niche plays a selective role in microbiome assembly. Plants depend upon beneficial interactions between roots and microbes for nutrient availability, growth promotion, and disease suppression. High-throughput sequencing approaches have provided recent insights into root microbiomes, but our current understanding is still limited relative to animal microbiomes. Here we present a detailed characterization of the root-associated microbiomes of the crop plant rice by deep sequencing, using plants grown under controlled conditions as well as field cultivation at multiple sites. The spatial resolution of the study distinguished three root-associated compartments, the endosphere (root interior), rhizoplane (root surface), and rhizosphere (soil close to the root surface), each of which was found to harbor a distinct microbiome. Under controlled greenhouse conditions, microbiome composition varied with soil source and genotype. In field conditions, geographical location and cultivation practice, namely organic vs. conventional, were factors contributing to microbiome variation. Rice cultivation is a major source of global methane emissions, and methanogenic archaea could be detected in all spatial compartments of field-grown rice. The depth and scale of this study were used to build coabundance networks that revealed potential microbial consortia, some of which were involved in methane cycling. Dynamic changes observed during microbiome acquisition, as well as steady-state compositions of spatial compartments, support a multistep model for root microbiome assembly from soil wherein the rhizoplane plays a selective gating role. Similarities in the distribution of phyla in the root microbiomes of rice and other plants suggest that conclusions derived from this study might be generally applicable to land plants.
Atomic-resolution in-situ TEM Studies of Lithium Electrochemistry in Co3O4-Carbon Nanotube Nanocomposite

In typical charge and discharge cycling, electrodes may exhibit metastable phases with unusual ordering to repeatedly host and extract lithium-ion and electrons. This is a clear consequence of not enough time and/or energy available for such metastable phases to relax and transform into their equilibrium counterparts (1). Such metastable structures may exist only for a short duration, which makes it extremely difficult to measure or even identify them experimentally. Yet, they clearly play important roles in the battery figures of merit, such as cycling stability, voltage hysteresis, to capacity. The recent developments in in-situ transmission electron microscopy (TEM) (2-6) has enabled us to observe de/lithiation processes at atomic resolution, identify metastable phases and monitor their continuous phase transformation, with the gradual addition of lithium-ions and electrons into the battery electrodes. Structural models of these metastable phases are derived from full DFT simulations, and seem to corroborate with high resolution phase contrast simulated images as compared to corresponding experimental ones. Li-Co-O system represents one of the most important materials for lithium-ion battery with rich chemistry and structures, i.e. LiCoO2 has been used as intercalated cathode in the first commercialized battery by SONY, while Co3O4 and CoO are found to be high-capacity anode materials with conversion reaction: MxOy + 2y Li+ + 2y e= xM0 + yLi2O. Here, Co3O4 nanoparticles grown on highly conductive multi-wall carbon nanotubes (CNT) are employed as a model material system to study the structural evolutions with different amount of lithium inserted or reacted during electrochemical activation. The in-situ electrochemical lithiation experiments were followed until cobalt oxide nanoparticles are completely reduced into Co nanoparticles along with the formation of Li2O by conversion reaction and reverse de-lithiation until return back to cobalt oxide. When lithium-ions are introduced at lower rate, metastable lithium-inserted LixCo3O4 (x=1 to 5) crystalline phases are observed prior to formation of Co0 and Li2O clusters as the product of conversion reaction. At higher rate, lithium-ions can occupy any empty sites simultaneously that instantly break the Co3O4 spinel lattice bypassing the metastable crystalline phases. The amount of lithium-ions intake in a low rate is larger than that of the high rate, which provides insight on the charge/discharge rate and capacity relation. The presentation will cover intricacies of such metastable structures and the overall dynamics of electrochemical processes, as monitored by in-situ TEM imaging, spectroscopy and diffraction.
Speech Dereverberation Using Fully Convolutional Networks

Speech derverberation using a single microphone is addressed in this paper. Motivated by the recent success of the fully convolutional networks (FCN) in many image processing applications, we investigate their applicability to enhance the speech signal represented by short-time Fourier transform (STFT) images. We present two variations: a “U-Net” which is an encoder-decoder network with skip connections and a generative adversarial network (GAN) with U-Net as generator, which yields a more intuitive cost function for training. To evaluate our method we used the data from the REVERB challenge, and compared our results to other methods under the same conditions. We have found that our method outperforms the competing methods in most cases.
Differentiable Learning of Quantum Circuit Born Machine

Quantum circuit Born machines are generative models which represent the probability distribution of classical dataset as quantum pure states. Computational complexity considerations of the quantum sampling problem suggest that the quantum circuits exhibit stronger expressibility compared to classical neural networks. One can efficiently draw samples from the quantum circuits via projective measurements on qubits. However, similar to the leading implicit generative models in deep learning, such as the generative adversarial networks, the quantum circuits cannot provide the likelihood of the generated samples, which poses a challenge to the training. We devise an efficient gradient-based learning algorithm for the quantum circuit Born machine by minimizing the kerneled maximum mean discrepancy loss. We simulated generative modeling of the BARS-AND-STRIPES dataset and Gaussian mixture distributions using deep quantum circuits. Our experiments show the importance of circuit depth and the gradient-based optimization algorithm. The proposed learning algorithm is runnable on near-term quantum device and can exhibit quantum advantages for probabilistic generative modeling.
The Emerging Field of Epitranscriptomics in Neurodevelopmental and Neuronal Disorders

Analogous to DNA methylation and histone modifications, RNA modifications represent a novel layer of regulation of gene expression. The dynamic nature and increasing number of RNA modifications offer new possibilities to rapidly alter gene expression upon specific environmental changes. Recent lines of evidence indicate that modified RNA molecules and associated complexes regulating and “reading” RNA modifications play key roles in the nervous system of several organisms, controlling both, its development and function. Mutations in several human genes that modify transfer RNA (tRNA) have been linked to neurological disorders, in particular to intellectual disability. Loss of RNA modifications alters the stability of tRNA, resulting in reduced translation efficiency and generation of tRNA fragments, which can interfere with neuronal functions. Modifications present on messenger RNAs (mRNAs) also play important roles during brain development. They contribute to neuronal growth and regeneration as well as to the local regulation of synaptic functions. Hence, potential combinatorial effects of RNA modifications on different classes of RNA may represent a novel code to dynamically fine tune gene expression during brain function. Here we discuss the recent findings demonstrating the impact of modified RNAs on neuronal processes and disorders.
OF RELIABILITY AND FACTORS AFFECTING THE RELIABILITY

A reliable and valid measure is required for measuring the abstract characteristics. The reliability of the measures are affected by the length of the scale, definition of the items, homogeneity of the groups, duration of the scale, objectivity in scoring, the conditions of measuring, the explanation of the scale, the characteristics of the items in scale, difficulty of scale, and reliability estimation method. Those factors must be known and taken into account to construct a reliable scale.
The Plasmodium falciparum var gene switching rate, switching mechanism and patterns of parasite recrudescence described by mathematical modelling

Recrudescing Plasmodium falciparum parasitaemia is attributed to the switching of PfEMP1, a variant antigen family encoded by the var gene repertoire, and the host's immune response. We have developed a mathematical model which incorporates var gene switching, and variant specific, non-variant specific and non-specific immunity. By conducting a sensitivity analysis of the model we have defined the parameter limits which produce chronic and recrudescing infections. We explore 3 switching mechanisms: ordered, random and uncoupled switching. We show that if var genes switch on and off independently at variable rates through the repertoire a chronic clinical infection is predicted. The fastest switching-on rate that produces a chronic infection is 0·03% per generation. The model predicts that non-variant specific immunity plays an important role in reducing disease severity. This work illustrates the complex relationship between the malaria parasite and its host and shows that var gene switching at rates substantially slower than 2% are essential for parasite survival.
Constructing Temporal Abstractions Autonomously in Reinforcement Learning

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