Miracle-dz/UniFAR-FTUs huggingface dataset:
Application of unequal interval grey model in analysis of settlement data

Based on the settlement data from earth's surface and buildings around Zhu-Que building in Xi'an city, an unequal interval GM (1,1) in gray system is erected to model, analyze and forecast the data in this paper. And then the authors compare this model with the polynomial regression model. The result verifies the correctness, practicability and validity of GM (1,1) in analyzing settlement deformation of high building and surface.
A comparison of the effects of fire needle and routine acupuncture for myofascitis

Abstract Background: Myofascitis is a common disease in clinic. The main cause of the disease is aseptic inflammation of local muscles and connective tissues such as myofascial, which can be manifested as paralysis, distension, and other discomfort, local muscle stiffness, spasm or palpable strain-like nodules. Chinese medicine ascribes it to “bi disease” and “Arthralgia disease,” while Western medicine believes that the disease is mainly due to local muscle and fascia edema and exudation caused by trauma or long-term strain, forcing nerves to jam and producing pain and other abnormal feelings. Although the disease is not life-threatening, the pain and distension caused by local inflammatory stimuli can affect the patient's daily life and sleep quality. The purpose of this systematic review is to evaluate the efficacy of fire needle vs routine acupuncture in the treatment of myofascitis. Methods: Randomized controlled trials (RCTS) of fire needle vs routine acupuncture for myofascial inflammation will be comprehensively searched from inception to September 2020 on PubMed, Embase, Cochrane Library, China Biomedical Literature (CBM), China National Knowledge Infrastructure (CNKI), Chongqing VIP (CQVIP), and Wanfang. Additionally, RCT registered sites, including http://www.ClinicalTrials. gov and http://www.chictr. org.cn, also will be the search. Visual analogue scale (VAS) was used to score the pain before and after treatment. The primary outcome will be to compare the difference in pain scores between the 2 interventions. Two independent authors filtered the literature in the above database, extracted the data, and cross-checked it. Results: This study will offer a reasonable comprehensive evidence for the treatment of myofascitis with fire needle. Conclusion: The conclusion of this study will provide evidence to judge the effectiveness of fire needle on myofascitis. Registration number: INPLASY202080034.
Plant-on-a-chip: continuous, soilless electrochemical monitoring of salt uptake and tolerance among different genotypes of tomato

Tomatoes (Solanum lycopersicum), a high-value crop, exhibit a unique relationship with salt, where increased levels of NaCl can enhance flavor, aroma and nutritional quality but can cause oxidative damage and reduce yields. A drive for larger, better-looking tomatoes has reduced the importance of salt sensitivity, a concern considering that the sodium content of agricultural land is increasing over time. Currently, there are no simple ways of comparing salt tolerance between plants, where a holistic approach looking at [Na+] throughout the plant typically involves destructive, single time point measurements or expensive imaging techniques. Finding methods that collect rapid information in real time could improve the understanding of salt resistance in the field. Here we investigate the uptake of NaCl by tomatoes using TETRIS (Time-resolved Electrochemical Technology for plant Root environment In-situ chemical Sensing), a platform used to measure chemical signals in the root area of living plants. Low-cost, screen-printed electrochemical sensors were used to measure changes in salt concentration via electrical impedance measurements, facilitating the monitoring of the uptake of ions by roots. We not only demonstrated differences in the rate of uptake of NaCl between tomato seedlings under different growth conditions, but also showed differences in uptake between varieties of tomato with different NaCl sensitivities and the relatively salt-resistant “wild tomato” (Solanum pimpinellifolium) sister species. Our results suggest that TETRIS could be used to ascertain physiological traits of salt resistance found in adult plants but at the seedling stage of growth. This extrapolation, and the possibility to multiplex and change sensor configuration, could enable high-throughput screening of many hundreds or thousands of mutants or varieties.
EnhancerNet: a model for enhancer selection in dense regulatory networks recapitulates the dynamics of cell type acquisition

Understanding how cell identity is encoded in the genome and acquired during differentiation is a central challenge in cell biology. We derive a theoretical framework called “EnhancerNet” that models dense feedback networks involving transcription factors and enhancers, which can be parameterized from terminal cell identities without fitting unobserved variables. EnhancerNet recapitulates the dynamics of enhancer selection and cell type specification via two distinct pathways: direct reprogramming or differentiation through transient, multipotent progenitor states. These pathways capture the hallmarks of their respective counterparts in animal cells, with the model reproducing known reprogramming recipes and the complex hematopoietic differentiation hierarchy. Using EnhancerNet, we show that hierarchical progenitors emerge as transient states during differentiation and propose a method to predict their identity from terminal states. The model explains how new cell types could evolve and highlights the functional importance of distal regulatory elements with dynamic chromatin in multicellular evolution.
Intra-Striatal Dopaminergic Inter-Subject Covariance in Social Drinkers and Nontreatment-Seeking Alcohol Use Disorder Participants

One of the neurobiological correlates of alcohol use disorder (AUD) is the disruption of striatal dopaminergic function. While regional differences in dopamine (DA) function have been well studied, inter-regional relationships (represented as inter-subject covariance) have not been investigated and may offer a novel avenue for understanding DA function. Positron emission tomography (PET) data with [11C]raclopride in 22 social drinking controls and 17 AUD participants were used to generate group-level striatal covariance (partial Pearson correlation) networks, which were compared edgewise, also comparing global network metrics and community structure. An exploratory analysis examined the impact of tobacco cigarette use status. Striatal covariance was validated in an independent publicly available [18F]fallypride PET sample of healthy volunteers. Striatal covariance of control participants from both datasets showed a clear bipartition of the network into two distinct communities, one in the anterior and another in the posterior striatum. This organization was disrupted in the AUD participant network, with significantly lower network metrics in AUD compared to the control network. Stratification by cigarette use suggests differential consequences on group covariance networks. This work demonstrates that network neuroscience can quantify group differences in striatal DA and that its inter-regional interactions offer new insight into the consequences of AUD.
DeepSLICEM: Clustering CryoEM particles using deep image and similarity graph representations

Finding the 3D structure of proteins and their complexes has several applications, such as developing vaccines that target viral proteins effectively. Methods such as cryogenic electron microscopy (cryo-EM) have improved in their ability to capture high-resolution images, and when applied to a purified sample containing copies of a macromolecule, they can be used to produce a high-quality snapshot of different 2D orientations of the macromolecule, which can be combined to reconstruct its 3D structure. Instead of purifying a sample so that it contains only one macromolecule, a process that can be difficult, time-consuming, and expensive, a cell sample containing multiple particles can be photographed directly and separated into its constituent particles using computational methods. Previous work, SLICEM, has separated 2D projection images of different particles into their respective groups using 2 methods, clustering a graph with edges weighted by pairwise similarities of common lines of the 2D projections. In this work, we develop DeepSLICEM, a pipeline that clusters rich representations of 2D projections, obtained by combining graphical features from a similarity graph based on common lines, with additional image features extracted from a convolutional neural network. DeepSLICEM explores 6 pretrained convolutional neural networks and one supervised Siamese CNN for image representation, 10 pretrained deep graph neural networks for similarity graph node representations, and 4 methods for clustering, along with 8 methods for directly clustering the similarity graph. On 6 synthetic and experimental datasets, the DeepSLICEM pipeline finds 92 method combinations achieving better clustering accuracy than previous methods from SLICEM. Thus, in this paper, we demonstrate that deep neural networks have great potential for accurately separating mixtures of 2D projections of different macromolecules computationally.
Wearable Neural Interfaces: Real-Time Identification of Motor Neuron Discharges in Dynamic Motor Tasks

Objective Robustness to non-stationary conditions is essential to develop stable and accurate wearable neural interfaces. Approach We propose a novel adaptive electromyography (EMG) decomposition algorithm that builds on blind source separation methods by leveraging the Kullback-Liebler divergence and kurtosis of the signals as metrics for online learning. The proposed approach provides a theoretical framework to tune the adaptation hyperparameters and compensate for non-stationarities in the mixing matrix, such as due to dynamic contractions, and to identify the underlying motor neuron (MN) discharges. The adaptation is performed in real-time (∼22 ms of computational time per 100-ms batches). Main results The proposed adaptation algorithm significantly improved all decomposition performance metrics with respect to the absence of adaptation in a wide range of motion of the wrist (80°). The rate of agreement, sensitivity, and precision were ≥ 90% in ≥ 80% of the cases in both simulated and experimentally recorded data, according to a two-source validation approach. Significance The findings demonstrate the feasibility of accurately decoding MN discharges in real-time during dynamic contractions from wearable systems mounted at the wrist and forearm. Moreover, the study proposes an experimental validation method for EMG decomposition in dynamic tasks.
A retinotopic reference frame for space throughout human visual cortex

We perceive a stable visual world across eye movements, despite the drastic retinal transients these movements produce. To explain vision’s spatial stability, it has been suggested that the brain encodes the location of attended visual stimuli in an external, or spatiotopic, reference frame. However, spatiotopy is seemingly at odds with the fundamental retinotopic organization of visual inputs. Here, we probe the spatial reference frame of vision using ultra-high-field (7T) fMRI and single-voxel population receptive field mapping, while independently manipulating both gaze direction and spatial attention. To manipulate spatial attention, participants performed an equally demanding visual task on either a bar stimulus that traversed the visual field, or a small foveated stimulus. To dissociate retinal stimulus position from its real-world position the entire stimulus array was placed at one of three distinct horizontal screen positions in each run. We found that population receptive fields in all cortical visual field maps shift with the gaze, irrespective of how spatial attention is deployed. This pattern of results is consistent with a fully retinotopic reference frame for visual-spatial processing. Reasoning that a spatiotopic reference frame could conceivably be computed at the level of entire visual areas rather than at the level of individual voxels, we also used Bayesian decoding of stimulus location from the BOLD response patterns in visual areas. We found that decoded stimulus locations also adhere to the retinotopic frame of reference, by shifting with gaze position. Again, this result holds for all visual areas and irrespective of the deployment of spatial attention. We conclude that visual locations are encoded in a retinotopic reference frame throughout the visual hierarchy.
On-farm hatching and contact with adult hen post hatch induce sex-dependent effects on performance, health and robustness in broiler chickens

To improve the early perinatal conditions of broiler chicks, alternative hatching systems have been developed. On-farm hatching (OFH) with an enriched microbial and stimulating environment by the presence of an adult hen is a promising solution. Day-old chicks were allotted within five hatching and rearing conditions: OFH, conventional hatchery (CH), CH and post-hatching treatment with antibiotics (CH + AB), as well as both hatching systems with an adult hen at hatching (OFH + H, CH + H). To challenge the robustness of chickens, they were exposed on D27 to suboptimal rearing conditions by combining for 4 h transport in boxes in a new room at a lower temperature and fasting. On their return to the original room, the chicken density was increased, and birds were orally vaccinated with the Gumboro vaccine. The impacts of these conditions on hatchability, chick quality score, performance, health and robustness were determined. The OFH chick body weights (BWs) were significantly greater than those of CH chicks at hatching. Whereas there was no effect of hatching conditions, the presence of hens decreased the hatchability rate, the quality score of OFH chicks and increased mortality at hatching. Treatment of CH chicks with antibiotics (CH + AB) temporarily decreased chicken BW at D19, but the feed conversion ratio (FCR) was not modified. At D19, OFH chicks had the highest BW compared to the other groups, and the presence of hens at hatching harmed chicken BW regardless of the hatching condition and FCR. An interaction between the effect of experimental rearing conditions and chicken sex was observed later for BW. In males, the OFH chickens were the heaviest compared to the other groups at D34 but not at D56. The presence of hens negatively impacted CH chicken BW at D56. In females, there was no effect of hatching condition on the BWs at D34 and D56, and the presence of hens had a positive impact on OFH chicken BW. There was no effect of hatching conditions on health parameters. In conclusion, the OFH system was a hatching system at least equivalent to the CH system. The presence of the hen at hatching and during the chick start-up phase on performance interacted with the hatching condition and the sex of the chickens.
Bacterial ecology and evolution converge on seasonal and decadal scales

Ecology and evolution are distinct theories, but the short lifespans and large population sizes of microbes allow evolution to unfold along contemporary ecological time scales. To document this in a natural system, we collected a two-decade, 471-metagenome time series from a single site in a freshwater lake, which we refer to as the TYMEFLIES dataset. This massive sampling and sequencing effort resulted in the reconstruction of 30,389 metagenomic-assembled genomes (MAGs) over 50% complete, which dereplicated into 2,855 distinct genomes (>96% nucleotide sequence identity). We found both ecological and evolutionary processes occurred at seasonal time scales. There were recurring annual patterns at the species level in abundances, nucleotide diversities (π), and single nucleotide variant (SNV) profiles for the majority of all taxa. During annual blooms, we observed both higher and lower nucleotide diversity, indicating that both ecological differentiation and competition drove evolutionary dynamics. Overlayed upon seasonal patterns, we observed long-term change in 20% of the species’ SNV profiles including gradual changes, step changes, and disturbances followed by resilience. Most abrupt changes occurred in a single species, suggesting evolutionary drivers are highly specific. Nevertheless, seven members of the abundant Nanopelagicaceae family experienced abrupt change in 2012, an unusually hot and dry year. This shift coincided with increased numbers of genes under selection involved in amino acid and nucleic acid metabolism, suggesting fundamental organic nitrogen compounds drive strain differentiation in the most globally abundant freshwater family. Overall, we observed seasonal and decadal trends in both interspecific ecological and intraspecific evolutionary processes. The convergence of microbial ecology and evolution on the same time scales demonstrates that understanding microbiomes requires a new unified approach that views ecology and evolution as a single continuum.
A Synergistic Workspace for Human Consciousness Revealed 1 by Integrated Information Decomposition 2 3

Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, United Kingdom 8 9 Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom 10 11 Department of Psychology, University of Cambridge, Cambridge, United Kingdom 12 13 Center for Psychedelic Research, Department of Brain Science, Imperial College London, London, 14 United Kingdom 15 16 Data Science Institute, Imperial College London, London, United Kingdom 17 18 Centre for Complexity Science, Imperial College London, London, United Kingdom 19 20 Department of Neurosciences, Cambridge University Hospitals NHS Foundation, Addenbrooke's 21 Hospital, Cambridge, United Kingdom 22 23 Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, United Kingdom 24 25 Department of Psychology and Department of Physiology and Pharmacology, The Brain and Mind 26 Institute, University of Western Ontario, London, Ontario, Canada 27 28 Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland 29 30 Division of Neurosurgery, School of Clinical Medicine, University of Cambridge, Cambridge, 31 United Kingdom 32
Impaired Response to Mismatch Novelty in the Li2+-Pilocarpine Rat Model of TLE: Correlation with Hippocampal Monoaminergic Inputs

Novelty detection, crucial to episodic memory formation, is impaired in epileptic patients with mesial temporal lobe resection. Mismatch novelty detection, that activates the hippocampal CA1 area in humans and is vital for memory reformulation and reconsolidation, is also impaired in patients with hippocampal lesions. In this work we investigated the response to mismatch novelty, as occurs with the new location of known objects in a familiar environment, in the Li2+-pilocarpine rat model of TLE and its correlation with hippocampal monoaminergic markers. Animals showing spontaneous recurrent seizures (SRSs) for at least 4 weeks at the time of behavioural testing showed impaired spatial learning in the radial arm maze, as described. Concurrently, SRSs rats displayed impaired exploratory responses to mismatch novelty, yet novel object recognition was not significantly affected in SRSs rats. While the levels of serotonin and dopamine transporters were mildly decreased in hippocampal membranes from SRS rats, the levels on the norepinephrine transporter, tyrosine hydroxylase and dopamine-β-hydroxylase were enhanced, hinting for an augmentation, rather than an impairment in noradrenergic function in SRS animals. Altogether, this reveals that mismatch novelty detection is particularly affected by hippocampal damage associated to the Li2+-pilocarpine model of epilepsy 4-8 weeks after the onset of SRSs and suggests that deficits in mismatch novelty detection may substantially contribute to cognitive impairment in MTLE. As such, behavioural tasks based on these aspects of mismatch novelty may prove useful in the development of cognitive therapy strategies aiming to rescue cognitive deficits observed in epilepsy.
An Adaptive Roadmap Guided Multi-RRTs Strategy for Single Query Path Planning

During the past decade, Rapidly-exploring Random Tree (RRT) and its variants are shown to be powerful sampling based single query path planning approaches for robots in high-dimensional configuration space. However, the performance of such tree-based planners that rely on uniform sampling strategy degrades significantly when narrow passages are contained in the configuration space. Given the assumption that computation resources should be allocated in proportion to the geometric complexity of local region, we present a novel single-query Multi-RRTs path planning framework that employs an improved Bridge Test algorithm to identify global important roadmaps in narrow passages. Multiple trees can be grown from these sampled roadmaps to explore sub-regions which are difficult to reach. The probability of selecting one particular tree for expansion and connection, which can be dynamically updated by on-line learning algorithm based on the historic results of exploration, guides the tree through narrow passage rapidly. Experimental results show that the proposed approach gives substantial improvement in planning efficiency over a wide range of single-query path planning problems.
Scaling Thermal Properties from the Leaf to the Canopy in the Alaskan Arctic Tundra

ABSTRACT Plants are strongly influenced by their thermal environments, and this influence manifests itself in a variety of ways, such as altered ranges, growth, morphology, or physiology. However, plants also modify their local thermal environments through feedbacks related to properties and processes such as albedo and evapotranspiration. Here, we used leaf- and plot- level thermography on the north slope of the Brooks Range, Alaska, to explore interspecific differences in thermal properties among arctic tundra plants, and to determine if species differentially contribute to plot temperature. At the leaf-level, we found significant differences (p < 0.05) for in situ temperatures among the 13 study species. At the plot level, we found that the fractional cover of vascular plant species, lichen, litter, and moss had a significant effect on plot temperature (p < 0.05, R2= 0.61). A second model incorporating thermal leaf properties—in addition to the fraction of vascular plant and other dominant ground covers—also predicted plot temperature, but with lower explanatory power (p < 0.05, R2= 0.32). These results potentially have important implications for our understanding of how individual plant species influence canopy-level thermal properties and how temperature—dependent properties and processes may be impacted by climate change—induced shifts in species composition.
A Random Walk-Based Stochastic Distributed Exploration Algorithm for Low-Cost Swarm Robots

The advancement of swarm robotics has made tremendous strides in recent years, expanding the scope of its deployment from outdoor settings like construction sites and planetary exploration to indoor scenarios such as transportation-related activities. However, due to the large deployment of units in swarm robots, they cannot be engineered to have the costly and high-performance characteristics of conventional large robots. Thus, it is desirable to maintain low performance per unit and to reduce manufacturing costs. This paper presents a stochastic distributed exploration algorithm that accounts for the above features of swarm robots, and its performance is verified through both simulations and experiments. The proposed algorithm is based on a random walk and avoids path planning and high-precision sensing, enabling it to function well even with low-performance robots, relying only on the distance to the center of the search area based on random walks. Simulation outcomes demonstrate that the proposed algorithm can explore the search area with a specified exploration distribution. The experiments affirm that the robot can sequentially explore multiple search areas.