Miracle-dz/UniFAR-FTUs huggingface dataset:
The physiological variability of channel density in hippocampal CA1 pyramidal cells and interneurons explored using a unified data-driven modeling workflow

Every neuron is part of a network, exerting its function by transforming multiple spatiotemporal synaptic input patterns into a single spiking output. This function is specified by the particular shape and passive electrical properties of the neuronal membrane, and the composition and spatial distribution of ion channels across its processes. For a variety of physiological or pathological reasons, the intrinsic input/output function may change during a neuron’s lifetime. This process results in high variability in the peak specific conductance of ion channels in individual neurons. The mechanisms responsible for this variability are not well understood, although there are clear indications from experiments and modeling that degeneracy and correlation among multiple channels may be involved. Here, we studied this issue in biophysical models of hippocampal CA1 pyramidal neurons and interneurons. Using a unified data-driven simulation workflow and starting from a set of experimental recordings and morphological reconstructions obtained from rats, we built and analyzed several ensembles of morphologically and biophysically accurate single cell models with intrinsic electrophysiological properties consistent with experimental findings. The results suggest that the set of conductances expressed in any given hippocampal neuron may be considered as belonging to two groups: one subset is responsible for the major characteristics of the firing behavior in each population and the other is responsible for a robust degeneracy. Analysis of the model neurons suggests several experimentally testable predictions related to the combination and relative proportion of the different conductances that should be expressed on the membrane of different types of neurons for them to fulfill their role in the hippocampus circuitry.
Multi‐year net ecosystem carbon balance of a restored peatland reveals a return to carbon sink

Peatlands after drainage and extraction are large sources of carbon (C) to the atmosphere. Restoration, through re‐wetting and revegetation, aims to return the C sink function by re‐establishing conditions similar to that of an undrained peatland. However, the time needed to re‐establish C sequestration is not well constrained due to the lack of multi‐year measurements. We measured over 3 years the net ecosystem exchange of CO2 (NEE), methane ( FCH4 ), and dissolved organic carbon (DOC) at a restored post‐extraction peatland (RES) in southeast Canada (restored 14 years prior to the start of the study) and compared our observations to the C balance of an intact reference peatland (REF) that has a long‐term continuous flux record and is in the same climate zone. Small but significant differences in winter respiration driven by temperature were mainly responsible for differences in cumulative NEE between years. Low growing season inter‐annual variability was linked to constancy of the initial spring water table position, controlled by the blocked drainage ditches and the presence of water storage structures (bunds and pools). Half‐hour FCH4 at RES was small except when Typha latifolia‐invaded drainage ditches were in the tower footprint; this effect at the ecosystem level was small as ditches represent a minor fraction of RES. The restored peatland was an annual sink for CO2 (−90 ± 18 g C m−2 year−1), a source of CH4 (4.4 ± 0.2 g C m−2 year−1), and a source of DOC (6.9 ± 2.2 g C m−2 year−1), resulting in mean net ecosystem uptake of 78 ± 17 g C m−2 year−1. Annual NEE at RES was most similar to wetter, more productive years at REF. Integrating structures to increase water retention, alongside re‐establishing key species, have been effective at re‐establishing the net C sink rate to that of an intact peatland.
Advanced Resource Allocation Technique for a Fair Downlink Non-Orthogonal Multiple Access System

In this paper, a novel resource allocation technique is proposed for a power-domain non-orthogonal multiple access scheme using successive interference cancellation in a downlink cellular system. It aims at providing a flexible balancing between throughput and fairness maximization and incorporates unequal power repartition among allocated subbands using waterfilling. Its main strength is the ability to achieve a high level of fairness in every scheduling slot, therefore improving the quality of experience for all users. Fairness is achieved by the introduction of a new efficient scheduling metric within the allocation process. Extensive simulation results show that the proposed metric enhances both long-term and short-term fairness, and improves system capacity, when compared to the conventional proportional fairness scheduler.
Enhancing Multi-Aspect Collaborative Filtering for Personalized Recommendation

Most existing Collaborative Filtering (CF) approach relies on single overall ratings assigned to items. However, to precisely understand users' behaviours, sometimes this rating alone is not adequate. A user may show his/her overall preferences on an item through the overall ratings but at the same time, they may not satisfy with certain aspects of the item. This situation happened due to the emphasis on aspects may be different among users and will affect a user's final decisions. Therefore, in this paper, we proposed the multi-aspect tensor factorization (MATF) to enhance the predictive accuracy of multi-aspect recommendation by using Tensor Factorization. The evaluation shows that the proposed model outperforms various well-known existing techniques on both single and multicriteria recommendation.
Incorporate Oblique Muscle Contractions to Strengthen Soft Robots

For the state-of-the-art of soft robotics, the current actuation mechanisms cannot produce shear forces, neither are the current stiffening mechanisms adaptive to various deformations. Consequently, the soft robots gain strength at the price of losing flexibility. To fill this gap, we proposed a new mechanism based on the muscle arrangements and incompressible property identified in biological hydrostatic skeletons. Beside longitudinal and transverse muscles, the proposed mechanism includes the oblique arrangement which is proved to play an indispensable role of producing shear forces. The effectiveness of the new mechanism is demonstrated through a benchmark problem - carrying a distributed load at the initial horizontal configuration, thus indicating an improved direction to realise shape-independent load-carrying capability of soft robotics. Furthermore, the proposed mechanism may explain how elephants coordinate the two contradicting properties, strength and flexibility, during their trunk manipulations.
Edge-Based Loss Function for Single Image Super-Resolution

In recent years, convolutional neural networks have shown state-of-the-art performance on the task of single-image super-resolution. Although these proposed networks have shown high-quality reconstruction results, the use of the mean-squared error (MSE) loss function for training tends to produce images that are overly smooth and blurry. The MSE does not consider image structures that are often important for achieving high human-perceived image quality. We propose a novel edge-based loss function to improve super-resolution resconstruction of images. Our loss function directly optimizes the edge pixels of the reconstructed image, thus driving the trained network to produce high-quality salient edges and thus sharper images. Extensive quantitative and qualitative results show that our proposed loss function significantly outperforms the MSE.
The association of rainfall and Buruli ulcer in southeastern Australia

Background Buruli ulcer has been increasing in incidence in southeastern Australia with unclear transmission mechanisms. We aimed to investigate the link between rainfall and case numbers in two endemic areas of the state of Victoria; the Bellarine and Mornington Peninsulas. Methodology We created yearly and monthly graphs comparing rainfall with local Buruli ulcer incidence for the period 2004–2016 by endemic region and then considered a range of time lag intervals of 0–24 months to investigate patterns of correlation. Conclusions Optimal positive correlation for the Bellarine Peninsula occurred with a 12-month prior rainfall lag, however, no significant correlation was observed on the Mornington Peninsula for any time lag. These results provide an update in evidence to further explore transmission mechanisms which may differ between these geographically proximate endemic regions.
7-Isopenthenyloxycoumarin, Arctigenin, and Hesperidin Modify Myeloid Cell Leukemia Type-1 (Mcl-1) Gene Expression by Hormesis in K562 Cell Line

Hormesis is a new concept in dose–response relationship. Despite of traditional dose–response curves, there is a low-dose stimulation and a high-dose inhibition in this case. Hormesis effect in apoptosis induction/inhibition by natural compounds is reported previously. Here, we searched this effect for myeloid cell leukemia type-1 (Mcl-1) gene expression by phytochemicals 7-isopenthenyloxycoumarin (7-IP), arctigenin (Arg), and hesperidin (Hsp). For this purpose, first we tested the cytotoxicity of various doses of these compounds against K562 leukemia cell lines for different times by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide method. After that we explored the effect of various doses of these phytochemicals on Mcl-1 gene expression for different times by real-time polymerase chain reaction method. We found that these phytochemicals have cytotoxicity against K562 cell line. Hesperidin is the most cytotoxic agent. We also found that these natural compounds have hormetic effect on Mcl-1 gene expression. The hormetic model in Mcl-1 gene expression is overcompensation stimulation. This phenomenon is reported for the first time. We conclude that 7-IP, Arg, and Hsp are cytotoxic against K562 cancerous cells and induce/inhibit Mcl-1 gene expression by hormesis dose–response relationship.
Vision-based Teleoperation of Shadow Dexterous Hand using End-to-End Deep Neural Network

In this paper, we present TeachNet, a novel neural network architecture for intuitive and markerless vision-based teleoperation of dexterous robotic hands. Robot joint angles are directly generated from depth images of the human hand that produce visually similar robot hand poses in an end-to-end fashion. The special structure of TeachNet, combined with a consistency loss function, handles the differences in appearance and anatomy between human and robotic hands. A synchronized human-robot training set is generated from an existing dataset of labeled depth images of the human hand and simulated depth images of a robotic hand. The final training set includes 400K pairwise depth images and joint angles of a Shadow C6 robotic hand. The network evaluation results verify the superiority of TeachNet, especially regarding the high-precision condition. Imitation experiments and grasp tasks teleoperated by novice users demonstrate that TeachNet is more reliable and faster than the state-of-the-art vision-based teleoperation method.
Effect of Virtual Agent's Contingent Responses and Icebreakers Designed based on Interaction Training Techniques on Inducing Intentional Stance

The human mental stance towards a virtual agent has an influence on the social relationship that exists between them. In this study, we focus on contingency, which is the behavior that occurs synchronously with the human action, and the icebreaker, which is a facilitation exercise that helps start an interaction. The aim of this study is to investigate whether an agent's contingent responses and icebreakers with the contingent agent are capable of inducing and maintaining an intentional stance. We conducted an experiment using an agent which provided contingent responses. In the experiment, participants first interacted with the contingent agent through an icebreaker. Afterwards, all participants performed a collaborative task. As a result, we conclude that the contingent responses and the icebreaker are capable of inducing and partially maintaining the intentional stance. In particular, the icebreaker designed based on interaction training techniques was effective to induce the intentional stance.
Clustering-Guided Gp-Ucb for Bayesian Optimization

Bayesian optimization is a powerful technique for finding extrema of an objective function, a closed-form expression of which is not given but expensive evaluations at query points are available. Gaussian Process (GP) regression is often used to estimate the objective function and uncertainty estimates that guide GP-Upper Confidence Bound (GP-UCB) to determine where next to sample from the objective function, balancing exploration and exploitation. In general, it requires an auxiliary optimization to tune the hyperparameter in GP-UCB, which is sometimes not easy to carry out in practice. In this paper we present a simple practical method which improves GP-UCB, especially in cases where the objective function is not smooth with sharp peaks and valleys. We first present a geometric interpretation of GP-UCB on which we base our development of the clustering-guided method to select the next observation. Clustering is applied to two-dimensional vectors whose entries correspond to the posterior mean and standard deviation computed by GP regression, which is followed by utility maximization with GP-UCB, in order to determine where next to sample from the objective function. Experiments on various functions demonstrate our method alleviates the chance of being trapped in local extrema, making small efforts for auxiliary optimization.
Inclusion of Angular Momentum During Planning for Capture Point Based Walking

When walking at high speeds, the swing legs of robots produce a non-negligible angular momentum rate. To accommodate this, we provide a reference trajectory generator for bipedal walking that incorporates predicted centroidal angular momentum at the planning stage. This can be done efficiently as the Centroidal Moment Pivot (CMP), Instantaneous Capture Point (ICP) and the center of mass (CoM) all have closed-form trajectory solutions due to their linear dynamics. This is then used to produce smooth, continuous trajectories. We furthermore provide a lightweight model to estimate angular momentum as induced during leg swing of the gait cycle. Our proposed trajectory generator is tested thoroughly in simulation and has been shown to successfully operate on the real hardware.
A Decomposed Dual-Cross Generative Adversarial Network for Image Rain Removal

Rain removal is important for many computer vision applications, such as surveillance, autonomous car, etc. Traditionally, rain removal is regarded as a signal removal problem which usually causes over-smoothing by removing texture details in non-rain background regions. This paper considers the issue of rain removal from a completely different perspective, to treat rain removal as a signal decomposition problem. Speciﬁ-cally, we decompose the rain image into two components, namely non-rain background image and rain streaks image. Then, we introduce an adversarial training mechanism to synthesize non-rain background image and rain streaks image in a Dual-Cross manner, which makes the two adversarial branches interact with each other, archiving a win-win result ultimately. The proposed Decomposed Dual-Cross Generative Adversarial Network (DDC-GAN) shows signiﬁcantly performance improvement compared with state-of-the-art methods on both synthetic and real-world images in terms of qualitative and quantitative measures (over 3dB gains in PSNR).
Structured Text Summarization via Open Domain Information Extraction

Given the dramatic growth of digital content, new solutions are needed for us to be able to get a quick overview of pertinent information without being inundated by irrelevant details. While there has been ample research on automatic summarization methods, summaries may still be somewhat convoluted and hard to absorb. In this paper, we propose the novel task of structured text summarization, which we address by combining ranking techniques with open information extraction. This method collaborates with linguistics and yields an uncluttered, more easily digestible overview of key insights from a text and performs very well in certain aspect in our experiments.
Severe Respiratory Illness Outbreak Associated with Human Coronavirus NL63 in a Long-Term Care Facility

We describe an outbreak of severe respiratory illness associated with human coronavirus NL63 in a long-term care facility in Louisiana in November 2017. Six of 20 case-patients were hospitalized with pneumonia, and 3 of 20 died. Clinicians should consider human coronavirus NL63 for patients in similar settings with respiratory disease.
Research Priorities to Support Effective Manta and Devil Ray Conservation

Manta and devil rays are filter-feeding elasmobranchs that are found circumglobally in tropical and subtropical waters. Although relatively understudied for most of the Twentieth century, public awareness and scientific research on these species has increased dramatically in recent years. Much of this attention has been in response to targeted fisheries, international trade in mobulid products, and a growing concern over the fate of exploited populations. Despite progress in mobulid research, major knowledge gaps still exist, hindering the development of effective management and conservation strategies. We assembled 30 leaders and emerging experts in the fields of mobulid biology, ecology, and conservation to identify pressing knowledge gaps that must be filled to facilitate improved science-based management of these vulnerable species. We highlight focal research topics in the subject areas of taxonomy and diversity, life history, reproduction and nursery areas, population trends, bycatch and fisheries, spatial dynamics and movements, foraging and diving, pollution and contaminants, and sub-lethal impacts. Mobulid rays remain a poorly studied group, and therefore our list of important knowledge gaps is extensive. However, we hope that this identification of high priority knowledge gaps will stimulate and focus future mobulid research.
Demonstration of T-Shaped Channel Tunnel Field-Effect Transistors

In this paper we have proposed a novel structure T-shaped channel TFET. , which is experimentally demonstrated for the first time and investigated its performance and conduct. This structure have surpassing advantages over planar conventional TFET in terms of recorded lower OFF current and thus significant suppression of ambipolar conduction and improved ON current and thus higher Ion/Ioff ratio. Three such T-shaped channel structures are simulated and named according to the material used: Silicon based-T Channel-Dual Gate TFET (Si-TC-DG-TFET), Silicon-Gallium Arsenide based-T Channel-Dual Gate TFET (Si-GaAs-TC-DG-TFET) and Gallium Arsenide based-T Channel-Dual Gate TFET (GaAs-TC-DG-TFET). All the fundamental device parameters are analyzed for comparative study to obtain appropriate material that can be used to get optimized results and complex investigate and demonstrate the effects of T-Channel approach which has commanding outcomes on all characteristics in a 2D TFET model. All the simulations are done in Silvaco, Atlas.
Toward Encrypted Video Tampering Detection and Localization Based on POB Number System Over Cloud

The unlimited growth in the amount of multimedia content has shifted the global infrastructure to the cloud-based multimedia hosting. However, the high probability of security breaches of the content is increasing demand for secure solutions toward this end. One such feasible solution is to encrypt the content to unreadable form before outsourcing to the cloud-based servers. In this paper, the media information, specifically the video content is distributed into multiple random shares based on the permutation ordered binary number system. The information remains fully concealed without any leakage at the cloud servers. Even if the attacks endanger the integrity of the information, the proposed scheme is enriched with the capability of chalking out accurately the altered pixels. These tampered regions are subsequently reflected in the reconstructed video frames obtained at authentic entity end possessing the secret keys required to build back the original content. Moreover, the proposed scheme is capable of detecting temporal attacks on the video frames by employing sequence-based authentication bits. The robustness of the proposed scheme has been validated under different attack scenarios and the scheme is found to be performing satisfactorily well.
Neurodegenerative Diseases: Regenerative Mechanisms and Novel Therapeutic Approaches

Regeneration refers to regrowth of tissue in the central nervous system. It includes generation of new neurons, glia, myelin, and synapses, as well as the regaining of essential functions: sensory, motor, emotional and cognitive abilities. Unfortunately, regeneration within the nervous system is very slow compared to other body systems. This relative slowness is attributed to increased vulnerability to irreversible cellular insults and the loss of function due to the very long lifespan of neurons, the stretch of cells and cytoplasm over several dozens of inches throughout the body, insufficiency of the tissue-level waste removal system, and minimal neural cell proliferation/self-renewal capacity. In this context, the current review summarized the most common features of major neurodegenerative disorders; their causes and consequences and proposed novel therapeutic approaches.
Cytokine-Modulated Natural Killer Cells Differentially Regulate the Activity of the Hepatitis C Virus

HCV genotype 2a strain JFH-1 replicates and produces viral particles efficiently in human hepatocellular carcinoma (huh) 7.5 cells, which provide a stable in vitro cell infection system for the hepatitis C virus (HCVcc system). Natural killer (NK) cells are large lymphoid cells that recognize and kill virus-infected cells. In this study, we investigated the interaction between NK cells and the HCVcc system. IL-10 is a typical immune regulatory cytokine that is produced mostly by NK cells and macrophages. IL-21 is one of the main cytokines that stimulate the activation of NK cells. First, we used anti-IL-10 to neutralize IL-10 in a coculture of NK cells and HCVcc. Anti-IL-10 treatment increased the maturation of NK cells by enhancing the frequency of the CD56+dim population in NK-92 cells. However, with anti-IL-10 treatment of NK cells in coculture with J6/JFH-1-huh 7.5 cells, there was a significant decrease in the expression of STAT1 and STAT5 proteins in NK-92 cells and an increase in the HCV Core and NS3 proteins. In addition, rIL-21 treatment increased the frequency of the CD56+dim population in NK-92 cells, Also, there was a dramatic increase in the expression of STAT1 and STAT5 proteins in rIL-21 pre-stimulated NK cells and a decrease in the expression of HCV Core protein in coculture with J6/JFH-1-huh 7.5 cells. In summary, we found that the functional activation of NK cells can be modulated by anti-IL-10 or rIL-21, which controls the expression of HCV proteins as well as HCV RNA replication.