Miracle-dz/UniFAR-FTUs huggingface dataset:
Distribution Patterns of Iron-Oxidizing Zeta- and Beta-Proteobacteria From Different Environmental Settings at the Jan Mayen Vent Fields

Iron oxidizers are widespread in marine environments and play an important role in marine iron cycling. However, little is known about the overall distribution of iron oxidizers within hydrothermal systems, including settings with little hydrothermal activity. Moreover, the extent to which different phylogenetic groups of iron oxidizers exhibit niche specialization toward different environmental settings, remains largely unknown. Obtaining such knowledge is critical to unraveling the impact of the activity of iron oxidizers and how they are adapted. Here, we used 16S rRNA sequencing to characterize the distribution of iron oxidizers in different environmental settings within the Jan Mayen hydrothermal vent fields (JMVFs). Putative iron oxidizers affiliated to Zetaproteobacteria and Betaproteobacteria were detected within iron mounds, bottom seawater, basalt surfaces, and surface layers of sediments. The detected iron oxidizers were compared to sequence types previously observed in patchily distributed iron mats associated with diffuse venting at the JMVFs. Most OTUs of iron oxidizers reoccurred under different environmental settings, suggesting a limited degree of niche specialization. Consequently, most of the detected iron oxidizers seem to be generalists with a large habitat range. Our study highlights the importance of gathering information about the overall distribution of iron oxidizers in hydrothermal systems to fully understand the role of this metabolic group regarding cycling of iron. Furthermore, our results provide further evidence of the presence of iron-oxidizing members of Betaproteobacteria in marine environments.
An efficient motion generation method for redundant humanoid robot arms based on motion continuity

ABSTRACT This paper proposes a novel method of motion generation for redundant humanoid robot arms, which can efficiently generate continuous collision-free arm motion for the preplanned hand trajectory. The proposed method generates the whole arm motion first and then computes the actuators’ motion, which is different from IK (inverse kinematics)-based motion generation methods. Based on the geometric constraints of the preplanned trajectory and the geometric structure of humanoid robot arms, the wrist trajectory and elbow trajectory can be got first without solving inverse kinematics and forward kinematics. Meanwhile, the constraints restrict all feasible arm configurations to an elbow-circle and reduce the arm configuration space to a two-dimension space. By combining the configuration space and collision distribution of arm motion, collision-free arm configurations can be identified and be used to generate collision-free arm motion, which can avoid unnecessary forward and inverse kinematics. The experiments show that the proposed method can generate continuous and collision-free arm motion for preplanned hand trajectories. GRAPHICAL ABSTRACT
Nanoparticle-modified chitosan-agarose-gelatin scaffold for sustained release of SDF-1 and BMP-2

Background Stromal cell-derived factor 1 (SDF-1) is an important chemokine for stem cell mobilization, and plays a critical role in mobilization of mesenchymal stem cells (MSCs). Bone morphogenetic protein 2 (BMP-2) plays a critical role in osteogenesis of MSCs. However, the use of SDF-1 and BMP-2 in bone tissue engineering is limited by their short half-lives and rapid degradation in vitro and in vivo. Methods The chitosan oligosaccharide/heparin nanoparticles (CSO/H NPs) were first prepared via self-assembly. Chitosan-agarose-gelatin (CAG) Scaffolds were then synthesized via gelation technology using cross-linked chitosan, agarose, and gelatin, and were modified by CSO/H NPs. The encapsulation efficiency and release kinetics of SDF-1 and BMP-2 were quantified using an enzyme-linked immunosorbent assay. A CCK-8 assays were used to evaluate biocompatibility of NP-modified scaffolds. The biological activity of the loaded SDF-1 and BMP-2 was evaluated using the transwell migration assay and osteogenic induction assay. An animal MSC recruitment model was used to study the ability of SDF-1 released from NP-modified scaffolds to induce migration of MSCs. Results In this study, we developed a novel nanoparticle-modified CAG scaffold for the delivery of SDF-1 and BMP-2. CCK-8 assays demonstrated excellent biocompatibility of NP-modified scaffolds. In addition, we investigated the release of SDF-1 and BMP-2 from NP-modified scaffolds, and evaluated the effect of released SDF-1 on MSC migration. The effect of released BMP-2 on MSC osteogenesis was also examined. In vitro cell migration assays showed that SDF-1 released from NP-modified scaffolds retained its migration activity; osteogenesis studies demonstrated that released BMP-2 exhibited a strong ability to induce differentiation towards osteoblasts. Our in vivo recruitment assays showed continuous chemotactic response of MSCs to SDF-1 released from the NP-modified scaffold. Conclusion The simplicity of synthesizing CSO/H NP-modified CAG scaffolds, combined with its high cytokine loading capacity and sustained release effect, renders NP-modified CAG scaffold an attractive candidate for sustained release of SDF-1 and BMP-2 to promote bone repair and regeneration.
The Aryl Hydrocarbon Receptor as an Immune-Modulator of Atmospheric Particulate Matter-Mediated Autoimmunity

This review examines the current literature on the effects of atmospheric particulate matter (PM) on autoimmune disease and proposes a new role for the aryl hydrocarbon receptor (AHR) as a modulator of T cells in PM-mediated autoimmune disease. There is a significant body of literature regarding the strong epidemiologic correlations between PM exposures and worsened autoimmune diseases. Genetic predispositions account for 30% of all autoimmune disease leaving environmental factors as major contributors. Increases in incidence and prevalence of autoimmune disease have occurred concurrently with an increase in air pollution. Currently, atmospheric PM is considered to be the greatest environmental health risk worldwide. Atmospheric PM is a complex heterogeneous mixture composed of diverse adsorbed organic compounds such as polycyclic aromatic hydrocarbons (PAHs) and dioxins, among others. Exposure to atmospheric PM has been shown to aggravate several autoimmune diseases. Despite strong correlations between exposure to atmospheric PM and worsened autoimmune disease, the mechanisms underlying aggravated disease are largely unknown. The AHR is a ligand activated transcription factor that responds to endogenous and exogenous ligands including toxicants present in PM, such as PAHs and dioxins. A few studies have investigated the effects of atmospheric PM on AHR activation and immune function and demonstrated that atmospheric PM can activate the AHR, change cytokine expression, and alter T cell differentiation. Several studies have found that the AHR modulates the balance between regulatory and effector T cell functions and drives T cell differentiation in vitro and in vivo using murine models of autoimmune disease. However, there are very few studies on the role of AHR in PM-mediated autoimmune disease. The AHR plays a critical role in the balance of effector and regulatory T cells and in autoimmune disease. With increased incidence and prevalence of autoimmune disease occurring concurrently with increases in air pollution, potential mechanisms that drive inflammatory and exacerbated disease need to be elucidated. This review focuses on the AHR as a potential mechanistic target for modulating T cell responses associated with PM-mediated autoimmune disease providing the most up-to-date literature on the role of AHR in autoreactive T cell function and autoimmune disease.
Role of Sensorimotor Cortex in Gestural-Verbal Integration

Action comprehension that is related to language or gestural integration has been shown to engage the motor system in the brain, thus providing preliminary evidence for the gestural-verbal embodiment concept. Based on the involvement of the sensorimotor cortex (M1) in language processing, we aimed to further explore its role in the cognitive embodiment necessary for gestural-verbal integration. As such, we applied anodal (excitatory) and sham transcranial direct current stimulation (tDCS) over the left M1 (with reference electrode over the contralateral supraorbital region) during a gestural-verbal integration task where subjects had to make a decision about the semantic congruency of the gesture (prime) and the word (target). We used a cross-over within-subject design in young subjects. Attentional load and simple reaction time (RT) tasks served as control conditions, applied during stimulation (order of three tasks was counterbalanced). Our results showed that anodal (atDCS) compared to sham tDCS (stDCS) reduced RTs in the gestural-verbal integration task, specifically for incongruent pairs of gestures and verbal expressions, with no effect on control task performance. Our findings provide evidence for the involvement of the sensorimotor system in gestural-verbal integration performance. Further, our results suggest that functional modulation induced by sensorimotor tDCS may be specific to gestural-verbal integration. Future studies should now evaluate the modulatory effect of tDCS on semantic congruency by using tDCS over additional brain regions and include assessments of neural connectivity.
Integrated unpaired appearance-preserving shape translation across domains

We address the problem of un-supervised geometric image-to-image translation. Rather than transferring the style of an image as a whole, our goal is to translate the geometry of an object as depicted in different domains while preserving its appearance. Towards this goal, we propose a fully un-paired model that performs shape translation within a single model and without the need of additional post-processing stages. Extensive experiments on the VITON, CMU-Multi-PIE and our own FashionStyle datasets show the effectiveness of the proposed method at achieving the task at hand. In addition, we show that despite their low-dimensionality, the features learned by our model have potential for the item retrieval task
Aerosol-synthesized siliceous nanoparticles: impact of morphology and functionalization on biodistribution

Introduction Siliceous nanoparticles (NPs) have been extensively studied in nanomedicine due to their high biocompatibility and immense biomedical potential. Although numerous technologies have been developed, the synthesis of siliceous NPs for biomedical applications mainly relies on a few core technologies predominantly intended to produce spherical-shaped NPs. Methods In this context, the impact of different morphologies of siliceous NPs on biodistribution in vivo is limited. In the present study, we developed a novel technique based on an aerosol silane reactor to produce sintered silicon NPs of similar size but different surface areas due to distinct spherical subunits. Silica-converted particles were functionalized for radiolabeling with copper-64 (64Cu) to systematically analyze their behavior in the passive targeting of A431 tumor xenografts in mice after intravenous injection. Results While low nonspecific uptake was observed in most organs, the majority of particles were accumulated in the liver, spleen, and lung. Depending on the morphologies and function-alization, significant differences in the uptake profiles of the particles were observed. In terms of tumor uptake, spherical shapes with lower surface areas showed the highest accumulation and tumor-to-blood ratios of all investigated particles. Conclusion This study highlights the importance of shape and fuctionalization of siliceous NPs on organ and tumor accumulation as significant factors for biomedical applications.
A flexible optimization-based method for synthesizing intent-expressive robot arm motion

We present an approach to synthesize robot arm trajectories that effectively communicate the robot’s intent to a human collaborator while achieving task goals. Our approach uses nonlinear constrained optimization to encode task requirements and desired motion properties. Our implementation allows for a wide range of constraints and objectives. We introduce a novel objective function to optimize robot arm motions for intent-expressiveness that works in a range of scenarios and robot arm types. Our formulation supports experimentation with different theories of how viewers interpret robot motion. Through a series of human-subject experiments on real and simulated robots, we demonstrate that our method leads to improved collaborative performance against other methods, including the current state of the art. These experiments also show how our perception heuristic can affect collaborative outcomes.
Cell Virtualization with Network Partition for Initial User Association in Software Defined Small-cell Networks

In recent years, dense small cell network has been deployed to address the challenge that has resulted from the unprecendented growth of mobile data traffic and users. It has proven to be a cost efficeient solution to offload traffic from macro-cells. Software defined heterogeneous wireless network can decouple the control plane from the data plane. The control signal goes through the macro-cell while the data traffic can be offloaded by small cells. In this paper, we propose a framework for cell virtualization and user association in order to satisfy versatile requirements of multiple tenants. In the proposed framework, we propose an interference graph partioning based virtual-cell association and customized physical-cell association for multi-homed users in a software defined small cell network. The proposed user association scheme includes 3 steps: initialization, virtual-cell association and physical-cell association. Simulation results show that the proposed virtual-cell association outperforms the other schemes. For physical-cell association, the results on resource utilization and user fairness are examined for mobile users and infrastructure providers.
Feature Selection Algorithms in Intrusion Detection System: A Survey

Regarding to the huge number of connections and the large flow of data on the Internet, Intrusion Detection System (IDS) has a difficulty to detect attacks. Moreover, irrelevant and redundant features influence on the quality of IDS precisely on the detection rate and processing cost. Feature Selection (FS) is the important technique, which gives the issue for enhancing the performance of detection. There are different works have been proposed, but a map for understanding and constructing a state of the FS in IDS is still need more investigation. In this paper, we introduce a survey of feature selection algorithms for intrusion detection system. We describe the well-known approaches that have been proposed in FS for IDS. Furthermore, we provide a classification with a comparative study between different contribution according to their techniques and results. We identify a new taxonomy for future trends and existing challenges.
Acute Low Alcohol Disrupts Hippocampus-Striatum Neural Correlate of Learning Strategy by Inhibition of PKA/CREB Pathway in Rats

The hippocampus and striatum guide place-strategy and response-strategy learning, respectively, and they have dissociable roles in memory systems, which could compensate in case of temporary or permanent damage. Although acute alcohol (AA) treatment had been shown to have adverse effects on hippocampal function, whether it causes the functional compensation and the underlying mechanisms is unknown. In this study, rats treated with a low dose of AA avoided a hippocampus-dependent spatial strategy, instead preferring a striatum-dependent response strategy. Consistently, the learning-induced increase in hippocampal, but not striatal, pCREB was rendered less pronounced due to diminished activity of pPKA, but not pERK or pCaMKII. As rats approached the turn-decision area, Sp-cAMP, a PKA activator, was found to mitigate the inhibitory effect of AA on intra- and cross-structure synchronized neuronal oscillations, and rescue response-strategy bias and spatial learning deficits. Our study provides strong evidence of the critical link between neural couplings and strategy selection. Moreover, the PKA/CREB-signaling pathway is involved in the suppressive effect of AA on neural correlates of place-learning strategy. The novel important evidence provided here shows the functional couplings between the hippocampus and striatum in spatial learning processing and suggests possible avenues for therapeutic intervention.
A collaborative mobile edge computing and user solution for service composition in 5G systems

Mobile edge computing (MEC) is an emergent technology that has revolutionized traditional cloud service solutions. Mobile edge computing extends cloud computing by providing processing, storage, and networking capabilities at the edge of the mobile network. Delay‐sensitive and context‐aware applications are able to execute within close proximity of mobile users. Additionally, today's cloud services are not tailored to user specifications, but rather diversified toward a group of users. To guarantee delivery of user‐specific services in 5G networks, service composition techniques should be incorporated. This article envisions a real‐time, context‐aware, service‐composition collaborative framework that lies at the edge of the network, comprising MEC and user devices for fast composite service delivery. The proposed solution decomposes cloud data into a set of files and services, which are then replicated to MEC nodes. Frequently requested files and services are further cached onto user mobile devices for faster access. Both MEC nodes and mobile users advertise their services onto the collaborative edge/user space, where services are delivered either composite or unrendered according to users' requests. Service composition is achieved through a learning‐based workflow‐net approach that relies on previous composition results to build service composition models to be used for new compositions. The presented solution provides guaranteed and fast delivery of the requested cloud composite services to end users while sustaining QoS requirements and load balancing among edge and mobile nodes.
Energy-Saving Oriented On/Off Strategies in Heterogeneous Networks : an Asynchronous Approach with Dynamic Traffic Variations

Recent works have validated the possibility of reducing the energy consumption in wireless heterogeneous networks, achieved by switching on/off some base stations (BSs) dynamically. In this paper, to realize energy conservation, the discrete time Markov Decision Process (DTMDP) is developed to match up the BS switching operations with the traffic load variations. Then, an asynchronous decision-making algorithm, which is based on the Bellman equation and the on/off priorities of the BSs, is firstly put forward and proved to be optimal in this paper. Through reducing the state and action space during one decision, the proposed asynchronous algorithm can avoid the “curse of dimensionality” occurred in DTMDP frequently. Finally, numerical simulations are conducted to validate the effectiveness and advantages of the proposed asynchronous on/off strategies.
Table for five, please: Dietary partitioning in boreal bats

Abstract Differences in diet can explain resource partitioning in apparently similar, sympatric species. Here, we analyzed 1,252 fecal droppings from five species (Eptesicus nilssonii, Myotis brandtii, M. daubentonii, M. mystacinus, and Plecotus auritus) to reveal their dietary niches using fecal DNA metabarcoding. We identified nearly 550 prey species in 13 arthropod orders. Two main orders (Diptera and Lepidoptera) formed the majority of the diet for all species, constituting roughly 80%–90% of the diet. All five species had different dietary assemblages. We also found significant differences in the size of prey species between the bat species. Our results on diet composition remain mostly unchanged when using either read counts as a proxy for quantitative diet or presence–absence data, indicating a strong biological pattern. We conclude that although bats share major components in their ecology (nocturnal life style, insectivory, and echolocation), species differ in feeding behavior, suggesting bats may have distinctive evolutionary strategies. Diet analysis helps illuminate life history traits of various species, adding to sparse ecological knowledge, which can be utilized in conservation planning.
The Association of Baseline Serum Tumour Markers with Outcome of Patients with Metastatic Colorectal Cancer Treated with Anti-EGFR Monoclonal Antibodies in the First Line

The measurement of serum tumour markers is a simple and non-invasive method for assessing the response to systemic therapies in metastatic colorectal cancer (mCRC) and estimation of prognosis. The aim of our retrospective study was to evaluate the association of baseline serum levels of carcinoembryonic antigen (CEA), carbohydrate antigen 19-9 (CA 19-9), thymidine kinase (TK) and tissue polypeptide specific antigen (TPS) with outcome of patients with mCRC treated with combination of chemotherapy and monoclonal antibodies against epidermal growth factor receptor (anti-EGFR mAbs) in the first line. In our study, the cohort included 102 patients treated with therapy based on anti-EGFR mAbs between years 2011 and 2017 at Department of Oncology and Radiotherapy, Medical School and University Hospital in Pilsen, Czech Republic. Serum samples were collected within one month before the initiation of treatment. In multivariate Cox analysis that included serum tumour markers and clinical baseline parameters show that high baseline serum CA 19-9 was significantly associated with worse progression-free survival (HR=1.871, p=0.0330) and also overall survival (HR=3.903, p=0.0006). We have not demonstrated association of baseline levels of CEA, TK and TPS with patients' outcome. CA 19-9 is commonly used serum tumour marker which is simple and readily available and its candidate prognostic importance in the setting of anti-EGFR therapy deserves to be studied in prospective trials.
Pleural anthracosis presenting with massive effusion: a rare entity

Pleural anthracosis is rare and, in most cases, is diagnosed incidentally or at autopsy. We report a 67‐year‐old man with pleural anthracosis. He was initially referred for possible tuberculous pleural effusion and had recurrent admissions for symptomatic pleural effusion, which increased with each subsequent episode. A thoracoscopic examination demonstrated diffuse hyperpigmentation in both parietal and visceral pleura. Parietal pleural biopsy indicated granuloma with foreign body giant cell. A contrast‐enhanced computed tomography (CECT) thorax showed focal plaques in parietal pleura with calcifications in the ipsilateral lung. Investigations for tuberculosis, fungal, and malignancy proved to be negative. With these results, a diagnosis of pleural anthracosis was made. This case highlights the unusual presentation of pleural anthracosis with pleural effusion.