Miracle-dz/UniFAR-FTUs huggingface dataset:
Calcium influx mediates the chemoattractant-induced translocation of the arrestin-related protein AdcC in Dictyostelium

ABSTRACT Arrestins are key adaptor proteins that control the fate of cell-surface membrane proteins and modulate downstream signaling cascades. The Dictyostelium discoideum genome encodes six arrestin-related proteins, harboring additional modules besides the arrestin domain. Here, we studied AdcB and AdcC, two homologs that contain C2 and SAM domains. We showed that AdcC – in contrast to AdcB – responds to various stimuli (such as the chemoattractants cAMP and folate) known to induce an increase in cytosolic calcium by transiently translocating to the plasma membrane, and that calcium is a direct regulator of AdcC localization. This response requires the calcium-dependent membrane-targeting C2 domain and the double SAM domain involved in AdcC oligomerization, revealing a mode of membrane targeting and regulation unique among members of the arrestin clan. AdcB shares several biochemical properties with AdcC, including in vitro binding to anionic lipids in a calcium-dependent manner and auto-assembly as large homo-oligomers. AdcB can interact with AdcC; however, its intracellular localization is insensitive to calcium. Therefore, despite their high degree of homology and common characteristics, AdcB and AdcC are likely to fulfill distinct functions in amoebae. Summary: The multimodular arrestin-related protein AdcC from Dictyostelium responds to a calcium increase by translocating to the plasma membrane in a C2- and SAM domain-dependent manner.
Dynamic Power Allocation for Downlink Multi-Carrier NOMA Systems

In this letter, the performance of optimal dynamic power allocation (PA) is analyzed for downlink multi-carrier non-orthogonal multiple access (MC-NOMA) systems. We study the PA optimization problem with a pair of users and weighted-sum-rate utility. A novel low-complexity algorithm is designed to solve the problem with a closed-form PA expression. The analytical data rate performance is derived and verified by simulation results. The numerical results indicate that a large difference in user channel states improves performance by enhancing the user diversity gain in NOMA systems. Moreover, the channel diversity gain can be achieved by multi-carrier transmission and increases with the number of subcarriers. Finally, the number of subcarriers for dynamic PA in MC-NOMA systems is discussed for practical applications.
Dynamic Attack-Resilient Routing in Software Defined Networks

The scale of connected devices in the modern communication network and its heterogeneous nature have made securing the network more challenging. However, with the advent of software defined networking (SDN), the algorithmic complexity is handled at a centralized control plane and the network elements perform only data forwarding based on control plane decisions. This enables researchers to design innovative security protocols at the control plane to dynamically defend against attacks. In this paper, we propose a dynamic attack-resilient routing (ARR) approach and develop an optimization formulation for fragmented multipath routing taking reliability and load into consideration for SDN-enabled networks. Though erasure encoding has been well studied for resilient data storage, it is rarely mentioned in the context of network routing owing to its complexity, redundancy, and difficulty of satisfying practical routing constraints. In this paper, we dynamically determine the optimal route for erasure-encoded fragments of the data, in terms of attack resilience, under the constraint on allowable encoding redundancy. Since the ARR algorithm is computationally prohibitive for larger networks, we develop a heuristic solution for the same using a multipath-tree. The proposed algorithm dynamically routes the data fragments along a set of reliable and lightly loaded paths to achieve multipath diversity and thereby improve data availability at the destination even in the presence of attacks. We demonstrate the effectiveness of our proposed approach in terms of weighted path reliability, resilience, and blocking performance through simulations.
Health-Related Quality of Life after Pediatric Severe Sepsis

Background: Pediatric severe sepsis is a public health problem with significant morbidities in those who survive. In this article, we aim to present an overview of the important studies highlighting the limited data available pertaining to long-term outcomes of survivors of pediatric severe sepsis. Materials and Methods: A review of literature available was conducted using PUBMED/Medline on pediatric severe sepsis outcomes. Long-term outcomes and health-related quality of life (HRQL) following severe sepsis was defined as any outcome occurring after discharge from the hospital following an episode of severe sepsis which affected either the survivor or the survivor’s family members. Results: Many children are discharged with worse clinical and functional outcomes, depending on their diagnosis, treatments received, psychological effects, and the impact of their illness on their parents. Additionally, they utilize healthcare services more than their peers and are often readmitted soon after discharge. However, pediatric HRQL studies with worthwhile outcome measures are limited and the current data on pediatric sepsis is mainly retrospective. Conclusions: There is significant and longstanding morbidity seen in children and their families following a severe sepsis illness. Further prospective data are required to study the long-term outcomes of sepsis in the pediatric population.
Unified Middlebox Model Design and Deployment With Dynamic Resources

Due to the expensive hardware and complex management of the traditional middlebox, a concerted effort toward the virtualized middlebox has been launched in both academia and industry. In this paper, we propose a unified middlebox model, MBBrick, which is composed of three operation modules (classifier, rewriter, and forwarder) and a control module. We then design a language, middlebox language, to describe the MBBrick process. By concatenating different modules, MBBrick can achieve the functions of different middleboxes or service chains in one single super middlebox. We design the framework for managing MBBrick and network resources. We propose the efficient algorithms to optimize the MBBrick deployment and schedule the traffic. We also consider the situation of the network failure and divide it into two types (the normal failure and the MBBrick failure). We propose the backup scheme for each MBBrick to cover the potential failure. If the failure occurs, this method can reduce the impact on the network performance. The experiment results show that MBBrick significantly reduces the processing latency and improves the network throughput.
Reconstruction of Visual Image From Functional Magnetic Resonance Imaging Using Spiking Neuron Model

Spikes are the basic elements of information dissemination in the organic brain. A spike train, a series of discrete action potentials, incorporates the conception of time. Nowadays, the majority of existing artificial neural networks use numerical information to realize machine learning and cognition tasks. The advantage of numerical computation is its precision and remarkable performance on well-structured problems. However, cognition tasks have semi-structured or ill-structured information, even worse, some cannot reach a conclusion. According to biological experiments, the spiking neuron model is potentially more suitable for dealing with undetermined and unstructured problems. Researchers are trying to decode functional magnetic resonance imaging (fMRI) data, and this is a typical task to extract meaningful information from relatively undetermined and unstructured data. In this paper, we selected the Tempotron neuron model to analyze and reconstruct visual images from fMRI data when subjects received several kinds of visual stimuli; the preliminary results of pattern reconstruction were unpolished, but somewhat effective. Thus, a new structure for the spiking neural network was built to achieve better results. Several important aspects of the proposed model were discussed in this paper: the encoding of external stimulating signals, the extraction of effective features, the relative position of spike trains on the timeline, the back propagation of error, and the rationality of parameter selection. These aspects are crucial in the spiking neuron model’s implementation, and are worth further investigation in future studies.
Identification of Changing Ribosome Protein Compositions using Mass Spectrometry

The regulatory role of the ribosome in gene expression has come into sharper focus. It has been proposed that ribosomes are dynamic complexes capable of changing their protein composition in response to environmental stimuli. MS is applied to identify quantitative changes in the protein composition of S. cerevisiae 80S ribosomes in response to different environmental stimuli. Using quantitative MS, it is found that the paralog yeast ribosomal proteins RPL8A (eL8A) and RPL8B (eL8B) change their relative proportions in the 80S ribosome when yeast is switched from growth in glucose to glycerol. By using yeast genetics and polysome profiling, it is shown that yeast ribosomes containing either RPL8A or RPL8B are not functionally interchangeable. The quantitative proteomic data support the hypothesis that ribosomes are dynamic complexes that alter their composition and functional activity in response to changes in growth or environmental conditions.
(WKSP) On the Potential of Data Extraction by Detecting Unaware Facial Recognition with Brain-Computer Interfaces

Consumer-grade brain-computer interfaces are becoming more readily available to consumers. Directly reading biological information opens the door for an individual to unwillingly expose personal information. Attackers may be able to glean private information based on the level of recognition a victim has to a specific face, and use that to their advantage. In this work, we use a variety of classification algorithms to classify two types of facial recognition: unaware and aware. To do this, source data is manipulated into two datasets for classification: A set of combined and averaged EEG data, and a set of combined EEG data. We find that in all cases, the combined dataset outperforms the combined and averaged dataset. Further, based on the promising results obtained, there's a risk that a malicious third party could utilize similar techniques to extract private information from individuals without their consent using brain-computer interfaces.
Thermal Features for Presentation Attack Detection in Hand Biometrics

This paper proposes a method for utilizing thermal features of the hand for the purpose of presentation attack detection (PAD) that can be employed in a hand biometrics system’s pipeline. By envisaging two different operational modes of our system, and by employing a DCNN-based classifiers fine-tuned with a dataset of real and fake hand representations captured in both visible and thermal spectrum, we were able to bring two important deliverables. First, a PAD method operating in an open-set mode, capable of correctly discerning 100% of fake thermal samples, achieving Attack Presentation Classification Error Rate (APCER) and Bona-Fide Presentation Classification Error Rate (BPCER) equal to 0%, which can be easily implemented into any existing system as a separate component. Second, a hand biometrics system operating in a closed-set mode, that has PAD built right into the recognition pipeline, and operating simultaneously with the user-wise classification, achieving rank-1 recognition accuracy of up to 99.75%. We also show that thermal images of the human hand, in addition to liveness features they carry, can also improve classification accuracy of a biometric system, when coupled with visible light images. To follow the reproducibility guidelines and to stimulate further research in this area, we share the trained model weights, source codes, and a newly created dataset of fake hand representations with interested researchers.
A Transport Scheme for Reducing Delays and Jitter in Ethernet-Based 5G Fronthaul Networks

Fronthaul networks are leveraging communication links between the remote radio heads and baseband units in cloud radio access networks, and common public radio interface (CPRI) is an interface to carry time-sensitive traffic over the fronthaul. For the fronthaul networks which impose stringent bandwidth, latency, and jitter requirements, Ethernet can be a cost-effective solution to carry the CPRI traffic. However, Ethernet networks have limitations to transport the multiple CPRI streams simultaneously and satisfy the strict service requirements due to the accumulation of unavoidable intrinsic delays at switches. To address these issues, this paper evaluates the impact of intrinsic delay on the performance of CPRI over Ethernet (CoE) networks with experimental results and proposes a virtual local area network-based CoE network architecture along with two transport algorithms to carry the multiple CPRI streams over Ethernet despite the intrinsic delays. We confirmed with computer simulations that with the proposed techniques, the end-to-end delays and jitter for a number of CPRI streams within the acceptable range of fronthaul requirements can be achieved.
CATCH-919 Hand: Design of a 9-actuator 19-DOF Anthropomorphic Robotic Hand

To achieve human-like dexterity for anthropomorphic robotic hands, it is essential to understand the biomechanics and control strategies of the human hand, in order to reduce the number of actuators being used without loosing hand flexibility. To this end, in this article, we propose a new interpretation about the working mechanism of the metacarpal (MCP) joint's extension and the underlying control strategies of the human hand, based on which we further propose a highly flexible finger design to achieve independent movements of interphalangeal (IP) joints and MCP joint. Besides, we consider the hyperextension of fingertip into our design which helps robotic finger present compliant and adaptive posture for touching and pinching. In addition, human thumb muscle functions are reconstructed in the proposed robotic hand design, by replacing 9 human muscle tendons with 3 cables in the proposed task-oriented design, realizing all 33 static and stable grasping postures. Videos are available at this https URL
Engaging Young Children as Application Design Partners: A Stakeholder-Inclusive Methodological Approach

Co-design, as it applies to the fields of human-computer interaction and user-centered design, can be simplistically defined as user involvement in technology design activities. According to Berggren and Hedler, co-design is beneficial in that it provides an alternative perspective for designers when directly engaging with a given user group. While the focus of co-design was traditionally on adult end users as testers of technology, gradually the concept of a design partnership was perceived as valuable. Over time, co-design activities included children, with the recognition that it was no longer viable for adults to make decisions as to the technological needs and requirements of children. Rather it was understood that children? s opinions must be integrated and factored into end products. The input of children in the design process as "active participants" particularly younger children, was previously negligible. This is generally attributed to the challenges associated with verbalization of thoughts and preferences.
Big Web Colors: Analyzing the World Top Sites

Colors are obviously important for web sites, but how much? in this paper we try to study the problem of abstracting from the actual content, and analyze if and how colors in images have a higher-level fundamental importance. Focusing on the world top web sites, we collected a large pool (almost two millions) of images, and then investigated the relationships of colors with the attractiveness of a page. Can colors alone boost the success of a page, and in what terms? To answer this question we developed an experiment involving a large number of people, measuring how and how much colors affect a page, abstracting from the content. The results show that, rather surprisingly, colors do have a more fundamental significance that can be decoupled from the underlying shapes. We provide qualitative and quantitative insights on how important colors are, and how they actually impact the success of a site in terms of user perception.
Time-Angle Domain Sparsity-Based MIMO Channel Estimation Approach in High Mobility Scenarios

This letter investigates the sparse channel estimation approach for multiple input multiple output systems in high mobility scenarios. The large quantity of channel estimation coefficients is significantly reduced by taking advantage of both the channel sparsity in time-angle domain and the basis expansion model for time-varying channel. After the establishment of the structured compressive sensing model, a Newton auxiliary block orthogonal matching pursuit algorithm is put forward to recover the channel. It is illustrated in the numerical simulation results that the proposed approach has excellent performance and outperforms the traditional counterparts.
Performance Modeling and Task Scheduling in Distributed Graph Processing

The accelerated growth of datasets observed in modern applications also applies to datasets modeled as graphs. To handle this problem, several large scale distributed graph processing models have been proposed, such as Pregel. These systems are designed to run in large clusters, where the resources must be allocated efficiently. In this paper we present a prediction model and a scheduler for Pregel-based distributed graph processing jobs. The jobs are treated as moldable tasks by the scheduler that, based on the predictions, allocates the best number of workers to each job in order to minimize makespan. Experimental results show that the prediction model has accuracy close to 90%, allowing the scheduler to work within the theoretical approximation limits of the optimal makespan.
Keyphrase Generation Based on Deep Seq2seq Model

Keyphrase can provide highly summative information which can help us improve information utilization efficiency in the era of information overload. Though previous researches about keyphrase generation have provided some workable solutions, they generate keyphrase by ranking and selecting meaningful words from the source text. These approaches belong to an extractive method, by which they cannot effectively use semantic meaning of the source text, and are unable to generate keyphrases which do not appear in the source text. So we propose a sequence-to-sequence framework with attention mechanism, copy mechanism, and coverage mechanism, which can effectively deal with the above-mentioned drawbacks. The experimental results on five data sets reveal that our proposed model can achieve a better performance than the traditional extraction approaches and can also generate absent keyphrases which do not appear in the source text.
Integrin Beta 1 Is Crucial for Urinary Concentrating Ability and Renal Medulla Architecture in Adult Mice

Integrins are heterodimers anchoring cells to the surrounding extracellular matrix (ECM), an active and complex process mediating a series of inside-out and outside-in stimuli regulating cellular turn-over, tissue growth and architecture. Itgb1 is the main subunit of the renal integrins and it is critical for renal development. This study aims to investigate the role of Itgb1 in the adult renal epithelial cells by knocking down Itgb1 in PAX8 expressing cells. Itgb1-Pax8 cKO mice develop a progressively worsening proteinuria and renal abnormalities leading to severe renal failure and hypertension. This phenotype is also associated with severe dysfunction of distal nephron and polyuria. To further investigate whether distal nephron involvement was primarily related to Itgb1 suppression or secondary to renal failure, an Itgb1-AQP2 cKO mouse model was generated. These mice lack Itgb1 expression in AQP2 expressing cells. They do not show any developmental alteration, but 1 month old mice are resistant to dDAVP administration and finally, at 2 months of age, they develop overt polyuria. This phenotype is due to primary collecting duct (CD) cells anoikis. The entire architecture of the outer medulla is altered, with loss of the typical organization pattern of vascular and tubular bundles alternation. Indeed, even though not primarily affected by genetic ablation, the TAL is secondarily affected in this model. It is sufficient to suppress Itgb1 expression in the CD in order to stimulate proliferation and then disappearance of neighboring TAL cells. This study shows that cell to cell interaction through the ECM is critical for architecture and function maintenance of the outer medulla and that Itgb1 is crucial for this process.
Privacy-Preserving Multi-User Encrypted Access Control Scheme for Cloud-Assisted IoT Applications

In this paper, we present a privacy preserving encrypted access control scheme to aggregate data for Cloud assisted IoT applications. Our scheme is based on attribute based encryption mechanisms and consists in enciphering a set of data contents, with respect to sub-sets of a general access policy. As such, the gateway is able to decrypt the resulting aggregated data only if it holds the matching certified attributes and it has received a sufficient number of partial ciphertexts. Our construction has several advantages. First, it provides a fine-grained access to aggregated data contents that are enciphered by different multiple encrypting entities. Second, it provides a privacy preserving encryption process, such that a curious gateway can neither identify the enciphering IoT device nor decipher single data chunks. Third, our concrete construction provides low computation and communication costs, adapted to resource-constrained devices, compared to most closely related schemes.
A Transparent Hypervisor-level Checkpoint-Restart Mechanism for a Cluster of Virtual Machines

A cluster of virtual machines is a common platform for running MPI applications in cloud computing environments. However, most traditional methods to provide fault tolerance to these applications are not fully transparent and require specific, checkpointing-enabled MPI software. This paper presents a novel Transparent Hypervisor-level Checkpoint-Restart mechanism, namely the Virtual Cluster Checkpoint-Restart (VCCR), to perform checkpoint and restart operations at hypervisor-level. VCCR is highly transparent to MPI applications and guest OS. In VCCR, a software framework consisting of a controller and agent processes is created to perform checkpoint and restart operations for the entire cluster. The checkpoint and restart protocols of VCCR are designed based on the principles of barrier synchronization and virtual time to maintain global consistency and efficiency. We have developed a prototype of VCCR on top the QEMU-KVM software and conducted two preliminary experiments using NAS Parallel Benchmark. Experimental results confirm that VCCR can correctly and efficiently checkpoint and restart a cluster of virtual machines.