Miracle-dz/UniFAR-FTUs huggingface dataset:
MalDetect: A Framework to detect Fast Flux Domains

Performing passive or active attacks through malware-infected systems (bots) by hiding the identity of an attacker, referred to as fast flux is one of the common threat in the context of security. With the connectivity of millions of unsecured systems to networks, detecting fast-flux based attack is one of the major challenge to the industry. This paper presents, a framework which discriminates fast flux domains from Content Distribution Network (CDN) in real-time. The proposed framework embeds features such as, DNS query response, Geographical-location of IP addresses, network distinction and delay in our framework to detect the fast flux domains. Our model has been evaluated using five different machine learning algorithms and out of which, the Random Forest (RF) algorithm performed the best with an F1 score of 0.9915 and Matthews Correlation Coefficient of 0.9672. We also did experimentation on different feature sets individually to identify the best performing feature set in detecting the fast flux domains. We observed Geographical location-based feature set outperformed than the other feature set with a significant accuracy and precision.
The Double-Edged Sword—How Human Papillomaviruses Interact With Immunity in Head and Neck Cancer

Patients with human papilloma virus (HPV)-associated head and neck squamous cell carcinoma (HNSCC) have remarkably better prognosis, which differs from HPV-negative oropharyngeal squamous cell carcinoma (OPSCC) with respect to clinical, genomic, molecular, and immunological aspects, especially having the characteristics of high levels of immune cell infiltration and high degrees of immunosuppression. This review will summarize immune evasion mechanisms in HPV-positive HNSCC, analyze the host various immune responses to HPV and abundant numbers of infiltrating immune cell, and discuss the differences between HPV-positive HNSCC with cervical cancer. A deeper understanding of the immune landscape will help new concepts to emerge in immune-checkpoint oncology, which might be a valuable add-on to established concepts.
Security Considerations in Modular Mobile Manipulation

Mobile manipulation will play an essential role in future production’s intralogistics. In addition, it can be assumed that location-independence of manipulation will greatly contribute to flexible production and higher efficiency in robot use. Modular mobile manipulators can be combined from standalone robotic components like mobile platforms and serial arms. This combination enables more flexibility since the robot can be adapted to specific use-cases by exchanging hardware. However, since those robots tend to be very complex systems, their integration into networked Industry 4.0 environments will also cause security risks. In this paper, we present a security architecture and secure interaction workflows for modular mobile manipulators that on the one hand secure the system against unauthorized manipulation and on the other hand enable the integration of mobile manipulators into larger IT infrastructures. Using the example of our inhouse-developed CHIMERA mobile manipulator, we show which architectural means can be considered in order to make a modular mobile manipulator secure. We analyze the expected attack vectors on mobile manipulators and describe their mitigation within our architecture.
Comparison of Mesenchymal Stromal Cells From Different Origins for the Treatment of Graft-vs.-Host-Disease in a Humanized Mouse Model

Mesenchymal stromal cells (MSCs) have potent immunomodulatory properties that make them an attractive tool against graft- vs.-host disease (GVHD). However, despite promising results in phase I/II studies, bone marrow (BM-) derived MSCs failed to demonstrate their superiority over placebo in the sole phase III trial reported thus far. MSCs from different tissue origins display different characteristics, but their therapeutic benefits have never been directly compared in GVHD. Here, we compared the impact of BM-, umbilical cord (UC-), and adipose-tissue (AT-) derived MSCs on T-cell function in vitro and assessed their efficacy for the treatment of GVHD induced by injection of human peripheral blood mononuclear cells in NOD-scid IL-2Rγnull HLA-A2/HHD mice. In vitro, resting BM- and AT-MSCs were more potent than UC-MSCs to inhibit lymphocyte proliferation, whereas UC- and AT-MSCs induced a higher regulatory T-cell (CD4+CD25+FoxP3+)/T helper 17 ratio. Interestingly, AT-MSCs and UC-MSCs activated the coagulation pathway at a higher level than BM-MSCs. In vivo, AT-MSC infusions were complicated by sudden death in 4 of 16 animals, precluding an analysis of their efficacy. Intravenous MSC infusions (UC- or BM- combined) failed to significantly increase overall survival (OS) in an analysis combining data from 80 mice (hazard ratio [HR] = 0.59, 95% confidence interval [CI] 0.32–1.08, P = 0.087). In a sensitivity analysis we also compared OS in control vs. each MSC group separately. The results for the BM-MSC vs. control comparison was HR = 0.63 (95% CI 0.30–1.34, P = 0.24) while the figures for the UC-MSC vs. control comparison was HR = 0.56 (95% CI 0.28–1.10, P = 0.09). Altogether, these results suggest that MSCs from various origins have different effects on immune cells in vitro and in vivo. However, none significantly prevented death from GVHD. Finally, our data suggest that the safety profile of AT-MSC and UC-MSC need to be closely monitored given their pro-coagulant activities in vitro.
Neural Networks for Image and Video Compression

The data transition has become one of the most actual problems nowadays. Classical methods of video and image compression give great results but refers huge computational resources. One of the improvement ways in video and still images processing and transmitting is using neural networks. In this field they can be used for pre-/post-processing, algorithm optimization, segmentation tasks. There is a lack of studies which pay attention to neural network application for reducing spatial and temporal redundancy in video encoding operations. In this work we propose new methods of preprocessing and postprocessing using convolutional neural networks along with classical algorithms of video compression. The main structure consists of downscale and upscale parts which allows to downsize a transmitted image or frame and reconstruct it in decoder side with high accuracy. The reconstruction process uses preprocessing before upscale operation and post-processing after image size restoration. The current algorithm works in conjunction with the classic video codec H.264/ A VC. The work's results show improvement of the transmitted image quality at a lower bit rate. The new method improves previous ones in term of compression rate.
A Novel Approach for Reversible Realization of 3:8 Decoder Circuit with Optimized Performance Parameters

Reversible realization of digital circuits basically aims for the low loss efficient computing systems. Among combinational digital circuits, decoders are considered as one of the most useful circuit. Till now, many design approaches have been already proposed by various researchers for the reversible realization of decoder circuits. Here, in this paper we have proposed a novel approach for the Reversible realization of 3:8 size decoder circuit with optimized performance parameters as compared to the earlier designs. The comparison is done in terms of total number of Reversible logic gates, constant inputs, garbage outputs and quantum cost. This design may be further explored for other low power applications.
Propagation of Plasma L-Phenylalanine Concentration Fluctuations to the Neurovascular Unit in Phenylketonuria: An in silico Study

Phenylketonuria (PKU) is an inherited metabolic disease characterized by abnormally high concentrations of the essential amino acid L-phenylalanine (Phe) in blood plasma caused by reduced activity of phenylalanine hydroxylase (PAH). While numerous studies have shown association between high plasma Phe concentration and intellectual impairment, it is not clear whether increased Phe fluctuations also observed in PKU affect the brain as well. To investigate this, time-resolved in vivo data on Phe and competing large neutral amino acid (LNAA) concentrations in neurons are needed, but cannot be acquired readily with current methods. We have used in silico modeling as an alternative approach to characterize the interactive dynamics of Phe and competing LNAAs (CL) in the neurovascular unit (NVU). Our results suggest that plasma Phe fluctuations can propagate into the NVU cells and change there the concentration of LNAAs, with the highest magnitude of this effect observed at low frequency and high amplitude-to-mean ratio of the plasma Phe concentration fluctuations. Our model further elucidates the effect of therapeutic LNAA supplementation in PKU, showing how abnormal concentrations of Phe and CL in the NVU move thereby toward normal physiologic levels.
Named Entity Recognition in Noisy Domains

Named Entity Recognition (NER) task is an important part for conversational AI. A typical user of a conversation system has no time to check the spelling or grammar in his or her utterances. Due to that user utterances contain typos and spelling errors, so the noise robustness should be considered as a significant aspect of NER task. In this work, we study noise robustness properties for variants of state of the art named entity recognition models on three languages, English on CoNLL'03 corpus, Russian, on Persons-1000 corpus and French, on CAp'2017 corpus, also, we demonstrate state of the art results for CAp'2017.
BAG3 Suppresses Loading of Ago2 to IL6 mRNA in Pancreatic Ductal Adenocarcinoma

Pancreatic stellate cells (PSCs) are a subset of pancreatic cancer-associated fibroblasts, which play a critical role in pancreatic fibrosis, a characteristic feature of pancreatic cancer. The interplay between PSCs and pancreatic cancer cells is vital for promotion of tumor progression and metastasis. BAG3 is correlated with poor prognostics in patients with pancreatic ductal adenocarcinoma (PDAC), however, the exact mechanisms remain largely unknown. In this study, we demonstrated that BAG3 downregulation decreased IL6 release by PDACs, and IL6 reduction was, at least partially, responsible for suppression of PSCs activation by PDACs with BAG3 downmodulation. Importantly, BAG3 expression positively correlated with fibrosis in pancreatic cancer tissue. With regard to the underlying mechanism, we demonstrated that BAG3 knockdown facilitated recruitment of Agonaute 2 (Ago2) to IL6 mRNA, resulting in destabilization of IL6 mRNA. In addition, the current study demonstrated that phosphorylation at Serine (Ser) 387 site was required for recruitment of Ago2-containing miRISC to IL6 mRNA and BAG3 knockdown facilitated Ago2 loading to IL6 mRNA via increasing its phosphorylation at Ser 387. This study shed new light on the tumor-promoting role of BAG3 in PDAC tumors, suggesting BAG3 might represent an interesting therapeutic opportunity to PDAC patients.
An Energy-Efficient User Association Scheme Based on Robust Optimization in Ultra-Dense Networks

In ultra-dense networks, due to the diversity of content requested by users, the traffic demand of each user is actually uncertain. User association schemes based on exact traffic demand seem to be outdated. With economic and operational considerations and environmental issues, energy efficiency has now become a key pillar of communication network design. Therefore, we propose an energy-efficient user association scheme based on robust optimization, which improves the stability of association and the energy efficiency of the system. First, a robust optimization model for user association scheme is designed in ultra-dense network deployments. In this model, we construct an uncertainty set of bandwidth to describe the uncertainty of the user traffic demand. Then we solve the association matrix through an iterative user association algorithm to maximize system energy efficiency. The simulation results show that the proposed user association scheme has better energy efficiency performance than the signal to interference plus noise ratio (SINR)-based user association scheme.
Congenital Transmission of Toxoplasma gondii After Experimental Reinfection With Brazilian Typical Strains in Chronically Infected Sheep

Toxoplasma gondii is a cause of congenital diseases, miscarriages and stillbirths in production animals. In Brazil, non-archetypal genotypes of the parasite may be related to severe disease. Experimental infection with T. gondii was studied in sheep to analyse congenital transmission-related parameters in reinfections with different Brazilian parasite strains. Thirteen T. gondii-seronegative sheep were orally infected with 2 × 103oocysts for the primary infection: G1 (4 animals) were inoculated with TgCatBr71 strain (Type BrI genotype) and G2 andG3 (5 and 4 animals, respectively) withTgCatBr60 strain (Type BrIII genotype). After chronification of infection, the animals were impregnated. A second infection was performed after 60 days of gestation. TheG1 andG3 animals were inoculated withTgCatBr60BrIII and the G2 animals withTgCatBr71 BrI oocysts. The effects of reinfection were compared with a control group (5 animals) through physical examination, ultrasound imaging and serology. Ovine experimental infections were evaluated using mouse bioassays, molecular analysis, serological tests, histopathology, and immunohistochemistry. No abortions occurred; a seropositive lamb and a mummified fetus from G2-BrIIIxBrI were produced. The vertical transmission rate detected in lambs from chronically infected sheep was 31.6% (6/19). It is demonstrated that reinfection and subsequent congenital transmission occured in one sheep with a primary Brl infection challenged with BrIII genotype of T. gondii. In a twin pregnancy from G2-BrIIIxBrI, congenital transmission from a latent infection was detected in both lambs. Congenital transmission could not be tracked in three lambs. Overall, previous T. gondii infection may fail to protect against congenital transmission from a reinfection and primary infection induced insufficient protection against vertical transmission which must be taken into account in decision-making for the use of seropositive animals as breeders. Similar trials with larger groups and contemplating host cellular immune response studies should be conducted to evaluate the actual impact of T. gondii reinfection involving different strains in sheep.
Enhanced Last-Touch Interaction Attribution Model in Online Advertising

The increased popularity of an internet opened a new way for e-business in terms of digital advertisement. In order to get back and improve the “return of investment”, how to allocate the revenue distribution to different marketing channels comes out to be the key problem in digital advertising. However, last interaction model, first interaction model, last click, last ad words’ click, linear attribution, time-decay attribution, position based attribution models are some of the attribution models developed to attribute and assign contribution to each marketing channel. These existing models consider the contributions of the other channels and some don’t consider the synergistic effects in revenue calculation from different marketing channels. This paper proposes Enhanced Last Touch Interaction (ELTI) model to allocate the revenue distribution to different marketing channels using game theory and synergistic effects. Additionally, the paper also implements and adopts the probabilistic approaches to prevent the simple intuitions made by many other attribution models. Prediction accuracy of above 75% of the ELTI model out performance the state-of-the art models.
On the Design of OFDM-Based Simultaneous Wireless Information and Power Transfer in Fog-Radio Access Networks

The fog-computing-based radio access network (F-RAN) plays a vital role in improving high energy and spectral efficiency. But the problems is that large-scale remote radio heads (RRHs) and fog-computing-based access point (F-APs) result in an increase of transmission power consumption. RF energy harvesting technology is expected to prolong the lifetime of communication networks. In this work, take wireless fronthaul into consideration, we propose a new communication scenario, where the BBU pool transfers information and energy to an user equipment (UE) with the help of a F-AP. Subcarrier separating relaying protocol is adopted at the F-AP to achieve power and information splitting. Afterwards, we formulate a resource allocation problem by maximizing the energy harvested at the UE, subject to three constraints: total transmit power, peak power for each subcarrier, and minimum system throughput. Simulation results provide a practical insight into the impact of some related system parameters, e.g., signal-to-noise power ratio (SNR) and the BBU pool to F-AP distance on the performance of wireless energy harvesting through a F-AP. In particular, the proposed algorithm has significant improvement on the system performance.
HRPSlam: A Benchmark for RGB-D Dynamic SLAM and Humanoid Vision

The dynamic environment is one of the challenging leftover problems for SLAM methods. Recently, researchers made a lot of efforts and achieved some breakthroughs in the dynamic SLAM research field. However, the existed RGB-D SLAM datasets are lacking the dynamic environment. In this paper, we present a novel SLAM benchmark which is dedicated to the dynamic environment SLAM solutions. Moreover, these datasets are acquired from an on-board camera on the HRP-4 humanoid robot, the humanoid dynamic motions, such as the shake from biped walking, the falling down case are included. The data of other on-board sensors, such as IMU, force sensor and joint angle encoders, are provided as well.
Development of B Cell Memory in Malaria

A single exposure to many viral and bacterial pathogens typically induces life-long immunity, however, the development of the protective immunity to Plasmodium parasites is strikingly less efficient and achieves only partial protection, with adults residing in endemic areas often experiencing asymptomatic infections. Although naturally acquired immunity to malaria requires both cell-mediated and humoral immune responses, antibodies govern the control of malarial disease caused by the blood-stage form of the parasites. A large body of epidemiological evidence described that antibodies to Plasmodium antigens are inefficiently generated and rapidly lost without continued parasite exposure, suggesting that malaria is accompanied by defects in the development of immunological B cell memory. This topic has been of focus of recent studies of malaria infection in humans and mice. This review examines the main findings to date on the processes that modulate the acquisition of memory B cell responses to malaria, and highlights the importance of closing outstanding gaps of knowledge in the field for the rational design of next generation therapeutics against malaria.
Uplink Grant-free Multi-codebook SCMA Based on High-overload Codebook Grouping

Fifth generation (5G) wireless networks are expected to support massive connectivity with a great number of users. Current LTE uplink (UL) system is not able to efficiently support massive connectivity, because of the extra overhead and latency with granting. So UL grant-free transmission is proposed for 5G. Sparse code multiple access(SCMA) is a typical non-orthogonal multiple access technology in 5G. With SCMA, multi-user data is spread to same time-frequency resources, such as OFDMA tones, through codebook mapping. In this paper, the general design of high-overload SCMA codebooks is proposed. In the UL grant-free system, Active Users Detection (AUD) in receiver detects the active pilots to determine the active users and their codebooks, and the number of pilots will affect the AUD performance. Every user may use different number of codebooks to encode data to multiple codewords, because of different service, and that is called Multi-codebook SCMA (McSCMA). In this paper, based on grant-free McSCMA, codebook grouping(CG) is proposed for decreasing the number of combinations of codebook(CoC) in order to reduce the number of pilots to improve the AUD performance. The simulation results demonstrate that the design of high-overload codebook is feasible, and CG can improve the AUD performance based on grant-free McSCMA.
Radiotherapy Both Promotes and Inhibits Myeloid-Derived Suppressor Cell Function: Novel Strategies for Preventing the Tumor-Protective Effects of Radiotherapy

Cancer immunotherapies aimed at neutralizing the programmed death-1 (PD-1) immune suppressive pathway have yielded significant therapeutic efficacy in a subset of cancer patients. However, only a subset of patients responds to antibody therapy with either anti-PD-1 or anti-PD-L1 antibodies. These patients appear to have so-called “hot” tumors containing tumor-reactive T cells. Therefore, checkpoint blockade therapy may be effective in a larger percentage of cancer patients if combined with therapeutics that also activate tumor-reactive T cells. Radiotherapy (RT) is a prime candidate for combination therapy because it facilitates activation of both local antitumor immunity and antitumor immunity at non-radiated, distant sites (abscopal response). However, RT also promotes tumor cell expression of PD-L1 and facilitates the development of myeloid-derived suppressor cells (MDSC), a population of immune suppressive cells that also suppress through PD-L1. This article will review how RT induces MDSC, and then describe two novel therapeutics that are designed to simultaneously activate tumor-reactive T cells and neutralize PD-1-mediated immune suppression. One therapeutic, a CD3xPD-L1 bispecific T cell engager (BiTE), activates and targets cytotoxic T and NKT cells to kill PD-L1+ tumor cells, despite the presence of MDSC. The BiTE significantly extends the survival time of humanized NSG mice reconstituted with human PBMC and carrying established metastatic human melanoma tumors. The second therapeutic is a soluble form of the costimulatory molecule CD80 (sCD80). In addition to costimulating through CD28, sCD80 inhibits PD-1 suppression by binding to PD-L1 and sterically blocking PD-L1/PD-1 signaling. sCD80 increases tumor-infiltrating T cells and significantly extends survival time of mice carrying established, syngeneic tumors. sCD80 does not suppress T cell function via CTLA-4. These studies suggest that the CD3xPD-L1 BiTE and sCD80 may be efficacious therapeutics either as monotherapies or in combination with other therapies such as radiation therapy for the treatment of cancer.
Task Allocation for Multi-APs with Mobile Edge Computing

Mobile Edge Computing(MEC) and Ultra-Dense Network(UDN) are two key technologies in next-generation network. UDN can bring a lot of convenience to MEC because small cells in UDN are close to users. However, the integration of these two technologies may bring many problems and one of the problems is task offloading. In this paper, we consider a practical application that contains many dependent subtasks. Some of these subtasks can be executed in parallel. We model the application as a Directed Acyclic Graph (DAG). The UE decides which subtask should be uploaded to which AP. We formulate this problem as a scheduling problem, which is NP-hard. In order to solve this problem, we propose a heuristic algorithm based on the list scheduling algorithm, called Unified Minimum Finish Time Algorithm. This algorithm jointly considers transmission time between APs and offloading time from UE to APs. Simulation results show that our proposed algorithm can significantly improve performance (compared to three baseline policies).