Miracle-dz/UniFAR-FTUs huggingface dataset:
Domain Aware Markov Logic Networks

Combining logic and probability has been a long stand- ing goal of AI research. Markov Logic Networks (MLNs) achieve this by attaching weights to formulas in first-order logic, and can be seen as templates for constructing features for ground Markov networks. Most techniques for learning weights of MLNs are domain-size agnostic, i.e., the size of the domain is not explicitly taken into account while learn- ing the parameters of the model. This often results in ex- treme probabilities when testing on domain sizes different from those seen during training. In this paper, we propose Domain Aware Markov logic Networks (DA-MLNs) which present a principled solution to this problem. While defin- ing the ground network distribution, DA-MLNs divide the ground feature weight by a scaling factor which is a function of the number of connections the ground atoms appearing in the feature are involved in. We show that standard MLNs fall out as a special case of our formalism when this func- tion evaluates to a constant equal to 1. Experiments on the benchmark Friends & Smokers domain show that our ap- proach results in significantly higher accuracies compared to existing methods when testing on domains whose sizes different from those seen during training.
Deep Learning for Real-Time Robust Facial Expression Analysis

The aim of this investigation is to classify real-life facial images into one of six types of emotions. For solving this problem, we propose to use deep machine learning algorithms and convolutional neural network (CNN). CNN is a modern type of neural network, which allows for rapid detection of various objects, as well as to make an effective object classification. For acceleration of CNN learning stage, we use supercomputer NVIDIA DGX-1. This process was implemented in parallel on a large number of independent streams on GPU. Numerical experiments for algorithms were performed on the images of Multi-Pie image database with various lighting of scene and angle rotation of head. For developed models, several metrics of quality were calculated. The designing algorithm was used in real-time video processing in human-computer interaction systems. Moreover, expression recognition can apply in such fields as retail analysis, security, video games, animations, psychiatry, automobile safety, educational software, etc.
Anti-inflammatory consequences of bile acid accumulation in virus-infected bile duct ligated mice

Cholestatic patients exhibiting high bile acid serum levels were reported to be more susceptible to bacterial and viral infections. Animal studies in bile duct ligated (BDL) mice suggest that cholestasis leads to an aggravation of hepatic bacterial infections. We have investigated the impact of cholestasis on mouse cytomegalovirus (MCMV)-induced immune responses and viral replication. While MCMV did not aggravate BDL-induced liver damage, BDL markedly reduced MCMV-triggered chemokine expression and immune cell recruitment to the liver. MCMV-infected BDL mice showed diminished trafficking of Ly6C+/F4/80+ myeloid cells and NK1.1+ NK cells to the liver compared to MCMV infected control mice. Moreover, virus-driven expression of CCL7, CCL12, CXCL9 and CXCL10 was clearly impaired in BDL- compared to sham-operated mice. Furthermore, production of the anti-inflammatory cytokine IL-10 was massively augmented in infected BDL mice. In contrast, intra- and extrahepatic virus replication was unaltered in BDL-MCMV mice when compared to sham-MCMV mice. Cholestasis in the BDL model severely impaired pathogen-induced chemokine expression in the liver affecting CCR2- and CXCR3-dependent cell trafficking. Cholestasis resulted in reduced recruitment of inflammatory monocytes and NK cells to the liver.
Monitoring-based auto-scalability across hybrid clouds

Cloud computing is a relatively new type of Internet-based computing that becomes more and more popular. Using methods like virtualization, adopting architectures based on microservices, automation of building and deployment processes, Cloud could provide on-demand resources and scale them accordingly to a Service Level Agreement (SLA). Even if there are a lot of Cloud computing providers (like Amazon AWS, Microsoft Azure, IBM, Google etc.), many of them providing advanced services, already deployed technologies, auto-scaling and monitoring tools, on the long run a private Cloud could cost less than a public Cloud. On the other hand, a private Cloud has the disadvantage of lacking hardware resources for scaling an unexpected spike of usage or periodical growths in the number of requests. This problem could be solved using a public Cloud provider API for extending the hardware by buying and selling resources, using a pay-per-use or a pay-as-you-go model. This paper describes and evaluates a private Cloud architecture capable of on demand deployment of microservices based applications, monitoring every instance using CPU, memory, networking and disk data collectors' software, monitoring every task queue and horizontally auto-scaling the number of instances per service. Using Cloud monitoring data, SLA and budget constraints we decide if a new instance should be spawned or terminated in the private Cloud or in a public Cloud. From the customer point of view the process of auto-scaling across the hybrid Cloud is transparent, but requires a horizontally scalable service. We will illustrate our work running an application packaged as microservices in containers in a Kubernetes private Cloud that will be extended using public resources from AWS. The results of the paper offers an architectural model that can be used to build an in-house, scalable Cloud.
Synergistic Anti-MRSA Activity of Cationic Nanostructured Lipid Carriers in Combination With Oxacillin for Cutaneous Application

Nanoparticles have become a focus of interest due to their ability as antibacterial agents. The aim of this study was to evaluate the anti-methicillin-resistant Staphylococcus aureus (MRSA) activity of cationic nanostructured lipid carriers (NLC) combined with oxacillin against ATCC 33591 and clinical isolate. The cationic resource on the NLC surface was soyaethyl morpholinium ethosulfate (SME). NLC loaded with oxacillin was produced to assess the antibacterial activity and the effectiveness of topical application for treating cutaneous infection. The hydrodynamic diameter and zeta potential of oxacillin-loaded NLC were 177 nm and 19 mV, respectively. When combined with NLC, oxacillin exhibited synergistic MRSA eradication. After NLC encapsulation, the minimum bactericidal concentration (MBC) of oxacillin decreased from 250 to 62.5 μg/ml. The combined NLC and oxacillin reduced the MRSA biofilm thickness from 31.2 to 13.0 μm, which was lower than the effect of NLC (18.2 μm) and antibiotic (25.2 μm) alone. The oxacillin-loaded NLC showed significant reduction in the burden of intracellular MRSA in differentiated THP-1 cells. This reduction was greater than that achieved with individual treatment. The mechanistic study demonstrated the ability of cationic NLC to disrupt the bacterial membrane, leading to protein leakage. The cell surface disintegration also increased oxacillin delivery into the cytoplasm, activating the bactericidal process. Topical NLC treatment of MRSA abscess in the skin decreased the bacterial load by log 4 and improved the skin’s architecture and barrier function. Our results demonstrated that a combination of nanocarriers and an antibiotic could synergistically inhibit MRSA growth.
ExtendJ: extensible Java compiler

ExtendJ (formerly JastAddJ) is an extensible Java compiler, supporting full Java source-to-bytecode compilation. ExtendJ enables researchers and developers to easily build powerful language extensions, custom static analyses, and other tools for Java. ExtendJ is built with Reference Attribute Grammars and Aspect Oriented Programming, enabling easy extension development.
Is Virtual Citizen Science A Game?

The use of game elements within virtual citizen science is increasingly common, promising to bring increased user activity, motivation, and engagement to large-scale scientific projects. However, there is an ongoing debate about whether or not gamifying systems such as these is actually an effective means by which to increase motivation and engagement in the long term. While gamification itself is receiving a large amount of attention, there has been little beyond individual studies to assess its suitability or success for citizen science; similarly, while frameworks exist for assessing citizen science performance, they tend to lack any appreciation of the effects that game elements might have had. We therefore review the literature to determine what the trends are regarding the performance of particular game elements or characteristics in citizen science, and survey existing projects to assess how popular different game features are. Investigating this phenomenon further, we then present the results of a series of interviews carried out with the EyeWire citizen science project team to understand more about how gamification elements are introduced, monitored, and assessed in a live project. Our findings suggest that projects use a range of game elements with points and leaderboards the most popular, particularly in projects that describe themselves as “games. ” Currently, gamification appears to be effective in citizen science for maintaining engagement with existing communities, but shows limited impact for attracting new players.
Variable Neighborhood Search for Partitioning Sparse Biological Networks into the Maximum Edge-Weighted <inline-formula><tex-math notation="LaTeX">$k$</tex-math><alternatives><mml:math><mml:mi>k</mml:mi></mml:math><inline-graphic xlink:href="grbic-ieq1-2898189.gif"/></alternatives></inline-formula>-

In a network, a <inline-formula><tex-math notation="LaTeX">$k$</tex-math><alternatives><mml:math><mml:mi>k</mml:mi></mml:math><inline-graphic xlink:href="grbic-ieq2-2898189.gif"/></alternatives></inline-formula>-plex represents a subset of <inline-formula><tex-math notation="LaTeX">$n$</tex-math><alternatives><mml:math><mml:mi>n</mml:mi></mml:math><inline-graphic xlink:href="grbic-ieq3-2898189.gif"/></alternatives></inline-formula> vertices where the degree of each vertex in the subnetwork induced by this subset is at least <inline-formula><tex-math notation="LaTeX">$n-k$</tex-math><alternatives><mml:math><mml:mrow><mml:mi>n</mml:mi><mml:mo>-</mml:mo><mml:mi>k</mml:mi></mml:mrow></mml:math><inline-graphic xlink:href="grbic-ieq4-2898189.gif"/></alternatives></inline-formula>. The maximum edge-weight <inline-formula><tex-math notation="LaTeX">$k$</tex-math><alternatives><mml:math><mml:mi>k</mml:mi></mml:math><inline-graphic xlink:href="grbic-ieq5-2898189.gif"/></alternatives></inline-formula>-plex partitioning problem is to find the <inline-formula><tex-math notation="LaTeX">$k$</tex-math><alternatives><mml:math><mml:mi>k</mml:mi></mml:math><inline-graphic xlink:href="grbic-ieq6-2898189.gif"/></alternatives></inline-formula>-plex partitioning in edge-weighted network, such that the sum of edge weights is maximal. The Max-EkPP has an important role in discovering new information in large biological networks. We propose a variable neighborhood search (VNS) algorithm for solving Max-EkPP. The VNS implements a local search based on the 1-swap first improvement strategy and the objective function that takes into account the degree of every vertex in each partition. The objective function favors feasible solutions and enables a gradual increase of the function's value, when moving from slightly infeasible to barely feasible solutions. Experimental computation is performed on real metabolic networks and other benchmark instances from the literature. Comparing to the previously proposed integer linear programming (ILP), VNS succeeds to find all known optimal solutions. For all other instances, the VNS either reaches previous best known solution or improves it. The proposed VNS is also tested on a large-scale dataset not considered up to now.
Hainanecio, a new genus of the Senecioneae, Asteraceae from China

Hainanecio Y. Liu & Q. E. Yang, a new genus of Senecioneae, Asteraceae, from Hainan Island, China, is described based on Sinosenecio hainanensis (Chang & Tseng) C. Jeffrey & Y. L. Chen. Distinguishing characters include pinnately-veined, ovate to obovate leaves, hemispherical involucres, white florets, apically acuminate and often 2-denticulate rays, basic chromosome number of x=29, typically triporate pollen, and helianthoid type of pollen wall ultrastructure.
Do Gravitational Waves Carry Energy? -Critique of a Procrustean Practice

We submit that, contrary to the standard view, gravitational waves (GWs) do not carry energy-momentum. Analysing the four standard arguments on which the standard view rests - viz. the kinetic effects of a GW on a detector, Feynman’s Sticky Bead Argument, an application of Noether’s Theorem and a general perturbative approach – we find none of them to be successful: Pre-relativistic premises underlie each of them – premises that, as we argue, no longer hold in General Relativity (GR). Finally, we outline a GR-consistent interpretation of the effects and, in particular, the spin-down of binary systems.
Beneficial microbes in a changing environment: are they always helping plants to deal with insects?

Summary Plants have a complex immune system that defends them against attackers (e.g. herbivores and microbial pathogens) but that also regulates the interactions with mutualistic organisms (e.g. mycorrhizal fungi and plant growth-promoting rhizobacteria). Plants have to respond to multiple environmental challenges, so they need to integrate both signals associated with biotic and abiotic stresses in the most appropriate response to survive. Beneficial microbes such as rhizobacteria and mycorrhizal fungi can help plants to ‘deal’ with pathogens and herbivorous insects as well as to tolerate abiotic stress. Therefore, beneficial microbes may play an important role in a changing environment, where abiotic and biotic stresses on plants are expected to increase. The effects of beneficial microbes on herbivores are highly context-dependent, but little is known on what is driving such dependency. Recent evidence shows that abiotic stresses such as changes in soil nutrients, drought and salt stress, as well as ozone can modify the outcome of plant–microbe–insect interactions. Here, we review how abiotic stress can affect plant–microbe, plant–insect and plant–microbe–insect interactions, and the role of the network of plant signal-transduction pathways in regulating such interactions. Most of the studies on the effects of abiotic stress on plant–microbe–insect interactions show that the effects of microbes on herbivores (positive or negative) are strengthened under stressful conditions. We propose that, at least in part, this is due to the crosstalk of the different plant signalling pathways triggered by each stress individually. By understanding the cross-regulation mechanisms we may be able to predict the possible outcomes of plant-microbe–insect interactions under particular abiotic stress conditions. We also propose that microbes can help plants to deal with insects mainly under conditions that compromise efficient activation of plant defences. In the context of global change, it is crucial to understand how abiotic stresses will affect species interactions, especially those interactions that are beneficial for plants. The final aim of this review is to stimulate studies unravelling when these ‘beneficial’ microbes really benefit a plant.
Data-driven management of dynamic public transport

The theme of the Fourth Industrial Revolution and Smart City appears increasingly also in transport. The aim of this paper is to provide an approach for evaluation of smart solution in public transport. A solution using combination of dynamic service and the Big Data is described in more detail. This dynamic service is influenced by many parameters and one of them can be the movement of the population. The movement of the population can be monitored through the Big Data.
Detection of multiple fluorescent labels using superconducting tunnel junction detectors

We show that cryogenically cooled, photon counting superconducting tunnel junctions (STJs) can be used to simultaneously record the optical spectra from multiple biological fluorochromes. Measurements with a single-pixel tantalum STJ with a wavelength resolving power R=λ/Δλ of about 10 confirm the expected sensitivity advantage with respect to the photomultiplier-based detectors commonly used to record signals from microarrays and other fluorescent biological systems.
An efficient covert channel

The signature algorithm with a broadband covert channel that does not want the sender to compromise the security of the entity signing key is the Elgamal signature algorithm. But contrary to the common idea, the design of the digital signature scheme does not maximize the covert uses of its signatures, but minimizes them. The suggested scheme illustrates that several discrete logarithm schemes are vulnerable, since they are used in more than one group concurrently, and the key data may reveal by these groups which discrete logarithm are facile, but the digital signature scheme is more secure in this means.
IN VITRO AND IN VIVO STUDIES OF THE EFFECTS OF COLD ARGON PLASMA ON DECREASING THE COAGULATION TIME

Introduction Cold plasma is a self-sterilized, painless, and non-contact method in surgeries. These properties allow it to be applied to the living tissues and heat-sensitive parts. The aim of this study was to design a new cold plasma producer device and evaluate the effects of cold argon plasma on decreasing the coagulation time of blood drop in vitro and that of the injured liver blood in vivo. Materials and Methods In an experimental study, two blood drops of a normal healthy human were placed on a glass slide. The experimental sample was irradiated by plasma until the complete coagulation occurred, while the control sample remained intact. The complete coagulation time was then measured for both samples. In another part of our study, 20 rats were divided into two experimental and control groups and anesthetized for experimentation. Livers of the rats in the control group were incised and the bleeding time was measured until complete coagulation. Livers of the experimental rats were irradiated by plasma after being incised, and the complete coagulation time was measured. Results Cold plasma treatment increased the speed of blood coagulation in both blood drop in vitro and the injured liver blood.in vivo. Histopathological examinations revealed that plasma treatment caused no significant tissue damages as compared with the control group. Conclusion The use of argon plasma coagulation device at the time of surgery, in addition to accelerating blood coagulation, caused no injury and burning on tissues. Plasma increases the platelets activation, fibroblasts proliferation and fibrin production. the mechanism of action is likely mediated by exogenous nitric oxide.
Candidiasis Treatment Should Pay Attention to the Immune Changing Patients

The guideline of the Infectious Diseases Society of America (IDSA) about candidiasis is a key standard for clinical doctors to treat patients, and textbook to teach medical students. However, in the progress of clinical treatment and documents checking, the immune changing patients, who suffered candidiasis, may be mismatched to the clinical treatment guidelines. The opinion could be shown by the literature of gastrointestinal system, and respiratory system, which suffered severely fungal infection mostly, mainly connected with the outside world and inside organ systems of the human body. They could show some patients have been excess treatment, and we should pay attention to the immune changing patients.
Comparison of rainfall estimations by TRMM 3B42, MPEG and CFSR with ground-observed data for the Lake Tana basin in Ethiopia

Planning for drought relief and floods in developing countries is greatly hampered by the lack of a sufficiently dense network of weather stations measuring precipitation. In this paper, we test the utility of three satellite products to augment the ground-based precipitation measurement to provide improved spatial estimates of rainfall. The three products are the Tropical Rainfall Measuring Mission (TRMM) product (3B42), Multi-Sensor Precipitation Estimate–Geostationary (MPEG) and the Climate Forecast System Reanalysis (CFSR). The accuracy of the three products is tested in the Lake Tana basin in Ethiopia, where 38 weather stations were available in 2010 with a full record of daily precipitation amounts. Daily gridded satellite-based rainfall estimates were compared to (1) point-observed ground rainfall and (2) areal rainfall in the major river sub-basins of Lake Tana. The result shows that the MPEG and CFSR satellites provided the most accurate rainfall estimates. On average, for 38 stations, 78 and 86% of the observed rainfall variation is explained by MPEG and CFSR data, respectively, while TRMM explained only 17% of the variation. Similarly, the areal comparison indicated a better performance for both MPEG and CFSR data in capturing the pattern and amount of rainfall. MPEG and CFSR also have a lower root mean square error (RMSE) compared to the TRMM 3B42 satellite rainfall. The bias indicated that TRMM 3B42 was, on average, unbiased, whereas MPEG consistently underestimated the observed rainfall. CFSR often produced large overestimates.
Successful Treatment of Pulmonary Graft versus Host Disease with Aerosolized Cyclosporine

We report the successful use of aerosolized cyclosporine (CSA ) therapy in two children who developed a bronchiolitis obliterans (BOS) following a haploidentical peripheral blood stem cell transplant for refractory biphenotypic leukemia and HLA-matched sibling bone marrow transplant for relapsed acute lymphoblastic leukemia respectively. CSA was non-toxic and was associated with signi icant a improvement and long-term stabilization in pulmonary function. Patients received CSA for 6 and 18 a months, respectively which allowed both patients to be liberated from additional immunosuppression. CSA appeared to be a safe, effective, and steroid-sparing therapy for chronic BOS following allogeneic a hematopoietic stem cell transplantation (allo-HSCT).
Network Behavior Abnormal Detection for Electricity Management System Based on Long Short-Term Memory

In this paper, we propose a deep learning based algorithm to implement the network behavior abnormal detection for electricity management system. The framework is composed by three main parts: network behavior feature generation, behavior labeling system, and LSTM based audition model. In the feature generation module, the user log file can be converted into time series of vectors that represent the features of user operation. Then the user behavior is labeled as normal or abnormal by exporters or defined simple rules. Finally, a LSTM based deep learning model will be trained from the tagged user log features and will be used to automatically audit the user behavior. According to the experimental results on simulated user log, the proposed algorithm can effectively detect the multi-type abnormal behaviors defined by exporters in the Electricity management system. The overall accuracy in the test dataset is over 96% which can improve the existing system in large extent.