Miracle-dz/UniFAR-FTUs huggingface dataset:
System design for moving target tracking based on mean-shift algorithm

This paper designs a moving target tracking system. Firstly, on the aspect of hardware, a moving target tracking platform is designed, which consists of visible CCD camera, servo PTZ, FPGA control card and PC. The platform can achieve target image acquisition, image transmission, PTZ control and algorithm processing. Secondly, on the aspect of algorithm, aiming at the deficiency of the Mean Shift (MS) algorithm in poor anti-background interference ability, a target modeling method is proposed. The method fuses HSV color feature and edge orientation feature for Mean-Shift iteration. Then the improved algorithm is tested on the DAPRA Egtest01 test sets. Experiment results show that the improved algorithm is good at tracking target whose color is similar to the background color. Finally, the improved algorithm is implemented on the hardware platform. The real-time automatic tracking experiment shows that the system can obtain a satisfied tracking target result.
Difference in code obfuscation between different programming languages

Some small developers are depended on the use of code obfuscation as an protection method for their source code. In this research we look at the result from obfuscation tools on four different programming languages. Those for programming languages are Java, PHP, VB.NET and JavaScript. First we look at which programming language is best and most suitable for obfuscation. In this research, 48 programs of different complexities have been put through five obfuscation tools for each programming language. The result was that VB.NET was easiest to obfuscate and is also the most suitable for obfuscation. After that, we try to reverse engineer the obfuscated code with deobfuscation tools. For Java two tools are used, and for the other languages three tools were used. For each programming language the deobfuscating tools were not able to reverse engineer the code from at least one obfuscation tool. The code obfuscated by JSImg (a JavaScript obfuscator) could not be reversed engineered at all. With VB.NET three obfuscation tools where somewhat successful in obfuscating the code to something that was still difficult to understand after deobfuscating. The research concludes in that Visual Basic . NET is the best programming language to protect source code.
A Novel Architecture of Modified Turbo Codes with an area efficient high speed interleaver

Modified Turbo Codes (MTC) is preferred over conventional Turbo Convolutional Codes (TCC) as they provide nearly the same performance but with the additional benefit of reduced decoding complexity. The Improved Low Complexity Hybrid Turbo Codes (ILCHTC) is a type of MTC, which achieves a Bit Error Rate (BER) performance near to Shannon's limit. This paper presents a high speed novel encoder structure called Enhanced ILCHTC and a high speed low power novel interleaver for the MTC and analyzes its BER performance. From the simulation results, it is observed that BER performance of Enhanced ILCHTC and ILCHTC with proposed interleaver is better and has high degree of error convergence and requires less than 50% of computations than TCC. From the synthesized results, it is observed that the computation time required to shuffle the bits by the proposed interleaver is 7.4% less than the time required by the existing interleaver. In addition, it is observed that the number of logic elements utilized by the proposed interleaver is 95, which is 8% less than the number of logic elements, utilized by the existing interleaver but the tradeoff is power, which is 1.63% more when compared to the existing interleaver. Thus, a high speed area efficient interleaver is proposed along with a novel encoder structure.
Error probability analysis of OOK and variable weight MPPM coding schemes for underwater optical communication systems affected by salinity turbulence

Underwater wireless optical communication (UWOC) systems are presented as a reliable alternative to typical underwater wireless systems (radio-frequency (RF) and acoustic waves) since they can provide much higher data rates with a higher level of communication security. Thus, a variety of potential applications have been recently proposed for UWOC systems, including offshore exploration, environmental monitoring, natural disaster precautions, or military operations. All of these must overcome the unpredictable nature of underwater channels due to scattering and turbulence processes associated with different factors, such as salinity, temperature, bubbles, or turbidity. Lately, a Weibull distribution has been demonstrated to have excellent agreement characterizing the fading of salinity-induced oceanic turbulence. Furthermore, an approximate closed-form expression is derived in this paper for the average bit error rate of any generic coding scheme by means of a Gauss-Laguerre quadrature. Numerical results obtained via Monte-Carlo simulation are provided to corroborate the validity of the derived analytical expressions.
Trainable V4-like filters for detecting retinal vascular bifurcations

Abstract • We propose a novel method to detect vascular bifurcations in retinal fundus images. • Our method is implemented in trainable filters that mimic the properties of some neurons in area V4 of visual cortex. • Such a filter is configured by combining given channels of a bank of Gabor filters using an AND-type operation. – Their selection is determined by an automatic analysis of a user-specified feature. • With only 25 filters we report a recall rate of 98.52% at a precision rate of 95.19% on 40 images.
Degradation kinetics and mechanism of RDX and HMX in TiO2 photocatalysis.

This study was undertaken to examine the photocatalytic degradation of explosives hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) and octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine (HMX) with a circular photocatalytic reactor, using a UV lamp as a light source and TiO2 as a photocatalyst. The effects of various parameters, such as the RDX or HMX concentration, the amount of TiO2, and the initial pH, on the photocatalytic degradation rates of explosives were examined. In the presence of both UV light and TiO2, RDX and HMX were more effectively degraded than with either UV or TiO2 alone. The degradation rates were found to obey pseudo-first-order kinetics represented by the Langmuir-Hinshelwood model. Increases in the RDX and HMX degradation rates were obtained with decreasing initial concentrations of the explosives. The RDX and HMX degradation rates were higher at pH 7 than at either pH 3 or pH 11. A dose of approximately 0.7 g l−1 of TiO2 degraded HMX more rapidly than did higher or lower TiO2 doses. RDX.
A Review on Sentiment Analysis in Arabic Using Document Level

With the rapid increase of web contents and the spread of social media and microblogs such as Twitter and etc., the focus on the sentiment analysis (SA) is deeply being studied. The research on Arabic sentiment analysis is progressing very slow in compared to English sentiment analysis. The former has recently attracted a considerable concentration of researchers. In this respect, this paper aims to present a brief review of some major works that have addressed the document-level sentiment analysis in Arabic. This review includes research and studies published during the period of 2011-2017 for different approaches of document-level sentiment analysis.
Morpho-metabolic Changes In Maize (Zea Mays L.) Under Edta And Citric Acid Mediated Phytoextraction Of Cadmium

To explore some morpho-metabolic characteristics and the phytoextraction potential of maize cultivars when exposed to cadmium stress and chelating effect of different levels of EDTA and citric acid. Five independent experiments were carried out in petri-dishes, sand and soil cultures.Initially six levels of Cd (0, 30, 60, 90, 120 and 150 mg/L) and five EDTA levels i.e. 0.25 (0.67 mM), 0.5 (1.34 mM), 1 (2.69 mM) and 2 g/L (5.38 mM) were optimized for their toxicity on maize. In the second experiment the Cd concentrations were increased to 150, 300, and 450 mg/L and 16 maize accessions were screened for determining their Cd tolerance.Third experiment was conducted to find out the appropriate dose of EDTA and stage of maize plant for maximum Cd uptake. Maximum phytoextraction by shoot and root was recorded for 1 g EDTA/L at harvest-I (10 days after application of EDTA). Fourth experiment using 0, 0.25 (1.19 mM), 0.5 (2.38 mM), 1 (4.76 mM) and 2 g/L (9.52 mM) citric acid along with single dose of Cd (300 mg/L) indicated that citric acid inhibited the uptake of Cd. Final experiment was conducted upto the yield, comprised two maize cultivars (Sahiwal- 2002 and Pak-affgoee), two Cd concentrations (150 and 300 mg/kg soil) with 0.5 g/kg of EDTA (5.38 mM) and citric acid (9.52 mmM). Interactive effect of Cd and chelators on growth, yield, gas exchange characteristics, water relations, plant pigments, biochemical parameters like MDA, antioxidant enzymes (CAT, POD and SOD) and ions accumulation (Ca, Mg, K, P, Zn, Fe and Cd) were determined. All these parameters were negatively affected under Cd application except total protein, antioxidants and carotenoids which increased to combat heavy metal stress.Conclusively, Cd had a negative impact on overall health of maize plant while citric acid enhanced the Cd tolerance, nevertheless EDTA improved Cd uptake in maize plants.
MonolithNet: Training monolithic deep neural networks via a partitioned training strategy

In this study, we explore the training of monolithic deep neural net-works in an effective manner. One of the biggest challenges withtraining such networks to the desired level of accuracy is the dif-ficulty in converging to a good solution using iterative optimizationmethods such as stochastic gradient descent due to the enormousnumber of parameters that need to be learned. To achieve this,we introduce a partitioned training strategy, where proxy layersare connected to different partitions of a deep neural network toenable isolated training of a much smaller number of parametersto convergence. To illustrate the efficacy of this training strategy,we introduce MonolithNet, a massive residual deep neural networkconsisting of 437 million parameters. The trained MonolithNet wasable to achieve a top-1 accuracy of 97% on the CIFAR10 imageclassification dataset, which demonstrates the feasibility of the pro-posed training strategy for training monolithic deep neural networksto high accuracies.
MicroRNA and mRNA Interaction Network Regulates the Malignant Transformation of Human Bronchial Epithelial Cells Induced by Cigarette Smoke

This study analyzes the correlation and interaction of miRNAs and mRNAs and their biological function in the malignant transformation of BEAS-2B cells induced by cigarette smoke (CS). Normal human bronchial epithelial cells (BEAS-2B) were continuously exposed to CS for 30 passages (S30) to establish an in vitro cell model of malignant transformation. The transformed cells were validated by scratch wound healing assay, transwell migration assay, colony formation and tumorigenicity assay. The miRNA and mRNA sequencing analysis were performed to identify differentially expressed miRNAs (DEMs) and differentially expressed genes (DEGs) between normal BEAS-2B and S30 cells. The miRNA-seq data of lung cancer with corresponding clinical data obtained from TCGA was used to further identify lung cancer-related DEMs and their correlations with smoking history. The target genes of these DEMs were predicted using the miRDB database, and their functions were analyzed using the online tool “Metascape. ” It was found that the migration ability, colony formation rate and tumorigenicity of S30 cells enhanced. A total of 42 miRNAs and 753 mRNAs were dysregulated in S30 cells. The change of expression of top five DEGs and DEMs were consistent with our sequencing results. Among these DEMs, eight miRNAs were found dysregulated in lung cancer tissues based on TCGA data. In these eight miRNAs, six of them including miR-96-5p, miR-93-5p, miR-106-5p, miR-190a-5p, miR-195-5p, and miR-1-3p, were found to be associated with smoking history. Several DEGs, including THBS1, FN1, PIK3R1, CSF1, CORO2B, and PREX1, were involved in many biological processes by enrichment analysis of miRNA and mRNA interaction. We identified the negatively regulated miRNA-mRNA pairs in the CS-induced lung cancer, which were implicated in several cancer-related (especially EMT-related) biological process and KEGG pathways in the malignant transformation progress of lung cells induced by CS. Our result demonstrated the dysregulation of miRNA-mRNA profiles in cigarette smoke-induced malignant transformed cells, suggesting that these miRNAs might contribute to cigarette smoke-induced lung cancer. These genes may serve as biomarkers for predicting lung cancer pathogenesis and progression. They can also be targets of novel anticancer drug development.
Modulation of TLR4 Sialylation Mediated by a Sialidase Neu1 and Impairment of Its Signaling in Leishmania donovani Infected Macrophages

Altered sialylation is generally maintained by a fine balance between sialidases and sialyltransferases, which plays an essential role during disease pathogenesis. TLR4 is a membrane-bound highly sialylated glycoprotein predominantly having α2,3-linked sialic acids. It is one of the most important client molecules in the anti-leishmanial innate immune arm. Here, we initiated a comprehensive study on the modulation of TLR4 sialylation in Leishmania donovani (L. d)-infected macrophages by a mammalian sialidase/neuraminidase-1 (Neu1) having substrate specificity toward α2,3-linked sialic acids. We observed reduced membrane-associated Neu1 with its decreased enzyme activity in infected macrophages. Moreover, we demonstrated reduced association of Neu1 with TLR4 leading to enhanced sialylation of TLR4 in these infected cells. Conversely, Neu1 over expression exhibited enhanced association of TLR4 with Neu1 leading to reduced sialylation which possibly linked to increased association of TLR4 with its downstream adaptor protein, MyD88. This, in turn, activated downstream MAP kinase signaling pathway, with enhanced nuclear translocation of NFκB that resulted in increased genetic and protein levels expression of Th1 cytokines and effector molecule nitric oxide secretion which ultimately leads to reduced parasite burden in macrophages. This was further validated by Neu1 silencing in infected macrophages which reversed such a situation. Such events strongly confirm the importance of Neu1 in modulation of TLR4 sialylation during parasite infection resulting in impairment of innate immune response. Furthermore, decreased membrane-bound Neu1 in infected macrophages could be attributed to its reduced tyrosine-phosphorylation as well as diminished association with cathepsin A. Both these phenomenon possibly play significant roles in inhibiting translocation of the sialidase from cytosol to membrane. Taken together, our study first time demonstrated impaired translocation of cytosolic Neu1 to the membrane of L. donovani-infected macrophages due to impaired phosphorylation of this enzyme. This novel finding establishes a link between enhanced α2,3-linked sialic acids on TLR4 and reduced membrane-bound Neu1 which plays a significant role for inhibiting downstream signaling to establish successful infection in the host cells.
Neutrophils in Psoriasis

Neutrophils are the most abundant innate immune cells. The pathogenic roles of neutrophils are related to chronic inflammation and autoimmune diseases. Psoriasis is a chronic systemic inflammatory disease affecting ~2–3% of the world population. The abundant presence of neutrophils in the psoriatic skin lesions serves as a typical histopathologic hallmark of psoriasis. Recent reports indicated that oxidative stress, granular components, and neutrophil extracellular traps from psoriatic neutrophils are related to the initial and maintenance phases of psoriasis. This review provides an overview on the recent (up to 2019) advances in understanding the role of neutrophils in the pathophysiology of psoriasis, including the effects of respiratory burst, degranulation, and neutrophil extracellular trap formation on psoriatic immunity and the clinical relationships.
Influence of Leptin and Adiponectin Supplementation on Intraepithelial Lymphocyte and Microbiota Composition in Suckling Rats

Dietary components in early life play a role in both microbiota and intestinal immune system maturation in mammalian species. Adipokines, as endogenously produced hormones from breast milk, may have an impact on this process. The aim of the present study was to establish the influence of leptin and adiponectin supplementation during suckling on the intraepithelial lymphocyte composition, intestinal barrier function, intestinal gene expression, and gut microbiota in rat. For this purpose, newborn Wistar rats were supplemented daily with leptin, adiponectin, or whey protein concentrate during the first 21 days of life. Lymphocyte composition was established by immunofluorescence staining and flow cytometry analysis; intestinal gene expression by real-time PCR and cecal microbiota were analyzed through 16S rRNA gene sequencing. Although leptin and adiponectin were able to increase the Tc TCRαβ+ and NKT cell proportion, they decreased the NK cell percentage in IEL. Moreover, adipokine supplementation differentially modified CD8+ IEL. While the supplementation of leptin increased the proportion of CD8αα+ IEL (associated to a more intestinal phenotype), adiponectin enhanced that of CD8αβ+ (related to a peripheral phenotype). Furthermore, both adipokines enhanced the gene expression of TNF-α, MUC-2, and MUC-3, and decreased that of FcRn. In addition, the adipokine supplementations decreased the abundance of the Proteobacteria phylum and the presence of Blautia. Moreover, leptin-supplemented animals had lower relative abundance of Sutterella and a higher proportion of Clostridium genus, among others. However, supplementation with adiponectin resulted in lower abundance of the Roseburia genus and a higher proportion of the Enterococcus genus. In conclusion, the supplementation with leptin and adiponectin throughout the suckling period had an impact on both the IEL composition and the gut microbiota pattern, suggesting a modulatory role of these adipokines on the development of intestinal functionality.
Fuzzy Role Based Access Control Design using Fuzzy Ontology

Fuzzy role-based access control (FRBAC) is essential for risk-based environments in many futuristic applications, even though role-based access control (RBAC) is the efficient and widely used access control model for enterprise applications. In FRBAC, authorization related information is vague. It brings the fuzziness in mapping among the components of FRBAC such as user, role and permission. Holding the fuzziness in FRBAC, it is challenging for the security engineer to verify the constraints and correctness of access control policy. On verifying the constraints and correctness of access control policy, knowledge representation techniques are much useful in practice. In this scenario, representing FRBAC using fuzzy ontology might be the right choice for semantic web application. The main objective of this article is to represent the access permissions of FRBAC using fuzzy ontology and verify whether the constraints of FRBAC are possible to get implemented in it or not.
Assessing privacy and quality of synthetic health data

This paper builds on the results of the ESANN 2019 conference paper "Privacy Preserving Synthetic Health Data" [16], which develops metrics for assessing privacy and utility of synthetic data and models. The metrics laid out in the initial paper show that utility can still be achieved in synthetic data while maintaining both privacy of the model and the data being generated. Specifically, we focused on the success of the Wasserstein GAN method, renamed HealthGAN, in comparison to other data generating methods. In this paper, we provide additional novel metrics to quantify the susceptibility of these generative models to membership inference attacks [14]. We also introduce Discriminator Testing, a new method of determining whether the different generators overfit on the training data, potentially resulting in privacy losses. These privacy issues are of high importance as we prepare a final workflow for generating synthetic data based on real data in a secure environment. The results of these tests complement the initial tests as they show that the Parzen windows method, while having a low privacy loss in adversarial accuracy metrics, fails to preserve privacy in the membership inference attack. Only HealthGAN shows both an optimal value for privacy loss and the membership inference attack. The discriminator testing adds to the confidence as HealthGAN retains resemblance to the training data, without reproducing the training data.
Towards Certified Model Checking for PLTL Using One-Pass Tableaux

The standard model checking setup analyses whether the given system specification satisfies a dedicated temporal property of the system, providing a positive answer here or a counter-example. At the same time, it is often useful to have an explicit proof that certifies the satisfiability. This is exactly what the {\it certified model checking (CMC)} has been introduced for. The paper argues that one-pass (context-based) tableau for PLTL can be efficiently used in the CMC setting, emphasising the following two advantages of this technique. First, the use of the context in which the eventualities occur, forces them to fulfil as soon as possible. Second, a dual to the tableau sequent calculus can be used to formalise the certificates. The combination of the one-pass tableau and the dual sequent calculus enables us to provide not only counter-examples for unsatisfied properties, but also proofs for satisfied properties that can be checked in a proof assistant. In addition, the construction of the tableau is enriched by an embedded solver, to which we dedicate those (propositional) computational tasks that are costly for the tableaux rules applied solely. The combination of the above techniques is particularly helpful to reason about large (system) specifications.
Verification Components for Hybrid Systems

These components formalise a semantic framework for the deductive verification of hybrid systems. They support reasoning about continuous evolutions of hybrid programs in the style of differential dynamic logic. Vector fields or flows model these evolutions, and their verification is done with invariants for the former or orbits for the latter. Laws of modal Kleene algebra or categorical predicate transformers implement the verification condition generation. Examples show the approach at work.