Miracle-dz/UniFAR-FTUs huggingface dataset:
A Survey of Deep Learning Methods for Cyber Security

This survey paper describes a literature review of deep learning (DL) methods for cyber security applications. A short tutorial-style description of each DL method is provided, including deep autoencoders, restricted Boltzmann machines, recurrent neural networks, generative adversarial networks, and several others. Then we discuss how each of the DL methods is used for security applications. We cover a broad array of attack types including malware, spam, insider threats, network intrusions, false data injection, and malicious domain names used by botnets.
The application of three-line array CCD photogrammetry theory on the lunar exploration

Now,lunar is the first selected celestial body for space exploration in the world,lunar exploration planet belongs to transmission planet.In this paper,we discuss the lunar photogrammetry using three-line array CCD photogrammetry theory,point out the key techniques and bring forward the resolve projects,which is validated through the simulation experiments.The research results show that three-line array CCD photogrammetry theory can resolve some difficult problems in our lunar exploration and can be used in lunar photogrammetry.
Estimating Root Zone Soil Moisture at Continental Scale Using Neural Networks

This study investigates the feasibility of artificial neural networks (ANNs) to retrieve root zone soil moisture (RZSM) at the depths of 20 cm (SM20) and 50 cm (SM50) at a continental scale, using surface information. To train the ANNs to capture interactions between land surface and various climatic patterns, data of 557 stations over the continental United States were collected. A sensitivity analysis revealed that the ANNs were able to identify input variables that directly affect the water and energy balance in root zone. The data important for RZSM retrieval in a large area included soil texture, surface soil moisture, and the cumulative values of air temperature, surface soil temperature, rainfall, and snowfall. The results showed that the ANNs had high skill in retrieving SM20 with a correlation coefficient above 0.7 in most cases, but were less effective at estimating SM50. The comparison of the ANNs showed that using soil texture data improved the model performance, especially for the estimation of SM50. It was demonstrated that the ANNs had high flexibility for applications in different climatic regions. The method was used to generate RZSM in North America using Soil Moisture and Ocean Salinity (SMOS) soil moisture data, and achieved a spatial soil moisture pattern comparable to that of Global Land Data Assimilation System Noah model with comparable performance to the SMOS surface soil moisture retrievals. The models can be efficient alternatives to assimilate remote sensing soil moisture data for shallow RZSM retrieval.
Modelling Of Renewable Energy Based Electric Robot Taxi with Security Monitoring System

The self-governing vehicle technology is an innovative concept. This paves way to accomplish new technological revolution. The demand of fuel is in peak, this can be balanced by electric source. A renewable source for electric energy is making reasonable changes in this trendy world. In forth coming days renewable electric source will be a lofty revolution and it also assists the society. The utility of renewable energy with self-governing technology will be a progressive novelty & Eco friendly. The competence of e-car is in hike, when paired to the fuel car. The smog is enhancing a worst issue in this universe, and it has an impact over the sustenance, but it can be tackled by this project.
Assessing landslide potential on coastal bluffs near Mukilteo, Washington—Geologic site characterization for hydrologic monitoring

During the summer 2015, the U.S. Geological Survey collected geologic and geotechnical data for two sites on coastal bluffs along the eastern shore of Puget Sound, Washington. The U.S. Geological Survey also installed hydrologic instrumentation at the sites and collected specimens for laboratory testing. The two sites are located on City of Mukilteo open-space land and are about 0.6 kilometers apart. The bluffs at each site are approximately 42 meters high, and rise steeply from the shoreline with 32–35° slopes. The more northerly of the two sites occupies an active landslide and is mostly unvegetated. The other site is forested, and although stable during the preparation of this report, shows evidence of historical and potential landslide activity. The slopes of the bluffs at both sites are mantled by a thin, nonuniform colluvium underlain by clay-rich glacial deposits and tills of the Whidbey Formation or Double Bluff Drift. Till consisting of sand, gravel, and cobbles caps the bluffs and rests on finer grained glacial deposits of sand, silt, and clay. These types of different glacial deposits are dense, vertically fractured, and generally have low permeability, but field observations indicate that locally the deposits are sufficiently permeable to allow lateral flow of water along fractures and subhorizontal boundaries between deposits of different texture. Laboratory tests indicate that many of the deposits are highly plastic, with low hydraulic conductivity, and moderate shear strength. Steep slopes combined with the strength and hydraulic characteristics of the deposits leave the bluffs prone to slope instability, particularly during the wet season when infiltrating rainfall changes moisture content, pore-water pressure, and effective stress within the hillslope. The instrumentation was designed to primarily observe rainfall variability and hydrologic changes in the subsurface that can affect stability of the bluffs, and also to compare the hydrologic response between areas where previous landslides have disturbed vegetation and areas where the bluff is apparently more stable and well vegetated.
Prototype development for secure public instant messaging (IM) at work

This report details the development of a secure messaging add-on for use on public Instant Messaging (IM) networks. It is a continuation of the project discussed in [25]. Due to sociopolitical and monetary reasons, the growth of secure enterprise IM systems has not kept pace with the use of insecure public IM systems. A solution to this problem is to develop a free prototype that is able to secure communications over a public IM network, using a set of guidelines for information security and IM network compatibility. The prototype was able to successfully integrate with a third party IM client and conduct an encrypted session over the MSN Messenger Network. With more development and testing the prototype could become a viable option for use as a secure IM add-on.
Electrical and Optical Properties of Controlled Reduced Graphene Oxide Prepared by a Green and Facile Route

: Three distinct homogeneous multilayer self-standing thin ﬁ lms, composed of stacked reduced graphene oxide (rGO) planes, were produced by improved Hummer’s method. In order to investigate their structural, electrical, and optical properties, the samples were characterized by Raman spectroscopy, ﬁ eld emission scanning electron microscopy (FESEM), four-point probe measurements, and Fourier-transform infrared spectroscopy (FTIR). The Raman spectra of the samples indicate the presence of minor surface defects and a relatively low oxygen content of rGOs. The FESEM images obtained from the samples reveals a smooth sheet-like surface with few wrinkles. Additionally, the cross-sectional images provide con ﬁ rmation of the presence of multi-stacked layer structures. Based on the resistance decreasing by about 0.35 to 0.65 percent per kelvin within the region of ambient temperature, the electrical resistance vs. temperature curves imply semiconducting behavior in the rGOs. The FTIR analysis of the samples conducted within the wavelength range of 2.5 to 25 µm, demonstrates a signi ﬁ cant absorption value exceeding 90%. This observation shows that the developed materials possess favorable characteristics making them an excellent absorber candidate as for sensing detectors in the infrared range. We systematically analyzed and con ﬁ rmed that the structural as well as optical and electrical properties of our obtained rGOs, may be ﬁ ne-tuned by adjusting the initial reactants concentration and annealing temperature.
InterTransViewer: a comparative description of differential gene expression profiles from different experiments

Meta-analysis of transcriptomic data from different experiments has become increasingly prevalent due to a significantly increasing number of genome-wide experiments investigating gene expression changes under various conditions. Such data integration provides greater accuracy in identifying candidate genes and allows testing new hypotheses, which could not be validated in individual studies. To increase the relevance of experiment integration, it is necessary to optimize the selection of experiments. In this paper, we propose a set of quantitative indicators for a comprehensive comparative description of transcriptomic data. These indicators can be easily visualized and interpreted. They include the number of differentially expressed genes (DEGs), the proportion of experiment-specific (unique) DEGs in each data set, the pairwise similarity of experiments in DEG composition and the homogeneity of DEG profiles. For automatic calculation and visualization of these indicators, we have developed the program InterTransViewer. We have used InterTransViewer to comparatively describe 23 auxin- and 16 ethylene- or 1-aminocyclopropane-1-carboxylic acid (ACC)-induced transcriptomes in Arabidopsis thaliana L. We have demonstrated that analysis of the characteristics of individual DEG profiles and their pairwise comparisons based on DEG composition allow the user to rank experiments in the context of each other, assess the tendency towards their integration or segregation, and generate hypotheses about the influence of non-target factors on the transcriptional response. As a result, InterTransViewer identifies potentially homogeneous groups of experiments. Subsequent estimation of the profile homogeneity within these groups using resampling and setting a significance threshold helps to decide whether these data are appropriate for meta-analysis. Overall, InterTransViewer makes it possible to efficiently select experiments for meta-analysis depending on its task and methods.
Mapping the Air Time of Eastern & Western Media on Conflict and War: A Comparative Study of BBC, DW, TRT and Al Jazeera on the Coverage of Second Nagorno-Karabakh War & the Aftermath

A significant body of literature exists examining the coverage of the first Nagorno-Karabakh war by Western media. However, there is a lack of comparative studies analyzing the coverage of the second Nagorno-Karabakh war by both Eastern and Western media. We examined 245 news reports from two prominent Eastern channels (TRT World and Al-Jazeera) and two prominent Western channels (BBC World News and DW) through content and frequency analyses. This study aims to investigate the magnitude of Air Time dedicated to the second Karabakh war by both Eastern and Western media, examining the disparities between the two. Additionally, it seeks to analyze the lexico-semantic linguistic manipulation techniques employed and the use of euphemisms and dysphemisms during the coverage. Our research reveals a pronounced bias favoring Armenia in the coverage provided by both Western television channels. Conversely, among Eastern television stations, TRT World exhibited a distinct pro-Azerbaijani leaning, while Al-Jazeera maintained a relatively neutral standpoint. This clearly shows that media outlets and journalists are not free from bias. They predominantly mix their reporting with their ideological beliefs or faith, state interests, and their country’s foreign policy directions.
Towards Compact Identity-based Encryption on Ideal Lattices

Basic encryption and signature on lattices have comparable eﬀiciency to their classical counterparts in terms of speed and key size. However, Identity-based Encryption (IBE) on lattices is much less eﬀi-cient in terms of compactness, even when instantiated on ideal lattices and in the Random Oracle Model (ROM). This is because the underlying preimage sampling algorithm used to extract the users’ secret keys requires huge public parameters. In this work, we specify a compact IBE instantiation for practical use by introducing various optimizations. Specifically, we first propose a modified gadget to make it more suitable for the instantiation of practical IBE. Then, by incorporating our gad-get and the non-spherical Gaussian technique, we provide an eﬀicient preimage sampling algorithm, based on which, we give a specification of a compact IBE on ideal lattice. Finally, two parameter sets and a proof-of-concept implementation are presented. Given the importance of the preimage sampling algorithm in lattice-based cryptography, we believe that our technique can also be applied to the practical instantiation of other advanced cryptographic schemes.
Scaling up evidence-based digital early life nutrition interventions in a county setting: an implementation trial – protocol for Phase 2 of the Nutrition Now project

Background Few effective health interventions transition from smaller efficacy or effectiveness studies to real-world implementation at scale, representing a gap between evidence and practice. Recognising this, we have developed Nutrition Now – a tailored digital resource building on four efficacious dietary interventions, aiming to improve nutrition in the important first 1,000 days of life. Nutrition Now targets and guides expectant parents and parents of 0–2 year olds, serves as a reliable source of evidence-based information for midwives and public health nurses at maternal and child healthcare (MCH) centres, and offers pedagogical tools for early childhood education and care (ECEC) staff. The aim of this study is to implement Nutrition Now at scale and evaluate the impact of different sets of multifaceted implementation strategies on implementation outcomes. Methods A quasi-experimental design with three study arms will be used, providing either low, medium or high implementation support, when rolled out in 50 municipalities in 2 counties in Norway. Nutrition Now will be implemented in MCH and ECEC settings and made available to expectant parents and parents of 0–2 year olds through social media and MCH. The implementation support builds on strategies described in the Expert Recommendations for Implementing Change (ERIC) implementation framework and is informed by dialogues with stakeholders. Impact of the different degree of implementation support will be assessed by examining reach, adoption, fidelity, and sustainability using usage data generated from the Nutrition Now resource, publicly available municipal data and qualitative interviews with MCH and ECEC staff. Discussion Nutrition Now Phase 2 will break new ground by scaling up successively delivered and complementary dietary interventions in the first 1,000 days of life in a real-life context. The project also seeks to identify what level of implementation support is most effective when implementing digital, scalable, evidence-based early-life nutrition interventions in community settings. The project will inform implementation research and provide knowledge about effective implementation strategies to be used in a national scale-up of Nutrition Now. Trial registration The study is registered prospectively (submitted 14/06/2022, registration date: 19/06/2022) in the International Standard Randomised Controlled Trial Number registry (ISRCTN): reg. Number: ISRCTN10694967, https://doi.org/10.1186/ISRCTN10694967.
Little evidence for a noun bias in Tseltal spontaneous speech

This study examines whether children acquiring Tseltal (Mayan) demonstrate a noun bias – an overrepresentation of nouns in their early vocabularies. Nouns, specifically concrete and animate nouns, are argued to universally predominate in children’s early vocabularies because their referents are naturally available as bounded concepts to which linguistic labels can be mapped. This early advantage for noun learning has been documented using multiple methods and across a diverse collection of language populations. However, past evidence bearing on a noun bias in Tseltal learners has been mixed. Tseltal grammatical features and child–caregiver interactional patterns dampen the salience of nouns and heighten the salience of verbs, leading to the prediction of a diminished noun bias and perhaps even an early predominance of verbs. We here analyze the use of noun and verb stems in children’s spontaneous speech from egocentric daylong recordings of 29 Tseltal learners between 0;9 and 4;4. We find weak to no evidence for a noun bias using two separate analytical approaches on the same data; one analysis yields a preliminary suggestion of a flipped outcome (i.e. a verb bias). We discuss the implications of these findings for broader theories of learning bias in early lexical development.
Learning solution of nonlinear constitutive material models using physics-informed neural networks: COMM-PINN

We applied physics-informed neural networks to solve the constitutive relations for nonlinear, path-dependent material behavior. As a result, the trained network not only satisﬁes all thermodynamic constraints but also instantly provides information about the current material state (i.e., free energy, stress, and the evolution of internal variables) under any given loading scenario without requiring initial data. One advantage of this work is that it bypasses the repetitive Newton iterations needed to solve nonlinear equations in complex material models. Additionally, strategies are provided to reduce the required order of derivation for obtaining the tangent operator. The trained model can be directly used in any ﬁnite element package (or other numerical methods) as a user-deﬁned material model. However, challenges remain in the proper deﬁnition of collocation points and in integrating several non-equality constraints that become active or non-active simultaneously. We tested this methodology on rate-independent processes such as the classical von Mises plasticity model with a nonlinear hardening law, as well as local damage models for interface cracking behavior with a nonlinear softening law. Finally, we discuss the potential and remaining challenges for future developments of this new approach.
Research on the simplification of building complex model under multi-factor constraints

With the wide application of 3D building cluster models in urban planning, visualization and other fields, how to improve the rendering efficiency and reduce the computational cost of building cluster models has become an important issue. To address this problem, this paper proposes a visual perception evaluation model used to assess the weights of buildings based on multi-factor considerations to determine the order of building simplification, and weights the vertex importance for the classical QEM algorithm to redefine the collapsing cost of the edges, which achieves the purpose of reducing the complexity of the model while maintaining the visual quality. Experimental results show that the algorithm can significantly reduce the model rendering time and computational cost while maintaining the visual quality.
Finite-Time pth Moment Asymptotically Bounded for Stochastic Nonlinear Systems and Its Application in Neural Networks Synchronization

This article pays attention to finite-time (FnT) <inline-formula> <tex-math notation="LaTeX">$p$ </tex-math></inline-formula>th moment asymptotically bounded (MAB) for stochastic nonlinear systems (SNSs) and its application to <inline-formula> <tex-math notation="LaTeX">$p$ </tex-math></inline-formula>th moment quasi-synchronization (MQS) of stochastic neural networks (SNNs) based on parameter mismatches. First, this article develops FnT asymptotically bounded theorems SNSs. In detail, several new FnT <inline-formula> <tex-math notation="LaTeX">$p$ </tex-math></inline-formula>th MAB theorems of the SNSs are proposed, the mathematical expression of finite settlement time is obtained, and the bounds of MAB are estimated. Second, new sufficient conditions are designed to ensure FnT <inline-formula> <tex-math notation="LaTeX">$p$ </tex-math></inline-formula>th MQS of SNNs. In particular, novel FnT <inline-formula> <tex-math notation="LaTeX">$p$ </tex-math></inline-formula>th MQS conditions of the SNNs enlarge the value of <inline-formula> <tex-math notation="LaTeX">$p$ </tex-math></inline-formula>. Moreover, when the initial value of the system meets certain conditions, the smaller the <inline-formula> <tex-math notation="LaTeX">$p$ </tex-math></inline-formula> is, the smaller the system synchronization control energy consumption is, which can be more meaningful. Finally, a numeric example illustrates the validity of the methods.
Short-period Lg magnitudes: Instrument, attenuation, and source effects

Abstract The applicaton of the Nutli (1973) definition of the m bLg magnitude to instruments and wave periods other than the short-period WWSSN seismograph is examined. The basic conclusion is that the Nuttli (1973) definition is applicable to a wider range of seismic instruments if the log 10 ( A/T ) term is replaced by log 10 A . For consistency and precision, the notation m bLg should be applied only to magnitudes based upon 1.0 Hz observations. The m bLg magnitude definition was constrained to be consistent with teleseismic P -wave m b estimates from four Central United States earthquakes. In general, for measurements made at a frequency f , the notation m Lg ( f ) should be used, where m L g ( f ) = 2.94 + 0.833 log ⁡ 10 ( r / 10 ) + 0.4342 γ r + log ⁡ 10 A , and r is the epicentral distance in kilometers, γ is the coefficient of anelastic attenuation, and A is the reduced ground amplitude in microns. Given its stability when estimated from different instruments, the m Lg ( f ) magnitude is an optimum choice for an easily applied, standard magnitude scale for use in regional seismic studies.
Chemical Characterization, Leishmanicidal Activity and In Vitro Cytotoxicity of the Essential Oil Extracted from Pectis brevipedunculata (Gardner) Sch.Bip. and Its Incorporation into Microemulsion Systems

Pectis brevipedunculata (Gardner) Sch.Bip. , known in Brazil as alecrim do campo, is a small Asteraceae family plant with a calming effect and consumed as tea. This species contains components, such as neral and geranial, that display various biological activities, such as leishmanicidal. The aim was to chemically characterize the essential oil (EO) obtained from P. brevipedunculata (EO-PB) by hydrodistillation and a microemulsion formulated with EO (ME-PB), Tween 80 and Transcutol P, assess the leishmanicidal effect against Leishmania (L.) amazonensis promastigotes and cytotoxicity against RAW 264.7. EO-PB and ME-PB were analyzed by Gas Chromatography Mass Spectrometry (GC/MS). Monoterpene hydrocarbons were noteworthy among the identified compounds. The main EO-PB constituents were α-pinene and limonene, followed by neral and geranial, which were maintained in ME-PB. EO-PB presented an inhibitory concentration (IC50) of 20 µg/mL and ME-PB of 0.93 µg/mL. ME-PB inhibition towards the parasite was 20-fold higher than that of EO-PB. This indicated that EO incorporation to the microemulsion resulted in optimized biological activity. Selectivity indices indicate that ME-PB is more selective concerning parasite inhibition. Thus, ME-PB may comprise an adequate approach against Leishmania, as the inhibitory concentration (IC50) promastigotes was lower than that considered toxic for cells cell cytotoxicity of 50% (CC50).