Miracle-dz/UniFAR-FTUs huggingface dataset:
Machine-Learning-Based Android Malware Family Classification Using Built-In and Custom Permissions

Malware family classification is grouping malware samples that have the same or similar characteristics into the same family. It plays a crucial role in understanding notable malicious patterns and recovering from malware infections. Although many machine learning approaches have been devised for this problem, there are still several open questions including, “Which features, classifiers, and evaluation metrics are better for malware familial classification”? In this paper, we propose a machine learning approach to Android malware family classification using built-in and custom permissions. Each Android app must declare proper permissions to access restricted resources or to perform restricted actions. Permission declaration is an efficient and obfuscation-resilient feature for malware analysis. We developed a malware family classification technique using permissions and conducted extensive experiments with several classifiers on a well-known dataset, DREBIN. We then evaluated the classifiers in terms of four metrics: macrolevel F1-score, accuracy, balanced accuracy (BAC), and the Matthews correlation coefficient (MCC). BAC and the MCC are known to be appropriate for evaluating imbalanced data classification. Our experimental results showed that: (i) custom permissions had a positive impact on classification performance; (ii) even when the same classifier and the same feature information were used, there was a difference up to 3.67% between accuracy and BAC; (iii) LightGBM and AdaBoost performed better than other classifiers we considered.
The Wizard and the Warrior: Leading with Passion and Power

PART ONE. CONFRONTING THE WIZARD AND WARRIOR WITHIN. 1. Light and Shadow: Richard Nixon and Mother Teresa. 2. Assessing Your Inner Wizard and Warrior. PART TWO. TOXIC, RELENTLESS, AND PRINCIPLED WARRIORS. 3. The Toxic Warrior. 4. The Relentless Warrior. 5. The Principled Warrior. PART THREE. THE WARRIOR PATH. 6. Warrior Heart. 7. Warrior Mind. 8. Warrior Skill. 9. Warrior Weapons. PART FOUR. WIZARD ROLES: AUTHENTIC, WANNABE, AND HARMFUL. 10. The Authentic Wizard. 11. The Wannabe Wizard. 12. The Harmful Wizard. PART FIVE. WIZARDS AT WORK. 13. The Wizard's Odyssey. 14. Summoning the Spirit. PART SIX. THE LEADER'S JOURNEY: FUSING WARRIOR AND WIZARD. 15. Personal Journey: The Ninja and the Samurai. 16. Learning to Lead: The Genesis and Rebirth of IBM. 17. Leading With Courage and Faith: Joan of Arc. 18. Creative Confrontation: Willem "Tex" Gunning. 19. Promoting the Dream: Martin Luther King Jr. 20. Enhancing the Wizard and Warrior Within. 21. The Sword and the Wand. Notes. Acknowledgments. The Authors. Index.
A Framework to Filter Unwelcome Messages from OSN User Walls

Today Usage of Online Social Networks is became ubiquitous. Social Media is spreading rapidly all over the world. Social media is the social interaction among people in which they create, share or exchange information and ideas in virtual communities and networks. Online social networking(OSNs) sites like Twitter, Orkut, YouTube, and Face book are among the most popular sites on the Internet. Users of these web sites forms a social network, which provides a powerful means of sharing, organizing, and finding useful information . Unlike web information , the Online social networks (OSN) are organized around more number of users joins the network, shares their information and create the links to communicate with other online users. The resulting social network sites provides a basis for maintaining social relationships, for finding users with similar interests, and for locating content and knowledge that has been contributed or endorsed by other users. In OSNs information filtering can be used for avoiding the unwanted messages sharing or commenting on the user Walls. In this paper, we have proposed a system to filter undesired messages from OSN walls. The system exploits a machine learning soft classifier to enforce customizable content-dependent FRs. Moreover, the flexibility of the proposed system in terms of filtering options is enhanced through the management of BLs.
Neglected and Underutilised Crops: A Systematic Review of Their Potential as Food and Herbal Medicinal Crops in South Africa

The African continent harbours many native species with nutraceutical and pharmaceutical potential. This study reviewed underutilised crops in South Africa to determine their potential as food and herbal medicinal crops. Over 5,000 species have been identified and earmarked for their medical attributes in formal and informal setups. Researchers, plant breeders and policymakers have mostly ignored the development potential of these crops. Consequently, their value chains are poorly developed. In South Africa, there is a wide range of neglected and underutilised crops, which were historically popular and used by communities; however, over the years, they have lost their status within farming systems and been relegated to the status of neglected and underutilised. Recently, driven by the need to transition to more sustainable and resilient food systems, there has been renewed interest in their potential as food and herbal medicinal crops to establish new value chains that include vulnerable groups. They are now gaining global attention, and their conservation and sustainable utilisation are now being prioritized. The review confirmed that several of these crops possess nutraceutical and pharmaceutical properties, highlighting their potential for development as food and herbal medicines. However, current production levels are too low to meet the requirements for industrial development; research and development should focus on all aspects of their value chain, from crop improvement to utilisation. A transdisciplinary approach involving a wide range of actors is needed to develop the identified neglected and underutilised crops’ potential as food and herbal medicinal crops and support the development of new and inclusive value chains.
Residual-based convolutional-neural-network (CNN) for low-dose CT denoising: impact of multi-slice input

Deep convolutional neural network (CNN) based methods have become popular choices for reducing image noise in CT. Some of these methods showed promising results, especially in terms of preserving natural CT noise texture. Early attempts of CNN denoising were based on 2D CNN models with either single-slice or 3-slice input. The 3-slice input was mainly to utilize the existing network architecture that were proposed for natural images with 3 input channels. Multi-slice input has the potential to incorporate spatial information from adjacent slices. However, it remains unknown if this strategy indeed improves the denoising performance compared to a 2D model with a single-slice input and what is the best network architecture to utilize the multi-slice input. Two categories of network architectures can be used for multi-slice input. First, multi-slice low-dose images can be stacked channelwise as multi-channel input to a 2D CNN model. Second, multi-slice images can be employed as the 3D volumetric input to a 3D CNN model, in which the 3D convolution layers are adopted. In this study, we compare the performance of multiple CNN models with 1, 3, and 7 input slices. For the 7-slice input, we also include a comparison between 2D and 3D CNN models. When the input channels of the 2D CNN model increases from 1 to 3 to 7, a trend of improved performance was observed. Comparing the two models with 7-slice input, the 3D model slightly outperforms the 2D model in terms of noise texture and homogeneity in liver parenchyma as well as better subjective visualization of vessels such as intrahepatic portal vein and jejunal artery.
Variational Nested Dropout

Nested dropout is a variant of dropout operation that is able to order network parameters or features based on the pre-defined importance during training. It has been explored for: I. Constructing nested nets Cui et al. 2020, Cui et al. 2021: the nested nets are neural networks whose architectures can be adjusted instantly during testing time, e.g., based on computational constraints. The nested dropout implicitly ranks the network parameters, generating a set of sub-networks such that any smaller sub-network forms the basis of a larger one. II. Learning ordered representation Rippel et al. 2014: the nested dropout applied to the latent representation of a generative model (e.g., auto-encoder) ranks the features, enforcing explicit order of the dense representation over dimensions. However, the dropout rate is fixed as a hyper-parameter during the whole training process. For nested nets, when network parameters are removed, the performance decays in a human-specified trajectory rather than in a trajectory learned from data. For generative models, the importance of features is specified as a constant vector, restraining the flexibility of representation learning. To address the problem, we focus on the probabilistic counterpart of the nested dropout. We propose a variational nested dropout (VND) operation that draws samples of multi-dimensional ordered masks at a low cost, providing useful gradients to the parameters of nested dropout. Based on this approach, we design a Bayesian nested neural network that learns the order knowledge of the parameter distributions. We further exploit the VND under different generative models for learning ordered latent distributions. In experiments, we show that the proposed approach outperforms the nested network in terms of accuracy, calibration, and out-of-domain detection in classification tasks. It also outperforms the related generative models on data generation tasks.
Semiclassical treatment for molecular rotation spectra in high electric fields

Molecular rotation spectra, generated by the coupling of the molecular electric-dipole moments to an external time-dependent electric field, are discussed in a few particular conditions which can be of some experimental interest. First, the spherical-pendulum molecular model is reviewed, with the aim of introducing an approximate method which consists in the separation of the azimuthal and zenithal motions. Second, rotation spectra are considered in the presence of a static electric field. Two particular cases are analyzed, corresponding to strong and weak fields. In both cases the dipoles perform rotations and vibrations about equilibrium positions, which may exhibit parametric resonances. For strong fields a large macroscopic electric polarization may appear. This situation may be relevant for polar matter (like pyroelectrics, ferroelectrics), or for heavy impurities embedded in a polar solid. The dipolar interaction is analyzed in polar condensed matter, where it is shown that new polarization modes appear for a spontaneous macroscopic electric polarization (these modes are tentatively called "dipolons"); one of the polarization modes is related to parametric resonances. The extension of these considerations to magnetic dipoles is briefly discussed. The treatment is extended to strong electric fields which oscillate with a high frequency, as those provided by high-power lasers. It is shown that the effect of such fields on molecular dynamics is governed by a much weaker, effective, renormalized, static electric field.
Plasma Physics Theory

Part 1 the elements of the kinetic theory of gases. Part 2. one-particle motion in a plasma. Part 3. the hydrodynamic description of a plasma. Part 4. plasma confinement. Part 5. collisions in a plasma. Part 6. plasma electron vibrations. Part 7. waves in an isotropic plasma. Part 8. waves in a magnetoplasma. Part 9 beams in a plasma. Part 10. nonlinear wave interaction. Part 11 fluctuations in a plasma. Part 12. wave scattering in a plasma. Part 13. correlations between particles. Part 14. waves as quasiparticles.
Toxoplasma gondii AP2XII-2 Contributes to Transcriptional Repression for Sexual Commitment

Toxoplasma gondii is a parasite that undergoes its sexual stage exclusively in feline intestines, making cats a major source of transmission. A better understanding of the proteins controlling the parasite’s life cycle stage transitions is needed for the development of new therapies aimed at treating toxoplasmosis and the transmission of the infection. ABSTRACT Toxoplasma gondii is a widespread protozoan parasite that has a significant impact on human and veterinary health. The parasite undergoes a complex life cycle involving multiple hosts and developmental stages. How Toxoplasma transitions between life cycle stages is poorly understood yet central to controlling transmission. Of particular neglect are the factors that contribute to its sexual development, which takes place exclusively in feline intestines. While epigenetic repressors have been shown to play an important role in silencing the spurious gene expression of sexually committed parasites, the specific factors that recruit this generalized machinery to the appropriate genes remain largely unexplored. Here, we establish that a member of the AP2 transcription factor family, AP2XII-2, is targeted to genomic loci associated with sexually committed parasites along with epigenetic regulators of transcriptional silencing, HDAC3 and MORC. Despite its widespread association with gene promoters, AP2XII-2 is required for the silencing of relatively few genes. Using the CUT&Tag (cleavage under targets and tagmentation) methodology, we identify two major genes associated with sexual development downstream of AP2XII-2 control, AP2X-10 and the amino acid hydroxylase AAH1. Our findings show that AP2XII-2 is a key contributor to the gene regulatory pathways modulating Toxoplasma sexual development. IMPORTANCE Toxoplasma gondii is a parasite that undergoes its sexual stage exclusively in feline intestines, making cats a major source of transmission. A better understanding of the proteins controlling the parasite’s life cycle stage transitions is needed for the development of new therapies aimed at treating toxoplasmosis and the transmission of the infection. Genes that regulate the sexual stages need to be turned on and off at the appropriate times, activities that are mediated by specific transcription factors that recruit general machinery to silence or activate gene expression. In this study, we identify a transcription factor called AP2XII-2 as being important for the repression of a subset of sexual stage genes, including a sexual stage-specific AP2 factor (AP2X-10) and a protein (AAH1) required to construct the infectious oocysts expelled from infected cats.
TRUE MEAN TEMPERATURE

Abstract The complexity of the question of obtaining the true mean temperature led the late A. Buchan to look favorably on the mean daily extremes (maximum plus minimum)/2 as an expression of the mean temperature. This view has become traditional among English-speaking races, but it has two very grave objections. and it is not adopted by continental or South American meteorologists. These objections are briefly : (1) Maximum and minimum thermometers. especially the latter, are far more likely to develop systematic errors than is the ordinary dry bulb. This remark applies with great force to hot countries, where in addition the observers are frequently untrained. In fact, it was this very difficulty which led to the adoption of a column of “True mean temperature” in Reseau Mondial. (2) The relation (maximum plus minimum)/2 to the true mean is not, even approximately fixed, but varies with the location, with the cloudiness, and with the time of year. The means of observations taken at 7 a. m. , 1 or 2 p. m. ,.
Setting the PACE in Product Development

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A multi-objective approach towards geospatial facility location

Applications of the sub-discipline of location science within the larger discipline of operations research include the location of important facilities, such as hospitals, fire stations, libraries and depots. Existing facility location resolution techniques are generally based on commercial and transportation modelling criteria with little or no consideration given to the characteristics and influence of surrounding terrain. Recent technological advances have, however, resulted in a subfield of location science rapidly increasing in popularity — the field of geospatial facility location. Geospatial facility location science places a strong emphasis on terrain and environmental factors in the search for suitable sites for facilities with complex location requirements. Examples of such facilities include radars, telecommunication towers, watchtowers and wind turbines. The applications in which geospatial facility location solution approaches are relevant generally include only one type of facility. As a result, problem-specific solution approaches tailored to the specific facility type considered are usually adopted. On closer inspection, however, the solution approaches followed for these facility location problems reveal striking similarities which may be exploited in a generic manner in order to provide more efficient solution tradeoff alternatives. By removing the problem-specific approach to facility location modelling and the design of the associated solution techniques, there is an opportunity to develop a generic, dynamically implementable geospatial facility location framework which may be applied to identify facility location trade-off alternatives in various applications. Moreover, networks of multiple facility types may be considered in such a framework — something that is a rarity in the current geospatial facility location literature. In view of the continual advancement of technology, a generic geospatial facility location framework may even prove to be applicable to future facility location problems in which the placement criteria are currently unknown. The design of a generic geospatial facility location framework is therefore pursued in this dissertation. A dynamic mathematical foundation, which eliminates facility-specific solution methodologies, is established. A computerised concept demonstrator based on this framework is implemented within a generic solution paradigm. This concept demonstrator accommodates as special cases a variety of popular facility location problems from the literature. The geospatial facility location framework is demonstrated to be a dynamic and useful tool for solving complex facility location problems that have not previously been encountered due to the limitations of problem-specific solution search designs. iii Stellenbosch University https://scholar.sun.ac.za
Awareness and Sources of Knowledge about Obstructive Sleep Apnea: A Cross Sectional Survey Study

Obstructive sleep apnea (OSA) is a multifactorial sleep breathing disorder, seriously impacting quality of life and involving approximately 1 billion of the world’s population. It is characterized by episodes of total cessation of breathing or decreases in airflow during sleep. Available data suggest that most cases of OSA remain undiagnosed even in developed countries. This is due to a lack of widespread knowledge about this pathology and the medical morbidities and mortality it brings about, among both laypeople and physicians. Moreover, despite receiving indications about the need to undergo specific evaluations for OSA signs and symptoms, sometimes patients do not pay sufficient attention to the problem. This is probably due to a lack of correct information on these issues. The present investigation analyzed the level of knowledge about OSA pathology and the sources through which a group of OSA patients gained information on their condition. A survey of 92 patients diagnosed with OSA (mean age 60.55 ± 10.10) and referred to the Unit of Orthodontics and Dental Sleep Medicine of the University of Bologna was conducted by means of a questionnaire investigating sociodemographic characteristics, the level of general knowledge on OSA pathology and its possible medical consequences. Despite about two third (67.38%) of the population demonstrating extensive knowledge, remarkably, a group of subjects (20.65%) had poor awareness of the OSA condition. A statistically significant correlation emerged between the level of knowledge about OSA and the level of education (p = 0.002). A great effort should be made to improve the quality of information and the communication modalities for OSA to enable a fully appropriate awareness of the condition among patients.