Miracle-dz/UniFAR-FTUs huggingface dataset:
AntiFuzz: Impeding Fuzzing Audits of Binary Executables

A general defense strategy in computer security is to increase the cost of successful attacks in both computational resources as well as human time. In the area of binary security, this is commonly done by using obfuscation methods to hinder reverse engineering and the search for software vulnerabilities. However, recent trends in automated bug finding changed the modus operandi. Nowadays it is very common for bugs to be found by various fuzzing tools. Due to ever-increasing amounts of automation and research on better fuzzing strategies, large-scale, dragnet-style fuzzing of many hundreds of targets becomes viable. As we show, current obfuscation techniques are aimed at increasing the cost of human understanding and do little to slow down fuzzing. In this paper, we introduce several techniques to protect a binary executable against an analysis with automated bug finding approaches that are based on fuzzing, symbolic/concolic execution, and taint-assisted fuzzing (commonly known as hybrid fuzzing). More specifically, we perform a systematic analysis of the fundamental assumptions of bug finding tools and develop general countermeasures for each assumption. Note that these techniques are not designed to target specific implementations of fuzzing tools, but address general assumptions that bug finding tools necessarily depend on. Our evaluation demonstrates that these techniques effectively impede fuzzing audits, while introducing a negligible performance overhead. Just as obfuscation techniques increase the amount of human labor needed to find a vulnerability, our techniques render automated fuzzing-based approaches futile.
SYNTHESIS AND CHARACTERIZATION OF BENT SHAPED LIQUID CRYSTALS HAVING AZOBENZENE MESOGENICS CORES

The objective of this study was to synthesize and characterize bent shaped liquid crystals with azobenzene mesogenic cores. The starting material for the synthesis was methyl-4-aminobenzoate. The initial step of the synthesis involved the diazonium salt coupling reaction with phenol to obtain 4-(4-methyl-diazobenzoate) phenol. The product formed then undergoes Williamson ether synthesis to obtain [4-(4-methyldiazobbenzoate) phenyloxy] hexadecane. Then, this compound was hydrolyzed with potassium hydroxide to obtain 4-(4-hexadekanyloxy-phenyazo) benzoic acid. The benzoic acid was reacted with nec and DMAP in dichloromethane to obtain I, 2phenylene bis [4-( 4-hexadekanyloxy-phenyazo) benzoate] as the final product. Yield of final product was 0.013 grams. The structure and characteristic of compounds synthesized were confirmed by spectroscopic analysis with IT-JR, 1H NMR, and DSC. IT -IR spectrum indicated the presence of functional groups included alkyl, ester, ether etc. 1H NMR spectrum showed the molecular structure of the intennediate compound whereas DSC thermogram point out the phase transition temperature and phase transition enthalpy of the final compound. From DSC thermogram, the crystalline temperature of final compound was 176.47 °c and the maximum melting point of final compound was 202.65 °C.
Markers of increased vascular risk in women with hypertension and type 2 diabetes mellitus

Background. Diabetes mellitus and arterial hypertension have important effects on vascular system and their major complications are caused by alterations of vasculature. These diseases are frequently associated. Beyond classical risk factors implicated in both diseases, in recent years some novel markers of vascular involvement have been studied, such as intima – media thickness (IMT) and parameters of arterial stiffness. Women seem to have an increased vascular risk associated with diabetes than do men. The aim of our study was to determine the consequences of hypertension associated with diabetes on intima media thickness and arterial stiffness in women. Patients and methods. We studied 54 women, 33 with diabetes mellitus and hypertension and 21 healthy controls (HC), matched for age. We evaluated classical risk factors for atherosclerosis, such as age, body mass index, smoking, lipid and glucose profile. We determined IMT of the carotid artery using an ultrasound device (ALOKA ProSound ɑ 10) and parameters of aortic stiffness – pulse wave velocity (PWV) and augmentation index (Aix) in all subjects using Arteriograph device (Tensio Med Ltd., Budapest, Hungary). Results. PWV was increased in patients compared HC (p=0.001). AIx, SBPao (aortic systolic blood pressure) and PPao (aortic pulse pressure) were also higher in patients but they did not have statistical power. IMT was significantly increased in patients compared with HC (p=0.01). In the group of patients IMT was significantly correlated with age, arterial pressure and SBPao. Patients had higher body mass index (BMI) and arterial pressure. There were no smokers in the study population. Of biochemical parameters only fasting plasma glucose was significantly higher in diabetic patients. Conclusion. In our study women with hypertension and diabetes had increased arterial stiffness and IMT compared to HC. Coexistence of diabetes and hypertension in women is associated with increased markers of vascular disease that may be a link to the important cardiovascular risk seen in these patients. Key-Words: vascular risk, diabetes, hypertension, arterial stiffness, intima-media thickness
Nikodym Maximal Functions Associated with Variable Planes in R 3

Given a vector ﬁeld a on R 3 , we consider a mapping x (cid:2)→ Π a ( x ) that assigns to each x ∈ R 3 , a plane Π a ( x ) containing x , whose normal vector is a ( x ). Associated with this mapping, we deﬁne a maximal operator M a N on L 1 loc ( R 3 ) for each N (cid:5) 1 by where the supremum is taken over all 1 /N × 1 /N × 1 tubes τ whose axis is embedded in the plane Π a ( x ). We study the behavior of M a N according to various vector ﬁelds a . In particular, we classify the operator norms of M a N on L 2 ( R 3 ) when a ( x ) is the linear function of the form ( a 11 x 1 + a 21 x 2 , a 12 x 1 + a 22 x 2 , 1). The operator norm of M a N on L 2 ( R 3 ) is related with the number given by D = ( a 12 + a 21 ) 2 − 4 a 11 a 22 .
Maximizing Influence over a Target User through Friend Recommendation

Given a graph, with a source node that needs to maximize its influence over a specific target node, a set of nodes need to be determined that will enable information flow from the source to the target node. By solving this problem, we can enable a user to receive more attention from a specific target user by forming useful connections between the two. Current friend recommendation algorithms focus on suggesting nodes that are similar to the user, but these algorithms are not designed to tackle the maximum influence issue. Based on the observation that information propagation on online social networks is enabled by the sharing activity, we define the influence of a source node over target as a variation of Katz centrality. In addition, we model the reluctance, to account for awkwardness between two users. With these measures, we propose k-node suggestion problem. However, the optimization problem of recommending a node set that maximizes influence is NP-hard. Therefore, in this paper, we suggest an algorithm to find a node set sequentially. Next, we model reluctance between two nodes, which is inversely related to node similarity. Reluctance is based on the intuition that people not related with the user, might not accept the user’s online connection request. By considering reluctance, we could identify the nodes that have a higher probability of refusing the connection request. We address this problem by proposing an Incremental Katz Approximation (IKA) algorithm that is designed to search the top-k nodes with high accuracy and has the ability to run on a large graph. The IKA algorithm can handle large graphs by approximating influence measure using Monte-Carlo simulation. This algorithm updates information diffusion incrementally to find the node that can maximize influence. We discuss the complexity of our algorithm and the evaluation results demonstrate the performance and scalability of our algorithm. We also report interesting behavior of the sequential recommendation result. In summary, our algorithm is effectively recommend friends such that they can improve influence of the source user on the target user.
ANALYSIS OF DIFFERENTIALLY EXPRESSED GENES RELATED TO INTRAMUSCULAR FAT AND CHEMICAL COMPOSITION IN DIFFERENT BREEDS OF CHICKEN

Poultry production has increased noticeably to meet consumers’ demand. Therefore, producers’ desire to achieve commercial profit requirements. The advancement of desirable traits has led to the achievement of undesirable taste and meat quality; as a result, consumers are searching for alternatives that will give them superior-tasting chicken meat (Berri et al., 2001; Du et al., 2010). Chemical composition and carcass traits, for instance, fat, protein, and ash, are important economic traits for poultry because they are associated with meat production efficiency. Intramuscular fat (IMF) plays a key role in meat quality. IMF deposition is generally distributed in the epimysium, perimysium, and endomysium that positioned between muscle cells and fibers. The meat with high IMF levels had favorable meat qualities such as improved tenderness, juiciness, flavor, and good water-holding capacity (Fernandez et al., 1999). So IMF is a factor through which meat quality could potentially be manipulated (Cui et al., 2012; Ros-Freixedes et al., 2014). Molecular mechanisms associated with meat quality have previously been examined in livestock (Moreno-Sánchez et al., 2010; Zhao et al., 2011) and mammals such as Laiwu (Hu et al., 2008) and Jinhua (Guo et al., 2011), which are local Chinese pig breeds. It is common knowledge that IMF deposition is associated with potential candidate genes such as H-FABP (Nechtelberger et al., 2001) and Sirt1 (Moynihan and Imai, 2006). So far, in Pak. J. Agri. Sci., Vol. 55(3), 611-619;2018 ISSN (Print) 0552-9034, ISSN (Online) 2076-0906 DOI: 10.21162/PAKJAS/18.6537 http://www.pakjas. com.pk
Numerical Simulation of Localized Preflame Autoignition in Enclosures

A novel computational approach based on the coupled 3D Flame-Tracking – Particle (FTP) method is used for numerical simulation of confined explosions caused by preflame autoignition. The Flame Tracking (FT) technique implies continuous tracing of the mean flame surface and application of the laminar/turbulent flame velocity concepts. The Particle method is based on the joint velocity – scalar probability density function approach for simulating reactive mixture autoignition in the preflame zone. The coupled algorithm is supplemented with the database of tabulated laminar flame velocities as well as with reaction rates of hydrocarbon fuel oxidation in wide ranges of initial temperature, pressure, and equivalence ratio. The main advantage of the FTP method is that it covers both possible modes of premixed combustion, namely, frontal and volumetric. As examples, combustion of premixed hydrogen–air, propane–air, and n-heptane–air mixtures in enclosures of different geometry is considered. At certain conditions, volumetric hot spots ahead of the propagating flame are identified. These hot spots transform to localized exothermic centers giving birth to spontaneous ignition waves traversing the preflame zone at very high apparent velocities, i.e., nearly homogeneous preflame explosion occurs. The abrupt pressure rise results in the formation of shock waves producing high overpressure peaks after reflections from enclosure walls.
POLARIZATIONDEPENDENT ELECTROMAGNETIC BAND GAP ( PDEBG ) STRUCTURES WITH CIRCULARLY POLARIZED ANTENNA : A REVIEW

In the field of wireless communication the Polarization dependent Electromagnetic Band gap (PDEBG) structures have proved in being very beneficial in using them with circularly polarized microstrip antenna due to its independent behavior of polarization sensitivity. In this paper we have reviewed the work so done on circularly polarized antenna based on PDEBG structures with detail analysis on the working principle of these structures. It also discusses its effect on antenna parameters like impedance bandwidth and gain. Keyword— Circular polarization, axial ratio, gain, return
An Evaluation of Language-Agnostic Inner-Attention-Based Representations in Machine Translation

In this paper, we explore a multilingual translation model with a cross-lingually shared layer that can be used as fixed-size sentence representation in different downstream tasks. We systematically study the impact of the size of the shared layer and the effect of including additional languages in the model. In contrast to related previous work, we demonstrate that the performance in translation does correlate with trainable downstream tasks. In particular, we show that larger intermediate layers not only improve translation quality, especially for long sentences, but also push the accuracy of trainable classification tasks. On the other hand, shorter representations lead to increased compression that is beneficial in non-trainable similarity tasks. We hypothesize that the training procedure on the downstream task enables the model to identify the encoded information that is useful for the specific task whereas non-trainable benchmarks can be confused by other types of information also encoded in the representation of a sentence.
Modeling online user product interest for recommender systems and ergonomics studies

This paper presents use of a tool built to monitor human‐website interaction without the need for eye tracking. Behavior indicators calculated from data collected by the tool can be used for many purposes such as web ergonomics enhancement, content adaptation, and, in particular, recommender systems. A random‐forests‐based modeling approach is shown as a generalization for earlier decision‐tree classification approach. Results of a usability survey conducted within the study are presented.
Physical activity and exercise training in preventive cardiology

Physical activity (PA) and exercise training (ET) are central and indispensable components for primary and secondary prevention of cardiovascular disease (CVD). In healthy individuals, PA reduces all-cause and CV mortality and has conrmed bene cial effects on the cardiovascular risk pro le. In secondary prevention, PA counselling und ET are two of the core components of a multidisciplinary cardiac rehabilitation (CR) program. Exercise-based CR is an established strategy in the secondary prevention of CV disease. It improves survival, reduces hospital admissions, improves cardiorespiratory tness (CRF), and quality of life (QoL). However, these bene cial effects require regular attendance under professional supervision and adherence to recommended guidelines. In patients with heart disease, proper patient assessment with a standardized exercise test as a basis for a tailored ET prescription is required. In healthy subjects this is advocated only in selected groups. Current guidelines recommend at least 150 min/week of moderate-intensity continuous aerobic PA in both healthy individuals as well as those with cardiac disease. In healthy adults, alternatively intensity can be increased and volume can be halved. High intensity interval training (HIIT) is a relatively new training modality and may be used complementary to continuous training in selected patient groups. HIIT seems to be superior compared to moderate continuous exercise in patients with cardio metabolic disease with regard to effects on the CV risk pro le, endothelial function, improvement in cardiorespiratory tness, and a reverse cardiac remodelling in patients with heart failure. One of the major challenges in preventive cardiology is the improvement of long-term adherence to PA recommendations. The aim of this article is to give an overview from the preventive cardiologist’s point of view with a focus on endurance ET prescription for the audience of sports and exercise medicine physicians.
Sheet 1 of 2 US 9 , 668 , 953 B 2 separasiox : & Easte : Reixatigy : & Siswari

A61K 8/355 (2013.01); A23L 5/00 (2016.08); A23L 33/105 (2016.08); A23L 33/18 (2016.08); A23L 33/28 (2016.08); A61 K 8/3 (2013.01); A61K 8/347 (2013.01); A61 K 8/4946 (2013.01); A61K 8/65 (2013.01); A61 K 8/66 (2013.01); A61K 8/67 (2013.01); A61 K 8/671 (2013.01); A61K 8/673 (2013.01); A61 K 8/676 (2013.01); A61K 8/735 (2013.01); A61 K 8/97 (2013.01); A61O 19/08 (2013.01); A23V 2002/00 (2013.01); A61 K 2800/92 (2013.01) (58) Field of Classification Search None See application file for complete search history.
Uncertainty Estimation and Visualization in Segmenting Uni- and Multi-modal Medical Imaging Data

Uncertainty is widespread when interpreting medical imaging data sets due to different sources of artifacts such as signal measurement errors or noise and partial volume effects in the acquisition process. The effectiveness of visualization methods for supporting decision making and diagnostic exploration is limited by the lack of suitable uncertainty estimation and visualization tools. A striking example of uncertainty visualization importance is given in neurosurgery, where errors in the range of a millimeter can have dramatic effects. Image segmentation plays an essential role in a broad range of computer vision and image processing applications such as pattern recognition, geographical imaging, geology, remote sensing, and medical imaging. In image segmentation, images are partitioned into disjoint regions of homogeneous properties. This study is concerned with deriving estimates of uncertainty associated with the segmentation result of single- and multi-modal medical imaging data, developing methods to visualize these estimates intuitively, and using these estimation in both evaluating and improving image segmentation results and the analysis of these results. As domain of applications, we use synthetic images that simulate the main brain structures in magnetic resonance imaging (MRI) data, simulated MRI data from BrainWeb, and Real MRI data as well. The main objectives of our study are to distinguish the certain and uncertain areas in the segmentation result, and to categorize the uncertain areas according to their level of uncertainty. By uncertain area, we basically understand the area that is affected by one or more sources of artifacts. Note: (see the complete abstract in the thesis)
z " : $ ) Source Pred . ( q " : $ ) Source ( X ) Encoder-Decoder ( EncDec ) SPM Computation

The Encoder-Decoder model is widely used in natural language generation tasks. However, the model sometimes suffers from repeated redundant generation, misses important phrases, and includes irrelevant entities. Toward solving these problems we propose a novel sourceside token prediction module. Our method jointly estimates the probability distributions over source and target vocabularies to capture the correspondence between source and target tokens. Experiments show that the proposed model outperforms the current state-of-the-art method in the headline generation task. We also show that our method can learn a reasonable token-wise correspondence without knowing any true alignment1.
Synonymy in Modern Tatar reflected by the Tatar-Russian Socio-Political Thesaurus

This paper discusses some aspects of lexical synonymy in the modern Tatar language that have been revealed in the course of compiling the bilingual Russian-Tatar Socio-Political Thesaurus. Building the thesaurus is aimed at fixing all Tatar single words and multiword items related to the socio-political sphere with their Russian equivalents. A distinguishing feature of the contemporary Tatar lexicon is a great deal of absolute synonyms which emerged due to a combination of intralinguistic and extralinguistic factors. We disclose social and linguistic causes of the emergence of synonyms, describe the main structural types of synonymous items, and present corpus data on their frequency. Corpus data prove that synonymy in socio-political terminology is rather an artificial and superficial phenomenon. Currently most Tatar socio-political terms are coined by calquing the corresponding Russian terms, and lexical preferences of translators and terminology developers may differ, which leads to a large number of competing items of different origin and structure. On the level of multiword items, lexical variation is complicated by the factor of syntactic variation, which in its turn multiplies the number of synonymous compounds. Parallel denominations are used for a wide range of phenomena, including official names of state structures and social institutions.
Estimation of Bacterial Functions in Samples Based on 16 S rRNA

Humans are hosts to an enormous variety of microbes, bacterial, archaeal, fungal, and viral. Unfortunately, science knows only little about them. Since most of the bacteria has not been studied yet, the main question for a given sample is not only which species of bacteria a specific sample contains, but also what can the bacteria in this sample do (i.e. lipid digestion or resistance to antibiotics). This task is called functional profile prediction and it will be the main focus of this paper. In this paper, I introduce methods for functional analysis, describe existing tools and then design a new tool inspired by them, which implements different methods for the prediction. The results of the experiments imply, that the implemented tool is accurate and useful when using the same method for experimental evaluation as existing tools. However, I propose a new approach to evaluation, that concerns only the most specific bacterial functions, where the results differ from the classic one. In the end, I discuss possible implications of this difference.
Fuzzy Linear Regression Approach for Power System State Estimation

the state estimation (SE) is the most important implemented function in the control center of electric power system. Without reliable and effective SE all monitoring and control functions of the control center are immaterial. The SE provides the data base by which all those functions can be performed. A hybrid estimator incorporating fuzzy logic concepts (if then rules) are introduced in the past. In this paper, a fast method for power system state estimation is introduced which is based on weighted least square (WLS) state estimation and fuzzy linear regression (FLR) model. The FLR model is based on inequality constrained linear programming (LP) optimization. In this approach, the WLS method will run for first iteration and then the FLR model will continue until the convergence is reached. The WLS-FLR approach provides not only the estimated states but also, an uncertainty range for those estimated states with less computational time. The effect of fuzziness degree and the measurements accuracy on the estimated states are discussed in this paper. The effectiveness of the proposed method is demonstrated by using 6bus, and IEEE 30-bus systems. Keywords— State Estimation;Weighted Least Square (WLS); Linear programming; Fuzzy Linear Regression (FLR); Uncertainty.