Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparative Analysis of Open-SSL Vulnerabilities & Heartbleed Exploit Detection

Since its introduction in 1994 the Secure Socket Layer (SSL) protocol (later renamed to Transport Layer Security (TLS)) evolved to the de facto standard for securing the transport layer. SSL/TLS can be used for ensuring data confidentiality, integrity and authenticity during transport. A main feature of the protocol is its flexibility. Modes of operation and security aims can easily be configured through different cipher suites. During its evolutionary development process several flaws were found. However, the flexible architecture of SSL/TLS allowed efficient fixes in order to counter the issues. This paper presents an overview on theoretical and practical attacks of the last 20 years.
Fluoride: Double-Edged Sword Implicated in Caries Prevention and in Fluorosis

How fluoride acts to prevent caries as well as cause demineralization is not well understood. Tunnels located inside apatite crystals are acting as ions exchangers favoring diffusion pathways, and substitution of ions such as fluoride inside the crystal lattice. Cariostatique effects prevent the carious decay, increasing the mineral solubility and remineralization. Given systemically or topically, fluorides added to water or used as salt, varnish, gel or paste, decrease the number and severity of carious lesions on deciduous and/or permanent erupted teeth. It comes out from fluoride supplementation that dental fluorosis may be induced. Slight fluorosis appears as white spots resulting from enamel hypomineralization. Pitting forming horizontal lines running across the surface of the teeth was also seen. For high doses of fluoride, altered enamel surfaces merge into large pigmented (brown to black) defects. Hence, fluorides appear as a double sword, actually involved in caries prevention, but also inducing mild to severe enamel deficiencies. Equilibrium between the well-documented caries prevention and fluoride contribution to enamel pathology implies a daily intake evaluation. The needs for fluoride consumption have to be carefully identified. They should be evaluated according to the age of the patient, the frequency of ingestion, and the mode of absorption. Fluorides in Dental Tissues: Organization, Substitutions, and Apatite-Type Structures of the Mineral Phase
PRO AND CON

From the Department of Anesthesiology, Ochsner Clinic Foundation, New Orleans, LA. Address reprint requests to Kelly Ural, MD, Ochsner Clinic Foundation, Department of Anesthesiology, 1514 Jefferson Hwy, New Orleans, LA 70121. E-mail: kural@ochsner.org © 2016 Elsevier Inc. All rights reserved. 1053-0770/2602-0034$36.00/0 http://dx.doi. org/10.1053/j.jvca. 2016.07. 001
Identification and molecular characteristic of fowl adenovirus serotype 4 isolated from a live Newcastle disease virus vaccine

[Objective] Fowl adenovirus (FAdV) infection in chicken flocks is very common in China currently. Because FAdV transmits both horizontally and vertically in chickens, it is essential and urgent to determine the contamination of attenuated vaccines produced in chicken embryo eggs by FAdV and its risk to induce epidemic of Hepatitis-Hydropericardium syndrome (HHS) caused by FAdV. The objectives were to ascertain the contamination of an attenuated live Newcastle disease virus (NDV) vaccine produced by Chinese veterinary drug company by FAdV and to investigate the possible reasons for current prevalence of HHS caused by FAdV in chicken flocks in China. [Methods] FAdV-specific PCR was employed to detect FAdV from the attenuated live vaccine of NDV La Sota strain. PCR positive samples were inoculated into chicken embryo eggs for the isolation of FAdV. Sequencing, identity analysis and the phylogenetic tree construction were performed to analyze the molecular characteristics, genotyping and serotyping of the isolates. [Results] A FAdV strain was obtained and named L160962 that shared the highest identity with serotype 4 FAdVs in the 52k and hexon genes according to homology analysis. Among the strains investigated, isolate L160962 shared identities at a level of 99.9%−100% with Chinese strains HN/151025 and CH/HNJZ/2015, 99.3% with Austrian strain KR5, and only 79.0%−83.3% with members in species A, B, D and E in the sequences of 52k and hexon. Phylogenetic analysis showed that isolate L160962 was clustered into serotype 4 within the species C with an identity higher than 99.9% and most close to the Chinese strains, suggesting that isolate L160962 is similar to the prevalent strains in China. [Conclusion] Our studies observed contamination of attenuated vaccines produced in chicken embryo eggs by serotype 4 of FAdV, which may be one of the reasons that lead to FAdV infection prevalent in chicken flocks in China.
Color Image Watermarking using Cycle Spinning based Sharp Frequency Localized Contourlet Transform and Principal Component Analysis

This paper describes a new approach for color image watermarking using Cycle Spinning based Sharp Frequency Localized Contourlet Transform and Principal Component Analysis. The approach starts with decomposition of images into various subbands using Contourlet Transform(CT) successively for all the color spaces of both host and watermark images. Then principal components of middle band(x bands) are considered for inserting operation. The ordinary contourlet transform suffers from lack of frequency localization. The localization being the most important criterion for watermarking, the conventional CT is not very suitable for watermarking. This problem of CT is over come by Sharp Frequency Localized Contourlet, but this lacks of translation invariance. Hence the cycle spinning based sharp frequency localized contourlet chosen for watermarking. Embedding at middle level sub bands(x band) preserves the curve nature of edges in the host image hence less disturbance is observed when host and watermark images are compared. This result in very good Peak Signal to Noise Ratio (PSNR) instead of directly adding of mid frequency components of watermark and host images the principal components are only added. Likewise the amount of payload to be added is reduced hence host images get very less distortion. Usage of principal components also helps in fruitful extraction of watermark information from host image hence gives good correlation between input watermark and extracted one. This technique has shown a very high robustness under various intentional and non intentional attacks.
A Comprehensive Survey on Human Facial Expression Detection

In the recent years recognition of Human's Facial Expression has been very active research area in computer vision. There have been several advances in the past few years in terms of face detection and tracking, feature extraction mechanisms and the techniques used for expression classification. This paper surveys some of the published work since 2001. The paper gives a time-line view of the advances made in this field, the applications of automatic face expression recognizers, the characteristics of an ideal system, the databases that have been used and the advances made in terms of their standardization and a detailed summary of the state of the art. The paper also discusses facial parameterization using FACS Action Units (AUs) and advances in face detection, tracking and feature extraction methods. It has the important role in the humancomputer interaction (HCI) systems. There are multiple methods devised for facial feature extraction which helps in identifying face and facial expressions.
Impact of Microorganisms on the Production and Degradation Processes of the Natural Polymers, Polyhydroxyalkonates, For Replacement of the Dangerous Plastics

The most dangerous problems these days are cleaning our earth from rubbish which is difficult to be degraded by time. Over the decades, the human population and the development is increasing rapidly all over the world in all field particularly in industrial field which is more vibrant than ever before. However, this development has contributed to the increased the amount of wastes rapidly. As a consequence, the earth is in danger since the environment has been ruined, and therefore, putting people’s health in warning. With the passage of time, accumulation of massive amount of wastes especially of non-degradable waste in the world is threatened the environment and potential survival of many species of organisms. Developed countries such as China and USA have serious concerns about the rising number of non-biodegradable waste which is disposed of in landfills and oceans. Consequently, abundant countries have a novel research of projects in order to improve the ways how to disposal of pollutant residues from the biosphere and environment. Another solution is the use of biodegradable plastic which are safe ad ecofriendly materials. Polyhydroxyalkonates (PHA) produced by bacteria and could be an attractive to common plastics because it fit well with new waste management strategies. The use of PHA produced by bacterial fermentation as a commodity polymer is limited by its high production cost compared to some widely used petroleum derived plastics.
Polya Tree Priors for the Proportional Hazards Model

The paper revisits estimation problem for the Cox proportional hazards model. We have considered the problem in a fully Bayesian nonparametric framework with Polya tree priors for the baseline survival function. The reason for choosing Polya tree priors is that it can select absolutely continuous probability measures with probability 1, given proper choice of parameters. Our finding improves the partial likelihood approach in the sense that it takes both ranks and spacings of the order statistics into account. Also, it generalizes the findings of Muliere and Walker Muliere (1997) by including covariates.
Corporate social responsibility guiding sustainable innovation in the fashion system: The role of standards

The theme of sustainability is an interesting topic in the fashion industry. This industry has one of the highest levels of pollution and also from a social outline is responsible for serious injuries to human dignity, given the poor working conditions in many factories in developing countries. The paper deepens the relation between corporate social responsibility (CSR) and innovation in the Italian fashion system. Which is the level of sustainable innovation in the Italian fashion industry? This is the research question deepened through the analysis of the degree of the social and environmental standards in the fashion system. Standards represent an important driver of organizational, process and product innovations, they impose the use of new technologies, new processes, new materials, but also a different organization of supply chains, and allow evaluating fashion companies’ concrete commitment in CSR. The research intends to explore this relation in order to contribute to the debate on this topic
Yuzvinsky ’ s conjecture in the dyadic case

We give a characterization of intercalate matrices as an algebraic variety over a finite field. We also prove Yuzvinsky’s conjecture on the minimum number of colors in an intercalate matrix for matrices with 5 or less rows. Finally, we obtain a set of 37 cases which, if established, would verify Yuzvinsky’s conjecture as true for matrices up to order 32× 32. 1991 Mathematics Subject Classification: 11E25, 05B99
Analiza imaginarului din texte

REZUMAT În lucrare este abordată problematica detectării automate a imaginarului din texte. Problema este foarte importantă deoarece rezolvarea ei permite identificarea conotațiilor unor texte, cu implicații majore asupra analizei interacțiunii textuale. Abordarea pleacă de la teoria imaginarului introdusă de istoricului Lucian Boia. Sunt folosite tehnici de prelucare a limbajului natural. Au fost făcute și sunt prezentate în lucrare mai multe analize de texte de referință.
Running Head: MUNICIPAL-ISSUED ID CARDS AND BIASED TREATMENT 1 Do Municipal-issued ID Cards Buffer Against Identity-based Biased Treatment? A Field Experiment in Retail Stores

The current field experiment examined discrimination against Latino customers in retail stores, and municipal identification (ID) cards as potential buffers against this type of discrimination. In an audit experiment, Latino “customers” were subject to discrimination relative to a matched team of European-American “customers” when making ten-dollar check payments at retail stores. Specifically, Latinos were asked to present an ID card more frequently than European-American customers, were quoted a higher minimum dollar amount for purchasing a gift certificate, and received more negative affect from salespersons. A municipal-issued ID card successfully buffered Latinos from further discrimination following an ID request. The association of Latino identity with foreignness and undocumented immigration and the usefulness of municipal ID card programs for reducing bias against Latinos are discussed. MUNICIPAL-ISSUED ID CARDS AND BIASED TREATMENT
Remembering faces and remembering whom to trust-An experimental study on cognitive racial discrimination VERY PRELIMINARY AND INCOMPLETE

The question addressed in this study is whether limitations in the ability to remember people from other races can explain differences in trust decisions within and across race. I conduct an experiment in a controlled environment. Participants are presented with a set of pictures of people of different races East Asian and Caucasian White and each person is labelled as “trustworthy” or “not trustworthy” in a random manner. Subjects are then shown all pictures again, and are asked whether they trust each person or not. The question is whether subjects can better recall whom to trust and whom to distrust among people from their own race in comparison to other races. An asymmetry could provide an alternative explanation for why trust is easier to sustain within race than across race.
2 Grassroots breeding of local crops and varieties in support of community biodiversity management and resilience in Nepal

Most of the poor live in rural areas and depend on agriculture for their livelihoods and well-being. A key livelihood asset that they maintain is their agrobiodiversity, which is made up of their crops, varieties and forest species. Improving the use of agrobiodiversity through enhanced understanding and better management offers opportunities to advance the well-being of small-scale farmers by providing more sustainable production systems, better nutrition and enhanced income opportunities (Jarvis et al., 2011). In the past, the world invested many resources in collecting and conserving farmers’ varieties of the major food crops for future use by plant breeders, rather than developing mechanisms to make local biodiversity accessible to poor and needy people. Many small-scale farmers in marginal areas have not yet benefited from the investments and great successes in modern plant breeding (Bellon, 2006). Various methods that together shape participatory crop improvement (PCI) have been developed in recent decades with the aim of meeting those farmers’ needs (Sthapit et al., 1996; Witcombe et al., 1996; Ceccarelli et al., 2009). However, most PCI methods do not assess the usefulness of plant genetic resources (PGR) that are easily available to farmers in the form of local varieties or semi-domesticated species before launching conventional breeding schemes with elements of farmer participation.
Design and Development of a 2D-Convolution CNN model for Recognition of Handwritten Gurumukhi and Devanagari Characters

Owing to the innumerable appearances due to different writers, their writing styles, technical environment differences and noise, the handwritten character recognition has always been one of the most challenging task in pattern recognition. The emergence of deep learning has provided a new direction to break the limits of decades old traditional methods. There exist many scripts in the world which are being used by millions of people. Handwritten character recognition studies of several of these scripts are found in the literature. Different hand-crafted feature sets have been used in these recognition studies. Feature based approaches derive important properties from the test patterns and employ them in a more sophisticated classification model. Feature extraction using Zernike moment and Polar harmonic transformation techniques was also performed and a moderate classification accuracy was also achieved. The problems faced while using these techniques led us to use CNN based recognition approach which is capable of learning the feature vector from the training character image samples in an unsupervised manner in the sense that no hand-crafting is employed to determine the feature vector. This paper presents a deep learning paradigm using a Convolution Neural Network (CNN) which is implemented for handwritten Gurumukhi and devanagari character recognition (HGDCR). In the present experiment, the training of a 34-layer CNN for a 35 class self-generated handwritten Gurumukhi and 60 class (50 alphabet and 10 digits) handwritten Devanagari character dataset was performed on a GPU (Graphic Processing Unit) machine. The experiment resulted with an average recognition accuracy of more than 92% in case of Handwritten Gurumukhi Character dataset and 97.25% in case of Handwritten Devanagari Character dataset. It was also concluded that the training and classification through our network design performed about 10 times faster than on a moderately fast CPU. The advantage of this framework is proved by the experimental results.
A Reliable Scheme To Filter False Data At Minimial Hops For Secured Wsn

Wireless Sensor Network has been widely used in various application areas like patient care, habitat monitoring, sensing physical parameters, traffic monitoring and so on. WSN integrates computing, communication and storage capabilities with monitoring and control of entities in the physical world, and must do so dependably, safely, securely, efficiently and in real‐time. Sensor nodes obtain the measurement from the physical components, process the measurements and send measured data to the controller through networks. According to measurements, the base station estimates the state of physical systems and sends feedback commands to control the operation of physical systems. The attacker can infuse false data to the system through compromised sensor nodes which eventually weaken the system’s security. To address the above issue few enroute filtering schemes exist but they lack resistance to the number of compromised nodes. The planned scheme endorses data at each hop before forwarding it to the next node which ensures detecting false data in minimal hop. Via simulation results it could be justified that the discussed scheme achieves better filtering capacity and resilience to compromised nodes.
Secure and Scalable Document Similarity on Distributed Databases: Differential Privacy to the Rescue

Abstract Privacy-preserving collaborative data analysis enables richer models than what each party can learn with their own data. Secure Multi-Party Computation (MPC) offers a robust cryptographic approach to this problem, and in fact several protocols have been proposed for various data analysis and machine learning tasks. In this work, we focus on secure similarity computation between text documents, and the application to k-nearest neighbors (k-NN) classification. Due to its non-parametric nature, k-NN presents scalability challenges in the MPC setting. Previous work addresses these by introducing non-standard assumptions about the abilities of an attacker, for example by relying on non-colluding servers. In this work, we tackle the scalability challenge from a different angle, and instead introduce a secure preprocessing phase that reveals differentially private (DP) statistics about the data. This allows us to exploit the inherent sparsity of text data and significantly speed up all subsequent classifications.
Secure Storing and Sharing of Documents on Cloud

Nowadays most of the citizens of India have their identity and personal documents starting from date of birth certificate, educational certificate, Voter ID, Ration Card, Driving License, vehicles registration number, PAN Card, Passport, Electricity bills, bank account numbers, insurance etc. While searching for jobs, it’s mandatory to carry important documents, but this involves risk. There are chances that these documents may be lost, stolen or even sometimes people may forget to carry necessary documents. This software system transforms the paper document/identities to the digital form for the better and easy access with verification and security of documents using AES (Advanced Encryption Standard) algorithm. Hence nobody can upload fake documents into this system. This software system helps the people to maintain their documents/identities for long time and citizens will always feel that they have their documents/identities in their hands. This paper explains the methodology of the securely storing and sharing the documents.
A Behavior Based Intrusion Detection System Using Machine Learning Algorithms

Humans are consistently referred to as the weakest link in information security. Human factors such as individual differences, cognitive abilities and personality traits can impact on behavior and play a significant role in information security. The purpose of this study is to identify, describe and classify the human factors affecting Information Security and develop a model to reduce the risk of insider misuse and assess the use and performance of the best-suited artificial intelligence techniques in detection of misuse. More specifically, this study provides a comprehensive view of the human related information security risks and threats, classification study of the human related threats in information security, a methodology developed to reduce the risk of human related threats by detecting insider misuse by a behavior-based intrusion detection system using machine learning algorithms, and the comparison of the numerical experiments for analysis of this approach. Specifically, by using the machine learning algorithm with the best learning performance, the detection rates of the attack types defined in the organized five dimensional human threats taxonomy were determined. Lastly, the possible human factors affecting information security as linked to the detection rates were sorted upon the evaluation of the taxonomy.
Design and Implementation of a Multi-Agent System for the Job Shop Scheduling Problem

Job shop scheduling is one of the strongly NP-complete combinatorial optimization problems. Developing effective search methods is always an important and valuable work. Metaheuristic methods such as genetic algorithms are widely applied to find optimal or nearoptimal solutions for the job shop scheduling problem. Parallelizing genetic algorithms is one of the best approaches that can be used to enhance the performance of these algorithms. In this paper, we propose an agent-based parallel genetic algorithm for the job shop scheduling problem. In our approach, initial population is created in an agent-based parallel way then an agent-based method is used to parallelize the genetic algorithm. Experimental results showed that the proposed approach enhances the performance.