Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of replacement of sugarcane by oilseed press cakes in greenhouse gases and volatile fatty acids production in vitro

This study aimed to evaluate the production of methane, carbon dioxide, and volatile fatty acids and changes in ruminal pH in vitro with oilseed press cakes inclusion, such as, cottonseed, sunflower, castor bean, moringa and jatropha at four different levels (0, 30, 50 and 70%) in replacement to the sugarcane in ruminant feeding using semi-automated in vitro technique. The byproduct that produced less CO2 was cottonseed cake (p = 0.0059). The cakes that produced the least amount of CH4 were moringa at 70% (p < 0.05) and cottonseed at 70% levels (p < 0.0001). The cakes that had the highest increases in VFAs were cottonseed and castor (p < 0.0001). Additionally, greater pH was moringa at 70% and cottonseed at 50% levels (p < 0.0001). The greater acetate concentration was 70% cottonseed cake, propionate concentration with 30% cottonseed and butyrate concentration with 50% moringa in sugarcane replace. At the 70% level, the moringa cake displayed the highest decreases in methane production and reduction in energy loss. At the 50% substitution level, the cottonseed cake is the most suitable replacement for sugarcane in order to reduce the production of greenhouse gases.
Analysis of directional dependence using asymmetric copula-based regression models

The directional dependence between variables using asymmetric copula regression has drawn much attention in recent years. There are, however, some critical issues which have not been properly addressed in regards to the statistical inference of the directional dependence. For example, the previous use of asymmetric copulas failed to fully capture the dependence patterns between variables, and the method used for the parameter estimation was not optimal. In addition, no method was considered for selecting a suitable asymmetric copula or for computing the general measurements of the directional dependence when there are no closed-form expressions. In this paper, we propose a generalized multiple-step procedure for the full inference of the directional dependence in joint behaviour based on the asymmetric copula regression. The proposed procedure utilizes several novel methodologies that have not been considered in the literature of the analysis of directional dependence. The performance and advantages of the proposed procedure are illustrated using two real data examples, one from biological research on histone genes, and the other from developmental research on attention deficit hyperactivity disorder.
Simultaneous Exposure of workers to EMF Radiated by a Three Band Base Station Antenna

INTRODUCTION Occupational exposure of maintenance workers in clo se proximity to transmitting base station antennas has been the focus of many studies [1][2][3]. However, most of these studies investigate exposure at a single frequency and do n ot consider the possibility of simultaneous exposure to several transmitting frequencies at the same time. By using numerical FDTD simulations, we have evaluated the combined EMF exp osure of an anatomical human model positioned in front of a 3 band panel base station antenna, with simultaneous exposure at frequencies of 900, 1800 and 2100 MHz.
Hibernation of Parti-Coloured Bat, Vespertilio murinus (Chiroptera, Vespertilionidae), in Belarus

Abstract Parti-coloured bat (Vespertilio murinus Linnaeus, 1758) was considered in Belarus as a migrant species until recently. This point of view was based on the absence of winter records as well as the registrations in Austria and Romania of two V. murinus′ specimens, banded in Belarus. The data, obtained over the past few years, allow to state, that the whole territory of Belarus belongs to the winter range of this species. Hibernating animals were observed exclusively in the anthropogenic roosts.
Energy Efficient Management for Mobile Ad Hoc Networks

This paper describes a mobile ad hoc network (MANET), a collection of digital data terminals that can communicate with one another without any fixed networking infrastructure. Since the nodes in a MANET are mobile, the routing and power management become critical issues. However, due to the slow advancement of battery technology, battery power continues to be a constrained resource and so power management in wireless networks remains to be an important issue. Though many devices proactive and reactive routing protocols exist for MANETs the reactive dynamic source routing (DSR) protocol is considered to be an efficient protocol. In this paper it is proposed to implement overhead reduction and efficient energy management for DSR in mobile ad hoc networks.
Host Fingerprinter Liveness Checker Relay Profiler Controlled web servers Controlled clients RESIP service Controlled DNS serversRESIP service RESIP service Purchase RESIP services Classifier DNS Whois Feature Extraction Training Dataset RESIP Candidates RESIP The Infiltration Framework Residential 

An emerging Internet business is residential proxy (RESIP) as a service, in which a provider utilizes the hosts within residential networks (in contrast to those running in a datacenter) to relay their customers’ traffic, in an attempt to avoid serverside blocking and detection. With the prominent roles the services could play in the underground business world, little has been done to understand whether they are indeed involved in Cybercrimes and how they operate, due to the challenges in identifying their RESIPs, not to mention any in-depth analysis on them. In this paper, we report the first study on RESIPs, which sheds light on the behaviors and the ecosystem of these elusive gray services. Our research employed an infiltration framework, including our clients for RESIP services and the servers they visited, to detect 6 million RESIP IPs across 230+ countries and 52K+ ISPs. The observed addresses were analyzed and the hosts behind them were further fingerprinted using a new profiling system. Our effort led to several surprising findings about the RESIP services unknown before. Surprisingly, despite the providers’ claim that the proxy hosts are willingly joined, many proxies run on likely compromised hosts including IoT devices. Through cross-matching the hosts we discovered and labeled PUP (potentially unwanted programs) logs provided by a leading IT company, we uncovered various illicit operations RESIP hosts performed, including illegal promotion, Fast fluxing, phishing, malware hosting, and others. We also reverse engineered RESIP services’ internal infrastructures, uncovered their potential rebranding and reselling behaviors. Our research takes the first step toward understanding this new Internet service, contributing to the effective control of their security risks.
COMBINING FUZZY AND CELLULAR LEARNING AUTOMATA METHODS FOR CLUSTERING WIRELESS SENSOR NETWORK TO INCREASE LIFE OF THE NETWORK

Wireless sensor networks have attracted attention of researchers considering their abundant applications. One of the important issues in this network is limitation of energy consumption which is directly related to life of the network. One of the main works which have been done recently to confront with this problem is clustering. In this paper, an attempt has been made to present clustering method which performs clustering in two stages. In the first stage, it specifies candidate nodes for being head cluster with fuzzy method and in the next stage, the node of the head cluster is determined among the candidate nodes with cellular learning automata. Advantage of the clustering method is that clustering has been done based on three main parameters of the number of neighbors, energy level of nodes and distance between each node and sink node which results in selection of the best nodes as a candidate head of cluster nodes. Connectivity of network is also evaluated in the second part of head cluster determination. Therefore, more energy will be stored by determining suitable head clusters and creating balanced clusters in the network and consequently, life of the network increases.
Mechanism of cervical squamous cell carcinoma radioresistance conferred by Aurora-A

Cervical squamous cell carcinoma (CSCC) is one of the most common gynecological malignant tumor,the main reason of treatment failure is radiation resistance. Aurora kinase A (Aurora-A, AURKA) is a member of serine/ threonine kinase family. The abnormal expression of Aurora-A induces tumorigenesis and radioresistance. This study was aimed to investigate the association of Aurora-A with CSCC radioresistance. Wecollect 98 cases of untreated patients diagnosed with CSCC and detect the expression of Aurora-A in biopsy specimens by immunohistochemistry. CSCCHCC94 cells were treated with Aurora-A kinase inhibitor MLN8237 and accept a certain amount of 4 Mv X-ray radiation (0, 2.0, 4.0, 6.0 Gy,) and then used to test cell proliferation, cell apoptosis, cell cycle, and cell cycle regulatory proteins respectively. The resultsshowed that Aurora-A was over-expression in CSCC and relate with cell invasion and metastasis. cell proliferation and cell apoptosis of MLN8237 treated group were increased after X-irradiation. And the expression of Cyclin D1, CDK2 and CDK6 were down-regulated to induce cell cycle arrest at G2/M phases. Therefore, we concluded that Aurora-A inhibitor can blocks cell proliferation and cell cycle progression, promote cell apoptosis, and increase the sensitivity of cervical cancercells to radiotherapy by regulating the expression of cell cycle related protein. Thus, Aurora-A may be used as one of therapeutic targets and an independent prognostic factor to increase the sensitivity of CSCC radiotherapy.
Downstep and its interaction with focus and boundary in Mandarin Chinese

1 It has been observed that in a HLH (High-Low-High) tone sequence, the second H tone is lowered in pitch, as compared to a HHH tone sequence, which was termed as downstep. To calculate the downstep effect and test its scope, we compared sentences in the tonal structure of (HHHHH H )(HHHHHHH) to (HHHHH L )(HHHHHHH). The syntactic boundary between the L (X) and the H (Y) was either a syllable boundary or a phrase boundary. Moreover, corrective focus was elicited either on the syllable X, Y, sentence final (Z) or none (wide focus). The results showed that: (1) in the wide focus and sentence-final focus (ZF) condition, downstep can last for several syllables; (2) a phrase boundary did not block downstep; (3) when syllable Y was focused, on-focus F0 raising did not override downstep, however, it stopped the trend of downstep in the following H tones; (4) when syllable X was focused, it caused a post-low-bouncing effect on the following H tones instead. Taken together the data showed that downstep is relatively stable and independent.
Prototypical actions with objects are more easily imagined than atypical actions

ABSTRACT Tool use is an important facet of everyday life, though sometimes it is necessary to use tools in ways that do not fit within their typical functions. Here we asked participants to imagine characters using objects based on instructions that fit the prototypical actions for the object or were atypical in a novel object-action imagery task. Atypical action instructions either described sensible, substitute uses of the object, or actions that were bizarre but possible. Participants were better able to imagine the prototypical than atypical actions, but no effect of bizarreness was found. We additionally assessed inter-individual differences in movement imagery ability using two objective tests. Performance in the object-action imagery task correlated with the movement imagery tests, providing a link between motor simulations and mental imagery ability.
Improved Zero-Knowledge Proofs for Lattice Encryption Schemes , Linking Classical and Lattice Primitives , and Applications

It now seems probable that a quantum computer breaking non-trivial instances of the RSA and discrete logarithm problem will be built in the not-too-distant future. Despite this, for many applications such as electronic voting or anonymous authentication where simple encryption and signature schemes are not sufficient, there are currently no practical protocols that one could use to defend against such quantum adversaries. One might think that such protection is not yet needed, but this creates vulnerabilities against an adversary who collects data today and is then able to break all the privacy and anonymity properties of current protocols using a quantum computer in the future. In the absence of efficient lattice schemes for advanced protocols, in this work we begin the investigation of “hybrid” schemes that try to maintain the efficiency of classical protocols, but with the forward-security of lattice-based ones. Our main result is a proposal of one such protocol – a group signature scheme that combines the efficiency of today’s number theoretic schemes, while using lattice encryption to guarantee privacy to its members even after quantum computers are developed. As intermediate steps, we provide a new and more efficient protocol for proving the validity of a lattice-based ciphertexts, and then extend this to a protocol that proves that a classical commitment and a lattice-based encryption contain the same secret. We believe that these two protocols are also interesting in their own right. From these two primitives, our group signature construction then follows a generic folklore approach, for which, to the best of our knowledge, we provide the first formal security proof.
Slimme sturing van publiek-private
 samenwerking bij publieke infrastructuur

Bij de aanleg en het beheer van publieke infrastructuur heeft het Rijk de laatste jaren voor publiek-private samenwerking, en met name voor het DBFM(O)-con‐ tract, als slim arrangement gekozen: langlopende contracten waarbij het ontwerp (D), de bouw (B), de financiering (F), het onderhoud (M) en vaak ook de exploitatie (O) integraal worden uitbesteed aan een privaat consortium. Met deze slimme DBFM(O)-contracten wordt getracht de sterke punten van overheid en de markt te combineren om de steeds grotere en complexere publieke opgaven aan te kunnen. De praktijk blijkt echter weerbarstig: recent hebben Rijkswaterstaat en een aantal private partijen het initiatief genomen tot wat zij noemden ‘een nieuwe marktvi‐ sie’. Daarin stellen ze voor om publiek-private samenwerking op een nieuwe leest te schoeien. Onder andere naar aanleiding van problemen bij DBFM(O)-projecten pleiten zij voor meer aandacht voor relationele aspecten van samenwerking, zoals houding, openheid en vertrouwen. Ook onderzoek laat zien dat het succes van DBFM(O)-projecten niet bepaald wordt door het contract of een strikt contractma‐ nagement. Slimme sturing vraagt om meer: om een verschuiving van een financi‐ eel-economisch georiënteerde contractuele benadering naar een meer sociologisch geïnspireerde relationele manier van sturen.
Survival Analysis Meets Data Stream Mining

Survival analysis deals with monitoring entities over their lifetime. The definition of "birth" and "death" events depends on the nature of a given entity. When we observe an infinite stream of birth and death events, at each point in time some of the monitored entities are "right-censored", i.e. we know the time elapsed since their birth event, but their death event has not occurred yet and we do not know when it will occur in the future. Often, the snapshots of partially censored observations keep arriving over time in the form of a data stream. Given each snapshot, we may be interested to predict the timing of death events for all live entities or, alternatively, to predict their label ("survived" or "failed") as a function of time. In this research, our intention is to modify standard classification algorithms, such as decision trees, so that they can seamlessly handle a snapshot stream of both censored and non-censored data. The objective is to provide reasonably accurate predictions after observing relatively few snapshots of the data stream and to improve the classification model with additional information obtained from each new snapshot.
Diagnosis of Breast Cancer using Decision Tree and Artificial Neural Network Algorithms

: Breast Cancer Diagnosis and Prognosis are two medical applications which have posed a challenge to the researchers. The use of machine learning and data mining techniques has revolutionized the whole process of breast cancer Diagnosis and Prognosis. Breast Cancer Diagnosis distinguishes benign from malignant breast lumps and Breast Cancer Prognosis predicts when Breast Cancer is likely to recur in patients that have had their cancers existed. Thus, these two problems are mainly in the scope of the classification problems. Most data mining methods which are commonly used in this domain are considered as classification category and applied prediction techniques assign patients to either a” benign” group that is non-cancerous or a” malignant” group that is cancerous. Hence, the breast cancer diagnostic problems are basically in the scope of the widely discussed classification problems. In this study, two powerful classification algorithms namely decision tree and Artificial Neural Network have been applied for breast cancer prediction. Experimental results show that the aforementioned algorithms has a promising results for this purpose with the overall prediction accuracy of 94% and 95.4%, respectively.
Poster : Using Packet Timing in Website Fingerprinting

Website Fingerprinting (WF) enables an eavesdropper to discover what sites the user is visiting despite the use of a VPN or even the Tor anonymity system. Recent WF attacks on Tor have reached high enough accuracy (up to 98%) to prompt Tor to consider adopting defenses based on packet padding. Defenses such as Walkie-Talkie mainly remove features related to bursts of traffic without affecting packet timing. This was reasonable given that previous research on WF attacks ignored or deemphasized the use of packet timing information. In this paper, we examine the extent to which packet timing can be used to facilitate WF attacks. In our experiment, we gained up to 61% accuracy on our unprotected dataset, 54% on our WTFPAD dataset, and 43% on our Walkie-Talkie dataset using only timing-based features in an SVM classifier. Using a convolutional neural network (CNN), we got 86% accuracy on our unprotected dataset, 76% and 47% accuracy on our WTF-PAD and WalkieTalkie dataset respectively. We intend to investigate further to develop an effective and robust WF attack using packet timing.
SDSS-IV MaNGA: characterizing non-axisymmetric motions in galaxy velocity fields using the Radon transform

We show how the Radon transform (defined as a series of line integrals through an image at different orientations and offsets from the origin) can be used as a simple, non-parametric tool to characterize galaxy velocity fields, specifically their global kinematic position angles (PA_k) and any radial variation or asymmetry in PA_k. This method is fast and easily automated, making it particularly beneficial in an era where IFU and interferometric surveys are yielding samples of thousands of galaxies. We demonstrate the Radon transform by applying it to gas and stellar velocity fields from the first ~2800 galaxies of the SDSS-IV MaNGA IFU survey. We separately classify gas and stellar velocity fields into five categories based on the shape of their radial PA_k profiles. At least half of stellar velocity fields and two-thirds of gas velocity fields are found to show detectable deviations from uniform coplanar circular motion, although most of these variations are symmetric about the center of the galaxy. The behavior of gas and stellar velocity fields is largely independent, even when PA_k profiles for both components are measured over the same radii. We present evidence that one class of symmetric PA_k variations is likely associated with bars and/or oval distortions, while another class is more consistent with warped disks. This analysis sets the stage for more in-depth future studies which explore the origin of diverse kinematic behavior in the galaxy population.
Extraction of Palladium from Acidic Chloride Media into Emulsion Liquid Membranes using LIX 984N-C ®

The extraction of palladium from hydrochloric acid solutions into emulsion liquid membranes (ELMs) using LIX 984N-C as the extractant was investigated. The influential factors and the total capacities of palladium extraction were determined by a batch method. The behavior of palladium extraction by ELMs under the operational conditions-pH of the external feed phase, surfactant and extractant concentration, internal stripping phase concentration, treat ratio and agitation speed were reported. Using LIX 984N-C, palladium was effectively extracted from the external acidic chloride feed phase into the internal receiving phase of W/O emulsions. More than 92% of palladium could be extracted at a feed pH of 2 with 3% Span 80, 9% LIX 984N-C and 7M HCl at a stirring speed of 300 rpm.
Rotating machinery fault diagnosis using similarity-based models

This work proposes an automatic fault classifier that uses similarity-based modeling (SBM) to identify faults on rotating machines. The similarity model can be used either as an auxiliary model to generate features for a classifier or as a standalone classifier. A new approach for training the model using a prototype-selection method is investigated. Experimental results are shown for the MaFaulDa database and for the Case Western Reserve University (CWRU) bearing database. Results indicate that the proposed modifications improve the generalization power of the similarity model and of the associated classifier, achieving accuracies of 96.4% on the MaFaulDa and 98.7% on the CWRU databases. Keywords— Fault diagnosis, Condition monitoring, Feature extraction, Similarity-based modeling, Machine learning.
Optimization of Test Data for Basis Path Testing using Artificial Intelligence Techniques

Software testing is a process carried out with the intent of finding errors. This helps in analyzing the stability and quality of a software. Stability and quality can be achieved by suitable test data. Test data can be generated either manually or by automated process. Manual generation of test data is a difficult task. It involves lot of effort due to presence of huge number of predicate nodes in a module. In this report, an automated process is proposed for test data generation in traditional methodology for the automatically constructed control flow graph. Code Coverage is a measure used in software testing process and is one of the key indicators of software quality. It helps the tester in evaluating the effectiveness of testing. It is achieved by automatically generating test data for various functions. Code coverage is not a method or a test; it is a measure which helps in improving software reliability. Effort has been made to gather code coverage information either by source code or by the requirements specified by the customer. But less attention has been paid to achieve better coverage. This report also emphasizes on code coverage, achieved through the test data generated, using some soft computing techniques. Here, three soft computing techniques such as Genetic algorithm, Particle swarm optimization and the Clonal selection algorithm techniques have been deployed for automatic test data generation. This test data was in turn used for code coverage analysis. Experimental results show that the test data generated using Clonal selection algorithm was much more effective in achieving better code coverage over Genetic algorithm and Particle swarm optimization.