Miracle-dz/UniFAR-FTUs huggingface dataset:
Recovery of Object Oriented Features from C++ Binaries

Reverse engineering is the process of examining and probing a program to determine the original design. Over the past ten years researchers have produced a number of capabilities to explore, manipulate, analyze, summarize, hyperlink, synthesize, componentize, and visualize software artifacts. Many reverse engineering tools focus on non-object-oriented software binaries with the goal of transferring discovered information into the software engineers trying to reengineer or reuse it. In this paper, we present a method that recovers object-oriented features from stripped C++ binaries. We discover RTTI information, class hierarchies, member functions of classes, and member variables of classes. The information obtained can be used for reengineering legacy software, and for understanding the architecture of software systems. Our method works for stripped binaries, i.e., Without symbolic or relocation information. Most deployed binaries are stripped. We compare our method with the same binaries with symbolic information to measure the accuracy of our techniques. In this manner we find our methods are able to identify 80% of virtual functions, 100% of the classes, 78% of member functions, and 55% of member variables from stripped binaries, compared to the total number of those artifacts in symbolic information in equivalent non-stripped binaries.
Application-level attack against Tor's hidden service

Tor has become one of the most popular overlay networks for anonymizing TCP traffic. Hidden service provided by Tor allows users to run a TCP server under a pseudonym, and its resources can be accessed without the operator's real identity being revealed. In this paper, we propose a novel HTTP based application-level attack against Tor's hidden web service. Under the assumption that the entry of the suspected hidden server's circuit is occupied, we evaluate the time correlation between the web accessing and the generated traffic in the malicious onion router. Furthermore, we analyze the probability that the malicious onion routers occupy the entry of the hidden server's circuit when advertise high bandwidth, which is the foundation of our attack. We conducted real-world experiments to evaluate our attack method. The empirical results demonstrate that the hidden service can be effectively and efficiently located.
Security embedding on UWB-IR physical layer

The main goal of this work is to incorporate security in an existing ultra wideband (UWB) network. We present an embedding method where a tag is added at the physical layer and superimposed to the UWB-impulse radio signal. The tag should be added in a transparent way so that guaranteeing compatibility with existing receivers ignoring the presence of the tag. We discuss technical details of the new embedding method. In addition, we discuss embedding strength and we analyze robustness performance. We demonstrate that the proposed embedding technique meets all the system design constraints.
Intuitive Fuzzy C-Means Algorithm for MRI Segmentation

A new model called intuitive fuzzy c-means (IFCM) model is proposed for the segmentation of magnetic resonance image in this paper. Fuzzy c-means (FCM) is one of the most widely used clustering algorithms and assigns memberships to which are inversely related to the relative distance to the point prototypes that are cluster centers in the FCM model. In order to overcome the problem of outliers in data, several models including possibilistic c-means (PCM) and possibilistic-fuzzy cmeans (PFCM) models have been proposed. In IFCM, a new measurement called intuition level is introduced so that the intuition level helps to alleviate the effect of noise. Several numerical examples are first used for experiments to compare the clustering performance of IFCM with those of FCM, PCM, and PFCM. A practical magnetic resonance image data set is then used for image segmentation experiment. Results show that IFCM compares favorably to several clustering algorithms including the SOM, FCM, CNN, PCM, and PFCM models. Since IFCM produces cluster prototypes less sensitive to outliers and to the selection of involved parameters than the other algorithms, IFCM is a good candidate for data clustering and image segmentation problems.
Digitally controlled oscillator (DCO)-based architecture for RF frequency synthesis in a deep-submicrometer CMOS Process

A novel digitally controlled oscillator (DCO)-based architecture for frequency synthesis in wireless RF applications is proposed and demonstrated. It deliberately avoids any use of an analog tuning voltage control line. Fine frequency resolution is achieved through high-speed /spl Sigma//spl Delta/ dithering. Other imperfections of analog circuits are compensated through digital means. The presented ideas enable the employment of fully-digital frequency synthesizers using sophisticated signal processing algorithms, realized in the most advanced deep-submicrometer digital CMOS processes which allow almost no analog extensions. They also promote cost-effective integration with the digital back-end onto a single silicon die. The demonstrator test chip has been fabricated in a digital 0.13-/spl mu/m CMOS process together with a DSP, which acts as a digital baseband processor with a large number of digital gates in order to investigate noise coupling. The phase noise is -112 dBc/Hz at 500-kHz offset. The close-in spurious tones are below -62 dBc, while the far-out spurs are below -80 dBc. The presented ideas have been incorporated in a commercial Bluetooth transceiver.
PATIENTS WITH HYPERTENSION SMBP Monitoring Different SMBP Devices Additional Support Figure A . Analytic framework for evaluation of SMBP monitoring Methods

High blood pressure (BP), or hypertension, is a common, long-term health condition, particularly among older adults. Untreated or ineffectively treated hypertension leads to increased cardiovascular morbidity and mortality, and increased consumption of health care resources, thus levying high human and financial costs to society. In adults, hypertension is defined as a persistently elevated BP equal to or greater than 140/90 mmHg.1 In children, the diagnosis is made from an average of three or more BP readings greater than the 95th percentile for age, sex, and height.2,3 The Seventh Joint National Committee (JNC 7) guideline recommends a BP goal of 140/90 mmHg or less in the general population and a lower threshold of 130/80 mmHg or less in patients with diabetes mellitus or chronic kidney disease.1
Fast evaluation-based algorithm for fixed-outline floorplanning

Floorplanning is a very crucial step in modern VLSI designs. It dominates the top-level spatial structure of a chip and initially optimizes the interconnections. Thus a good floorplan solution among circuit modules definitely has a positive impact on the placement, routing and even manufacturing. In this paper, we propose an efficient approach for the evaluation of the insertion points. The proposed method evaluates 2n insertion points, instead of all (n + 1)2 insertion points as did in the state-of-the-art. The proposed techniques can be integrated into the general simulated annealing algorithm, resulting in a fast algorithm for floorplanning. Experimental results show that, the state-of-the-art can be improved up to 37% in terms of running time, without loss of success rate. In addition, our algorithm is comparable to the state-of-the-art in terms of wirelength.
Facial cartography: interactive scan correspondence

We present a semi-automatic technique for computing surface correspondences between 3D facial scans in different expressions, such that scan data can be mapped into a common domain for facial animation. The technique can accurately correspond high-resolution scans of widely differing expressions -- without requiring intermediate pose sequences -- such that they can be used, together with reflectance maps, to create high-quality blendshape-based facial animation. We optimize correspondences through a combination of Image, Shape, and Internal forces, as well as Directable forces to allow a user to interactively guide and refine the solution. Key to our method is a novel representation, called an Active Visage, that balances the advantages of both deformable templates and correspondence computation in a 2D canonical domain. We show that our semi-automatic technique achieves more robust results than automated correspondence alone, and is more precise than is practical with unaided manual input.
Shootin1 Acts in Concert with KIF20B to Promote Polarization of Migrating Neurons

Shootin1 has been ascribed a role in regulating polarization of primary hippocampal neurons. To better understand the possible role of Shootin1 in the developing brain, we identified a member of the kinesin superfamily, KIF20B, as a novel Shootin1 interacting protein and a potential mediator of Shootin1 interaction with microtubules. KIF20B/Shootin1 binding was mapped to a 57 aa KIF20B sequence, which was used as a dominant-negative fragment. Direct interaction between that peptide (MBD) and Shootin1 was confirmed by surface plasmon resonance-based technology and the affinity was determined in the 10−7 m range. The proteins are expressed in the developing brain and formed a complex in vivo based on coimmunoprecipitation experiments and coimmunostaining in primary neurons. In primary hippocampal neurons Kif20b knockdown reduced Shootin1 mobilization to the developing axon, as evidenced by immunostaining and fluorescence recovery after photobleaching analysis, suggesting that Shootin1 is a novel KIF20B cargo. shRNA targeting of Shootin1 reduced PIP3 accumulation in the growth cone, as did Kif20b shRNA. In the developing mouse brain, Kif20b knockdown or expression of the KIF20B minimal binding domain inhibited neuronal migration, and in vivo migration assays suggested that Shootin1/Kif20b acts in the same genetic pathway. Time-lapse imaging of multipolar cells in the subventricular zone revealed that downregulating levels of either Shootin1 or Kif20b hindered the transition from multipolar to bipolar cells. Collectively, our data demonstrate the importance of the Shootin1/KIF20B interaction to the dynamic process of pyramidal neuronal polarization and migration.
Generalized Ontology-Based Production Systems

We define generalized ontology-based production systems (GOPSs), which formalize a very general and powerful combination of ontologies and production systems. We show that GOPSs capture and generalize many existing formal notions of production systems. We introduce a powerful verification query language for GOPSs, which is able to express the most relevant formal properties of production systems previously considered in the literature. We establish a general sufficient condition for the decidability of answering verification queries over GOPSs. Then, we define Lite-GOPS, a particular class of GOPSs based on the use of a light-weight ontology language (DL-LiteA), a light-weight ontology query language (EQL-Lite(UCQ)), and a tractable semantics for updates over Description Logic ontologies. We show decidability of all the above verification tasks over Lite-GOPSs, and prove tractability of some of such tasks.
Learning Abstract Classes using Deep Learning

Humans are generally good at learning abstract concepts about objects and scenes (e.g.\ spatial orientation, relative sizes, etc.). Over the last years convolutional neural networks have achieved almost human performance in recognizing concrete classes (i.e.\ specific object categories). This paper tests the performance of a current CNN (GoogLeNet) on the task of differentiating between abstract classes which are trivially differentiable for humans. We trained and tested the CNN on the two abstract classes of horizontal and vertical orientation and determined how well the network is able to transfer the learned classes to other, previously unseen objects.
Recognition of interest in human conversational speech

Recognition of interest of a speaker within a human dialog bears great potential in many commercial applications. Within this work we therefore introduce an approach that analyses acoustic and linguistic cues of a spoken utterance. A systematic generation of more than 5k hi-level features basing on prosodic and spectral feature contours by means of descriptive statistical analysis and subsequent feature space optimization is used to find relevant acoustic attributes. For linguistic information integration a bag-of-words representation is used relying on a speech recognizer’s output. One main aspect is the database of more than 2k spontaneous sub-speaker turns recorded and annotated for this analysis. Several influence factors as microphone distance and ASR versus annotation of spoken content are discussed. Overall remarkable performance of a running prototype can be reported discriminating between three levels of interest.
Kisspeptin-GPR54 Signaling in Mouse NO-Synthesizing Neurons Participates in the Hypothalamic Control of Ovulation

Reproduction is controlled in the brain by a neural network that drives the secretion of gonadotropin-releasing hormone (GnRH). Various permissive homeostatic signals must be integrated to achieve ovulation in mammals. However, the neural events controlling the timely activation of GnRH neurons are not completely understood. Here we show that kisspeptin, a potent activator of GnRH neuronal activity, directly communicates with neurons that synthesize the gaseous transmitter nitric oxide (NO) in the preoptic region to coordinate the progression of the ovarian cycle. Using a transgenic Gpr54-null IRES-LacZ knock-in mouse model, we demonstrate that neurons containing neuronal NO synthase (nNOS), which are morphologically associated with kisspeptin fibers, express the kisspeptin receptor GPR54 in the preoptic region, but not in the tuberal region of the hypothalamus. The activation of kisspeptin signaling in preoptic neurons promotes the activation of nNOS through its phosphorylation on serine 1412 via the AKT pathway and mimics the positive feedback effects of estrogens. Finally, we show that while NO release restrains the reproductive axis at stages of the ovarian cycle during which estrogens exert their inhibitory feedback, it is required for the kisspeptin-dependent preovulatory activation of GnRH neurons. Thus, interactions between kisspeptin and nNOS neurons may play a central role in regulating the hypothalamic–pituitary–gonadal axis in vivo.
Dimensionality Detection and Integration of Multiple Data Sources via the GP-LVM

The Gaussian Process Latent Variable Model (GP-LVM) is a non-linear probabilistic method of embedding a high dimensional dataset in terms low dimensional `latent' variables. In this paper we illustrate that maximum a posteriori (MAP) estimation of the latent variables and hyperparameters can be used for model selection and hence we can determine the optimal number or latent variables and the most appropriate model. This is an alternative to the variational approaches developed recently and may be useful when we want to use a non-Gaussian prior or kernel functions that don't have automatic relevance determination (ARD) parameters. Using a second order expansion of the latent variable posterior we can marginalise the latent variables and obtain an estimate for the hyperparameter posterior. Secondly, we use the GP-LVM to integrate multiple data sources by simultaneously embedding them in terms of common latent variables. We present results from synthetic data to illustrate the successful detection and retrieval of low dimensional structure from high dimensional data. We demonstrate that the integration of multiple data sources leads to more robust performance. Finally, we show that when the data are used for binary classification tasks we can attain a significant gain in prediction accuracy when the low dimensional representation is used.
MMPs and angiogenesis affect the metastatic potential of a human vulvar leiomyosarcoma cell line

Gynaecological leiomyosarcoma (gLMS) represent a heterogeneous group of soft tissue sarcoma, characterized by rare incidence, high aggressiveness and propensity to infiltrate secondary organs, poor prognosis and lethality, because of the lack of biological mechanisms that underlying their progression and effective pharmaceutical treatments. This study was focused on some of the aspects of progression and dissemination of a subtype of gLMS namely vulvar LMS (vLMS). We therefore used a vulvar LMS‐derived cell line namely SK‐LMS‐1, coupled with in vitro and in vivo assays. We observed that SK‐LMS‐1 cells have a strong invasive capacity in vitro, through the activity of matrix metalloproteinases 2 and 9, while in vivo these cells induce a strong angiogenic response and disseminate to the chick embryo liver. Therefore, we postulate that metalloproteinases are involved in the spreading behaviour of SK‐LMS‐1. Further investigations are necessary to better understand the molecular and cellular machinery involved in the progression of this malignancy.
Reported Job Satisfaction: What Does it Mean?

We emphasize the major influences of experienced utility gaps or regret, i.e. the difference between what happened and what might have happened, on job satisfaction. The main prediction that we test is that job satisfaction correlates with the wage gaps experienced in the past and present, holding other job-related satisfactions constant, with the possible exception of young workers. We further test that this effect of wage gaps on job satisfaction declines with working experience. We find evidence on a Canadian cross-section that the past matters.
Relationships of plasma interleukin-18 concentrations to hyperhomocysteinemia and carotid intimal-media wall thickness in patients with type 2 diabetes.

OBJECTIVE We compared plasma interleukin (IL)-18 concentrations in patients with type 2 diabetes with those in age-matched control subjects and investigated whether plasma IL-18 was associated with plasma total homocysteine (tHcy) concentration or carotid intimal-media wall thickness (IMT), an early marker of atherosclerosis, in these patients. RESEARCH DESIGN AND METHODS We measured plasma IL-18 in 103 type 2 diabetic patients and 45 age-matched control subjects. We also measured patients' plasma tHcy and serum high-sensitivity C-reactive protein (hs-CRP). IMT was evaluated for both common carotid arteries. RESULTS Plasma IL-18 was significantly higher in diabetic patients than in control subjects (203 +/- 153 vs. 118 +/- 37 pg/ml, P < 0.001). High IL-18 was defined as equaling or exceeding the mean + 2 SD of plasma IL-18 in control subjects (192 pg/ml). Patients with high IL-18 showed a greater carotid IMT than those with normal IL-18. Carotid plaques were more numerous in diabetic patients with high IL-18 than in those with normal IL-18. Plasma tHcy concentrations were significantly higher in patients with high IL-18 than in those with normal IL-18. Univariate and multivariate analyses showed a strong independent association between tHcy and IL-18. Plasma IL-18 also correlated positively with serum hs-CRP. CONCLUSIONS In patients with type 2 diabetes, plasma IL-18 concentrations are greater than in nondiabetic subjects. Plasma IL-18 is an independent determinant of plasma tHcy, which is linked independently with atherosclerotic carotid wall thickening.
Authenticated error-correcting codes with applications to multicast authentication

We consider the problem of authenticating a stream of packets transmitted over a network controlled by an adversary who may perform arbitrary attacks on the stream: He may drop or modify chosen packets, rearrange the order of the packets in any way, and inject new, random, or specially crafted packets into the stream. In contrast, prior work on the multicast authentication problem has focused on a less powerful adversarial network model or has examined a considerably more restrictive setting with specific timing or structural assumptions about the network. We model the ability of the network to modify a stream of n packets with two parameters: the survival rate α (0 <α≤ 1) denoting the fraction of the packets that are guaranteed to reach any particular receiver unmodified and the flood rate β (β ≥ 1) indicating the factor by which the size of the received stream at any particular receiver may exceed the size of the transmitted stream. Combining error-correcting codes with standard cryptographic primitives, our approach gives almost the same security guarantees as if each packet were individually signed, but requires only one signature operation for the entire stream and adds to each transmitted packet only a small amount of authentication information, proportional to β/α2. We prove the security and correctness of our scheme and analyze its performance in terms of communication overhead and computational effort at the sender and the receiver. Our results demonstrate how list decoding can be transformed into unambiguous decoding in the public-key model and the bounded computational model for the underlying communication channel. Overall, our technique provides an authenticated error-correcting code of independent interest that may be useful in other settings.
The detection of interturn stator faults in doubly-fed induction generators

Presently, many condition monitoring techniques that are based on steady-state analysis are being applied to wind generators. However, the operation of wind generators is predominantly transient, therefore prompting the development of non-stationary techniques for fault detection. In this paper we apply steady-state techniques, e.g. motor current signatures analysis (MCSA) and the extended Park's vector approach (EPVA), as well as a new transient technique that is a combination of the EPVA, the discrete wavelet transform and statistics, to the detection of turn faults in a doubly-fed induction generators (DFIG). It is shown that steady-state techniques are not effective when applied to DFIG's operating under transient conditions. The new technique shows that stator turn faults can be unambiguously detected under transient conditions.
Mmi1, the Yeast Homologue of Mammalian TCTP, Associates with Stress Granules in Heat-Shocked Cells and Modulates Proteasome Activity

As we have shown previously, yeast Mmi1 protein translocates from the cytoplasm to the outer surface of mitochondria when vegetatively growing yeast cells are exposed to oxidative stress. Here we analyzed the effect of heat stress on Mmi1 distribution. We performed domain analyses and found that binding of Mmi1 to mitochondria is mediated by its central alpha-helical domain (V-domain) under all conditions tested. In contrast, the isolated N-terminal flexible loop domain of the protein always displays nuclear localization. Using immunoelectron microscopy we confirmed re-location of Mmi1 to the nucleus and showed association of Mmi1 with intact and heat shock-altered mitochondria. We also show here that mmi1Δ mutant strains are resistant to robust heat shock with respect to clonogenicity of the cells. To elucidate this phenotype we found that the cytosolic Mmi1 holoprotein re-localized to the nucleus even in cells heat-shocked at 40°C. Upon robust heat shock at 46°C, Mmi1 partly co-localized with the proteasome marker Rpn1 in the nuclear region as well as with the cytoplasmic stress granules defined by Rpg1 (eIF3a). We co-localized Mmi1 also with Bre5, Ubp3 and Cdc48 which are involved in the protein de-ubiquitination machinery, protecting protein substrates from proteasomal degradation. A comparison of proteolytic activities of wild type and mmi1Δ cells revealed that Mmi1 appears to be an inhibitor of the proteasome. We conclude that one of the physiological functions of the multifunctional protein module, Mmi1, is likely in regulating degradation and/or protection of proteins thereby indirectly regulating the pathways leading to cell death in stressed cells.