Miracle-dz/UniFAR-FTUs huggingface dataset:
Analyzing Performance Vulnerability due to Resource Denial›of›Service Attack on Chip Multiprocessors

Due to the ever-increasing design complexity and physical constraint in frequency scaling, chip multiprocessors are considered the de facto architecture baseline for future processor generation. Through resource sharing, applications running on a CMP can achieve better resource utilization and faster inter-core communication, leading to a higher overall throughput for the entire system. From a different perspective, however, such architectures are also more susceptible to Denial-of-Service (DoS) attacks on these shared resources, increasing the vulnerability in performance. Furthermore, as the number of cores increases, attacks similar to Distributed Denial-of-Service (DDoS) attacks on the Internet can be employed to throttle these on-chip resources with the presence of multiple malicious applications. In this paper, we design several types of Denial-of-Service attacks and analyze their impact to the performance of CMPs. We also suggest a few potential countermeasure techniques to address these vulnerability for legitimate applications.
DFIG wind turbines operating in a fixed reference frame

HVDC connected offshore wind farms represent a weak grid that causes stability issues in voltage oriented controlled converters. In addition the conventional line side converter control is not applicable for island grids without an existing AC-voltage source. A Fixed Reference Frame (FixReF) control proved already beneficial in full scale converter wind turbines. In this paper, the usage of FixReF in wind energy plants with doubly fed induction generators is investigated.
Disclosure of intended use of sell-off proceeds and long-run performance

This study investigates the long-run return performance following sell-off announcements of UK companies that apply the proceeds either for debt reduction or investment. Consistent with existing literature, we find that debt reduction sellers enjoy higher announcement time market reactions. In contrast, the subsequent longrun return performance is negative for the debt reduction sellers and positive for their investment counterparts. This disparity in shareholder wealth implies the market misjudges the priced information conveyed by the sell-off announcements. We find greater financial distress among the debt reduction sellers, indicating that their poorer fundamentals could have contributed to the value decline. JEL classification: G34
Green Synthesis and Characterization of Silver/Chitosan/Polyethylene Glycol Nanocomposites without any Reducing Agent

This paper presents the green synthesis of silver nanoparticles (Ag NPs) in aqueous medium. This method was performed by reducing AgNO3 in different stirring times of reaction at a moderate temperature using green agents, chitosan (Cts) and polyethylene glycol (PEG). In this work, silver nitrate (AgNO3) was used as the silver precursor while Cts and PEG were used as the solid support and polymeric stabilizer. The properties of Ag/Cts/PEG nanocomposites (NCs) were studied under different stirring times of reaction. The developed Ag/Cts/PEG NCs were then characterized by the ultraviolet-visible (UV-Vis) spectroscopy, X-ray diffraction (XRD), transmission electron microscopy (TEM), scanning electron microscopy (SEM) and Fourier transform infrared (FTIR) spectroscopy.
Repeatability and randomness in heterogeneous freezing nucleation

This study is aimed at clarifying the relative importance of the specific character of the nuclei and of the duration of supercooling in heterogeneous freezing nucleation by immersed impurities. Laboratory experiments were carried out in which sets of water drops underwent multiple cycles of freezing and melting. The drops contained suspended particles of mixtures of materials; the resulting freezing temperatures ranged from ? 6°C to ? 24°C. Rank correlation coefficients between observed freezing temperatures of the drops in successive runs were >0.9 with very high statistical significance, and thus provide strong support for the modified singular model of heterogeneous immersion freezing nucleation. For given drops, changes in freezing temperatures between cycles were relatively small (<1°C) for the majority of the events. These frequent small fluctuations in freezing temperatures are interpreted as reflections of the random nature of embryo growth and are associated with a nucleation rate that is a function of a temperature difference from the characteristic temperatures of nuclei. About a sixth of the changes were larger, up to ±5°C, and exhibited some systematic patterns. These are thought to arise from alterations of the nuclei, some being permanent and some transitory. The results are used to suggest ways of describing ice initiation in cloud models that account for both the temperature and the time dependence of freezing nucleation.
Fuzzy Shape Analysis

Foreword The intention of this report is to list and analyze some of the published results related to different approaches of applying fuzzy set theory to fuzzy shape analysis. These results provide a good background for further development of fuzzy shape analysis methods, which is our main goal. It should be noted that only fuzzy shape analysis techniques are considered, and not other approaches to use fuzzy set theory in (crisp) shape analysis (like, e.g., fuzzy reasoning). Even the methods referring to grey-level images are studied only if their adjustment to fuzzy sets is straightforward, by simple normalization of grey levels to the interval [0, 1]. The focus is, thus, on the shapes obtained by segmentation techniques which assign to the image pixels application-dependent membership values to the fuzzy object (shape). The overall organization of the paper is as follows: At the beginning (Section 1) a brief introduction is given. It refers to the classification and evaluation of existing crisp shape analysis methods, as well as to the general approaches when introducing fuzziness into the binary concepts. Section 2 introduces some basic fuzzy shape definitions. In Sections 3 and 4, we report on a class of shape analysis methods which produce a numerical shape descriptor, such as extent, diameter, area, perimeter, shape signature, Fourier transform based motion descriptor, and moments. Sections 5 is related to shape descrip-tors which produce an image (non-numerical result) as an output; we report on convexity, symmetry, distance transform, medial axis transform, and mathematical morphology, in fuzzy settings. Section 6 contains some comments on the reported results. The reporting style balances between " easy to follow " and " get the information " concept; we would be very glad if both, rather than none, is achieved.
A novel one-way clustering based gene expression data biclustering method

Gene expression data biclustering is very important for the research on gene regulatory mechanisms. Especially biclustering has also been proved to be very useful to analyze data matrix other than gene expression data. Compared with the traditional clustering methods, bicluster detection is very different since the elements of one bicluster may be greatly distributed among the original data matrix. In this paper a novel one-way bicluster detection method is proposed. It makes use of the existing traditional clustering algorithms such as K-means as an intermediate tool to do data clustering. Based on the clustering results and a characteristic of bicluster, the biclusters are detected one by one. Furthermore an efficient submatrices and tables creation method is proposed to save the memory storage and accelerate the processing speed. At the end of the paper an experiment with the simulated data are presented.
Concentrations of besifloxacin, gatifloxacin, and moxifloxacin in human conjunctiva after topical ocular administration

Purpose To evaluate the pharmacokinetic properties of besifloxacin, gatifloxacin, and moxifloxacin in the conjunctival tissue of healthy volunteers after topical application. Methods One-hundred eight (108) subjects were randomly assigned to receive one drop of besifloxacin (0.6% suspension), gatifloxacin (0.3% solution), or moxifloxacin (0.5% solution) ophthalmic formulations in one eye prior to conjunctival biopsy. Conjunctival samples were taken from subjects at either 15 minutes, 30 minutes, 2 hours, 6 hours, 12 hours, or 24 hours after dosing. Results All three fluoroquinolones reached a peak mean concentration 15 minutes after dosing. The mean concentrations of besifloxacin, gatifloxacin, and moxifloxacin at 15 minutes were 2.30 ± 1.42 μg/g, 4.03 ± 3.84 μg/g, and 10.7 ± 5.89 μg/g, respectively. Concentrations decreased with each subsequent time point. At 24 hours after dosing, concentrations of besifloxacin were measurable in 4 of 6 subjects, compared with 3 of 6 subjects for gatifloxacin and 2 of 6 subjects for moxifloxacin. Besifloxacin had the greatest mean residence time (4.7 hours) in the conjunctival tissue. With regard to methicillin-resistant strains of Staphylococcus aureus and Staphylococcus epidermidis, besifloxacin had the greatest area-under-the-curve (AUC) to MIC90 ratio. Nine percent (9%) of study subjects (N = 7) experienced a transient reduction in visual acuity. Conclusion All three fluoroquinolones were well tolerated and reached levels in the conjunctiva above the MIC90s of methicillin-sensitive S. aureus and S. epidermidis for at least 2 hours.
Denoising network tomography estimations

In this paper, we apply the technique of sparse shrinkage coding (SCS) to denoise the network tomography model with errors. SCS is used in the field of image recognition for denoising of the image data and we are the first one to apply this technique for estimating error free link delays from erroneous link delay data. To make SCS properly adoptable in network tomography, we have made some changes in the SCS technique such as the use of Non Negative Matrix Factorization (NNMF) instead of ICA for the purpose of estimating sparsifying transformation. Our technique does not need the knowledge of the routing matrix which is assumed known in conventional tomography. The estimated error free link delays are compared with the original error free link delays based on the data obtained from a laboratory test bed. The simulation results reveal that denoising of the tomography data has been carried out successfully by applying SCS.
Measuring unmeasurable attributes of software quality using Pragmatic Quality Factor

Software quality is evolving beyond static measurement to a wider scope of quality definition. Previous studies have indicated the importance of human aspect in software quality. But the quality models have not included comprehensively this aspect together with the behavioural aspect of software quality. This research has proposed a Pragmatic Quality Factors (or PQF) as a software quality measurement and metrics that includes both aspects of quality. These aspects of quality are essential as to balance between technical and non-technical (human) facet. In addition, this model provides flexibility by giving priorities and weights to the quality attributes. The priority and weight are necessary to reflect business requirement in the real business environment. Therefore, it is more practical that suits with different users and purposes. It is implemented through collaborative perspective approach between users, developers and independent assessor. This model shows how the unmeasurable characteristics can be measured indirectly using measures and metrics approach. It has been tested involving assessment and certification exercises in real case studies in Malaysia.
A Framework for Transaction-Level Quality of Service for M-Commerce Applications

In the emerging wireless Internet environment involving m-commerce and other mobile applications, an increasing number of users are likely to adopt mobile transactions. These transactions may have very diverse requirements and some of them may require a significant amount of network resources and/or bounded delays. One of many unique characteristics of transactions involving a financial value is the criticality of its completion. The unique requirements of mobile transactions necessitate the introduction of new metrics for quality-of-service. So far, most of the quality-of-service research in wireless networks has focused on call or connection- level QoS. In this paper, we propose a framework to support QoS requirements of mobile transactions by resource allocation at the connection level, transaction level, and a combination of connection and transaction levels. To measure the QoS effectiveness of mobile transactions, two new metrics, transaction completion probability and transaction response time, are introduced. Simulation and analytical models are used for computing different metrics for transaction performance under varying network and traffic conditions. The results show that the balanced transaction and connection level resource allocation can improve the probability of transactions completion and resource utilization. This improvement is at the cost of slightly increased processing overload, which is dependent on both the group size and number of transactions during a connection.
A Direct Physical Interface for Navigation and Positioning of a Robotic Nursing Assistant

People often use direct physical contact to guide a person to a desired location (e.g., leading a child by the hand) or to adjust a person's posture for a task (e.g., a dance instructor working with a dancer). When a user is in close proximity to a robot, physical contact becomes a potentially valuable channel for communication. We define a direct physical interface (DPI) as an interface that enables a user to influence a robot's behavior by making contact with its body. We evaluated a DPI in a controlled laboratory setting with 18 nurses and compared its performance with that of a comparable gamepad interface. The DPI significantly outperformed the gamepad according to several objective and subjective measures. Nurses also tended to exert more force at the robot's end-effectors and command higher velocities when using the DPI to perform a navigation task compared with using the DPI to perform a positioning task. Based on user surveys, we identify various nursing tasks where robotic assistance may be useful and provide design recommendations specifically in the area of healthcare.
Path clustering using Dynamic Time Warping technique

In order to monitor the safety and security of an area, video surveillance system is deployed and implemented in the said area. Such video surveillance system usually relies on the detection of suspicious behavior that is captured by the surveillance camera. In this paper, we present a novel method for clustering similar trajectories in video surveillance system. The purpose of performing trajectories clustering is to build a path model which can be used to detect any suspicious activity in the monitored scene. Path models are learnt from the accumulation of trajectory data over long time periods, and can be used to augment the classification of subsequent track data. This approach does not employ the traditional way of constructing path model, yet it simplifies the computation in the process of clustering similar trajectories by calculating average path for each detected and matched trajectory. The results demonstrate the efficiency of the proposed approach in clustering the path for detecting deviant walking paths.
Overexpression in MCF-7 Breast Cancer Cells Involved in the Proliferative Effects of Thioredoxin B Transactivation Is Increased But Is Not κ Nuclear Factor

Thioredoxin (Trx) is a small redox-active protein that provides reducing equivalents for key cysteine residues of proteins through thiol-disulfide exchange, such as the transcription factor nuclear factor-kB (NF-kB). NF-kB activation has been associated previously with cell growth and the inhibition of apoptosis. We have shown in earlier studies that overexpression of Trx in MCF-7 cells increases anchorageindependent growth. In this study, the activation of NF-kB was examined as a mechanism through which Trx overexpression might promote anchorage-independent growth. Constitutive NFkB activity is elevated 4 –7-fold in Trx-overexpressing cells. NFkB activity was inhibited in these cells by expressing a dominant-negative mutant of the I kBa protein (I kBaM). Expression of IkBaM in Trx-overexpressing cells dramatically reduced the Trx-associated increase in NFkB activity but did not affect anchorage-dependent or -independent growth. The results suggest that increased growth in MCF-7 cells overexpressing Trx is not mediated by increased activation of the transcription factor, NF-kB. Additionally, activator protein-1 (AP-1), another transcription factor associated with growth, was increased up to 10-fold in Trxoverexpressing cells. Thus, AP-1 activation might contribute to the growth-promoting effect of Trx.
Probabilistic Darwin Machines for Object Detection

Since the apparition of the first object detection systems in the late 1960s, the complexity of faced scenarios has been continuously growing. From a small set of simple objects in a homogeneous background, where simple alignment strategies or the use of geometric primitives were enough to recognize them, to nowadays, where we are dealing with sets of thousands of complex objects in cluttered scenes, where more sophisticated methods to describe and recognize objects are necessary. In this paper, we present an approach to the object detection problem based on Probabilistic Darwin Machines (PDM), where one of the most used object detection systems has been redefined in order to allow the use large feature sets, which are able to better describe the objects. Two different PDM are used in combination with a large set of visual features in order to learn an object detection system for five different real world visual object classes.
A vehicle routing model based on large-scale radio frequency identification data

Abstract The rapid development of sensing, computing, and wireless communication techniques has given rise to an increasing number and increasing availability of high-resolution data that record real-time traffic information. In this study, radio frequency identification (RFID) data collected in Nanjing (a major city in southern China) were used to estimate dynamic travel demands and develop an RFID data-based vehicle routing model that simultaneously considers individual benefits and social good. The proposed vehicle routing model also used information regarding driver origins that contribute to major congestion; therefore, the routing model can be applied to a group of targeted vehicles only, providing more adaptive, efficient, and feasible routing strategies to mitigate traffic congestion.
Alien, a Highly Conserved Protein with Characteristics of a Corepressor for Members of the Nuclear Hormone Receptor Superfamily

ABSTRACT Some members of nuclear hormone receptors, such as the thyroid hormone receptor (TR), silence gene expression in the absence of the hormone. Corepressors, which bind to the receptor’s silencing domain, are involved in this repression. Hormone binding leads to dissociation of corepressors and binding of coactivators, which in turn mediate gene activation. Here, we describe the characteristics of Alien, a novel corepressor. Alien interacts with TR only in the absence of hormone. Addition of thyroid hormone leads to dissociation of Alien from the receptor, as shown by the yeast two-hybrid system, glutathioneS-transferase pull-down, and coimmunoprecipitation experiments. Reporter assays indicate that Alien increases receptor-mediated silencing and that it harbors an autonomous silencing function. Immune staining shows that Alien is localized in the cell nucleus. Alien is a highly conserved protein showing 90% identity between human and Drosophila. Drosophila Alien shows similar activities in that it interacts in a hormone-sensitive manner with TR and harbors an autonomous silencing function. Specific interaction of Alien is seen with Drosophila nuclear hormone receptors, such as the ecdysone receptor and Seven-up, the Drosophila homologue of COUP-TF1, but not with retinoic acid receptor, RXR/USP, DHR 3, DHR 38, DHR 78, or DHR 96. These properties, taken together, show that Alien has the characteristics of a corepressor. Thus, Alien represents a member of a novel class of corepressors specific for selected members of the nuclear hormone receptor superfamily.
SmartShuffle: Managing Online Virtual Machine Shuffle in Virtualized Data Centers

Virtual machine (VM) live migration provides spatial flexibility by rearranging VM placement (i.e., VM shuffle) in several scenarios, including server consolidation, power consumption saving, fault tolerance, QoS management and network congestion resolving. However, VM live migration would consume scarce bandwidth and even cause network congestion. Since the bandwidth used by VM migration is usually the same as the services running in the VM, migration traffic would dominate network path and affect other application traffic as the traffic of a VM migration is usually several GBs. It gets worse in VM shuffle where plenty of VMs are needed to be moved. In this paper, we explore the opportunity to manage online VM shuffle and minimize the impact to data center networks. An efficient online VM shuffle scheduling method named SmartShuffle is presented. SmartShuffle tries to minimize the VM shuffle duration by coordinating VM migration in a proper scheduling order. VMs benefiting others maximally are migrated preferentially. We employ the simulated annealing algorithm to search for a solution for SmartShuffle. Our evaluation shows that SmartShuffle decreases the shuffle duration dramatically.
Mealtime, Temporal, and Daily Variability of the Human Urinary and Plasma Metabolomes in a Tightly Controlled Environment

While metabolomics has tremendous potential for diagnostic biomarker and therapeutic target discovery, its utility may be diminished by the variability that occurs due to environmental exposures including diet and the influences of the human circadian rhythm. For successful translation of metabolomics findings into the clinical setting, it is necessary to exhaustively define the sources of metabolome variation. To address these issues and to measure the variability of urinary and plasma metabolomes throughout the day, we have undertaken a comprehensive inpatient study in which we have performed non-targeted metabolomics analysis of blood and urine in 26 volunteers (13 healthy subjects with no known disease and 13 healthy subjects with autosomal dominant polycystic kidney disease not taking medication). These individuals were evaluated in a clinical research facility on two separate occasions, over three days, while on a standardized, weight-based diet. Subjects provided pre- and post-prandial blood and urine samples at the same time of day, and all samples were analyzed by “fast lane” LC-MS-based global metabolomics. The largest source of variability in blood and urine metabolomes was attributable to technical issues such as sample preparation and analysis, and less variability was due to biological variables, meals, and time of day. Higher metabolome variability was observed after the morning as compared to the evening meal, yet day-to-day variability was minimal and urine metabolome variability was greater than that of blood. Thus we suggest that blood and urine are suitable biofluids for metabolomics studies, though nontargeted mass spectrometry alone may not offer sufficient precision to reveal subtle changes in the metabolome. Additional targeted analyses may be needed to support the data from nontargeted mass spectrometric analyses. In light of these findings, future metabolomics studies should consider these sources of variability to allow for appropriate metabolomics testing and reliable clinical translation of metabolomics data.