Miracle-dz/UniFAR-FTUs huggingface dataset:
A fuzzy-logic-based cluster head selection algorithm in VANETs

Due to vehicles high mobility, there have been many clustering-based MAC protocols proposed to control Vehicular Ad hoc Network topology more effectively. Cluster head (CH) selection and cluster formation is of paramount importance in a highly dynamic environment such as VANETs. In this paper, we propose a novel cluster head selection criteria where cluster heads are selected based on their relative speed and distance from vehicles within their neighborhood. The maintenance phase in the proposed algorithm is adaptable to drivers' behavior on the road and has a learning mechanism for predicting the future speed and position of all cluster members using fuzzy logic inference system. The simulation results show that the proposed algorithm has a high average cluster head lifetime and more stable cluster topology with less communication and coordination between cluster members compared to other schemes.
An early-time infrared and optical study of the Type Ia Supernova 1998bu in M96

We present first-season infrared (IR) and optical photometry and spectroscopy of the Type Ia Supernova 1998bu in M96. We also report optical polarimetry of this event. SN 1998bu is one of the closest type Ia supernovae of modern times, and the distance of its host galaxy is well determined. We find that SN 1998bu is both photometrically and spectroscopically normal. However, the extinction to this event is unusually high, with A(V) = 1.0 +/- 0.11. We find that SN 1998bu peaked at an intrinsic M-V = -19.37 +/- 0.23. Adopting a distance modulus of 30.25 (Tanvir et al.) and using Phillips et al.'s relations for the Hubble constant, we obtain H-0 = 70.4 +/- 4.3 km s(-1) Mpc(-1). Combination of our IR photometry with those of Jha et al. provides one of the most complete early-phase IR light curves for a SN Ia published so far. In particular, SN 1998bu is the first normal SN Ia for which good pre-t(Bmax) IR coverage has been obtained. It reveals that the J, H and K light curves peak about 5 days earlier than the flux in the B-band curve.
Adenovirus-mediated transfer of the thyroid sodium/iodide symporter gene into tumors for a targeted radiotherapy.

The Na+/I- symporter (NIS) present in the membranes of thyroid cells is responsible for the capacity of the thyroid to concentrate iodide. This allows treatment of thyroid cancers with 131I. We propose to enlarge this therapeutic strategy to nonthyroid tumors by using an adenoviral vector to deliver the NIS gene into the tumor cells. We constructed a recombinant adenovirus encoding the rat NIS gene under the control of the cytomegalovirus promoter (AdNIS). Infection of SiHa cells (human cervix tumor cells) with AdNIS resulted in perchlorate-sensitive 125I uptake by these cells to a level 125-225 times higher than that in noninfected cells. Similar results were obtained for other human tumor cell lines, including MCF7 and T-47D (mammary gland), DU 145 and PC-3 (prostate), A549 (lung), and HT-29 (colon), demonstrating that the AdNIS vector can function in tumor cells of various origins. In addition, AdNIS-infected tumor cells were selectively killed by exposure to 131I, as revealed by clonogenic assays. To assess the efficiency of this cancer gene therapy strategy in vivo, we injected the AdNIS vector in human tumors (SiHa or MCF7 cells) established s.c. in nude mice. Immunohistological analysis confirmed the expression of the NIS protein in the tumor. Three days after intratumoral injection, AdNIS-treated tumors could specifically accumulate 125I or 123I, as revealed by kinetics and imaging experiments. A quantitative analysis demonstrated that the uptake in AdNIS-injected tumors was 4-25 times higher than that in nontreated tumors. On average, 11% of the total amount of injected 125I could be recovered per gram of AdNIS-treated tumor tissue. Altogether, these data indicate that AdNIS is very efficient in triggering significant iodide uptake by a tumor, outlining the potential of this novel cancer gene therapy approach for a targeted radiotherapy.
Impact of node density on the performance of ad hoc routing protocols

An ad hoc network comprises of mobile computing devices that use wireless transmission for communication. It has no fixed infrastructure. The mobile devices also serve as routers. Ad hoc wireless networks can be deployed quickly anywhere and anytime as they eliminate the complexity of infrastructure setup. It finds applications in military communications, emergency operations, hybrid wireless network architectures and wireless mesh networks. A variety of routing protocols for ad hoc networks has been proposed in the past. The routing protocols are broadly classified into Proactive, Reactive and Hybrid protocols. This paper evaluates the performance of FSR (Proactive), AODV (Reactive) and ZRP (Hybrid) routing protocols using qualnet simulator.
The impact of deregulation and corporate structure on productive efficiency: The case of the U.S. electric utility industry, 1990–2004

In this study, we present empirical evidence on the productive efficiency of electric utilities in the United States over the period, 1990-2004. This is a period marked by major attempts to introduce competition in the industry with the expectation that it will lead firms to improve their productive efficiency and ultimately to lower consumer prices. The actual experience has been surprising, since electricity prices have either fallen little or even risen sharply in some states. Relying on recent advances in the estimation of productive efficiency, we find that firms in jurisdictions that adopted competitive mechanisms have lower productive efficiency compared to firms in jurisdictions where rate-of-return regulation was retained. Furthermore, we provide evidence that firms in states that adopted competition have experienced decreases in productive efficiency, while firms in states with traditional regulation saw increases in efficiency over time. Since the introduction of deregulation has brought greater discretion to managers, we also examine the impact of various organizational choices on productive efficiency. Interestingly, the separation of the generation function from other functions, a hallmark of the effort to deregulate the industry, is associated with an adverse impact on productive efficiency. These findings question the claim that competition necessarily fosters higher productive efficiency. Alternatively, true competition may have been circumvented.
CpG island hypermethylation of BRCA1 and loss of pRb as co-occurring events in basal/triple-negative breast cancer

Triple-negative breast cancer (TNBC) occurs in approximately 15% of all breast cancer patients, and the incidence of TNBC is greatly increased in BRCA1 mutation carriers. This study aimed to assess the impact of BRCA1 promoter methylation with respect to breast cancer subtypes in sporadic disease. Tissue microarrays (TMAs) were constructed representing tumors from 303 patients previously screened for BRCA1 germline mutations, of which a subset of 111 sporadic tumors had previously been analyzed with respect to BRCA1 methylation. Additionally, a set of eight tumors from BRCA1 mutation carriers were included on the TMAs. Expression analysis was performed on TMAs by immunohistochemistry (IHC) for BRCA1, pRb, p16, p53, PTEN, ER, PR, HER2, CK5/6, EGFR, MUC1 and Ki-67. Data on BRCA1 aberrations and IHC expression was examined with respect to breast cancer-specific survival. The results demonstrate that CpG island hypermethylation of BRCA1 significantly associates with the basal/triple-negative subtype. Low expression of pRb, and high/intense p16, were associated with BRCA1 promoter hypermethylation, and the same effects were seen in BRCA1 mutated tumors. The expression patterns of BRCA1, pRb, p16 and PTEN were highly correlated, and define a subgroup of TNBCs characterized by BRCA1 aberrations, high Ki-67 (≥40%) and favorable disease outcome. In conclusion, our findings demonstrate that epigenetic inactivation of the BRCA1 gene associates with RB/p16 dysfunction in promoting TNBCs. The clinical implications relate to the potential use of targeted treatment based on PARP inhibitors in sporadic TNBCs, wherein CpG island hypermethylation of BRCA1 represents a potential marker of therapeutic response.
Is a framework enough?: cross-device testing and debugging

Although numerous cross-device frameworks have been proposed in recent years, we know of only a few cross-device applications that have been implemented and many of these are prototypes to showcase the frameworks. Fewer still have been deployed and are accessible to the public. To go beyond prototyping, applications need to be carefully tested and bugs eliminated but current cross-device frameworks provide little support for this and it therefore remains a challenge. Tied to the lack of real-world applications, there is also a lack of cross-device developers who could be studied to gather requirements for better support. However, based on principles of responsive design, there are many tools available and widely used in practice to support the development of web applications that can be accessed from diverse devices, including ones to facilitate testing and debugging. Inspired by these tools, we have created XDTools -- a new integrated set of tools for testing and debugging cross-device applications. A preliminary qualitative evaluation with 12 developers produced promising results.
Multifunctional Gold-Mesoporous Silica Nanocomposites for Enhanced Two-Photon Imaging and Therapy of Cancer Cells

Three dimensional sub-micron resolution has made two-photon nanomedicine a very promising medical tool for cancer treatment since current techniques cause significant side effects for lack of spatial selectivity. Two-photon-excited (TPE) photodynamic therapy (PDT) has been achieved via mesoporous nanoscaffolds, but the efficiency of the treatment could still be improved. Herein, we demonstrate the enhancement of the treatment efficiency via gold-mesoporous organosilica nanocomposites for TPE-PDT in cancer cells when compared to mesoporous organosilica particles. We performed the first comparative study of the influence of the shape and spatial position of gold nanoparticles (AuNPs) with mesoporous silica nanoparticles (MSN) functionalized with thiol groups and doped with a two-photon electron donor (2PS). The resulting multifunctional nanocarriers displayed TPE-fluorescence and were imaged inside cells. Furthermore, mesoporous organosilica NPs decorated gold nanospheres (AuNSs) induced 63 percent of selective killing on MCF-7 breast cancer cells. This study thus provides insights for the design of more effective multifunctional two-photon-sensitive nanocomposites via AuNPs for biomedical applications.
Negotiating Privacy: The European Union, The United States, And Personal Data Protection

Data Privacy: Setting the International Standard. Why the Conflict? : Exploring Public Opinion and Business Concerns. Keeping Business Out of the Loop: Negotiating the European Data Protection Directive. Keeping Privacy Advocates Out of the Loop: Negotiating the Safe Harbor Agreement. The EU Standard Gains Critical Mass: International Responses. Implementing the Safe Harbor Agreement: How Well Does It Work? New Controversies Test the EU Privacy Standard. Implications for the Future. Appendixes: Comparing the European Data Protection Directive and the OECD Guidelines. Synopsis of U.S. Federal Privacy Legislation
Essential Role of MAPK Phosphatase-1 in the Negative Control of Innate Immune Responses

TLR-induced innate immunity and inflammation are mediated by signaling cascades leading to activation of the MAPK family of Ser/Thr protein kinases, including p38 MAPK, which controls cytokine release during innate and adoptive immune responses. Failure to terminate such inflammatory reactions may lead to detrimental systemic effects, including septic shock and autoimmunity. In this study, we provide genetic evidence of a critical and nonredundant role of MAPK phosphatase (MKP)-1 in the negative control of MAPK-regulated inflammatory reactions in vivo. MKP-1−/− mice are hyperresponsive to low-dose LPS-induced toxicity and exhibit significantly increased serum TNF-α, IL-6, IL-12, MCP-1, IFN-γ, and IL-10 levels after systemic administration of LPS. Furthermore, absence of MKP-1 increases systemic levels of proinflammatory cytokines and exacerbates disease development in a mouse model of rheumatoid arthritis. When activated through TLR2, TLR3, TLR4, TLR5, and TLR9, bone marrow-derived MKP-1−/− macrophages exhibit increased cytokine production and elevated expression of the differentiation markers B7.2 (CD86) and CD40. MKP-1-deficient macrophages also show enhanced constitutive and TLR-induced activation of p38 MAPK. Based on these findings, we propose that MKP-1 is an essential component of the intracellular homeostasis that controls the threshold and magnitude of p38 MAPK activation in macrophages, and inflammatory conditions accentuate the significance of this regulatory function.
Direct 3D metric reconstruction from two views using differential evolution

To obtain a 3D metric reconstruction from two images taken with a same camera without previous calibration, it is necessary to estimate the intrinsic camera parameters and the orientation and position of the two views with respect to the camera. At the present time, there are several algorithms to estimate camera parameters from two views, all of them are based on the epipolar geometry and the estimation of the fundamental matrix. However, it is well known there are some configurations where the fundamental matrix can not be estimated, called critical configurations. In this article we present a novel method to retrieve directly the camera parameters, and orientation and position parameters for two views, from points taken over the two images, using the differential evolution (DE) algorithm. This method exploits the reprojection error as the cost function for DE, instead of computing the fundamental matrix. Experimental results show our method recovers 3D points, intrinsic, and orientation and position parameters on non-critical configurations and in the critical configuration of pure translation. We used simulated and real images to prove its effectiveness and robustness.
MATCHED FILTER BASED SPECTRUM SENSING FOR COGNITIVE RADIO AT LOW SIGNAL TO NOISE RATIO

Custom usage of a Cognitive Radio is administrated by the essential utilization aspect of the radio spectrum the natural resource. Cognitive radio trying to resourcefully share the radio spectrum along with potential primary users in the spectrum that must be identified in order to evade causing harmful interference with other users on the spectrum. The vibrant usage of spectrum belongs to the white space assessment and how accurately it can be utilized. In this paper we put forward an open situation of channel estimation at low signal to noise ratio. A Matched Filter based system is well-thought-out to make the spectrum sensing resolution based on the observed signal to noise ratio from the Cognitive Users. With the existing knowledge of the regulated system parameters, the fusion Centre can make a global sensing decision consistently without any additional requirements such as channel state information, prior information and prior prospects about the primary user's signal. Numerical results in terms of receiver operating characteristics show that the sensing performance of the proposed Matched filter based system outperforms the performance of the adaptive Takagi and Sugeno’s fuzzy energy based system model at low Signal to Noise Ratio and one order Cyclostationary detection based on estimated signal to noise ratio.
Governance–Performance Relationship: A Re‐Examination Using Technical Efficiency Measures

The objective of this study is to analyse further the governance–performance relationship while improving on two methodological issues: control for endogeneity and firm performance measurement. To mitigate the endogeneity problem, we first focus on subsamples of firms for which we ex ante expect better corporate governance to cause better performance. Second, we use generalized least squares regressions for panel data. To control for potential measurement bias, we measure firm performance using data envelopment analysis (DEA). The research is conducted in Canada over a five-year period from 2001 to 2005. Corporate governance is measured based on the Report on Business corporate governance index published by the Globe and Mail. Overall, the results show that better governed firms are more efficient. This study is in line with a growing number of recent studies that propose alternative measures of firm performance. By using DEA, this study brings together the corporate finance and productivity literature.
Studying Hepatitis C Virus: Making the Best of a Bad Virus

An estimated 3% of the world population is infected with hepatitis C virus (HCV) ([5][1], [232][2]). In most infected individuals, this remarkable RNA virus evades the immune system and establishes a chronic infection that can lead to cirrhosis, liver cancer, and death. While advances have been made
Face Detection using Neural Network & Gabor Wavelet Transform

This paper is based on classifications of the features of a face detected using Gabor filter feature extraction techniques in image processing. The feature vector based on Gabor filters used as the input of the classifier, which is a Feed Forward Neural Network (FFNN) on a reduced feature subspace learned by an approach simpler than Principal Component Analysis (PCA). The effectiveness of the proposed method is demonstrated by the experimental results on testing large number of images and comparisons with state of the art method. Face detection and recognition has many applications in a variety of fields such as security systems, video conferencing and identification. Human face detection and recognition is an active area of research spanning several disciplines such as image processing, pattern recognition and computer vision. Face detection and recognition are preliminary steps to a wide range of applications such as personal identity verification, video-surveillance, lip tracking, facial expression extraction, gender classification, advanced human and computer interaction. Most methods are based on neural network approaches, feature extraction, Markov chain, skin color, and others are based on template matching (1). Pattern localization and classification is the step, which is used to classify face and non- face patterns. Many systems dealing with object classification are based on skin color. In this paper we are interested by the design of an ANN algorithm in order to achieve image classification. This paper is organized as follows: In section II, we give an overview over classification for face detection. Description of our model is discussed in Section III. Section Ideals with the training method.
Neglected Risks in Mutual Fund Performance Measurement: An Additional Cost to Stock-Picking

This paper takes a closer look at utility based performance measurement proposed by Goetzmann et al. (2007) and used in popular Morningstar star ratings. Utility based per- formance measures offer a very intuitive way of risk correction and are hard to manipulate. They require, however, a proper benchmark measure to filter out lucky funds. I propose to use the Daniel et al. (1997) (DGTW) characteristic based benchmark portfolios as bench- marks for the utility based performance measure. I find that the DGTW selection measure consistently overestimates the manager’s selection skills in certainty equivalent terms, and that this overestimation can be decomposed into an idiosyncratic and a systematic compo- nent. In diversified fund portfolios, the certainty equivalent selection measure is, on average, 87bps higher than in undiversified fund portfolios. The remaining undiversifiable risks cost 47bps per year in certainty equivalent terms and can be explained in part be imprecise correction for known systematic risk factors, in part by unknown but undiversifiable risk factors. The certainty equivalent measure captures risk particularly well in years with high moment realizations of the CRSP value weighted index.
Managing Knowledge for Product-Service System Innovation: The Role of Web 2.0 Technologies

OVERVIEW: In the emerging service economy, many traditional product manufacturing companies are seeking innovative ways to do business, focusing on product-service combinations. Development of these offerings requires the integration of a wider span of expertise from several companies, which poses new challenges in the way knowledge is captured and managed. On the basis of a case study from an aerospace supply chain, this paper first identifies the limitations of current knowledge-management systems in such a setting and then discusses the role of Web 2.0 technologies in managing knowledge across the knowledge life cycle. Web 2.0 technologies have potential to lower barriers to leveraging informal and unstructured knowledge, contextualized information, networks of connections, and collective creation and maintenance of knowledge assets, which could complement current knowledge-management systems in multicompany product development efforts.
Annals of the New York Academy of Sciences Perception, Action, and Word Meanings in the Human Brain: the Case from Action Verbs

Among other things, humans talk about what they perceive and do, like " glowing, " " hopping, " and " squeaking. " What is the relationship between our sensory-motor experiences and word meanings? Does understanding action-verbs rely on the same neural circuits as seeing and acting? The available evidence indicates that sensory-motor experience and word meanings are represented in distinct, but interacting systems. Understanding action-verbs does not rely on early modality-specific visual or motor circuits. Instead, word comprehension relies on a network of amodal brain regions in the left frontal, temporal, and parietal cortices that represent conceptual and grammatical properties of words. Interactions between word meanings and sensory-motor experiences occur in higher-order polymodal brain regions.
Application of independent component analysis in denoising of steel structural vibration signal in frequency domain

In structural vibration signals, some kind of convolution takes places imultaneously with the linear mixing. In order to reduce noise and obtain the useful signals, the paper firstly transforms time signals into frequency signals through FFT, then applies FastICA to separate the useful signals from signals mixed by noise, transforms frequency signals into time signals through IFFT, finally accomplishes the separating of the useful signals and noise. This method is proved effective by denoising the steel structural vibration signals in lab.