Miracle-dz/UniFAR-FTUs huggingface dataset:
A Review-Detection & alleviation of Clone Attacks in Wireless Sensor Networks

Wireless Sensor Networks (WSNs) offer an excellent opportunity to monitor environments, and have a lot of interesting applications, some of which are quite sensitive in nature and require full proof secured environment. The security mechanisms used for wired networks cannot be directly used in sensor networks as there is no user-controlling of each individual node, wireless environment, and more importantly, scarce energy resources. In this research, we consider a typical threat known as clone node attack, where an adversary creates its own low-cost sensor nodes called clone nodes and misinforms the network to acknowledge them as legitimate nodes. To instigate this attack, an adversary only needs to physically capture one node, and after collecting all secret credentials, an adversary clones the sensor node and deploys one or more clones of the compromised node into the network at strategic positions, damaging the whole network by carrying out many internal attacks. Detecting the node clone attack has become an imperative research topic in sensor network security, and designing detection schemes against node clone attack involves different threatening issues and challenges. In this review, we have classified the existing detection schemes and comprehensively explore various suggestions in each category as to demonstrate limitations of the existent detections as well as effective contributions.
Accuracy of inverse solution computation of dominant frequencies and phases during atrial fibrillation

Ablation of sources identified by dominant frequency (DF) or phase analyses in patients with atrial fibrillation (AF) is proposed as a therapy to terminate the arrhythmia. The aim of this study was to evaluate noninvasive identification of AF sources by solving the inverse problem. Realistic mathematical models of atria and torso anatomy with different DF patterns of AF were used. For these models inverse-computed electrograms EGMs were compared to intracardiac EGMs in terms of their voltage, phase and frequency spectrum errors. In models without added noise, atrial spectrums were estimated with lower relative errors than phases (3.8±3.8 vs 41±17 % respectively, p<;0.01) and after noise addition differences between relative errors of spectrums and phases were more pronounced (5.5±4.1 vs 48±14 %, respectively p<;0.01). Non-invasive location of the highest DF during AF showed a better accuracy than in the phase and voltage domain, being a promising clinical tool for identification of sources prior to ablation.
Advanced ICT platform for real-time monitoring and infrastructure efficiency at the city level

In recent years, the European Union (EU) has developed a shared European vision of sustainable urban development. Towards this direction, holistic solutions and advanced energy management services are necessary, addressed to any local authority that has as purpose to implement sustainable energy action plans. In this context, the aim of this paper is to present an advanced Information and Communication Technologies (ICT) platform for real-time monitoring and infrastructure efficiency at the city level, namely a Web Portal addressed to city authorities. The Web Portal will enable the city administration to collect data for energy management, real-time monitoring and billing purposes from city's infrastructure, sensors, meters and other energy sources and react to critical incidents or systems failure in an urban (city) environment. All the collected data will be handled by the "green" tools of the ICT platform, focused on the city's municipal buildings, pillars/poles and electric vehicle stations.
Fundamental physical processes associated with bypass transition

The DNS (Direct Numerical Simulation) study of Wu & Moin (2009) clearly shows the formation of hairpins and other features observed in experiments but not clearly evident in DNS investigations by others. The results also show features clearly observed in bypass transition, such as the formation of streaks and their subsequent nonlinear breakdown. We are extending the approach and methodology of Wu & Moin and will apply it to more directly examine the underlying physical processes associated with bypass transition at smaller FST (Free Stream Turbulence) levels. In particular, we are interested in the role played by two–dimensional TS (Tollmien-Schlichting) waves as a result of nonlinear interaction with FST. The basic approach is to reduce the rms amplitude level of the turbulent patch in the Wu & Moin simulation so that breakdown does not occur when the FST is acting alone. Two–dimensional TS waves are then introduced to observe the interactions with the FST. The inlet amplitude of the TS waves is tuned so that when they are acting alone, the wave amplitude remains small enough so that the behavior remains linear and there is no onset of any secondary instability within the domain. The FST and TS inlet conditions will then be combined and any breakdown that occurs can be attributed to nonlinear interactions. We are also considering the interaction of FST with steady streaks that occur in boundary layers as a result of the interaction of a non-uniform freestream with the leading edge of a flat plate.
MILP BASED VALUE BACKUPS IN POMDPS WITH VERY LARGE OR CONTINUOUS ACTION SPACES

Partially observed Markov decision processes (POMDPs) serve as powerful tools to model stochastic systems with partial state information. Since the exact solution methods for POMDPs are limited to problems with very small sizes of state, action and observation spaces, approximate pointbased solution methods like Perseus have gained popularity. In this work, a mixed integer linear program (MILP) is developed for calculation of exact value updates (in Perseus and similar algorithms), when the POMDP has very large or continuous action space. Since the solution time of the MILP is very sensitive to the size of the observation space, the concept of post-decision belief space is introduced to generate a more efficient and flexible model. An example is presented to illustrate the concepts and compare the results with those of the existing techniques.
Antidepressant efficacy of high-frequency transcranial magnetic stimulation over the left dorsolateral prefrontal cortex in double-blind sham-controlled designs: a meta-analysis

Background For more than a decade high-frequency repetitive transcranial magnetic stimulation (rTMS) has been applied to the left dorsolateral prefrontal cortex (DLPFC) in search of an alternative treatment for depression. The aim of this study was to provide an update on its clinical efficacy by performing a meta-analysis involving double-blind sham-controlled studies. Method A literature search was conducted in the databases PubMed and Web of Science in the period between January 1980 and November 2007 with the search terms ‘depression’ and ‘transcranial magnetic stimulation’. Thirty double-blind sham-controlled parallel studies with 1164 patients comparing the percentage change in depression scores from baseline to endpoint of active versus sham treatment were included. A random effects meta-analysis was performed to investigate the clinical efficacy of fast-frequency rTMS over the left DLPFC in depression. Results The test for heterogeneity was not significant (QT=30.46, p=0.39). A significant overall weighted mean effect size, d=0.39 [95% confidence interval (CI) 0.25–0.54], for active treatment was observed (z=6.52, p<0.0001). Medication resistance and intensity of rTMS did not play a role in the effect size. Conclusions These findings show that high-frequency rTMS over the left DLPFC is superior to sham in the treatment of depression. The effect size is robust and comparable to at least a subset of commercially available antidepressant drug agents. Current limitations and future prospects are discussed.
The effect of magnetic fields on the mass determination of clusters of galaxies

We test the effects of magnetic fields on the mass determination of galaxy clusters with the X-ray method. As this method takes into account only thermal pressure, additional non-thermal pressure support, e.g. caused by a magnetic field, can result in an underestimation of the mass. SPH models of galaxy clusters including magnetic fields of various strengths in two different cosmologies are used for the test. We compare the true mass of the model clusters with the mass determined from simulated X-ray images of the same models. The effect of the magnetic field on the mass in relaxed clusters is found to be negligible compared to other uncertainties, even at small radii, where the strongest effects are expected. However in one model, in which the cluster is in the process of merging, we find an effect of up to a factor of 2 caused by the magnetic field. In relaxed clusters the mass estimate, averaged over many models, is at most 15% smaller in models with relatively high magnetic field of 2G compared to models without a magnetic field with a small dependence on the cosmology chosen. Therefore we con- clude that the presence of a magnetic field cannot be responsible for the discrepancies of a factor of 2-3 found between X-ray and lensing mass in the central regions of relaxed clusters.
Extending an on-line information site with accurate domain-dependent extracts from the World Wide Web

This paper describes a new procedure that has been developed for extending an existing on-line information system about The Voyages of the Beagle with information collected automatically from Internet. A Term Identification procedure finds relevant terms in the document; and the algorithm uses conventional search engines (such as Google) to look for pages about those terms. Next, a sequence of filters rule out all the information considered irrelevant, and the remaining data is put together in “summary pages” available to the students. Our experiments so far have attained very good results, and in a form that was sent to several users of the on-line site they all showed much excitement about the tool.
New Techniques for Noninteractive Zero-Knowledge

Noninteractive zero-knowledge (NIZK) proof systems are fundamental primitives used in many cryptographic constructions, including public-key encryption secure against chosen ciphertext attack, digital signatures, and various other cryptographic protocols. We introduce new techniques for constructing NIZK proofs based on groups with a bilinear map. Compared to previous constructions of NIZK proofs, our techniques yield dramatic reduction in the length of the common reference string (proportional to security parameter) and the size of the proofs (proportional to security parameter times the circuit size). Our novel techniques allow us to answer several long-standing open questions in the theory of noninteractive proofs. We construct the first perfect NIZK argument system for all NP. We construct the first universally composable NIZK argument for all NP in the presence of an adaptive adversary. We construct a non-interactive zap for all NP, which is the first that is based on a standard cryptographic security assumption.
Rethinking education and poverty

Rethinking Education and Poverty is about the two-way relationship between poverty and education – in a nutshell, the book asks: how does poverty shape educational processes, experiences and outcomes and what role might education, and educational research, play in the alleviation of poverty? Billed on its back cover as ‘bringing together scholars from around the world’ and ‘international in scope’, in fact, apart from three chapters that are explicitly internationally oriented (Chapters 2, 11 and 12), the book primarily focuses on the relationship between poverty and education in the United States. This does not make the collection any less valuable or interesting to an international audience, however, because the United States represents a fascinating case study both of how educational inequalities have been reproduced and exacerbated in recent decades and what can be done to address them. These are issues with substantial relevance to those working in other national or transnational contexts where the influence of neoliberal economic and education policies is strongly felt. A great strength of this book is its eclecticism. In selecting which chapters to include, editor William Tierney appears to have gone for maximum diversity in terms both of the substantive focus of the chapters (encompassing school education, higher education and learning out of school) and the methodological, theoretical and ideological perspectives taken by the contributors. It is unusual to see such a diversity of issues and perspectives in one collection. Tierney describes the approach as orthogonal, with contributors invited to consider the poverty–education relationship from different intersecting angles with a view to producing ‘a fulsome portrait of what education might accomplish in the reduction of poverty’ (p. 8). There is no attempt to consolidate these perspectives into a coherent, integrated whole and indeed it would have been foolhardy to attempt to do so since, although the perspectives are in some cases complementary, in others they are either incommensurable or in apparent tension with one another. Therefore, whilst each chapter is informative and thought provoking in its own right, of equal interest is the fascinating juxtaposition of diverse perspectives which challenges the reader to think deeply about how best to understand the relationship between education and poverty.
Perspective methods of human identification: Ear biometrics

Geometrical methods of feature extraction from ear images in order to perform human identification are presented. Geometrical approach is motivated by the actual procedures used by police and forensic experts (so-called ear otoscopy). In their work, geometrical features of ears such as size, height, width, and shapes of earlobe are useful and valid proofs of identity. The contribution of the article is development of the new and original methods of geometrical feature extraction from 2D ear images. Four novel algorithms of ear feature extraction from contour images are described in detail. Moreover, identification results obtained for each of the methods, based on the distance of feature vectors in the feature space, are presented.
Learning hierarchical category structure in deep neural networks

Psychological experiments have revealed remarkable regularities in the developmental time course of cognition. Infants generally acquire broad categorical distinctions (i.e., plant/animal) before finer ones (i.e., bird/fish), and periods of little change are often punctuated by stage-like transitions. This pattern of progressive differentiation has also been seen in neural network models as they learn from exposure to training data. Our work explains why the networks exhibit these phenomena. We find solutions to the dynamics of error-correcting learning in linear three layer neural networks. These solutions link the statistics of the training set and the dynamics of learning in the network, and characterize formally how learning leads to the emergence of structured representations for arbitrary training environments. We then consider training a neural network on data generated by a hierarchically structured probabilistic generative process. Our results reveal that, for a broad class of such structures, the learning dynamics must exhibit progressive, coarse-to-fine differentiation with stage-like transitions punctuating longer dormant periods.
Analytic solutions to the problem of Coulomb and confining potentials

The oscillator representation method is presented and used to calculate the energy spectra for a superposition of Coulomb and power-law potentials and for Coulomb and Yukawa potentials. The method provides an efficient way to obtain analytic results for arbitrary values of the parameters specifying the above-type potentials. The calculated energies of the ground and excited states of the quantum systems in question are found to comply well with exact results.
Fast articulated motion tracking using a sums of Gaussians body model

We present an approach for modeling the human body by Sums of spatial Gaussians (SoG), allowing us to perform fast and high-quality markerless motion capture from multi-view video sequences. The SoG model is equipped with a color model to represent the shape and appearance of the human and can be reconstructed from a sparse set of images. Similar to the human body, we also represent the image domain as SoG that models color consistent image blobs. Based on the SoG models of the image and the human body, we introduce a novel continuous and differentiable model-to-image similarity measure that can be used to estimate the skeletal motion of a human at 5–15 frames per second even for many camera views. In our experiments, we show that our method, which does not rely on silhouettes or training data, offers an good balance between accuracy and computational cost.
Meiotic Chromosome Analysis of the Giant Water Bug, Lethocerus indicus

Abstract The giant water bug, Lethocerus indicus (Lepeletier and Serville) (Heteroptera: Belostomatidae), a native species of Southeast Asia, is one of the largest insects belonging to suborder Heteroptera. In this study, the meiotic chromosome of L. indicus was studied in insect samples collected from Thailand, Myanmar, Loas, and Cambodia. Testicular cells stained with lacto-acetic orcein, Giemsa, DAPI, and silver nitrate were analyzed. The results revealed that the chromosome complement of L. indicus was 2n = 22A + neo-XY + 2m, which differed from that of previous reports. Each individual male contained testicular cells with three univalent patterns. The frequency of cells containing neo-XY chromosome univalent (∼5%) was a bit higher than that of cells with autosomal univalents (∼3%). Some cells (∼0.5%) had both sex chromosome univalents and a pair of autosomal univalents. None of the m-chromosome univalents were observed during prophase I. In addition, this report presents clear evidence about the existence of m-chromosomes in Belostomatidae.
Evaluation of TRAP-sequencing technology with a versatile conditional mouse model

Gene expression profiling of various cell lineages has provided invaluable insights into the molecular mechanisms regulating cellular development and differentiation. However, in vivo molecular profiling of rare and interspersed cell populations, such as endothelial cells, has remained challenging. We have generated a versatile floxed translating ribosome affinity purification (TRAP) mouse model, mCherryTRAP, for Cre-dependent translational profiling of distinct cell lineages from intact tissues. To identify cell type–specific transcripts using TRAP, the data have to be filtered to remove both background transcripts not expressed in the profiled cell type and transcripts expressed in all cell populations of the tissue/organ. Filtering has previously been achieved using transcribed RNA from the tissue/organ. Using the mCherryTRAP model, we demonstrate extensive differential expression of RNAs between the translatome and transcriptome of embryonic brains and kidneys. We evaluate the implications of these data for TRAP studies of abundant and rare cell populations. Finally, we demonstrate the applicability of the technology to study organ-specific endothelial cell differentiation.
Function-Associated Antigen-1 Interaction of ICAM-1 and Leukocyte Affinity and Kinetic Analysis of the Molecular

LFA-1 is a member of the b 2 integrin family, and interacts with ICAM-1, a member of the Ig superfamily containing ﬁve Ig-like domains. Interaction of LFA-1 with ICAM-1 is important in a number of cellular events, including Ag-speciﬁc T cell activation and leukocyte transendothelial migration, which are known to be typically transient and highly regulated. In this study, we have used surface plasmon resonance technology to study the ICAM-1/LFA-1 interaction at the molecular level. A soluble form of LFA-1 (sLFA-1), normally expressed as two noncovalently associated membrane-bound subunits, has been produced, and its interaction with ICAM-1 has been examined. The kinetic analysis of a monomeric sLFA-1 binding to the ﬁrst two domains of ICAM-1 expressed as a chimeric IgG fusion protein (D1D2-IgG) revealed that sLFA-1 was bound to the D1D2-IgG chimera with a K d of 500 nM and dissociated with a k diss of 0.1 s 2 1 . Monomeric membrane-bound LFA-1 puriﬁed from plasma membranes showed a similar kinetic to sLFA-1. These results suggest that the monovalent interaction between ICAM-1 and LFA-1 has a primarily high afﬁnity and a slow dissociation rate constant as compared with other adhesion molecules, suggesting a potential mechanism for ﬁrm adhesion. The Journal of Immunology, 1998, 161: 4016–4022.
Anonymous Misbehavior Detection in Mobile Ad Hoc Networks

In this paper, we propose the first protocol that can achieve anonymous misbehavior detection in mobile ad hoc networks. On the one hand, our protocol can provide anonymity for the witness who reports observed misbehavior. Together with a distributed trust mechanism, our protocol can identify malicious or selfish users in an anonymous manner. On the other hand, the misuse of witness anonymity is prevented in such a way that any malicious user who broadcasts multiple claims against the same user for the same reason can be identified. An exemplary scenario is simulated to show the necessities of witness anonymity in mobile ad hoc networks and the effectiveness of our protocol in achieving such anonymity.
Mavenness: A Non-Explored Trait of Quality Salespeople

Over the past several years, Soles Managers have struggled to identify the right mix of traits and characteristics that would describe successful and good quality salespersons. Extant literature has proposed that salespeople that possess empathy, ego drive, integrity, high energy level, ability and propensity to learn, ability to build positive business relationships, have a high self-image of success, and are excellent communicators and listeners will tend to be more successful. This research introduces a new concept of mavenness, which has not been considered before by soles researchers and scholars. A maven is a person who possesses expertise in a given area, is passionate and willing to shore this expertise with his/ her followers. Maven salespeople will have expertise about their markets and products and will be very passionate about shoring their product expertise with their customers, thus creating long-term successful relationships. Thus it is incumbent of sales managers to assess the mavenness of potential salespeople before hiring them.
E-Tree: An Efficient Indexing Structure for Ensemble Models on Data Streams

Ensemble learning is a common tool for data stream classification, mainly because of its inherent advantages of handling large volumes of stream data and concept drifting. Previous studies, to date, have been primarily focused on building accurate ensemble models from stream data. However, a linear scan of a large number of base classifiers in the ensemble during prediction incurs significant costs in response time, preventing ensemble learning from being practical for many real-world time-critical data stream applications, such as Web traffic stream monitoring, spam detection, and intrusion detection. In these applications, data streams usually arrive at a speed of GB/second, and it is necessary to classify each stream record in a timely manner. To address this problem, we propose a novel Ensemble-tree (E-tree for short) indexing structure to organize all base classifiers in an ensemble for fast prediction. On one hand, E-trees treat ensembles as spatial databases and employ an R-tree like height-balanced structure to reduce the expected prediction time from linear to sub-linear complexity. On the other hand, E-trees can be automatically updated by continuously integrating new classifiers and discarding outdated ones, well adapting to new trends and patterns underneath data streams. Theoretical analysis and empirical studies on both synthetic and real-world data streams demonstrate the performance of our approach.