Miracle-dz/UniFAR-FTUs huggingface dataset:
SEP: A Stable Election Protocol for clustered heterogeneous wireless sensor networks

We study the impact of heterogeneity of nodes, in terms of their energy, in wireless sensor networks that are hierarchically clustered. In these networks some of the nodes become cluster heads, aggregate the data of their cluster members and transmit it to the sink. We assume that a percentage of the population of sensor nodes is equipped with additional energy resources—this is a source of heterogeneity which may result from the initial setting or as the operation of the network evolves. We also assume that the sensors are randomly (uniformly) distributed and are not mobile, the coordinates of the sink and the dimensions of the sensor field are known. We show that the behavior of such sensor networks becomes very unstable once the first node dies, especially in the presence of node heterogeneity. Classical clustering protocols assume that all the nodes are equipped with the same amount of energy and as a result, they can not take full advantage of the presence of node heterogeneity. We propose SEP, a heterogeneous-aware protocol to prolong the time interval before the death of the first node (we refer to as stability period), which is crucial for many applications where the feedback from the sensor network must be reliable. SEP is based on weighted election probabilities of each node to become cluster head according to the remaining energy in each node. We show by simulation that SEP always prolongs the stability period compared to (and that the average throughput is greater than) the one obtained using current clustering protocols. We conclude by studying the sensitivity of our SEP protocol to heterogeneity parameters capturing energy imbalance in the network. We found that SEP yields longer stability region for higher values of extra energy brought by more powerful nodes.
Transmit Power Control for Secondary Use in Environments with Correlated Shadowing

In this paper we propose a general model to estimate the maximum allowed transmit power of a secondary node based on the measured signal from the primary transmitter that is willing to share its downlink spectrum. The transmit power should satisfy primary constraints related to the minimum required Signal to Interference and Noise Ratio (SINR) of its users. The model can be used by secondary nodes whether or not they have full knowledge about the correlation between the different path losses. Simulation results have shown the high impact of the level of correlation on the performance of both primary and secondary users.
A Wireless Optogenetic Headstage with Multichannel Electrophysiological Recording Capability

We present a small and lightweight fully wireless optogenetic headstage capable of optical neural stimulation and electrophysiological recording. The headstage is suitable for conducting experiments with small transgenic rodents, and features two implantable fiber-coupled light-emitting diode (LED) and two electrophysiological recording channels. This system is powered by a small lithium-ion battery and is entirely built using low-cost commercial off-the-shelf components for better flexibility, reduced development time and lower cost. Light stimulation uses customizable stimulation patterns of varying frequency and duty cycle. The optical power that is sourced from the LED is delivered to target light-sensitive neurons using implantable optical fibers, which provide a measured optical power density of 70 mW/mm2 at the tip. The headstage is using a novel foldable rigid-flex printed circuit board design, which results into a lightweight and compact device. Recording experiments performed in the cerebral cortex of transgenic ChR2 mice under anesthetized conditions show that the proposed headstage can trigger neuronal activity using optical stimulation, while recording microvolt amplitude electrophysiological signals.
A fault-tolerant transactional agent model on distributed object systems

A transactional agent is a mobile agent to manipulate objects distributed on computers with some commitment condition like atomic commitment. Computers may stop by fault. In the client-server model, servers can be fault-tolerant according to replication and checkpointing technologies. However, an application program cannot be performed if a client computer is faulty. A transactional agent can move to another operational computer if some destination computer to which the agent to move is faulty. In this paper, we discuss how a program reliably manipulating objects can be realized in a mobile agent in presence of computer faults.
Transforming Growth Factor Beta 3 Is Required for Excisional Wound Repair In Vivo

Wound healing is a complex process that relies on proper levels of cytokines and growth factors to successfully repair the tissue. Of particular interest are the members of the transforming growth factor family. There are three TGF-ß isoforms–TGF- ß 1, 2, and 3, each isoform showing a unique expression pattern, suggesting that they each play a distinct function during development and repair. Previous studies reported an exclusive role for TGF-ß 3 in orofacial development and a potent anti-scarring effect. However, the role of TGF- ß 3 in excisional wound healing and keratinocyte migration remains poorly understood. We tested the effect of TGF-ß 3 levels on excisional cutaneous wounds in the adult mouse by directly injecting recombinant TGF-ß 3 or neutralizing antibody against TGF-ß 3 (NAB) in the wounds. Our results demonstrate that TGF-ß 3 does not promote epithelialization. However, TGF-ß 3 is necessary for wound closure as wounds injected with neutralizing antibody against TGF-ß 3 showed increased epidermal volume and proliferation in conjunction with a delay in keratinocyte migration. Wild type keratinocytes treated with NAB and Tgfb3-deficient keratinocytes closed an in vitro scratch wound with no delay, suggesting that our in vivo observations likely result from a paracrine effect.
Design and implementation of efficient intelligent robotic gripper

The gripper is one critical component of an industrial robot which is often useful in industrial environments for object grasping during handling process. In this paper, a gripper is designed and implemented to grasp unknown objects with different masses, dimensions, and coefficients of friction considering simplicity, wide range of objects and economy. The proposed grasping process during object lifting and handling is mainly based on the slip reflex principle, as applying insufficient force leads to object slipping, and dropping may occur. In the mean time, applying extra force during grasping may lead to object crushing. A new system controller scheme using fuzzy logic based on empirical investigation of the human hand skills is proposed to control the applied force on the object to avoid the risk of object crushing or dropping. Adaptive neuro-fuzzy inference system ANFIS is used to model the assigned robotic gripper based on input/output variables measurement. Reducing the distance of the slippage and process time can be achieved owing to the proposed robotic gripper as shown in experimental results.
Super-resolution reconstruction for Kinect 3D data

In this study, a super-resolution (SR) reconstruction approach for Kinect 3D data is proposed. The proposed approach contains four steps: (1) extract the edge maps from the low-resolution (LR) depth map and the high-resolution (HR) color image using Canny edge detector, subsample the edge map of the HR color image, and segment the HR color image using mean shift segmentation, (2) detect and fill depth holes in the LR depth map, (3) upsample the LR depth map and reduce edge artifacts using local edge enhancement, and (4) perform HR depth map determination by energy cost minimization and refine the final HR depth map by joint bilateral filtering. Based on the experimental results obtained in this study, the performance of the proposed approach is better than those of four comparison approaches.
Mining hidden connections among biomedical concepts from disjoint biomedical literature sets through semantic‐based association rule

The novel connection between Raynaud disease and fish oils was uncovered from two disjointed biomedical literature sets by Swanson in 1986. Since then, there have been many approaches to uncover novel connections by mining the biomedical literature. One of the popular approaches is to adapt the association rule (AR) method to automatically identify implicit novel connections between concept A and concept C from two disjointed sets of documents through intermediate B concept. Since A and C concepts do not occur together in the same data set, the mining goal is to find novel connection among A and C concepts in the disjoint data sets. It first applies association rule to the two disjointed biomedical literature sets separately to generate two rule sets (A→B, B→C), and then applies transitive law to get the novel connections A→C. However, this approach generates a huge number of possible connections among the millions of biomedical concepts and a lot of these hypothetical connections are spurious, useless, and/or biologically meaningless. Thus it is essential to develop new approach to generate highly likely novel and biologically relevant connections among the biomedical concepts. This paper presents a biomedical semantic‐based association rule system (Bio‐SARS) that significantly reduce spurious/useless/biologically irrelevant connections through semantic filtering. Compared to other approaches such as latent semantic indexing and traditional association rule‐based approach, our approach generates much fewer rules and a lot of these rules represent relevant connections among biological concepts. © 2009 Wiley Periodicals, Inc.
MULTI-LINGUAL FINGERSPELLING RECOGNITION IN A KIOSK FOR THE HANDICAPPED

This paper presents the design and evaluation of a multi-lingual fingerspelling recognition module that is designed for an information terminal. Through the use of multimodal input and output methods, the information terminal acts as a communication medium between deaf and blind people. The system converts fingerspelled words to speech and vice versa using fingerspelling recognition, fingerspelling synthesis, speech recognition and speech synthesis in Czech, Russian and Turkish Languages. We describe an adaptive skin color based fingersign recognition system with a close to real-time performance and present recognition results on 88 different letters signed by five different signers, using more than four hours of training and test videos.
Sound Waves Effectively Assist Tobramycin in Elimination of Pseudomonas aeruginosa Biofilms In vitro

Microbial biofilms are highly refractory to antimicrobials. The aim of this study was to investigate the use of low-frequency vibration therapy (20–20 kHz) on antibiotic-mediated Pseudomonas aeruginosa biofilm eradication. In screening studies, low-frequency vibrations were applied on model biofilm compositions to identify conditions in which surface standing waves were observed. Alginate surface tension and viscosity were also measured. The effect of vibration on P. aeruginosa biofilms was studied using a standard biofilm assay. Subminimal inhibitory concentrations (sub-MIC) of tobramycin (5 μg/ml) were added to biofilms 3 h prior, during, and immediately after vibration and quantitatively assessed by (2,3-bis-(2-methoxy-4-nitro-5-sulfophenyl)-2H-tetrazolium-5-carboxanilide) reduction assay (XTT) and, qualitatively, by confocal laser scanning microscopy (CLSM). The standing waves occurred at frequencies <1,000 Hz. Biofilms vibrated without sub-MIC tobramycin showed a significantly reduced metabolism compared to untreated controls (p < 0.05). Biofilms treated with tobramycin and vibrated simultaneously (450, 530, 610, and 650 Hz), or vibrated (450 and 650 Hz) then treated with tobramycin subsequently, or vibrated (610Hz, 650Hz) after 3 h of tobramycin treatment showed significantly lower metabolism compared to P. aeruginosa biofilm treated with tobramycin alone (p < 0.05). CLSM imaging further confirmed these findings. Low frequency vibrations assisted tobramycin in killing P. aeruginosa biofilms at sub-MIC. Thus, sound waves together with antibiotics are a promising approach in eliminating pathogenic biofilms.
Cannabis Use and Social Anxiety in Adolescence: The Role of Facilitation Expectancies

Cannabis use is frequently related to social anxiety in young adulthood, but the nature of this relationship is unclear. Moreover, much research has been conducted on the role of cannabis effects expectancies and their relationship to social anxiety among young adults, but less is known about adolescence. The study examined the relationship between social anxiety, cannabis use patterns, and cannabis effects expectancies among a nonclinical sample of 1,305 adolescents (51% female). Non-users reported higher social anxiety scores than non-problematic and risky users. Compared to users, non-users had more negative expectancies. Risky and problematic users showed higher social and sexual facilitation expectancies and perceptual and cognitive enhancement expectancies. In addition, social anxiety was related to global negative expectancies and social and sexual facilitation expectancies. Moreover, we found that among socially anxious adolescents, social and sexual facilitation expectancies are dissuasive reasons to use cannabis. Clinical implications and future directions are discussed.
Graph-based web video search reranking through consistency analysis using spectral clustering

This paper proposes a graph-based Web video search reranking method through consistency analysis using spectral clustering. Graph-based reranking is effective for refining text-based video search results. Generally, this approach constructs a graph where the vertices are videos and the edges reflect their pairwise similarities. A lot of reranking methods are built based on a scheme which regularizes the smoothness of pairwise ranking scores between adjacent nodes. However, since the overall consistency is measured by aggregating the individual consistency over each pair, errors in score estimation increase when noisy samples are included within their neighbors. To deal with the noisy samples, different from the conventional methods, the proposed method models the global consistency of the graph structure. Specifically, in order to detect this consistency, the propose method introduces a spectral clustering algorithm which can detect video groups, whose videos have strong semantic correlation, on the graph. Furthermore, a new regularization term, which smooths ranking scores within the same group, is introduced to the reranking framework. Since score regularization is performed by both local and global aspect simultaneously, the accurate score estimation becomes feasible. Experimental results obtained by applying the proposed method to a real-world video collection show its effectiveness.
Robust Model-Free Tracking of Non-Rigid Shape

We present a robust algorithm for estimating non-rigid motion in video sequences. We build on recent methods for tracking video by enforcing global structure (such as rank constraints) on the tracking. These methods assume color constancy in the neighborhood of each tracked feature, an assumption that is violated by occlusions, deformations, lighting changes, and other effects. Our method identifies outliers while solving for flow. This allows us to obtain high-quality tracking from difficult sequences, even when there is no single “reference frame” in which all tracks are visible.
Translation of Rhetorical Figures in the Advertising Discourse: A Case Study

Rhetorical figures, which are frequently applied in advertisements, can add literary flavor to the texts, gratify audiences’ aesthetic needs, and deepen their impression. In advertisement translation, it is very common that the rhetorical figures applied in the original text are replaced with new ones in the translation. This research focuses on rhetorical figures’ function of enhancing audiences’ memory and discusses the realization of this function in translation. The psychological studies on human needs are referred to in the analyses, especially aesthetic needs, for the use of rhetorical figures provides audiences with aesthetic pleasure and gratifying their aesthetic needs involves their emotion and enhances their memorization. To have aesthetic needs is universal across cultures; however, the ways to satisfy such needs may vary due to linguistic and cultural differences. The flexible treatment of rhetorical figures in advertisement translation mirrors such differences in terms of needs gratification, and investigation in this regard can reveal the linguistic and cultural nuances and provide translators with practical guidance.
RNA interference blocks gene expression and RNA synthesis from hepatitis C replicons propagated in human liver cells

RNA interference represents an exciting new technology that could have therapeutic applications for the treatment of viral infections. Hepatitis C virus (HCV) is a major cause of chronic liver disease and affects >270 million individuals worldwide. The HCV genome is a single-stranded RNA that functions as both a messenger RNA and replication template, making it an attractive target for the study of RNA interference. Double-stranded small interfering RNA (siRNA) molecules designed to target the HCV genome were introduced through electroporation into a human hepatoma cell line (Huh-7) that contained an HCV subgenomic replicon. Two siRNAs dramatically reduced virus-specific protein expression and RNA synthesis to levels that were 90% less than those seen in cells treated with negative control siRNAs. These same siRNAs protected naive Huh-7 cells from challenge with HCV replicon RNA. Treatment of cells with synthetic siRNA was effective >72 h, but the duration of RNA interference could be extended beyond 3 weeks through stable expression of complementary strands of the interfering RNA by using a bicistronic expression vector. These results suggest that a gene-therapeutic approach with siRNA could ultimately be used to treat HCV.
State of art in the field of Search-based Mutation Testing

Search-based Mutation Testing makes use of Meta-heuristic optimization techniques like Genetic Algorithm, Hill Climbing and other such Evolutionary Approaches for the process of mutation testing. This paper presents the opportunities and challenges faced in applying Search-based techniques to mutation testing. Enormous amount of research has been done in the recent years in this area. The major challenge is the storage and computational cost for a large set of mutants. This paper also lists the latest research, available tools and updates to SBMT.
The Counterintuitive Relationship between Conceptual and Perceptual Similarities and Eyewitness Suggestibility

Summary The tendency to confuse witnessed and suggested information can result in inaccurate eyewitness testimonies and convictions of innocent people. Studies that tested how similarities between witnessed and suggested information affect the tendency to confuse them reached inconsistent results. Here, we claim that there is a more complex and not necessarily linear relationship between similarity and memory distortions. Participants (164) viewed two subsequent stories, which varied in the conceptual and perceptual similarities between them. We found a significant interaction between conceptual and perceptual similarities. When we presented two conceptually different stories, perceptual similarity increased the suggestibility effect compared with perceptual dissimilarity. Conversely, when we presented two conceptually similar stories, perceptual similarity decreased suggestibility compared with perceptual dissimilarity. Accordingly, we suggest that similarity between two events may increase the suggestibility effect. However, counter-intuitively, once similarity reaches a certain threshold, the coherence level between the events reduces the tendency to confuse them. Copyright © 2014 John Wiley & Sons, Ltd.
Unsupervised Semantic Similarity Computation using Web Search Engines

In this paper, we propose two novel web-based metrics for semantic similarity computation between words. Both metrics use a web search engine in order to exploit the retrieved information for the words of interest. The first metric considers only the page counts returned by a search engine, based on the work of [1]. The second downloads a number of the top ranked documents and applies "widecontext" and "narrow-context" metrics. The proposed metrics work automatically, without consulting any human annotated knowledge resource. The metrics are compared with WordNet-based methods. The metrics' performance is evaluated in terms of correlation with respect to the pairs of the commonly used Charles - Miller dataset. The proposed "wide-context" metric achieves 71% correlation, which is the highest score achieved among the fully unsupervised metrics in the literature up to date.
(Not) a stadium of four million: speaking back to dominant discourses of the Rugby World Cup in New Zealand

New Zealand won the rights to host the 2011 Rugby World Cup (RWC) on the back of a slogan – A stadium of 4 million – that implied almost that the entire country would support the event. What transpired was a media frenzy of coverage that discursively supported the ‘truth’ of the slogan. In this article, I interrogate public responses to the Cup, taking a bottom-up approach that focuses on those whose voices and experiences were silenced in the public discourse. The results indicate not only the power of media coverage to influence individuals' perceptions of how others feel but its marginalizing nature for those views that are not represented. One consequence of the 2011 RWC coverage was that New Zealanders who were disinterested in, or actively resistant to, the Cup found themselves alienated from the dominant discourse and without a public space to speak their truths. Ultimately, despite some private contestation of the media's ‘truth claims’, the lack of public challenge left the articulation of rugby and nationalism not only intact but even further entrenched.
Kerberos Authentication in Wireless Sensor Networks

We proposed an authentication mechanism in the wireless sensor network. Sensor network uses the Kerberos authentication scheme for the authentication of bases station in the network. Kerberos provides a centralized authentication server whose function is to authenticate user by providing him the ticket to grant request to the base station. In this paper we have provided architecture for the authentication of base station in the wireless sensor network based on the Kerberos server authentication scheme.
Fast and Memory‐Efficient Voronoi Diagram Construction on Triangle Meshes

Geodesic based Voronoi diagrams play an important role in many applications of computer graphics. Constructing such Voronoi diagrams usually resorts to exact geodesics. However, exact geodesic computation always consumes lots of time and memory, which has become the bottleneck of constructing geodesic based Voronoi diagrams. In this paper, we propose the window‐VTP algorithm, which can effectively reduce redundant computation and save memory. As a result, constructing Voronoi diagrams using the proposed window‐VTP algorithm runs 3–8 times faster than Liu et al.'s method [ LCT11 ], 1.2 times faster than its FWP‐MMP variant and more importantly uses 10–70 times less memory than both of them.