Miracle-dz/UniFAR-FTUs huggingface dataset:
A Cluster-Based Cooperative Localization Algorithm

Cooperative localization (CL) is an efficient way to enhance the position estimate by cooperating among agents, especially under an insufficient signal source situation. To realize CL, a suitable network architecture has to be designed. For the centralized CL, all the information is transmitted to a data center to find a global optimal solution for all the agents. Note that the centralized network is not scalable in communication aspect since all the information has to be collected before estimation, which requires complex scheduling for range measurement and measurement report. On the other hand, an agent estimates its own position and exchanges with other agents locally to solve the scalability issue in the distributed CL. However, measurement information collected locally in the distributed scheme is less than measurement information in the centralized scheme, which might degrade the position estimate and cause divergence by propagating position estimate iteratively. In order to solve the scalability issue of centralized CL and the divergence issue of distributed CL, cluster network is adopted in the paper. After cluster formation, an agent estimates its initial position based on intra-cluster measurement in a cluster to obtain a reliable initial position. To further cooperate with the agent of other clusters, the cluster gateway iteratively refines its position estimate with other cluster gateways based on inter-cluster measurement. Simulation results validate that the proposed cluster-based CL outperforms distributed CL.
Three-dimensional Finite Element Analysis of the Cartilaginous Structures in the Human Temporomandibular Joint

While the movability of the human temporomandibular joint is great, the strains and stresses in the cartilaginous structures might largely depend on the position of the mandible with respect to the skull. This hypothesis was investigated by means of static three-dimensional finite element simulations involving different habitual condylar positions. Furthermore, the influence of several model parameters was examined by sensitivity analyses. The results indicated that the disc moved together with the condyle in the anterior direction without the presence of ligaments and the lateral pterygoid muscle. By adapting its shape to the changing geometry of the articular surfaces, the disc prevented small contact areas and thus local peak loading. In a jaw-closed configuration, the influence of 30° variations of the loading direction was negligible. The load distribution capability of the disc appeared to be proportional to its elasticity and was enhanced by the fibrocartilage layers on the articular surfaces.
Successive Interference Cancellation: Carving Out MAC Layer Opportunities

Successive interference cancellation (SIC) is a PHY capability that allows a receiver to decode packets that arrive simultaneously. While the technique is well known in communications literature, emerging software radio platforms are making practical experimentation feasible. This motivates us to study the extent of throughput gains possible with SIC from a MAC layer perspective and scenarios where such gains are worth pursuing. We find that contrary to our initial expectation, the gains are not high when the bits of interfering signals are not known a priori to the receiver. Moreover, we observe that the scope for SIC gets squeezed by the advances in bitrate adaptation. In particular, our analysis shows that interfering one-to-one transmissions benefit less from SIC than scenarios with many-to-one transmissions (such as when clients upload data to a common access point). In view of this, we develop an SIC-aware scheduling algorithm that employs client pairing and power reduction to extract the most gains from SIC. We believe that our findings will be useful guidelines for moving forward with SIC-aware protocol research.
Use of quality control charts for detection of outliers and temporal trends in cumulative meta‐analysis

Cumulative meta‐analysis (CMA) aims to aggregate accumulating evidence. Essentially a visual tool, CMA should be supplemented by formal statistical methods for assessment of the significance of the accumulating evidence, and for detection of temporal trends in effect sizes. These methods should also take into account multiple testing inherent in CMA. We review the existing methods for detection of temporal trends in effect sizes and suggest a new approach, namely the use of standard quality control (QC) charts, in particular X charts and CUSUM charts, to detect possible outliers and trends over time. We discuss the application of the QC charts to four popular measures of effect size: the odds ratios, the relative risks, the correlation coefficients and the standardized mean differences. Applications of QC charts are illustrated by three meta‐analysis examples from medicine, ecology and evolutionary biology. Copyright © 2011 John Wiley & Sons, Ltd.
How Adolescents Cope With Bullying

Abstract Bullying is a stressful event for adolescents at school and was the fourth most common reason for calls to Kids Help Line in 2002. This study sought to examine coping styles used by students affected by bullying in Years 8 and 10 attending three Queensland high schools. Eighty-eight students completed the Bully Survey containing questions about bullying experiences and the way they coped in those situations. No year level differences were found in terms of the type of bullying experienced or the way in which students coped with these experiences. A significant interaction was found between duration of bullying and perceived control for the proportional use of disengagement coping (i.e., denial, avoidance and wishful thinking strategies). A significant simple main effect was found between perceived stressfulness and proportional use of involuntary engagement coping (i.e., rumination, intrusive thoughts, emotional arousal, physiological arousal and impulsive actions). Implications of these findings for schools are discussed.
miR-122 affects the viability and apoptosis of hepatocellular carcinoma cells

Abstract Objective. miR-122 is highly abundant in liver and a hepato-specific microRNA. There is evidence to show that miR-122 expression is down-regulated in human hepatocellular carcinoma (HCC). It is not known whether miR-122 affects the cellular behavior of hepatoma cells. The aim of this study was to investigate the effects of miR-122 on the viability and apoptosis of hepatoma cells. Material and methods. The viability and apoptosis of Huh-7 and HepG2 cells treated with miR-122 or miR-122 antisense RNA (anti-miR-122) were analyzed by adenosine triphosphate (ATP)-based luminescent assay, annexin V-based flow cytometry, and terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) detection. The miR-122 coding genes in both cell lines were sequenced. Results. Although two putative promoter sequences for the miR-122 gene at 18q21.31 were detected, the miR-122 coding sequence was missing in HepG2 cells, which might be the reason for the absence of miR-122 expression. There was no significant difference between the viabilities of HepG2 cells transfected with miR-122 and mock HepG2 cells (p >0.05). However, the viability of Huh-7 transfected with anti-miR-122 was significantly elevated at 24, 36, and 48 h posttransfection compared with that of mock cells (p <0.01). Both the flow cytometry and TUNEL assay showed that the apoptotic level of Huh-7 transfected with anti-miR-122 was significantly decreased at 48 h posttransfection (p <0.01). Conclusions. miR-122 down-regulated the viability but up-regulated the apoptosis of hepatoma cell Huh-7. The absence of miR-122 expression in HepG2 cells was due to the loss of the miR-122 coding sequence in chromosome 18. These results imply that aberrant expression of miR-122 may contribute to hepatocarcinogenesis.
Bedside formulas for K.t/V. A kinder, gentler approach to urea kinetic modeling.

Based on an empiric analysis of urea kinetic modeling equations, three formulas were derived for use at the bedside: (F1) Ob.t = 14.W. (K.t/V); (F2) target R = e-K.t/V + 0.03 + UF/W; (F3) K.t/V = -In (R - 0.03 - UF/W); where Qb = blood flow (ml/min); t = session length (h); R = post/pre BUN; UF = ultrafiltrate volume (L/session); and W = postdialysis weight (kg). When a particular K.t/V is desired, F1 is used to estimate Qb for a given W and t. Qb, t, and/or dialyzer type are then adjusted until R = target R calculated by F2 (based on target K.t/V, UF, and W). F3 estimates delivered K.t/V from R, UF, and W. These formulas were validated against 336 conventional 3-point modeling sessions in 256 patients. The multiplier "14" in F1 actually averaged 12.5 +/- 2.8, the large standard deviation suggesting that use of F1 would often result in K.t/V values substantially above or below the target K.t/V. The main causes of error were unusual V/W or K/Qb. On the other hand, F2 and F3 were highly accurate: target R estimated by F2 predicted actual R (at a given K.t/V, UF, and W) very well (% error = 0.65 +/- 2.3); K.t/V estimated by F3 predicted actual K.t/V (% error = 0.74 +/- 2.7). The results suggest that attainment of a target R (F2) will ensure that the target K.t/V is being delivered; F3 is useful to estimate K.t/V.F1 is an initial estimate only of the dialysis Rx; it must be followed by adjustment of t, Qb, or dialyzer until target R (from F2) is attained.
Analyse sémantique des réseaux sociaux

L'explosion des fonctionnalites sociales au sein des applications du Web a favorise le deploiement d'un panorama de medias sociaux permettant aux utilisateurs de librement contribuer, de se regrouper et d'interagir entre eux. La combinaison de divers moyens de publication et de socialisation permet de rapidement partager, recommander et propager l'information dans son reseau social, ainsi que de solliciter des reactions et de nouvelles contributions. Ces espaces partages ont favorise la creation et le developpement de communautes d'interets qui publient, filtrent et organisent de vastes repertoires de references dans leurs domaines, avec une impressionnante reactivite aux changements. Afin de reproduire les succes du Web dans la gestion d'information, de plus en plus de plates-formes sociales sont deployees dans des intranets d'entreprise. Cependant, l'avantage de ces plates-formes est fortement attenue lorsque le reseau social devient si grand que les informations pertinentes sont noyees dans des flux continus de notifications. Organiser cette enorme quantite d'informations est l'un des defis majeurs du Web 2.0 afin de tirer pleinement partie des benefices de l'Entreprise 2.0, a savoir, l'utilisation des technologies du Web 2.0, tel que les blogs et les wikis, dans un intranet. Cette these propose d'ameliorer l'analyse des reseaux sociaux multiples et varies emergeant des usages sociaux du Web, au travers d'une contribution originale qui enrichit l'analyse des reseaux sociaux avec les technologies du Web Semantique. L'analyse des reseaux sociaux propose des algorithmes de graphes pour caracteriser la structure d'un reseau social et ses positions strategiques. Les technologies du Web Semantique permettent de representer et d'echanger les connaissances entre des applications distribuees sur le Web avec un modele de graphes richement types (RDF), un langage de requete (SPARQL) et des langages de description de modeles (RDFS et OWL). Dans cette these, nous fusionnons ces deux modeles afin d'aller au-dela de l'analyse structurelle des graphes sociaux en integrant un traitement semantique de leur typage et des connaissances qu'ils contiennent. En particulier nous examinons comment (1) modeliser des donnees sociales en ligne a base d'ontologies, (2) realiser une analyse du reseau social qui tire partie de la semantique de ces representations, et (3) detecter et etiqueter explicitement des communautes a partir de reseaux sociaux et de folksonomies.
Mining maximal cliques from an uncertain graph

We consider mining dense substructures (maximal cliques) from an uncertain graph, which is a probability distribution on a set of deterministic graphs. For parameter 0 <; α <; 1, we consider the notion of an α-maximal clique in an uncertain graph. We present matching upper and lower bounds on the number of α-maximal cliques possible within a (uncertain) graph. We present an algorithm to enumerate α-maximal cliques whose worst-case runtime is near-optimal, and an experimental evaluation showing the practical utility of the algorithm.
Knockdown of S100A7 reduces lung squamous cell carcinoma cell growth in vitro and in vivo.

OBJECTIVE S100A7 plays a role in the malignant potential of several epithelial cancers, and could candidate diagnostic marker or therapeutic target. Nuclear factor kappa B (NF-κB) regulates cancer cell growth and is modulated by phospholipase activity in many cancer cells. In the present study, we first evaluate the involvement of S100A7 in lung squamous cell carcinoma and its clinical usefulness for diagnosis. We then study whether knockdown of S100A7 in lung squamous cell carcinoma cells would reduce cell proliferation and NF-κB activity in vitro and attenuate tumor growth in vivo. METHODS We examined S100A7 expression in lung squamous cell carcinoma tissues by immunohistology . The human lung squamous cell carcinoma cell line NCI-H520 were transduced with short hairpin RNA targeting S100A7. Quantitative reverse transcriptase-polymerase chain reaction and immunoblotting confirmed knockdown of S100A7 messenger RNA and protein, respectively. Cell proliferation was evaluated by the MTT assay. NF-κB phosphorylation was assayed by western blot. 1×10(6) of NCI-H520/S100A7 knockdown cells were injected into the left flanks of nude mice (aged 6 to 8 weeks). Tumors were followed for 35 days, then removed and stained with hematoxylin and eosin, stained with Ki-67, and analyzed for S100A7 protein expression. RESULTS S100A7 protein levels were significantly higher in carcinoma specimens than in nonneoplastic tissues. S100A7 might be a useful marker for diagnosis of lung squamous cell carcinoma. In vitro data showed that inhibition of S100A7 decreased proliferation of NCI-H520 cells. S100A7 knockdown reduced NF-κB phosphorylation and tumor growth in vivo and vivo. Explanted knockdown tumors maintained lower S100A7 levels compared with wild-type, confirmed by immunohistology. Ki-67 staining was more prominent throughout the wild-type tumors compared with knockdown tumors. CONCLUSIONS Our present results suggest that S100A7 level is a promising tool for diagnosis of lung squamous cell carcinoma. Knockdown of S100A7 suppresses lung cancer growth in part by attenuating NF-κB activity. S100A7 may be a promising therapeutic target for lung squamous cell carcinoma.
L1-Regularized Reconstruction Error as Alpha Matte

Sampling-based alpha matting methods have traditionally followed the compositing equation to estimate the alpha value at a pixel from a pair of foreground (F) and background (B) samples. The (F,B) pair that produces the least reconstruction error is selected, followed by alpha estimation. The significance of that residual error has been left unexamined. In this letter, we propose a video matting algorithm that uses L1-regularized reconstruction error of F and B samples as a measure of the alpha matte. A multiframe nonlocal means framework using coherency sensitive hashing is utilized to ensure temporal coherency in the video mattes. Qualitative and quantitative evaluations on a dataset exclusively for video matting demonstrate the effectiveness of the proposed matting algorithm.
Sample-drop firmness analysis of TDMA-scheduled control applications

This paper proposes methods for verification of (m, k)-firmness properties of control applications running on a shared TDMA-scheduled processor. We particularly consider dropped samples arising from processor sharing. Based on the available processor budget for any sample that is ready for execution, the Finite-Point (FP) method is proposed for quantification of the maximum number of dropped samples. The FP method is further generalized using a timed automata based model to consider the variation in the period of samples. The UPPAAL tool is used to validate and verify the timed automata based model. The FP method gives an exact bound on the number of dropped samples, whereas the timed-automata analysis provides a conservative bound. The methods are evaluated considering a realistic case study. Scalability analysis of the methods shows acceptable verification times for different sets of parameters.
Visceral Afferents Directly Activate Catecholamine Neurons in the Solitary Tract Nucleus

Brainstem A2/C2 neurons are catecholamine (CA) neurons within the solitary tract nucleus (NTS) that influence many homeostatic functions, including cardiovascular reflexes, food intake, and stress. Because NTS is a major interface between sensory visceral afferents and the CNS, NTS CA neurons are ideally suited to coordinate complex responses by their projections to multiple brain regions. To test how NTS CA neurons process visceral afferent information carried by solitary tract (ST) afferents, we identified CA neurons using transgenic mice expressing TH-EGFP (enhanced green fluorescent protein under the control of the tyrosine hydroxylase promoter) and recorded synaptic responses to ST activation in horizontal slices. ST shocks evoked large-amplitude, short-latency, glutamatergic EPSCs (ST-EPSCs) in 90% of NTS CA neurons. Within neurons, ST-EPSCs had constant latency, rarely failed, and depressed substantially at high ST frequencies, indicating that NTS CA neurons receive direct monosynaptic connections from afferent terminals. NTS CA neurons received direct ST inputs from only one or two afferent fibers, with one-half also receiving smaller amplitude indirect inputs. Up to 90% of ST shocks evoked action potentials in NTS CA neurons. However, transmission of sensory afferent information through NTS CA neurons critically depended on the expression of an A-type potassium current (IKA), which when active attenuated ST-activated action potentials to a 37% success rate. The satiety peptide, cholecystokinin, presynaptically facilitated glutamate transmission in one-half of NTS CA neurons. Thus, NTS CA neurons are directly driven by visceral afferents with output being modulated by presynaptic peptide receptors and postsynaptic potassium channels.
Gonadotropins Activate Oncogenic Pathways to Enhance Proliferation in Normal Mouse Ovarian Surface Epithelium

Ovarian cancer is the most lethal gynecological malignancy affecting American women. The gonadotropins, follicle stimulating hormone (FSH) and luteinizing hormone (LH), have been implicated as growth factors in ovarian cancer. In the present study, pathways activated by FSH and LH in normal ovarian surface epithelium (OSE) grown in their microenvironment were investigated. Gonadotropins increased proliferation in both three-dimensional (3D) ovarian organ culture and in a two-dimensional (2D) normal mouse cell line. A mouse cancer pathway qPCR array using mRNA collected from 3D organ cultures identified Akt as a transcriptionally upregulated target following stimulation with FSH, LH and the combination of FSH and LH. Activation of additional pathways, such as Birc5, Cdk2, Cdk4, and Cdkn2a identified in the 3D organ cultures, were validated by western blot using the 2D cell line. Akt and epidermal growth factor receptor (EGFR) inhibitors blocked gonadotropin-induced cell proliferation in 3D organ and 2D cell culture. OSE isolated from 3D organ cultures stimulated with LH or hydrogen peroxide initiated growth in soft agar. Hydrogen peroxide stimulated colonies were further enhanced when supplemented with FSH. LH colony formation and FSH promotion were blocked by Akt and EGFR inhibitors. These data suggest that the gonadotropins stimulate some of the same proliferative pathways in normal OSE that are activated in ovarian cancers.
Improving Fairness in Multi-Hop Mesh Networks Using 802.11e

In this paper we introduce a tractable analytic model of throughput performance for general 802.11 multi-hop networks. We use this model to explore a number of fairness issues in 802.11 multi-hop networks that have a significant impact on performance and capacity for realistic traffic. Schemes using the functionality provided by 802.11e are proposed to mitigate this unfairness and their efficacy demonstrated.
Parallel Genetic Programming on Fine-Grained SIMD Architectures

As tile field of Genetic Programming (GP) matures and its breadth of application increases, the need for parallel implementations becomes absolutely necessary. The transputer-based system recently presented by Koza ([8]) is one of the rare such parallel implementations. Until today, no implementation has been proposed for parallel GP using a SIMD architecture, except for a data-parallel approach ([16]), although others have exploited workstation farms and pipelined supercomputers. One reason is certainly the apparent difficulty of dealing with the parallel evaluation of different S-expressions when only a single instruction can be executed at the same time on every processor. The aim of this paper is to present such an implementation of parallel GP on a SIMD system, where each processor can efficiently evaluate a different S-expression. We have implemented this approach on a MasPar MP-2 computer, and will present some timing results. To the extent that SIMD machines, like the MasPar are available to offer cost-effective cycles for scientific experimentation, this is a useful approach.
LIMITATIONS OF DIFFUSION‐WEIGHTED IMAGING IN THE DIAGNOSIS OF POSTOPERATIVE INFECTIONS

OBJECTIVEDiffusion-weighted imaging (DWI) has assumed a rapidly emerging role in the diagnosis of intracranial infection; however, its usefulness in the recognition of postoperative infection has been largely unexplored. We sought to determine the ability of DWI to accurately detect a broad range of postneurosurgical infections as well as identify individual factors that may limit its applicability. METHODSWe retrospectively identified 65 patients who had undergone surgery for the confirmed diagnosis of infection between August 2001 and February 2005 and had received preoperative magnetic resonance imaging evaluation, including DWI. Fifty patients developed infections after a primary neurosurgical procedure (“postoperative” infections), whereas 15 infections occurred without antecedent intervention (“spontaneous” infections). Logistic regression analysis was used to identify factors associated with false-negative DWI findings. Additionally, we investigated the false-positive rate of DWI by retrospectively reviewing a series of 30 consecutive patients who underwent craniotomy and received postoperative DWI. RESULTSSpontaneously developing cranial infections exhibited evidence of restricted diffusion in 14 out of 15 (93%) patients; however, infections that occurred postoperatively were associated with a significant false-negative rate using DWI (36%; P < 0.01). Within the subset of patients with postoperative infection, location of infection significantly correlated with the DWI false-negative rate. Infections located extradurally were less likely to demonstrate restricted diffusion compared with those located primarily within the subdural or intraparenchymal spaces. Additionally, false-positive DWI findings were observed in 11 of the 30 patients (37%) who had DWI obtained postoperatively in the absence of infection. CONCLUSIONUtilization of DWI for the diagnosis of infection after primary neurosurgical intervention is associated with an elevated false-negative rate. The absence of restricted diffusion is not sufficient to exclude the presence of pyogenic postcraniotomy infection and should not be used as the principle determinant of patient management in this clinical setting.