Miracle-dz/UniFAR-FTUs huggingface dataset:
Potential use of imatinib in Ewing's Sarcoma: evidence for in vitro and in vivo activity.

BACKGROUND Ewing's sarcoma cells express c-kit, a receptor tyrosine kinase, and its ligand, stem cell factor (SCF), creating a potential autocrine loop that may promote tumor survival. We thus examined whether the specific tyrosine kinase inhibitor imatinib mesylate (hereafter imatinib; formerly STI571) could inhibit the proliferation of Ewing's sarcoma cells in vitro and in vivo. METHODS The effect of imatinib on c-kit expression and phosphorylation in Ewing's sarcoma cells was examined by immunoblotting. The effect of imatinib on cell growth and apoptosis was examined with an MTT [3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide] assay and with a morphologic test and Annexin V staining, respectively. The effect of imatinib oral therapy (every 12 hours for 5-7 days) on primary tumor growth was assessed in Ewing's sarcoma xenografts in SCID/bg mice (5 or 10 mice per group). RESULTS All Ewing's sarcoma cell lines tested were sensitive to imatinib-mediated apoptosis with a concentration inhibiting growth by 50% (IC50) of 10-12 micro M. Imatinib inhibited SCF-mediated c-kit phosphorylation (IC50 = 0.1-0.5 microM). In the xenograft model, imatinib treatment resulted in the regression or control of primary Ewing's sarcomas. After 6 days of treatment, the mean lower extremity volume including xenograft tumor was 3744 mm3 (95% confidence interval [CI] = 3050 to 4437 mm3), 1442 mm3 (95% CI = 931 to 1758 mm3), and 346 mm3 (95% CI = 131 to 622 mm3) in mice treated with carrier alone or with imatinib at 50 mg/kg or at 100 mg/kg, respectively. CONCLUSIONS Imatinib interferes with growth of all Ewing's sarcoma cell lines tested in vitro and in vivo. Targeted inhibition of tyrosine kinase-dependent autocrine loops, therefore, may be a viable therapeutic strategy for Ewing's sarcoma.
Biomarker Effects in Carassius auratus Exposure to Ofloxacin, Sulfamethoxazole and Ibuprofen

Ofloxacin, sulfamethoxazole and ibuprofen are three commonly used drugs which can be detected in aquatic environments. To assess their ecotoxicity, the effects of these three pharmaceuticals and their mixture on AChE (acetylcholinesterase) activity in the brain, and EROD (7-ethoxyresorufin-O-deethylase) and SOD (superoxide dismutase) activities in the liver of the freshwater crucian carp Carassius auratus were tested after exposure for 1, 2, 4 and 7 days. The results showed that treatments with 0.002–0.01 mg/L ofloxacin and 0.0008–0.004 mg/L sulfamethoxazole did not significantly change AChE, EROD and SOD activities. AChE activity was significantly inhibited in response to treatment with >0.05mg/L ofloxacin and >0.02 mg/L sulfamethoxazole. All three biomarkers were induced significantly in treatments with ibuprofen and the mixture of the three pharmaceuticals at all the tested concentrations. The combined effects of ofloxacin, sulfamethoxazole and ibuprofen were compared with their isolated effects on the three biomarkers, and the results indicated that exposure to ibuprofen and the mixture at environmentally relevant concentrations could trigger adverse impacts on Carassius auratus. The hazard quotient (HQ) index also demonstrated a high risk for ibuprofen. Moreover, the present study showed that the effects of ofloxacin, sulfamethoxazole and ibuprofen might be additive on the physiological indices of Carassius auratus.
Efficient SourceAuthenticationfor Multicasting in MANETs JohnS

1 Abstract— In this paper, we investigate a popular source authentication scheme, TESLA (Timed Efficient Stream Loss-tolerant Authentication) for multicast communication in mobile ad hoc networks. We evaluate the performance of a source authentication schemeinspired fr om TESLA and TESLA based on simulations. Time synchronization is a crucial assumption made by these schemes.We describe effective means to achieve time synchronization in MANETs and conclude that overlay networks, whether they are UAVs or satellitesare essential for high efficiency and performance. Since such overlay networks are typical in hierarchical wir elessmobile networks, the proposed schemesare very appropriate for thesescenarios.We claim that having an overlay network will help in routing and key distrib ution, in addition to time synchronization.
The Computational Power of Dynamic Bayesian Networks

This paper considers the computational power of constant size, dynamic Bayesian networks. Although discrete dynamic Bayesian networks are no more powerful than hidden Markov models, dynamic Bayesian networks with continuous random variables and discrete children of continuous parents are capable of performing Turing-complete computation. With modified versions of existing algorithms for belief propagation, such a simulation can be carried out in real time. This result suggests that dynamic Bayesian networks may be more powerful than previously considered. Relationships to causal models and recurrent neural networks are also discussed.
Spectral element discretization of the vorticity, velocity and pressure formulation of the Stokes problem

We consider the Stokes problem provided with non standard boundary conditions which involve the normal component of the velocity and the tangential components of the vorticity. We write a variational formulation of this problem with three independent unknowns: the vorticity, the velocity and the pressure. Next we propose a discretization by spectral element methods which relies on this formulation. A detailed numerical analysis leads to optimal error estimates for the three unknowns and numerical experiments confirm the interest of the discretization.
On the convergence speed of adaptive IIR filters with rational spectrum input signals

A previously presented framework for the convergence speed analysis of adaptive IIR filters considered white input signals and an identification configuration. In this framework, a local model was built and the Hankel singular values of the system being identified had a fundamental role. It also led to the successive approximations (SA) algorithm, attaining a large speed gain. Here, an approach to extend this framework is presented, allowing more general rational spectrum input signals and unifying the analysis of the identification and inverse identification configurations. It leads to a model that has the same form and depends on the same number of Hankel singular values as in the white input case. The singular values, however, refer now to the result of a certain degree-preserving transformation of the system being identified. Conditions for faster convergence as well as the application of the SA algorithm follow naturally from the extended framework.
Why Do Some Employees Fall into and Fail to Exit a Job-Lock Situation?

Previous studies have paid little attention to the employees' ability to exit a job-lock situation and factors that determine this ability. It remains unclear why some employees who experience job lock are able to exit this state while others remain in job lock. We use longitudinal data to identify employees who have fallen in the state of job lock and their subsequent behavior—exiting or remaining in job lock. By use of a first-order Markov transition models, we analyze the relevance of sociodemographic features, employment, occupational, sectoral, and contextual factors, as well as personality characteristics in explaining the transition or its absence. Overall the results show that both demographic factors and work-related aspects increase the likelihood that an employee enters the long-term job lock state (especially for older, married, full-time employed, those in a craft occupation and governmental sector, and in a region with high unemployment). Mental health problems and personality characteristics (low peak-end self-esteem and decisional procrastination) have a significant effect on the probability to stay in long-term job lock. On the contrary, having a managerial, service, or associate occupation, working in the private sector, and having promotion opportunities increase the chance of an exit from the state of job lock.
Safe driving by detecting lane discipline and driver drowsiness

In the modern day world, road accidents have become very common. They not only cause damage to property, but also keep at risk the lives of people travelling. Road safety is an issue of national concern, looking at its magnitude and the incidental negative impacts on the economy, public health, safety and the general welfare of the people. These road accidents may be due to many reasons like rash driving, drink and driving, inexperience, jumping signals, ignoring signboards. Since, road accidents is an important issue to be addressed, this paper will be concentrating on avoiding the road accidents by concentrating mainly on-Drunk driving or drowsiness and lane discipline. The paper has two parts. Firstly, lane detection using Hough Transform. Secondly, eye detection of driver for drowsiness detection. Thus, the main focus is on the fatigue of the driver and his maintenance of lane discipline.
The number of O-type runaways, the number of O and Wolf-Rayet stars with a compact companion and the formation rate of double pulsars predicted by massive close binary evolution.

Using a detailed model of massive close binary evolution and accounting properly for the effects of asymmetric supernova explosions (SN) where we use recent observations of pulsar runaway velocities, we determine the theoretically expected number of post-SN O-type stars with and without a compact companion (CC), the number of O-type runaways, the number of WR+CC systems and the formation rate of binary pulsars in our Galaxy. We conclude that • at least 50% of the O-type runaways are formed through the binary scenario, • less than 3% of all WR stars may hide a CC, • the formation rate of binary pulsars in our Galaxy ≈ 0.003-0.01 times the formation rate of massive stars; this corresponds roughly to a binary pulsar formation rate of the order of 10/year in agreement with the observations. Our results reveal a significant fraction of single WR stars butwith a binary history.We also predict the existence of ’weird’ WR stars, i.e a WR star with a CC in its centre (descendants of Thorne-Żytkow objects).
A test data generation tool for testing RFID middleware

This paper presents a noble RFID data generation tool to enable efficient and low cost testing of the RFID middleware. RFID systems have been widely used in many business areas such as supply-chain management and yard management. As a key component of RFID system, the RFID middleware should be carefully evaluated from various environments. However, taking a variety of tests for RFID middleware is very complex and costly process because it requires construction of test environments such as deploying RFID devices, tagging of product items, and so on. For instance, the stress testing of RFID middleware needs to deploy millions of tags which take lots of money, time and human recourses. To solve these problems, we design virtual readers and tags for constructing virtual environment instead of real devices. Using virtual devices, we implement a test data generation tool which generates tag stream data for testing the RFID middleware. To simulate real RFID environment, we first define several parameters for representing real environments. By configuring the parameters, this tool can generate test data set which emulates various business scenarios. We also define several measurement metrics which are related to four factors like group, redundancy, noisy as well as route to verify the correctness of the generated data set. The experimental results show that our testing tool is cable for facilitating RFID middleware test.
Balancing Revocation and Storage Trade-Offs in Secure Group Communication

In this paper, we focus on trade-offs between storage cost and rekeying cost for secure multicast. Membership in secure multicast groups is dynamic and requires multiple updates in a single time frame. We present a family of algorithms that provide a trade-off between the number of keys maintained by users and the time required for rekeying due to revocation of multiple users. We show that some well-known algorithms in the literature are members of this family. We show that algorithms in this family can be used to reduce the cost of rekeying by 43-79 percent when compared with previous solutions while keeping the number of keys manageable. We also describe a scheme to reduce the number of secrets further when revocations are periodic. Furthermore, we describe techniques to provide preferential treatment for long standing members of the group without affecting the performance of the algorithms. Using our techniques, as the group size increases, long standing members need to store smaller number of keys than short-lived members. This property is useful for adapting to the variable storage requirements of users in current day heterogeneous networks.
Why politicians favor redheads : a theory of tactical horizontal redistribution

This paper studies a very pure form of “vote purchasing”. We consider whether it may be in the interest of a party to discriminate between groups that, possibly except for size, are identical in all welfare relevant spects, i.e. the groups are assumed to have the same income, needs, etc. To emphasise this aspect we label the groups brown-heads and redheads. The interpretation is that they differ only in some characteristic that is entirely irrelevant from a welfare perspective. There are no systematic differences between people with the same income. Taking two samples of people from an income class their political support will be identically distributed. We will show that even with these uniformity assumptions there can be strong incentives for political parties to undertake vote purchasing by favouring one of the identical groups at the expense of the other.
Introducing Heat and Geodesic Kernel Smoothing on Cortical Manifolds

Gaussian kernel smoothing has been widely used in 3D medical images as a way to increase signal-to-noise ratio and coloring dependent noise structure for random field theory, in part, due to its simplicity in numerical implementation. Gaussian kernel is isotropic in Euclidian space, i.e., it assigns the same weights to observations equal distance apart. However, data residing on the convoluted brain cortex fails to be isotropic in the Euclidean sense. On the curved surface, a straight line between two points is not the shortest distance so one may incorrectly assign less weights to closer observations. The question we attempt to answer is how to correctly formulate isotropic smoothing for data on the cortical surface. Methods: When data lie on a 2D cortical surface, data smoothing must be weighted according to geodesic distance along the surface. One existing approach called diffusion smoothing formulates smoothing as the process of heat diffusion by explicitly solving an isotropic diffusion equation with the given data as an initial condition [1, 2, 3]. The drawback of the diffusion smoothing approach is the complexity of setting up a finite element method and making the numerical scheme stable [4]. To address these shortcomings, we propose a simpler method called heat kernel smoothing and its extension called geodesic kernel smoothing. The heat kernel smoothing is formulated as iterated convolutions between the data and a heat kernel. It can be proven that smoothing with a large bandwidth is equivalent to iterative smoothing with a smaller bandwidth [3]. Furthermore, for a small bandwidth the heat kernel converges locally to a Gaussian kernel. Extending the heat kernel smoothing method, we have developed geodesic kernel smoothing. We first compute the geodesic distance on the cortex using the dynamic programming. Then the geodesic kernel is constructed by assigning weights as a function of the geodesic distance and appropriately normalizing the kernel. This approach avoid the necessity of choosing a small bandwidth so the smoothing can be performed efficiently with less number of iterations and a larger bandwidth. Results: Heat kernel smoothing on actual cortical thickness data was performed for illustration. The figure shows smoothing with bandwidth s=1 and 20, 100 and 200 iterations. Conclusions: Both heat kernel and geodesic kernel smoothing are effective cortical surface data smoothing techniques. Figure 1. Heat kernel smoothing on actual cortical thickness data. The bandwidth σ = 1 was used with 20, 100 and 200 iterations.
Quality of service provisioning and energy minimized scheduling in software defined flexible optical networks

The over-provisioning of capacities in optical networks is not a sustainable approach in the long run. In this paper, we propose a software defined networking scheme for quality of service provisioning through energy efficient assignment of optical transponders, employing bandwidth variable distance adaptive modulation and coding. Our scheme enables avoiding over-provisioning of transponder capacity as well as short-term major changes in equipment allocation for networks with dynamic traffic. We make use of the seasonal auto-regressive integrated moving average model to forecast the statistics of network traffic for an arbitrary time span based on the requirements and the constraints of the service provider. The quality of service measure is defined as the probability of congestion at the core router ports. A stochastic linear programming approach is used to provide a solution for energy efficient assignment of optical transponders and electronic switching capacity while ensuring a certain level of quality of service to core routers. The scheduling of optical lightpath capacities is performed for the entire duration of time under consideration, whereas the scheduling of electronic switching capacities is performed based on the short-term dynamics of the traffic. Numerical results show up to 48% improvement in the energy efficiency of optical networks and 45% reduction in the number of optical lightpaths through the implementation of the proposed technique, compared to a design based on employing conventional fixed optical transponders and no traffic rerouting, where both schemes satisfy the congestion probability requirements.
Robust video monitoring system for transport applications based on joint use of multiple description coding and multiple antennas

In this paper, we investigate the joint use of multiple description coding (MDC) and multiple-input multiple-output (MIMO) technology in the specific context of wireless embedded real time video surveillance for transportation applications. The combination of both techniques is expected to provide reliability of transmitted data and graceful degradation of reconstructed video signal. The transmission chain proposed in this work is based on the WiMAX IEEE 802.16d standard. It consists in a 2times4 MIMO system associated with an OFDM physical layer. Different MDC algorithms have been developed with respect to the actual H.264/AVC compression standard. Preliminary results are presented and discussed in order to illustrate the interest of the proposed solution in terms of error robustness and decoded video quality.
ORTHODONTIC PROBLEMS IN PATIENTS WITH HYPODONTIA AND TAURODONTISM OF PERMANENT MOLARS

Taurodontism is a morphological abnormality of the tooth shape with the following characteristic features: vertically enlarged pulp chamber, apical displacement of the bifurcation and trifurcation, shortened roots and no constriction at the level of the cementoenamel junction. This anomaly is still neglected by orthodontists when it comes to making treatment plans in spite of the reports in the literature of a close association of this condition with hypodontia and oligodontia. Aim: The article discusses the orthodontic problems arising in treating patients with hypodontia and taurodontism and suggests approaches to reducing the risk of complications during orthodontic tooth movement. Discussion: Failure to identify taurodont teeth in hypodontic patients can cause serious complications in their orthodontic management because of the greater susceptibility of these types of teeth to root resorption in orthodontic tooth movement. Besides, these types of teeth are less anchorage. Conclusion: The high incidence of taurodontism in hypodontic patients presents a clinical challenge for general dental practitioners and orthodonists alike. Furthermore, successful management of hypodontia rests on the orthodontist’s ability to identify taurodont teeth and correctly include them in treatment plan.
On the Decidability of Consistent Query Answering

Consistent query answering (CQA) is about formally characterizing and computing semantically correct answers to queries posed to a database that may fail to satisfy certain integrity constraints. In this paper, we revisit the decidability status of consistent query answering by considering different parameters of the problem as input to the decision problem. More specifically, we obtain some new results about the undecidability and combined complexity of CQA.
This meta-analysis provides some evidence to support the use of high-tech AAC interventions to improve social-communication skills in individuals with intellectual and developmental disabilities

This meta-analysis provides some evidence to support the use of high-tech AAC interventions to improve social-communication skills in individuals with intellectual and developmental disabilities Devender R. Banda* & Nouf M. Alzrayer (Commentary authors) Special Education Program, Department of Educational Psychology and Leadership, Texas Tech University, Lubbock, TX, USA; Special Education Department, College of Education, King Saud University, Riyadh, Saudi Arabia .
From atomistic simulation towards multiscale modelling of materials

This paper discusses some current trends in computational materials science, especially the striving to forge links between modelling activities at various length and timescales. At the atomistic scale, methods based on quantum mechanical, especially density-functional, theories for electronic properties link to atomic/molecular dynamics and kinetic Monte Carlo simulations. Coarse graining leads to lattice-gas and cellular automata, and eventually to continuum equations solved by finite-element and finite-difference techniques. As examples of hierarchical modelling of materials, the paper describes recent work on anisotropic chemical etching of silicon, irradiation processing of fullerenes, oxygen clustering in silicon and self-diffusion in the compound semiconductor GaSb.
A Caveolin Dominant Negative Mutant Associates with Lipid Bodies and Induces Intracellular Cholesterol Imbalance

Recent studies have indicated a role for caveolin in regulating cholesterol-dependent signaling events. In the present study we have analyzed the role of caveolins in intracellular cholesterol cycling using a dominant negative caveolin mutant. The mutant caveolin protein, cav-3DGV, specifically associates with the membrane surrounding large lipid droplets. These structures contain neutral lipids, and are accessed by caveolin 1–3 upon overexpression. Fluorescence, electron, and video microscopy observations are consistent with formation of the membrane-enclosed lipid rich structures by maturation of subdomains of the ER. The caveolin mutant causes the intracellular accumulation of free cholesterol (FC) in late endosomes, a decrease in surface cholesterol and a decrease in cholesterol efflux and synthesis. The amphiphile U18666A acts synergistically with cavDGV to increase intracellular accumulation of FC. Incubation of cells with oleic acid induces a significant accumulation of full-length caveolins in the enlarged lipid droplets. We conclude that caveolin can associate with the membrane surrounding lipid droplets and is a key component involved in intracellular cholesterol balance and lipid transport in fibroblasts.