Miracle-dz/UniFAR-FTUs huggingface dataset:
TNF receptors regulate vascular homeostasis in zebrafish through a caspase-8, caspase-2 and P53 apoptotic program that bypasses caspase-3

SUMMARY Although it is known that tumor necrosis factor receptor (TNFR) signaling plays a crucial role in vascular integrity and homeostasis, the contribution of each receptor to these processes and the signaling pathway involved are still largely unknown. Here, we show that targeted gene knockdown of TNFRSF1B in zebrafish embryos results in the induction of a caspase-8, caspase-2 and P53-dependent apoptotic program in endothelial cells that bypasses caspase-3. Furthermore, the simultaneous depletion of TNFRSF1A or the activation of NF-κB rescue endothelial cell apoptosis, indicating that a signaling balance between both TNFRs is required for endothelial cell integrity. In endothelial cells, TNFRSF1A signals apoptosis through caspase-8, whereas TNFRSF1B signals survival via NF-κB. Similarly, TNFα promotes the apoptosis of human endothelial cells through TNFRSF1A and triggers caspase-2 and P53 activation. We have identified an evolutionarily conserved apoptotic pathway involved in vascular homeostasis that provides new therapeutic targets for the control of inflammation- and tumor-driven angiogenesis.
Max-Min Fairness and Sum-Rate Maximization of MU-VLC Local Networks

In this paper, we study multi-user multiple-input single-output (MU-MISO) visible light communications (VLC)for indoor broadcast systems. Multiple LED arrays are deployed as transmitters to serve multiple users simultaneously. In such broadcast systems, the main challenging issue is the presence of multi-user interference (MUI) among users. In order to completely cancel the MUI, the zero forcing (ZF) precoding technique which is originally designed for radio frequency (RF)communications, is adopted due to its low computational complexity. However, different from RF counterpart the VLC signal is inherently non-negative leading to the necessity of modifying the design of ZF precoding matrix. The paper investigates the maxmin fairness and the lower bound for the sum-rate maximization of all users in the room scale scenario taken into account the non-negativity signal constraint imposing on precoding matrix. Furthermore, numerical results show that relative user's positions has a considerable impact on the system performance.
Video quality representation classification of Safari encrypted DASH streams

The increasing popularity of HTTP adaptive video streaming services has dramatically increased bandwidth requirements on operator networks, which attempt to shape their traffic through Deep Packet Inspection (DPI). However, Google and certain content providers have started to encrypt their video services. As a result, operators often encounter difficulties in shaping their encrypted video traffic via DPI. This highlights the need for new traffic classification methods for encrypted HTTP adaptive video streaming to enable smart traffic shaping. These new methods will have to effectively estimate the quality representation layer and playout buffer. We present a new method and show for the first time that video quality representation classification for (YouTube) encrypted HTTP adaptive streaming is possible. We analyze the performance of this classification method with Safari over HTTPS. Based on a large number of offline and online traffic classification experiments, we demonstrate that it can independently classify, in real time, every video segment into one of the quality representation layers with 96.13% average accuracy.
Sidestepping implementation traps when implementing knowledge management: lessons learned from Siemens

This case study provides an in-depth analysis of Siemens' lessons learned when implementing knowledge management. For the analysis of the case-study data, we use established tools from the marketing literature, and integrate these with the change management literature. The aim is to provide a rich-yet-parsimonious conceptualisation of Siemens' lessons learned in dealing with two distinct implementation traps. The first trap is called customer trap and suggests that the needs of two ‘knowledge management customers’ have to be carefully balanced. Specifically, the ‘end customer’ of the initiative (the user of the initiative) and the ‘business customer’ of the initiative (top management) may have different expectations and requirements that need to be taken into consideration both separately and jointly. The second trap is called personalisation/standardisation trap and points to the need to balance standardisation (often needed due to the global scale of knowledge management initiatives) with customisation (too much of which can lead to an undifferentiated mix in which value propositions of individual initiatives are hard to appreciate).
A direct conversion quadrature transmitter with digital interface in 45 nm CMOS for high-speed 60 GHz communications

A compact 60 GHz direct conversion quadrature transmitter is designed and fabricated in 45 nm standard LP CMOS. The transmitter features an integrated power amplifier with continuous output level control and interfaces binary data signals with nominal peak-to-peak voltage swing of 300 mV. The highest measured modulation bandwidth is limited by the measurement setup to 4 GHz but is simulated to be as high as 10 GHz. In single sideband up-converting operation mode, the measured image suppression ratio is 22 dB with 36 dB of carrier suppression corresponding to approximately 8% EVM in the output signal constellation. The output RF frequency can be from 54 GHz to 66 GHz to accommodate several channels and the output power can be adjusted from −3 dBm to 10 dBm. The chip is operated from a 2 V supply and draws 180 mA current.
Retinal dystrophy of Swedish briard/briard-beagle dogs is due to a 4-bp deletion in RPE65.

The RPE65 gene encodes a 65-kDa microsomal protein expressed exclusively in retinal pigment epithelium (RPE). Mutations in the human RPE65 gene have recently been identified in patients with autosomal recessive, severe, childhood-onset retinal dystrophy. Here we report the characterization of a 2.4-kb canine Rpe65 cDNA. The longest open reading frame predicts a 533-amino-acid protein with a calculated molecular mass of about 61 kDa prior to protein modification. Sequence comparison shows that RPE65 is highly conserved throughout mammalian evolution. We have identified a homozygous 4-bp deletion (485delAAGA) in putative exon 5 of the canine Rpe65 gene in affected animals of a highly inbred kinship of Swedish briard/briard-beagle dogs, in which an autosomal recessive, early-onset, and progressive retinal dystrophy segregates. The deletion results in a frameshift and leads to a premature stop codon after inclusion of 52 canine RPE65-unrelated amino acids from residue 153 onward. More than two-thirds of the wildtype polypeptide chain will be missing, and the mutant protein is most likely nonfunctional (null allele). Clinical features of the canine disease are quite similar to those described in human. Therefore this form of canine retinal dystrophy provides an attractive animal model of the corresponding human disorder with immediate significance for various therapeutic approaches, including RPE transplantation.
Incidence and Risk Factors of Parastomal Hernia

Purpose Among the various stoma complications, the parastomal hernia (PSH) is the most common. Prevention of PSH is very important to improve the quality of life and to prevent further serious complications. The aim of this study was to analyze the incidence and the risk factors of PSH. Methods From January 2002 and October 2008, we retrospectively reviewed 165 patients who underwent an end colostomy. As a routine oncologic follow-up, abdomino-pelvic computed tomography was used to examine the occurrence of the PSH. The associations of age, sex, body mass index (BMI), history of steroid use and comorbidities to the development of the PSH were analyzed. The median duration of the follow-up was 36 months (0 to 99 months). Results During follow-up, 50 patients developed a PSH and the 5-year cumulative incidence rate of a PSH, obtained by using the Kaplan-Meier method, was 37.8%. In the multivariate COX analysis, female gender (hazard ratio [HR], 3.29; 95% confidence interval [CI], 1.77 to 6.11; P < 0.0001), age over 60 years (HR, 2.37; 95% CI, 1.26 to 4.46; P = 0.01), BMI more than 25 kg/m2 (HR, 1.8; 95% CI, 1.02 to 3.16; P = 0.04), and hypertension (HR, 2.08; 95% CI, 1.14 to 3.81; P = 0.02) were all independent risk factors for the development of a PSH. Conclusion The 5-year incidence rate of a PSH was 37.8%. The significant risk factors of a PSH were as follows: female gender, age over 60 years, BMI more than 25 kg/m2, and hypertension. Using a prophylactic mesh during colostomy formation might be advisable when the patients have these factors.
Preceptor rewards: How to say thank you for mentoring the next generation of nurse practitioners

Purpose: To answer the question how do faculty nurture and reward clinical preceptors and what supports do preceptors require? Data sources: Data came from the literature and from surveying a purposive sample of 26 faculty members teaching clinical courses and arranging precepted experiences for nurse practitioner (NP) students at 26 public and private institutions across the United States. The vehicles for the survey were personal contact and e‐mail. Conclusions: Schools offer preceptor rewards varying widely in their monetary value, from tuition and continuing education vouchers, verification of hours toward recertification, access to services and events on campus, reduced price or free admission to museums, cultural and sports events, and lectures. Faculty nurture preceptors by nominating them for awards, providing letters of reference, editing manuscripts, and collaborating on research projects. Supports for preceptors from the literature reflected National Organization of Nurse Practitioner Faculties guidelines (2000), and the policies of schools and clinical agencies, such as providing copies of program objectives and student credentials. Implications for practice and education: As NP programs have proliferated, there is increased pressure on faculty to find, nurture, reward, and retain good preceptors. Faculty must continue to work with program and agency administrators to comply with policies and create preceptor rewards to recognize their gifts to us, to our schools, and to the profession.
The Price of Selection in Differential Privacy

In the differentially private top-$k$ selection problem, we are given a dataset $X \in \{\pm 1\}^{n \times d}$, in which each row belongs to an individual and each column corresponds to some binary attribute, and our goal is to find a set of $k \ll d$ columns whose means are approximately as large as possible. Differential privacy requires that our choice of these $k$ columns does not depend too much on any on individual's dataset. This problem can be solved using the well known exponential mechanism and composition properties of differential privacy. In the high-accuracy regime, where we require the error of the selection procedure to be to be smaller than the so-called sampling error $\alpha \approx \sqrt{\ln(d)/n}$, this procedure succeeds given a dataset of size $n \gtrsim k \ln(d)$. We prove a matching lower bound, showing that a dataset of size $n \gtrsim k \ln(d)$ is necessary for private top-$k$ selection in this high-accuracy regime. Our lower bound is the first to show that selecting the $k$ largest columns requires more data than simply estimating the value of those $k$ columns, which can be done using a dataset of size just $n \gtrsim k$.
Zwischenstaatliche Variationen bei Bevölkerungseinstellungen zur EU: ein mehrebenenanalytischer Untersuchungsansatz

This article analyses the reasons for the enormous inter-state variations in public support for the EU. For this purpose, the method of multi-level-analysis is used, which is an extension of the traditional OLS-regression and which is especially suitable for dealing with contextual or multilevel data structures. In analysing a Eurobarometer dataset, statespecific macro variables are included as explanatory variables for public opinion towards the EU and procedure of the multilevel-analysis will be illustrated.
SDN APIs and Models for Two-Sided Resource Management in Broadband Access Networks

Access networks, largely based on DSL or cable links, continue to be the bandwidth bottleneck between device-rich households and high-speed core networks, causing frustration for both end-users and content service providers (CSPs). In this paper, we advocate that the scarce bandwidth resource on the access link be managed jointly, under software control, by the Internet service provider (ISP), consumer, and CSP. Our first contribution is to develop software defined networking (SDN) APIs for bandwidth control at fine-grain (per-flow) by the CSP and at coarse-grain (per-device) by the consumer, and highlight the benefits of such an architecture for all entities. Second, we develop an economic model to guide the ISP in determining bandwidth allocation that balances the needs of the CSP against those of the consumer, and demonstrate its utility via simulation of trace data comprising over 10 million flows. Finally, we prototype our system using commodity home routers and open-source SDN platforms, and conduct experiments in a campus-scale network to demonstrate how our scheme permits proactive and reactive improvement in end-user experience.
Least-Squares Finite Element Discretization of the Neutron Transport Equation in Spherical Geometry

The main focus of this paper is the numerical solution of the steady-state, mono-energetic Boltzmann transport equation for neutral particles through mixed material media in a spherically symmetric geometry. Standard solution strategies, like the discrete ordinates method, may lead to nonphysical approximate solutions. In particular, a point source at the center of the sphere yields undesirable ray effects. Posing the problem in spherical coordinates avoids ray effects and other nonphysical numerical artifacts in the simulation process, at the cost of coupling all angles in the PDE setting. In addition, traditional finite element or finite difference techniques for spherical coordinates often yield incorrect scalar flux at the center of the sphere, known as flux dip, and oscillations near steep gradients. In this paper, a least-squares finite element method with adaptive mesh refinement is used to approximate solutions to the nonscattering, one-dimensional neutron transport equation in spherically symmetr.
Estimation of Parameters for Macroparasite Population Evolution Using Approximate Bayesian Computation

Summary We estimate the parameters of a stochastic process model for a macroparasite population within a host using approximate Bayesian computation (ABC). The immunity of the host is an unobserved model variable and only mature macroparasites at sacrifice of the host are counted. With very limited data, process rates are inferred reasonably precisely. Modeling involves a three variable Markov process for which the observed data likelihood is computationally intractable. ABC methods are particularly useful when the likelihood is analytically or computationally intractable. The ABC algorithm we present is based on sequential Monte Carlo, is adaptive in nature, and overcomes some drawbacks of previous approaches to ABC. The algorithm is validated on a test example involving simulated data from an autologistic model before being used to infer parameters of the Markov process model for experimental data. The fitted model explains the observed extra‐binomial variation in terms of a zero‐one immunity variable, which has a short‐lived presence in the host.
Traffic sign detection and classification for Advanced Driver Assistant Systems

Traffic signs include many useful environmental information which can help drivers learn about the change of the road ahead and the driving requirements. Therefore, more and more scholars have concentrated on the issues about recognition the traffic signs by using computer vision and machine learning techniques. And now, traffic signs recognition algorithm has become an important part of Advanced Driver Assistance Systems (ADAS). A novel traffic signs recognition algorithm, which based on machine vision and machine learning techniques, is proposed in this paper. There are two steps in our algorithm: detection and recognition. First of all, the candidate regions are detected by using the color features of the pixels in the detection step. Next, the cascaded Feedforward Neural Networks with Random Weights (FNNRW) classifiers are utilized for shape and content recognition. The experimental results indicate that the average running time of the whole system is less than 40ms, with an accuracy rate of about 91 percent. Therefore, the proposed system has good performance both in accuracy and efficiency and is suitable for the application of Advanced Driver Assistance Systems.
Multi-Objective Ant Colony Optimization Based on the Physarum-Inspired Mathematical Model for Bi-Objective Traveling Salesman Problems

Bi-objective Traveling Salesman Problem (bTSP) is an important field in the operations research, its solutions can be widely applied in the real world. Many researches of Multi-objective Ant Colony Optimization (MOACOs) have been proposed to solve bTSPs. However, most of MOACOs suffer premature convergence. This paper proposes an optimization strategy for MOACOs by optimizing the initialization of pheromone matrix with the prior knowledge of Physarum-inspired Mathematical Model (PMM). PMM can find the shortest route between two nodes based on the positive feedback mechanism. The optimized algorithms, named as iPM-MOACOs, can enhance the pheromone in the short paths and promote the search ability of ants. A series of experiments are conducted and experimental results show that the proposed strategy can achieve a better compromise solution than the original MOACOs for solving bTSPs.
Audio-video automatic speech recognition: an example of improved performance through multimodal sensor input

One of the advantages of multimodal HCI technology is the performance improvement that can be gained over conventional single-modality technology by employing complementary sensors in different modalities. Such information is particular useful in practical, real-world applications where the application's performance must be robust against all kinds of noise. An example is the domain of automatic speech recognition (ASR). Traditionally, ASR systems only use information from the audio modality. In the presence of acoustic noise, the performance drops quickly. However, it can and has been shown that incorporating additional visual speech information from the video modality improves the performance significantly, so that AV ASR systems can be employed in applications areas where audio-only ASR systems would fail, thus opening new application areas for ASR technology. In thispaper, a non-intrusive (no artificial markers), real-time 3D lip tracking system is presented as well as its application to AV ASR. The multivariate statistical analysis 'co-inertia analysis' is also shown, which offers improved numerical stability over other multivariate analyses even for small sample sizes.
A Comparative Study of Graph-Based, Eikonal, and Monodomain Simulations for the Estimation of Cardiac Activation Times

The bidomain and monodomain equations are well established as the standard set of equations for the simulation of cardiac electrophysiological behavior. However, the computational cost of detailed bidomain/monodomain simulations limits their applicability in scenarios where a large number of simulations needs to be performed (e.g., parameter estimation). In this study, we present a graph-based method, which relies on point-to-point path finding to estimate activation times for single points in cardiac tissue with minimal computational costs. To validate our approach, activation times are compared to monodomain simulation results for an anatomically based rabbit ventricular model, incorporating realistic fiber orientation and conduction heterogeneities. Differences in activation times between the graph-based method and monodomain results are less than 10% of the total activation time, and computational performance is orders of magnitude faster with the proposed method when calculating activation times at single points. These results suggest that the graph-based method is well suited for estimating activation times when the need for fast performance justifies a limited loss of accuracy.
On-line admission control and packet scheduling with interleaving

This paper presents a comprehensive study of the effect of job interleaving by preemption on the throughput of a single server where requests arrive with a given processing time and slack. The problem is to decide which requests to serve so as to maximize the server's utilization. This simple model captures many situations, both at the application (e.g., delivery of video) as well as at the network/transmission levels (e.g., scheduling of packets from input to output interface of a switch). The problem is on-line in nature, and thus we use competitive analysis for measuring the performance of our scheduling algorithms. We consider two modes of operation - with and without commitment - and derive upper and lower bounds for each case. Since competitive analysis is based on the worst-case scenario, the average-case performance of the algorithms is also examined by a simulation study.
Novel Subcellular Distribution Pattern of A-Type K+ Channels on Neuronal Surface

Potassium channels comprise the most diverse family of ion channels. In nerve cells, their critical roles in synaptic integration and output generation have been demonstrated. Here, we provide evidence for a distribution that predicts a novel role of K+ channels in the CNS. Our experiments revealed a highly selective clustering of the Kv4.3 A-type K+ channel subunits at specialized junctions between climbing fibers and cerebellar GABAergic interneurons. High-resolution ultrastructural and immunohistochemical experiments demonstrated that these junctions are distinct from known chemical and electrical (gap junctions) synapses and also from puncta adherentia. Each cerebellar interneuron contains many such K+ channel-rich specializations, which seem to be distributed throughout the somatodendritic surface. We also show that such K+ channel-rich specializations are not only present in the cerebellum but are widespread in the rat CNS. For example, mitral cells of the main olfactory bulb establish Kv4.2 subunit-positive specializations with each other. At these specializations, both apposing membranes have a high density of K+ channels, indicating bidirectional signaling. Similar specializations with pronounced coclustering of the Kv4.2 and 4.3 subunits were observed between nerve cells in the medial nucleus of the habenula. Based on our results and on the known properties of A-type K+ channels, we propose that strategically clustered K+ channels at unique membrane specializations could mediate a novel type of communication between nerve cells.