Miracle-dz/UniFAR-FTUs huggingface dataset:
Improved Antisense Oligonucleotide Design to Suppress Aberrant SMN2 Gene Transcript Processing: Towards a Treatment for Spinal Muscular Atrophy

Spinal muscular atrophy (SMA) is caused by loss of the Survival Motor Neuron 1 (SMN1) gene, resulting in reduced SMN protein. Humans possess the additional SMN2 gene (or genes) that does produce low level of full length SMN, but cannot adequately compensate for loss of SMN1 due to aberrant splicing. The majority of SMN2 gene transcripts lack exon 7 and the resultant SMNΔ7 mRNA is translated into an unstable and non-functional protein. Splice intervention therapies to promote exon 7 retention and increase amounts of full-length SMN2 transcript offer great potential as a treatment for SMA patients. Several splice silencing motifs in SMN2 have been identified as potential targets for antisense oligonucleotide mediated splice modification. A strong splice silencer is located downstream of exon 7 in SMN2 intron 7. Antisense oligonucleotides targeting this motif promoted SMN2 exon 7 retention in the mature SMN2 transcripts, with increased SMN expression detected in SMA fibroblasts. We report here systematic optimisation of phosphorodiamidate morpholino oligonucleotides (PMO) that promote exon 7 retention to levels that rescued the phenotype in a severe mouse model of SMA after intracerebroventricular delivery. Furthermore, the PMO gives the longest survival reported to date after a single dosing by ICV.
Towards a Taxonomy of Unit Tests

Not all unit tests are alike. Some tests are simple one-liners, while others contain a battery of assertions. Certain tests focus on a single method, while others test interactions between methods. There are even tests that do not contain assertions at all. This can make it difficult for a developer to understand which methods are tested by which tests, to what degree they are tested, and what to take into account while refactoring. We have manually analyzed the test base of a large existing object-oriented system in order to derive a first taxonomy of unit tests. We have then developed some simple tools to semi-automatically categorize tests according to this taxonomy, and applied it to two case studies. Beside explaining our taxonomy, we report on our initial results using it, namely that a majority of unit tests focus on single methods and that our lightweight automatic categorization could already classify more than 50% of these single method commands.
A Comparative Study on Hungarian Acoustic Model Sets and Training Methods

In recent speech recognition systems the base unit of recognition is generally the speech sound. To each speech sound an acoustic model is associated, whose parameters are estimated by statistical methods. The proper training data fundamentally determine the efﬁciency of the recognizer. Present day technology and computational capacity allow speech recognition systems to operate with large dictionaries and complex language models, but the quality of the basic pattern matching units has large inﬂuence on the reliability of the system. In our experiments presented here we investigated the effects of different training methods to the recognition accuracy; namely, the effect of increasing the number of speakers and the number of mixtures were examined in the case of pronunciation modeling and context independent models.
On secure communication over wireless erasure networks

This paper studies the secrecy capacity of unicast communication in a wireless erasure network setting in the presence of a wire-tapper. From an information-theoretic setting of perfect secrecy, both upper bounds and achievable secrecy rates are presented. Secrecy capacity is determined in closed form for a class of broadcast constrained erasure networks.
Video-Rate Panorama for Free-Viewpoint TV

Free Viewpoint Video and TV are technologies regarded as the future of digital entertainment allowing users to navigate through multiple video streams of an event to select novel viewpoints. In this paper, we propose an automatic real-time video stitching algorithm that is capable of producing spherical panoramas for FTV applications. The algorithm works by splitting automatic image stitching into one-time and recurring computations. We utilize GPUs for accelerating the recurring computations and achieving real-time performance. By effectively caching the repeated transform maps, we improve the stitching performance by two orders of magnitude compare to CPU implementations. The multiple stitching steps are pipelined to distribute the panorama stitching computations between multiple processing nodes to produce visually appealing panoramas at 30Hz without any noticeable blurring or stitching artifacts for five HD synchronized cameras.
Forkhead Transcription Factor FKHR-L1 Modulates Cytokine-Dependent Transcriptional Regulation of p27KIP1

ABSTRACT Interleukin-3 (IL-3), IL-5, and granulocyte-macrophage colony-stimulating factor regulate the survival, proliferation, and differentiation of hematopoietic lineages. Phosphatidylinositol 3-kinase (PI3K) has been implicated in the regulation of these processes. Here we investigate the molecular mechanism by which PI3K regulates cytokine-mediated proliferation and survival in the murine pre-B-cell line Ba/F3. IL-3 was found to repress the expression of the cyclin-dependent kinase inhibitor p27KIP1 through activation of PI3K, and this occurs at the level of transcription. This transcriptional regulation occurs through modulation of the forkhead transcription factor FKHR-L1, and IL-3 inhibited FKHR-L1 activity in a PI3K-dependent manner. We have generated Ba/F3 cell lines expressing a tamoxifen-inducible active FKHR-L1 mutant [FKHR-L1(A3):ER*]. Tamoxifen-mediated activation of FKHR-L1(A3):ER* resulted in a striking increase in p27KIP1 promoter activity and mRNA and protein levels as well as induction of the apoptotic program. The level of p27KIP1 appears to be critical in the regulation of cell survival since mere ectopic expression of p27KIP1 was sufficient to induce Ba/F3 apoptosis. Moreover, cell survival was increased in cytokine-starved bone marrow-derived stem cells from p27KIP1 null-mutant mice compared to that in cells from wild-type mice. Taken together, these observations indicate that inhibition of p27KIP1transcription through PI3K-induced FKHR-L1 phosphorylation provides a novel mechanism of regulating cytokine-mediated survival and proliferation.
Inductance and Current Distribution Extraction in Nb Multilayer Circuits with Superconductive and Resistive Components

We describe a calculation tool and modeling methods to find self and mutual inductance and current distribution in superconductive multilayer circuit layouts. Accuracy of the numerical solver is discussed and compared with experimental measurements. Effects of modeling parameter selection on calculation results are shown, and we make conclusions on the selection of modeling parameters for fast but sufficiently accurate calculations when calibration methods are used. Circuit theory for the calculation of branch impedances from the output of the numerical solver is discussed, and compensation for solution difficulties is shown through example. We elaborate on the construction of extraction models for superconductive integrated circuits, with and without resistive branches. We also propose a method to calculate current distribution in a multilayer circuit with multiple bias current feed points. Finally, detailed examples are shown where the effects of stacked vias, bias pillars, coupling, ground connection stacks and ground return currents in circuit layouts for the AIST advanced process (ADP2) and standard process (STP2) are analyzed. We show that multilayer inductance and current distribution extraction in such circuits provides much more information than merely branch inductance, and can be used to improve layouts; for example through reduced coupling between conductors. key words: ground plane return currents, inductex, layout extraction, numerical inductance calculation, parasitic coupling
Validation of Expression Patterns for Nine miRNAs in 204 Lymph-Node Negative Breast Cancers

Introduction Although lymph node negative (LN-) breast cancer patients have a good 10-years survival (∼85%), most of them still receive adjuvant therapy, while only some benefit from this. More accurate prognostication of LN- breast cancer patient may reduce over- and under-treatment. Until now proliferation is the strongest prognostic factor for LN- breast cancer patients. The small molecule microRNA (miRNA) has opened a new window for prognostic markers, therapeutic targets and/or therapeutic components. Previously it has been shown that miR-18a/b, miR-25, miR-29c and miR-106b correlate to high proliferation. Methods The current study validates nine miRNAs (miR-18a/b miR-25, miR-29c, miR-106b, miR375, miR-424, miR-505 and let-7b) significantly correlated with established prognostic breast cancer biomarkers. Total RNA was isolated from 204 formaldehyde-fixed paraffin embedded (FFPE) LN- breast cancers and analyzed with quantitative real-time Polymerase Chain Reaction (qPCR). Independent T-test was used to detect significant correlation between miRNA expression level and the different clinicopathological features for breast cancer. Results Strong and significant associations were observed for high expression of miR-18a/b, miR-106b, miR-25 and miR-505 to high proliferation, oestrogen receptor negativity and cytokeratin 5/6 positivity. High expression of let-7b, miR-29c and miR-375 was detected in more differentiated tumours. Kaplan-Meier survival analysis showed that patients with high miR-106b expression had an 81% survival rate vs. 95% (P = 0.004) for patients with low expression. Conclusion High expression of miR-18a/b are strongly associated with basal-like breast cancer features, while miR-106b can identify a group with higher risk for developing distant metastases in the subgroup of Her2 negatives. Furthermore miR-106b can identify a group of patients with 100% survival within the otherwise considered high risk group of patients with high proliferation. Using miR-106b as a biomarker in conjunction to mitotic activity index could thereby possibly save 18% of the patients with high proliferation from overtreatment.
Application of neural networks for transformer fault diagnosis

Power transformer is one of the most important components in a power system. It experiences thermal and electrical stresses during its operation. The insulation system consisting of mineral oil and the insulation paper used in transformer undergoes chemical changes under these stresses and gases are generated. These gases dissolve in oil. The extracted dissolved gases are analysed in the laboratory using gas chromatograph. The fault identifications in a transformer are based on certain key- gas ratios. International standards such as IEEE and ASTM are in use for fault identification. However, these standards are not able to diagnose the fault under certain conditions. Hence, there is a need to improve the diagnostic accuracy. In this paper an attempt has been made to diagnose the faults in a power transformer using a three level perceptron network. Three types of neural network simulation models are developed using MATLAB™ Software and trained using the IEC TC 10 databases of faulty equipments inspected in service. The outputs of the Neural Network models are compared with the IEEE and ASTM methods. The comparison of the results indicates that the condition assessments offered by the models are capable of predicting the fault with higher success rate than the conventional diagnostic methods.
A tracking approach to localization and synchronization in mobile ad-hoc sensor networks

Self localization is a term used to describe the ability of a network to automatically determine the location of its nodes, given little or no external information. Self localization is an enabling technology for many future capabilities; specifically those that rely on a large number of sensors that self organize to form a coherent system. Most prior work in this area focuses on centralized computation with stationary nodes and synchronized clocks. We report on preliminary results for a setting that is more general in three ways. First, nodes in the network are moving. This implies the pair-wise distances between nodes are not fixed and therefore an iterative tracking procedure is needed to estimate the time varying node positions. Second, we do not assume synchronization between clocks on different nodes. In fact, we allow the clocks to have both an unknown offset and to be running at differing rates (i.e., a drift). Third, our method is decentralized, so there is no need for a single entity withfaccess to all measurements. In this setup, each node in the network is responsible for estimating its state. The method is based on repeated pair-wise communication between nodes. We focus on two types of observables in this paper. First, we use the time between when a message was sent from one node and when it was received by another node. In the case of synchronized clocks and stationary nodes, this observable provides information about the distance between the nodes. In the more general case with non-synchronized clocks, this observable is coupled to the clock offsets and drifts as well as the distance between nodes. Second, we use the Doppler stretch observed by the receiving node. In the case of synchronized clocks, this observable provides information about the line of sight velocity between the nodes. In the case of non-synchronized clocks, this observable is coupled to the clock drift as well as the line of sight velocity. We develop a sophisticated mathematical representation that allows all of these effects to be accounted for simultaneously. We approach the problem from a Bayesian viewpoint, where measurements are accumulated over time and used to form a probability density on the state, conditioned on the measurements. What results is a recursive filtering (or tracking) algorithm that optimally merges the measurements. We show by simulation and illustrative data collections that our method provides an efficient decentralized method for determining the location of a collection of moving nodes.
Nonlinear selection and the evolution of variances and covariances for continuous characters in an anole

The pattern of genetic variances and covariances among characters, summarized in the additive genetic variance‐covariance matrix, G, determines how a population will respond to linear natural selection. However, G itself also evolves in response to selection. In particular, we expect that, over time, G will evolve correspondence with the pattern of multivariate nonlinear natural selection. In this study, we substitute the phenotypic variance‐covariance matrix (P) for G to determine if the pattern of multivariate nonlinear selection in a natural population of Anolis cristatellus, an arboreal lizard from Puerto Rico, has influenced the evolution of genetic variances and covariances in this species. Although results varied among our estimates of P and fitness, and among our analytic techniques, we find significant evidence for congruence between nonlinear selection and P, suggesting that natural selection may have influenced the evolution of genetic constraint in this species.
Exploring Organizational Change and Employee Acceptance in a Local County Government

The conflict over whether or not performance appraisal and merit pay systems are effective continues to be a challenging topic for employers and employees in both privateand public-sector organizations. Public-sector organizations are under increasing political pressure to do more with less, much like their private-sector counterparts. Public-sector organizations are also under pressure to get more out of their employees than in the past. One way to do this is via a well-managed human resource system that includes effective performance appraisal and merit pay technologies.
Normative stakeholder management orientation: Business vs. non-business students

Using a sample of Spanish undergraduate students, this research contributes to stakeholder theory by developing empirical testing of normative stakeholder management orientation. It also offers empirical evidence on how the type of higher education received affects how individuals assess stakeholders’ interests. The results show that, in general, business students give less importance to the normative approach and consider it less necessary to take secondary stakeholders into account for a normative reason than their non-business counterparts do. Therefore, this study raises awareness on the influence of business education on individuals’ ethical decision-making process and suggests some possible changes for business teaching.
Video image processing greatly enhances contrast, quality, and speed in polarization-based microscopy

Video cameras with contrast and black level controls can yield polarized light and differential interference contrast microscope images with unprecedented image quality, resolution, and recording speed. The theoretical basis and practical aspects of video polarization and differential interference contrast microscopy are discussed and several applications in cell biology are illustrated. These include: birefringence of cortical structures and beating cilia in Stentor, birefringence of rotating flagella on a single bacterium, growth and morphogenesis of echinoderm skeletal spicules in culture, ciliary and electrical activity in a balancing organ of a nudibranch snail, and acrosomal reaction in activated sperm.
The neuro vector engine: Flexibility to improve convolutional net efficiency for wearable vision

Deep Convolutional Networks (ConvNets) are currently superior in benchmark performance, but the associated demands on computation and data transfer prohibit straightforward mapping on energy constrained wearable platforms. The computational burden can be overcome by dedicated hardware accelerators, but it is the sheer amount of data transfer, and level of utilization that determines the energy-efficiency of these implementations. This paper presents the Neuro Vector Engine (NVE) a SIMD accelerator for ConvNets for visual object classification, targeting portable and wearable devices. Our accelerator is very flexible due to the usage of VLIW ISA, at the cost of instruction fetch overhead. We show that this overhead is insignificant when the extra flexibility enables advanced data locality optimizations, and improves HW utilization over ConvNet vision applications. By co-optimizing accelerator architecture and algorithm loop structure, 30 Gops is achieved with a power envelope of 54mW and only 0.26mm2 silicon footprint at TSMC 40nm technology, enabling high-end visual object recognition by portable and even wearable devices.
Brain Localization and Behavioral Impact of the G-Protein-Gated K+ Channel Subunit GIRK4

Neuronal G-protein-gated potassium (KG) channels are activated by several neurotransmitters and constitute an important mode of synaptic inhibition in the mammalian nervous system. KG channels are composed of combinations of four subunits termed G protein-gated inwardly rectifying K+channels (GIRK). All four GIRK subunits are expressed in the brain, and there is a general consensus concerning the expression patterns of GIRK1, GIRK2, and GIRK3. The localization pattern of GIRK4, however, remains controversial. In this study, we exploit the negative background of mice lacking a functional GIRK4 gene to identify neuronal populations that contain GIRK4 mRNA. GIRK4 mRNA was detected in only a few regions of the mouse brain, including the deep cortical pyramidal neurons, the endopiriform nucleus and claustrum of the insular cortex, the globus pallidus, the ventromedial hypothalamic nucleus, parafascicular and paraventricular thalamic nuclei, and a few brainstem nuclei (e.g., the inferior olive and vestibular nuclei). Mice lacking GIRK4 were viable and appeared normal and did not display gross deficiencies in locomotor activity, visual tasks, and pain perception. Furthermore, GIRK4-deficient mice performed similarly to wild-type controls in the passive avoidance paradigm, a test of aversive learning. GIRK4 knock-out mice did, however, exhibit impaired performance in the Morris water maze, a test of spatial learning and memory.
Dual Metronomic Chemotherapy with Nab-Paclitaxel and Topotecan Has Potent Antiangiogenic Activity in Ovarian Cancer

There is growing recognition of the important role of metronomic chemotherapy in cancer treatment. On the basis of their unique antiangiogenic effects, we tested the efficacy of nab-paclitaxel, which stimulates thrombospondin-1, and topotecan, which inhibits hypoxia-inducible factor 1-α, at metronomic dosing for the treatment of ovarian carcinoma. In vitro and in vivo SKOV3ip1, HeyA8, and HeyA8-MDR (taxane-resistant) orthotopic models were used to examine the effects of metronomic nab-paclitaxel and metronomic topotecan. We examined cell proliferation (Ki-67), apoptosis (cleaved caspase-3), and angiogenesis (microvessel density, MVD) in tumors obtained at necropsy. In vivo therapy experiments demonstrated treatment with metronomic nab-paclitaxel alone and in combination with metronomic topotecan resulted in significant reductions in tumor weight (62% in the SKOV3ip1 model, P < 0.01 and 96% in the HeyA8 model, P < 0.03) compared with vehicle (P < 0.01). In the HeyA8-MDR model, metronomic monotherapy with either cytotoxic agent had modest effects on tumor growth, but combination therapy decreased tumor burden by 61% compared with vehicle (P < 0.03). The greatest reduction in MVD (P < 0.05) and proliferation was seen in combination metronomic therapy groups. Combination metronomic therapy resulted in prolonged overall survival in vivo compared with other groups (P < 0.001). Tube formation was significantly inhibited in RF-24 endothelial cells exposed to media conditioned with metronomic nab-paclitaxel alone and media conditioned with combination metronomic nab-paclitaxel and metronomic topotecan. The combination of metronomic nab-paclitaxel and metronomic topotecan offers a novel, highly effective therapeutic approach for ovarian carcinoma that merits further clinical development. Mol Cancer Ther; 14(12); 2677–86. ©2015 AACR.
Estimation of vehicle velocity and traffic intensity using rectified images

This paper presents an automatic method to estimate vehicle velocity and determine the number of vehicles per lane using rectified images. This approach requires the knowledge of two lengths on the ground plane and can be applied to highway scenarios that possess fairly straight lanes in areas near the camera. A scale factor is determined, in order to ascertain vehicle velocity in the sought units. This scale factor associates distances traveled on the image plane with distances on the ground plane and can be obtained by identifying the period and location of the striped highway lanes on the rectified background image. Once the previously referred lines are located it is then possible to locate the highway lane boundaries and, therefore, determine the mean vehicle velocity of each lane.
Proceedings of the Fourth Workshop on Explicit Substitutions Theory and Applications (WESTAPP '01)

This report contains the proceedings of the fourth Workshop on Explicit Substitutions Theory and Applications. Prior events took place at Tsukuba (1998), Trento (1999) and Norwich (2000). The aim of this workshop is to bring together researchers working on both theoretical and applied aspects of explicit substitutions, to present recent work (possibly still in progress), and to discuss new ideas and emerging trends. This year two well-known contributors to lambda-calculus explicit substitutions, Corrado Bohm and Paul-Andre Mellies, were invited to give their view on the development of the field. In addition, four papers presented new developments.