Miracle-dz/UniFAR-FTUs huggingface dataset:
Ieee Transactions on Intelligent Transportation Systems 1 Monocular Road Terrain Detection by Combining Visual and Spatial Information

—For future driver assistance systems and autonomous vehicles, the road course, i.e., the width and shape of the driving path, is an important source of information. In this contribution we introduce a new hierarchical two-stage approach for learning the spatial layout of road scenes. In the first stage, base classifiers analyze the local visual properties of patches extracted from monocular camera images and provide metric confidence maps. We use classifiers for road appearance, boundary appearance, and lane-marking appearance. The core of the proposed approach is the computation of SPatial RAY (SPRAY) features from each metric confidence map in the second stage. A boosting classifier selecting discriminative SPRAY features can be trained for different types of road terrain and allows to capture the local visual properties together with their spatial layout in the scene. In this contribution, the extraction of road area and ego-lane on inner city video streams is demonstrated. Especially the detection of the ego-lane is a challenging semantic segmentation task showing the power of SPRAY features, because on a local appearance level, the ego-lane is not distinguishable from other lanes. We have evaluated our approach operating at 20 Hz on a GPU on a publicly available dataset, demonstrating the performance on a variety of road types and weather conditions.
Study on the Different Expression of Molecular Markers between Cardiac Cancer and Distal Gastric Cancer and Their Correlations with Clinicopathological Features

Background and Aim: Currently, few studies have reported the different expression of molecular markers between distal gastric cancer and cardiac cancer. Here, we sought to make an investigation about it by a retrospective analysis. Methods: The expression of 8 proteins, including epidermal growth factor receptor, glutathione S-transferase π (GST-π), cyclin D1, Neu/Her-2, C-myc, p53, p27 and p21, were evaluated in 110 cases with cardiac cancer and 101 cases with distal gastric cancer who underwent curative surgery at the Cancer Hospital, Fudan University, in 2005 by immunohistochemistry method. Results: The TNM stage, differentiation grade, invasion depth and lymph node metastasis were significantly different between cardiac cancer and distal gastric cancer. p21 (p = 0.034), Neu (p = 0.017), and GST-π (p = 0.003) were expressed in relatively higher levels in cardiac cancer than in distal gastric cancer. Furthermore, the clinical pathological parameters were significantly correlated with the expression of molecules mentioned above. Conclusion: Different molecular mechanisms may be involved in the tumorigenesis and development of cardiac cancer and distal gastric cancer.
T-cell receptor-induced JNK activation requires proteolytic inactivation of CYLD by MALT 1

Jens Staal, Yasmine Driege, Tine Bekaert, Annelies Demeyer, David Muyllaert, Petra Van Damme, Kris Gevaert and Rudi Beyaert* Department of Molecular Biomedical Research, Unit of Molecular Signal Transduction in Inflammation, VIB, Zwijnaarde, Ghent, Belgium, Department of Biomedical Molecular Biology, Ghent University, Zwijnaarde, Ghent, Belgium, Department of Medical Protein Research, VIB, Ghent, Belgium and Department of Biochemistry, Ghent University, Ghent, Belgium
Mutation of the Arabidopsis NRT1.5 Nitrate Transporter Causes Defective Root-to-Shoot Nitrate Transport[W][OA]

Little is known about the molecular and regulatory mechanisms of long-distance nitrate transport in higher plants. NRT1.5 is one of the 53 Arabidopsis thaliana nitrate transporter NRT1 (Peptide Transporter PTR) genes, of which two members, NRT1.1 (CHL1 for Chlorate resistant 1) and NRT1.2, have been shown to be involved in nitrate uptake. Functional analysis of cRNA-injected Xenopus laevis oocytes showed that NRT1.5 is a low-affinity, pH-dependent bidirectional nitrate transporter. Subcellular localization in plant protoplasts and in planta promoter-β-glucuronidase analysis, as well as in situ hybridization, showed that NRT1.5 is located in the plasma membrane and is expressed in root pericycle cells close to the xylem. Knockdown or knockout mutations of NRT1.5 reduced the amount of nitrate transported from the root to the shoot, suggesting that NRT1.5 participates in root xylem loading of nitrate. However, root-to-shoot nitrate transport was not completely eliminated in the NRT1.5 knockout mutant, and reduction of NRT1.5 in the nrt1.1 background did not affect root-to-shoot nitrate transport. These data suggest that, in addition to that involving NRT1.5, another mechanism is responsible for xylem loading of nitrate. Further analyses of the nrt1.5 mutants revealed a regulatory loop between nitrate and potassium at the xylem transport step.
Hepcidin and the Iron-Infection Axis

Double-Edged Iron Hepcidin is a small peptide hormone discovered by three groups investigating iron-regulated liver genes and antimicrobial peptides. This new hormone turned out not only to regulate iron but also to have homology with peptides required for innate immune responses. Drakesmith and Prentice (p. 768) review the importance of hepcidin during infection, explaining how it is involved in withholding iron from microbial pathogens to curtail replication and how intracellular bacteria are able to thwart this host response. Recent work highlights the potential hazards of iron-supplementation in infection, particularly in malaria, whereby an overload of iron, meant to treat malaria-induced anemia, may negate the protective effects of hepcidin. Iron lies at the center of a battle for nutritional resource between higher organisms and their microbial pathogens. The iron status of the human host affects the pathogenicity of numerous infections including malaria, HIV-1, and tuberculosis. Hepcidin, an antimicrobial-like peptide hormone, has emerged as the master regulator of iron metabolism. Hepcidin controls the absorption of dietary iron and the distribution of iron among cell types in the body, and its synthesis is regulated by both iron and innate immunity. We describe how hepcidin integrates signals from diverse physiological inputs, forming a key molecular bridge between iron trafficking and response to infection.
Security in Bluetooth, RFID and wireless sensor networks

Recently, new families of wireless ad hoc networks have emerged for specialized applications--- personal area networks. Wireless personal area networks (WPAN) is rapidly gaining popularity. A wide variety of traditional computing devices and embedded Internet appliances are networked around us. However, due to the broadcast nature of these networks and the heterogeneity of devices on these networks, new security problems will arise, because the different types of devices have different capabilities and security requirements. In this paper, an overview of security issues like attacks and its countermeasures for wireless personal area networks such as Bluetooth, RFID and wireless sensor networks has been provided.
Update on sudden infant death syndrome.

PURPOSE OF REVIEW With the introduction of the Back to Sleep campaign by the American Academy of Pediatrics in 1992, the incidence of Sudden infant death syndrome has decreased by almost 50%. Despite this success, SIDS continues to be the most common cause of unexplained infant death in Western countries. This article will briefly review the definition, etiology, and risk factors of SIDS. Attention will then focus on ways to target specific associated risk factors and at risk populations to promote a continued downward trend in the number of SIDS deaths. RECENT FINDINGS Recent literature in SIDS research has focused on identifying infants at continued risk for SIDS. Children attending child care centers have an increased risk for SIDS, which is of particular concern as the number of infants in child care continues to rise. The reasons for this, along with strategies to decrease this risk, will be reviewed. In addition, the SIDS rate among black infants continues to be more than twice that of white infants. A review of the reasons for this disparity and ways to intervene through targeted campaigns will be discussed. Recent data has also suggested that the prevention of SIDS should not be an indication for use of home cardiorespiratory monitoring. The use of home monitoring may be warranted for some infants and will be reviewed. SUMMARY Our jobs as pediatricians should be to ensure that the incidence of SIDS continues to decline. This can be done through parent education at each and every well child visit, lobbying to enforce state law to implement SIDS education campaigns for child care centers and within African-American communities, and continued review of the most current literature in SIDS research to keep ourselves current and well informed.
The Visible Empathy of Infants and Toddlers

Katherine, eight months old, sits on the carpet in the middle of a bustling child care room. She has been mesmerized by a pop-up toy but glances up during her play and seems frightened by the commotion around her. Brandon, 19 months old, who sits nearby, notices her change in mood. Katherine begins to cry. Brandon toddles toward her and gently leans over to whisper in her ear. He babbles to her in an unmistakable “motherese” tone, seeming to convey “Don’t worry” while also gently patting her hand. He comforts her in the same way the teachers comfort the children.
How to Generate Cyclically Permutable Codes From Cyclic Codes

On the basis of the characteristics of cyclic codes, the codeword space can be partitioned into small subspaces where cyclically shifted codewords of a particular codeword occupy the same subspace. A cyclically permutable code generates codewords belonging to each subspace. However, no approach for the efficient construction of cyclically permutable code from binary cyclic codes has been proposed thus far. In this study, we propose an approach for the efficient and systematic construction of a cyclically permutable code from a cyclic code by utilizing an algebraic property. The proposed coding method improves the robustness of watermarking, particularly for video frames, against a clipping attack
Agent-Based Meta-Heuristic Approach to Discrete Optimization

The paper presents an idea of agent-based meta-heuristic integrating a computational optimization system (evolutionary multi-agent system) with ant colony optimization technique. In the proposed model, chosen parameters of ant colonies may be encoded as genotypes and subjected to evolution process carried out by agents. The goal of the whole system is to search for the best solution of the discrete optimization problem based on the results of the ant colonies run using different parameters. The proposed concept forms a base for further research on bringing different interactions known in ant-colony optimization to the inter-agent level. The considerations are illustrated with preliminary experimental results obtained for parallel ant system solving quadratic assignment problem.
Zero-data Learning of New Tasks

We introduce the problem of zero-data learning, where a model must generalize to classes or tasks for which no training data are available and only a description of the classes or tasks are provided. Zero-data learning is useful for problems where the set of classes to distinguish or tasks to solve is very large and is not entirely covered by the training data. The main contributions of this work lie in the presentation of a general formalization of zero-data learning, in an experimental analysis of its properties and in empirical evidence showing that generalization is possible and significant in this context. The experimental work of this paper addresses two classification problems of character recognition and a multitask ranking problem in the context of drug discovery. Finally, we conclude by discussing how this new framework could lead to a novel perspective on how to extend machine learning towards AI, where an agent can be given a specification for a learning problem before attempting to solve it (with very few or even zero examples).
Paradigms for Preclinical Investigations of Female Sexual Function and Dysfunction (HSDD and FSAD)

A prerequisite for successful discovery of treatment options for female sexual dysfunction is a deeper understanding of sexual function per se, e.g. which physiological systems are involved, and what goes wrong in a dysfunctional state. The availability of animal models, which capture the physiological underpinnings of a disorder and have been shown to respond to existing clinical treatments are a major success factor in this endeavor. For example, the translational ability of penile erection models are extremely good, since they have high predictive value for drugs used to treat erectile dysfunction. Predictive validity of models of female sexual dysfunction is less well established. However, results from recent efforts to back-translate effects from drugs that have shown efficacy in clinical trials into laboratory animals provide promising starting points for a better disease understanding and model validation. This chapter will briefly outline those models that have potential in helping understand female sexual function and dysfunction, followed by three examples (flibanserin, bremolantide, apomorphine) of how clinically efficacious compounds contributed to elucidate the physiology and pharmacology underlying both the natural and pathological states (Bechara et al. 2004; Caruso et al. 2004b; Clayton et al. 2010; Safarinejad 2008) of arousal and desire disorders, the major indications in terms of prevalence (Johannes et al. 2009). Modeling a complex human behavior in the laboratory imparts many challenges. Only a few fundamental issues faced in the laboratory are similar in the clinic – ie. the necessity to define a ‘normal’ range of responses for a given function before attempting to assess a dysfunctional range. In the clinic, questionnaire based tools have been developed, that can define ‘healthy’ and ‘dysfunctional’ states of sexual behavior within human populations. Furthermore, the two behavioral domains ‘desire’ and ‘arousal’ become distinguishable when dysfunction is present (DeRogatis et al. 2011). This can principally be achieved in the lab too, since each species has a clear set of behaviors used to solicit sexual contact. Although it is not always easy to separate desire from arousal in rodents as these two components of the sexual response are temporally connected in a natural setting, they can be isolated and studied as distinct physiological pathways. However, in order to have translational relevance, such laboratory studies must address measures aligned with those used clinically. With this request a number of issues arise that are unique to working with
Guaranteed Outlier Removal with Mixed Integer Linear Programs

The maximum consensus problem is fundamentally important to robust geometric fitting in computer vision. Solving the problem exactly is computationally demanding, and the effort required increases rapidly with the problem size. Although randomized algorithms are much more efficient, the optimality of the solution is not guaranteed. Towards the goal of solving maximum consensus exactly, we present guaranteed outlier removal as a technique to reduce the runtime of exact algorithms. Specifically, before conducting global optimization, we attempt to remove data that are provably true outliers, i.e., those that do not exist in the maximum consensus set. We propose an algorithm based on mixed integer linear programming to perform the removal. The result of our algorithm is a smaller data instance that admits a much faster solution by subsequent exact algorithms, while yielding the same globally optimal result as the original problem. We demonstrate that overall speedups of up to 80% can be achieved on common vision problems1.
Self-administration of morphine, DAMGO, and DPDPE into the ventral tegmental area of rats

Intracranial self-administration of mu- and delta-opioid agonists was demonstrated in male Long-Evans rats. Independent groups were allowed to lever-press for ventral tegmental area (VTA) microinfusions of morphine, the selective mu agonist [D-Ala2,N-Me-Phe4-Gly5-ol]- enkephalin (DAMGO), the selective delta-agonist [D-Pen2,D-Pen5]- enkephalin (DPDPE), or ineffective drug vehicle. Morphine, DAMGO, and DPDPE were each effective in establishing and maintaining lever- pressing habits. Lever-pressing responses were extinguished during a session when vehicle was substituted for drug, and reinstated when drug reinforcement was reestablished. Thus, it appears that VTA mu- and delta-opioid receptors are each involved in reinforcement of opiate self-administration. The effective dose of DAMGO--both for establishing and for maintaining the lever-press habit--was 100 times lower than the effective doses for DPDPE and morphine, suggesting that the major contribution of VTA mechanisms to intravenous heroin self- administration involves an action on mu-opioid receptors.
A 146 mm/sup 2/ 8 Gb NAND flash memory with 70 nm CMOS technology

A 146 mm/sup 2/ 8 Gb NANO flash memory with 4-level programmed cells is fabricated in a 70 nm CMOS technology. A single-sided pad architecture and extended block-addressing scheme without redundancy is adopted for die size reduction. The programming throughput is 6 MB/s and is comparable to binary flash memories.
No reference image quality assessment based on statistical distribution of local Sub-Image-Similarity

The research on no reference image quality assessment (NR IQA) is the most attractive one in the area of image quality perception. In this paper, we propose to use the statistical distribution of local Sub-Image-Similarity (SIS) measures for NR IQA model design. Here the mean and the difference properties among the local SIS measurements in different directions are synthesized into five quality labels to depict the perceptual quality property of deteriorated images. The proposed NR IQA model is developed based on the statistical distribution of quality labels over whole image, via a SVM regression. Experiments show that the proposed model performs best according to the predictive accuracy when compared to the published NR IQA models, and works stably with different parameter selections and cross database evaluations.
Clinical Significance of Vascular Endothelial Growth Factor C Expression and Angiogenesis at the Deepest Invasive Site of Advanced Colorectal Carcinoma

Aim: Vascular endothelial growth factor C (VEGF-C) is known to be associated with the development of the lymphatic vascular system. The aim of this study was to elucidate the clinical significance of VEGF-C expression and microvessel density (MVD) at the deepest invasive site in advanced colorectal carcinoma (CRC). Methods: 152 patients who had undergone surgical resection for advanced CRC entered this study. VEGF-C expression was examined immunohistochemically with anti-VEGF-C polyclonal antibody C-20. Tumor MVD was determined immunohistochemically with anti-CD34 antibody. VEGF-C expression was defined as positive if distinct staining of the cytoplasm was observed in at least 10% of tumor cells at the deepest invasive site, central portion and superficial part of the tumor. MVD was estimated by averaging the count of three ×400 fields in the most vascular area at the deepest invasive site. Results: VEGF-C expression was detected in 71 of 152 lesions (46.7%) at the deepest invasive site. VEGF-C expression correlated significantly with poorer histologic grade, depth of invasion, lymphatic invasion, lymph node metastasis, venous invasion, liver metastasis and Duke’s stage. At the central portion and superficial part, there were no significant differences between VEGF-C expression and clinicopathological findings. VEGF-C expression at the deepest invasive site also correlated significantly with MVD. In cases with curative surgery, patients with VEGF-C expression at the deepest invasive site had a significantly poorer prognosis than those without VEGF-C expression. Furthermore, prognosis for patients with both VEGF-C expression and high MVD at the deepest invasive site was significantly poorer than that of patients without VEGF-C expression and with low MVD. Multivariate analysis with logistic regression for 5-year survival in patients with curative surgery showed that lymph node metastasis and VEGF-C expression were significant risk factors. Conclusions: VEGF-C expression at the deepest site of tumor invasion can be a useful predictor of poor prognosis in advanced CRC and show a close relation to angiogenesis.
Analysis of heart rate during a tennis training session and its relationship with heart-healthy index.

The control of heart rate with pulsometer is a good marker for evaluating the response of heart to exercise. The aims of this research were: first, to assess heart rate obtained during a tennis training, changing the intensity at those stages in which the player is hitting the ball, through various forms of displacement: 1) view if there are significant differences between them and 2) see if they get heart cardiac frequency. 45 students were monitored for 4th and 5th of Science Degree in Physical Activity and Sport (20.98 ± 3.67 years). They do a session with four areas of intensity (walking slowly, walking fast, jogging and running). The cardiac response to exercise showed that these areas have significant differences among themselves and are within the areas marked as hearthealthy.
Iterative Hierarchical Optimization for Misspecified Problems (IHOMP)

For complex, high-dimensional Markov Decision Processes (MDPs), it may be necessary to represent the policy with function approximation. A problem is misspecified whenever, the representation cannot express any policy with acceptable performance. We introduce IHOMP : an approach for solving misspecified problems. IHOMP iteratively learns a set of context specialized options and combines these options to solve an otherwise misspecified problem. Our main contribution is proving that IHOMP enjoys theoretical convergence guarantees. In addition, we extend IHOMP to exploit Option Interruption (OI) enabling it to decide where the learned options can be reused. Our experiments demonstrate that IHOMP can find near-optimal solutions to otherwise misspecified problems and that OI can further improve the solutions.