Stability enhancement method and experiment of orchard vehicle control

Study on orchard working vehicle rollover and tipping prediction is important to maintain vehicle stability control in complicated operation conditions of orchard. Existing rollover and tipping prediction models for vehicles can not directly apply to orchard working vehicle, which structure and loading are changing under operation. So it is necessary to move ahead study on orchard vehicle bodywork posture prediction and rollover and tipping prediction by theoretical analysis, mathematical modelling, real vehicle test and other methods. In this paper, firstly, we establish orchard working vehicle dynamic model, analyses variation of key parameters during vehicle instability state, and look for characteristic parameters of vehicle instability. Secondly, active safety control algorithm which based on posture detection of vehicle body is researched. Finally, control model is verified and optimized by scaled test

Comparison of the clonality of urothelial carcinoma developing in the upper urinary tract and those developing in the bladder

PURPOSE: To identify the origin of synchronous and metachronous urothelial carcinoma (UC) of the bladder and upper urinary tract to get a better understanding of the basic mechanism behind the multifocality of UC, which may provide a sound bases for the future development of new strategies for detection, prevention and therapy. METHODS: Six patients with UC of the bladder and synchronous or metachronous UC of the upper urinary tract were studied. Genetic analysis involving the study of loss of heterozygosity (LOH) has been evaluated on their tumours using well characterised and new markers of UC (D9S171, D9S177, D9S303 and TP53). RESULTS: Five of the six patients demonstrated informative results. Four of five (80%) of patients had synchronous or metacharonous UC tumour and showed patterns of LOH consistent with tumorigenesis from monoclonal tumour origin. One of five (20%) patients exhibited a LOH consistent with oligoclonal tumorigenesis. CONCLUSION: These findings suggest that both the monoclonal and field cancerization theory of tumorigenesis may play a role in tumors of the urothelial tract. However, more data is needed

The anti-resection activity of the X protein encoded by Hepatitis Virus B

Chronic infection of hepatitis virus B (HBV) is associated with an increased incidence of hepatocellular carcinoma (HCC). HBV encodes an oncoprotein (HBx) that is crucial for viral replication and interferes with multiple cellular activities including gene expression, histone modifications and genomic stability. To date, it remains unclear how disruption of these activities contributes to hepatocarcinogenesis. Here, we report that HBV exhibits a novel anti‐resection activity by disrupting DNA end resection, thus impairing the initial steps of homologous recombination (HR). This anti‐resection activity occurs in primary human hepatocytes (PHHs) undergoing a natural viral infection‐replication cycle, as well as in cells with integrated HBV genomes. Among the seven HBV‐encoded proteins, we identified HBx as the sole viral factor that inhibits resection. By disrupting an evolutionarily conserved Cullin4A‐DDB1‐RING type of E3 ligase, CRL4WDR70, via its H‐box, we show that HBx inhibits H2B monoubiquitylation at lysine 120 (uH2B) at double strand breaks, thus reducing the efficiency of long‐range resection. We further show that directly impairing H2B monoubiquitylation elicited tumorigenesis upon engraftment of deficient cells in athymic mice, confirming that the impairment of CRL4WDR70 function by HBx is sufficient to promote carcinogenesis. Finally, we demonstrated that lack of H2B monoubiquitylation is manifest in human HBV‐associated HCC (HBVHCC) when compared with HBV‐free HCC, implying corresponding defects of epigenetic regulation and end resection. We conclude that the anti‐resection activity of HBx induces an HR defect and genome instability and contributes to tumorigenesis of host hepatocytes

Endoribonuclease YbeY Is Essential for RNA Processing and Virulence in Pseudomonas aeruginosa

Posttranscriptional regulation plays an essential role in the quick adaptation of pathogenic bacteria to host environments, and RNases play key roles in this process by modifying small RNAs and mRNAs. We find that the Pseudomonas aeruginosa endonuclease YbeY is required for rRNA processing and the bacterial virulence in a murine acute pneumonia model. Transcriptomic analyses reveal that knocking out the ybeY gene results in downregulation of oxidative stress response genes, including the catalase genes katA and katB Consistently, the ybeY mutant is more susceptible to H2O2 and neutrophil-mediated killing. Overexpression of katA restores the bacterial tolerance to H2O2 and neutrophil killing as well as virulence. We further find that the downregulation of the oxidative stress response genes is due to defective expression of the stationary-phase sigma factor RpoS. We demonstrate an autoregulatory mechanism of RpoS and find that ybeY mutation increases the level of a small RNA, ReaL, which directly represses the translation of rpoS through the 5' UTR of its mRNA and subsequently reduces the expression of the oxidative stress response genes. In vitro assays demonstrate direct degradation of ReaL by YbeY. Deletion of reaL or overexpression of rpoS in the ybeY mutant restores the bacterial tolerance to oxidative stress and the virulence. We also demonstrate that YbeZ binds to YbeY and is involved in the 16S rRNA processing and regulation of reaL and rpoS as well as the bacterial virulence. Overall, our results reveal pleiotropic roles of YbeY and the YbeY-mediated regulation of rpoS through ReaL.IMPORTANCE The increasing bacterial antibiotic resistance imposes a severe threat to human health. For the development of effective treatment and prevention strategies, it is critical to understand the mechanisms employed by bacteria to grow in the human body. Posttranscriptional regulation plays an important role in bacterial adaptation to environmental changes. RNases and small RNAs are key players in this regulation. In this study, we demonstrate critical roles of the RNase YbeY in the virulence of the pathogenic bacterium Pseudomonas aeruginosa We further identify the small RNA ReaL as the direct target of YbeY and elucidate the YbeY-regulated pathway on the expression of bacterial virulence factors. Our results shed light on the complex regulatory network of P. aeruginosa and indicate that inference with the YbeY-mediated regulatory pathway might be a valid strategy for the development of a novel treatment strategy.</p

Development, implementation, and evaluation of a competency-based didactic and simulation-focused boot camp for incoming urology residents: Report of the first three years

Introduction: The Royal College of Physicians and Surgeons of Canada’s Competence by Design (CBD) initiative presents curricula challenges to ensure residents gain proficiency while progressing through training. To prepare first-year urology residents (R1s), we developed, implemented, and evaluated a didactic and simulation-focused boot camp to implement the CBD curriculum. We report our experiences and findings of the first three years. Methods: Urology residents from two Canadian universities participated in the two-day boot camp at the beginning of residency. Eleven didactic and six simulation sessions allowed for instruction and deliberate practice with feedback. Pre-and post-course multiple-choice questionnaires (MCQs) and an objective structured clinical exam (OSCE) evaluated knowledge and skills uptake. For initial program evaluation, three R2s served as historical controls in year 1. Results: Nineteen residents completed boot camp. The mean age was 26.4 (±2.8) and 13 were male. Participants markedly improved on the pre- and post-MCQs (year 1: 62% and 91%; year 2: 55% and 89%; year 3: 58% and 86%, respectively). Participants scored marginally higher than the controls on four of the six OSCE stations. OSCE scores remained \u3e88% over the three cohorts. All participants reported higher confidence levels post-boot camp and felt it was excellent preparation for residency. Conclusions: During its first three years, our urology boot camp has demonstrated high feasibility and utility. Knowledge and technical skills uptake were established via MCQ and OSCE results, with participants’ scores near or above those of R2 controls. This boot camp will remain in our CBD curriculum and can provide a framework for other urology residency programs

Plasmonic antenna hybrids for active control in the near and midinfrared

Resumen del trabajo presentado a la Spanish Conference on Nanophotonics (Conferencia Española de Nanofotónica-CEN), celebrada en Donostia-San Sebastián (España) del 3 al 5 de octubre de 2018.Hybrid platforms combining metallic plasmonic nanoantennas (NAs) and materials with interesting properties as phase-change or spintronics offer excellent technological opportunities for active plasmonics, as they can provide large changes in their optical response. In this talk I will demostrate first how gold NAs grown on vanadium dioxie (VO2), characterized by a reversible insulator-to-metal transition (IMT) at around 68ºC, can improve the performance of this material by providing an efficient enhancement mechanism for both the optically induced excitation and readout. Using picosecond laser pulses a highly localized phase transition is driven in nanoscale regions around the NAs. These antennas-VO2 hybrid solutions provide a conceptual framework to merge field localization and phase transition enabling nanoscale optical memory functionalities. In the second part I will show how the combination of Au microantenna arrays with a Ni81Fe19/Au multilayer supports provide metamaterial platforms with new functionalities. In this case, the plasmon resonance sustained by the NAs alliate with the GMR and MRE effects of the multilayer to allow low magnetic-field controlled modulation in the mid-infrared, where light modulation is very challenging. This approach establishes a roadmap for spintronically-controlled devices in the whole mid-IR to THz band.Peer Reviewe

Partitionnement de grands flux de données d'images hyperspectrales

With the development of automated and optimized decision-making systems, large data stream partitioning, which does not rely on training samples, has attracted more and more attention. In the stat-of-the-art, a majority of data stream partitioning methods are parametric which require the specification of one or more user-defined parameters and/or the number of classes before the partitioning process. Indeed, in practical applications, obtaining prior information about the dataset and determining optimal parameter values in advance can be challenging. Therefore, our research focuses on the development of an unsupervised and non-parametric method which is easy to apply by users, benefiting from the fact that it eliminates the need for prior information and obviates the requirement for empirical parameters tuning. The developed method can autonomously estimate the number of classes and partition the data stream. It is efficient to partition large and high spatial and spectral dimensional data streams, especially hyperspectral data streams. Our proposed method was assessed on real-world and synthetic databases. According to several objective evaluation criteria, it outperforms the five compared data stream partitioning methods (three parametric unsupervised methods, one semi-supervised method and one supervised method using active learning).Avec le développement de systèmes de prise de décision automatisés et optimisés, le partitionnement de grands flux de données, qui ne dépend pas d'échantillons d'apprentissage, attire de plus en plus l'attention. Dans l'état de l'art, la majorité des méthodes de partitionnement de flux de données sont paramétriques, ce qui nécessite la spécification d'un ou plusieurs paramètres définis par l'utilisateur et/ou du nombre de classes avant le processus de partitionnement. En effet, dans les applications pratiques, obtenir des connaissances a priori sur l'ensemble de données et déterminer les valeurs de paramètres optimales à l'avance est un défi. Par conséquent, notre recherche se concentre sur le développement d'une méthode non supervisée et non paramétrique facile à utiliser par les utilisateurs, bénéficiant du fait qu'elle élimine le besoin de connaissances a priori et supprime la nécessité de régler les paramètres de manière empirique. La méthode développée peut estimer de manière autonome le nombre de classes et partitionner le flux de données. Elle est efficace pour partitionner un flux de données de grandes tailles spatiale et spectrale, en particulier les flux de données hyperspectraux. La méthode proposée a été évaluée sur des bases de données réelles et synthétiques. Selon plusieurs critères d'évaluation objectifs, elle surpasse les cinq méthodes de partitionnement de flux de données comparées (trois méthodes paramétriques non supervisées, une méthode semi-supervisée et une méthode supervisée utilisant l'apprentissage actif)

Partitionnement de grands flux de données d'images hyperspectrales

With the development of automated and optimized decision-making systems, large data stream partitioning, which does not rely on training samples, has attracted more and more attention. In the stat-of-the-art, a majority of data stream partitioning methods are parametric which require the specification of one or more user-defined parameters and/or the number of classes before the partitioning process. Indeed, in practical applications, obtaining prior information about the dataset and determining optimal parameter values in advance can be challenging. Therefore, our research focuses on the development of an unsupervised and non-parametric method which is easy to apply by users, benefiting from the fact that it eliminates the need for prior information and obviates the requirement for empirical parameters tuning. The developed method can autonomously estimate the number of classes and partition the data stream. It is efficient to partition large and high spatial and spectral dimensional data streams, especially hyperspectral data streams. Our proposed method was assessed on real-world and synthetic databases. According to several objective evaluation criteria, it outperforms the five compared data stream partitioning methods (three parametric unsupervised methods, one semi-supervised method and one supervised method using active learning).Avec le développement de systèmes de prise de décision automatisés et optimisés, le partitionnement de grands flux de données, qui ne dépend pas d'échantillons d'apprentissage, attire de plus en plus l'attention. Dans l'état de l'art, la majorité des méthodes de partitionnement de flux de données sont paramétriques, ce qui nécessite la spécification d'un ou plusieurs paramètres définis par l'utilisateur et/ou du nombre de classes avant le processus de partitionnement. En effet, dans les applications pratiques, obtenir des connaissances a priori sur l'ensemble de données et déterminer les valeurs de paramètres optimales à l'avance est un défi. Par conséquent, notre recherche se concentre sur le développement d'une méthode non supervisée et non paramétrique facile à utiliser par les utilisateurs, bénéficiant du fait qu'elle élimine le besoin de connaissances a priori et supprime la nécessité de régler les paramètres de manière empirique. La méthode développée peut estimer de manière autonome le nombre de classes et partitionner le flux de données. Elle est efficace pour partitionner un flux de données de grandes tailles spatiale et spectrale, en particulier les flux de données hyperspectraux. La méthode proposée a été évaluée sur des bases de données réelles et synthétiques. Selon plusieurs critères d'évaluation objectifs, elle surpasse les cinq méthodes de partitionnement de flux de données comparées (trois méthodes paramétriques non supervisées, une méthode semi-supervisée et une méthode supervisée utilisant l'apprentissage actif)

Research Concerning the Impact of Sino-U.S. Rapprochement on U.S. Foreign Policy Towards Korea in 1972

학위논문(석사) --서울대학교 국제대학원 :국제학과(한국학전공),2009.8.Maste