All roads lead to the places of your interest: An on-demand, ride-sharing visitor transport service

Successful visitor transport within large tourist sites should balance visitor experience and operating costs. Inspired by the model of sharing economy, we design a “user-centered” intelligent visitor transport system to improve the efficiency and quality of experience of transport service in large tourist sites. The system’s core approach is a three-stage heuristic model based on Pareto optimality. Results of the proposed service indicate a drastic reduction of visitor delay time and an improvement in energy efficiency. The proposed scheduling schemes for organizers are more diversified and adaptable than the existing service

Plant regeneration system from cotyledons-derived calluses cultures of Stylosanthes guianensis cv. ‘Reyan 2’

The objective of this study was to successfully establish plant regeneration system with cotyledons of Stylosanthes guianensis Sw. cv. ‘Reyan 2’ as explants. In this study, the following results were obtained; (1) the highest rates of callus induction on medium MS with 3.0 mg L-1 2, 4-D with cotyledons as explants were 74%. The above medium of formulation was adopted for subculture; (2) the highest rates of callus differentiation medium MS with 3.0 mg L-1 6-BA with cotyledons as explants was 66%; (3) the optimum medium of shoot growth was MS medium plus 1.0 mg L-1 6-BA, 0.5 mg L-1 NAA and 0.4 mg L-1 GA; (4) the rooting rate was 60% on optimum rooting medium with 0.2 mg L-1 NAA; (5) the survival rate of plant transplanting was 70% after transferred to pots with garden soil. In conclusion, the efficient plant regeneration system developed here will be helpful for rapid micropropagation and further genetic improvement in S. guianensis Sw. cv. ‘Reyan 2’.Key words: Stylosanthes guianensis Sw. cv. Reyan 2, callus, cotyledons, plant regeneration

The cumulative effects of known susceptibility variants to predict primary biliary cirrhosis risk.

Multiple genetic variants influence the risk for development of primary biliary cirrhosis (PBC). To explore the cumulative effects of known susceptibility loci on risk, we utilized a weighted genetic risk score (wGRS) to evaluate whether genetic information can predict susceptibility. The wGRS was created using 26 known susceptibility loci and investigated in 1840 UK PBC and 5164 controls. Our data indicate that the wGRS was significantly different between PBC and controls (P=1.61E-142). Moreover, we assessed predictive performance of wGRS on disease status by calculating the area under the receiver operator characteristic curve. The area under curve for the purely genetic model was 0.72 and for gender plus genetic model was 0.82, with confidence limits substantially above random predictions. The risk of PBC using logistic regression was estimated after dividing individuals into quartiles. Individuals in the highest disclosed risk group demonstrated a substantially increased risk for PBC compared with the lowest risk group (odds ratio: 9.3, P=1.91E-084). Finally, we validated our findings in an analysis of an Italian PBC cohort. Our data suggested that the wGRS, utilizing genetic variants, was significantly associated with increased risk for PBC with consistent discriminant ability. Our study is a first step toward risk prediction for PBC

Post-fire residual mechanical properties of steel butt weld — Experimental study

Butt weld connection is one of the most commonly used connection types in steel structures, and its post-fire mechanical property is crucial for the estimation of the residual mechanical capacity of steel structures after building fires. To study the mechanical properties of butt weld connections after being exposed to high temperatures, Q235 and Q345 butt weld specimens were designed, heated to various high temperatures between 400 °C and 800 °C, and then naturally cooled to room temperature. Tensile tests were conducted on these butt weld specimens to obtain the force–displacement curves and relevant mechanical properties (yield and ultimate strengths) at various temperatures. The following conclusions were obtained from the test results: (1) The post-fire mechanical properties of the butt weld specimens were affected by material grade and heating temperature; (2) when the temperature exceeded 600 °C, the yield and ultimate strengths of the Q235 and Q345 butt weld specimens began to decrease; the strength reduction of the latter was greater than that of the former; (3) when the temperature was 800 °C, the yield strength and ultimate strength of Q235 decreased to 87% and 91% of the ambient-temperature yield and ultimate strengths, respectively; and (4) the yield and ultimate strengths of Q345 decreased to 83% and 87% of those at room temperature. Computational formulas for the yield and ultimate strengths of the butt weld specimens at high temperatures were also fitted and verified with test data to provide a safety evaluation method for steel structures after a fire

Distributed parameter estimation in unreliable sensor networks via broadcast gossip algorithms

In this paper, we present an asynchronous algorithm to estimate the unknown parameter under an unreliable network which allows new sensors to join and old sensors to leave, and can tolerate link failures. Each sensor has access to partially informative measurements when it is awakened. In addition, the proposed algorithm can avoid the interference among messages and effectively reduce the accumulated measurement and quantization errors. Based on the theory of stochastic approximation, we prove that our proposed algorithm almost surely converges to the unknown parameter. Finally, we present a numerical example to assess the performance and the communication cost of the algorithm.This work was supported in part by the National Natural Science Foundation of China under Grant 61503308 and Grant 61472331, in part by the Natural Science Foundation Project of Chongqing CSTC 2015jcyjA40043, and in part by Fundamental Research Funds for the Central Universities under Grant SWU114036. This publication was made possible by NPRP grant #4-1162-1-181 from the Qatar National Research Fund (a member of Qatar Foundation)

Documentation of a new hypotrich species in the family Amphisiellidae, Lamtostyla gui n. sp. (Protista, Ciliophora) using a multidisciplinary approach

An integrated approach considering both morphologic and molecular data is now required to improve biodiversity estimations and provide more robust systematics interpretations in hypotrichs, a highly differentiated group of ciliates. In present study, we document a new hypotrich species, Lamtostyla gui n. sp., collected from Chongming wetland, Shanghai, China, based on investigations using living observation, protargol staining, scanning and transmission electron microscopy, and gene sequencing. The new species is mainly recognized by having a short amphisiellid median cirral row composed of four cirri, three frontoventral cirri, three dorsal kinetids, four to eight macronuclear nodules, and small colorless cortical granules distributed as rosettes around dorsal bristles. Transmission electron microscope observation finds the associated microtubules of cirri and pharyngeal discs of L. gui are distinct from those in other hypotrichs. Morphogenesis of this species indicates that parental adoral membranelles retained intact or partial renewed is a potential feature to separate Lamtostyla granulifera-group and Lamtostyla lamottei-group. Phylogenetic analysis based on small subunit ribosomal RNA (rRNA) gene shows that this molecular marker is not useful to resolve phylogenetic relationships of the genus Lamtostyla, as well as many other hypotrichous taxa. We additionally characterize the internal transcribed spacers (ITS) region and the almost complete large subunit rRNA, which will be essential for future studies aimed at solving phylogenetic problems of Lamtostyla, or even the family Amphisiellidae. As a final remark, the critical screening of GenBank using ITS genes of our organism allows us to recognize a large amount of hypotrichous sequences have been misclassified as fungi. This observation suggests that hypotrichs could be frequently found in fungi-rich environment and overlooked by fungal specialists

Deep Learning in Lane Marking Detection: A Survey

Lane marking detection is a fundamental but crucial step in intelligent driving systems. It can not only provide relevant road condition information to prevent lane departure but also assist vehicle positioning and forehead car detection. However, lane marking detection faces many challenges, including extreme lighting, missing lane markings, and obstacle obstructions. Recently, deep learning-based algorithms draw much attention in intelligent driving society because of their excellent performance. In this paper, we review deep learning methods for lane marking detection, focusing on their network structures and optimization objectives, the two key determinants of their success. Besides, we summarize existing lane-related datasets, evaluation criteria, and common data processing techniques. We also compare the detection performance and running time of various methods, and conclude with some current challenges and future trends for deep learning-based lane marking detection algorithm