Mycorrhizal Dependency in Certain Indian Cotton Cultivars

Mycorrhizal dependencies of ten cotton cultivars were evaluated in the green houseusing completely randomized block design model. Acid-delinted seeds were sown inpolybags containing natural black soil. Plant growth, nutrient content and mycorrhizalcolonization levels were studied. Cotton cultivars exhibited mycorrhizal colonizationranging from 36.52 to 73.5 %. Plant dry weight and tissue Nitrogen content were positivelycorrelated whereas tissue Potassium was not correlated with the mycorrhization. Rootdiameter, number of root hairs and root length were varied among the cultivars. Rootdiameter was highest in the cultivar NHH 44, whereas root hair number was more in Suvin.Root hair length was maximum in the cultivar Suvin. Mycorrhizal dependency wasnegatively correlated with root hair number and root hair length. Maximum mycorrhizaldependency was exhibited by the cultivar Surya. The results showed the existence of strongmycorrhizal dependency in the cotton cultivars

Uterine contractions in rodent models and humans

Aberrant uterine contractions can lead to preterm birth and other labour complications and are a significant cause of maternal morbidity and mortality. To investigate the mechanisms underlying dysfunctional uterine contractions, researchers have used experimentally tractable small animal models. However, biological differences between humans and rodents change how researchers select their animal model and interpret their results. Here, we provide a general review of studies of uterine excitation and contractions in mice, rats, guinea pigs, and humans, in an effort to introduce new researchers to the field and help in the design and interpretation of experiments in rodent models

TRA-942: IMPUTATION OF MISSING CLASSIFIED TRAFFIC DATA DURING WINTER SEASON

Highway agencies collect traffic data to calculate traffic parameters such as Annual Average Daily Traffic (AADT), Design Hourly Volume (DHV) and then to use as input in the planning, operation and management of their highway systems. The traffic data are usually collected through traffic monitoring programs. In particular, the Weigh-in-Motion (WIM) system is one of data collection systems to capture configuration patterns of vehicle travelling on the detection area. It is learned from literatures that traffic monitoring devices are prone to be in malfunctioning and, consequently, providing erroneous or missing traffic data due to the adverse weather conditions in which they operate. It is very critical for transportation agencies to be able to estimate classified missing traffic data in high accuracy level because the truck traffic plays a crucial role in developing pavement design and evaluation long term pavement performance. Several imputation methods have been cited in the literature but none of them have been designed to impute classified traffic data missed during severe winter weather conditions. To do this, winter weather model is structured and then calibrated to relate classified traffic volume variation to weather factors (snowfall and temperature) with traffic data collected from WIM stations located on highway network of Alberta, Canada and weather data collected from weather stations nearby WIM stations. Performance of the developed weather model is compared with a nonparametric regression method namely k-Nearest Neighbour (k-NN) method in terms of several error measures. It is concluded that winter weather models show better performance in terms of error measures than k-NN method while imputing the missing classified traffic data

Muscle Synergies: Use and Validation in Clinics, Robotics, and Sports

Since understanding how the human brain generates neural commands to control muscles during motor tasks still remains an untapped question, great interest is shown in the validation and application of muscle synergies among research groups focused on the electromyography (EMG). In the last decades, the factorization of the EMG signals by means of muscle synergies has been proposed to understand the neurophysiological mechanisms related to the central nervous system ability in reducing the dimensionality of muscle control. For this reason, we planned a special issue on validation and application of the muscle synergy theory to discuss the methodological issues and to propose novel applications in clinics, robotics, and sports. The special issue achieved success among researchers as demonstrated by the large amount of submitted papers and the scientific impact of the published ones. The special issue is composed of twelve manuscripts. Three systematic reviews are included: (i) the first one is focused on the meaning of the muscle synergy theory to understand its applicability as a neurorehabilitation tool (Singh et al.); (ii) the second one is useful to understand the applications of muscle synergies in the investigation of muscle coordination during walking of poststroke patients (Seamon et al.); and (iii) the third one offers a complete overview on the tangible applications of muscle synergies in clinics, robotics, and sports (Taborri et al.). As concerns clinics, the effects of upper limb weakness and task failure, which is the inability to maintain a certain level of force during a task, on the muscle synergies are evaluated by Roh et al. and Castronovo et al., respectively. As regards robotics, the feasibility to use a muscle synergy approach to implement the control system of an upper limb exoskeleton is presented by Chiavenna et al. Moving to the sports, two papers are focused on understanding the muscle synergy organization during the execution of specific technical actions of the badminton (Matsunaga et al. and Barnamehei et al.), one paper shows the muscle synergy structure involved in stability exercises of rhythmic gymnastics (Rutkowska-Kucharska et al.), while the motor control underlying the throwing movement is studied by Cruz-Ruiz et al. Finally, two papers investigate some fundamental methodological issues; in particular concerning the influence of initialization techniques for the application of non-negative matrix factorization (Soomro et al.) and the reliability and repeatability of the methodology for extracting muscle synergies during daily life activities (Taborri et al.). We hope that this special issue can represent an important step to strengthen the use of muscle synergies to explain how the human brain organizes the muscle activation both in clinics and robotics, as well as in sports applications

Electrogenic transport and K(+) ion channel expression by the human endolymphatic sac epithelium.

The endolymphatic sac (ES) is a cystic organ that is a part of the inner ear and is connected to the cochlea and vestibule. The ES is thought to be involved in inner ear ion homeostasis and fluid volume regulation for the maintenance of hearing and balance function. Many ion channels, transporters, and exchangers have been identified in the ES luminal epithelium, mainly in animal studies, but there has been no functional study investigating ion transport using human ES tissue. We designed the first functional experiments on electrogenic transport in human ES and investigated the contribution of K(+) channels in the electrogenic transport, which has been rarely identified, even in animal studies, using electrophysiological/pharmacological and molecular biological methods. As a result, we identified functional and molecular evidence for the essential participation of K(+) channels in the electrogenic transport of human ES epithelium. The identified K(+) channels involved in the electrogenic transport were KCNN2, KCNJ14, KCNK2, and KCNK6, and the K(+) transports via those channels are thought to play an important role in the maintenance of the unique ionic milieu of the inner ear fluid

Electronic Structure of Electron-doped Sm1.86Ce0.14CuO4: Strong `Pseudo-Gap' Effects, Nodeless Gap and Signatures of Short Range Order

Angle resolved photoemission (ARPES) data from the electron doped cuprate superconductor Sm$_{1.86}$Ce$_{0.14}$CuO$_4$ shows a much stronger pseudo-gap or "hot-spot" effect than that observed in other optimally doped $n$-type cuprates. Importantly, these effects are strong enough to drive the zone-diagonal states below the chemical potential, implying that d-wave superconductivity in this compound would be of a novel "nodeless" gap variety. The gross features of the Fermi surface topology and low energy electronic structure are found to be well described by reconstruction of bands by a $\sqrt{2}\times\sqrt{2}$ order. Comparison of the ARPES and optical data from the $same$ sample shows that the pseudo-gap energy observed in optical data is consistent with the inter-band transition energy of the model, allowing us to have a unified picture of pseudo-gap effects. However, the high energy electronic structure is found to be inconsistent with such a scenario. We show that a number of these model inconsistencies can be resolved by considering a short range ordering or inhomogeneous state.Comment: 5 pages, 4 figure

Investment Opportunities Forecasting: Extending the Grammar of a GP-based Tool

In this paper we present a new version of a GP financial forecasting tool, called EDDIE 8. The novelty of this version is that it allows the GP to search in the space of indicators, instead of using pre-specified ones. We compare EDDIE 8 with its predecessor, EDDIE 7, and find that new and improved solutions can be found. Analysis also shows that, on average, EDDIE 8's best tree performs better than the one of EDDIE 7. The above allows us to characterize EDDIE 8 as a valuable forecasting tool