The interaction of kinetin and indolebutic acid on the rooting of cuttings

The object of this study is to understand what effect the interaction of indolebutyric acid and kinetin would have on the rooting of cuttings. If an interaction should show up it might provide a clue for methods of inducing roots on cuttings which are difficult to root. In some cases, as noticed in tobacco pith tissue, kinetin increases callus formation and rooting from callus tissue is sometimes easier than from more differentiated tissue

Discretized Bayesian pursuit – A new scheme for reinforcement learning

The success of Learning Automata (LA)-based estimator algorithms over the classical, Linear Reward-Inaction ( L RI )-like schemes, can be explained by their ability to pursue the actions with the highest reward probability estimates. Without access to reward probability estimates, it makes sense for schemes like the L RI to first make large exploring steps, and then to gradually turn exploration into exploitation by making progressively smaller learning steps. However, this behavior becomes counter-intuitive when pursuing actions based on their estimated reward probabilities. Learning should then ideally proceed in progressively larger steps, as the reward probability estimates turn more accurate. This paper introduces a new estimator algorithm, the Discretized Bayesian Pursuit Algorithm (DBPA), that achieves this. The DBPA is implemented by linearly discretizing the action probability space of the Bayesian Pursuit Algorithm (BPA) [1]. The key innovation is that the linear discrete updating rules mitigate the counter-intuitive behavior of the corresponding linear continuous updating rules, by augmenting them with the reward probability estimates. Extensive experimental results show the superiority of DBPA over previous estimator algorithms. Indeed, the DBPA is probably the fastest reported LA to date

Enhancing Control of Built Assets through Computer Aided Design - Past, Present and Emerging Trends

This paper presents the trends in Computer aided drafting and design within the Architecture, Engineering, Construction and Operations (AECO) industry by examining past, present and emerging technologies, standards, deliverables and stakeholders involved. The use of Computer Aided Design (CAD) has evolved from the drawing board in the pre 1970s, through two dimensional CAD in the 1980s to three dimensional CAD in the 1990s. In the year 2000 Building Information Modelling (BIM) became increasingly popular but there have been significant barriers to its adoption, few of them being interoperability and the lack of involvement of key stakeholders. To overcome these and progress to an Integrated Project Delivery (IPD) ecosystem, it is recommended that the industry should engage property owners and policy makers who can influence the sustained use of interoperable products and processes in the built environment. The acronym CAD has been widely used in the industry as Computer aided- design but in this essay, CAD has been used to reflect the use of computers for drafting, design, analysis, simulation and collaboration

An unusual presentation of catastrophic antiphospholipid antibody syndrome in the background of sepsis

A 59-year-old female presented with complaints of gangrenous changes over right ring finger and reduced renal output. She was in hypotension and had to be started on ionotropes. She also had acute kidney injury and was initiated on hemodialyis. Inspite of culture directed antibiotics and amputation of the necrotic region, her condition worsened. Considering the acute multisystem worsening, i.e., less than a week, concomitant autoimmune etiology was considered. Antiphospholipid antibodies were positive. Her tissue biopsy was suggestive of vasculitis. Hence the diagnosis of catastrophic antiphospholipid antibody syndrome (CAPS) was made. Quick recognition and appropriate treatment play a cornerstone in treatment of CAPS. She was pulsed with methylprednisolone and also treated with intravenous immunoglobulins and anticoagulants. She showed remarkable improvement and responded to the treatment. CAPS should always be kept as a differential in case of multisystem acute deterioration even in the background of sepsis. The treatment is a big challenge to physicians given the associated mortality rate if not briskly treated

Challenges of modeling rainfall triggered landslides in a data-sparse region: A case study from the Western Ghats, India

Accurate rainfall estimates are required to forecast the spatio-temporal distribution of rain-triggered landslides. In this study, a comparison between rain gauge and satellite rainfall data for assessing landslide distribution in a data-sparse region, the mountainous district of Idukki, along the Western Ghats of southwestern India, is carried out. Global Precipitation Mission Integrated Multi-satellitE Retrievals for GPM-Late (GPM IMERG-L) rainfall products were compared with rain gauge measurements, and it was found that the satellite rainfall observations were underpredicting the actual rainfall. A conditional merging algorithm was applied to develop a product that combines the accuracy of rain gauges and the spatial variability of satellite precipitation data. Correlation Coefficient (CC) and Root Mean Squared Error (RMSE) were used to check the performance of the conditional merging process. An example from a station with the least favorable statistics shows the CC increasing from 0.589 to 0.974 and the RMSE decreasing from 65.22 to 20.01. A case scenario was considered that evaluated the performance of a landslide prediction model by relying solely on a sparse rain gauge network. Rainfall thresholds computed from both the conditionally merged GPM IMERG-L and the rain gauge data were compared and the differences indicated that relying solely on a discrete, sparse rain gauge network would create false predictions. A total of 18.7% of landslide predictions only were identified as true positives, while 60.7% was the overall false-negative rate, and the remaining were false-positives. This pointed towards the need of having a continuous data that is both accurate in measurement and efficient in capturing spatial variability of rainfall

Gold nanoparticles approach to detect chondroitin sulphate and hyaluronic acid urothelial coating

This study investigated the location of hyaluronic acid (HA)-and chondroitin sulphate (CS)-coated gold nanoparticles in rabbit bladder and evaluated gene expression of CD44, RHAMM and ICAM-1 receptors involved in HA and CS transport into the cell. Gold nanoparticles were synthesised by reduction of gold salts with HA or CS to form HA-AuNPs and CS-AuNPs. Bladder samples were incubated with CS-AuNPs and HA-AuNPs or without glycosaminoglycans. Transmission electron microscopy, optic microscopy and scanning electron microscopy were used to determine the location of the synthesised AuNPs. Real-time PCR was used to analyse expression of urothelial cell receptors CD44, RHAMM, ICAM-1, after ex vivo administration of CS-AuNPs and HA-AuNPs. We showed that HA-AuNPs and CS-AuNPs were located in the cytoplasm and tight junctions of urothelial umbrella cells; this appearance was absent in untreated bladders. There were no significant differences in gene expression levels for CD44, RHAMM and ICAM-1 receptors in treated versus control bladder tissues. In conclusion, we clearly showed the presence of exogenous GAGs in the bladder surface and the tight junctions between umbrella cells, which is important in the regeneration pathway of the urothelium. The GAGs-AuNPs offer a promising approach to understanding the biophysical properties and imaging of urothelial tissue

Upper tropospheric humidity from SAPHIR on-board Megha-Tropiques

Upper tropospheric humidity (UTH) has been derived using a ‘brightness temperature (Tb) transformation’ method from the humidity sounder channels of SAPHIR payload on - board Megha - Tropiques (MT). These channels are very close to the water vapour absorption peak at 183.31 GHz. The channel at 183.31 0.2 GHz enables retrieval of humidity up to the hig h est altitude possible wit h the present nadir - looking microwave humidity sounders. Megha - Tropiques satllite has an equatorially inclined orbit, which e n sures frequent spatial and temporal coverage of the global tropical belt. Transformation coeff i cients for the first three channels for all the incidence angles have been derived and are used to convert brightness temperatures to weighted average upper tropospheric humidity having weighting function peaks at different pressure levels. The methodology has been validated by comparing the SAPHIR - derived UTH with that derived from radiosonde observations. Inter - comparison of the derived UTH has been done with layer averaged humidity product from SAPHIR measurements and with UTH product using infrared measurements from Kalpana satellite ( MOSDAC). UTH over the tropical belt for six months has been studied taking the advantage of the humidity product with high spatial and temporal resolution. The transformation coefficients and methodology to identify the cloud - free pixels to derive UTH from the three channels for all the possible incidence angles are presented here, so that the users can directly derive UTH from the brightness temperature data

Characterization of dimensional changes of cement pastes and mortars in fresh state applying an interferometric technique

The effect produced by the incorporation of additives in Portland cement based materials over dimensional changes occurring during the setting process was evaluated employing a fiber optic Fizeau interferometric sensor. The sensor system employed a broadband light source (SLED) centered at 1550 nm, whose spectral emission was modulated by the interferometer formed between the material surface and the end of the optical fiber used to illuminate the sample. An optical spectrum analyzer was used to monitor the variation of the modulated spectrum, while the mentioned process took place. The expansion or contraction experienced by materials with different compositions was observed and quantified. Results obtained point out the accuracy and the potential of the technique.Fil: Mesa Yandy, Angelica Maria. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico la Plata. Centro de Investigaciones Opticas (i); Argentina. Universidad Nacional de La Plata. Facultad de Ingenieria; Argentina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; ArgentinaFil: Duchowicz, Ricardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico la Plata. Centro de Investigaciones Opticas (i); Argentina. Universidad Austral. Facultad de Ingeniería; Argentina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; ArgentinaFil: Russo, Nelida Araceli. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico La Plata. Centro de Investigaciones Opticas (i); Argentina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; ArgentinaFil: Zerbino, Raul Luis. Universidad Nacional de La Plata. Facultad de Ingenieria; Argentina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; Argentin

Modeling a teacher in a tutorial-like system using Learning Automata

The goal of this paper is to present a novel approach to model the behavior of a Teacher in a Tutorial- like system. In this model, the Teacher is capable of presenting teaching material from a Socratic-type Domain model via multiple-choice questions. Since this knowledge is stored in the Domain model in chapters with different levels of complexity, the Teacher is able to present learning material of varying degrees of difficulty to the Students. In our model, we propose that the Teacher will be able to assist the Students to learn the more difficult material. In order to achieve this, he provides them with hints that are relative to the difficulty of the learning material presented. This enables the Students to cope with the process of handling more complex knowledge, and to be able to learn it appropriately. To our knowledge, the findings of this study are novel to the field of intelligent adaptation using Learning Automata (LA). The novelty lies in the fact that the learning system has a strategy by which it can deal with increasingly more complex/difficult Environments (or domains from which the learning as to be achieved). In our approach, the convergence of the Student models (represented by LA) is driven not only by the response of the Environment (Teacher), but also by the hints that are provided by the latter. Our proposed Teacher model has been tested against different benchmark Environments, and the results of these simulations have demonstrated the salient aspects of our model. The main conclusion is that Normal and Below-Normal learners benefited significantly from the hints provided by the Teacher, while the benefits to (brilliant) Fast learners were marginal. This seems to be in-line with our subjective understanding of the behavior of real-life Students