A Multi-Step Nonlinear Dimension-Reduction Approach with Applications to Bigdata

In this paper, a multi-step dimension-reduction approach is proposed for addressing nonlinear relationships within attributes. In this work, the attributes in the data are first organized into groups. In each group, the dimensions are reduced via a parametric mapping that takes into account nonlinear relationships. Mapping parameters are estimated using a low rank singular value decomposition (SVD) of distance covariance. Subsequently, the attributes are reorganized into groups based on the magnitude of their respective singular values. The group-wise organization and the subsequent reduction process is performed for multiple steps until a singular value-based user-defined criterion is satisfied. Simulation analysis is utilized to investigate the performance with five big data-sets

Direct Error Driven Learning for Deep Neural Networks with Applications to Bigdata

In this paper, generalization error for traditional learning regimes-based classification is demonstrated to increase in the presence of bigdata challenges such as noise and heterogeneity. To reduce this error while mitigating vanishing gradients, a deep neural network (NN)-based framework with a direct error-driven learning scheme is proposed. To reduce the impact of heterogeneity, an overall cost comprised of the learning error and approximate generalization error is defined where two NNs are utilized to estimate the costs respectively. To mitigate the issue of vanishing gradients, a direct error-driven learning regime is proposed where the error is directly utilized for learning. It is demonstrated that the proposed approach improves accuracy by 7 % over traditional learning regimes. The proposed approach mitigated the vanishing gradient problem and improved generalization by 6%

The Realities of Evaluating Educational Technology in School Settings

\ua9 2024 Copyright held by the owner/author(s).HCI researchers are increasingly interested in the evaluation of educational technologies in context, yet acknowledge that challenges remain regarding the logistical, material and methodological constraints of this approach to research [18, 53].Through the analysis of the authors\u27 contributed thematic research vignettes, the following article exposes the practical realities of evaluating educational technologies in school settings. This includes insights into the planning stages of evaluation, the relationship between the researcher and the school environment, and the impact of the school context on the data collection process.We conclude by providing an orientation for the design of HCI educational technology research undertaken in school contexts, providing guidance such as considering the role of modular research design, clarifying goals and expectations with school partners, and reporting researcher positionality

Local influence of boundary conditions on a confined supercooled colloidal liquid

We study confined colloidal suspensions as a model system which approximates the behavior of confined small molecule glass-formers. Dense colloidal suspensions become glassier when confined between parallel glass plates. We use confocal microscopy to study the motion of confined colloidal particles. In particular, we examine the influence particles stuck to the glass plates have on nearby free particles. Confinement appears to be the primary influence slowing free particle motion, and proximity to stuck particles causes a secondary reduction in the mobility of free particles. Overall, particle mobility is fairly constant across the width of the sample chamber, but a strong asymmetry in boundary conditions results in a slight gradient of particle mobility.Comment: For conference proceedings, "Dynamics in Confinement", Grenoble, March 201

Prevailing Arguments and Types of Conclusions of Parent\u2013Child Argumentation

This chapter examines the types of arguments used most often by parents and children and the different types of conclusions of their argumentative discussions. The conceptual tool adopted for the analysis is based on the integration of the pragma-dialectical ideal model of a critical discussion (van Eemeren & Grootendorst, 2004) with the Argumentum Model of Topics (Rigotti & Greco Morasso, 2019). The integration of these two tools of analysis permits to reconstruct the inferential configuration of the arguments used by parents and children and to identify the types of conclusions of their argumentative discussions. Exemplary argumentative sequences that bring to light the results obtained through the qualitative analysis of a larger corpus of argumentative discussions between parents and children are presented and discussed

Effect of Ashwagandha and Aloe vera pretreatment on intestinal transport of buspirone across rat intestine

The transport of buspirone across rat intestine (duodenum, jejunum, ileum and colon) was studied by using the non-everted sac method. Rats were pretreated with ashwagandha (Withania somnifera) and Aloe vera juice for 7 days. The rats were sacrificed by using anesthetic ether, the intestinal segments were isolated and used for the studies. The probe drug (buspirone) solution was placed in the isolated intestinal sac. Samples were collected at preset time points and replaced with fresh buffer. The drug content in the samples was estimated using high performance liquid chromatography method. Control experiments were also performed. The results reveal that there was a significant (p < 0.05) difference compared to control, in the transport of buspirone from the intestinal sacs which were pretreated with ashwagandha and Aloe vera juice. It suggests that both ashwagandha and Aloe vera might be acting by inhibiting the transporters and enzymes which are responsible for transport/metabolism of buspirone.Colegio de Farmacéuticos de la Provincia de Buenos Aire

The Bacterial Fimbrial Tip Acts as a Mechanical Force Sensor

The subunits that constitute the bacterial adhesive complex located at the tip of the fimbria form a hook-chain that acts as a rapid force-sensitive anchor at high flow

Training and expertise in undertaking assisted vaginal delivery (AVD): a mixed methods systematic review of practitioners views and experiences

Abstract: Background: During childbirth, complications may arise which necessitate an expedited delivery of the fetus. One option is instrumental assistance (forceps or a vacuum-cup), which, if used with skill and sensitivity, can improve maternal/neonatal outcomes. This review aimed to understand the core competencies and expertise required for skilled use in AVD in conjunction with reviewing potential barriers and facilitators to gaining competency and expertise, from the point of view of maternity care practitioners, funders and policy makers. Methods: A mixed methods systematic review was undertaken in five databases. Inclusion criteria were primary studies reporting views, opinions, perspectives and experiences of the target group in relation to the expertise, training, behaviours and competencies required for optimal AVD, barriers and facilitators to achieving practitioner competencies, and to the implementation of appropriate training. Quality appraisal was carried out on included studies. A mixed-methods convergent synthesis was carried out, and the findings were subjected to GRADE-CERQual assessment of confidence. Results: 31 papers, reporting on 27 studies and published 1985–2020 were included. Studies included qualitative designs (3), mixed methods (3), and quantitative surveys (21). The majority (23) were from high-income countries, two from upper-middle income countries, one from a lower-income country: one survey included 111 low-middle countries. Confidence in the 10 statements of findings was mostly low, with one exception (moderate confidence). The review found that AVD competency comprises of inter-related skill sets including non-technical skills (e.g. behaviours), general clinical skills; and specific technical skills associated with particular instrument use. We found that practitioners needed and welcomed additional specific training, where a combination of teaching methods were used, to gain skills and confidence in this field. Clinical mentorship, and observing others confidently using the full range of instruments, was also required, and valued, to develop competency and expertise in AVD. However, concerns regarding poor outcomes and litigation were also raised. Conclusion: Access to specific AVD training, using a combination of teaching methods. Complements, but does not replace, close clinical mentorship from experts who are positive about AVD, and opportunities to practice emerging AVD skills with supportive supervision. Further research is required to ascertain effective modalities for wider training, education, and supportive supervision for optimal AVD use

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

Aluminium batteries

Investigations on the prospective use of aluminium as anode for power sources have been reviewed in this paper. The ultimate aim of these investigations is to make a commercially viable aluminium-air cell for automobile propulsion. The difficulties faced in this field are the suppression of self corrosion and gassing of aluminium in alkaline solutions. The air electrode i.e. the cathode used in aluminium batteries, which has been considered hitherto is the breathing-type carbon element or pressurised porous electrode used in fuel cells. Pressurised porous electrode is found to be more advantageous and compatible with the anode reaction on the basis of electrode kinetic