Factors Influencing the Adoption of Electronic Health Records in the Australian Environment

With the widespread use of medical records and the subsequent rise in the use of electronic health records (EHRs), the success of their adoption has become an important consideration for health agencies. In the current digital environment, the adoption of EHR has become significant because it limits the use of paper trails, and the care may be more effective because it is based on the electronic transfer of patient information. However, an improvement in the quality of the healthcare service is dependent upon how well EHRs are managed in healthcare as many stakeholders will contribute to them. While the advantages of EHRs are significant and cannot be disputed, a number of concerns have been raised regarding their success, as well as the ways in which they are adopted. The diversity of factors that affect the adoption of EHRs in various contexts requires a comprehensive investigation in order to establish a precise knowledge of their adoption in various healthcare settings. Such identification will help to mitigate many issues in their organisation at policy, workflow efficiency adoption and management levels. In this study, various factors that affect the adoption of EHRs in Australia will be identified and explored so as to arrive at a conceptual model that can be empirically tested later. Considering the vast amount of resources being dedicated to the adoption of EHRs in Australia, identifying barriers to their adoption, especially on an organisational level is essential for its success. Many studies have been conducted to understand barriers to the adoption of EHRs in Australia; however, there have been few studies concentrating on an organisational level in order to explore the challenges and obstacles that face specific organisations

Conceptual framework for telehealth adoption in Indian healthcare

India is a developing country with a large landmass and a huge socio-culturally, economically and, ethnically diverse population. The healthcare system for such a diverse and complex country could entail challenges and difficulties in execution and outreach. Here, the emerging area of Telehealth could afford a place for itself in providing healthcare and health education to a large section of people residing in areas where there is acute shortage of healthcare professionals. Almost, seventy per cent of the population in India are rural. The infrastructure in India, similar to other developing countries, is erratic and differs throughout the country. Similarly, the ICT infrastructure is developed in the urban areas whereas there are insufficient ICT facilities in the rural areas. As telehealth depends on the utilisation of ICT infrastructure it is essential to conduct a study to find out the determinants of ICT adoption in the Indian telehealth environment. Moreover, as evident from relevant literature, telehealth is in a nascent stage in India, with most of the projects currently in a pilot study level. As such, it would be practical to conduct the study from an organisational point of view because the organisational adoption of ICT will eventually foster the implementation of telehealth in the domain of Indian healthcare. The study focuses on developing a conceptual framework of ICT adoption in the Indian telehealth environment, as limited research has been conducted in this area. The study highlighted the drivers and barriers of telehealth around the world, reviewed the relevant models of ICT adoption and generated themes to develop the conceptual framework. Empirical testing of the conceptual framework may have the potential to establish and confirm the determinants of ICT adoption in the Indian telehealth environment. The conceptual framework may be utilised for governmental and non-governmental policy level decision making

PDRL: Multi-Agent based Reinforcement Learning for Predictive Monitoring

Reinforcement learning has been increasingly applied in monitoring applications because of its ability to learn from previous experiences and can make adaptive decisions. However, existing machine learning-based health monitoring applications are mostly supervised learning algorithms, trained on labels and they cannot make adaptive decisions in an uncertain complex environment. This study proposes a novel and generic system, predictive deep reinforcement learning (PDRL) with multiple RL agents in a time series forecasting environment. The proposed generic framework accommodates virtual Deep Q Network (DQN) agents to monitor predicted future states of a complex environment with a well-defined reward policy so that the agent learns existing knowledge while maximizing their rewards. In the evaluation process of the proposed framework, three DRL agents were deployed to monitor a subject's future heart rate, respiration, and temperature predicted using a BiLSTM model. With each iteration, the three agents were able to learn the associated patterns and their cumulative rewards gradually increased. It outperformed the baseline models for all three monitoring agents. The proposed PDRL framework is able to achieve state-of-the-art performance in the time series forecasting process. The proposed DRL agents and deep learning model in the PDRL framework are customized to implement the transfer learning in other forecasting applications like traffic and weather and monitor their states. The PDRL framework is able to learn the future states of the traffic and weather forecasting and the cumulative rewards are gradually increasing over each episode.Comment: This work has been submitted to the Springer for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

The cyclin-dependent kinase PITSLRE/CDK11 is required for successful autophagy

(Macro)autophagy is a membrane-trafficking process that serves to sequester cellular constituents in organelles termed autophagosomes, which target their degradation in the lysosome. Autophagy operates at basal levels in all cells where it serves as a homeostatic mechanism to maintain cellular integrity. The levels and cargoes of autophagy can, however, change in response to a variety of stimuli, and perturbations in autophagy are known to be involved in the aetiology of various human diseases. Autophagy must therefore be tightly controlled. We report here that the Drosophila cyclin-dependent kinase PITSLRE is a modulator of autophagy. Loss of the human PITSLRE orthologue, CDK11, initially appears to induce autophagy, but at later time points CDK11 is critically required for autophagic flux and cargo digestion. Since PITSLRE/CDK11 regulates autophagy in both Drosophila and human cells, this kinase represents a novel phylogenetically conserved component of the autophagy machinery

Electron-phonon interaction contribution to the total energy of group IV semiconductor polymorphs: evaluation and implications

In density functional theory (DFT) based total energy studies, the van der Waals (vdW) and zero-point vibrational energy (ZPVE) correction terms are included to obtain energy differences between polymorphs. We introduce a new correction term, due to electron-phonon interactions (EPI). We rely on Allen's general formalism, which goes beyond the Quasi-Harmonic Approximation (QHA), to include the free energy contributions due to quasiparticle interactions. We show that, for semiconductors and insulators, the EPI contributions to the free energies of electrons and phonons are constant terms. Using Allen's formalism in combination with the Allen-Heine theory for EPI corrections, we calculate the zero-point EPI corrections to the total energy for cubic and hexagonal polytypes of Carbon, Silicon and Silicon Carbide. The EPI corrections alter the energy differences between polytypes. In SiC polytypes, the EPI correction term is more sensitive to crystal structure than the vdW and ZPVE terms and is thus essential in determining their energy differences. It clearly establishes that the cubic SiC-3C is metastable and hexagonal SiC-4H is the stable polytype. Our results are consistent with the experimental results of Kleykamp. Our study enables the inclusion of EPI corrections as a separate term in the free energy expression. This opens the way to beyond the QHA by including the contribution of EPI on all thermodynamic properties.Comment: Submitted for publication. 32 pages and 2 figure

Exhumation history of the Higher Himalayan Crystalline along Dhauliganga-Goriganga river valleys, NW India: new constraints from fission track analysis

New apatite and zircon fission track data collected from two transects along the Dhauliganga and Goriganga rivers in the NW Himalaya document exhumation of the Higher Himalayan Crystalline units. Despite sharing the same structural configuration and rock types and being separated by only 60 km, the two study areas show very different patterns of exhumation. Fission track (FT) data from the Dhauliganga section show systematic changes in age (individual apatite FT ages range from 0.9 ± 0.3 to 3.6 ± 0.5 Ma, r 2 = 0.82) that record faster exhumation across a zone that extends from the Main Central Thrust to north of the Vaikrita thrust. By contrast, FT results from the Goriganga Valley show a stepwise change in ages across the Vaikrita thrust that suggests Quaternary thrust sense displacement. Footwall samples yield a weighted mean apatite age of 1.6 ± 0.1 Ma compared to 0.7 ± 0.04 Ma in the hanging wall. A constant zircon fission track age of 1.8 ± 0.4 Ma across both the footwall and hanging wall shows the 0.9 Ma difference in apatite ages is due to movement on the Vaikrita thrust that initiated soon after ∼1.8 Ma. The Goriganga section provides clear evidence for >1 Ma of tectonic deformation in the brittle crust that contrasts with previous exhumation studies in other areas of the high Himalaya ranges; these studies have been unable to decouple the role of climate erosion from tectonics. One possibility why there is a clear tectonic signal in the Goriganga Valley is that climate erosion has not yet fully adjusted to the tectonic perturbation

Observations of neutral carbon in 29 high-z lensed dusty star forming galaxies and the comparison of gas mass tracers

The nature and evolution of high-redshift dusty star-forming galaxies (high-z DSFGs) remain an open question. Their massive gas reservoirs play an important role in driving the intense star-formation rates hosted in these galaxies. We aim to estimate the molecular gas content of high-z DSFGs by using various gas mass tracers such as the [CI], CO, [CII] emission lines and the dust content. These tracers need to be well calibrated as they are all limited by uncertainties on factors such as aCO, XCI, aCII and GDR, thereby affecting the determination of the gas mass accurately. The main goal of our work is to check the consistency between the gas mass tracers and cross-calibrate the uncertain factors. We observe the two [CI] line transitions for 29 SPT-SMGs with the ALMA-ACA. Additionally, we also present new APEX observations of [CII] line for 9 of these galaxies. We find a nearly linear relation between the infrared luminosity and [CI] luminosity if we fit the starbursts and main-sequence galaxies separately. We measure a median [CI]-derived excitation temperature of 34.5+/-2.1 K. We probe the properties of the interstellar medium (ISM) such as density and radiation field intensity using [CI] to mid- or high-J CO lines and [CI] to infrared luminosity ratio, and find similar values to the SMG populations in literature. Finally, the gas masses estimated from [CI], CO, dust, and [CII] do not exhibit any significant trend with the infrared luminosity or the dust temperature. We provide the various cross-calibrations between these tracers. Our study confirms that [CI] is a suitable tracer of the molecular gas content, and shows an overall agreement between all the classical gas tracers used at high redshift. However, their absolute calibration and thus the gas depletion timescale measurements remain uncertain.Comment: Accepted for publication in A&A, 25 pages, 11 figures, 6 table