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As intelligent electronics get laden with multimodal sensors, the data transfer and computation increase their energy expenditure. Consequently, researchers aim to develop efficient computing paradigms or integrate energy harvesting from ambient sources. Halide perovskites possess unique photophysics and coupled ionic-electronic dynamics that actualise memory devices for brain-inspired computing. Synergising the computing capability with their conventional light harvesting efficacy could aptly address the aforementioned problem. In a novel approach, the transient open circuit voltage (V OC) of a methylammonium lead bromide-based solar cell was exploited to serve as a self-powered volatile short-term memory for optoelectronic in-sensor reservoir computing. The origin of the memory is attributed to the influence of mobile ions on the carrier generation and recombination in the device. The system's versatility and task specificity were shown by engineering the volatility of the memory. The benchmarking task of MNIST handwritten digit recognition was performed with the highly reproducible and robust transformation of optical inputs into unique reservoir states. To demonstrate the high nonlinearity, second-order time-series prediction (NARMA2) was performed. Finally, an exemplary cardiac health-monitoring application was showcased by monolithic reading and processing of a physiological time series known as photoplethysmography (PPG) to identify atrial fibrillation with increased computational efficiency. [Display omitted] • Halide Perovskite solar cells are shown to be ideal devices for in-sensor reservoir computing. • Coupled ionic-electronic dynamics of halide perovskite solar cells leveraged to realise self-powered optoelectronic short-term memory. • Tasks such as MNIST Handwritten Digit Recognition and Second Order Nonlinear Equation Prediction (NARMA2) are demonstrated. • Implementation in healthcare applications is shown in computationally efficient detection of atrial fibrillation through photoplethysmography (PPG). • Through extensive physical characterization and device modelling, the key role of the mobile halide ions is identified. [ABSTRACT FROM AUTHOR]

[Display omitted] • We review studies on computational implications of dendritic nonlinearities in neurons. • We discuss how synaptic plasticity can interact with dendritic nonlinearities for improved learning. • We link these studies to applications in machine learning and deep learning. • Thus, we propose a path to more powerful and more efficient machine learning methods and hardware. In this paper, we discuss the nonlinear computational power provided by dendrites in biological and artificial neurons. We start by briefly presenting biological evidence about the type of dendritic nonlinearities, respective plasticity rules and their effect on biological learning as assessed by computational models. Four major computational implications are identified as improved expressivity, more efficient use of resources, utilizing internal learning signals, and enabling continual learning. We then discuss examples of how dendritic computations have been used to solve real-world classification problems with performance reported on well known data sets used in machine learning. The works are categorized according to the three primary methods of plasticity used—structural plasticity, weight plasticity, or plasticity of synaptic delays. Finally, we show the recent trend of confluence between concepts of deep learning and dendritic computations and highlight some future research directions. [ABSTRACT FROM AUTHOR]

The concept of 'readiness to practice' of nursing students is not well understood even though being 'ready for practice' is the focus of undergraduate programs. The aim of this study was to critically explore senior student's views about their readiness to practice as a registered nurse. This study was undertaken in a school of nursing in the South Island of New Zealand. The participants included all senior nursing students assigned to their final clinical practicum from five cohorts across two and half years. The response rate for the survey across five cohorts was 46% (n = 245). The majority of students were New Zealand European females aged 30 years or younger. Students felt they were confident with their professional responsibilities and considered that they had prepared well for the profession. They agreed that they were confident with their communication skills. Areas of concern were; caring for a dying patient and caring for more than four patients at one time. This study suggests that senior nursing students feel they are work ready. [ABSTRACT FROM AUTHOR]

Stroke survivors (SS) are rising with higher incidence of stroke in developing countries. In addition to physical impairment, other factors such as cognition, social interaction, and depression determine the functional outcome after stroke. Considering the paucity of data from developing countries, we planned to determine the change in various functional parameters among SS. This community-based prospective study was carried out in Kolkata, India among 283 SS between 2006 and 2010. Functional outcome was assessed at baseline and at 3 annual follow-up visits using validated tools. A stepwise regression analysis was performed with demographic and stroke-related covariates against various measures of functional outcome. Result showed that mean Barthel Index score at baseline was 76.4 ± 30.8. Bengali version of mental status examination and Geriatric Depression Scale scores trended down over time with a negative regression coefficient of -.2061 (standard error [SE], .0937) and -.4488 (SE, .2145). Other outcomes did not change. Female gender, depression, and cognitive dysfunction had an unfavorable impact, whereas education correlated positively. In conclusions female gender and neuropsychiatric disturbances showed poor functional outcome compared with education, which correlates with better outcome. This information will be helpful for patients in developing countries for planning stroke rehabilitation. [ABSTRACT FROM AUTHOR]

The article describes a study of the incidence of mental depression following stroke in community-living older patients in Kolkata, India. Subjects were evaluated for cognitive ability, disability, and post-stroke depression (PSD) using Bengali versions of rating scales. The results indicate that age, education level, and socioeconomic status were significant influences on the prevalence of post-stroke depression.

Abstract: Electron–positronium scattering has been investigated in the Debye plasma environment employing the close-coupling approximation. Three models, viz. 3-state CCA, 6-state CCA and 9-state CCA, have been employed. The 2s2 1Se autodetaching resonant state of the positronium negative ion has been successfully predicted for various plasma environments. The position of the resonance for different Debye lengths are in close agreement with those of Kar and Ho [S. Kar, Y.K. Ho, Phys. Rev. A 71 (2005) 052503]. [Copyright &y& Elsevier]

Deterioration of shear strength parameters of carbonate joints under the influence of acid rainwater is a serious concern in rock engineering. Considering this, limestone specimens with planar joints (i.e. joints having roughness coefficient <5) collected from the Lanjiberna limestone mine (in the state of Odisha, India) were investigated. Depreciation of shear strength parameters of the joints concerning short-term exposure to a simulated typical acid rain (i.e. pH 4 solution) condition was evaluated. A total of 24 direct shear tests were performed on natural limestone joints and their degraded equivalents. Both peak shear strength and peak friction angle of a degraded joint are found to be less than those of its natural counterpart. The drop in peak friction angle is found to be 8–10% and 14–19% due to submergence of the joints in pH 4 solution for 5 days and 10 days, respectively. It was ascertained that the deterioration of the asperity strength due to the short-term exposure of the planar joint surfaces to the pH 4 solution overrides the effect of insignificant macroscopic change of the surface roughness caused by solution induced micro-cavities and hence, controls the degradation of the shear strength parameters. [ABSTRACT FROM AUTHOR]

An abstract of the article "Identification of Neuroanatomical Substrates of Set-Shifting Ability: Evidence From Patients With Focal Brain Lesions," by Pritha Mukhopadhyay and colleagues is presented.

Abstract: In this study anisotropy of magnetic susceptibility (AMS) measurements are made on quartzites that do not contain visible foliations. Using AMS data, the magnetic foliation is recognized in the quartzites. Ultrasonic P-wave velocity and point load strength (which is a proxy for uniaxial compressive strength) are determined in cores drilled parallel as well as perpendicular to the magnetic foliation. Ultrasonic P-wave velocity is greater in the direction parallel to the foliation and lower perpendicular to the same. Conversely, point load strength is lower in the direction parallel to the magnetic foliation and greater perpendicular to it. AMS data are compared with the anisotropy of P-wave velocity as well as rock strength anisotropy. It is noted that quartzites with a strong magnetic fabric also have a high P-wave velocity anisotropy as well as rock strength anisotropy. Based on the results, usefulness of AMS in identification of principal testing directions for rock mechanics investigations in rocks devoid of mesoscopic foliations is discussed. [ABSTRACT FROM AUTHOR]

We demonstrate the use of a low-power and compact hardware implementation of Random Feature Extractor (RFE) core in image recognition applications. We show that weight distributions with zero mean are necessary for good performance in this application. We also show the performance in this application of a recently proposed weight reuse technique that virtually expands the number of random features available from RFE core. Further, we propose a method of reducing computation cost by pruning “incognizant” or redundant random feature neurons. For proof of concept, we validated our approach by using our RFE core as the first stage of Extreme Learning Machine (ELM) – a two layer neural network – and using 12, 800 hidden neurons were able to achieve upto 97.8% accuracy on MNIST database of handwritten digits. The RFE ASIC occupies 5 mm × 5 mm area in 0.35 µm CMOS process. By using the proposed pruning method, an accuracy of 97% is obtained by using only 4749 effective hidden neurons and consuming 6.1 µJ/classify. Input pre-processing and ELM second stage requiring just addition operations can be implemented using digital adders with estimated power consumption of 24.9 nJ/classify. With a total energy consumption of only 6.12 µJ/classify, this low-power mixed signal ASIC can act as a co-processor in portable electronic gadgets with cameras. [ABSTRACT FROM AUTHOR]

GATA and Friend of GATA (FOG) form a transcriptional complex that plays a key role in cardiovascular development in both fish and mammals. In the present study we demonstrate that the basic helix-loop-helix transcription factor Atonal homolog 8 (Atoh8) is required for development of the heart in fish but not in mice. Genetic studies reveal that Atoh8 interacts specifically with Gata4 and Fog1 during development of the heart and swim bladder in the fish. Biochemical studies reveal that ATOH8, GATA4, and FOG2 associate in a single complex in vitro. In contrast to fish, ATOH8-deficientmice exhibit normal cardiac development and loss of ATOH8 does not alter cardiac/ development in Gata4 mice. This species difference in the role of ATOH8 is explained in part by LacZ and GFP reporter alleles that reveal restriction of Atoh8 expression to atrial but not ventricularmyocardium in the mouse. Our findings identify ATOH8 as a novel regulator of GATA-FOG function that is required for cardiac development in the fish but not the mouse. Whether ATOH8 modulates GATA-FOG function at other sites or in more subtle ways in mammals is not yet known. [ABSTRACT FROM AUTHOR]

The present research reports a facile synthesis of bare phase pure CaAl-LDH nanoparticle (sample A) and intercalation of anti-cancer drug etoposide (ETO) into the same via simple anion exchange technique to obtain ETO loaded CaAl-LDH (sample B). The basal spacing (d 002) of sample A was increased from 8.5764 Å to 17.18 Å upon intercalation of ETO. Further ETO loading was found to be 27.72% as estimated by UV–Vis spectrophotometer. The release profile of ETO from sample B in phosphate buffer saline (PBS) at pH 7.4 follows quasi-Fickian diffusion phenomenon in Korsmeyer–Peppas kinetics model. In vitro cell viability was undertaken using A549 (human lung adenocarcinoma) cell line in a dose dependent manner to determine the synergistic anti-cancer potential of sample B. It was observed that at an equivalent dose, the cancer cell viability was substantially reduced, in case of sample B compared to sample A and bare etoposide drug, respectively, which was further corroborated by cell proliferation/migration assay. The cellular uptake using A549 cell line showed an increasing trend with increasing time period (11.67% and 19.30% at 24 h and 72 h) respectively, confirmed by flow cytometry, exhibiting a substantial reduction of CAMKIIα protein for sample A and sample B to 110.52 pg/ml and 95.14 pg/ml respectively. Results also showed significant down regulation of SOD gene activity. All the above results exhibited the synergistic anti-cancer potential of sample B for possible application in the management of non small cell lung carcinoma (NSCLC). • Synergistic anticancer activity of etoposide drug loaded CaAl-LDH nanoparticles • Significant reduction of cell viability (A549 cells) using CaAl-LDH-ETO nanoconjugate, with respect to control batches • Corroboration of the above observation by cellular and molecular level assays [ABSTRACT FROM AUTHOR]