Wireless for Machine Learning

As data generation increasingly takes place on devices without a wired connection, Machine Learning over wireless networks becomes critical. Many studies have shown that traditional wireless protocols are highly inefficient or unsustainable to support Distributed Machine Learning. This is creating the need for new wireless communication methods. In this survey, we give an exhaustive review of the state of the art wireless methods that are specifically designed to support Machine Learning services. Namely, over-the-air computation and radio resource allocation optimized for Machine Learning. In the over-the-air approach, multiple devices communicate simultaneously over the same time slot and frequency band to exploit the superposition property of wireless channels for gradient averaging over-the-air. In radio resource allocation optimized for Machine Learning, Active Learning metrics allow for data evaluation to greatly optimize the assignment of radio resources. This paper gives a comprehensive introduction to these methods, reviews the most important works, and highlights crucial open problems.Comment: Corrected typo in author name. From the incorrect Maitron to the correct Mairto

Optimized intermolecular potential for nitriles based on Anisotropic United Atoms model

An extension of the Anisotropic United Atoms intermolecular potential model is proposed for nitriles. The electrostatic part of the intermolecular potential is calculated using atomic charges obtained by a simple Mulliken population analysis. The repulsion-dispersion interaction parameters for methyl and methylene groups are taken from transferable AUA4 literature parameters [Ungerer et al., J. Chem. Phys., 2000, 112, 5499]. Non-bonding Lennard-Jones intermolecular potential parameters are regressed for the carbon and nitrogen atoms of the nitrile group (–C≡N) from experimental vapor-liquid equilibrium data of acetonitrile. Gibbs Ensemble Monte Carlo simulations and experimental data agreement is very good for acetonitrile, and better than previous molecular potential proposed by Hloucha et al. [J. Chem. Phys., 2000, 113, 5401]. The transferability of the resulting potential is then successfully tested, without any further readjustment, to predict vapor-liquid phase equilibrium of propionitrile and n-butyronitrile

Arterial dP/dtmax accurately reflects left ventricular contractility during shock when adequate vascular filling is achieved

Background: Peak first derivative of femoral artery pressure (arterial dP/dt max) derived from fluid-filled catheter remains questionable to assess left ventricular (LV) contractility during shock. The aim of this study was to test if arterial dP/dt maxis reliable for assessing LV contractility during various hemodynamic conditions such as endotoxin-induced shock and catecholamine infusion.Methods: Ventricular pressure-volume data obtained with a conductance catheter and invasive arterial pressure obtained with a fluid-filled catheter were continuously recorded in 6 anaesthetized and mechanically ventilated pigs. After a stabilization period, endotoxin was infused to induce shock. Catecholamines were transiently administrated during shock. Arterial dP/dt maxwas compared to end-systolic elastance (Ees), the gold standard method for assessing LV contractility.Results: Endotoxin-induced shock and catecholamine infusion lead to significant variations in LV contractility. Overall, significant correlation (r = 0.51; p < 0.001) but low agreement between the two methods were observed. However, a far better correlation with a good agreement were observed when positive-pressure ventilation induced an arterial pulse pressure variation (PPV) ≤ 11% (r = 0.77; p < 0.001).Conclusion: While arterial dP/dt maxand Ees were significantly correlated during various hemodynamic conditions, arterial dP/dt maxwas more accurate for assessing LV contractility when adequate vascular filling, defined as PPV ≤ 11%, was achieved. © 2012 Morimont et al; licensee BioMed Central Ltd

A comparative study of four intensive care outcome prediction models in cardiac surgery patients

<p>Abstract</p> <p>Background</p> <p>Outcome prediction scoring systems are increasingly used in intensive care medicine, but most were not developed for use in cardiac surgery patients. We compared the performance of four intensive care outcome prediction scoring systems (Acute Physiology and Chronic Health Evaluation II [APACHE II], Simplified Acute Physiology Score II [SAPS II], Sequential Organ Failure Assessment [SOFA], and Cardiac Surgery Score [CASUS]) in patients after open heart surgery.</p> <p>Methods</p> <p>We prospectively included all consecutive adult patients who underwent open heart surgery and were admitted to the intensive care unit (ICU) between January 1^st2007 and December 31^st2008. Scores were calculated daily from ICU admission until discharge. The outcome measure was ICU mortality. The performance of the four scores was assessed by calibration and discrimination statistics. Derived variables (Mean- and Max- scores) were also evaluated.</p> <p>Results</p> <p>During the study period, 2801 patients (29.6% female) were included. Mean age was 66.9 ± 10.7 years and the ICU mortality rate was 5.2%. Calibration tests for SOFA and CASUS were reliable throughout (p-value not < 0.05), but there were significant differences between predicted and observed outcome for SAPS II (days 1, 2, 3 and 5) and APACHE II (days 2 and 3). CASUS, and its mean- and maximum-derivatives, discriminated better between survivors and non-survivors than the other scores throughout the study (area under curve ≥ 0.90). In order of best discrimination, CASUS was followed by SOFA, then SAPS II, and finally APACHE II. SAPS II and APACHE II derivatives had discrimination results that were superior to those of the SOFA derivatives.</p> <p>Conclusions</p> <p>CASUS and SOFA are reliable ICU mortality risk stratification models for cardiac surgery patients. SAPS II and APACHE II did not perform well in terms of calibration and discrimination statistics.</p

Exploiting inflammation for therapeutic gain in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy associated with &#60;5% 5-year survival, in which standard chemotherapeutics have limited benefit. The disease is associated with significant intra- and peritumoral inflammation and failure of protective immunosurveillance. Indeed, inflammatory signals are implicated in both tumour initiation and tumour progression. The major pathways regulating PDAC-associated inflammation are now being explored. Activation of leukocytes, and upregulation of cytokine and chemokine signalling pathways, both have been shown to modulate PDAC progression. Therefore, targeting inflammatory pathways may be of benefit as part of a multi-target approach to PDAC therapy. This review explores the pathways known to modulate inflammation at different stages of tumour development, drawing conclusions on their potential as therapeutic targets in PDAC

Interpersonal and affective dimensions of psychopathic traits in adolescents : development and validation of a self-report instrument

We report the development and psychometric evaluations of a self-report instrument designed to screen for psychopathic traits among mainstream community adolescents. Tests of item functioning were initially conducted with 26 adolescents. In a second study the new instrument was administered to 150 high school adolescents, 73 of who had school records of suspension for antisocial behavior. Exploratory factor analysis yielded a 4-factor structure (Impulsivity α = .73, Self-Centredness α = .70, Callous-Unemotional α = .69, and Manipulativeness α = .83). In a third study involving 328 high school adolescents, 130 with records of suspension for antisocial behaviour, competing measurement models were evaluated using confirmatory factor analysis. The superiority of a first-order model represented by four correlated factors that was invariant across gender and age was confirmed. The findings provide researchers and clinicians with a psychometrically strong, self-report instrument and a greater understanding of psychopathic traits in mainstream adolescents

Spontaneous Brain Activity in the Default Mode Network Is Sensitive to Different Resting-State Conditions with Limited Cognitive Load

BACKGROUND: Recent functional MRI (fMRI) studies have demonstrated that there is an intrinsically organized default mode network (DMN) in the resting brain, primarily made up of the posterior cingulate cortex (PCC) and the medial prefrontal cortex (MPFC). Several previous studies have found that the DMN is minimally disturbed during different resting-state conditions with limited cognitive demand. However, this conclusion was drawn from the visual inspection of the functional connectivity patterns within the DMN and no statistical comparison was performed. METHODOLOGY/PRINCIPAL FINDINGS: Four resting-state fMRI sessions were acquired: 1) eyes-closed (EC) (used to generate the DMN mask); 2) EC; 3) eyes-open with no fixation (EO); and 4) eyes-open with a fixation (EO-F). The 2-4 sessions were counterbalanced across participants (n = 20, 10 males). We examined the statistical differences in both functional connectivity and regional amplitude of low frequency fluctuation (ALFF) within the DMN among the 2-4 resting-state conditions (i.e., EC, EO, and EO-F). Although the connectivity patterns of the DMN were visually similar across these three different conditions, we observed significantly higher functional connectivity and ALFF in both the EO and the EO-F conditions as compared to the EC condition. In addition, the first and second resting EC conditions showed significant differences within the DMN, suggesting an order effect on the DMN activity. CONCLUSIONS/SIGNIFICANCE: Our findings of the higher DMN connectivity and regional spontaneous activities in the resting state with the eyes open suggest that the participants might have more non-specific or non-goal-directed visual information gathering and evaluation, and mind wandering or daydreaming during the resting state with the eyes open as compared to that with the eyes closed, thus providing insights into the understanding of unconstrained mental activity within the DMN. Our results also suggest that it should be cautious when choosing the type of a resting condition and designating the order of the resting condition in multiple scanning sessions in experimental design

“Thinking about Not-Thinking”: Neural Correlates of Conceptual Processing during Zen Meditation

Recent neuroimaging studies have identified a set of brain regions that are metabolically active during wakeful rest and consistently deactivate in a variety the performance of demanding tasks. This “default network” has been functionally linked to the stream of thoughts occurring automatically in the absence of goal-directed activity and which constitutes an aspect of mental behavior specifically addressed by many meditative practices. Zen meditation, in particular, is traditionally associated with a mental state of full awareness but reduced conceptual content, to be attained via a disciplined regulation of attention and bodily posture. Using fMRI and a simplified meditative condition interspersed with a lexical decision task, we investigated the neural correlates of conceptual processing during meditation in regular Zen practitioners and matched control subjects. While behavioral performance did not differ between groups, Zen practitioners displayed a reduced duration of the neural response linked to conceptual processing in regions of the default network, suggesting that meditative training may foster the ability to control the automatic cascade of semantic associations triggered by a stimulus and, by extension, to voluntarily regulate the flow of spontaneous mentation

Assessing hospitals' clinical risk management: Development of a monitoring instrument

<p>Abstract</p> <p>Background</p> <p>Clinical risk management (CRM) plays a crucial role in enabling hospitals to identify, contain, and manage risks related to patient safety. So far, no instruments are available to measure and monitor the level of implementation of CRM. Therefore, our objective was to develop an instrument for assessing CRM in hospitals.</p> <p>Methods</p> <p>The instrument was developed based on a literature review, which identified key elements of CRM. These elements were then discussed with a panel of patient safety experts. A theoretical model was used to describe the level to which CRM elements have been implemented within the organization. Interviews with CRM practitioners and a pilot evaluation were conducted to revise the instrument. The first nationwide application of the instrument (138 participating Swiss hospitals) was complemented by in-depth interviews with 25 CRM practitioners in selected hospitals, for validation purposes.</p> <p>Results</p> <p>The monitoring instrument consists of 28 main questions organized in three sections: 1) Implementation and organizational integration of CRM, 2) Strategic objectives and operational implementation of CRM at hospital level, and 3) Overview of CRM in different services. The instrument is available in four languages (English, German, French, and Italian). It allows hospitals to gather comprehensive and systematic data on their CRM practice and to identify areas for further improvement.</p> <p>Conclusions</p> <p>We have developed an instrument for assessing development stages of CRM in hospitals that should be feasible for a continuous monitoring of developments in this important area of patient safety.</p