Risk perceptions about personal Internet-of-Things: Research directions from a multi-panel Delphi study

Internet-of-Things (IoT) research has primarily focused on identifying IoT devices\u27 organizational risks with little attention to consumer perceptions about IoT device risks. The purpose of this study is to understand consumer risk perceptions for personal IoT devices and translate these perceptions into guidance for future research directions. We conduct a sequential, mixed-methods study using multi-panel Delphi and thematic analysis techniques to understand consumer risk perceptions. The results identify four themes focused on data exposure and user experiences within IoT devices. Our thematic analysis also identified several emerging risks associated with the evolution of IoT device functionality and its potential positioning as a resource for malicious actors to conduct security attacks

Ripple oscillations in the left temporal neocortex are associated with impaired verbal episodic memory encoding

Background: We sought to determine if ripple oscillations (80-120Hz), detected in intracranial EEG (iEEG) recordings of epilepsy patients, correlate with an enhancement or disruption of verbal episodic memory encoding. Methods: We defined ripple and spike events in depth iEEG recordings during list learning in 107 patients with focal epilepsy. We used logistic regression models (LRMs) to investigate the relationship between the occurrence of ripple and spike events during word presentation and the odds of successful word recall following a distractor epoch, and included the seizure onset zone (SOZ) as a covariate in the LRMs. Results: We detected events during 58,312 word presentation trials from 7,630 unique electrode sites. The probability of ripple on spike (RonS) events was increased in the seizure onset zone (SOZ, p<0.04). In the left temporal neocortex RonS events during word presentation corresponded with a decrease in the odds ratio (OR) of successful recall, however this effect only met significance in the SOZ (OR of word recall 0.71, 95% CI: 0.59-0.85, n=158 events, adaptive Hochberg p<0.01). Ripple on oscillation events (RonO) that occurred in the left temporal neocortex non-SOZ also correlated with decreased odds of successful recall (OR 0.52, 95% CI: 0.34-0.80, n=140, adaptive Hochberg , p<0.01). Spikes and RonS that occurred during word presentation in the left middle temporal gyrus during word presentation correlated with the most significant decrease in the odds of successful recall, irrespective of the location of the SOZ (adaptive Hochberg, p<0.01). Conclusion: Ripples and spikes generated in left temporal neocortex are associated with impaired verbal episodic memory encoding

2014 Epilepsy Benchmarks Area III: Improve Treatment Options for Controlling Seizures and Epilepsy-Related Conditions Without Side Effects

The Epilepsy Benchmark goals in Area III focus on making progress in understanding and controlling seizures and related conditions as well as on developing biomarkers and new therapies that will reduce seizures and improve outcomes for individuals with epilepsy. Area III emphasizes a need to better understand the ways in which seizures start, propagate, and terminate and whether those network processes are common or unique in different forms of epilepsy. The application of that knowledge to improved seizure prediction and detection will also play a role in improving patient outcomes. Animal models of treatment-resistant epilepsy that are aligned with etiologies and clinical features of human epilepsies are especially encouraged as necessary tools to understand mechanisms and test potential therapies. Antiseizure therapies that target (either alone or in combination) novel or multiple seizure mechanisms are prioritized in this section of the Benchmarks. Area III goals also highlight validation of biomarkers of treatment response and safety risk, effective self-management, and patient-centered outcome measures as important areas of emphasis for the next five to ten years

Big data in epilepsy: Clinical and research considerations. Report from the Epilepsy Big Data Task Force of the International League Against Epilepsy

Epilepsy is a heterogeneous condition with disparate etiologies and phenotypic and genotypic characteristics. Clinical and research aspects are accordingly varied, ranging from epidemiological to molecular, spanning clinical trials and outcomes, gene and drug discovery, imaging, electroencephalography, pathology, epilepsy surgery, digital technologies, and numerous others. Epilepsy data are collected in the terabytes and petabytes, pushing the limits of current capabilities. Modern computing firepower and advances in machine and deep learning, pioneered in other diseases, open up exciting possibilities for epilepsy too. However, without carefully designed approaches to acquiring, standardizing, curating, and making available such data, there is a risk of failure. Thus, careful construction of relevant ontologies, with intimate stakeholder inputs, provides the requisite scaffolding for more ambitious big data undertakings, such as an epilepsy data commons. In this review, we assess the clinical and research epilepsy landscapes in the big data arena, current challenges, and future directions, and make the case for a systematic approach to epilepsy big data

Liquid State Anomalies for the Stell-Hemmer Core-Softened Potential

We study the Stell-Hemmer potential using both analytic (exact $1d$ and approximate $2d$) solutions and numerical $2d$ simulations. We observe in the liquid phase an anomalous decrease in specific volume and isothermal compressibility upon heating, and an anomalous increase in the diffusion coefficient with pressure. We relate the anomalies to the existence of two different local structures in the liquid phase. Our results are consistent with the possibility of a low temperature/high pressure liquid-liquid phase transition.Comment: 4 pages in one gzipped ps file including 11 figures; One RevTex and 11 gzipped eps figure

Controversies in epilepsy: Debates held during the Fourth International Workshop on Seizure Prediction

Debates on six controversial topics were held during the Fourth International Workshop on Seizure Prediction (IWSP4) convened in Kansas City, KS, USA, July 4–7, 2009. The topics were (1) Ictogenesis: Focus versus Network? (2) Spikes and Seizures: Step-relatives or Siblings? (3) Ictogenesis: A Result of Hyposynchrony? (4) Can Focal Seizures Be Caused by Excessive Inhibition? (5) Do High-Frequency Oscillations Provide Relevant Independent Information? (6) Phase Synchronization: Is It Worthwhile as Measured? This article, written by the IWSP4 organizing committee and the debaters, summarizes the arguments presented during the debates

Life cycle assessment of the environmental performance of conventional and organic methods of open field pepper cultivation

Summarization: As the scale of the organic cultivation sector keeps increasing, there is growing demand for reliable data on organic agriculture and its effect on the environment. Conventional agriculture uses chemical fertilizers and pesticides, whilst organic cultivation mainly relies on crop rotation and organic fertilizers. The aim of this work is to quantify and compare the environmental sustainability of typical conventional and organic pepper cultivation systems. Methods: Two open field pepper cultivations, both located in the Anthemountas basin, Northern Greece, are selected as case studies. Life cycle assessment (LCA) is used to quantify the overall environmental footprint and identify particular environmental weaknesses (i.e. unsustainable practices) of each cultivation system. Results are analysed at both midpoint and endpoint levels in order to obtain a comprehensive overview of the environmental sustainability of each system. Attributional LCA (ALCA) is employed to identify emissions associated with the life cycles of the two systems. Results are presented for problem-oriented (midpoint) and damage-oriented (endpoint) approaches, using ReCiPe impact assessment. Results and discussion: At midpoint level, conventional cultivation exhibits about threefold higher environmental impact on freshwater eutrophication, than organic cultivation. This arises from the extensive use of nitrogen and phosphorus-based fertilizers, with consequent direct emissions to the environment. The remaining impact categories are mainly affected by irrigation, with associated indirect emissions linked to electricity production. At endpoint level, the main hotspots identified for conventional cultivation are irrigation and fertilizing, due to intensive use of chemical fertilizers and (to a lesser degree) pesticides. For organic pepper cultivation, the main environmental hotspots are irrigation, machinery use, and manure loading and spreading processes. Of these, the highest score for irrigation derives from the heavy electricity consumption required for groundwater pumping associated with the fossil-fuel-dependent Greek electricity mix. Conclusions: Organic and conventional cultivation systems have similar total environmental impacts per unit of product, with organic cultivation achieving lower environmental impacts in ‘freshwater eutrophication’, ‘climate change’, ‘terrestrial acidification’ and ‘marine eutrophication’ categories. Conventional cultivation has a significantly greater effect on the freshwater eutrophication impact category, due to phosphate emissions arising from application of chemical fertilizers.Presented on: International Journal of Life Cycle Assessmen

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types