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Abstract Duvalo “volcano” is a site of anomalous geogenic degassing close to Ohrid (North Macedonia) not related to volcanic activity, despite its name. CO2 flux measurements made with the accumulation chamber (321 sites over ∼50,000 m2) showed fluxes up to nearly 60,000 g m−2 d−1, sustaining a total output of ∼67 t d−1. Soil gas samples were taken at 50 cm depth from sites with high CO2 fluxes and analyzed for their chemical and isotope composition. The gas is mainly composed by CO2 (>90%) with significant concentrations of H2S (up to 0.55%) and CH4 (up to 0.32%). The isotope compositions of He (R/RA 0.10) and of CO2 (δ13C ∼ 0‰) exclude significant mantle contribution, while δ13C‐CH4 (∼−35‰) and δ2H‐CH4 (∼−170‰) suggest a thermogenic origin for CH4. The area is characterized by intense seismic activity and Duvalo corresponds to an active tectonic structure bordering the Ohrid graben. The production of H2S within the stratigraphic sequence may be explained by thermochemical reduction of sulfate. The uprising H2S is partially oxidized to sulfuric acid that, reacting with carbonate rocks, releases CO2. The tectonic structure of the area favors fluid circulation, sustaining H2S production and oxidation, CO2 production and allowing the escape of the gases to the atmosphere. In the end, Duvalo represents a tectonic‐related CO2 degassing area whose gases originate mostly, if not exclusively, in the shallowest part of the crust (1,000 t km−2 d−1).

Abstract Background Shoulder arthroscopy is a safe and effective procedure with a low complication rate. Although rare, there are potentially life-threatening risks such as fluid extravasation causing airway compromise. Case presentation We report the case of a 65-year-old female treated with an arthroscopic rotator cuff repair who had significant extravasation of arthroscopic fluid causing severe facial and neck swelling. Overnight intubation was required for respiratory monitoring until the edema had resolved enough to allow safe extubation. Conclusion This case highlights the risk factors and clinical course of a patient with airway compromise caused by extravasation of fluid during shoulder arthroscopy. Although shoulder arthroscopy is a safe procedure, surgeon familiarity with the risk factors for this complication and close monitoring can aid in its identification and allow for appropriate treatment.

Verrucomicrobial methanotrophs are a group of aerobic bacteria isolated from volcanic environments. They are acidophiles, characterized by the presence of a particulate methane monooxygenase (pMMO) and a XoxF-type methanol dehydrogenase (MDH). Metagenomic analysis of DNA extracted from the soil of Favara Grande, a geothermal area on Pantelleria Island, Italy, revealed the presence of two verrucomicrobial Metagenome Assembled Genomes (MAGs). One of these MAGs did not phylogenetically classify within any existing genus. After extensive analysis of the MAG, we propose the name of “Candidatus Methylacidithermus pantelleriae” PQ17 gen. nov. sp. nov. The MAG consisted of 2,466,655 bp, 71 contigs and 3,127 predicted coding sequences. Completeness was found at 98.6% and contamination at 1.3%. Genes encoding the pMMO and XoxF-MDH were identified. Inorganic carbon fixation might use the Calvin-Benson-Bassham cycle since all genes were identified. The serine and ribulose monophosphate pathways were incomplete. The detoxification of formaldehyde could follow the tetrahydrofolate pathway. Furthermore, “Ca. Methylacidithermus pantelleriae” might be capable of nitric oxide reduction but genes for dissimilatory nitrate reduction and nitrogen fixation were not identified. Unlike other verrucomicrobial methanotrophs, genes encoding for enzymes involved in hydrogen oxidation could not be found. In conclusion, the discovery of this new MAG expands the diversity and metabolism of verrucomicrobial methanotrophs.

The Favara Grande is a geothermal area located on Pantelleria Island, Italy. The area is characterized high temperatures in the top layer of the soil (60°C), low pH (3–5) and hydrothermal gas emissions mainly composed of carbon dioxide (CO2), methane (CH4), and hydrogen (H2). These geothermal features may provide a suitable niche for the growth of chemolithotrophic thermoacidophiles, including the lanthanide-dependent methanotrophs of the phylum Verrucomicrobia. In this study, we started enrichment cultures inoculated with soil of the Favara Grande at 50 and 60°C with CH4 as energy source and medium containing sufficient lanthanides at pH 3 and 5. From these cultures, a verrucomicrobial methanotroph could be isolated via serial dilution and floating filters techniques. The genome of strain AP8 was sequenced and based on phylogenetic analysis we propose to name this new species Methylacidimicrobium thermophilum AP8. The transcriptome data at μmax (0.051 ± 0.001 h−1, doubling time ~14 h) of the new strain showed a high expression of the pmoCAB2 operon encoding the membrane-bound methane monooxygenase and of the gene xoxF1, encoding the lanthanide-dependent methanol dehydrogenase. A second pmoCAB operon and xoxF2 gene were not expressed. The physiology of strain AP8 was further investigated and revealed an optimal growth in a pH range of 3–5 at 50°C, representing the first thermophilic strain of the genus Methylacidimicrobium. Moreover, strain AP8 had a KS(app) for methane of 8 ± 1 μM. Beside methane, a type 1b [NiFe] hydrogenase enabled hydrogen oxidation at oxygen concentrations up to 1%. Taken together, our results expand the knowledge on the characteristics and adaptations of verrucomicrobial methanotrophs in hydrothermal environments and add a new thermophilic strain to the genus Methylacidimicrobium.

ABSTRACT Volcanic and geothermal environments are characterized by low pH, high temperatures, and gas emissions consisting of mainly CO2 and varied CH4, H2S, and H2 contents which allow the formation of chemolithoautotrophic microbial communities. To determine the link between the emitted gases and the microbial community composition, geochemical and metagenomic analysis were performed. Soil samples of the geothermic region Favara Grande (Pantelleria, Italy) were taken at various depths (1 to 50 cm). Analysis of the gas composition revealed that CH4 and H2 have the potential to serve as the driving forces for the microbial community. Our metagenomic analysis revealed a high relative abundance of Bacteria in the top layer (1 to 10 cm), but the relative abundance of Archaea increased with depth from 32% to 70%. In particular, a putative hydrogenotrophic methanogenic archaeon, related to Methanocella conradii, appeared to have a high relative abundance (63%) in deeper layers. A variety of [NiFe]-hydrogenase genes were detected, showing that H2 was an important electron donor for microaerobic microorganisms in the upper layers. Furthermore, the bacterial population included verrucomicrobial and proteobacterial methanotrophs, the former showing an up to 7.8 times higher relative abundance. Analysis of the metabolic potential of this microbial community showed a clear capacity to oxidize CH4 aerobically, as several genes for distinct particulate methane monooxygenases and lanthanide-dependent methanol dehydrogenases (XoxF-type) were retrieved. Analysis of the CO2 fixation pathways showed the presence of the Calvin-Benson-Bassham cycle, the Wood-Ljungdahl pathway, and the (reverse) tricarboxylic acid (TCA) cycle, the latter being the most represented carbon fixation pathway. This study indicates that the methane emissions in the Favara Grande might be a combination of geothermal activity and biological processes and further provides insights into the diversity of the microbial population thriving on CH4 and H2. IMPORTANCE The Favara Grande nature reserve on the volcanic island of Pantelleria (Italy) is known for its geothermal gas emissions and high soil temperatures. These volcanic soil ecosystems represent “hot spots” of greenhouse gas emissions. The unique community might be shaped by the hostile conditions in the ecosystem, and it is involved in the cycling of elements such as carbon, hydrogen, sulfur, and nitrogen. Our metagenome study revealed that most of the microorganisms in this extreme environment are only distantly related to cultivated bacteria. The results obtained profoundly increased the understanding of these natural hot spots of greenhouse gas production/degradation and will help to enrich and isolate the microbial key players. After isolation, it will become possible to unravel the molecular mechanisms by which they adapt to extreme (thermo/acidophilic) conditions, and this may lead to new green enzymatic catalysts and technologies for industry.

Volcanic and geothermal areas are hot and often acidic environments that emit geothermal gasses, including H2, CO and CO2. Geothermal gasses mix with air, creating conditions where thermoacidophilic aerobic H2- and CO-oxidizing microorganisms could thrive. Here, we describe the isolation of two Kyrpidia spormannii strains, which can grow autotrophically by oxidizing H2 and CO with oxygen. These strains, FAVT5 and COOX1, were isolated from the geothermal soils of the Favara Grande on Pantelleria Island, Italy. Extended physiology studies were performed with K. spormannii FAVT5, and showed that this strain grows optimally at 55°C and pH 5.0. The highest growth rate is obtained using H2 as energy source (μmax 0.19 ± 0.02 h–1, doubling time 3.6 h). K. spormannii FAVT5 can additionally grow on a variety of organic substrates, including some alcohols, volatile fatty acids and amino acids. The genome of each strain encodes for two O2-tolerant hydrogenases belonging to [NiFe] group 2a hydrogenases and transcriptome studies using K. spormannii FAVT5 showed that both hydrogenases are expressed under H2 limiting conditions. So far no Firmicutes except K. spormannii FAVT5 have been reported to exhibit a high affinity for H2, with a Ks of 327 ± 24 nM. The genomes of each strain encode for one putative CO dehydrogenase, belonging to Form II aerobic CO dehydrogenases. The genomic potential and physiological properties of these Kyrpidia strains seem to be quite well adapted to thrive in the harsh environmental volcanic conditions.

Nisyros Island (Greece) is an active volcano hosting a high-enthalpy geothermal system. During June 2013, an extensive survey on Hg concentrations in different matrices (fumarolic fluids, atmosphere, soils, and plants) was carried out at the Lakki Plain, an intracaldera area affected by widespread soil and fumarolic degassing. Concentrations of gaseous elemental mercury (GEM), together with H2S and CO2, were simultaneously measured in both the fumarolic emissions and the atmosphere around them. At the same time, 130 samples of top soils and 31 samples of plants (Cistus creticus and salvifolius and Erica arborea and manipuliflora) were collected for Hg analysis. Mercury concentrations in fumarolic gases ranged from 10,500 to 46,300 ng/m3, while Hg concentrations in the air ranged from high background values in the Lakki Plain caldera (10-36 ng/m3) up to 7100 ng/m3 in the fumarolic areas. Outside the caldera, the concentrations were relatively low (2-5 ng/m3). The positive correlation with both CO2 and H2S in air highlighted the importance of hydrothermal gases as carrier for GEM. On the other hand, soil Hg concentrations (0.023-13.7 μg/g) showed no significant correlations with CO2 and H2S in the soil gases, whereas it showed a positive correlation with total S content and an inverse one with the soil pH, evidencing the complexity of the processes involving Hg carried by hydrothermal gases while passing through the soil. Total Hg concentrations in plant leaves (0.010-0.112 μg/g) had no direct correlation with soil Hg, with Cistus leaves containing higher values of Hg with respect to Erica. Even though GEM concentrations in the air within the caldera are sometimes orders of magnitude above the global background, they should not be considered dangerous to human health. Values exceeding the WHO guideline value of 1000 ng/m3 are very rare (

El objetivo del presente estudio es determinar los tamaños mandibulares normales para nuestra población colombiana en pacientes menores de 7 años, aportando tablas de normalidad que relacionen el tamaño mandibular con el del maxilar, la base de cráneo, la talla y el peso del paciente. Realizamos un estudio de corte transversal con 600 pacientes sanos de 0 a 7 años de edad, comparando el peso y talla de la muestra con el de la población general. Tomamos las siguientes mediciones antropométricas: otobasion inferior-nasion, otobasion inferiorgnation, trago-subnasion-trago, trago-pogonion-trago y overjet (sobremordida horizontal) y calculamos el índice mandibular (arco maxilar x overjet / arco mandibular). Relacionamos todas las medidas con el peso y talla de cada paciente. Obtuvimos las tablas de normalidad, tablas de correlación y curvas de crecimiento. Comprobamos que el crecimiento mandibular se comporta de forma logarítmica en el primer año de vida y luego lo hace linealmente. La sobremordida horizontal (overjet) promedio es de 2 mm con un rango de normalidad de 0 a 4 mm, con una alta correlación con el índice mandibular. La talla presenta una muy buena correlación con las medidas antropométricas analizadas, no así el peso y la edad. No se demostró un aumento en la velocidad de crecimiento mandibular a lo largo del tiempo en comparación con el crecimiento maxilar y de la base del cráneo. La mejoría de la vía aérea esperada en el primer año de vida en pacientes con micrognatia podría ser secundaria al crecimiento logarítmico máxilo-mandibular y no al sobrecrecimiento mandibular compensatorio o catch up mandibular.

Volcanic and geothermal systems emit endogenous gases by widespread degassing from soils, including CH4, a greenhouse gas twenty-five times as potent as CO2. Recently, it has been demonstrated that volcanic or geothermal soils are not only a source of methane, but are also sites of methanotrophic activity. Methanotrophs are able to consume 10–40 Tg of CH4 a−1 and to trap more than 50% of the methane degassing through the soils. We report on methane microbial oxidation in the geothermally most active site of Pantelleria (Italy), Favara Grande, whose total methane emission was previously estimated at about 2.5 Mg a−1 (t a−1). Laboratory incubation experiments with three top-soil samples from Favara Grande indicated methane consumption values of up to 59.2 nmol g−1 soil d.w. h−1. One of the three sites, FAV2, where the highest oxidation rate was detected, was further analysed on a vertical soil profile, the maximum methane consumption was measured in the top-soil layer, and values greater than 6.23 nmol g−1 h−1 were still detected up to a depth of 13 cm. The highest consumption rate was measured at 37 °C, but a still detectable consumption at 80 °C (> 1.25 nmol g−1 h−1) was recorded. The soil total DNA extracted from the three samples was probed by Polymerase Chain Reaction (PCR) using standard proteobacterial primers and newly designed verrucomicrobial primers, targeting the unique methane monooxygenase gene pmoA; the presence of methanotrophs was detected at sites FAV2 and FAV3, but not at FAV1, where harsher chemical–physical conditions and negligible methane oxidation were detected. The pmoA gene libraries from the most active site (FAV2) pointed to a high diversity of gammaproteobacterial methanotrophs, distantly related to Methylocaldum-Metylococcus genera, and the presence of the newly discovered acido-thermophilic Verrucomicrobia methanotrophs. Alphaproteobacteria of the genus Methylocystis were isolated from enrichment cultures under a methane-containing atmosphere at 37 °C. The isolates grow at a pH range of 3.5 to 8 and temperatures of 18–45 °C, and consume 160 nmol of CH4 h−1 mL−1 of culture. Soils from Favara Grande showed the largest diversity of methanotrophic bacteria detected until now in a geothermal soil. While methanotrophic Verrucomicrobia are reported as dominating highly acidic geothermal sites, our results suggest that slightly acidic soils, in high-enthalpy geothermal systems, host a more diverse group of both culturable and uncultivated methanotrophs.

In this work we will show how local substrate patterning leads to a long range controlled propagation of dislocations in SiGe films grown on Si(001) substrates. Dislocations preferentially nucleate in the inhomogeneous strain field associated with the patterned pits, and then partialize on the local (111) surfaces which form the pit sidewalls. The resulting V-shaped defects extend for several microns and effectively block the propagation of randomly nucleated dislocations which propagate in the perpendicular direction. The surface morphology and strain fields associated with the extended defects have been characterized by atomic force microscopy and μRaman spectroscopy, and the defects have been directly observed with high resolution transmission electron microscopy. [ABSTRACT FROM AUTHOR]

Objective: Non-invasive biomarkers have recently shown promise for seizure forecasting in people with epilepsy. In this work, we developed a seizure-day forecasting algorithm based on nocturnal sleep features acquired using a smart shirt., Methods: Seventy-eight individuals with epilepsy admitted to the Centre hospitalier de l'Université de Montréal epilepsy monitoring unit wore the Hexoskin biometric smart shirt during their stay. The shirt continuously measures electrocardiography, respiratory, and accelerometry activity. Ten sleep features, including sleep efficiency, sleep latency, sleep duration, time spent in non-rapid eye movement sleep (NREM) and rapid eye movement sleep (REM), wakefulness after sleep onset, average heart and breathing rates, high-frequency heart rate variability, and the number of position changes, were automatically computed using the Hexoskin sleep algorithm. Each night's features were then normalized using a reference night for each patient. A support vector machine classifier was trained for pseudo-prospective seizure-day forecasting, with forecasting horizons of 16- and 24-h to include both diurnal and nocturnal seizures (24-h) or diurnal seizures only (16-h). The algorithm's performance was assessed using a nested leave-one-patient-out cross-validation approach., Results: Improvement over chance (IoC) performances were achieved for 48.7% and 40% of patients with the 16- and 24-h forecasting horizons, respectively. For patients with IoC performances, the proposed algorithm reached mean IoC, sensitivity and time in warning of 34.3%, 86.0%, and 51.7%, respectively for the 16-h horizon, and 34.2%, 64.4% and 30.2%, respectively, for the 24-h horizon., Significance: Smart shirt-based nocturnal sleep analysis holds promise as a non-invasive approach for seizure-day forecasting in a subset of people with epilepsy. Further investigations, particularly in a residential setting with long-term recordings, could pave the way for the development of innovative and practical seizure forecasting devices., Plain Language Summary: Seizure forecasting with wearable devices may improve the quality of life of people living with epilepsy who experience unpredictable, recurrent seizures. In this study, we have developed a seizure forecasting algorithm using sleep characteristics obtained from a smart shirt worn at night by a large number of hospitalized patients with epilepsy (78). A daily seizure forecast was generated following each night using machine learning methods. Our results show that around half of people with epilepsy may benefit from such an approach., (© 2024 The Author(s). Epilepsia Open published by Wiley Periodicals LLC on behalf of International League Against Epilepsy.)

Wearable-based seizure detection devices hold promise in reducing seizure-related adverse events and relieving the daily stress experienced by people with epilepsy. In this work, we present the latest evidence regarding the performance of three seizure detection wearables (eight studies) commercially available in Canada to provide guidance to clinicians. Overall, their ability to detect focal-to-bilateral and/or generalized tonic-clonic seizures ranges between 21.0% and 98.15% in sensitivity, with the 24h false alarm rates ranging from 0 to 1.28. While performance in epilepsy monitoring units show promise, the lack of evidence in outpatient settings precludes strong recommendations for their use in daily life.

Connectivity analyses of intracranial electroencephalography (iEEG) could guide surgical planning for epilepsy surgery by improving the delineation of the seizure onset zone. Traditional approaches fail to quantify important interactions between frequency components. To assess if effective connectivity based on cross-bispectrum -a measure of nonlinear multivariate cross-frequency coupling- can quantitatively identify generators of seizure activity, cross-bispectrum connectivity between channels was computed from iEEG recordings of 5 patients (34 seizures) with good postsurgical outcome. Personalized thresholds of 50% and 80% of the maximum coupling values were used to identify generating electrode channels. In all patients, outflow coupling between α (8-15 Hz) and β (16-31 Hz) frequencies identified at least one electrode inside the resected seizure onset zone. With the 50% and 80% thresholds respectively, an average of 5 (44.7%; specificity = 82.6%) and 2 (22.5%; specificity = 99.0%) resected electrodes were correctly identified. Results show promise for the automatic identification of the seizure onset zone based on cross-bispectrum connectivity analysis.

Introduction: While it is known that poor sleep is a seizure precipitant, this association remains poorly quantified. This study investigated whether seizures are preceded by significant changes in sleep efficiency as measured by a wearable equipped with an electrocardiogram, respiratory bands, and an accelerometer., Methods: Nocturnal recordings from 47 people with epilepsy hospitalized at our epilepsy monitoring unit were analyzed (304 nights). Sleep metrics during nights followed by epileptic seizures (24 h post-awakening) were compared to those of nights which were not., Results: Lower sleep efficiency (percentage of sleep during the night) was found in the nights preceding seizure days ( p < 0.05). Each standard deviation decrease in sleep efficiency and increase in wake after sleep onset was respectively associated with a 1.25-fold (95 % CI: 1.05 to 1.42, p < 0.05) and 1.49-fold (95 % CI: 1.17 to 1.92, p < 0.01) increased odds of seizure occurrence the following day. Furthermore, nocturnal seizures were associated with significantly lower sleep efficiency and higher wake after sleep onset ( p < 0.05), as well as increased odds of seizure occurrence following wake (OR: 5.86, 95 % CI: 2.99 to 11.77, p < 0.001)., Discussion: Findings indicate lower sleep efficiency during nights preceding seizures, suggesting that wearable sensors could be promising tools for sleep-based seizure-day forecasting in people with epilepsy., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Gagliano, Ding, Toffa, Beauregard, Robert, Lesage, Sawan, Nguyen and Bou Assi.)

Objective: Uncontrolled epilepsy creates a constant source of worry for patients and puts them at a high risk of injury. Identifying recurrent "premonitory" symptoms of seizures and using them to recalibrate seizure prediction algorithms may improve prediction performances. This study aimed to investigate patients' ability to predict oncoming seizures based on preictal symptoms., Methods: Through an online survey, demographics and clinical characteristics (e.g., seizure frequency, epilepsy duration, and postictal symptom duration) were collected from people with epilepsy and caregivers across Canada. Respondents were asked to answer questions regarding their ability to predict seizures through warning symptoms. A total of 196 patients and 150 caregivers were included and were separated into three groups: those who reported warning symptoms within the 5 minutes preceding a seizure, prodromes (symptoms earlier than 5 minutes before seizure), and no warning symptoms., Results: Overall, 12.2% of patients and 12.0% of caregivers reported predictive prodromes ranging from 5 minutes to more than 24 hours before the seizures (median of 2 hours). The most common were dizziness/vertigo (28%), mood changes (26%), and cognitive changes (21%). Statistical testing showed that respondents who reported prodromes also reported significantly longer postictal recovery periods compared to those who did not report predictive prodromes ( P < 0.05)., Conclusion: Findings suggest that patients who present predictive seizure prodromes may be characterized by longer patient-reported postictal recovery periods. Studying the correlation between seizure severity and predictability and investigating the electrical activity underlying prodromes may improve our understanding of preictal mechanisms and ability to predict seizures.

Over a third of patients suffering from epilepsy continue to live with recurrent disabling seizures and would greatly benefit from personalized seizure forecasting. While electroencephalography (EEG) remains most popular for studying subject-specific epileptic precursors, dysfunctions of the autonomous nervous system, notably cardiac activity measured in heart rate variability (HRV), have also been associated with epileptic seizures. This work proposes an unsupervised clustering technique which aims to automatically identify preictal HRV changes in 9 patients who underwent simultaneous electrocardiography (ECG) and intracranial EEG presurgical monitoring at the University of Montreal Hospital Center. A 2-class k-means clustering combined with a quantitative preictal HRV change detection technique were adopted in a subject- and seizure-specific manner. Results indicate inter and intra-patient variability in preictal HRV changes (between 3.5 and 6.5 min before seizure onset) and a statistically significant negative correlation between the time of change in HRV state and the duration of seizures (p<0.05). The presented findings show promise for new avenues of research regarding multimodal seizure prediction and unsupervised preictal time assessment.Clinical Relevance- This study proposed an unsupervised technique for quantitatively identifying preictal HRV changes which can be eventually used to implement an ECG-based seizure forecasting algorithm.

According to Fourier's law, a temperature difference across a material results in a linear temperature profile and a thermal conductance that decreases inversely proportional to the system length. These are the hallmarks of diffusive heat flow. Here, we report heat flow in ultrathin (25 nm) GaP nanowires in the absence of a temperature gradient within the wire and find that the heat conductance is independent of wire length. These observations deviate from Fourier's law and are direct proof of ballistic heat flow, persisting for wire lengths up to at least 15 μm at room temperature. When doubling the wire diameter, a remarkably sudden transition to diffusive heat flow is observed. The ballistic heat flow in the ultrathin wires can be modeled within Landauer's formalism by ballistic phonons with an extraordinarily long mean free path.

This work proposes a novel approach for the classification of interictal and preictal brain states based on bispectrum analysis and recurrent Long Short-Term Memory (LSTM) neural networks. Two features were first extracted from bilateral intracranial electroencephalography (iEEG) recordings of dogs with naturally occurring focal epilepsy. Single-layer LSTM networks were trained to classify 5-min long feature vectors as preictal or interictal. Classification performances were compared to previous work involving multilayer perceptron networks and higher-order spectral (HOS) features on the same dataset. The proposed LSTM network proved superior to the multilayer perceptron network and achieved an average classification accuracy of 86.29% on held-out data. Results imply the possibility of forecasting epileptic seizures using recurrent neural networks, with minimal feature extraction.

The ability to accurately forecast seizures could significantly improve the quality of life of patients with drug-refractory epilepsy. Prediction capabilities rely on the adequate identification of seizure activity precursors from electroencephalography recordings. Although a long list of features has been proposed, none of these is able to independently characterize the brain states during transition to a seizure. This work assessed the feasibility of using the bispectrum, an advanced signal processing technique based on higher order statistics, as a precursor of seizure activity. Quantitative features were extracted from the bispectrum and passed through two statistical tests to check for significant differences between preictal and interictal recordings. Results showed statistically significant differences (p < 0.05) between preictal and interictal states using all bispectrum-extracted features. We used normalized bispectral entropy, normalized bispectral squared entropy, and mean of magnitude as inputs to a 5-layer multilayer perceptron classifier and achieved respective held-out test accuracies of 78.11%, 72.64%, and 73.26%.

Nanowires have emerged as a promising platform for the development of novel and high-quality heterostructures at large lattice misfit, inaccessible in a thin film configuration. However, despite core-shell nanowires allowing a very efficient elastic release of the misfit strain, the growth of highly uniform arrays of nanowire heterostructures still represents a challenge, for example due to a strain-induced bending morphology. Here we investigate the bending of wurtzite GaP/In x Ga 1-x P core-shell nanowires using transmission electron microscopy and energy dispersive x-ray spectroscopy, both in terms of geometric and compositional asymmetry with respect to the longitudinal axis. We compare the experimental data with finite element method simulations in three dimensions, showing that both asymmetries are responsible for the actual bending. Such findings are valid for all lattice-mismatched core-shell nanowire heterostructures based on ternary alloys. Our work provides a quantitative understanding of the bending effect in general while also suggesting a strategy to minimise it.

Direct band gap III-V semiconductors, emitting efficiently in the amber-green region of the visible spectrum, are still missing, causing loss in efficiency in light emitting diodes operating in this region, a phenomenon known as the "green gap". Novel geometries and crystal symmetries however show strong promise in overcoming this limit. Here we develop a novel material system, consisting of wurtzite Al x In 1- x P nanowires, which is predicted to have a direct band gap in the green region. The nanowires are grown with selective area metalorganic vapor phase epitaxy and show wurtzite crystal purity from transmission electron microscopy. We show strong light emission at room temperature between the near-infrared 875 nm (1.42 eV) and the "pure green" 555 nm (2.23 eV). We investigate the band structure of wurtzite Al x In 1- x P using time-resolved and temperature-dependent photoluminescence measurements and compare the experimental results with density functional theory simulations, obtaining excellent agreement. Our work paves the way for high-efficiency green light emitting diodes based on wurtzite III-phosphide nanowires.

Seizure forecasting would improve the quality of life of patients with refractory epilepsy. Although early findings were optimistic, no single feature has been found capable of individually characterizing brain dynamics during transition to seizure. Cross-frequency phase amplitude coupling has been recently proposed as a precursor of seizure activity. This work evaluates the existence of a statistically significant difference in mean phase amplitude coupling distribution between the preictal and interictal states of seizures in dogs with bilaterally implanted intracranial electrodes. Results show a statistically significant change (p<0.05) of phase amplitude coupling during the preictal phase. This change is correlated with the position of implanted electrodes and is more significant within high-gamma frequency bands. These findings highlight the potential benefit of bilateral iEEG analysis and the feasibility of seizure forecasting based on slow modulation of high frequency amplitude., (Copyright © 2017 Elsevier B.V. All rights reserved.)

One of the major challenges in the growth of quantum well and quantum dot heterostructures is the realization of atomically sharp interfaces. Nanowires provide a new opportunity to engineer the band structure as they facilitate the controlled switching of the crystal structure between the zinc-blende (ZB) and wurtzite (WZ) phases. Such a crystal phase switching results in the formation of crystal phase quantum wells (CPQWs) and quantum dots (CPQDs). For GaP CPQWs, the inherent electric fields due to the discontinuity of the spontaneous polarization at the WZ/ZB junctions lead to the confinement of both types of charge carriers at the opposite interfaces of the WZ/ZB/WZ structure. This confinement leads to a novel type of transition across a ZB flat plate barrier. Here, we show digital tuning of the visible emission of WZ/ZB/WZ CPQWs in a GaP nanowire by changing the thickness of the ZB barrier. The energy spacing between the sharp emission lines is uniform and is defined by the addition of single ZB monolayers. The controlled growth of identical quantum wells with atomically flat interfaces at predefined positions featuring digitally tunable discrete emission energies may provide a new route to further advance entangled photons in solid state quantum systems.

Group IV semiconductor optoelectronic devices are now possible by using strain-free direct band gap GeSn alloys grown on a Ge/Si virtual substrate with Sn contents above 9%. Here, we demonstrate the growth of Ge/GeSn core/shell nanowire arrays with Sn incorporation up to 13% and without the formation of Sn clusters. The nanowire geometry promotes strain relaxation in the Ge 0.87 Sn 0.13 shell and limits the formation of structural defects. This results in room-temperature photoluminescence centered at 0.465 eV and enhanced absorption above 98%. Therefore, direct band gap GeSn grown in a nanowire geometry holds promise as a low-cost and high-efficiency material for photodetectors operating in the short-wave infrared and thermal imaging devices.

Thanks to their uniqueness, nanowires allow the realization of novel semiconductor crystal structures with yet unexplored properties, which can be key to overcome current technological limits. Here we develop the growth of wurtzite GaP/In x Ga 1-x P core-shell nanowires with tunable indium concentration and optical emission in the visible region from 590 nm (2.1 eV) to 760 nm (1.6 eV). We demonstrate a pseudodirect (Γ 8c -Γ 9v ) to direct (Γ 7c -Γ 9v ) transition crossover through experimental and theoretical approach. Time resolved and temperature dependent photoluminescence measurements were used, which led to the observation of a steep change in carrier lifetime and temperature dependence by respectively one and 3 orders of magnitude in the range 0.28 ± 0.04 ≤ x ≤ 0.41 ± 0.04. Our work reveals the electronic properties of wurtzite In x Ga 1-x P.

In this work we will show how local substrate patterning leads to a long range controlled propagation of dislocations in SiGe films grown on Si(001) substrates. Dislocations preferentially nucleate in the inhomogeneous strain field associated with the patterned pits, and then partialize on the local (111) surfaces which form the pit sidewalls. The resulting V-shaped defects extend for several microns and effectively block the propagation of randomly nucleated dislocations which propagate in the perpendicular direction. The surface morphology and strain fields associated with the extended defects have been characterized by atomic force microscopy and μRaman spectroscopy, and the defects have been directly observed with high resolution transmission electron microscopy.

The growth of wurtzite/zincblende (WZ and ZB, respectively) superstructures opens new avenues for band structure engineering and holds the promise of digitally controlling the energy spectrum of quantum confined systems. Here, we study growth kinetics of pure and thus defect-free WZ/ZB homostructures in GaP nanowires with the aim to obtain monolayer control of the ZB and WZ segment lengths. We find that the Ga concentration and the supersaturation in the catalyst particle are the key parameters determining growth kinetics. These parameters can be tuned by the gallium partial pressure and the temperature. The formation of WZ and ZB can be understood with a model based on nucleation either at the triple phase line for the WZ phase or in the center of the solid-liquid interface for the ZB phase. Furthermore, the observed delay/offset time needed to induce WZ and ZB growth after growth of the other phase can be explained within this framework.

Each geriatric patient has observable problems which can generate treatment goals implemented by a treatment plan. Extensive record keeping would be required to document this tripartite scheme. In practice, either problem-oriented or goal-oriented records are used. Problem records tend to drift toward a goal concept, since problems are usually stated in only sufficient detail to serve as a guide to treatment. The results of a problem-oriented format are described for 143 state hospital patients whose mean age was 74 years. The most common number of problems was 5 per patient. Physical problems were the most frequent (N equals 456), followed by behavioral (N equals 203), thought-related (N equals 156), administrative (N equals 99), affective (N equals 69), and attitudinal (N equals 10). The author's experience with both systems leaves them with preference for the problem-oriented system with geriatric patients since physical problems are so numerous.