Three-dimensional nitrogen-doped graphene supported molybdenum disulfide nanoparticles as an advanced catalyst for hydrogen evolution reaction

An efficient three-dimensional (3D) hybrid material of nitrogen-doped graphene sheets (N-RGO) supporting molybdenum disulfide (MoS2) nanoparticles with high-performance electrocatalytic activity for hydrogen evolution reaction (HER) is fabricated by using a facile hydrothermal route. Comprehensive microscopic and spectroscopic characterizations confirm the resulting hybrid material possesses a 3D crumpled few-layered graphene network structure decorated with MoS2 nanoparticles. Electrochemical characterization analysis reveals that the resulting hybrid material exhibits efficient electrocatalytic activity toward HER under acidic conditions with a low onset potential of 112 mV and a small Tafel slope of 44 mV per decade. The enhanced mechanism of electrocatalytic activity has been investigated in detail by controlling the elemental composition, electrical conductance and surface morphology of the 3D hybrid as well as Density Functional Theory (DFT) calculations. This demonstrates that the abundance of exposed active sulfur edge sites in the MoS2 and nitrogen active functional moieties in N-RGO are synergistically responsible for the catalytic activity, whilst the distinguished and coherent interface in MoS 2 /N-RGO facilitates the electron transfer during electrocatalysis. Our study gives insights into the physical/chemical mechanism of enhanced HER performance in MoS2/N-RGO hybrids and illustrates how to design and construct a 3D hybrid to maximize the catalytic efficiency

CMS physics technical design report : Addendum on high density QCD with heavy ions

Peer reviewe

Detection of activity avalanches and speeding up seek in MREG data

Recent studies pinpoint visually cued networks of avalanches with MEG/EEG data, and hemodynamic fingerprints of neuronal avalanches as sudden high signal activity peaks in classical fMRI data. However, detection of neural avalanches faces the problem that the data contain a lot of physiological noise making the automatic analysis difficult. The aim of this study was to detect dynamic patterns of brain activity spreads with the use of ultrafast magnetic resonance encephalography (MREG). MREG achieves 10 Hz whole brain sampling, allowing the estimation of the spatial spread of an avalanche. A computational method was developed to separate neuronal avalanches from motion and physiological pulsations, and detect activity avalanches in human brain default mode network (DMN). Brain activity peaks could be identified from parts of the DMN, and normalized MREG data around each peak was extracted individually in order to show dynamic avalanche spreads as videos within the DMN. Individual avalanche videos of specific parts of the DMN were then averaged over a group of subjects. The results indicate that the detected peaks must be parts of activity avalanches, starting from (or crossing) the DMN. To support analyses on large fMRI data, like MREG recordings, also a method and implementation are presented to achieve a thousand fold speed-up for seeking in large compressed NIfTI neuroimaging data files. The method includes the creation of a novel index structure for the compressed data in order to achieve a speed-up of over hundred up to even five thousand, compared to the currently available implementations. By configuring the index structure, one can set an operating point which optimizes the efficiency as speed-up versus index size according to the requirements by the user.Uusimmat tutkimukset osoittavat, että MEG/EEG-datasta on visuaalisesti havaittavissa neuraalisia verkkoja joissa tapahtuu avalanssi-ilmiöitä. Lisäksi klassisessa fMRI-datassa on havaittu neuronaalisiin avalansseihin liittyviä hemodynaamisia jälkiä, jotka ilmenevät äkillisinä voimakkaina piikkeinä datassa. Neuraalisen avalanssin havaitsemisen automatisointi on kuitenkin hyvin haastavaa, koska data sisältää myös merkittäviä fysiologista kohinakomponentteja. Tämän tutkimuksen tavoitteena oli kehittää laskennallinen menetelmä havaita aivojen aktiviteetin leviämisen dynaamisia rakenteita hyödyntäen ultranopeaa magneettisen resonanssin enkefalografiaa (MREG). MREG kykenee saavuttamaan aivojen näytteistyksen 10 Hz taajuudella, mikä mahdollistaa neuraalisen avalanssin spatiaalisen leviämisen havaitsemisen. Työssä kehitettiin menetelmä erottaa neuraalinen avalanssi liikkeen ja fysiologisten pulsaatioiden tuottamista signaalikomponenteista, sekä havaita aktiviteettiavalanssi ihmisaivojen lepotilan aikaisessa neuraalisessa verkossa (default mode network, DMN). Menetelmä identifioi aivojen aktiviteettipiikkejä DMN-verkosta, normalisoi piikkien ympärillä olevan aktiviteettidatan yksilöllisesti ja lopulta esittää avalanssin leviämisen videona. Verkon toiminnan tutkimiseksi yksilölliset avalanssivideot määrätyistä DMN-verkon osista keskiarvoistettiin koehenkilöryhmän ylitse, jolloin ryhmäkäyttäytymisestä pääteltiin identifioitujen piikkien todella liittyvän DMN-verkosta alkaneisiin tai sen ylittäviin avalansseihin. Lisäksi työssä kehitettiin menetelmä nopeuttaa fMRI/MREG-datan käsittelyaikoja merkittävästi, mistä on suurta etua käsiteltäessä kompressoituja NIfTI-muodossa tallennettuja suuria neurokuvantamisen aineistoja. Menetelmä perustuu uudenlaiseen indeksointimenetelmään, jolla kompressoitua aineistoa voidaan selata nopeudella, joka ylittää monisatakertaisesti tai jopa monituhatkertaisesti perinteellisen menetelmän nopeuden. Konfiguroimalla indeksirakenne sopivasti voidaan asettaa toimintapiste menetelmälle siten, että haluttu kompromissi nopeuden ja indeksirakenteen viemän muistitilan kesken saavutetaan

Changes in A1C levels are significantly associated with changes in levels of the cardiovascular risk biomarker hs-CRP: Results from the SteP study

OBJECTIVE-The effect of therapeutic strategies on cardiovascular (CV) disease can be evaluated by monitoring changes in CV risk biomarkers. This study investigated the effect of a structured self-monitoring of blood glucose (SMBG) protocol and the resulti

Changes in A1C levels are significantly associated with changes in levels of the cardiovascular risk biomarker hs-CRP: Results from the SteP study

OBJECTIVE-The effect of therapeutic strategies on cardiovascular (CV) disease can be evaluated by monitoring changes in CV risk biomarkers. This study investigated the effect of a structured self-monitoring of blood glucose (SMBG) protocol and the resulti

Respiratory brain impulse propagation in focal epilepsy

Abstract Respiratory brain pulsations pertaining to intra-axial hydrodynamic solute transport are markedly altered in focal epilepsy. We used optical flow analysis of ultra-fast functional magnetic resonance imaging (fMRI) data to investigate the velocity characteristics of respiratory brain impulse propagation in patients with focal epilepsy treated with antiseizure medication (ASM) (medicated patients with focal epilepsy; ME, n = 23), drug-naïve patients with at least one seizure (DN, n = 19) and matched healthy control subjects (HC, n = 75). We detected in the two patient groups (ME and DN) several significant alterations in the respiratory brain pulsation propagation velocity, which showed a bidirectional change dominated by a reduction in speed. Furthermore, the respiratory impulses moved more in reversed or incoherent directions in both patient groups vs. the HC group. The speed reductions and directionality changes occurred in specific phases of the respiratory cycle. In conclusion, irrespective of medication status, both patient groups showed incoherent and slower respiratory brain impulses, which may contribute to epileptic brain pathology by hindering brain hydrodynamics

Respiratory-related brain pulsations are increased in epilepsy:a two-centre functional MRI study

Abstract Resting-state functional MRI has shown potential for detecting changes in cerebral blood oxygen level-dependent signal in patients with epilepsy, even in the absence of epileptiform activity. Furthermore, it has been suggested that coefficient of variation mapping of fast functional MRI signal may provide a powerful tool for the identification of intrinsic brain pulsations in neurological diseases such as dementia, stroke and epilepsy. In this study, we used fast functional MRI sequence (magnetic resonance encephalography) to acquire ten whole-brain images per second. We used the functional MRI data to compare physiological brain pulsations between healthy controls (n = 102) and patients with epilepsy (n = 33) and furthermore to drug-naive seizure patients (n = 9). Analyses were performed by calculating coefficient of variation and spectral power in full band and filtered sub-bands. Brain pulsations in the respiratory-related frequency sub-band (0.11–0.51 Hz) were significantly (P < 0.05) increased in patients with epilepsy, with an increase in both signal variance and power. At the individual level, over 80% of medicated and drug-naive seizure patients exhibited areas of abnormal brain signal power that correlated well with the known clinical diagnosis, while none of the controls showed signs of abnormality with the same threshold. The differences were most apparent in the basal brain structures, respiratory centres of brain stem, midbrain and temporal lobes. Notably, full-band, very low frequency (0.01–0.1 Hz) and cardiovascular (0.8–1.76 Hz) brain pulses showed no differences between groups. This study extends and confirms our previous results of abnormal fast functional MRI signal variance in epilepsy patients. Only respiratory-related brain pulsations were clearly increased with no changes in either physiological cardiorespiratory rates or head motion between the subjects. The regional alterations in brain pulsations suggest that mechanisms driving the cerebrospinal fluid homeostasis may be altered in epilepsy. Magnetic resonance encephalography has both increased sensitivity and high specificity for detecting the increased brain pulsations, particularly in times when other tools for locating epileptogenic areas remain inconclusive