batterydata/paper-abstracts huggingface dataset:
This paper introduces a complete work-flow for the translation of dynamic isolated signs based on data acquired from a data-glove. A sign language translation system based on a wearable device represents indeed a more efficient solution with respect to cameras or position trackers for helping speech-impaired people on a daily basis. The paper describes the different steps required for a sign language translation, namely segmentation, feature extraction and classification, together with the custom data-glove used for data-acquisition. The paper presents also experimental results, comparing different machine learning classifiers and discussing their performances both in terms of translation accuracy and computational time. The proposed work-flow has been tested both on data acquired from a custom data-glove and on a public database, and it outperforms those of other works in literature. The reported analysis suggests a multi-layer perceptron neural network as the most suitable classifier for the realization of a wearable sign language translation system.
Recently, the three-spined stickleback (Gasterosteus aculeatus L.) has been proposed as a suitable fish species for detecting both androgen- and estrogen-induced endocrine disruption by environmental pollutants. This relatively pollution-tolerant fish is present in most European streams and small rivers but also coastal and estuarian areas. The purpose of the present field study was to determine the extent to which multiple biomarkers in this fish species could distinguish between streams with different pollution levels. Sticklebacks were sampled in French rivers characterised by various urban, industrial or agricultural contaminations and in outdoor lotic mesocosms as reference site. Physiological parameters including condition factor and liver somatic index, biotransformation enzymes such as 7-ethoxyresorufin-O-deethylase (EROD) and glutathione-S-transferase, antioxidant enzymes including glutathione peroxidase and total glutathione (GSH) content and lipoperoxidation (as TBARS) showed several differences between sites. For example, fish from an heavily contaminated stream exhibited a 9-fold EROD induction associated to a decrease of GSH and a 3-fold increase of TBARS content in comparison to fish from uncontaminated sites. When fish were transferred from polluted river to clean water, some of these biomarkers rapidly returned to basal levels found in fish in the reference site while others, like TBARS levels were still high after 2 weeks of depuration. Based on multivariate analyses, the battery of biomarkers proved to differentiate all sites, with a very good classification rate for highly contaminated streams. Influence of fish gender and sampling period on biomarker responses was also observed and is discussed. The results of this field study provide additional support for the use of stickleback for in situ multi-biomarker assessment.
To understand the mechanism of crack propagation in nano electrode materials due to lithium concentration variation during charging cycling, an analytical model is developed based on the diffusion induced stress evolution and crack propagation in a spherical particle electrode during phase transformation. In the model, the effect of the phase transformation on concentration variation, stress evolution and stress discontinuity is clarified. In addition, it has been found that concentration jumps result in hoop stress discontinuities, which can lead to crack at the interface. Then, the stress intensity factor is derived from the interface crack innano electrodes during galvanostatic charging. The stress intensity factors obtained indicate that interface crack will not propagate when stress intensity factor is less than the fracture toughness of electrode materials during lithiation. Significantly, failure mechanics criterion diagram with critical nanoparticle electrode size and current density is arrived. The present model maybe used to help the structural design for electrodes in lithium ion batteries.
The treatment of low-grade glioma is still debated. Surgery is the first-line approach, and the correct timing of radiation therapy has not yet been defined since “early” radiation therapy improves relapse-free survival but not overall survival. Since a longer progression-free survival is desirable, the main issue related to radiotherapy is the incidence of late neurocognitive toxicity.
A novel process called Liquid Source Misted Chemical Deposition (LSMCD) was used to synthesize Al-doped LiMn2O4 cathode films for Lithium microbatteries. The cathode films were characterized by XRD, SEM, cyclic volatmmetry, and charge/discharge test. LiMn1.8Al0.2O4 film crystallized at 800°C in rapid thermal annealing (RTA) for 5min under oxygen atmosphere exhibited more improved electrochemical rechargeability than spinel LiMn2O4 film because the substitution of Al3+ for Mn3+ increased MnO bonding strength in the spinel framework and suppressed the two-phase behavior of the unsubstituted spinel during the intercalation/deintercalation that is the origin of the failure mechanism in the 4V region. As a result, LiMn1.8Al0.2O4 film showed an initial discharge capacity of 52μAh/cm2 μm and no capacity fade over 100 cycles.
Autophosphorylation of αCaMKII is regarded as a ‘molecular memory’ for Ca2+ transients and a crucial mechanism in aversely, but less so in appetitively, motivated learning and memory. While there is a growing body of research implicating αCaMKII in general in behavioral responses to threat or fearful stimuli, little is known about the contribution of the autophosphorylation. The present study asked how αCaMKII autophosphorylation controls anxiety-like behavioral responses toward novel, potentially threatening stimuli. We tested homozygous and heterozygous T286A αCaMKII autophosphorylation deficient mice and wild types in a systematic series of behavioral tests. Homozygous mutants were more active in the open field test and showed reduced anxiety-related behavior in the light/dark test, but these findings were confounded by a hyperlocomotor phenotype. The analysis of elevated plus maze showed significantly reduced anxiety-related behavior in the αCaMKII autophosphorylation-deficient mice which appeared to mediate a hyperlocomotor response. An analysis of home cage behavior, where neither novel nor threatening stimuli were present, showed no differences in locomotor activity between genotypes. Increased locomotion was not observed in the novel object exploration test in the αCaMKII autophosphorylation-deficient mice, implying that hyperactivity does not occur in response to discrete novel stimuli. The present data suggest that the behavior of αCaMKII autophosphorylation-deficient mice cannot simply be described as a low anxiety phenotype. Instead it is suggested that αCaMKII autophosphorylation influences locomotor reactivity to novel environments that are potentially, but not necessarily threatening.
Publisher Summary This chapter discusses manufacturing, as a general term referring to industry, is to make products that have been designed for certain application. Manufacturing has been influenced not only by the increased demands on producing routine products and creating new products but also by social, economic and even political changes. There are ever increasing demands on miniaturized/micro products/systems and components, e.g. MEMS (micro-electric-mechanical systems) and micro-systems, micro-reactors, fuel cells, micro-mechanical devices, and micro-medical components, which are now popularly used in vehicles, aircraft, telecommunication and IT facilities, home appliances, medical devices and implants. Micro-manufacturing concerns manufacturing methods, technologies, equipment, organizational strategies, and systems for the manufacture of products and/or features that have at least two dimensions that are within sub-millimeter ranges. Micro-manufacturing engineering is a general term which concerns a series of relevant activities within the chain of manufacturing micro-products/features, including design, analysis, materials, processes, tools, machinery, operational management methods, and systems.
There is evidence that hourly variations in exposure to airborne particulate matter (PM) may be associated with adverse health effects. Still there are only few published data on short-term levels of personal exposure to PM in community settings. The objectives of the study were to assess hourly and shorter-term variations in personal PM2.5 exposure in Helsinki, Finland, and to compare results from portable photometers to simultaneously measured gravimetric concentrations. The effect of relative humidity on the photometric results was also evaluated. Personal PM2.5 exposures of elderly persons were assessed for 24 h every second week, resulting in 308 successful measurements from 47 different subjects. Large changes in concentrations in minutes after cooking or changing microenvironment were seen. The median of daily 1-h maxima was over twice the median of 24-h averages. There was a strong significant association between the two means, which was not linear. Median (95th percentile) of the photometric 24-h concentrations was 12.1 (37.7) and of the 24-h gravimetric concentrations 9.2 (21.3) μg/m3. The correlation between the photometric and the gravimetric method was quite good (R2=0.86). Participants spent 94.1% of their time indoors or in a vehicle, where relative humidity is usually low and thus not likely to cause significant effects on photometric results. Even outdoors, the relative humidity had only modest effect on concentrations. Photometers are a promising method to explore the health effects of short-term variation in personal PM2.5 exposure.
The aim of this study is to investigate the association of oral dryness with overall survival and determine the threshold points of moisture degree for predicting 7-day survival in palliative care patients.
In this work, an easy, reliable, effective approach for preparation of modified Boron Nitride (BN) from h-BN(Hexagonal boron nitride) was developed via liquid-phase exfoliation using a dopamine chemistry. Supramolecular interactions of the polydopamine (PDA) with h-BN has been used to achieve the facile surface modification of h-BN by forming a PDA shell on its surface. The successful and effective preparation of different h-BN-PDA hybrids has been confirmed by Scanning Electron Microscopy (SEM), Raman spectroscopy, XRD, IR and TGA investigations. The PDA coating increases the dispersibility of these hybrids as filler in polymers. Since polymer-based thermal interface materials (TIMs) with excellent thermal conductivity and electrical resistivity are in high demand, epoxy composites filled with h-BN, BBN (Ball milled Boron Nitride), MBN (Modified Boron Nitride) and MBBN (Modified Ball milled Boron Nitride) were processed. The thermal conductivity is as high as 4 W/mK for MBBN as compared with 0.2 W/mK of neat epoxy. This method of producing multifunctional exfoliated h-BN provides eco-friendly, easy handling, and suitable as a unique paradigm for developing the next generation of thermal conductive devices and solution-processed semiconductors.
The electrochemical insertion of sodium ions into different types of hard carbons was achieved in electrolytes composed of ethylene carbonate as the solvent and NaClO4 as the salt. For all the materials studied the sodium uptake increases when the carbon highest heat treatment temperature (HTT) decreases. PAN-based carbon fibres appear to be suitable structures to allow significant sodium insertion. Thus, T650 ex-PAN fibres lead to a reversible capacity close to 209 mAh g−1. In that case, sodium insertion occurs in two main ways: one is the adsorption on the single graphene layers and the other is the concomitant insertion into the porosity that occurs below 0.1 V versus Na+/Na. This second mechanism, which is indicated by a low-voltage plateau on the electrochemical curves, allows significant insertion. The compared electrochemical study of two saccharose-coke samples corresponding to different regions of Dahn's classification underlines the importance of the carbon precursor and of the manufacture process. The reversible capacity is equal to 184 mAh g−1 for the sample heat treated at 800°C which presents a high hydrogen content whereas it is close to 145 mAh g−1 for the one characterized by a HTT of about 1500°C and a low hydrogen content. The best electrochemical performances are obtained for pyrolyzed cellulose carbons. Indeed, the reversible capacity is about 279 mAh g−1. Outgassing these carbons at 950°C results in such a decrease of the reversible capacity down to 145 mAh g−1. That can be related either to the thermal elimination of heteroelements or to modifications of the pore size distribution. Consequently, the most suitable hard carbon material for anodic applications in rechargeable sodium-ion batteries should both present a high residual hydrogen content and a significant microporosity.
Lithium iron phosphate mixed with nano-sized acetylene black (LiFePO4-AB) was synthesized by a hydrothermal method and subsequent high-energy ball-milling process. Different contents of AB were added to improve the electronic conductivity of LiFePO4. The structural and morphological performance of LiFePO4-AB was investigated by X-ray diffraction (XRD), Raman spectroscopy, scanning electron microscope, and high-resolution transmission electron microscope. LiFePO4-AB/Li batteries were fabricated in an argon-filled glove box, and their electrochemical performance was analyzed by cyclic voltammetry and charge/discharge tests. The XRD results demonstrate that LiFePO4-AB has an olivine-type structure indexed to the orthorhombic Pnma space group. LiFePO4-AB/Li battery with 10 wt% AB shows the best high-rate discharge properties with the discharge capacities of 116 mAh g−1 at 1 C and 85 mAh g−1 at 10 C at room temperature.
The ionic liquid (IL) N-Methyl-N-methoxymethylpyrrolidinium bis(fluorosulfonyl)amide ([Pyr1,1O1][FSA]) was synthesized, and its physicochemical and electrochemical properties were investigated with respect to its application as an electrolyte in lithium-ion secondary batteries operating over a wide temperature range. [Pyr1,1O1][FSA]/Li salt (0.34 mol kg−1) composites were prepared by adding lithium bis(trifluoromethylsulfonyl)amide (LiTFSA) into the IL. [Pyr1,1O1][FSA] and [Pyr1,1O1][FSA]/LiTFSA exhibited melting temperatures (T m) below −30 °C. [Pyr1,1O1][FSA] exhibited a higher ionic conductivity value as compared with that of the corresponding IL with only alkyl substituents. The electrochemical window for both [Pyr1,1O1][FSA] and [Pyr1,1O1][FSA]/LiTFSA was 5.1 V. Stable lithium deposition and dissolution occurred on a Ni electrode at 25 °C.
Performance optimization and cost reduction of a vanadium flow battery (VFB) system is essential for its commercialization and application in large-scale energy storage. However, developing a VFB stack from lab to industrial scale can take years of experiments due to the influence of complex factors, from key materials to the battery architecture. Herein, we have developed an innovative machine learning (ML) methodology to optimize and predict the efficiencies and costs of VFBs with extreme accuracy, based on our database of over 100 stacks with varying power rates. The results indicated that the cost of a VFB system (S-cost) at energy/power (E/P) = 4 h can reach around 223 $ (kW h)−1, when the operating current density reaches 200 mA cm−2, while the voltage efficiency (VE) and utilization ratio of the electrolyte (UE) are maintained above 90% and 80%, respectively. This work highlights the potential of the ML methodology to guide stack design and optimization of flow batteries to further accelerate their commercialization.
This research aims at improving the lesson/training form, so that the instruction process becomes more efficient. The improvement consists of turning the lesson “classical” form into the “clepsydra” form, according to the following scheme: global effective - reduced effective - 1:1 effective - reduced effective - global effective. The “clepsydra” lesson/training structuring will induce an optimization of the training process and, implicitly, of the performances. The “clepsydra” can include all the lesson themes, respectively all the training components or, selectively, a certain theme (certain themes). We can notice the adversity degree differentiations between both the “clepsydra” halves and their sequences. Thus, if the first half has all the adversity degrees, the second one has semi-active and active adversity degrees, with the active adversity compulsoriness in the “clepsydra” last sequence. The adversity degree is related to the previously mentioned aspects and to the instruction level. Progress rate within the “clepsydra” structures is significantly better (15 to 30%).
In this work, the nitrogen doped graphene films with hierarchical network structures have been successfully fabricated via a robust routine of adjusting the content of large- and small-sized reduced graphene oxide (RGO) sheets in the graphene films, where the large-sized RGO sheets act as the backbone to form the well-connected network structures and small-sized RGO sheets act as the interlayer and interpore linkers to connect the large-sized RGO sheets and large pores. A maximum capacitance of 429.7 F g−1 is obtained for the optimized RGO electrode with small-sized RGO content of 40 wt%, which is 61.9% improvement compared to the RGO electrodes with pure large-sized RGO sheets. While, the specific surface area and electrical conductivity of the optimized RGO electrode are 36.1% and 26.2% improvement compared to the pure large-sized electrode. Therefore, we attribute the improved capacitance primarily comes from the increasing of specific surface area due to the formation of fine hierarchical structures and the better connection of the network structures (the increasing of electrical conductivity) for the optimized RGO electrode. Besides, the optimized RGO electrode exhibits good cycle, rate performance, power and energy density compared to the previous carbon based supercapacitor. Herein, we can precisely control the specific surface area and electrical conductivity of RGO electrode by simply adjusting the content of large- and small-sized RGO, which may shed useful insight for the design of high performance supercapacitors and Li-ion batteries.
Our current knowledge about the anatomical substrate of impaired resting-state cortical oscillatory coupling in mild cognitive impairment is still rudimentary. Here, we show that both resting-state oscillatory coupling and its anatomical correlates clearly distinguish healthy older (HO) adults from individuals with amnestic mild cognitive impairment (aMCI). aMCI showed failures in neural-phase coupling of resting-state electroencephalographic alpha activity mostly evident between fronto-temporal and parietal regions. As oligomers of amyloid-beta (Aβ) are linked to synaptic dysfunction in Alzheimer’s disease (AD), we further investigated whether plasma concentrations of these oligomers (Aβ40 and Aβ42) accounted for impaired patterns of oscillatory coupling in aMCI. Results revealed that decreased plasma Aβ42 was associated with augmented coupling of parieto-temporal regions in HO subjects, but no relationship was found in aMCI. Oscillatory coupling of frontal regions was also significantly reduced in aMCI carriers of the ε4 allele of the Apolipoprotein E (ApoE) compared to ε4 noncarriers, although neither neuroanatomical nor plasma Aβ changes accounted for this difference. However, the abnormal pattern of oscillatory coupling in aMCI was negatively related to volume of the angular gyrus, and positively related to volume of the precuneus and the splenium of the corpus callosum. Previous evidence suggests that all these regions are neuropathological targets of AD. The current study takes that scenario one step further, suggesting that this anatomical damage could be responsible for disrupted cortical oscillatory coupling in aMCI. Together, these data shed light on how the MCI status modifies anatomo-functional relationships underlying coordination of large-scale cortical systems in the resting-state.
A simple and novel strategy has been developed for the morphology-controlled synthesis of hierarchical CoS2 microspheres. The hierarchical mesoporous CoS2 architecture constructed by ultrathin nanosheets, when applied as electrode materials for supercapacitors, achieves a highest specific capacitance of 718.7Fg−1 at 1Ag−1 under a high mass loading, excellent rate capability (66.3% capacitance retention from 1Ag−1 to 20Ag−1), and good cycling stability (only a loss of 7.0% in the specific capacitance after 1000 cycles). Therefore, this work provides a promising approach for the rational design and synthesis of morphology-tunable micro/nanomaterials with superior properties for supercapacitors and other electrochemical applications.
Sorption technology has the potential to provide high energy density thermal storage units with negligible losses. However, major experimental and computational advancements are necessary to unlock the full potential of such storage technology, and to efficiently model its performance at system scale. This work addresses for the first time, the development, use and capabilities of neural networks models to predict the performance of a sorption thermal energy storage system. This type of models has the potential to have a lower computational cost compared to traditional physics-based models and an easier integrability into broader energy system models. Two neural network architectures are proposed to predict dynamically the state of charge, outlet temperature and therefore thermal power output of a sorption storage reactor. Every neural network architecture has been investigated in 32 different configurations for the two operating modes (hydration and dehydration), and a systematic training procedure identified the best configuration for each architecture and each operating mode. A campaign of test cases was thoroughly investigated to assess the performance of the proposed neural network architectures. The results show that the proposed model is capable to accurately replicate and predict the dynamic behavior of the storage system, with mean squared error estimators below 2 · 10−3 and 50 °C2 for the state of charge and the outlet temperature outputs, respectively. Our findings, therefore, highlight the potential of an artificial neural networks based modelling technique for sorption heat storage, which is accurate, computationally efficient, and with the potential to be driven by real time data.
Proton-conducting polymer electrolytes based on methacrylates were prepared by direct, radical polymerization of ethyl (EMA), 2-ethoxyethyl (EOEMA), and 2-hydroxyethyl methacrylate (HEMA). Samples with embedded solutions of phosphoric acid in propylene carbonate (PC), γ-butyrolactone (GBL), N,N-dimethylformamide (DMF) and their mixtures were studied using impedance, voltammetrical and thermogravimetric methods. Membranes of long-term stability exhibit ionic conductivity up to 6.7×10−5 Scm−1 at 25°C reached for the sample PEMA–PC–H3PO4 (31:42:27mol.%). The accessible electrochemical potential window is 2.2–3V depending on the working electrode material (glassy carbon or platinum). The thermogravimetric analysis shows that the membranes are thermally stable up to 110–130°C.