Cellulose as a binding material in graphitic anodes for Li ion batteries: a performance and degradation study

Four types of cellulose, in particular carboxy methyl cellulose (CMC), are tested as potential binding materials in graphitic anodes for lithium ion batteries. It is shown that a minimum content of a cellulose which gives acceptable anode properties (reversible capacity>300 mA h g⁻¹ during the first 10 cycles, irreversible loss<20%) is about 2 wt.%, which is less than in the case of conventional polymeric binders (5-10 wt.%). Kinetics of insertion-deinsertion and passivation processes seem not to be affected by the presence of cellulose. Explanation for the electrode failure at cellulose contents lower than 1 wt.% is given based on X-ray diffraction and microscopy investigations. Finally, the structure (distribution) of cellulose in the composite anode material is discussed and (indirectly) checked with a series of experiments. Most results are compared with the corresponding results obtained either with gelatin or conventional polymeric binders or both.     

Modelling the scatter of E–N curves using a serial hybrid neural network

If structural reliability is estimated by following a strain-based approach, a material’s strength should be represented by the scatter of the ε–N (E–N) curves that link the strain amplitude with the corresponding statistical distribution of the number of cycles-to-failure. The basic shape of the ε–N curve is usually modelled by the Coffin–Manson relationship. If a loading mean level also needs to be considered, the original Coffin–Manson relationship is modified to account for the non-zero mean level of the loading, which can be achieved by using a Smith–Watson–Topper modification of the original Coffin–Manson relationship. In this paper, a methodology for estimating the dependence of the statistical distribution of the number of cycles-to-failure on the Smith–Watson–Topper modification is presented. The statistical distribution of the number of cycles-to-failure was modelled with a two-parametric Weibull probability density function. The core of the presented methodology is represented by a multilayer perceptron neural network combined with the Weibull probability density function using a size parameter that follows the Smith–Watson–Topper analytical model. The article presents the theoretical background of the methodology and its application in the case of experimental fatigue data. The results show that it is possible to model ε–N curves and their scatter for different influential parameters, such as the specimen’s diameter and the testing temperature.     

Upregulation of Cathepsin X in Glioblastoma: Interplay with γ-Enolase and the Effects of Selective Cathepsin X Inhibitors

Glioblastoma (GBM) is the most common and deadly primary brain tumor in adults. Understanding GBM pathobiology and discovering novel therapeutic targets are critical to finding efficient treatments. Upregulation of the lysosomal cysteine carboxypeptidase cathepsin X has been linked to immune dysfunction and neurodegenerative diseases, but its role in cancer and particularly in GBM progression in patients is unknown. In this study, cathepsin X expression and activity were found to be upregulated in human GBM tissues compared to low-grade gliomas and nontumor brain tissues. Cathepsin X was localized in GBM cells as well as in tumor-associated macrophages and microglia. Subsequently, potent irreversible (AMS36) and reversible (Z7) selective cathepsin X inhibitors were tested in vitro. Selective cathepsin X inhibitors decreased the viability of patient-derived GBM cells as well as macrophages and microglia that were cultured in conditioned media of GBM cells. We next examined the expression pattern of neuron-specific enzyme γ-enolase, which is the target of cathepsin X. We found that there was a correlation between high proteolytic activity of cathepsin X and C-terminal cleavage of γ-enolase and that cathepsin X and γ-enolase were colocalized in GBM tissues, preferentially in GBM-associated macrophages and microglia. Taken together, our results on patient-derived material suggest that cathepsin X is involved in GBM progression and is a potential target for therapeutic approaches against GBM.     

SARS-CoV-2 Spike Protein Binding of Glycated Serum Albumin—Its Potential Role in the Pathogenesis of the COVID-19 Clinical Syndromes and Bias towards Individuals with Pre-Diabetes/Type 2 Diabetes and Metabolic Diseases

The immune response to SARS-CoV-2 infection requires antibody recognition of the spike protein. In a study designed to examine the molecular features of anti-spike and anti-nucleocapsid antibodies, patient plasma proteins binding to pre-fusion stabilised complete spike and nucleocapsid proteins were isolated and analysed by matrix-assisted laser desorption ionisation–time of flight (MALDI-ToF) mass spectrometry. Amongst the immunoglobulins, a high affinity for human serum albumin was evident in the anti-spike preparations. Careful mass comparison revealed the preferential capture of advanced glycation end product (AGE) forms of glycated human serum albumin by the pre-fusion spike protein. The ability of bacteria and viruses to surround themselves with serum proteins is a recognised immune evasion and pathogenic process. The preference of SARS-CoV-2 for AGE forms of glycated serum albumin may in part explain the severity and pathology of acute respiratory distress and the bias towards the elderly and those with (pre)diabetic and atherosclerotic/metabolic disease.     

Numerical modelling of the NGI-DSS test and cyclic threshold shear strain for degradation in sand

Ability of laboratory determination of a sand behaviour in static and dynamic loading conditions are influenced by (among other things): sample preparation, number of tests, size of strains, speed of loading and averaging of the errors during examination. Dynamic load per se causes accumulation of the pore water pressure and the phenomenon of stiffening-threshold-degradation which makes the understanding of the sand behaviour more difficult. The complex behaviour of granular material, i.e. sand, is caused by chemical and physical properties of individual particles and their mutual interaction. Obviously, these interrelationships could not be analysed on the basis of laboratory testing. One way to analyse it is numerically, with algorithm that takes into consideration the characteristics of individual particles as well as their interaction in the sand matrix. Discrete element method (DEM) is a numerical method which takes into consideration the discrete nature of sand and shape of particles and is used as an elementary research tool for sand behaviour. Program package PFC3D is based on DEM and allows the modelling of the laboratory equipment, materials and calibration of its micro-characteristics, based on experimental results. The research of cyclic threshold shear strain for degradation in sand includes observation and visualization of the sample preparation (creation of the material skeleton), pouring of the material (transition from liquid to meta-stable state), influence of the particle shape (interlocking, arching), consolidation (deformation of the skeleton) and development and braking of force chains through the sample. This paper explores the suitability of the selected numerical method for modelling of NGI-DSS device, calibration of the tested granular material (Nevada sand) and preparation of the sample for testing and presentation of the stiffening-threshold-degradation phenomenon.     

Foraging theory for autonomous vehicle speed choice

We consider the optimal control design of an abstract autonomous vehicle (AAV). The AAV searches an area for tasks that are detected with a probability that depends on vehicle speed, and each detected task can be processed or ignored. Both searching and processing are costly, but processing also returns rewards that quantify designer preferences. We generalize results from the analysis of animal foraging behavior to model the AAV. Then, using a performance metric common in behavioral ecology, we explicitly find the optimal speed and task processing choice policy for a version of the AAV problem. Finally, in simulation, we show how parameter estimation can be used to determine the optimal controller online when density of task types is unknown.     

Improving the performance of Federated Digital Library services

The number of Digital Libraries (DLs) accessible over the Open Archives Initiative–Protocol for Metadata Harvesting (OAI–PMH) has been constantly increasing in the past years. Earlier efforts in the DL area have concentrated on metadata harvesting and provisioning of value-added Federated Digital Library (FDL) services to the users. FDL services, however, have to meet significant performance and scalability requirements, which is difficult to achieve in centralized metadata harvesting systems. The goal of the present study was to evaluate the benefits of using Web Services Resource Framework (WSRF) compliant grid middleware infrastructure for providing efficient and reliable FDL services. The presented FDL application allows for parallel harvesting of OAI–PMH compliant DLs. The results show that this approach efficiently solves the performance related problems, while it also contributes to greater flexibility of the system. The quality of service is improved as metadata can be updated frequently, and the system does not exhibit a single point of failure.     

Do simultaneous inventions sleep? A case study on nursing sleeping papers

Simultaneous inventions and Sleeping papers are two interesting phenomena in scientific discovery and knowledge development processes, however they were not yet researched as a single occurrence. To close this gap, we performed a bibliometric study in which we analysed if simultaneous discoveries can also be subjected to delayed recognition. The analysis was performed on four already identified nursing Sleeping Papers and resulted in one Sleeping simultaneous invention. Sleeping simultaneous inventions or partially sleeping inventions may represent a valuable source for improved understanding about knowledge development processes and are worth candidates for future research.

     

Strong Hydrogen Bonds in Acetylenedicarboxylic Acid Dihydrate

Acetylenedicarboxylic acid dihydrate (ADAD) represents a complex with strong hydrogen bonding between the carboxylic OH and the water molecule. An X-ray re-examination of the ADAD crystal structure confirms the O^…O distance of the short hydrogen bonds, and clearly shows different bond lengths between the two oxygen atoms with respect to the carbon atom in the carboxyl group, indicating a neutral structure for the complex. The neutral structure was also confirmed by vibrational spectroscopy, as no proton transfer was observed. The diffraction studies also revealed two polymorph modifications: room temperature (α) and low temperature (β), with a phase transition at approximately 4.9 °C. The calculated vibrational spectra are in satisfactory agreement with the experimental spectra. A comparison of the structure and the vibrational spectra between the ADAD and the oxalic acid dihydrate reveals some interesting details. The crystal structures of both crystal hydrates are almost identical; only the O^…O distances of the strongest hydrogen bonds differ by 0.08 Å. Although it was expected that a larger O^…O spacing in the ADAD crystal may significantly change the infrared and Raman spectra, especially for the frequency and the shape of the acidic OH stretching vibration, both the shape and frequency are almost identical, with all subpeaks topped on the broad OH stretching vibration. The O^…O distance dependent are only in- and out-of-plane OH deformations modes. The presence of polarons due to the ionized defects was not observed in the vibrational spectra of ADAD. Therefore, the origin of the broad OH band shape was explained in a similar way to the acid dimers. The anharmonicity of a potential enhances the coupling of the OH stretching with the low-frequency hydrogen bond stretching, which, in addition to the Fermi resonance, structures the band shape of the OH stretching. The fine structure found as a superposition of a broad OH stretching is attributed to Davydov coupling.