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.     

Description of Structural Damage Caused by the Terrorist Attack on the Pentagon

On September 11, 2001, an airliner was intentionally crashed into the Pentagon. It struck at the first elevated slab on the west wall, and slid approximately 310?ft (94.5?m) diagonally into the building. The force of the collision demolished numerous columns and the fa?ade of the exterior wall, and induced damage to first-floor columns and the first elevated slab over an area approximately 90?ft (27.4?m) wide and 310?ft (94.5?m) long. None of the building collapsed immediately. The portion that remained standing, even after an intense fire, sustained substantial damage at the first-floor level.     

Toughness of the Pentagon Structure

On September 11, 2001, the reinforced concrete structure of the Pentagon Building was able to resist, without collapse, the impact of a large commercial airliner despite the total loss of 26 columns and severe damage to 15 columns at the ground level. The ensuing fire and related fire-fighting activities led to the collapse of a portion of the building approximately one-half hour after the impact. In this paper, the reasons for the demonstrated toughness of the reinforced concrete structure are examined and attributed to use of spiral columns, effective splicing of reinforcing bars, strong girders, and short span lengths.     

Experimental and numerical analysis of seasonal solar‐energy storage in buildings

This paper presents seasonal‐energy storage of solar energy for the heating of buildings. We distinguish several types of seasonal storage, such as latent, sensible, and chemical storage, among which the thermochemical storage is used and analysed in this research. In the first part, a laboratory heat‐storage tank, which was made in the laboratory for heating, sanitary, and solar technology and air conditioning from the Faculty of Mechanical Engineering, University of Ljubljana, Slovenia, was presented. The experimental model was tested for charging and discharging mode. Two types of numerical models for sorption thermal‐energy storage exist, which are microscale and macroscale (integral). For microscale analysis, the analysis system (ANSYS) model can be used to simulate the behaviour in the adsorption reactor. On macroscale or integral scale, TRaNsient SYStem (TRNSYS) model was used to perform the operation of the storages on the yearly basis. In the second part the simulation of the underfloor heating system operation with a built‐in storage tank was carried out for two locations, Ljubljana and Portoro?. Furthermore, the comparison between a thermochemical and sensible‐heat storage was performed with TRNSYS and Excel software. In this comparison, the focus was on the surface parameters of the SCs and volume of the thermal‐storage tank for the coverage of the energy demand for selected building. With this analysis, we would like to show the advantage of the thermochemical storage system, to provide greater coverage of the energy demand for the operation of the building, compared with the seasonal sensible‐heat storage (SSHS). Such a heat‐storage technology could, in the future, be a key contributor to the more environmentally friendly and more sustainable way of delivering energy needs for buildings.     

Circuit model for a symmetrical condensed TLM node

An equivalent circuit for a symmetrical condensed TLM node is presented. The basic circuit has twelve ports and consists of 24 1:1 ideal transformers. Three additional conductances model the conductivity of the medium. The circuit is extended with additional ideal transformers giving six ports for short-circuit and open-circuit stubs which model the permittivity and permeability of the inhomogeneous medium. The scattering matrix of the 18-port network is determined symbolically by solving a set of linear circuit equations. The matrix agrees with previously published results for a symmetrical condensed TLM node, obtained from Maxwell's equations.     

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.     

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.