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Abstract: This report presented a new generation of UV-crosslinking solvent-based pressure-sensitive adhesive (PSA) based on photoinitiator-grafted polystyrene-block-polybutadiene-block-polystyrene (SBS). The SBS, onto which the 4-maleimidobenzophenone (4-MBP) as photoinitiator was grafted, was used as the main component of a PSA. After the UV-crosslinking, a crosslinked structure was formed between polymer chains. FTIR showed that the photoinitiator monomer was successfully grafted onto the hydrophobic polymer. The grafting ratio could be facilely controlled by adjusting the feed amounts of the BPO initiators. The tests of adhesion properties indicated that the 180° peel strength, shear persistent adhesivity and tack property were in the useful range for biomedical applications. [Copyright &y& Elsevier]

Assessing the applicability of an energy storage system (ESS) based on its duty cycle, i.e., its charge/discharge profile, which represents the demands (associated with a specific application) on an ESS, has attracted great attention in the field of renewable energy. The duty cycle of an ESS is determined and analyzed in this paper. The process of obtaining the duty cycle includes extracting common factors from the ESS operation data using factor analysis, clustering the original fragments using a k -means clustering analysis of the common factors, and constructing typical duty-cycle curves using representative sections of each cluster dataset. The duty cycles of the ESS in schedule output, output smoothness, and schedule and smoothness combination applications, for example, were obtained and analyzed. In a schedule output application, the power ratio of the ESS is the primary characteristic parameter, and each band (high, mid, and low) of the power grade accounts for one third of the duty cycle. The changing rate of the power is the key to the assessment and evaluation of output smoothness. The duty cycle of the schedule and smoothness combination application can be treated as a linear superposition of independent duty cycles. The results showed that a combination of factor analysis and k -means clustering methods can effectively identify and quantify the characteristic parameters of the duty cycle to determine the applicability of the ESS. [ABSTRACT FROM AUTHOR]

Recently, increasing research efforts have been devoted into developing high-concentration protein drugs for subcutaneous injection, especially for those with short half-lives and high-dose requirement. Proteins at high concentrations normally present increased colloidal and structural instability, such as aggregation, fibrillation and gelation, which significantly challenges the high-concentration formulation development of protein drugs. Here we used endostatin, a 20 kD recombinant protein, as a model drug for high-concentration formulation optimization. The colloidal and conformational stability of endostatin at high concentration of 30 mg/mL were investigated in formulations containing various excipients, including saccharides (mannitol, sorbitol and sucrose), salts (ArgHCl and NaCl), and surfactants (tween 20 and 80). Protein fibrillation was characterized and semi-quantified by optical polarized light microscopy and transmission electron microscopy, and the amount of fiber formation at elevated temperature of 40 °C was determined. The soluble protein aggregates were characterized by dynamic and static light scattering before and after dilution. The conformational stability were characterized by polyacrylamide gel electrophoresis, fluorescence, circular dichroism, and differential scanning calorimetry. We observed that the soluble aggregation, fibrillation and gelation, induced by conformational and colloidal instabilities of the protein solution, could be substantially optimized by using suitable stabilizers such as combinations of saccharides and surfactants; while formation of gel and soluble aggregates at high protein concentration ( e.g. , 30 mg/mL) and elevated temperature (40 °C) could be prevented by avoiding the usage of salts. It’s worth emphasizing that some stabilizers, such as salts and surfactants, could show opposite contributions in conformational and colloidal stabilities of endostatin. Therefore, cautions are needed when one attempts to correlate the colloidal stability of high-concentration proteins with their conformational stability, and the colloidal and conformational protein stabilities must be harmonized by a balanced selection of various types of excipients. [ABSTRACT FROM AUTHOR]

By lyophilization of rifampicin (RIF) solution in TBA/water with various solvent compositions, uniform and amorphous rifampicin (RIF) microspheres were produced. Using 55% TBA solution, the obtained RIF microspheres have a mono-dispersive size distribution with diameters range from 1 to 3 μm. The RIF microspheres are found to be amorphous by X-ray diffraction, and are expected to dissolve much faster than the crystalline RIF upon inhalation. Mechanistic investigation revealed that the amorphous RIF microspheres were formed due to liquid–liquid phase separation (LLPS) occurred during the freezing of the TBA/water solution. We also observed that the RIF microspheres can be readily phagocytized by activated THP-1 cells within 15 min. The suitable size distribution, high solubility, and readiness for phagocytosis by macrophages, all suggest that the lyophilized amorphous RIF microspheres could be potentially used as an anti-tuberculosis inhalation therapy. In addition, similar process was used to lyophilize TBA/water solutions of several other drugs, including rifaximin, rifapentine, paclitaxel, and isoniazid. We found that for drugs with appropriate physiochemical properties, such as paclitaxel and rifaximin, mono-dispersive microspheres could be obtained as well, which demonstrated that freezing induced LLPS could be utilized as a novel particle engineering methodology to produce drug microspheres by lyophilization. [ABSTRACT FROM AUTHOR]

A battery energy storage system (BESS) can smooth the fluctuation of output power for micro-grid by eliminating negative characteristics of uncertainty and intermittent for renewable energy for power generation, especially for wind power. By integrated with lithium battery storage system the utilization and overall energy efficiency can be improved. However, this target could be obtained only if the BESS is optimal matched. For this issue, the degradation of battery capacity has a significant impact on the operating costs of Wind-ESS system. The research focus on the optimal method for components sizing of BESS in Wind-ESS system with independent system operators. We present an operating cost model for the hybrid energy storage system considering capacity fading of lithium battery in the cycle life. For the optimal objective of component sizing, the global optimization method of dynamic programming (DP) is adopted by setting operating costs and capacity degradation as optimal objectives under the constrains of performance for lithium battery and requirement for grid operation. Based on the DP algorithm and capacity degradation of battery model, the optimal output of the wind power is obtained. The rule based method and genetic algorithm are also be used for simulation. The simulation results show that compared with other two optimal approaches, capacity degradation and operation cost of energy storage for wind power generation system are significantly reduced. • Construction of a system operating cost model. • Use of dynamic programming to reduce operating cost. • Capacity sizing method for wind power-energy storage system. [ABSTRACT FROM AUTHOR]

Although data-driven fault diagnosis methods have achieved remarkable results, these achievements often rely on high-quality datasets without noisy labels, which can mislead the model into producing inaccurate or overfitting classification boundaries in the latent feature space, leading to a significant decrease in the accuracy or even complete failure. To address this challenge, this study proposes a label correction and sample selection approach named MgBIF. The aim is to enable models to robustly perform supervised learning under unknown ratios of noisy labels and achieve the performance of high accuracy and strong generalization. Specifically, MgBIF first creates an exclusive granular ball for each sample in the latent feature space, then fuses labels from other samples within the granular ball to generate pseudo-labels, which are used to correct the current labels. Subsequently, samples with high-confidence labels are selected from the training data with corrected labels to construct a clean dataset for supervised learning, thus minimizing the misguidance of noisy labels on the model during gradient-based parameter updates. A series of experiments validate the effectiveness and superiority of the MgBIF, which can effectively suppress the negative impact of noisy labels in low-noise environments (achieving an accuracy of over 96%) and significantly improve accuracy in high-noise environments (with a maximum improvement of 80%), outperforming the current state-of-the-art methods. MgBIF, therefore, provides a competitive and robust training strategy for uncertain label noise ratio datasets, which is expected to promote the process of automatic annotators replacing expert annotations to construct datasets in the era of large datasets, thereby helping many practical engineering projects reduce costs and increase efficiency. [ABSTRACT FROM AUTHOR]

Abstract: Amphibious proton exchange membranes (PEMs) which could be used under both wet and dry conditions were prepared by sol–gel method in this work. Those novel hybrid PEMs were constructed by three parts: (1) polysiloxane with two basic sites (–NH– on the pendant and in the triazole); (2) H3PO4 as the proton source; (3) poly(vinyl alcohol) (PVA) which had good film-forming capacity and ability to anchor the H3PO4 under wet conditions. The resulting hybrid membranes were thermally stabilized up to 200°C. A matrix-change between polysiloxane and PVA could be observed at a high PVA doping level. The proton conducting property of these membranes was investigated under both hydrous and anhydrous conditions. From 25 to 120°C, the non-soaked and soaked (soaked in the water) membranes showed the proton conductivity of 19–68 and 9–31mScm−1 at 100% relative humidity (RH), respectively. Under completely dry conditions, the proton conductivity of these membranes showed large dependence on the temperature and the proton conductivity of 4.7–21mScm−1 was achieved at 150°C for these membranes. The excellent performance of these hybrid membranes under both wet and dry conditions demonstrated that they have potential use as electrolytes in polymer electrolyte membrane fuel cells (PEMFCs) operating either in a watery or in a water-free environment and so called “amphibious” proton conducting membranes. [ABSTRACT FROM AUTHOR]