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IntroductionExtracorporeal cardiopulmonary resuscitation (ECPR) is an emerging strategy in highly selected patients with refractory cardiac arrest (CA). Animal models can help to identify new therapeutic strategies to improve neurological outcome and cardiac function after global ischemia in CA. Aim of the study was to establish a reproducible ECPR rat model of ventricular fibrillation CA (VFCA) that leads to consistent neuronal damage with acceptable long-term survival rates, which can be used for future research.Materials and methodsMale Sprague Dawley rats were resuscitated with ECPR from 6 min (n = 15) and 8 min (n = 16) VFCA. Animals surviving for 14 days after return of spontaneous resuscitation (ROSC) were compared with sham operated animals (n = 10); neurological outcome was assessed daily until day 14. In the hippocampal cornu ammonis 1 region viable neurons were counted. Microglia and astrocyte reaction was assessed by Iba1 and GFAP immunohistochemistry, and collagen fibers in the myocardium were detected in Azan staining. QuPath was applied for quantification.ResultsOf the 15 rats included in the 6 min CA group, all achieved ROSC (100%) and 10 (67%) survived to 14 days; in the 8 min CA group, 15 (94%) achieved ROSC and 5 (31%) reached the endpoint. All sham animals (n = 10) survived 2 weeks. The quantity of viable neurons was significantly decreased, while the area displaying Iba1 and GFAP positive pixels was significantly increased in the hippocampus across both groups that experienced CA. Interestingly, there was no difference between the two CA groups regarding these changes. The myocardium in the 8 min CA group exhibited significantly more collagen fibers compared to the sham animals, without differences between 6- and 8-min CA groups. However, this significant increase was not observed in the 6 min CA group.ConclusionOur findings indicate a uniform occurrence of neuronal damage in the hippocampus across both CA groups. However, there was a decrease in survival following an 8-min CA. Consequently, a 6-min duration of CA resulted in predictable neurological damage without significant cardiac damage and ensured adequate survival rates up to 14 days. This appears to offer a reliable model for investigating neuroprotective therapies.

Low thermal conductivity of organic phase change materials (PCMs) for thermal energy storage systems induces the necessity to apply suitable heat transfer enhancement techniques for these materials. The purpose of this study was to improve thermal conductivity of a PCM erythritol by using sodium chloride as an additive, such that the material can be applied for steam cooking systems when integrated with solar parabolic trough collectors. In this study, erythritol-NaCl composites were synthesized by using the melting method, and the key physicochemical properties of the composites were estimated by using differential scanning calorimetry (DSC) coupled with thermo-gravimetric analysis (TGA). The observations indicate that there has been a significant improvement in the thermal conductivity of erythritol supplemented with NaCl. Further, thermal behaviour of the material indicates that it is suitable for steam cooking applications. Furthermore, mathematical models based on the experimental observations can be potentially utilized for further studies of erythritol-NaCl composites.

Various studies show that electrification, integrated into a circular economy, is crucial to reach sustainable mobility solutions. In this context, the circular use of electric vehicle batteries (EVBs) is particularly relevant because of the resource intensity during manufacturing. After reaching the end-of-life phase, EVBs can be subjected to various circular economy strategies, all of which require the previous disassembly. Today, disassembly is carried out manually and represents a bottleneck process. At the same time, extremely high return volumes have been forecast for the next few years, and manual disassembly is associated with safety risks. That is why automated disassembly is identified as being a key enabler of highly efficient circularity. However, several challenges need to be addressed to ensure secure, economic, and ecological disassembly processes. One of these is ensuring that optimal disassembly strategies are determined, considering the uncertainties during disassembly. This paper introduces our design for an adaptive disassembly planner with an integrated disassembly strategy optimizer. Furthermore, we present our optimization method for obtaining optimal disassembly strategies as a combination of three decisions: (1) the optimal disassembly sequence, (2) the optimal disassembly depth, and (3) the optimal circular economy strategy at the component level. Finally, we apply the proposed method to derive optimal disassembly strategies for one selected battery system for two condition scenarios. The results show that the optimization of disassembly strategies must also be used as a tool in the design phase of battery systems to boost the disassembly automation and thus contribute to achieving profitable circular economy solutions for EVBs.

Frazil ice, consisting of loose disc-shaped ice crystals, is the first ice that forms in the annual cycle in the marginal ice zone (MIZ) of the Antarctic. A sufficient number of frazil ice crystals form the surface “grease ice” layer, playing a fundamental role in the freezing processes in the MIZ. As soon as the ocean waves are sufficiently damped by a frazil ice cover, a closed ice cover can form. In this article, we investigate the rheological properties of frazil ice, which has a crucial influence on the growth of sea ice in the MIZ. An in situ test setup for measuring temperature and rheological properties was developed. Frazil ice shows shear thinning flow behavior. The presented measurements enable real-data-founded modelling of the annual ice cycle in the MIZ.

Steam cooking using parabolic trough collectors is a well-established sustainable technology. The augmentation of a thermal energy storage (TES) system with such a sustainable system will make the technology completely reliable on the renewable energy source. However, there are limited research findings to improve the thermal performance of the TES heat exchangers by adopting non-structural and non-elemental modifications. In this article, experimental studies have been performed on a TES shell and tube heat exchanger that could be envisaged for steam cooking applications. Erythritol was used as the phase change material. The heat exchanger was operated in two modes: progressive and impulsive. From the observations, the performance of the impulsive mode was better than the progressive mode. The impulsive mode of functionality witnessed a 32% decrease in the charging duration, 2.5% increase in the energy stored and 50% increase in the charging rate in comparison to the progressive mode. [ABSTRACT FROM AUTHOR]

Erythritol ((2 R,3S)-Butane-1,2,3,4-tetrol) is being considered as a phase change material (PCM) of interest owing to its potential applicability for solar thermal applications. But however, lack of inclusive material characterisation outcomes drives the need to bridge this research gap. In this study, erythritol was subjected to both chemical and thermal characterisation investigations. X-ray diffractometry (XRD) investigation estimated the degree of crystallinity to be 73.48% and the crystallite size to be 38.79 nm. The fourier transform infrared spectroscopy (FT-IR) investigation has identified -OH, -C-H and -CH2 to be the major functional groups. The scanning electron microscopy (SEM) investigation visualised the crystalline architecture of the PCM. The energy dispersive x-ray spectroscopy (EDAX) investigation quantified the composition of C and O in the eclectic constituency. The UV-visible spectrophotometry investigations confirmed that erythritol could be utilised for direct solar thermal applications. The thermal characterisation investigations rendered the latent heat of the PCM to be 333.48 kJ kg −1 and its peak melting temperature to be 118.18°C. The thermal stability investigations estimated the latent heat loss per cycle to be 1.1451 kJ kg −1. [ABSTRACT FROM AUTHOR]

The ICRF slow wave is a potential carrier for parallel RF electric fields known to cause unwanted plasma-wall interactions in magnetic confinement fusion experiments. In nowadays machines the slow wave is usually confined to the far scrape-off layer or the limiter shadow, but conditions in future experiments and reactors may allow the slow wave to be propagative in a larger region. Simulations with RAPLICASOL for various geometries show that the ICRF slow waves appear as the so-called resonance cones (RCs) characterized by large localized electric fields. The RCs emerge from the points along the plasma-antenna interface where (in the cold plasma approximation) the radio frequency electric field diverges. We demonstrate that in the parameter range of interest, the propagation of the RCs in a plasma with a density gradient is defined by a simple geometric model, using the local plasma density and the frequency as input parameters. In the context of experiments at ASDEX Upgrade, simulations illustrate that the RCs can emerge from a single tile of the ICRF antenna limiter. Experiments at the Ion-cyclotron System Hardware Test ARrangement (ISHTAR) were conducted to test the detection principle in a simple environment. In agreement with simulations and with predicted characteristics which depend on operation parameters, the RCs are excited by an RF antenna and propagate through the relatively homogeneous plasma in ISHTAR. The cones are detected at a distance from the antenna using two probes scanning through the plasma. In ASDEX Upgrade, a single tile of an antenna limiter was modified to launch RF power into a specially tailored low-density scrape-off layer. Probes at the mid-plane manipulator were then used to detect the wave electric fields at a distance from the RF source. The detected RF signals show that the signal maxima are located close to the lower hybrid resonance density and are highest when the source and the probes are connected along magnetic field lines. These observations agrees with the model for RCs from the simulations.

In this research work, nano-phase change material (NPCM) composites were prepared by adding 1 %, 2 %, and 3 % mass fractions of highly conductive carbon-based graphene nanoparticles into the base phase change material (PCM). The existence and uniform graphene dispersion in the PCM was confirmed through Raman spectrometer and scanning electron microscope (SEM) analysis. The Fourier transform infrared (FTIR) and x-Ray diffraction (XRD) results showed that all three NPCM composites were chemically stable, and their crystallinity was similar to the base PCM. For the sample with 3 % graphene, the solid-state thermal conductivity was increased by 219.89 %, and liquid-state thermal conductivity was increased by 161.65 %, with a 3.52 % drop in latent heat capacity was revealed from differential scanning calorimetry (DSC) analysis. All NPCM composites have onset and peak melting temperatures closer to the base PCM. Hence, the NPCM composites can be employed for thermal energy storage (TES) integrated solar water heater (SWH) applications. [ABSTRACT FROM AUTHOR]

Various studies show that electrification, integrated into a circular economy, is crucial to reach sustainablemobility solutions. In this context, the circular use of electric vehicle batteries (EVBs) is particularly relevant because of the resource intensity during manufacturing. After reaching the end-of-life phase, EVBs can be subjected to various circular economy strategies, all of which require the previous disassembly. Today, disassembly is carried out manually and represents a bottleneck process. At the same time, extremely high return volumes have been forecast for the next few years, and manual disassembly is associated with safety risks. That is why automated disassembly is identified as being a key enabler of highly efficient circularity. However, several challenges need to be addressed to ensure secure, economic, and ecological disassembly processes. One of these is ensuring that optimal disassembly strategies are determined, considering the uncertainties during disassembly. This paper introduces our design for an adaptive disassembly planner with an integrated disassembly strategy optimizer. Furthermore, we present our optimization method for obtaining optimal disassembly strategies as a combination of three decisions: (1) the optimal disassembly sequence, (2) the optimal disassembly depth, and (3) the optimal circular economy strategy at the component level. Finally, we apply the proposed method to derive optimal disassembly strategies for one selected battery system for two condition scenarios. The results show that the optimization of disassembly strategies must also be used as a tool in the design phase of battery systems to boost the disassembly automation and thus contribute to achieving profitable circular economy solutions for EVBs. [ABSTRACT FROM AUTHOR]

Latent heat thermal energy storage heat exchangers store heat energy by virtue of the phase transition that occurs in the thermal storage media. Since phase change materials (PCMs) are utilized as the media, there is a critical necessity for the appropriate selection of the PCM utilized. Since multiple thermo-physical properties and multiple PCMs are required to be evaluated for the selection, there arises a need for multiple criteria decision making (MCDM) algorithms to be adopted for the selection. But owing to the different weight estimation techniques employed and the voluminous quantity of selection algorithms available, there arises a need for a comparative methodology to be adopted. This study was intended to select an optimal PCM for a sustainable steam cooking application coupled with a thermal energy storage system. In this research study, six PCMs were chosen as the alternatives and five thermo-physical properties were chosen as the criteria for the evaluation. 11 different algorithms were augmented with 3 different weight estimation techniques and therefore a total of 33 algorithms were employed in this study. All of the algorithms have chosen Erythritol as the optimal PCM for the application. The outcomes of the MCDM algorithms have been validated through an intricate Pearson's correlation coefficient study. [ABSTRACT FROM AUTHOR]

Vehicle drive systems are often oversized for common customer operation in order to cover the high demands of rare driving events such as towing a trailer, high acceleration or steep inclines. This high torque and power requirement affects the efficiency map and the highest efficiency is around the area of increased torque and speed. However, in everyday use, drive systems are mostly driven by customers at low speed and load, and therefore are not operating in the most efficient area. Designing a drive system that only covers the area of highest customer operation can increase efficiency by moving the sweet spot of efficiency to the relevant area, and thus reduce energy consumption. Therefore, customer data need to be analyzed in order to identify customer requirements and to localize the area of greatest operation. The method presented in this paper analyzes customer data in order to identify design-relevant parameters for a customer-specific drive system design. The available customer data results from event-based counts and are submitted as a statistical frequency distribution. These statistics are compared with discrete time series recorded during test drives in order to derive representative time series that correspond to customer behavior. By applying the time frame-based load analysis to these relevant time series, the desired design-relevant parameters are pointed out.

Chronic pain is a complex, debilitating, and escalating health problem worldwide, impacting 1 in 5 adults. Current treatment is compromised by dose-limiting side effects, including high abuse liability, loss of ability to function socially and professionally, fatigue, drowsiness, and apathy. PICK1 has emerged as a promising target for the treatment of chronic pain conditions. Here, we developed and characterized a cell-permeable fatty acid-conjugated bivalent peptide inhibitor of PICK1 and assessed its effects on acute and chronic pain. The myristoylated PICK1 inhibitor, myr-NPEG4-(HWLKV)2 (mPD5), self-assembled into core-shell micelles that provided favorable pharmacodynamic properties and relieved evoked mechanical and thermal hypersensitivity as well as ongoing hypersensitivity and anxiodepressive symptoms in mouse models of neuropathic and inflammatory pain following subcutaneous administration. No overt side effects were associated with mPD5 administration, and it had no effect on acute nociception. Finally, neuropathic pain was relieved far into the chronic phase (18 weeks after spared nerve injury surgery) and while the effect of a single injection ceased after a few hours, repeated administration provided pain relief lasting up to 20 hours after the last injection.