Cold storage condensation heat recovery system with a novel composite phase change material

© 2016 Elsevier Ltd. Using condensation heat from cold storage refrigeration systems to provide heat for domestic hot water preparation and industrial hot water supply promotes energy conservation. However, few studies have investigated cold storage condensation heat recovery using phase change materials (PCMs). In this study, a cold storage condensation heat recovery system that uses PCMs has been designed and analysed. According to the principle of energy cascade recycling, different operation modes could be effectively switched to recycle condensation heat. Furthermore, a novel and suitable phase change composite material is developed for cold storage condensation heat recovery, which has a relatively large latent heat, high thermal conductivity, and an appropriate phase change temperature (i.e. 80 °C). With carnauba wax (CW) as the PCM and expanded graphite (EG) as the additive, a composite was developed with an optimal mass ratio of CW:EG = 10:1. The thermal and physical properties and the interior structure of the composite were then investigated using a scanning electron microscope (SEM), thermal constants analyser (Hot Disk), differential scanning calorimeter (DSC), and Fourier transform infrared spectrometer (FT-IR). Furthermore, experiments on the melting and solidification processes and accelerated thermal cycling were also conducted. It was found that at the optimal mass ratio of 10:1, the temperatures of the CW/EG composite in the melting and solidification processes were 81.98 °C and 80.43 °C, respectively, while the corresponding latent heats were 150.9 J/g and 142.6 J/g, respectively. During both processes, CW could retain its original worm-like structure after being completely adsorbed by EG. Compared to only CW, the melting and solidification time of the CW/EG composite were reduced by 81.7% and 55.3%, respectively, while its thermal conductivity was 16.4 times higher. After 1000 runs of accelerated thermal cycling, the endothermic/exothermic phase change temperatures of CW and the CW/EG composite increased by only 0.42%/0.42% and 0.23%/0.27%, respectively, while their endothermic/exothermic latent heats decreased by 4.96%/4.78% and 2.05%/3.44%, respectively. These results indicate that both CW and the CW/EG composite have excellent thermal reliability, while the CW/EG composite exhibits a slightly better performance. Finally, the experiments show that the CW/EG composite has desirable thermal and physical properties such as high thermal conductivity and reliability; Hence, it has good potenti al as a material for facilitating condensation heat recovery from cold storage refrigeration systems

Hybrid Graph: A Unified Graph Representation with Datasets and Benchmarks for Complex Graphs

Graphs are widely used to encapsulate a variety of data formats, but real-world networks often involve complex node relations beyond only being pairwise. While hypergraphs and hierarchical graphs have been developed and employed to account for the complex node relations, they cannot fully represent these complexities in practice. Additionally, though many Graph Neural Networks (GNNs) have been proposed for representation learning on higher-order graphs, they are usually only evaluated on simple graph datasets. Therefore, there is a need for a unified modelling of higher-order graphs, and a collection of comprehensive datasets with an accessible evaluation framework to fully understand the performance of these algorithms on complex graphs. In this paper, we introduce the concept of hybrid graphs, a unified definition for higher-order graphs, and present the Hybrid Graph Benchmark (HGB). HGB contains 23 real-world hybrid graph datasets across various domains such as biology, social media, and e-commerce. Furthermore, we provide an extensible evaluation framework and a supporting codebase to facilitate the training and evaluation of GNNs on HGB. Our empirical study of existing GNNs on HGB reveals various research opportunities and gaps, including (1) evaluating the actual performance improvement of hypergraph GNNs over simple graph GNNs; (2) comparing the impact of different sampling strategies on hybrid graph learning methods; and (3) exploring ways to integrate simple graph and hypergraph information. We make our source code and full datasets publicly available at https://zehui127.github.io/hybrid-graph-benchmark/.Comment: Preprint. Under review. 16 pages, 5 figures, 11 table

Recent Advances in Morphological Cell Image Analysis

This paper summarizes the recent advances in image processing methods for morphological cell analysis. The topic of morphological analysis has received much attention with the increasing demands in both bioinformatics and biomedical applications. Among many factors that affect the diagnosis of a disease, morphological cell analysis and statistics have made great contributions to results and effects for a doctor. Morphological cell analysis finds the cellar shape, cellar regularity, classification, statistics, diagnosis, and so forth. In the last 20 years, about 1000 publications have reported the use of morphological cell analysis in biomedical research. Relevant solutions encompass a rather wide application area, such as cell clumps segmentation, morphological characteristics extraction, 3D reconstruction, abnormal cells identification, and statistical analysis. These reports are summarized in this paper to enable easy referral to suitable methods for practical solutions. Representative contributions and future research trends are also addressed

Incoherent illumination for motion-based imaging through thick scattering medium

Object-motion-based speckle correlation can recover hidden objects from any inhomogeneous medium, which takes advantage of the inherent connection that the cross-correlation between speckle patterns can reflect the autocorrelation of object, providing a route for imaging through or inside thick scattering media. However, once the object is phase-modulated, the above-mentioned relation will not be satisfied under coherent illumination, and the objects cannot be recovered using the existing approaches. Here, we propose an incoherent illumination method for object-motion-based imaging. Theoretical analysis and experimental results show that the cross-correlation between the object-motion-based speckle patterns can be directly used to represent the intensity autocorrelation of the object, making it possible to recover hidden objects regardless of whether the object is phase-modulated or not. Moreover, the proposed approach has a lower root-mean-square error for extracting the autocorrelation patterns of the hidden object. The proposed imaging mechanism blazes a way of imaging moving objects with scattering-induced or intrinsic phase profile, which is in favor of complex imaging scenarios such as inhomogeneous object imaging, deep tissue imaging, and passive lighting scattering imaging

Exploring the Ligand-Protein Networks in Traditional Chinese Medicine: Current Databases, Methods, and Applications

The traditional Chinese medicine (TCM), which has thousands of years of clinical application among China and other Asian countries, is the pioneer of the "multicomponent-multitarget" and network pharmacology. Although there is no doubt of the efficacy, it is difficult to elucidate convincing underlying mechanism of TCM due to its complex composition and unclear pharmacology. The use of ligand-protein networks has been gaining significant value in the history of drug discovery while its application in TCM is still in its early stage. This paper firstly surveys TCM databases for virtual screening that have been greatly expanded in size and data diversity in recent years. On that basis, different screening methods and strategies for identifying active ingredients and targets of TCM are outlined based on the amount of network information available, both on sides of ligand bioactivity and the protein structures. Furthermore, applications of successful in silico target identification attempts are discussed in detail along with experiments in exploring the ligand-protein networks of TCM. Finally, it will be concluded that the prospective application of ligand-protein networks can be used not only to predict protein targets of a small molecule, but also to explore the mode of action of TCM

The Effect of Zhongyong Thinking on Remote Association Thinking: An EEG Study

The Doctrine of the Mean (zhongyong) introduced by Confucianism is not only an aspect of faith, but also a way of thinking for Chinese individuals. Zhongyong includes two thinking forms: eclectic thinking (ET; i.e., “neither-A-nor-B”) and integrated thinking (IT; i.e., “both-A-and-B”). Given the inclination of Asian individuals toward situational cognition, this study used questions about situations familiar to Chinese undergraduates to activate either ET or IT. This was done to investigate the effects of the two divergent thinking forms of zhongyong on performance levels on the Remote Associates Test (RAT). Both behavioral and EEG results found that participants in the IT condition demonstrated higher RAT scores than those in the ET condition. The conclusion was that the RAT and priming tasks shared the same neural mechanism. This meant that the priming tasks of IT allowed participants to enter a state of creative preparation in advance, further affecting resolution of the RAT

Danhong Injection Reversed Cardiac Abnormality in Brain–Heart Syndrome via Local and Remote β-Adrenergic Receptor Signaling

Ischemic brain injury impacts cardiac dysfunction depending on the part of the brain affected, with a manifestation of irregular blood pressure, arrhythmia, and heart failure. Generally called brain–heart syndrome in traditional Chinese medicine, few mechanistic understanding and treatment options are available at present. We hypothesize that considering the established efficacy for both ischemic stroke and myocardial infarction (MI), Danhong injection (DHI), a multicomponent Chinese patent medicine, may have a dual pharmacological potential for treating the brain–heart syndrome caused by cerebral ischemic stroke through its multi-targeted mechanisms. We investigated the role of DHI in the setting of brain–heart syndrome and determined the mechanism by which it regulates this process. We induced Ischemia/Reperfusion in Wistar rats and administered intravenous dose of DHI twice daily for 14 days. We assessed the neurological state, infarct volume, CT scan, arterial blood pressure, heart rhythm, and the hemodynamics. We harvested the brain and heart tissues for immunohistochemistry and western blot analyses. Our data show that DHI exerts potent anti-stroke effects (infarct volume reduction: ∗∗p < 0.01 and ∗∗∗p < 0.001 vs. vehicle. Neurological deficit correction: ∗p < 0.05 and ∗∗∗p < 0.001 vs. vehicle), and effectively reversed the abnormal arterial pressure (∗p < 0.05 vs. vehicle) and heart rhythm (∗∗p < 0.01 vs. vehicle). The phenotype of this brain–heart syndrome is strikingly similar to those of MI model. Quantitative assessment of hemodynamic in cardiac functionality revealed a positive uniformity in the PV-loop after administration with DHI and valsartan in the latter. Immunohistochemistry and western blot results showed the inhibitory effect of DHI on the β-adrenergic pathway as well as protein kinase C epsilon (PKCε) (∗∗p < 0.01 vs. model). Our data showed the underlying mechanisms of the brain–heart interaction and offer the first evidence that DHI targets the adrenergic pathway to modulate cardiac function in the setting of brain–heart syndrome. This study has made a novel discovery for proper application of the multi-target DHI and could serve as a therapeutic option in the setting of brain–heart syndrome

Higher homocysteine and fibrinogen are associated with early-onset post-stroke depression in patients with acute ischemic stroke

BackgroundPost-stroke depression (PSD) is a well-established psychiatric complication following stroke. Nevertheless, the relationship between early-onset PSD and homocysteine (Hcy) or fibrinogen remains uncertain.MethodsAcute ischemic stroke (AIS) patients who met the established criteria were enrolled in this study. Early-onset PSD was diagnosed two weeks after the stroke. The severity of depressive symptoms was assessed by the Hamilton Depression Scale-17 items (HAMD-17), with patients scored ≥7 assigned to the early-onset PSD group. Spearman rank correlation analysis was employed to evaluate the associations between Hcy, fibrinogen, and HAMD scores across all patients. Logistic regression analysis was conducted to investigate the relationship between Hcy, fibrinogen, and early-onset PSD. Receiver operating characteristic curve (ROC) analysis was ASSDalso performed to detect the predictive ability of Hcy and fibrinogen for early-onset PSD.ResultsAmong the 380 recruited patients, a total of 106 (27.89%) patients were diagnosed with early-onset PSD. The univariate analysis suggested that patients in the PSD group had a higher admission National Institutes of Health Stroke Scale (NIHSS) score, modified Rankin Scale score (mRS), Hcy, and fibrinogen levels than patients in the non-PSD group (P<0.05). The logistic regression model indicated that Hcy (odds ratio [OR], 1.344; 95% confidence interval [CI] 1.209–1.494, P<0.001) and fibrinogen (OR, 1.57 6; 95% CI 1.302–1.985, P<0.001) were independently related to early-onset PSD. Area under curve (AUC) of Hcy, fibrinogen, and Hcy combined fibrinogen to predict early-onset PSD was 0.754, 0.698, and 0.803, respectively.ConclusionThis study indicates that Hcy and fibrinogen may be independent risk factors for early-onset PSD and can be used as predictive indicators for early-onset PSD

Promoter and regulon analysis of nitrogen assimilation factor, σ54, reveal alternative strategy for E. coli MG1655 flagellar biosynthesis

Bacteria core RNA polymerase (RNAP) must associate with a σ factor to recognize promoter sequences. Promoters recognized by the σ54 (or σN) associated RNA polymerase are unique in having conserved positions around −24 and −12 nucleotides upstream from the transcriptional start site. Using DNA microarrays representing the entire Escherichia coli genome and promoter validation approaches, we identify 40 in vivo targets of σ54, the nitrogen assimilation σ factor, and estimate that there are 70 σ54 promoters in total. Immunoprecipitation assays have been performed to further evaluate the efficiency of our approaches. In addition, promoter consensus binding search and primer extension assay helped us to identify a new σ54 promoter carried by insB-5 in the upstream of flhDC operon. The involvement of σ54 in flagellar biosynthesis in sequenced E. coli strain MG1655 indicates a fluid gene regulation phenomenon carried by some mobile elements in bacteria genome

Adaptation in bacterial flagellar and motility systems: from regulon members to ‘foraging’-like behavior in E. coli

Bacterial flagellar motility and chemotaxis help cells to reach the most favorable environments and to successfully compete with other micro-organisms in response to external stimuli. Escherichia coli is a motile gram-negative bacterium, and the flagellar regulon in E. coli is controlled by a master regulator FlhDC as well as a second regulator, flagellum-specific sigma factor, σF. To define the physiological role of these two regulators, we carried out transcription profiling experiments to identify, on a genome-wide basis, genes under the control of these two regulators. In addition, the synchronized pattern of increasing CRP activity causing increasing FlhDC expression with decreasing carbon source quality, together with the apparent coupling of motility activity with the activation of motility and chemotaxis genes in poor quality carbon sources, highlights the importance of CRP activation in allowing E. coli to devote progressively more of its limited reserves to search out better conditions. In adaptation to a variety of carbon sources, the motile bacteria carry out tactical responses by increasing flagellar operation but restricting costly flagellar synthesis, indicating its capability of strategically using the precious energy in nutrient-poor environments for maximizing survival