Case Study of Optimized Cascaded Phase Change Thermal Energy Storage Unit

Phase change materials are paid increasing attention by the scholars in the past decades. For maintaining a relatively constant renewable energy output as a competent alternative for fossil fuel replacement, phase change storage unit are widely studied. However, for better pursuit of thermal energy performance and energy efficiency, only single staged phase change storage unit is not enough for increasing thermal requirements. Therefore, a triple staged phase change thermal energy storage unit have been proposed in this study. Meanwhile, correspondent comparison with single staged counterpart have been conducted along with related optimization. It has been concluded that the proposed thermal storage unit achieved 334.95 J/s & 41.54% / 186.37 J/s & 53.22 % in thermal energy exchange rate & exergy efficiency during endothermic/exothermic respectively. 3/21.4 L/min are the optimal circulating heat transfer fluid flowrates for endothermic/exothermic (better discharging rate)/ exothermic (better energy efficiency). Moreover, 100/9/15 are the best temperatures of circulating water for endothermic/ exothermic (better discharging rate)/ exothermic (better energy efficiency)

A novel double-chain silver(I) coordination polymer: catena-poly[[[μ-aqua-aqua­disilver(I)]-bis­(μ3-5-methyl­pyrazine-2-carboxyl­ato)] dihydrate]

In the title silver(I) coordination polymer, {[Ag2(C6H5N2O2)2(H2O)2]·2H2O}n, the [Ag2(μ2-H2O)(H2O)] cores are extended by anti­parallel 5-methyl­pyrazine-2-carboxyl­ate (L) ligands, forming a novel double-chain structure. Both Ag+ cations show a distorted square-pyramidal coordination. Ag1 is bonded to two water molecules, one L N atom, one N atom and one carboxylate O atom from a neighbouring L, whereas Ag2 is surrounded by two L N atoms, two L carboxylate O atoms and one bridging water molecule. O—H⋯O hydrogen-bonding inter­actions involving water clusters and carboxyl­ate O atoms link the mol­ecules into a three-dimensional supra­molecular architecture, which is further consolidated by weak C—H⋯O inter­actions and π–π stacking inter­actions [centroid–centroid distance 3.643 (5) Å]

Neutrophil CD64 index as a good biomarker for early diagnosis of bacterial infection in pregnant women during the flu season

BACKGROUND: Pregnant women are at high risk of developing febrile illness during the flu season. Early identification of a viral or bacterial infection is crucial in the management of febrile pregnant patients. Neutrophil CD64 (nCD64) has been shown to have more important diagnostic value in sepsis than traditional inflammatory indicators. METHODS: The pregnant women enrolled were divided into three groups according to disease: influenza A infection, bacterial infection and healthy controls. Peripheral blood CD64, leukocyte, C-reactive protein (CRP), procalcitonin (PCT) and human Th1/Th2-related cytokines levels were routinely measured. The correlation between and diagnostic value of the nCD64 index and other biomarkers were evaluated using Spearman\u27s correlation test and receiver operating characteristic (ROC) curve analysis. RESULTS: Pregnant women with bacterial infection had significantly elevated levels of leukocytes (8.4 vs. 5.95, 10 CONCLUSIONS: Our study demonstrates the clinical value of the nCD64 index in distinguishing between bacterial infection and influenza A in pregnant women

Prevalence and Relevant Factors of Nocturia and Its Impact on Sleep Quality in Chinese University Students

The purpose of this study was to investigate the prevalence and relevant factors of nocturia and its impact on sleep quality in university students in Mainland China. A large-scale survey was conducted on 14,000 university students from 3 universities in Henan province, China by using an anonymous questionnaire. The questionnaire collected the information from the past six months. The relationships between the prevalence of nocturia and its relevant factors were evaluated. A total of 13,874 questionnaires were collected and 13,104 qualified for statistical analysis. A total of 659 students suffered from clinically relevant nocturia (CRN) (4.56% in male and 5.34% in female). Both univariate analysis and the logistic stepwise regression model showed that the prevalence of nocturia was significantly related to female, history of enuresis, ease of waking up, urgency, frequency and RUTI (P \u3c 0.05). The sleep quality and the university entrance score of CRN group was significantly lower than that of control group (P \u3c 0.05). Nocturia was common in Chinese university students and showed a negative impact on sleep and academic performance. Gender of female, history of enuresis, ease of waking up, urgency, frequency and RUTI were relevant factors for CRN

Integrated assessment of trace elements in a marine ranching area based on multi-species and multi-level biomarkers: a case study in China’s national-level marine ranching demonstration area

The goal of this study was to evaluate the trace element pollution in a marine ranching area in China based on molecular responses (expression of metallothionein and antioxidant enzyme genes), and biochemical biomarkers (metallothionein content, antioxidant enzyme activities, and malonaldehyde level) in four indicator species. We collected samples of two fish (Lateolabrax maculatus and Sebastes schlegelii), one crustacean (Charybdis japonica), and one gastropod (Rapana venosa) from the western Furong Island marine ranching area and from an adjacent area in March 2022 and measured the trace element content in these indicator species as well as in the seawater and sediment. We found that the bioaccumulation characteristics of trace elements and the response patterns of biomarkers were species specific. Moreover, not every biomarker was significantly correlated with environmental trace element content. We then established two biomarker combinations indicative of trace element pollution in seawater and sediment, respectively, based on the correlation between biomarkers and trace element contents. The selected biomarkers were integrated using integrated biomarker response version 2 (IBRv2). IBRv2 values in the studied marine ranching area were lower than those in the adjacent area. Additionally, these values were consistent with the bioaccumulation of trace elements in the indicator species, the integrated trace element pollution index for seawater, and the potential risk index for sediment. These results show that this multi-biomarker and multi-species IBRv2 approach provided a comprehensive diagnosis of trace element pollution in the marine ranching area. Therefore, its application may be beneficial for marine environmental monitoring and management in view of the ecotoxicological impact of pollutants on organisms

Multivariate Classification of Major Depressive Disorder Using the Effective Connectivity and Functional Connectivity

Major depressive disorder (MDD) is a mental disorder characterized by at least 2 weeks of low mood, which is present across most situations. Diagnosis of MDD using rest-state functional magnetic resonance imaging (fMRI) data faces many challenges due to the high dimensionality, small samples, noisy and individual variability. To our best knowledge, no studies aim at classification with effective connectivity and functional connectivity measures between MDD patients and healthy controls. In this study, we performed a data-driving classification analysis using the whole brain connectivity measures which included the functional connectivity from two brain templates and effective connectivity measures created by the default mode network (DMN), dorsal attention network (DAN), frontal-parietal network (FPN), and silence network (SN). Effective connectivity measures were extracted using spectral Dynamic Causal Modeling (spDCM) and transformed into a vectorial feature space. Linear Support Vector Machine (linear SVM), non-linear SVM, k-Nearest Neighbor (KNN), and Logistic Regression (LR) were used as the classifiers to identify the differences between MDD patients and healthy controls. Our results showed that the highest accuracy achieved 91.67% (p < 0.0001) when using 19 effective connections and 89.36% when using 6,650 functional connections. The functional connections with high discriminative power were mainly located within or across the whole brain resting-state networks while the discriminative effective connections located in several specific regions, such as posterior cingulate cortex (PCC), ventromedial prefrontal cortex (vmPFC), dorsal cingulate cortex (dACC), and inferior parietal lobes (IPL). To further compare the discriminative power of functional connections and effective connections, a classification analysis only using the functional connections from those four networks was conducted and the highest accuracy achieved 78.33% (p < 0.0001). Our study demonstrated that the effective connectivity measures might play a more important role than functional connectivity in exploring the alterations between patients and health controls and afford a better mechanistic interpretability. Moreover, our results showed a diagnostic potential of the effective connectivity for the diagnosis of MDD patients with high accuracies allowing for earlier prevention or intervention