Theoretical models for predicting ventilation performance of vertical solar chimneys in tunnels

Solar chimney as a reliable renewable energy system has been primarily utilized for building ventilation, but its application in the tunnel is rarely explored. This study develops theoretical models to predict the ventilation performance of vertical solar chimney in urban tunnel. Five temperature distribution types within the chimney cavity are analyzed, including uniform, vertically linear, horizontally semi-parabolic, two piecewise semi-parabolic in the depth direction, and three-dimensional parabolic profiles. The theoretical models consider the effect of chimney configuration, tunnel geometry, glazing materials, and solar radiation intensity on airflow rate through solar chimney. Validation against experimental data and numerical simulation shows that considering three-dimensional temperature distributions results in an average 11 % deviation from validation data, outperforming assumptions of uniform (29.3 % deviation) or lower-dimensional profiles. The volumetric flow rate through solar chimney exponentially decreased with h/w and h/d that the optimum ratio of h/d is 10. The airflow rate linearly increased with 0.14 power of glazing absorptivity. This analysis provides technical guidance for optimizing solar chimney design in tunnels, enhancing natural ventilation, and reducing energy consumption for mechanical ventilation systems

Collective Excitation in High-Energy Nuclear Collisions -- In Memory of Professor Lianshou Liu

We celebrate the legacies of our friend and mentor Professor Lianshou Liu who was one of the pioneers for the phenomenology of multi-particle interactions and initiated the physics of relativistic heavy-ion collisions in China. In this article, we discuss some of the recent exciting experimental observations on the collective phenomena including collectivity, chirality, criticality, strangeness production, and thermal equilibrium in high-energy nuclear collisions. Future directions, especially the physics at high baryon density, will be discussed with a focus on the first-order phase boundary and hyperon-nucleon interactions.Comment: 20 pages, 10 figure

Molecular mechanism for bidirectional regulation of CD44 for lipid raft affiliation by palmitoylations and PIP2

The co-localization of Cluster-of-Differentiation-44 protein (CD44) and cytoplasmic adaptors in specific membrane environments is crucial for cell adhesion and migration. The process is controlled by two different pathways: On the one hand palmitoylation keeps CD44 in lipid raft domains and disables the linking to the cytoplasmic adaptor, whereas on the other hand, the presence of phosphatidylinositol-4,5-biphosphate (PIP2) lipids accelerates the formation of the CD44-adaptor complex. The molecular mechanism explaining how CD44 is migrating into and out of the lipid raft domains and its dependence on both palmitoylations and the presence of PIP2 remains, however, elusive. In this study, we performed extensive molecular dynamics simulations to study the raft affinity and translocation of CD44 in phase separated model membranes as well as more realistic plasma membrane environments. We observe a delicate balance between the influence of the palmitoylations and the presence of PIP2 lipids: whereas the palmitoylations of CD44 increases the affinity for raft domains, PIP2 lipids have the opposite effect. Additionally, we studied the association between CD44 and the membrane adaptor FERM in dependence of these factors. We find that the presence of PIP2 lipids allows CD44 and FERM to associate in an experimentally observed binding mode whereas the highly palmitoylated species shows no binding affinity. Together, our results shed light on the sophisticated mechanism on how membrane translocation and peripheral protein association can be controlled by both protein modifications and membrane composition

Antimicrobial peptaibols, novel suppressors of tumor cells, targeted calcium-mediated apoptosis and autophagy in human hepatocellular carcinoma cells

<p>Abstract</p> <p>Background</p> <p>Hepatocellular carcinoma (HCC) is one of the most common cancers in the world which is highly chemoresistant to currently available chemotherapeutic agents. Thus, novel therapeutic targets are needed to be sought for the successful treatment of HCC. Peptaibols, a family of peptides synthesized non-ribosomally by the <it>Trichoderma </it>species and other fungi, exhibit antibiotic activities against bacteria and fungi. Few studies recently showed that peptaibols exerted cytotoxicity toward human lung epithelial and breast carcinoma cells. However, the mechanism involved in peptaibol-induced cell death remains poorly understood.</p> <p>Results</p> <p>Here, we showed that Trichokonin VI (TK VI), a peptaibol from <it>Trichoderma pseudokoningii </it>SMF2, induced growth inhibition of HCC cells in a dose-dependent manner. It did not obviously impair the viability of normal liver cells at lower concentration. Moreover, the suppression of cell viability resulted from the programmed cell death (PCD) with characteristics of apoptosis and autophagy. An influx of Ca²⁺triggered the activation of μ-calpain and proceeded to the translocation of Bax to mitochondria and subsequent promotion of apoptosis. On the other hand, typically morphological characteristics consistent with autophagy were also observed by punctate distribution of MDC staining and the induction of LC3-II, including extensive autophagic vacuolization and enclosure of cell organelles by these autophagosomes. More significantly, specific depletion of Bak expression by small RNA interfering (siRNA) could partly attenuate TK VI-induced autophagy. However, siRNA against Bax led to increased autophagy.</p> <p>Conclusion</p> <p>Taken together, these findings showed for the first time that peptaibols were novel regulators involved in both apoptosis and autophagy, suggesting that the class of peptaibols might serve as potential suppressors of tumor cells.</p

Triaqua­(1,10-phenanthroline-2,9-dicarboxyl­ato)cobalt(II) dihydrate

The title compound, [Co(C14H6N2O4)(H2O)3]·2H2O, has two­fold crystallographic symmetry. The CoII atom is in a distorted penta­gonal-bipyramidal coordination environment with two N atoms and two O atoms from a tetradentate 1,10-phenanthroline-2,9-dicarboxyl­ate ligand and one O atom from a water mol­ecule forming the penta­gonal plane, and two O atoms from two water mol­ecules occupying axial positions. In the crystal, adjacent mol­ecules are linked by O—H⋯O hydrogen bonds, forming a three-dimensional network

3,3′-Dibromo-1,1′-[(propane-1,3-diyl­dioxy)­bis(nitrilo­methyl­idyne)]dibenzene

The mol­ecule of the title compound, C17H16Br2N2O2, lies on a twofold axis that passes through the middle atom of the three-atom trimethyl­ene unit. The two aromatic rings are aligned at an angle of 76.02 (4)°

A multi-module artificial neural network approach to pattern recognition with optimized nanostructured sensor array

Abstract The selection of appropriate sensing array nanomaterials and the pattern recognition of sensing signals are two challenges for the development of sensitive, selective, and cost-effective sensor array systems. To tackle both challenges, the work described in this paper focuses on the development of a new hybrid method which couples multi-module method with artificial neural networks (ANNs) for the optimization-optimized multi-module ANN classifier (OMAC) to enhance the correct detection rate for multiple volatile organic compounds (VOCs). In this OMAC method, each module is dedicated to a group of VOCs with specific inputs. Each sensor element&apos;s selectivity is quantitatively evaluated to assist the selection of sensing array materials, which also facilitates the selection of inputs to each dedicated neural network module. This OMAC method is shown to be useful for achieving a high overall recognition rate for a selected set of vapor analytes. The results are discussed, along with the implications to the better design of ANN pattern classifiers in chemical sensor applications