The Emerging of Hydrovoltaic Materials as a Future Technology: A Case Study for China

Water contains tremendous energy in various forms, but very little of this energy has yet been harvested. Nanostructured materials can generate electricity by water-nanomaterial interaction, a phenomenon referred to as hydrovoltaic effect, which potentially extends the technical capability of water energy harvesting. In this chapter, starting by describing the fundamental principle of hydrovoltaic effect, including water-carbon interactions and fundamental mechanisms of harvesting water energy with nanostructured materials, experimental advances in generating electricity from water flows, waves, natural evaporation, and moisture are then reviewed. We further discuss potential applications of hydrovoltaic technologies, analyze main challenges in improving the energy conversion efficiency and scaling up the output power, and suggest prospects for developments of the emerging technology, especially in China

Investigating causal associations among gut microbiota, metabolites, and liver diseases: a Mendelian randomization study

ObjectiveThere is some evidence for an association between gut microbiota and nonalcoholic fatty liver disease (NAFLD), alcoholic liver disease (ALD), and viral hepatitis, but no studies have explored their causal relationship.MethodsInstrumental variables of the gut microbiota (N = 13266) and gut microbiota-derived metabolites (N = 7824) were acquired, and a Mendelian randomization study was performed to explore their influence on NAFLD (1483 European cases and 17,781 European controls), ALD (2513 European cases and 332,951 European controls), and viral hepatitis risk (1971 European cases and 340,528 European controls). The main method for examining causality is inverse variance weighting (IVW).ResultsIVW results confirmed that Anaerotruncus (p = 0.0249), Intestinimonas (p = 0.0237), Lachnoclostridium (p = 0.0245), Lachnospiraceae NC2004 group (p = 0.0083), Olsenella (p = 0.0163), and Peptococcus (p = 0.0472) were protective factors for NAFLD, and Ruminococcus 1 (p = 0.0120) was detrimental for NAFLD. The higher abundance of three genera, Lachnospira (p = 0.0388), Desulfovibrio (p = 0.0252), and Ruminococcus torques group (p = 0.0364), was correlated with a lower risk of ALD, while Ruminococcaceae UCG 002 level was associated with a higher risk of ALD (p = 0.0371). The Alistipes (p = 0.0069) and Ruminococcaceae NK4A214 group (p = 0.0195) were related to a higher risk of viral hepatitis. Besides, alanine (p = 0.0076) and phenyllactate (p = 0.0100) were found to be negatively correlated with NAFLD, while stachydrine (Op = 0.0244) was found to be positively associated with NAFLD. The phenylacetate (p = 0.0353) and ursodeoxycholate (p = 0.0144) had a protective effect on ALD, while the threonate (p = 0.0370) exerted a detrimental influence on ALD. The IVW estimates of alanine (p = 0.0408) and cholate (p = 0.0293) showed their suggestive harmful effects against viral hepatitis, while threonate (p = 0.0401) displayed its suggestive protective effect against viral hepatitis.ConclusionIn conclusion, our research supported causal links between the gut microbiome and its metabolites and NAFLD, ALD, and viral hepatitis

Psychological distress among women undergoing in vitro fertilization-embryo transfer: A cross-sectional and longitudinal network analysis

BackgroundWomen undergoing in vitro fertilization-embryo transfer (IVF-ET) treatment were generally found to experience varying degrees of psychological distress across the treatment. Existing studies focused on total scores and diagnostic thresholds to characterize the symptoms’ severity, which might hinder scientific progress in understanding and treating psychological distress.AimsWe aimed to investigate (a) how depression and anxiety symptoms are interconnected within a network, and (b) the changes of the network (symptom connections and network centralities) over time, in women undergoing in vitro fertilization-embryo transfer.MethodsA 4-wave longitudinal study was designed with 343 eligible women recruited from the Reproductive Medicine Center of a tertiary hospital in China. The network models were created to explore the relationship and changes between psychopathology symptoms both within and across anxiety and depression, with anxiety measured by the Generalized Anxiety Disorder-7 and depression measured by the Patient Health Questionnaire-9. Symptom network analysis was conducted to evaluate network and network properties, network centrality, and bridge centrality, as well as change trajectory network.ResultsFor the strength centrality, “inability to control worry” and “worrying too much” were the most central symptoms at T1; however, these symptoms decreased. The centrality of “sadness” and “guilt” tended to increase steadily and became dominant symptoms. For bridge centrality indices, several bridge symptoms were identified separately from T1 to T4: “irritability,” “concentration difficulties,” “nervousness,” and “restlessness;” “guilt” exhibited increased bridge symptoms. Furthermore, the change trajectory network indicated that “suicide ideation” became more closely related to guilt but not to worrying too much over time.ConclusionThis study provides novel insights into the changes in central features, connections, and bridge symptoms during IVF-ET treatment and identified several bridge symptoms separately at different stages, which could activate the connection between psychopathology symptoms. The results revealed that sense of guilt was associated with worsening psychopathology symptoms, indicating that future psychological interventions should target guilt-related symptoms as a priority

SARS-CoV-2 infection causes dopaminergic neuron senescence

COVID-19 patients commonly present with signs of central nervous system and/or peripheral nervous system dysfunction. Here, we show that midbrain dopamine (DA) neurons derived from human pluripotent stem cells (hPSCs) are selectively susceptible and permissive to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. SARS-CoV-2 infection of DA neurons triggers an inflammatory and cellular senescence response. High-throughput screening in hPSC-derived DA neurons identified several FDA-approved drugs that can rescue the cellular senescence phenotype by preventing SARS-CoV-2 infection. We also identified the inflammatory and cellular senescence signature and low levels of SARS-CoV-2 transcripts in human substantia nigra tissue of COVID-19 patients. Furthermore, we observed reduced numbers of neuromelanin+ and tyrosine-hydroxylase (TH)+ DA neurons and fibers in a cohort of severe COVID-19 patients. Our findings demonstrate that hPSC-derived DA neurons are susceptible to SARS-CoV-2, identify candidate neuroprotective drugs for COVID-19 patients, and suggest the need for careful, long-term monitoring of neurological problems in COVID-19 patients.</p

SARS-CoV-2 infection causes dopaminergic neuron senescence

COVID-19 patients commonly present with signs of central nervous system and/or peripheral nervous system dysfunction. Here, we show that midbrain dopamine (DA) neurons derived from human pluripotent stem cells (hPSCs) are selectively susceptible and permissive to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. SARS-CoV-2 infection of DA neurons triggers an inflammatory and cellular senescence response. High-throughput screening in hPSC-derived DA neurons identified several FDA-approved drugs that can rescue the cellular senescence phenotype by preventing SARS-CoV-2 infection. We also identified the inflammatory and cellular senescence signature and low levels of SARS-CoV-2 transcripts in human substantia nigra tissue of COVID-19 patients. Furthermore, we observed reduced numbers of neuromelanin+ and tyrosine-hydroxylase (TH)+ DA neurons and fibers in a cohort of severe COVID-19 patients. Our findings demonstrate that hPSC-derived DA neurons are susceptible to SARS-CoV-2, identify candidate neuroprotective drugs for COVID-19 patients, and suggest the need for careful, long-term monitoring of neurological problems in COVID-19 patients.</p

Evolution of Zeolite Crystals in Self-Supporting Faujasite Blocks: Effects of Hydrothermal Conditions

In order to prepare self-supporting faujasite (FAU) zeolite, a self-supporting zeolite block was synthesized in situ by hydrothermal treatment of a metakaolin base geopolymer. The effects of hydrothermal conditions such as hydrothermal alkalinity, temperature and time on the phase composition, microstructure and mechanical strength of the hydrothermal samples were investigated and evidenced by a series of characterization methods such as X-ray diffraction (XRD), scanning electron microscopy (SEM), and Brunauer-Emmet-Teller (BET). The results showed that a self-supporting faujasite block could be obtained by hydrothermal treatment of the geopolymer block in 2 M NaOH solution at 90 &deg;C for 24 h, which had high crystallinity, regular morphology and high compressive strength. The self-supporting zeolite block had a compressive strength of 11.7 MPa, a pore volume of 0.24 cm3/g, and an average pore diameter of 7.86 nm. The specific surface area and the microporous specific surface area of the self-supporting faujasite blocks were 80.36 m2/g and 19.7 m2/g, respectively

Phenolic Resin Foam Composites Reinforced by Acetylated Poplar Fiber with High Mechanical Properties, Low Pulverization Ratio, and Good Thermal Insulation and Flame Retardant Performance

Phenolic foam composites (PFs) are of substantial interest due to their uniform closed-cell structure, low thermal conductivity, and good thermal insulation performance. However, their disadvantages of a high pulverization rate and poor mechanical properties restrict their application in building exterior insulation. Therefore, the toughening of these composites is necessary. In this paper, poplar fiber was treated with an acetylation reagent, and the acetylated fiber was used to prepare modified phenolic foams (FTPFs); this successfully solved the phenomenon of the destruction of the foam structure due to the agglomeration of poplar fiber in the resin substrate. The foam composites were comprehensively evaluated via the characterization of their chemical structures, surface morphologies, mechanical properties, thermal conductivities, and flame retardant properties. It was found that the compressive strength and compressive modulus of FTPF-5% respectively increased by 28.5% and 37.9% as compared with those of PF. The pulverization ratio was reduced by 32.3%, and the thermal insulation performance and flame retardant performance (LOI) were improved. Compared with other toughening methods for phenolic foam composites, the phenolic foam composites modified with surface-compatibilized poplar fiber offer a novel strategy for the value-added utilization of woody fiber, and improve the toughness and industrial viability of phenolic foam

Airborne Single-Pass Multi-Baseline InSAR Layover Separation Method Based on Multi-Look Compressive Sensing

Due to the small number of baselines (2–3), the traditional L1 norm compressive sensing method for layover solution in InSAR has poor separation ability and height estimation stability and a long operation time. This paper, based on the idea of multi-look, adopts a multi-look compressive sensing method and a multi-look compressive sensing method based on separable approximate sparse reconstruction. The layover separation method based on multi-look compressive sensing adopts the surrounding pixels around the current point as independent observations together with this point to increase the observation vector in compressive sensing, and uses the singular value decomposition method to obtain the noise value, which is used to improve the dimensions of measured data in compressive sensing, reduces the noise level, and improves the stability of noise estimation. Meanwhile, the results of the multi-look L1 norm solution method are closer to those of the L0 norm solution, and the sparse reconstruction ability of compressive sensing is improved. Thus, the separation ability of the scatterers in the layover areas and the stability of height estimation are stronger. In addition, the multi-look compressive sensing method based on separable approximate sparse reconstruction constructs differential operation and soft functions, transforms the L1–L2 norm optimization into an iterative soft threshold shrinkage processing mode, and improves the processing speed by means of the threshold iteration method, which can effectively reduce the operation time while maintaining the resolution ability of scatterers in layover areas and the height direction estimation accuracy and provides the possibility for large-scale data processing. These two methods are effectively verified by means of simulation and measured data. The simulation experiments of the two methods are based on the airborne MEMPHIS system with four antennas, and the height values of the layover scatterers solved by the two methods are more reliable, stable, and closer to the real value than those solved by the traditional compressive sensing method. The operation time of the separable approximate sparse reconstruction method is comparable to the processing time of the traditional compressive sensing method and nearly one-quarter that of the multi-look compressive sensing method. The real data experiments of the two methods are based on the airborne Millimeter-wave InSAR system with three antennas. The two methods both have certain height resolutions in the height direction estimation of layover areas and fine elevation continuity, while traditional compressive sensing method cannot satisfy the condition of sparsity and has poor scatterer separation and elevation continuity. Nevertheless, the multi-look compressive sensing method is a little more stable than the separable approximate sparse reconstruction method, and the operation time of the separable approximate sparse reconstruction method is comparable to the traditional compressive sensing method and nearly one-fifth that of the multi-look compressive sensing method

(2S,3R)-3-(2-Bromophenyl)-2-nitro-2,3,6,7-tetrahydro-1-benzofuran-4(5H)-one

The title compound, C14H12BrNO4, has two chiral C atoms. The C atom next to the O atom in the dihydrofuran ring has an S configuration, while the adjacent chiral C atom has an R configuration. The cyclohex-2-enone and dihydrofuran rings both adopt envelope conformations, with the flap atoms (middle CH2 in cyclohex-2-enone and NO2-substituted C in dihydrofuran) lying 0.612&#8197;(3) and 0.295&#8197;(2)&#8197;&#197;, respectively, from the mean plane of the remaining atoms. The dihedral angle between the mean planes of the furan and benzene rings is 80.0&#8197;(3)&#176;. In the crystal, the molecules are linked by C&#8212;H...O interactions, generating a three-dimensional network

Application of BIM in Tunnel Design with Compaction Pile Reinforced Foundation Carrying Carbon Assessment Based on Advanced Dynamo Visual Programming: A Case Study in China

Carbon emission assessment in civil engineering has gained worldwide attention due to the negative effects of greenhouse gases on the environment. Significant amounts of building materials and electric power are consumed during the construction of tunnels, causing the release of greenhouse gases into the atmosphere. In addition, building information modeling (BIM) can be utilized to realize the computerized design of tunnels, and improve construction efficiency. However, the traditional BIM software (Autodesk Revit) lacks tunnel components and is unable to directly create a three-dimensional tunnel axis. This paper adopted BIM to build a three-dimensional model of the tunnel components for tunnel and carried out batch parameterization and component lofting based on Dynamo visual programming. The BIM of the tunnel guided the construction procedures and improved the construction efficiency. Based on the emission coefficient method, we calculated the carbon emissions from each component and loaded them into the BIM during the parameterization process. After the tunnel modeling design was completed, a bill of quantities was obtained. Then, the carbon emissions from the whole tunnel construction were calculated according to the bill. Thus, the combination of BIM technology and tunnel engineering was realized; this has practical significance for reductions in emissions, and cleaner construction in relation to tunnel engineering