The demand for efficient natural ventilation (NV) systems has increased for the development of sustainable buildings. However, the uncertainty of NV remains a challenging issue for appropriate ...utilization strategies of NV. For the successful implementation of NV systems in buildings, it is essential to clarify when and how to use NV systems in advance. In order to achieve the objectives, this study investigated the predictive models of NV rate (NVR) through eight machine learning (ML) algorithms, which are suitable for the interpretation of non-linear relationships between the measured indoor and outdoor environmental variables. Among all of the algorithms, deep neural network (DNN) ensured the best prediction performance for the NVR and it was shown that 40%, 46%, and 38% better predictive performance in terms of mean absolute error (MAE), root mean squared error (RMSE), and mean absolute percentage error (MAPE) than multivariate linear regression (MLR), which had the highest error rate, respectively. Based on the Shapley additive explanation (SHAP), the most influential features that affected to results of predictive models were examined and most of the ML approaches, except for MLR, had similar features (the pressure difference, outdoor temperature, wind speed, indoor relative humidity, solar radiation, the difference of indoor/outdoor relative humidity, and wind direction). The results of this study can improve the prediction performance for NVR, and this would contribute to the development of an intelligent NV system. Future work needs to develop the optimal operating strategies for hybrid ventilation systems integrating NV and mechanical systems.
•Performances of eight machine learning algorithms were compared for predicting natural ventilation rate (NVR).•Deep neural network (DNN) was shown the best prediction performance of NVR with all of the evaluation metrics.•Optimal combination of input features and hyper-parameters in the models leads to improvement of prediction accuracy.•Relationships between results in each model and input features were interpreted using SHapley Additive Explanation (SHAP).
Chemically bonded graphene/carbon nanotube composites as flexible supercapacitor electrode materials are synthesized by amide bonding. Carbon nanotubes attached along the edges and onto the surface ...of graphene act as spacers to increase the electrolyte‐accessible surface area. Our lamellar structure electrodes demonstrate the largest volumetric capacitance (165 F cm‐3) ever shown by carbon‐based electrodes.
Mechanosensory feedback from the digestive tract to the brain is critical for limiting excessive food and water intake, but the underlying gut-brain communication pathways and mechanisms remain ...poorly understood
. Here we show that, in mice, neurons in the parabrachial nucleus that express the prodynorphin gene (hereafter, PB
neurons) monitor the intake of both fluids and solids, using mechanosensory signals that arise from the upper digestive tract. Most individual PB
neurons are activated by ingestion as well as the stimulation of the mouth and stomach, which indicates the representation of integrated sensory signals across distinct parts of the digestive tract. PB
neurons are anatomically connected to the digestive periphery via cranial and spinal pathways; we show that, among these pathways, the vagus nerve conveys stomach-distension signals to PB
neurons. Upon receipt of these signals, these neurons produce aversive and sustained appetite-suppressing signals, which discourages the initiation of feeding and drinking (fully recapitulating the symptoms of gastric distension) in part via signalling to the paraventricular hypothalamus. By contrast, inhibiting the same population of PB
neurons induces overconsumption only if a drive for ingestion exists, which confirms that these neurons mediate negative feedback signalling. Our findings reveal a neural mechanism that underlies the mechanosensory monitoring of ingestion and negative feedback control of intake behaviours upon distension of the digestive tract.
In the present study, composite sandwich structures were investigated to evaluate the effects of porous foams and surface patterns on structural stability and mass reduction of the composite sandwich ...structures. The composite structures used in the experiments consisted of three layers; the top and bottom polycarbonate (PC) layers and the core porous foam layers. Copper, nickel, and polypropylene (PP) foams were considered in the modeling of composite structures. Laser cutting technology was applied to the top PC layers of the composite structures to realize the surface patterns. Impact hammer and mass drop tests were performed on the composite structures to investigate their vibration attenuation and shock absorption performances. Numerous combinations of composite structures were considered by varying the foam materials and layer thicknesses to determine the best configuration. Finite element method (FEM)-based simulations were conducted to verify the experimental results. The results of this study support the implementation of porous foams and surface patterns for the increase in vibration attenuation and shock absorption performance, while achieving mass reduction for various applications in the engineering field.
•Surface patterns are realized on sandwich structures using laser cutting technology.•Porous foam and surface patterns are utilized to enhance vibration attenuation performance.•Increased shock absorption is induced by core porous foam layers of sandwich structures.•Finite element simulations are done to verify the experimental results of impact hammer and mass drop tests.
Titanium alloy is being widely used in various applications in aerospace, energy and biomedical industries mainly due to its superior material properties such as high strength even at high ...temperatures, lightweight and corrosion resistance. However, because of its extremely poor machinability, many enhancement techniques such as minimum quantity lubrication (MQL), cryogenic machining, laser assisted machining (LAM), etc., have been proposed to improve the machinability. This study specifically examined the machinabilities of MQL and cryogenic machining for Ti-6Al-4V and compared to those of dry and wet machining. Liquid nitrogen (LN2) was used for cryogenic machining with the specially designed cryogenic spraying systems. In addition to traditional MQL, a new MQL technique, with the lubricant mixed with a small amount (~0.1%) of exfoliated graphite nano-platelets (xGnPs), was tested to make the comparison against other techniques. The results obtained showed that both cryogenic and MQL machining showed improved performance in comparison to the dry and wet machining. For cryogenic machining, however, the exposure to LN2 causes the thermal gradient on the cutting tools and the hardening of the titanium alloy during the machining, which resulted in excessive tool wear and micro-fracture and increased the cutting forces.
G-protein-coupled receptor 40 (GPR40) is considered as an attractive drug target for treating type 2 diabetes, owing to its role in the free fatty acid-mediated increase in glucose-stimulated insulin ...secretion (GSIS) from pancreatic β-cells. To identify a new chemotype of GPR40 agonist, a series of 2-aryl-substituted indole-5-propanoic acid derivatives were designed and synthesized. We identified two GPR40 agonist lead compounds4k (3-2-(4-fluoro-2-methylphenyl)-1H-indol-5-ylpropanoic acid) and 4o (3-2-(2,5-dimethylphenyl)-1H-indol-5-ylpropanoic acid), having GSIS and glucagon-like peptide 1 secretory effects. Unlike previously reported GPR40 partial agonists that only activate the Gq pathway, 4k and 4o activated both the Gq and Gs signaling pathways and were characterized as GPR40 full agonists. In in vivo efficacy studies, 4o significantly improved glycemic control in both C57BL/6J and db/db mice and increased plasma-active GLP-1 in C57BL/6J mice. Thus, 4o represents a promising lead for further development as a novel GPR40 full agonist against type 2 diabetes.
It was reported that LAMMER kinase in
Schizosaccharomyces pombe
plays an important role in cation-dependent and galactose-specific flocculation. Analogous to other flocculating yeasts, when cell wall ...extracts of the Δ
lkh1
strain were treated to the wild-type strain, it displayed flocculation. Gas2, a 1,3-β-glucanosyl transferase, was isolated from the EDTA-extracted cell-surface proteins in the Δ
lkh1
strain. While disruption of the
gas2
+
gene was not lethal and reduced the flocculation activity of the ∆
lkh1
strain, the expression of a secreted form of Gas2, in which the GPI anchor addition sequences had been removed, conferred the ability to flocculate upon the WT strain. The Gas2-mediated flocculation was strongly inhibited by galactose but not by glucose. Immunostaining analysis showed that the cell surface localization of Gas2 was crucial for the flocculation of fission yeast. In addition, we identified the regulation of
mbx2
+
expression by Lkh1 using RT-qPCR. Taken together, we found that Lkh1 induces asexual flocculation by regulating not only the localization of Gas2 but also the transcription of
gas2
+
through Mbx2.
The endosomal sorting complex required for transport (ESCRT) plays a crucial role in the transportation and degradation of proteins. We determined that Vps27, a key protein of the ESCRT-0 complex, is ...required for the transport of the virulence factor laccase to the cell wall in
Laccase activity was perturbed, as was melanin production, in
Δ strains. In the absence of
, there was an accumulation of multivesicular bodies with vacuolar fragmentation and mistargeting of the vacuolar carboxypeptidase CPY/Prc1, resulting in an extracellular localization. In addition, deletion of
resulted in a defect in laccase targeting of a Lac1-green fluorescent protein (GFP) fusion to the cell wall with trapping within intracellular puncta; this deletion was accompanied by reduced virulence in a mouse model. However, the actin cytoskeleton remained intact, suggesting that the trafficking defect is not due to defects in actin-related localization. Extracellular vesicle maturation was also defective in the
Δ mutant, which had a larger vesicle size as measured by dynamic light scattering. Our data identify cryptococcal
as a required gene for laccase trafficking and attenuates virulence of
in a mouse intravenous (i.v.) meningitis model.
As the Internet of Things, artificial intelligence, and the fourth industrial revolution advance, smart factories and machines increasingly gain intelligent features that enable the integration of ...more sophisticated functionalities. Approaches to achieving this intelligence involve both internal systems, such as human–machine interface (HMI), and external systems, such as big data platforms and cloud services. Although current research leans toward studying external systems, accomplishing intelligent functions through such means poses more challenges in achieving real-time responses during machining processes than using internal systems. When intellectualizing machine tools through internal HMI systems, three critical issues must be addressed. First, HMI functions are structured to depend on the HMI itself, leading to a ripple effect where a problem occurring in one HMI function impacts the entire system. Second, owing to differences in development tools and programming languages, the interconnectivity between functions developed by multiple stakeholders to be loaded onto the HMI may suffer, leading to potential inefficiencies and increased maintenance costs. Third, although various types of computer numerical control (CNC) machines need to communicate with the HMI function, the diverse communication methods and development tools used by each CNC manufacturer result in identical intelligent functions being developed separately for each CNC type. To address these challenges, this study proposes an innovative HMI platform capable of executing and developing various intelligent functions. The HMI platform and its major components are designed and implemented through component-based development (CBD). Subsequently, the performance and effectiveness of the platform are validated using quality attribute scenarios.
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