Analysis Of Experiments Research Articles

The Identification of Leidenfrost Phenomenon Formation on TiO2-Coated Surfaces and the Modelling of Heat Transfer Processes.

Experiments on specimen cooling dynamics and possible film boiling around a body are very important in various industrial applications, such as nucleate boiling, to decrease drag reduction or achieve better surface properties in coating technologies. The objective of this study was to investigate the interaction between the heat transfer processes and cooling dynamics of a sample in different boundary conditions. This article presents new experimental data on specimens coated with Al-TiO2 film and Leidenfrost phenomenon (LP) formation on the film's surface. Furthermore, this manuscript presents numerical heat and mass transfer parameter results. The comparative analysis of new experiments on Al-TiO2 film specimens and other coatings such as polished aluminium, Al-MgO, Al-MgH2 and Al-TiH2 provides further detail on oxide and hydride materials. In the experimental cooling dynamics experiments, specimens were heated up to 450 °C, while the sub-cooling water temperatures were 14*‒20 °C (room temperature), 40 °C and 60 °C. The specimens' cooling dynamics were calculated by applying Newton's cooling law, and heat transfer was estimated by calculating the heat flux q transferred from the specimens' surface and the Bi parameter. The metadata results from the performed experiments were used to numerically model the cooling dynamics curves for different material specimens. Approximated polynomial equations are proposed for the polished aluminium, Al-TiO2, Al-MgO, Al-MgH2 and Al-TiH2 materials. The provided comparative analysis makes it possible to see the differences between oxides and hydrides and to choose materials for practical application in the industrial sector. The presented results could also be used in software packages to model heat transfer processes.

BPP: a platform for automatic biochemical pathway prediction.

A biochemical pathway consists of a series of interconnected biochemical reactions to accomplish specific life activities. The participating reactants and resultant products of a pathway, including gene fragments, proteins, and small molecules, coalesce to form a complex reaction network. Biochemical pathways play a critical role in the biochemical domain as they can reveal the flow of biochemical reactions in living organisms, making them essential for understanding life processes. Existing studies of biochemical pathway networks are mainly based on experimentation and pathway database analysis methods, which are plagued by substantial cost constraints. Inspired by the success of representation learning approaches in biomedicine, we develop the biochemical pathway prediction (BPP) platform, which is an automatic BPP platform to identify potential links or attributes within biochemical pathway networks. Our BPP platform incorporates a variety of representation learning models, including the latest hypergraph neural networks technology to model biochemical reactions in pathways. In particular, BPP contains the latest biochemical pathway-based datasets and enables the prediction of potential participants or products of biochemical reactions in biochemical pathways. Additionally, BPP is equipped with an SHAP explainer to explain the predicted results and to calculate the contributions of each participating element. We conduct extensive experiments on our collected biochemical pathway dataset to benchmark the effectiveness of all models available on BPP. Furthermore, our detailed case studies based on the chronological pattern of our dataset demonstrate the effectiveness of our platform. Our BPP web portal, source code and datasets are freely accessible at https://github.com/Glasgow-AI4BioMed/BPP.

Identification of BAF60b as a Chromatin-Remodeling Checkpoint of Diet-Induced Fatty Liver Disease.

Overnutrition has gradually become the primary causative factor of nonalcoholic fatty liver disease (NAFLD). However, how nutritional signals are integrated to orchestrate the transcriptional programs important for NAFLD progression remains poorly understood. Here, we identified hepatic BAF60b as a lipid-sensitive subunit of the switch/sucrose-nonfermentable (SWI/SNF) chromatin-remodeling complex and is negatively associated with liver steatosis in mice and humans. Hepatic BAF60b deficiency promotes high-fat diet (HFD)-induced liver steatosis in mice, while transgenic expression of BAF60b in the liver attenuates HFD-induced obesity and NAFLD, both accompanied by a marked regulation of PPARγ expression. Mechanistically, through motif analysis of liver ATAC-Seq and multiple validation experiments, we identified CCAAT/enhancer-binding protein β (C/EBPβ) as the transcription factor that interacts with BAF60b to suppress PPARγ gene expression, thereby controlling hepatic lipid accumulation and NAFLD progression. This work uncovers hepatic BAF60b as a negative regulator of liver steatosis through C/EBPβ dependent chromatin remodeling.

CircHIPK3 nucleates IGF2BP2 and functions as a competing endogenous RNA

Circular RNAs represent a class of endogenous RNAs that regulate gene expression and influence cell biological decisions with implications for the pathogenesis of several diseases. Here, we disclose a novel gene-regulatory role of circHIPK3 by combining analyses of large genomics datasets and mechanistic cell biological follow-up experiments. Using time-course depletion of circHIPK3 and specific candidate RNA-binding proteins, we identify several perturbed genes by RNA sequencing analyses. Expression-coupled motif analyses identify an 11-mer motif within circHIPK3, which also becomes enriched in genes that are downregulated upon circHIPK3 depletion. By mining eCLIP datasets and combined with RNA immunoprecipitation assays, we demonstrate that the 11-mer motif constitutes a strong binding site for IGF2BP2 in bladder cancer cell lines. Our results suggest that circHIPK3 can sequester IGF2BP2 as a competing endogenous RNA (ceRNA), leading to target mRNA stabilization. As an example of a circHIPK3-regulated gene, we focus on the STAT3 mRNA as a specific substrate of IGF2BP2 and validate that manipulation of circHIPK3 regulates IGF2BP2-STAT3 mRNA binding and, thereby, STAT3 mRNA levels. Surprisingly, absolute copy number quantifications demonstrate that IGF2BP2 outnumbers circHIPK3 by orders of magnitude, which is inconsistent with a simple 1:1 ceRNA hypothesis. Instead, we show that circHIPK3 can nucleate multiple copies of IGF2BP2, potentially via phase separation, to produce IGF2BP2 condensates. Our results support a model where a few cellular circHIPK3 molecules can induce IGF2BP2 condensation, thereby regulating key factors for cell proliferation.

CircHIPK3 nucleates IGF2BP2 and functions as a competing endogenous RNA.

Circular RNAs represent a class of endogenous RNAs that regulate gene expression and influence cell biological decisions with implications for the pathogenesis of several diseases. Here, we disclose a novel gene-regulatory role of circHIPK3 by combining analyses of large genomics datasets and mechanistic cell biological follow-up experiments. Using time-course depletion of circHIPK3 and specific candidate RNA-binding proteins, we identify several perturbed genes by RNA sequencing analyses. Expression-coupled motif analyses identify an 11-mer motif within circHIPK3, which also becomes enriched in genes that are downregulated upon circHIPK3 depletion. By mining eCLIP datasets and combined with RNA immunoprecipitation assays, we demonstrate that the 11-mer motif constitutes a strong binding site for IGF2BP2 in bladder cancer cell lines. Our results suggest that circHIPK3 can sequester IGF2BP2 as a competing endogenous RNA (ceRNA), leading to target mRNA stabilization. As an example of a circHIPK3-regulated gene, we focus on the STAT3 mRNA as a specific substrate of IGF2BP2 and validate that manipulation of circHIPK3 regulates IGF2BP2-STAT3 mRNA binding and, thereby, STAT3 mRNA levels. Surprisingly, absolute copy number quantifications demonstrate that IGF2BP2 outnumbers circHIPK3 by orders of magnitude, which is inconsistent with a simple 1:1 ceRNA hypothesis. Instead, we show that circHIPK3 can nucleate multiple copies of IGF2BP2, potentially via phase separation, to produce IGF2BP2 condensates. Our results support a model where a few cellular circHIPK3 molecules can induce IGF2BP2 condensation, thereby regulating key factors for cell proliferation.

Experimental investigation on the grading optimisation and storage effect of crushed gangue for backfill

ABSTRACT Backfilling with coal gangue can effectively control gangue pollution and surface subsidence. In order to optimise the control effect of crushed gangue overlying rock, this article focuses on the regulating effect of gangue particle size grading on mechanical properties. Through research on the physical properties of gangue and natural graded gangue compaction experiments, the porosity of gangue and the process of gangue crushing are analysed. It is shown that the gangue material has good load-bearing performance. By storage analysis of the natural gradation experiments, the alarm height of the gangue was 20 m. Through compression experiments of group B, it was found that the particle deformation first increased and then decreased. By the analysis of particle strain energy density and breakage energy, it is concluded that the strain energy density of the sample from high to low is B1, B2, B6, A5, B5, B4, and the breakage energy to reach the sample state from low to high is A5, B6, B5, B4, B3, B2, B1, respectivley. The B6 group sample was found to have the best control effect on the overlying rock, thus providing suggestions for optimising the efficiency and effectiveness of backfill mining.

Tetragonal/orthorhombic phase Bi2WO6 homojunction for photoelectrochemical degradation of rhodamine B with high efficiency

Photoelectrochemical (PEC) degradation of organic pollutants to CO2 and H2O is a promising strategy to solve the growing environmental problems. Bismuth tungstate (Bi2WO6) has attracted much attention due to its good chemical stability and moderate conduction band valence band position. However, the PEC activity of Bi2WO6 catalysts is greatly limited due to its rapidly complex electron-hole. This article reports a rational low-cost design that successfully prepares tetragonal/orthorhombic Bi2WO6 homojunction on FTO conductive glass substrates through a simple two-step solvothermal method, significantly enhancing the PEC performance. The study investigated the effectiveness of photoelectrochemical degradation of the recalcitrant organic pollutant Rhodamine B (RhB) and conducted an in-depth exploration of the photoelectrocatalytic reaction process and mechanism. The experimental results indicate that the homojunction achieves a degradation rate of up to 100 % for the recalcitrant organic pollutant RhB within 30 minutes, significantly surpassing that of single-phase Bi2WO6, and at the same time the sample maintains good stability after five cycles of operation. Further analysis of the capture experiments indicates that holes (h+) and superoxide radicals (·O2⁻) are the primary active species responsible for RhB degradation. This study not only provides new insights into the design of high-efficiency photoelectrode, but also offers new solutions for environmental pollution control.

A Multiscale Modeling and Experimental Study on the Tensile Strength of Plain-Woven Composites with Hybrid Bonded-Bolted Joints.

CFRP hybrid bonded-bolted (HBB) joints combine the advantages of traditional joining methods, namely adhesive bonding, and bolting, to achieve optimal connection performance, making them the most favored connection method. The structural parameters of CFRP HBB joints, including overlap length, bolt-hole spacing, and fit clearance relationships, have a complex impact on connection performance. To enhance the connectivity performance of joint structures, this paper develops a multiscale finite element analysis model to investigate the impact of structural parameters on the strength of CFRP HBB joint structures. Coupled with experimental validation, the study reveals how changes in structural parameters affect the unidirectional tensile failure force of the joints. Building on this, an analytical approach and inverse design methodology for the mechanical properties of CFRP HBB joints based on deep supervised learning algorithms are developed. Neural networks accurately and efficiently predict the performance of joints with unprecedented combinations of parameters, thus expediting the inverse design process. This research combines experimentation and multiscale finite element analysis to explore the unknown relationships between the mechanical properties of CFRP HBB joints and their structural parameters. Furthermore, leveraging DNN neural networks, a rapid calculation method for the mechanical properties of hybrid joints is proposed. The findings lay the groundwork for the broader application and more intricate design of composite materials and their connection structures.

A nonsense variant in KRT31 is associated with autosomal-dominant monilethrix.

Monilethrix is a rare hereditary hair disorder that is characterised by a beaded hair shaft structure and increased hair fragility. Patients may also present with keratosis pilaris and nail changes. Research has identified three genes for autosomal-dominant monilethrix (KRT81, KRT83, and KRT86), and one gene for the autosomal-recessive form (DSG4). To investigate the genetic basis of autosomal-dominant monilethrix in families with no pathogenic variants in any of the known monilethrix genes, and to understand the mechanistic basis of variant pathogenicity using a cellular model. Nine affected individuals from four unrelated families were included in this study. A clinical diagnosis of monilethrix was assigned based on clinical examination and/or trichoscopy. Exome sequencing (ES) was performed in six individuals to identify pathogenic variants, and Sanger sequencing was used for co-segregation and haplotype analyses. Cell culture experiments (immunoblotting, immunofluorescence, and reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) analyses) were used to confirm variant pathogenicity, to determine expression and subcellular localisation of proteins, and to identify a possible nonsense-mediated mRNA decay. In six affected individuals with clinically suggested monilethrix, ES led to the identification of the nonsense variant c.1081G>T; p.(Glu361*) in KRT31, which was subsequently identified in other affected members of these families by Sanger sequencing. This variant led to the abolition of both the last three amino acids of the 2B subdomain and the complete C-terminal tail domain of keratin 31. Immunoblotting demonstrated that when co-expressed with its binding partner keratin 85, the truncated keratin 31 was still expressed, albeit less abundantly than the wild type protein. Immunofluorescence revealed that p.(Glu361*) keratin 31 had an altered cytoskeletal localisation and formed vesicular-like structures in the cell cytoplasm near the cell membrane. RT-qPCR analysis did not generate evidence for a nonsense mediated decay of the mutant transcript. This study is the first to identify pathogenic variants in KRT31 as a cause of autosomal-dominant monilethrix. This highlights the importance of hair keratin proteins in hair biology, and will increase the molecular diagnostic yield for rare ectodermal phenotypes of hair and nail tissues.

Efficient leather spreading operations by dual-arm robotic systems

To achieve precise grasping and spreading of irregular sheet-like soft objects (such as leather) by robots, this study addresses several challenges, including the irregularity of leather edges and the ambiguity of feature recognition points. To tackle these issues, this paper proposes an innovative method that involves alternately grasping the lowest point twice and using planar techniques to effectively spread the leather. We improved the YOLOV8 algorithm by incorporating the BIFPN network structure and the WIOU loss function, and trained a dedicated dataset for the lowest grasping points and planar grasping points, thereby achieving high-precision recognition. Additionally, we determined the optimal posture for grasping the lowest point and constructed an experimental platform, successfully conducting multiple rounds of leather grasping and spreading experiments with a success rate of 72%. Through an in-depth analysis of the failed experiments, this study reveals the limitations of the current methods and provides valuable guidance for future research.

Geometry import into virtual reality visualization engine for HEP experiments at BM@N

Modern visualization and multimedia platforms, such as Unity, provide immersive interaction for HEP experiment data analysis. In this work, we present the method for importing the detector geometry, solids hierarchy, and materials from GDML format directly to Unity. This method is based on parsing files in GDML format and generating the geometry using mesh generation algorithms and Constructive Solid Geometry methods. The provided method is applied to the BM@N experiment at NICA accelerator complex in Joint Institute of Nuclear Research and can be used in virtual reality and augmented reality applications for data analysis and outreach events in high energy physics experiments.

Local condensation heat transfer analysis of three-component mixture refrigerant R455A in plate heat exchanger

Plate heat exchangers are gaining popularity as condensers for their compact design and high efficiency. However, the uneven fluid distribution in channels poses a challenge to effective heat transfer. Existing literature lacks experimental analysis of local heat transfer coefficients for pure and zeotropic mixture refrigerants in plate heat exchangers. This study experimentally analyzed the local heat transfer of the three-component zeotropic mixture R455A at various conditions (mass flux 20, 30, and 50 kg m−2 s−1 and saturation temperatures 30 and 35 °C). Results show that the heat transfer coefficient increases with flow rates and decreases with saturation temperature. However, results indicated lower heat transfer coefficients compared to pure refrigerants due to mixture effects. In addition, the local distribution of the heat transfer coefficient revealed that the heat transfer coefficient is highest at the center compared to the edges of the channel due uneven distribution of refrigerants within the channel. This HTC pattern confirms an asymmetrical flow within the plate. A new correlation is being developed to predict the heat transfer coefficient of the ternary mixture, showing improved accuracy than previously proposed correlations.

Theoretical and experimental analysis of evaporative cooling with hydrophilic screen mesh on condenser surface

In this study, we theoretically and experimentally analyzed the effect of evaporative cooling on the external thermal resistance of a condenser with a water-filled hydrophilic screen mesh. To calculate the external thermal resistance of the condenser theoretically, the external thermal resistance model was developed, considering evaporative cooling in the screen mesh. The evaporative mass flow rate in the screen mesh was calculated using the Lewis number, which can convert heat transfer to mass transfer. Especially, the maximum flow rate absorbed by the screen mesh was theoretically determined by the capillary limit. In experimental approach, hydrophilic screen meshes with mesh numbers M100, M150, and M200 were manufactured and attached to an aluminum plate simulating the condenser surface. The external thermal resistance of the condenser was measured. Based on the results, the theoretical model was well matched with experimental results. The effects of the air velocity, mesh number, and heat flux on the external thermal resistance of the condenser with evaporative cooling in the water-filled hydrophilic screen mesh were investigated. Finally, it is shown that the external thermal resistance of the condenser with evaporative cooling using the water-filled hydrophilic screen mesh can be reduced up to an average of 92 %.

A Comparative Analysis of Machine Learning Algorithms for Identifying Cultural and Technological Groups in Archaeological Datasets through Clustering Analysis of Homogeneous Data

Machine learning algorithms have revolutionized data analysis by uncovering hidden patterns and structures. Clustering algorithms play a crucial role in organizing data into coherent groups. We focused on K-Means, hierarchical, and Self-Organizing Map (SOM) clustering algorithms for analyzing homogeneous datasets based on archaeological finds from the middle phase of Pre-Pottery B Neolithic in Southern Levant (10,500–9500 cal B.P.). We aimed to assess the repeatability of these algorithms in identifying patterns using quantitative and qualitative evaluation criteria. Thorough experimentation and statistical analysis revealed the pros and cons of each algorithm, enabling us to determine their appropriateness for various clustering scenarios and data types. Preliminary results showed that traditional K-Means may not capture datasets’ intricate relationships and uncertainties. The hierarchical technique provided a more probabilistic approach, and SOM excelled at maintaining high-dimensional data structures. Our research provides valuable insights into balancing repeatability and interpretability for algorithm selection and allows professionals to identify ideal clustering solutions.

Enhancing breast cancer treatment: mesoporous dopamine nanoparticles in synergy with chrysin for photothermal therapy.

Breast cancer is one of the most prevalent cancers, primarily affecting women. Among its subtypes, estrogen receptor-positive (ER+) breast cancer is particularly common. Inhibiting estrogen's effects is crucial for treating ER+ breast cancer, but current therapies often have significant side effects and limitations. Chrysin, a natural flavonoid, has shown potential in reducing estrogen receptor expression, but its poor water solubility hampers clinical application. This study explores the use of mesoporous dopamine nanoparticles (mPDA) to enhance the delivery and efficacy of Chrysin, combined with photothermal therapy (PTT), for breast cancer treatment. Chrysin-loaded mPDA nanoparticles (Chrysin@mPDA) were synthesized and characterized for their morphology, drug-loading efficiency, stability, and photothermal properties. Network pharmacology was used to predict Chrysin's mechanisms in breast cancer, which were validated through gene expression analysis in cell experiments. The therapeutic efficacy of Chrysin@mPDA with and without PTT was evaluated in a mouse model of breast cancer, with tumor volume and weight measured. Immunohistochemical analysis was conducted to assess estrogen receptor expression and immune cell infiltration in tumor tissues. Chrysin@mPDA nanoparticles demonstrated a high drug-loading capacity and excellent stability. Photothermal studies confirmed the nanoparticles' ability to generate heat upon laser exposure, significantly enhancing Chrysin release in acidic conditions with laser irradiation. Network pharmacology identified key target genes affected by Chrysin, including ESR1, BRCA1, CTNNB1, and BAX, which were validated through qPCR. In vivo, the combination of Chrysin@mPDA and PTT significantly reduced tumor volume and weight, decreased estrogen receptor-positive cells, and increased infiltration of CD3+CD4+ and CD3+CD8+ T cells in tumor tissues. The study highlights the potential of Chrysin-loaded mPDA nanoparticles combined with PTT as an effective strategy for breast cancer treatment. This approach addresses the limitations of Chrysin's solubility and enhances its therapeutic efficacy through synergistic mechanisms. The dual action of Chrysin in modulating gene expression and PTT in inducing localized hyperthermia and immune response suggests a promising avenue for improved breast cancer prognosis and reduced recurrence.

Underwater multi-sensor fusion localization with visual-inertial-depth using hybrid residuals and efficient loop closing

Unmanned underwater vehicles (UUVs) need robust localization systems to complete their missions safely. To address the degradation of the localization accuracy of UUVs using visual-based simultaneous localization and mapping (SLAM) in underwater environments. A full SLAM system that fuses visual-inertial-depth measurements using hybrid residuals and efficient loop closing is proposed. Specifically, a novel visual hybrid residual is presented with an adaptive dynamic weighting factor. Reprojection and photometric double constraints are constructed simultaneously using the selected robust features. These constraints are then optimized jointly with the IMU measurements and the relative depth measurements to obtain a more accurate pose. Furthermore, a new three-step image-to-sequence strategy and a convolutional auto-encoder (CAE)-based global image representation are adopted to select candidate frames in order to improve the recall of underwater visual loop closure detection. Quantitative and qualitative analyses of real-world artificial pool and ocean experiments demonstrate the accuracy and effectiveness of the proposed system.

Water-induced reversible deformation materials: Synthesis and UV polymerization of sulfonic based polyacrylates

Reversible deformable materials driven by water or humidity have crucial applications in many areas. A novel sulfonic based cross-linked polyacrylates were prepared by simple UV emulsion copolymerization of functional sulfonic based acrylates with conventional acrylates and epoxy acrylate resins. The structure of sulfonic based acrylates was characterized by FT-ATR,1H-NMR, high-resolution mass spectrometry. The thermal properties, surface morphology and structure of the cured polymers were analyzed. The reversible deformation induced by water and humidity were explored. Based on analysis of surface morphology, XPS and etching experiments, a reasonable deformation mechanism is proposed that the hydrophilic groups migrate to the surface of the oil-in-water colloidal particle film due to the difference in polarity and show a gradient distribution, and hydration of hydrophilic groups results in water absorption and film expansion. Reversible deformation materials driven by water or humidity are of great significance in the field of research on smart material systems.

Water Absorption Behavior of Date Palm Fruit Branches Fiber (DPF) Composites: Experimental and Statistical Analyses

ABSTRACT The environmental effects on the response of Date Palm Fiber (DPF) composites are explored through an in-depth analysis of water absorption behavior. This study comprehensively investigates the influence of fiber content, immersion time, and water type on mass gain. Rigorous experimentation and advanced statistical analyses quantify the percent contribution of each factor, emphasizing the dominant role of fiber content at 96.61%. While immersion time and water type contribute relatively smaller percentages (2.11% and 1.28%, respectively), their insights are invaluable for tailored composite design. The study extends to interaction effects, showcasing the combined influence of factors. Regression models, progressing from linear and reciprocal formulations to comprehensive global models, are developed. Meticulous examination of prediction accuracy, using diverse statistical metrics, highlights the superior performance of the global reciprocal model across different water types. This work provides essential insights for optimizing DPF composite design, fabrication, and application, empowering engineers and researchers to make informed decisions in industries demanding tailored water absorption behavior.

Modeling the unsteady wake of an impulsively started circular cylinder using refined potential flow theory

Cylindrical structures find usage in many engineering applications including tethered oil drums and engine canisters slung beneath helicopters in flight. The motion of air around such circular cylindrical structures and the helicopter presents interesting phenomena including flow separation, wakes and turbulence. The physics of these are enshrined in the continuity equation and the Navier–Stokes equations. Therefore, their studies are not only important in mathematics and physics, but they are also required for efficient helicopter operations. In practice, reduced-order models of these operations that take in aerodynamics models of the tethered loads are utilized for stability analysis, flight certification and pilot training because of the prohibitive cost of experimentation and computational analyses of these configurations. However, there is a dearth of realistic analytical models of finite cylinder flows because of the Navier–Stokes problem. Classical potential flow theory provides an avenue to develop such models, but the extant gaps in its predictions significantly preclude its usage for engineering applications. Attempting to bridge these gaps, this article introduces refined potential flow theory in which the governing equations and boundary conditions are satisfied. Viscous effects, fluctuations of the mean flow and three-dimensional effects are also incorporated. For characterization, refined potential flow theory is employed on an incompressible flow over an impulsively started circular cylinder for Reynolds numbers and non-dimensional times in the range 30<Re<104 and 0.2 ≤ T ≤ 77, 047 respectively. There is an excellent prediction of 0.209 for the Strouhal number at Re=3,900 . At this transitional Reynolds number, the harmonics of the Strouhal frequency are also captured, and the characteristic irregular fluctuations at sub-Strouhal frequencies are discernible in the velocity spectra. As the flow becomes more turbulent, these become more pronounced at Re=9,500 when the predicted Strouhal number is within 10% of experimental result. In the fully developed stage, spectra analyses of the wake velocity components at some downstream locations also display Kolmogorov's Five-Thirds law of homogeneous isotropic turbulence. The present model can thus aid the development of reduced-order models of helicopter operations that feature tethered cylindrical loads.

Penicianstinoids F-K, six undescribed meroterpenoids from the marine algicolous fungus Penicillium sp. RR-DL-1-7

Six previously undescribed meroterpenoids, penicianstinoids F-K (1–6), together with four known analogues, dehydroaustinol (7), dehydroaustin (8), penicianstinoid A (9), and furanoaustinol (10), were isolated from the cultures of the algicolous fungus Penicillium sp. RR-DL-1-7, derived from the red alga Rhodomela confervoides. Their structures and relative configuration were established by detailed spectroscopic analysis of NMR and HR-MS experiments, and the absolute configurations were assigned by X-ray diffraction and ECD spectral analysis. None of the isolates showed obvious growth inhibitory effects against five plankton and four bacteria species tested.