Miracle-dz/UniFAR-FTUs huggingface dataset:
Heat Transfer Enhancement in a Rectangular Channel With the Combination of Ribs, Dimples and Protrusions

Rib turbulators can enhance the heat transfer successfully, but in most cases this is associated with large pressure loss penalties. Recently, dimple techniques become an attractive method for gas turbine blade internal cooling because dimples enhance heat transfer with low pressure penalty. In the present paper, a compound heat transfer enhancement technique, heat transfer enhancement in rectangular channel (Aspect ratio = 4) with the combination of ribs, dimples and protrusions, are investigated. The calculations are conducted on five different channel configurations. Case 1 which is the baseline configuration is a rectangular channel with rectangular ribs (e/Dh = 0.078, P/e = 10). In case 2, one row of dimples are placed between two ribs. In case 3, instead of dimples, one row of protrusions are placed between two ribs. In case 4, three rows of dimples are place between two ribs. Case 5 places three rows of protrusions between two ribs instead of dimples. The present paper focuses on Reynolds numbers (based on the channel hydraulic diameter) ranging from 10000 to 60000. In all configurations, the non-dimensional dimple/protrusion depths are 0.2. The results show that the rib+dimple cases provide minor increase in Nu/Nu0 , f/f0 and thermal performance. Within the Reynolds number range studied, the Nu/Nu0 values of the three row rib+protrusion case is 17% ∼ 7% higher than that of the baseline case, and the decrease in f/f0 is about 10%. The thermal performance of the three row rib+protrusion case is about 16% higher than that of the baseline case. The Nu/Nu0 values of the one row rib+protrusion case is about 9% higher than that of the baseline case, and the decrease in f/f0 is about 12%. The thermal performance of the one row rib+protrusion case is about 14% higher than that of the baseline case. It can be concluded that rib+protrusion technique in rectangular channel has the potential to provide heat transfer enhancement with low pressure penalty.Copyright © 2011 by ASME
FEM Simulation of the Effect of Mold Initial Temperature on Carbon Macrosegregation in Large-Size Steel Ingots

The impact of initial mold temperatures on the formation of macrosegregated zone during the solidification process of large size steel ingots was numerically investigated. Three initial mold temperatures, representing the most commonly encountered industrial conditions, were examined. The flows induced by pouring jet, the thermo-solutal convection, and the thermomechanical deformation of the phases were all taken into consideration. The results indicated that a higher mold temperature increased the macrosegregation intensity in the upper section of the casting, along the centerline and in the mid-radius solute-enriched bands. The increase was associated with the increased temperature gradient in the casting, the advance predominance of thermal convection, and the delayed solidification process.
Detecting user status from smartphone sensor data

Due to the high increment in usage and built-in advanced technology of smartphones, human activity recognition relying on smartphone sensor data has become a focused research area. In order to reduce noise of collected data, most of previous studies assume that smartphones are fixed at certain positions. This strategy is impractical for real life applications. To overcome this issue, we here investigate a framework that allows detecting the status of a traveller as idle or moving regardless the position and the direction of smartphones. The application of our work is to estimate the total energy consumption of a traveller during a trip. A number of experiments have been carried out to show the effectiveness of our framework when travellers are not only walking but also using primitive vehicles like motorbikes.
Large Scale Frequency Domain Numerical Simulation of Aircraft Engine Tone Noise Radiation and Scattering

The engines represent a major source of aircraft noise both at take off and landing. For the large turbofan engines used nowadays on commercial aircraft, fan noise dominates in particular during approach flight and landing, when the thrust force necessary from the jet is relatively small. The tonal noise generated by fan rotor-stator interaction as cylindrical duct modes is radiated from the fan inlet and exhaust and is scattered by the various surfaces surrounding the nacelle, such as fuselage and wing. Eventually both the direct and the scattered field propagate to the far field through the complex mean flow around the aircraft. Earlier studies of fan inlet noise propagation either incorporate only the effects of the nacelle boundary layer [4] or consider the flow around the nacelle axisymmetric and inviscid [10, 8]. However, the non-uniform flow around the nacelle and the relative positions of the nacelle, fuselage and wing offer the designer a range of options for reducing the noise footprint of an aircraft. A numerical simulation of the phenomenon, which is a very convenient alternative to experiments at least in the initial design stage, represents a large-scale computational problem which becomes feasible using the recent developments in computational methods for advanced architecture computers. Time-domain methods have been proposed by various authors, including the present ones [9, 12, 14], to address this problem. Under that approach, it is straightforward to have a full nonlinear model for the sound propagation, based on the inviscid flow (Euler) equations, that applies both for take-off and landing. The use of an explicit low-storage time integration method avoids the need to store and solve a matrix at each time step, thus keeping the computer memory requirements relatively low. In this paper we present a different and complementary methodology based on the frequency domain solution of the linearized full potential equation. The possibility to solve for the acoustic field in one step as a boundary value problem must in this case be weighed against the difficulty of finding the solution of a system of equations with complex coefficients. As the size of this system increases rapidly with the frequency, a direct solution even using sparse solvers is precluded by the large memory requirements. An efficient method for its iterative solution must be devised. The paper first introduces the governing equations for the sound propagation problem. A new treatment of the radiation boundary conditions in the form of an augmented, perfectly matched layer (PML) equation, is then presented. This new equation allows us to have
ActiveCrowd: integrating active learning with Amazon Mechanical Turk

Won the Second Runner-up in the Final Year Project Competition 2014-2015 organized by the IEEE (Hong Kong) Computational Intelligence Chapter; the Third Prize in the Challenge Cup 2015 - Hong Kong University Students Extra-Curriculum Technology Contest under the category of Information Technology; and the Merit Award in Crossover 2015 Pan-Pearl River Delta Region Universities IT Project Competition (Hong Kong SAR Region).
Contrasting intensity of aragonite dissolution and dolomite cementation in glacial versus interglacial intervals of a subtropical carbonate succession

Aragonite and high‐Mg calcite are abundant in modern, neritic carbonate systems but almost absent in their fossil counterparts. Dissolution of these metastable mineral phases commonly leaves no visible trace in the sedimentary record, compromising the derivation of palaeoenvironmental information from the rock record. The upper 25 m of Integrated Ocean Drilling Program (IODP) Site U1460 on the outer ramp of the western Australian Shelf were investigated to study shallow burial (tens of metres) marine diagenesis in organic‐carbon poor sediments using microscopic, total organic carbon, biomarkers and mineralogical analysis in combination with porewater geochemistry. Aragonite dissolution is negligible at the seafloor but intensifies ca 5 m below, even though bulk porewaters are supersaturated for aragonite. This apparent contradiction likely results from dissolution in undersaturated microenvironments. Aragonite dissolution below 5 to 6 m is on average more intense in interglacial compared to glacial intervals. The presence of disseminated framboidal pyrite and porewater results indicate that minor sulphate reduction is active at IODP Site U1460. Sulphate reduction is probably limited by the low organic matter content (ca 0.2%). It is well‐known from the literature that incipient sulphate reduction can lead to a drop in pH and consequently to carbonate dissolution. It is therefore assumed that the slightly higher concentration of organic matter in the interglacial intervals allowed increased aragonite dissolution during sulphate reduction compared to glacial beds. Low amounts of dolomite cement (<15%) start to form at the same depth (5 to 6 m) as aragonite dissolution intensifies. Dolomite formation and aragonite dissolution also show covariance on a metre‐scale below 5 to 6 m, indicating that a low carbonate saturation state might enhance dolomite formation. This mechanism provides an indirect link between dolomite formation, aragonite dissolution and orbital cycles. The outcome of this study, therefore, contributes to a better understanding of differential diagenesis in marine carbonates.
Ai-Tong-An-Gao-Ji and Fisetin Inhibit Tumor Cell Growth in Rat CIBP Models by Inhibiting the AKT/HIF-1α Signaling Pathway

Background Ai-Tong-An-Gao-Ji (ATAGJ) has been extensively applied for acute bone cancer pain treatment with a satisfactory efficacy, while the specific mechanisms remain unclear and require further investigation. Methods Overlapped genes of ATAGJ and CIBP obtained from SwissTargetPrediction website and GeneCards database were presented as a Venn diagram. A network diagram of drug-component-target was further established using the Cytoscape 3.6. 0 software. The effect of fisetin on Walker 256 cell proliferation was observed by clone formation assay and EDU assay, and the interaction between fisetin and AKT was revealed using the immunoprecipitation assay. Effects of fisetin on AKT/HIF-1α signaling pathway in Walker 256 cells were ultimately detected using Western blot and qPCR assays. Results The key component fisetin and core target gene AKT were sorted out using the drug-component-target network with a binding energy between fisetin and AKT less than −5 kcal/mol. Clone formation assay and EDU assay showed that fisetin substantially suppressed the proliferation of Walker 256 cells. Immunoprecipitation assay results revealed that the combination of fisetin and AKT decreased the level of AKT/HIF-1α signaling pathway of Walker 256 cells. Conclusions The fisetin of ATAGJ can markedly suppress Walker 256 cells, and the mechanisms may be intimately associated with the combination of fisetin and AKT. Furthermore, fisetin decreased the level of p-AKT and inhibited the expression of the AKT/HIF-1α signaling pathway.
Institutional Investor Heterogeneity and Corporate Response to the Covid‐19 Pandemic

Abstract We examine the role of institutional investors in determining firms’ decisions whether to reduce dividends and share buybacks during the Covid‐19 pandemic. Our simple model predicts that the probability of cuts in payouts is linked to the holdings and types of institutions. We link our model to the attention‐based theories of the firm. We posit that the highly proximate nature of the pandemic may encourage greater risk aversion in organizations. Consequently, the presence of institutions that actively engage with managers results in a reduction in shareholders’ payouts during the pandemic to enable firms to deal with increased uncertainty, while institutions that seek short‐term value releases reduce the probability of cuts. We test our hypotheses using novel hand‐collected data on shareholders’ payout cuts in the UK during the Covid‐19 lockdown. We find that in firms with larger institutional holdings, shareholders’ payouts are more likely to be reduced as a response to the pandemic. However, institutional heterogeneity matters as institutions with a view to improve firms’ long‐term growth are more likely to affect corporate payout decisions. In contrast, institutions that focus on regular income (e.g. pension funds) seem to resist cuts even in the aftermath of a severe exogenous shock like the Covid‐19 pandemic.
Resilience Assessment for Microgrid with Pre-Position and Reconfiguration of Emergency Distribution Generations Under Natural Hazard

Recently, increasing the number and severity of the natural hazards requires the resilience assessment and enhancement of the power system, especially the microgrid system. The emergency distribution generations have great potential to enhance the resilience of microgrid against blackouts under the emergency environment. This paper investigates the resilience assessment of the microgrid system under natural hazard, where emergency distribution generations are firstly pre-positioned on system nodes and then reconfigured after system damage occurs. A new resilience metric index and an efficient approximation computation method are provided for the resilience assessment of the focused problem. A new pre-position strategy and a new reconfiguration strategy on emergency distribution generations are proposed for the microgrid system emergency restoration under natural hazard. Also, a framework of resilience assessment is provided for problem-solving. The results of extensive experiments on the modified IEEE 30-Bus system and modified IEEE 118-Bus system confirm the effectiveness of the resilience assessment methodology and the superiority of proposed restoration strategies.
ACAGT-007a, an ERK MAPK Signaling Modulator, in Combination with AKT Signaling Inhibition Induces Apoptosis in KRAS Mutant Pancreatic Cancer T3M4 and MIA-Pa-Ca-2 Cells

The mitogen-activated protein kinase (MAPK)/ERK and phosphatidylinositol-3 kinase (PI3K)/AKT pathways are dysregulated in various human cancers, including pancreatic ductal adenocarcinoma (PDAC), which has a very poor prognosis due to its lack of efficient therapies. We have previously identified ACAGT-007a (GT-7), an anti-cancer compound that kills ERK-active melanoma cells by inducing ERK-dependent apoptosis. Here, we investigated the apoptosis-inducing effect of GT-7 on three PDAC cell lines and its relevance with the MAPK/ERK and PI3K/AKT signaling pathways. GT-7 induced apoptosis in PDAC cells with different KRAS mutations (MIA-Pa-Ca-2 (KRAS G12C), T3M4 (KRAS Q61H), and PANC-1 (KRAS G12D)), being T3M4 most susceptible, followed by MIA-Pa-Ca-2, and PANC-1 was most resistant to apoptosis induction by GT-7. GT-7 stimulated ERK phosphorylation in the three PDAC cells, but only T3M4 displayed ERK-activation-dependent apoptosis. Furthermore, GT-7 induced a marked down-regulation of AKT phosphorylation after a transient peak in T3M4, whereas PANC-1 displayed the strongest and most sustained AKT activation, followed by MIA-Pa-Ca-2, suggesting that sustained AKT phosphorylation as a determinant for the resistance to GT-7-mediated apoptosis. Consistently, a PI3K inhibitor, Wortmannin, abolished AKT phosphorylation and enhanced GT-7-mediated apoptosis in T3M4 and MIA-Pa-Ca-2, but not in PANC-1, which showed residual AKT phosphorylation. This is the first report that ERK stimulation alone or in combination with AKT signaling inhibition can effectively induce apoptosis in PDAC and provides a rationale for a novel concurrent targeting of the PI3K/AKT and ERK pathways.
Recursive Histogram Tracking-Based Rapid Online Anomaly Detection in Cyber-Physical Systems

Prompt online detection of anomalies induced by malicious attacks enhances the efficacy of real-time operation and mitigation of attack, an indispensable part of any cyber-physical system (CPS) management. This article proposes a novel online rapid detection scheme that continuously monitors the data packet stream and infers the sequence of probability distributions, estimated as histograms, and alerts when a change in the histogram is detected, reporting both the attack as well as an estimate of its instant of commencement. A statistical data-driven attack model is proposed and employed that is general enough to represent two ubiquitous types of attacks on CPS: 1) replay and 2) bias-injection. The proposed detection framework relies on the fact that CPSs possess well-defined dynamics that are affected by quasistationary noise, which allows the histogram sequences of the system data packets to converge (to different distributions under the presence of the attack versus the absence of attack). The proposed online scheme detects an attack, and estimates the attack commencement time by relying on the computed distance between real-time estimated histogram versus apriori learned nominal histogram. Our formulation further sheds light on two different attack initiation-time-based subcases, “early” (attack starts before sufficient data of nominal behavior was collected to allow its histogram sequence to be closer to its nominal value) versus “late. ” The designed algorithm of our scheme has linear time complexities in the dimension of data packets and algorithm parameters, which makes it suited for rapid detection. The proposed algorithm is implemented and validated on two real supervisory control and data acquisition system datasets, where a low detection delay demonstrates the effectiveness of the scheme.
COMPARISION AND EVALUATION OF MODELS FOR STRUCTURAL SEISMIC RESPONSES ANALYSIS

Two types of models, displacement input model and uniform acceleration input model, for structural response calculation subjected to earthquake ground motions, are reviewed and discussed. It is found that the omitted damping terms in the two models are different, which may have significant influence on structural responses. It is recommended that displacement input model, rather than uniform acceleration input model, to be adopted in comparing seismic responses caused by consistent excitations with those caused by multi-support excitations, to avoid the influence of the difference in omitted damping terms. Moreover, it is pointed out, contrary to the current viewpoints, modal superposition method is not applicable to the displacement input model.
Improving Graph Classification by Means of Linear Combinations of Reduced Graphs

The development and research of graph-based matching techniques that are both computationally efficient and accurate is a pivotal task due to the rapid growth of data acquisition and the omnipresence of structural data. In the present paper, we propose a novel framework using information gained from diversely reduced graph spaces to improve the classification accuracy of a structural classifier. The basic idea consists of three subsequent steps. First, the original graphs are reduced to different size levels with the aid of node centrality measures. Second, we compute the distances between the reduced graphs in the corresponding graph subspaces. Finally, the distances are linearly combined and fed into a distance-based classifier to produce the final classification. On six graph datasets we empirically demonstrate that classifiers clearly benefit from the combined distances obtained in the graph subspaces.
Using hybrid modelling to predict basal area and evaluate effects of climate change on growth of Norway spruce and Scots pine stands

ABSTRACT When modelling forest growth, capturing the effects of climate change is needed for reliable long-term predictions and management choices. This remains a challenge because commonly used mensurational forest growth and yield models, relying on inventory data, cannot account for climate change effects. We developed hybrid physiological/mensurational basal area growth and yield models, which combine physiological response to climatic conditions and empirical relations. We included climate and site effects by replacing time with light sums of photosynthetically active radiation and modifying the latter with monthly soil water, vapour pressure deficit, temperature, and frost days. When parameterised with permanent sample plot data for Scots pine and Norway spruce across Sweden, the hybrid models could reproduce observations well, although with no increase in precision compared with time-based mensurational models. When considering different climate scenarios, a significant impact on productivity from climate change emerged. For example, a 2 °C warming enhanced Scots pine production by up to 14% in regions where temperatures were originally cooler and soil water deficit was low (i.e. northwest Sweden), but depressed it, up to 9%, elsewhere. Hence, climate-sensitive models that take local variations into account are necessary for accurate predictions and sustainable forest management.
Variable Offset Computation Space for Automatic Cooling Dimensioning

The injection mold is one of the most important elements for the part precision of this important mass production process. The thermal mold design is realized by cooling channels around the cavity and poses as a decisive factor for the part quality. Thus, the objective but specific design of the cooling channel layout is crucial for a reproducible part with high-dimensional accuracy in production. Consequently, knowledge-based and automated methods are used to create the optimal heat management in the mold. One of these methods is the inverse thermal mold design, which uses a specific calculation space. The geometric boundary conditions of the optimization algorithm influence the resulting thermal balance within the mold. As the calculation area in the form of an offset around the molded part is one of these boundary conditions, its influence on the optimization result is determined. The thermal optimizations show a dependency on different offset shapes due to the offset thickness and coalescence of concave geometries. An algorithm is developed to generate an offset for this thermal mold design methodology considering the identified influences. Hence, a reproducible and adaptive offset is generated automatically for a complex geometry, and the quality function result improves by 43% in this example.
Black Fungi and Stone Heritage Conservation: Ecological and Metabolic Assays for Evaluating Colonization Potential and Responses to Traditional Biocides

Identifying species involved in biodeterioration processes is helpful, however further effort is needed to assess their ecological requirements and actual activity. Black fungi (BF) represent one of the most underestimated threats to stone cultural heritage in the Mediterranean basin; they are difficult to kill or remove due to their ability to grow inside the rock and cope with several stresses. Despite this, little is known about BF and factors favoring their growth on stone surfaces. Eighteen BF species were here investigated for temperature and salt tolerance, and metabolic traits by plate assays. The relation between some highly damaged monuments and their BF settlers was assessed using X-ray diffraction analysis, mercury intrusion porosimetry, and SEM. The sensitiveness to four commonly used traditional biocides was also tested. All strains were able to grow within the range of 5–25 °C and in the presence of 3.5% NaCl. Instrumental analyses were fundamental in discovering the relation between halophilic strains and weathered marble sculptures. The acid, cellulase, esterase, and protease production recorded proved BF’s potential to produce a chemical action on carbonate stones and likely affect other materials/historical artefacts. Besides, the use of carboxymethylcellulose and Tween 20 should be evaluated in restoration practice to prevent tertiary bioreceptivity. Agar diffusion tests helped identify the most resistant species to biocides, opening the perspective of its use as reference organisms in material testing procedures.