Bubble Burst Research Articles

Nature-inspired trapped air cushion surfaces for environmentally sustainable antibiofouling

Feathers of seabirds and waterfowl (for example the mallard duck (Anas platyrhynchos)) consist of hierarchical fibrillar structures encapsulated with hydrophobic preen oil. These characteristics afford waterproofing through the entrapment of air pockets, enabling swimming and diving for such bird species. This liquid repellency mechanism for bird feathers is mimicked by surface hydrophobisation of fibrous nonwoven polypropylene textiles to create large volumes of trapped air at the solid–liquid interface (plastron). Higher static water contact angle values correlate to a greater resistance towards water ingress (akin to the behaviour of mallard feathers). In order to extend the trapped gas layer lifetimes, the transportation of air from the water surface to a submerged air bubble by the diving bell spider (Argyroneta aquatica) for respiration is mimicked via short duration (< 1 s) solar-powered air bubble bursts once every 2 h. This combination of ornithological and arachnological inspired approaches yields stable trapped gas layers at the solid–liquid interface which are shown to inhibit biofouling in real-world outdoor wet environments.

The mirror of history: How to statistically identify stock market bubble bursts

This paper proposes a method for detecting bubble phases and the timing of bursts in global stock markets. The study identifies 27 bubbles in 29 global stock market indices over the last century. Using transformations and change-point detection on index returns, we discover that every major bubble has the same two-phase pattern indeed. Although the mechanisms or causes of each bubble are complex and unique, they all follow the same pattern. Thus, our findings suggest that history has a tendency to repeat itself.

On "Storm Clouds on the Horizon: The 3 Perils of Unconstrained Academic Growth in Physical Therapist Education." Deusinger SS, Landers MR. Phys Ther. 2022;102:pzac046. https://doi.org/10.1093/ptj/pzac046.

We wholeheartedly agree with Deusinger and Landers1 that the current proliferation of new doctor of physical therapy (DPT) programs will likely lead to damaging consequences for the collective enterprise of academic physical therapy as well as for the students and patients it exists to serve. We do, however, believe that their forecast of “storm clouds on the horizon” is insufficiently severe. Instead, we would argue that, to borrow a phrase from Game of Thrones,2 “Winter is coming.” The unsustainable proliferation of new DPT programs in a marketplace in which demand cannot possibly keep up with supply is a classic example of an economic bubble. Eventually and inevitably, bubbles burst. Indeed, we have seen this occur before in physical therapist professional education. From 1989 to 2002, the number of physical therapist education programs in the United States increased by 75% (from 118 to 205).3 That bubble burst in the late 1990s, partly as the result of the passage of the ``Balanced Budget Amendment'' by the Republican-controlled US Congress in 1997, which led to drastic reimbursement cutbacks and reductions in jobs for physical therapists.4 The results were not pretty. The applicant pool plummeted by 74%, from an average of 342 applicants per program in 1995 to 88 in 2002.3 Total enrollment in US physical therapist education programs dropped by 30% from 1997 to 2003.3 Many programs were unable to fill their classes. Total enrollment did not recover until 2009; average applications per program, not until 2011.3 Those were hard years for physical therapy academic programs – for faculty, for students, and, most of all, for graduates.

Detection and monitoring of seafloor methane bubbles using hydrophones

Natural marine seeps of methane are important sources of greenhouse gas emissions that enter the global environment. Monitoring marine methane seeps will reveal important information about how they form, their source regions, and how much of the inventory is microbially consumed within the water column before the gas is released to the atmosphere. While active acoustics methods have been extensively used to detect and monitor methane emissions from the seafloor, there are only a few studies showing the use of passive acoustics for bubble sound detection and monitoring. In this presentation, we use passive acoustics data recorded in a methane seep field in Puget Sound to characterize the bubble sound and estimate the bubble radii from their sound frequency. We use the ratio of a short-term average from a bubble burst over the long-term average to automatically detect the bubble sounds. We also show the relationship between the number of bubble sound detections and the hydrostatics seafloor pressure fluctuations due to tidal changes in water height.

Air-in-liquid compound drop impact onto a pool

We investigate numerically the dynamics of a drop containing a bubble impacting onto a pool of the same liquid. We show that the bubble can be engulfed into the pool after impact only for a limited range of impact velocities and bubble sizes. Below a critical Weber number, the compound drop bounces from the surface. By contrast, above a second threshold in Weber number, the bubble bursts during impact. Depending on the bubble size, we identify two different mechanisms responsible for this higher impact velocity threshold, with central bursting at lower bubble sizes, or dimple bursting at larger bubble sizes. We then characterize and model the dynamics of the cavity, to finally provide an overview of the mechanisms affecting the bubble stability in the liquid.

Role of Mixing Dynamics on Mass Convection-Diffusion in Sparkling Wines: A Laboratory Study

This study is based on the hypothesis that the bubbles-induced vortex flows could enhance the release of carbon dioxide (CO2) from a glass of effervescent wine. To provide tangible evidence, we conducted a series of experiments, the first of which aimed to correlate the filling height and the bubble-induced flow dynamics with the CO2 volume flux released from the vessel during a tasting. The results obtained through micro-weighing and PIV experiments showed a correlation between the filling height, the mixing flow dynamics, and the amount of CO2 released at the air/wine interface by several mechanisms (bubble burst, diffusion). In order to hide the role of bubbles, we proposed a simple experimental device that consisted in stirring the wine (supersaturated in dissolved gas) mechanically, while avoiding the phenomenon of nucleation. This mechanical stirring system allowed for controlling the intensity of convective movements of the liquid phase by varying the rotation frequency of a glass rod. The results of this experiment have provided irrefutable evidence of a close link between the stirring dynamics of a wine supersaturated in dissolved gases and the release of CO2 by a mass convection-diffusion phenomenon.

Multi-dimensional Self-Exciting NBD Process and Default Portfolios

In this study, we apply a multidimensional self-exciting negative binomial distribution (SE-NBD) process to default portfolios with 13 sectors. The SE-NBD process is a Poisson process with a gamma-distributed intensity function. We extend the SE-NBD process to a multidimensional process. Using the multidimensional SE-NBD process (MD-SE-NBD), we can estimate interactions between these 13 sectors as a network. By applying impact analysis, we can classify upstream and downstream sectors. The upstream sectors are real-estate and financial institution (FI) sectors. From these upstream sectors, shock spreads to the downstream sectors. This is an amplifier of the shock. This is consistent with the analysis of bubble bursts. We compare these results to the multidimensional Hawkes process (MD-Hawkes) that has a zero-variance intensity function.

Ultrasound and laser-promoted dual-gas nano-generator for combined photothermal and immune tumor therapy.

The combination of photothermal therapy (PTT) and immune tumor therapy has emerged as a promising avenue for cancer treatment. However, the insufficient immune response caused by inefficient immunogenic cell death (ICD) inducers and thermal resistance, immunosuppression, and immune escape resulting from the hypoxic microenvironment of solid tumors severely limit its efficacy. Herein, we report an ultrasound and laser-promoted dual-gas nano-generator (calcium carbonate-polydopamine-manganese oxide nanoparticles, CPM NPs) for enhanced photothermal/immune tumor therapy through reprogramming tumor hypoxic microenvironment. In this system, CPM NPs undergo reactive decomposition in a moderately acidic tumor, resulting in the generation of calcium, manganese ions, carbon dioxide (CO2), and oxygen (O2). Calcium and manganese ions act as adjuvants that trigger an immune response. The cancer cell membrane rupture caused by sudden burst of bubbles (CO2 and O2) under ultrasound stimulation and the photothermal properties of PDA also contributed to the ICD effect. The generation of O2 alleviates tumor hypoxia and thus reduces hypoxia-induced heat resistance and immunosuppressive effects, thereby improving the therapeutic efficacy of combination PTT and immune therapy. The present study provides a novel approach for the fabrication of a safe and effective tumor treatment platform for future clinical applications.

The Greek sovereign debt crisis as an important chapter in the history of the European Monetary Union: empirical evidence and some thoughts on implications for investors and financial risk managers

After the burst of the US real estate price bubble in 2008, the events in Greece played, at least for some time, a unique role on the path towards the European sovereign debt crisis. We examine this issue empirically and then discuss some relevant questions for policymakers, regulators, fixed income investors, and financial risk managers. Our findings should be of interest when modeling risk premia determined in the market for sovereign bonds issued by countries that have introduced the Euro. Given the exposure of the European insurance industry to these fixed-income securities, the results are important for asset managers and financial risk managers that are working in this segment of the financial services industry.

Preparing for the Bursting of the Psychedelic Hype Bubble

This Viewpoint presents impediments to the clinical application of psychedelics created by extreme shifts in public perception while advocating further study and encouraging the dispute of claims not supported by available evidence.

Dynamic dependence and hedging strategies in BRICS stock markets with oil during crises

This paper discusses the asymmetric volatility spillovers between these two markets of BRICS’ countries during different financial and economic circumstances from 2010 until 2021, using the ARFIMA-FIAPARCH to model the dynamics of the marginal distribution. We study the feasibility of hedging stocks with oil, risk measurement functions allow financial practitioners to calculate the optimal hedge ratios and the corresponding to hedge portfolio returns. A dual long memory model is adopted to estimate the conditional mean and the conditional variance. Thereafter, a VaR,CVaR and ΔCVaR are applied to assess oil price exposure. Furthermore, to evaluate the optimal portfolio, we adopted the optimal portfolio weight, the optimal hedge ratio and the hedge effectiveness oil. Our results show that there are distinct economic benefits from hedging stocks with oil, although the effectiveness of hedging is both time-varying and market-state-dependent. We determine that the volatility transmission was time-varying and that influence from the Asian crisis, the bursting of the dot com bubble, the 2008 global financial crisis, the recent oil-price crash, and COVID 19 alternated between negative and positive values, over the entire studied period. During times of global financial uncertainty, investors reduce stock positions more than commodity positions, thus crude oil prices shock negatively affect the portfolio returns of stock-oil hedges. all stock market–oil pairs display the highest hedging effectiveness during the COVID-19 pandemic, which proved that the oil market can assist as a hedge for stock market in a portfolio.

Was the ICO boom just a sideshow of the Bitcoin and Ether Momentum?

We investigate whether the market for ICOs in 2017–2018 and 2021 showed signs of contagion from prices of Bitcoin and Ether. During phases of optimism, ICO daily returns display low correlations with those of Bitcoin or Ether. But when the bubble bursts, correlations jump to very high levels, signaling that the ICO market becomes a sideshow of the cryptocurrency dynamics. We demonstrate that this high correlation was not present during the Nasdaq bubble in the 1990s, signaling that the price dynamics of digital tokens seems to be driven by a common factor, much more than in previous bubbles.

Bubble-crash experience and investment styles of mutual fund managers

This study examines the effect of fund managers' bubble-crash experience on their investment styles. Using the 2007–2008 and 2014–2015 bubble-crash events of China's A-share market, we find that managers who experienced a stock market crash are more value-oriented in their portfolios. While the effect of firsthand bubble-crash experience on investment style is significant, we find little evidence of the impact of secondhand experience gained from institutional memory or the management team. We explain these findings using incomplete information learning theory, salience theory, and the change in risk preferences. Moreover, different investment styles across manager types affect fund performance around the time the new bubble burst in June 2015. Managers with 2007–2008 bubble-crash experience and a more value-oriented investment style have lower (higher) fund returns than those without such experience before (after) the bubble burst.

Mechanism of flash boiling bubble breakup based on rim-like structure

Flash boiling is an important phenomenon in internal multiphase flow and could lead to unique spray structures. Many researchers have investigated this phenomenon using optical diagnostic methods, and progress has been made in spray morphology studies as well as bubble dynamics inside the nozzle. However, the detailed transition mechanism from in-nozzle bubble to out-nozzle spray droplets has not been experimentally observed, and present theories could not elaborate the morphology change in the micro-scale droplets with high velocities. To illustrate the transition procedure from bubble to droplets of flash boiling bubbles, high-speed imaging technique is adopted on a specially designed optical nozzle with a two-dimensional ambient cavity to investigate the transition from in-nozzle flash boiling bubbles to out-nozzle spray droplets. A unique rim-like structure has been observed, and quantitative and qualitative analyses are made to figure out the nature of this rim. Based on the study, the driving force, as well as the transition process of flash boiling bubbles, has been demonstrated in detail, it is found that under high superheated degrees, the bubble burst process is governed by joint effort of thermal phase change and mechanical deformation. Based on the observed phenomena and theoretical analysis, a new flash boiling spray breakup theory that coincides with the actual physical process has been established.

To learn or not to learn? Evaluating autonomous, adaptive, automated traders in cryptocurrencies financial bubbles

Financial bubbles represent a severe problem for investors. In particular, the cryptocurrency market has witnessed the bursting of different bubbles in the last decade, which in turn have had spillovers on all the markets and real economies of countries. These kinds of markets and their unique characteristics are of great interest to researchers. Generally, investors and financial operators study market trends to understand when bubbles might occur using technical analysis tools. Such tools, which have been historically used, resulted in being precious allies at the basis of more advanced systems. In this regard, different autonomous, adaptive and automated trading agents have been introduced in the literature to study several kinds of markets. Among these, we can distinguish between agents with Zero/Minimal Intelligence (ZI/MI) and Computational Intelligence (CI)-based agents. The first ones typically trade on the market without resorting to complex learning strategies; the second ones usually use (deep) reinforcement learning mechanisms. However, these trading agents have never been tested on the cryptocurrencies market and related financial bubbles, which are still mostly overlooked in the literature. It is unclear how these agents can make profits/losses before, during, and after a bubble to adjust their strategy and avoid critical situations. This paper compares a broad set of trading agents (between ZI/MI and CI ones) and evaluates them with well-known financial indicators (e.g., volatility, returns Sharpe ratio, drawdown, Sortino and Omega ratio). Among the experiment’s outcomes, ZI/MI agents were more explainable than CI ones. Based on the results obtained above, we introduce GGSMZ, a trading agent relying on a neuro-fuzzy mechanism. The neuro-fuzzy system is able to learn from the trades performed by the agents adopted in the previous stage. GGSMZ’s performances overcome those of other tested agents. We argue that GGSMZ could be used by investors as a decision support tool.

Bursting bubble flow microextraction combined with gas chromatography for determination of organochlorine pesticides in aqueous samples

Bubble-bursting flow microextraction (BBFME) is a simple and powerful microextraction method that conforms to the principles of green analytical chemistry (GAC). This method, combined with GC, is used for extraction, pre-concentration, and determination of some organochlorine pesticides (OCPs) in aqueous samples. In this method, the target analytes are transferred to the surface of the sample solution by the flow of gas bubbles. After the bubbles burst, the analytes disperse into the upper space and are finally collected and extracted. One of the unique properties of gas bubbles is the creation of a two-phase liquid–gas system, whereby the extraction process occurs at the liquid–gas interface where analytes interact with gas molecules in the bubble. In this study, a new method based on the availability of gas bubbles was proposed and investigated. The conditions affecting BBFME performance, including extraction time, the effect of ionic strength, and sample pH were investigated. Under optimal conditions, the dynamic linear range was 0.74–100.0 μg L-1, and the limit of detection and limit of quantification were 0.24–0.33 and 0.74–0.98 μg L-1, respectively. The range of enrichment factor and recovery under optimal conditions was between 228 and 273 and between 82.1 % and 98.2 %, respectively. Finally, using the BBFME method, the toxins simazine, γ-BHC, alachlor, aldrin and dieldrin were successfully extracted from various aqueous samples with satisfactory relative recoveries ranging from 95.3 to 105.1 %.

Hunting, Fighting, or Playing with Bubbles: Possible Usage and Acoustic Characteristics of Bubble Burst Sounds Produced by the Amazon River Dolphin (Inia geoffrensis)

Acoustic characteristics of bubble production by an odontocete were documented for the first time. Bubble sounds produced by the Amazon river dolphin (Inia geoffrensis) were recorded incidentally as part of a survey of fish sounds in the Pacaya–Samiria National Reserve of Peru on six dates between 4 and 24 July 2012. Dolphins were observed to periodically produce large clouds of bubbles underneath or near the survey boat (averaging 7/survey or 8/h) as it drifted through areas of actively foraging dolphins. The bubble production was classified as bubble bursts due to their similarity to bubble bursts produced by other cetaceans. Bubble burst sounds had a mean peak frequency of 402 Hz and duration of 8.9 s (n = 51). Bubble bursts were temporally clustered with an average interval of 169 s (0.1 to 1,187 s) between bursts. Bubble bursts were disproportionately more likely to be present when fish sounds were also present, but it is not known if the association was due to predation or other factors. A review of the literature finds similar bubble production has been reported in at least 14 other species of cetaceans (4 mysticetes and 10 odontocetes). Most are commonly associated with play, surprise, agonistic, and foraging behaviors. We discuss each of these possibilities and conclude that Amazon river dolphin bubble burst behavior is most likely related to foraging or aggressive behavior because the behavior occurred in feeding areas and appeared to be directed at the drifting boat. We further propose a novel hypothesis that the bubble bursts are a hunting strategy used to disperse prey associated with floating vegetation mats and other forms of drifting materials used by fishes for shelter. Future research is needed to better understand the behavior associated with bubble production by the Amazon river dolphin.

Novel 3D-printed buoyant structures for improvement in flue gas CO2-derived microalgal biomass production by enhancing anti-biofouling on vertical polymeric photobioreactor

Novel 3D-printed buoyant structures can be applied in various environmental processes because of their considerable advantages. Microalgae cultivation in photobioreactors, directly supplemented by industrial CO2, enables environmental pollution mitigation/cleanup and sustainable energy production. However, in photobioreactor systems, biofilm formation due to gas bubbling decreases microalgal productivity. Therefore, in this study, we aimed to develop a novel 3D-printed buoyant structure to suppress biofilm formation. The 10 mm-sized spherical buoyant structure reduced the height and area of the biofilm by 58.3% and 82.5%, respectively. The structure decreased space where bubble burst occurred and controlled the bubble size, reducing the overall biomass loss by 58.7%. It did not reduce photobioreactor performance noticeably during semi-continuous cultivation, indicating the possibility of long-term applicability. In large-scale outdoor microalgae cultivation using flue gas CO2, the buoyant structure improved the cell density and biodiesel production potential without contamination. This study provides a promising strategy to contribute to biological CO2 mitigation through the utilization of flue gas CO2 for enhanced microalgal production, paving the way for energy and environmental sustainability.

How is machine learning useful for macroeconomic forecasting?

SummaryWe move beyond Is Machine Learning Useful for Macroeconomic Forecasting? by adding the how. The current forecasting literature has focused on matching specific variables and horizons with a particularly successful algorithm. To the contrary, we study the usefulness of the underlying features driving ML gains over standard macroeconometric methods. We distinguish four so‐called features (nonlinearities, regularization, cross‐validation, and alternative loss function) and study their behavior in both the data‐rich and data‐poor environments. To do so, we design experiments that allow to identify the “treatment” effects of interest. We conclude that (i) nonlinearity is the true game changer for macroeconomic prediction, (ii) the standard factor model remains the best regularization, (iii) K‐fold cross‐validation is the best practice, and (iv) the is preferred to the ‐insensitive in‐sample loss. The forecasting gains of nonlinear techniques are associated with high macroeconomic uncertainty, financial stress and housing bubble bursts. Furthermore, ML nonlinearities are helpful when considering density forecasts.

New collectivity measures for financial covariances and correlations

Complex systems are usually non-stationary and their dynamics is often dominated by collective effects. Collectivity, defined as coherent motion of the whole system or of some of its parts, manifests itself in the time-dependent structures of covariance and correlation matrices. The largest eigenvalue corresponds to the collective motion of the system as a whole, while the other large, isolated, eigenvalues indicate collectivity in parts of the system. In the case of finance, these are industrial sectors. By removing the collective motion of the system as a whole, the latter effects are much better revealed. We measure a remaining collectivity to which we refer as average sector collectivity. We identify collective signals around the Lehman Brothers crash and after the dot-com bubble burst. For the Lehman Brothers crash, we find a potential precursor. We analyze 213 US stocks over a period of more than 30 years from 1990 to 2021. We plot the average sector collectivity versus the collectivity corresponding to the largest eigenvalue to study the whole market trajectory in a two dimensional space spanned by both collectivities. Therefore, we capture the average sector collectivity in a much more precise way. Additionally, we observe that larger values in the average sector collectivity are often accompanied by trend shifts in the mean covariances and mean correlations. As of 2015/2016 the collectivity in the US stock markets changed fundamentally.