Showing papers by "Stony Brook University published in 2022"

VQL: Efficient and Verifiable Cloud Query Services for Blockchain Systems

Abstract: Despite increasingly emerging applications, a primary concern for blockchain to be fully practical is the inefficiency of data query. Direct queries on the blockchain take much time by searching every block, while indirect queries on a blockchain database greatly degrade the authenticity of query results. To conquer the authenticity problem, we propose a Verifiable Query Layer (VQL) that can be deployed in the cloud to provide both efficient and verifiable data query services for blockchain systems. The middleware layer extracts data from the underlying blockchain system and efficiently reorganizes them in databases. To prevent falsified data from being stored in the middleware, a cryptographic fingerprint is calculated based on each constructed database. The database fingerprint will be first verified by miners and then written into the blockchain. Moreover, public users can verify the entire databases or several databases that interest them in the middleware layer. We implement VQL together with the verification schemes and conduct extensive experiments based on a practical blockchain system. The evaluation results demonstrate that VQL can efficiently support various data query services and guarantee the authenticity of query results for blockchain systems.

Development of Measures for the Hierarchical Taxonomy of Psychopathology (HiTOP): A Collaborative Scale Development Project:

Abstract: In this article, we describe the collaborative process that is underway to develop measures for the Hierarchical Taxonomy of Psychopathology (HiTOP). The HiTOP model has generated much interest in ...

Bacterial infections and death among patients with Covid-19 versus non Covid-19 patients with pneumonia.

Abstract: Background Many patients with Coronavirus disease-2019 (Covid-19) present with radiological evidence of pneumonia. Because it is difficult to determine co-existence of bacterial pneumonia, many of these patients are initially treated with antibiotics. We compared the rates of bacterial infections and mortality in Covid-19 patients with pulmonary infiltrates versus patients diagnosed with ‘pneumonia’ the year previously. Methods We conducted a medical record review of patients admitted with Covid-19 and a pulmonary infiltrate and compared them with patients diagnosed with pneumonia admitted in the prior year before the pandemic. Data abstracted included baseline demographics, comorbidities, signs and symptoms, laboratory and microbiological results, and imaging findings. Outcomes were bacterial infections and mortality. Patients presenting with and without Covid-19 were compared using univariable and multivariable analyses. Results There were 1398 and 1001 patients admitted through the emergency department (ED) with and without Covid-19 respectively. Compared with non-Covid-19 patients, those with Covid-19 were younger (61±18 vs. 65±25 years, P Conclusions The rate of bacterial infections is lower in Covid-19 patients with pulmonary infiltrates compared with patients diagnosed with pneumonia prior to the pandemic and most are nosocomial. Mortality was higher in Covid-19 than non-Covid-19 patients even after adjusting for age, tachypnea, hypoxemia, and bacterial infection.

Spin impurities, Wilson lines and semiclassics

Abstract: A bstract We consider line defects with large quantum numbers in conformal field theories. First, we consider spin impurities, both for a free scalar triplet and in the Wilson-Fisher O (3) model. For the free scalar triplet, we find a rich phase diagram that includes a perturbative fixed point, a new nonperturbative fixed point, and runaway regimes. To obtain these results, we develop a new semiclassical approach. For the Wilson-Fisher model, we propose an alternative description, which becomes weakly coupled in the large spin limit. This allows us to chart the phase diagram and obtain numerous rigorous predictions for large spin impurities in 2 + 1 dimensional magnets. Finally, we also study 1 / 2-BPS Wilson lines in large representations of the gauge group in rank-1 $$ \mathcal{N} $$ N = 2 superconformal field theories. We contrast the results with the qualitative behavior of large spin impurities in magnets.

The Hierarchical Taxonomy of Psychopathology (HiTOP) in psychiatric practice and research

Abstract: The Hierarchical Taxonomy of Psychopathology (HiTOP) has emerged out of the quantitative approach to psychiatric nosology. This approach identifies psychopathology constructs based on patterns of co-variation among signs and symptoms. The initial HiTOP model, which was published in 2017, is based on a large literature that spans decades of research. HiTOP is a living model that undergoes revision as new data become available. Here we discuss advantages and practical considerations of using this system in psychiatric practice and research. We especially highlight limitations of HiTOP and ongoing efforts to address them. We describe differences and similarities between HiTOP and existing diagnostic systems. Next, we review the types of evidence that informed development of HiTOP, including populations in which it has been studied and data on its validity. The paper also describes how HiTOP can facilitate research on genetic and environmental causes of psychopathology as well as the search for neurobiologic mechanisms and novel treatments. Furthermore, we consider implications for public health programs and prevention of mental disorders. We also review data on clinical utility and illustrate clinical application of HiTOP. Importantly, the model is based on measures and practices that are already used widely in clinical settings. HiTOP offers a way to organize and formalize these techniques. This model already can contribute to progress in psychiatry and complement traditional nosologies. Moreover, HiTOP seeks to facilitate research on linkages between phenotypes and biological processes, which may enable construction of a system that encompasses both biomarkers and precise clinical description.

Localized magnetic field in the O(N) model

Abstract: A bstract We consider the critical O ( N ) model in the presence of an external magnetic field localized in space. This setup can potentially be realized in quantum simulators and in some liquid mixtures. The external field can be understood as a relevant perturbation of the trivial line defect, and thus triggers a defect Renormalization Group (RG) flow. In agreement with the g -theorem, the external localized field leads at long distances to a stable nontrivial defect CFT (DCFT) with g < 1. We obtain several predictions for the corresponding DCFT data in the epsilon expansion and in the large N limit. The analysis of the large N limit involves a new saddle point and, remarkably, the study of fluctuations around it is enabled by recent progress in AdS loop diagrams. Our results are compatible with results from Monte Carlo simulations and we make several predictions that can be tested in the future.

Metastable dynamics of neural circuits and networks

Abstract: Cortical neurons emit seemingly erratic trains of action potentials or "spikes," and neural network dynamics emerge from the coordinated spiking activity within neural circuits. These rich dynamics manifest themselves in a variety of patterns, which emerge spontaneously or in response to incoming activity produced by sensory inputs. In this Review, we focus on neural dynamics that is best understood as a sequence of repeated activations of a number of discrete hidden states. These transiently occupied states are termed "metastable" and have been linked to important sensory and cognitive functions. In the rodent gustatory cortex, for instance, metastable dynamics have been associated with stimulus coding, with states of expectation, and with decision making. In frontal, parietal, and motor areas of macaques, metastable activity has been related to behavioral performance, choice behavior, task difficulty, and attention. In this article, we review the experimental evidence for neural metastable dynamics together with theoretical approaches to the study of metastable activity in neural circuits. These approaches include (i) a theoretical framework based on non-equilibrium statistical physics for network dynamics; (ii) statistical approaches to extract information about metastable states from a variety of neural signals; and (iii) recent neural network approaches, informed by experimental results, to model the emergence of metastable dynamics. By discussing these topics, we aim to provide a cohesive view of how transitions between different states of activity may provide the neural underpinnings for essential functions such as perception, memory, expectation, or decision making, and more generally, how the study of metastable neural activity may advance our understanding of neural circuit function in health and disease.

The Development of Preliminary HiTOP Internalizing Spectrum Scales.

Abstract: As part of a broader project to create a comprehensive self-report measure for the Hierarchical Taxonomy of Psychopathology consortium, we developed preliminary scales to assess internalizing symptoms. The item pool was created in four steps: (a) clarifying the range of content to be assessed, (b) identifying target constructs to guide item writing, (c) developing formal definitions for each construct, and (d) writing multiple items for each construct. This yielded 430 items assessing 57 target constructs. Responses from a heterogeneous scale development sample (N = 1,870) were subjected to item-level factor analyses based on polychoric correlations. This resulted in 39 scales representing a total of 213 items. The psychometric properties of these scales replicated well across the development sample and an independent validation sample (N = 496 adults). Internal consistency analyses established that most scales assess relatively narrow forms of psychopathology. Structural analyses demonstrated the presence of a strong general factor. Additional analyses of the 35 nonsexual dysfunction scales revealed a replicable four-factor structure with dimensions we labeled Distress, Fear, Body Dysmorphia, and Mania. A final set of analyses established that the internalizing scales varied widely-and consistently-in the strength of their associations with neuroticism and extraversion.

The SWI/SNF chromatin remodeling assemblies BAF and PBAF differentially regulate cell cycle exit and cellular invasion in vivo

Abstract: Chromatin remodelers such as the SWI/SNF complex coordinate metazoan development through broad regulation of chromatin accessibility and transcription, ensuring normal cell cycle control and cellular differentiation in a lineage-specific and temporally restricted manner. Mutations in genes encoding the structural subunits of chromatin, such as histone subunits, and chromatin regulating factors are associated with a variety of disease mechanisms including cancer metastasis, in which cancer co-opts cellular invasion programs functioning in healthy cells during development. Here we utilize Caenorhabditis elegans anchor cell (AC) invasion as an in vivo model to identify the suite of chromatin agents and chromatin regulating factors that promote cellular invasiveness. We demonstrate that the SWI/SNF ATP-dependent chromatin remodeling complex is a critical regulator of AC invasion, with pleiotropic effects on both G0 cell cycle arrest and activation of invasive machinery. Using targeted protein degradation and enhanced RNA interference (RNAi) vectors, we show that SWI/SNF contributes to AC invasion in a dose-dependent fashion, with lower levels of activity in the AC corresponding to aberrant cell cycle entry and increased loss of invasion. Our data specifically implicate the SWI/SNF BAF assembly in the regulation of the G0 cell cycle arrest in the AC, whereas the SWI/SNF PBAF assembly promotes AC invasion via cell cycle-independent mechanisms, including attachment to the basement membrane (BM) and activation of the pro-invasive fos-1/FOS gene. Together these findings demonstrate that the SWI/SNF complex is necessary for two essential components of AC invasion: arresting cell cycle progression and remodeling the BM. The work here provides valuable single-cell mechanistic insight into how the SWI/SNF assemblies differentially contribute to cellular invasion and how SWI/SNF subunit-specific disruptions may contribute to tumorigeneses and cancer metastasis.

Healing Mechanisms in Cutaneous Wounds: Tipping the Balance

Abstract: Acute and chronic cutaneous wounds pose a significant health and economic burden. Cutaneous wound healing is a complex process that occurs in four distinct, yet overlapping, highly coordinated stages: hemostasis, inflammation, proliferation, and remodeling. Postnatal wound healing is reparative, which can lead to the formation of scar tissue. Regenerative wound healing occurs during fetal development and in restricted postnatal tissues. This process can restore the wound to an uninjured state by producing new skin cells from stem cell reservoirs, resulting in healing with minimal or no scarring. Focusing on the pathophysiology of acute burn wounds, this review highlights reparative and regenerative healing mechanisms (including the role of cells, signaling molecules, and the extracellular matrix) and discusses how components of regenerative healing are being used to drive the development of novel approaches and therapeutics aimed at improving clinical outcomes. Important components of regenerative healing, such as stem cells, growth factors, and decellularized dermal matrices, are all being evaluated to recapitulate more closely the natural regenerative healing process. Impact Statement Acute wounds from thermal injury are common; they exert substantial physical and psychological effects on a patient and result in significant morbidity and mortality. This review provides a detailed overview of the mechanisms of reparative and regenerative wound healing; discusses the key cell types, signaling molecules, and molecular targets that influence these important biological pathways; and highlights current therapeutic approaches aimed at promoting regenerative wound healing. An increased understanding of the underlying mechanisms of reparative and regenerative healing will contribute to the development of innovative strategies for the clinical treatment of patients with severe burns.

A C3-continuous NURBS transition scheme for the CNC machining of short linear segments

Abstract: Linear motion commands, as used in computer numerical control (CNC) machine tools, require smoothing to guarantee continuous and steady machining. To date, several transition schemes have been developed to locally insert specially designed curves into the corners between linear segments. The purpose is to ensure both a high calculation efficiency and a good dynamic performance of CNC machining. However, very few studies have focused on the smoothness of transition curves. This study develops an analytical C3-continuous NURBS transition scheme, focusing on three issues: the C3-continuity of the mixed toolpath, the smoothing error, and shape control of the transition curve. Shape control is the main focus of this study. Its difficulty lies in determining the weights corresponding to control points according to the geometric characteristics of the linear toolpath considered. A simpler and effective method involves using an oscillating circle to determine the weights, effectively solving the shape-control problem. Simulation and experimental results demonstrate that the proposed method significantly improves the machining efficiency while ensuring machining quality.

Protein Flexibility and Dissociation Pathway Differentiation Can Explain Onset of Resistance Mutations in Kinases**

Abstract: Understanding how mutations render a drug ineffective is a problem of immense relevance. Often the mechanism through which mutations cause drug resistance can be explained purely through thermodynamics. However, the more perplexing situation is when two proteins have the same drug binding affinities but different residence times. In this work, we demonstrate how all-atom molecular dynamics simulations using recent developments grounded in statistical mechanics can provide a detailed mechanistic rationale for such variances. We discover dissociation mechanisms for the anti-cancer drug Imatinib (Gleevec) against wild-type and the N368S mutant of Abl kinase. We show how this point mutation triggers far-reaching changes in the protein's flexibility and leads to a different, much faster, drug dissociation pathway. We believe that this work marks an efficient and scalable approach to obtain mechanistic insight into resistance mutations in biomolecular receptors that are hard to explain using a structural perspective.

A C3-continuous NURBS transition scheme for the CNC machining of short linear segments

Abstract: Linear motion commands, as used in computer numerical control (CNC) machine tools, require smoothing to guarantee continuous and steady machining. To date, several transition schemes have been developed to locally insert specially designed curves into the corners between linear segments. The purpose is to ensure both a high calculation efficiency and a good dynamic performance of CNC machining. However, very few studies have focused on the smoothness of transition curves. This study develops an analytical C3-continuous NURBS transition scheme, focusing on three issues: the C3-continuity of the mixed toolpath, the smoothing error, and shape control of the transition curve. Shape control is the main focus of this study. Its difficulty lies in determining the weights corresponding to control points according to the geometric characteristics of the linear toolpath considered. A simpler and effective method involves using an oscillating circle to determine the weights, effectively solving the shape-control problem. Simulation and experimental results demonstrate that the proposed method significantly improves the machining efficiency while ensuring machining quality.

The 2020 global stock market crash: Endogenous or exogenous?

Abstract: Starting on February 20, 2020, the global stock markets began to suffer the worst decline since the Great Recession in 2008, and the COVID-19 has been widely blamed on the stock market crashes. In this study, we applied the log-periodic power law singularity (LPPLS) methodology based on multilevel time series to unravel the underlying mechanisms of the 2020 global stock market crash by analyzing the trajectories of 10 major world stock market indexes from both developed and emergent stock markets, including the S&P 500, the DJIA, and the NASDAQ from the United State, the FTSE from the United Kingdom, the DAX from Germany, the NIKKEI from Japan, the CSI 300 from China, the HSI from Hong Kong, the BSESN from India, and the BOVESPA from Brazil. In order to effectively distinguish between endogenous crash and exogenous crash in stock market, we proposed using the LPPLS confidence indicator as a classification proxy. The results show that the apparent LPPLS bubble patterns of the super-exponential increase, corrected by the accelerating logarithm-periodic oscillations, have indeed presented in the price trajectories of the seven indexes: S&P 500, DJIA, NASDAQ, DAX, CSI 300, BSESN, and BOVESPA, indicating that the large positive bubbles have formed endogenously prior to the 2020 stock market crash, and the subsequent crashes for the seven indexes are endogenous, stemming from the increasingly systemic instability of the stock markets inherently, while the well-known external shocks, such as the COVID-19 pandemic, the corporate debt bubble, and the 2020 Russia–Saudi Arabia oil price war, only served as sparks during the 2020 global stock market crash. In contrast, the crashes in the three remaining indexes: FTSE, NIKKEI, and HSI, are exogenous and hence are perhaps the only crashes truly due to the COVID-19 pandemic. We also found that in terms of the regime changes of the stock markets, no obvious LPPLS negative bubble pattern has been observed in the price trajectories of the 10 stock market indexes, indicating that the regime changes from a bear market to a bull market in late March 2020 are exogenous, stemming from external factors. The unprecedented market and economy rescue efforts from federal reserves and central banks across the world in unison may have played a critical role in quelling the 2020 global stock market crash in the nick of time. This paper creates a paradigm for future studies in real-time crash detection and underlying mechanism dissection. It serves to warn us of the imminent risks in not only the stock market but also other financial markets and economic indexes.

OpenMP application experiences: Porting to accelerated nodes

Abstract: As recent enhancements to the OpenMP specification become available in its implementations, there is a need to share the results of experimentation in order to better understand the OpenMP implementation’s behavior in practice, to identify pitfalls, and to learn how the implementations can be effectively deployed in scientific codes. We report on experiences gained and practices adopted when using OpenMP to port a variety of ECP applications, mini-apps and libraries based on different computational motifs to accelerator-based leadership-class high-performance supercomputer systems at the United States Department of Energy. Additionally, we identify important challenges and open problems related to the deployment of OpenMP. Through our report of experiences, we find that OpenMP implementations are successful on current supercomputing platforms and that OpenMP is a promising programming model to use for applications to be run on emerging and future platforms with accelerated nodes.

Online Pricing and Trading of Private Data in Correlated Queries

Abstract: With the commoditization of private data, data trading in consideration of user privacy protection has become a fascinating research topic. The trading for private web browsing histories brings huge economic value to data consumers when leveraged by targeted advertising. And the online pricing of these private data further helps achieve more realistic data trading. In this paper, we study the trading and pricing of multiple correlated queries on private web browsing history data at the same time. We propose CTRADE , which is a novel online data CommodiTization fRamework for trAding multiple correlateD queriEs over private data. CTRADE first devises a modified matrix mechanism to perturb query answers. It especially quantifies privacy loss under the relaxation of classical differential privacy and a newly devised mechanism with relaxed matrix sensitivity, and further compensates data owners for their diverse privacy losses in a satisfying manner. CTRADE then proposes an ellipsoid-based query pricing mechanism according to a given linear market value model, which exploits the features of the ellipsoid to explore and exploit the close-optimal dynamic price at each round. In particular, the proposed mechanism produces a low cumulative regret, which is quadratic in the dimension of the feature vector and logarithmic in the number of total rounds. Through real-data based experiments, our analysis and evaluation results demonstrate that CTRADE balances total error and privacy preferences well within acceptable running time, indeed produces a convergent cumulative regret with more rounds, and also achieves all desired economic properties of budget balance, individual rationality, and truthfulness.

State-of-Charge Balancing for Battery Energy Storage Systems in DC Microgrids by Distributed Adaptive Power Distribution

Abstract: We consider the control problem of fulfilling the desired total charging/discharging power while balancing the state-of-charge (SoC) of the networked battery units with unknown parameters in a battery energy storage system. We develop power allocating algorithms for the battery units. These algorithms make use of distributed estimators for the average desired power and the average unit state and the adaptive parameter estimators, and are showed to fulfill the desired total power while achieving battery unit SoC balancing as long as the undirected graph that represents the communication network among the battery units is connected and there is at least one battery unit with the knowledge of the desired total power. Numerical simulation verifies the effectiveness of the proposed power allocating algorithms.

Australian wildfire smoke in the stratosphere: the decay phase in 2020/2021 and impact on ozone depletion

Abstract: Abstract. Record-breaking wildfires raged in southeastern Australia in late December 2019 and early January 2020. Rather strong pyrocumulonimbus (pyroCb) convection developed over the fire areas and lofted enormous amounts of biomass burning smoke into the tropopause region and caused the strongest wildfire-related stratospheric aerosol perturbation ever observed around the globe. We discuss the geometrical, optical, and microphysical properties of the stratospheric smoke layers and the decay of this major stratospheric perturbation. A multiwavelength polarization Raman lidar at Punta Arenas (53.2∘ S, 70.9∘ W), southern Chile, and an elastic backscatter Raman lidar at Río Grande (53.8∘ S, 67.7∘ W) in southern Argentina, were operated to monitor the major record-breaking event until the end of 2021. These lidar measurements can be regarded as representative for mid to high latitudes in the Southern Hemisphere. A unique dynamical feature, an anticyclonic, smoke-filled vortex with 1000 km horizontal width and 5 km vertical extent, which ascended by about 500 m d−1, was observed over the full last week of January 2020. The key results of the long-term study are as follows. The smoke layers extended, on average, from 9 to 24 km in height. The smoke partly ascended to more than 30 km height as a result of self-lofting processes. Clear signs of a smoke impact on the record-breaking ozone hole over Antarctica in September–November 2020 were found. A slow decay of the stratospheric perturbation detected by means of the 532 nm aerosol optical thickness (AOT) yielded an e-folding decay time of 19–20 months. The maximum smoke AOT was around 1.0 over Punta Arenas in January 2020 and thus 2 to 3 orders of magnitude above the stratospheric aerosol background of 0.005. After 2 months with strongly varying smoke conditions, the 532 nm AOT decreased to 0.03-0.06 from March–December 2020 and to 0.015–0.03 throughout 2021. The particle extinction coefficients at 532 nm were in the range of 10–75 Mm−1 in January 2020 and, later on, mostly between 1 and 5 Mm−1. Combined lidar–photometer retrievals revealed typical smoke extinction-to-backscatter ratios of 69 ± 19 sr (at 355 nm), 91 ± 17 sr (at 532 nm), and 120 ± 22 sr (at 1064 nm). An ozone reduction of 20 %–25 % in the 15–22 km height range was observed over Antarctica and New Zealand ozonesonde stations in the smoke-polluted air, with particle surface area concentrations of 1–5 µm2 cm−3.