Dynamic Screening Research Articles

Dynamic Gust Detection and Conditional Sequence Modeling for Ultra-Short-Term Wind Speed Prediction

As the foundation for optimizing wind turbine operations and ensuring energy stability, wind speed forecasting directly impacts the safe operation of the power grid, the rationality of grid planning, and the balance of supply and demand. Furthermore, gust events, characterized by sudden and rapid wind speed fluctuations, pose significant challenges for ultra-short-term wind speed forecasting, making the data more complex and thus harder to predict accurately. To address this issue, this paper proposes a novel hybrid model that combines dynamic gust detection with Conditional Long Short-Term Memory (Conditional LSTM) and incorporates dynamic window adjustment and wind speed difference threshold screening methods. The model dynamically adjusts the window size to accurately detect gust events and uses a conditional LSTM model to adjust predictions based on gust and non-gust conditions. Experimental results show that the proposed model exhibits higher prediction accuracy across various wind speed scenarios, particularly during gust events. Through detailed experiments using data from a single actual wind farm, the effectiveness and practicality of the proposed hybrid model are demonstrated. The experimental results indicate that the proposed model outperforms contrast models, especially in handling gust events, significantly enhancing the robustness of ultra-short-term wind speed predictions.

Dynamic screening with liquidity constraints

AbstractWe consider a dynamic screening model with serially independent types where the agent is short-term liquidity constrained. We model a liquidity constraint as a hard constraint that forces the agent to renege whenever he would suffer a loss from fulfilling the contract terms in a given period. In particular, the violation of a liquidity constraint is a verifiable event that future contract terms can condition on. This verifiability leads to less stringent truth-telling constraints than those considered in the existing literature. We show that the weaker constraints do not affect optimal contracting, however. Moreover, we develop a novel method to study private values settings with continuous types and show that a regularity condition that has analogues in the literature on multi-dimensional screening ensures that the optimal contract is deterministic.

Influence of dynamical screening of four-quarks interaction on the chiral phase diagram

We investigate the effect of screening of the four-quarks contact interactions by the ring diagram at finite temperature and density in an effective chiral model inspired by QCD in the Coulomb gauge. As a consequence, a medium-dependent coupling naturally emerges which, in a class of chiral models, brings the chiral crossover temperature down to the value calculated in lattice QCD at low net-baryon density. Furthermore, it implies a stronger divergence of the chiral susceptibility at the critical point compared to the mean-field dynamics. At high densities, the screening induces a substantial instability region and its size depends on the regularization schemes. We discuss the properties of an effective potential for a class of models described by momentum-independent gap equations. In particular, we introduce the method to construct an approximate effective potential from the gap equations to determine the location of the first-order phase transition. Published by the American Physical Society 2024

A Dynamically Ion-Sieved Electrolyte towards Ultralong-Lifespan Zn-Ion Batteries.

The practical deployment of Zn-ion batteries faces challenges such as dendrite growth, side reactions and cathode dissolution in traditional electrolytes. Here, we develop a highly conductive and dynamically ion-sieved electrolyte to simultaneously enhance the Zn metal reversibility and suppress the cathode dissolution. The dynamic ion screen at the electrode/electrolyte interface is achieved by numerous pyrane rings with a radius of 3.69 Å, which can selectively facilitate the plating/stripping and insertion/extraction process of [Zn(H2O)6]2+ and Zn2+ on the anode and cathode surfaces. As a proof of concept, Zn//Zn symmetric cells deliver exceptional cyclic stability for over 6,800 h and ultrahigh cumulative plated capacity of 1.95 Ah cm-2. Zn//Na2Mn3O7 cells exhibit satisfactory cycling performance with capacity retention of 82.7 % after 4,000 cycles, and the assembled pouch cells achieve excellent stability and durability. This work provides valuable insights into the development of electrolytes aimed at enhancing the interface stability of aqueous batteries.

A Dynamically Ion‐Sieved Electrolyte towards Ultralong‐Lifespan Zn‐Ion Batteries

AbstractThe practical deployment of Zn‐ion batteries faces challenges such as dendrite growth, side reactions and cathode dissolution in traditional electrolytes. Here, we develop a highly conductive and dynamically ion‐sieved electrolyte to simultaneously enhance the Zn metal reversibility and suppress the cathode dissolution. The dynamic ion screen at the electrode/electrolyte interface is achieved by numerous pyrane rings with a radius of 3.69 Å, which can selectively facilitate the plating/stripping and insertion/extraction process of [Zn(H2O)6]2+ and Zn2+ on the anode and cathode surfaces. As a proof of concept, Zn//Zn symmetric cells deliver exceptional cyclic stability for over 6,800 h and ultrahigh cumulative plated capacity of 1.95 Ah cm−2. Zn//Na2Mn3O7 cells exhibit satisfactory cycling performance with capacity retention of 82.7 % after 4,000 cycles, and the assembled pouch cells achieve excellent stability and durability. This work provides valuable insights into the development of electrolytes aimed at enhancing the interface stability of aqueous batteries.

Insights into missing populations: Exploring characteristics of unscreened patients with cancer in psychosocial distress and social drivers of health screening in an ambulatory setting.

174 Background: Psychosocial distress is common among patients with cancer and distress screening is required for American College of Surgeons Commission on Cancer accreditation. Screenings proactively identify needs, connect patients to services, reduce distress and improve cancer outcomes. We implemented a dynamic 17-question electronic screening tool that includes: assessment for psychosocial distress, social drivers of health (SDH) and spiritual care, and evaluated differences in patient characteristics among those who did and did not complete the survey. Methods: The survey was developed through an interdisciplinary review of evidence-based questions to proactively address supportive care needs for patients. It is available in English and Spanish and sent to patients via the patient portal 7 days before the second oncology appointment with a reminder 3 days before the appointment. It was implemented across 5 Mount Sinai Health System ambulatory facilities, spanning 3 New York City boroughs between June 2022 and February 2024. We used descriptive statistics to compare demographic and clinical characteristics of patients who did and did not complete the survey. Results: A total of 11,199 patients were assigned surveys; (42%) did not complete it. Patients who did not complete the survey were more likely to be Asian and Hispanic, older age, to speak a language other than English, reside in Queens or Brooklyn, and were less likely to have Commercial insurance compared to those who completed the survey (p<0.001 for all). There was no difference in sex (p=0.93) among the groups. Conclusions: There are significant disparities in the completion rates of electronic psychosocial distress and SDH screenings among patients with cancer, revealing that certain groups are less likely to engage with the tool. Targeted strategies are needed to increase screening completion rates among these populations. Future efforts should focus on addressing language barriers, enhancing technological accessibility, and developing culturally sensitive approaches to ensure all patients benefit from these screenings so we can better identify and address the supportive care needs of all cancer patients. Characteristics of patients who did and did not complete the survey. Characteristic Did Not Complete4654 (42%) Completed6545 (58%) p-value Race <0.001 Black 978 (21) 1538 (23) Asian 642 (14) 698 (11) Unknown 225 (5) 258 (4) Other/Patient Declined 1298 (28) 1461 (22) White 1511 (32) 2590 (40) Age (mean (SD)) 64 (14) 61 (15) <0.001 Non English Language 1167 (25) 956 (15) <0.001

Dynamic Screening in International Crises

Dynamic Screening in International Crises

Effects of dynamical dielectric screening on the excitonic spectrum of monolayer semiconductors

Effects of dynamical dielectric screening on the excitonic spectrum of monolayer semiconductors

Exciton-Exciton Interactions in Van der Waals Heterobilayers

Exciton-exciton interactions are key to understanding nonlinear optical and transport phenomena in van der Waals heterobilayers, which emerged as versatile platforms to study correlated electronic states. We present a combined theory-experiment study of excitonic many-body effects based on first-principle band structures and Coulomb interaction matrix elements. Key to our approach is the explicit treatment of the fermionic substructure of excitons and dynamical screening effects for density-induced energy renormalization and dissipation. We demonstrate that dipolar blueshifts are almost perfectly compensated by many-body effects, mainly by screening-induced self-energy corrections. Moreover, we identify a crossover between attractive and repulsive behavior at elevated exciton densities. Theoretical findings are supported by experimental studies of spectrally narrow, mobile interlayer excitons in atomically reconstructed, h-BN-encapsulated MoSe2/WSe2 heterobilayers. Both theory and experiment show energy renormalization on a scale of a few meV even for high injection densities in the vicinity of the Mott transition. Our results revise the established picture of dipolar repulsion dominating exciton-exciton interactions in van der Waals heterostructures and open up opportunities for their external design. Published by the American Physical Society 2024

Eliashberg Theory for Dynamical Screening in Bilayer Exciton Condensation.

We study the effect of dynamical screening of interactions on the transition temperatures (T_{c}) of exciton condensation in a symmetric bilayer of quadratically dispersing electrons and holes by solving the linearized Eliashberg equations for the anomalous interlayer Green's functions. We find that T_{c} is finite for the range of density and layer separations studied, decaying exponentially with interlayer separation. T_{c} is suppressed well below that predicted by a Hartree Fock mean field theory with unscreened Coulomb interaction, but is above the estimates from the statically screened Coulomb interaction. Furthermore, using a diagrammatic framework, we show that the system is always an exciton condensate at zero temperature but T_{c} is exponentially small for large interlayer separation.

Dissipative Kinematics in Binary Neutron Star Mergers

We highlight the recent progress in the calculation of transport coefficients pertinent to binary neutron star mergers. Specifically, we analyze the bulk viscosity coefficient driven by both the DURCA and MURCA processes and electron transport coefficients in dense and hot plasma relevant to the merger scenario. The study considers high temperatures (T>6×1010 K) and dense environments (nB∼n0−3n0). Bulk viscosity exhibits resonant behavior, with peak values and Peak positions dependent on particle interaction rates and thermodynamic susceptibilities. Susceptibilities are calculated by modeling the nuclear matter in the density functional approach. The bulk viscosity coefficient peaks at T∼1011 K, with a compression–rarefaction oscillation dissipation time scale of 20–50 ms. Electrical transports incorporate frequency-dependent dynamical screening in quantized electron–ion scattering rates. Consequently, dynamical screening reduces the maxima of electrical and thermal conductivities, shortening corresponding dissipation time scales. These results highlight the crucial role of dissipation coefficients in understanding binary neutron star mergers.

Clinical and genetic characteristics of 1672 cases of amyotrophic lateral sclerosis in China: a single-center retrospective study.

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease. In recent years, continuous discoveries of new ALS-causing genes have enhanced the understanding of the genotype-phenotype relationship in ALS, aiding in disease progression prediction and providing a more comprehensive basis for genetic diagnosis. A total of 1672 ALS patients who visited the Neurology Department of Peking Union Medical College Hospital between January 2014 and December 2022 and met the revised El Escorial diagnostic criteria were included. Clinical data were collected, whole exome sequencing and dynamic mutation screening of the C9ORF72 gene were performed, and the clinical phenotypes and genotypes of the patients were analyzed. The average age of onset for the 1672 ALS patients was 52.6 ± 11.2years (range 17-85years), with a median disease duration of 14months at the time of visit (interquartile range 9-24months, range 2-204months). The male to female ratio was 833:839. The patients included 297 (17.8%) with bulbar onset, 198 (11.8%) with flail arm/leg syndrome, 89 (5.3%) with familial ALS, and 52 (3.1%) with concomitant frontotemporal dementia (FTD). Pathogenic variants associated with ALS were detected in 175 patients (10.5% of the cohort), with the most common mutations being SOD1, FUS, and ANXA11. Among patients with familial ALS, 56.2% (50/89) had genetic mutations, compared to 7.9% (125/1583) in sporadic ALS cases. From the perspective of phenotype-genotype correlation, (1) In ALS-FTD patients, the most common genetic mutations were ANXA11 and C9ORF72 repeat expansions. Patients with flail arm/leg syndrome more frequently carried mutations in SOD1, ANXA11, and hnRNPA1; (2) Despite genetic heterogeneity, it was observed that mutations in FUS and NEK1 were more common in males, and patients with FUS mutations had a younger age of onset; mutations in SOD1 and SQSTM1 were more likely to present with lower limb onset. This study provides comprehensive data on the genetic characteristics of ALS patients in China through large-scale clinical data and genetic analysis of 1672 cases. Differences in age of onset, onset site, and clinical phenotype among ALS patients with different genotypes can help clinicians better predict disease progression and provide a basis for precise diagnosis and individualized treatment.

Dynamic tuberculosis screening for healthcare employees

Regular tuberculosis (TB) screening is required for healthcare employees. TB is a potentially deadly disease. Early detection prevents the spread of the disease and helps with treatment. Two types of TB diagnostic tests, which vary in terms of cost and accuracy, are available on the market. Thus, hospitals need to carefully consider the available screening options to effectively monitor TB prevalence at low cost. We develop the first optimization model and solution approach in the literature that can be used to obtain effective TB screening policies where testing decisions are differentiated based on employee characteristics. We categorize healthcare employees based on the department they work in, the specific job they do, and their history of vaccination against TB. We develop a Markov decision process (MDP) model to determine which TB test should be utilized for each employee category to minimize the total costs related to testing, undetected infections, and employees’ time lost due to testing. Due to the size of the problem, we use approximate dynamic programming (ADP) to obtain near-optimal solutions. We analyze the ADP solutions under varying assumptions to develop a screening policy that specifies not only the type of the tests that should be used but also the frequency with which each test should be administered. We further examine the impact of system parameters such as costs and TB prevalence on our policy recommendation via a sensitivity analysis. The results indicate that our approach yields a simple policy that can be used by healthcare providers that do not have the expertise or the resources to develop and solve sophisticated optimization models on an ongoing basis.

Dynamic microfluidic single-cell screening identifies pheno-tuning compounds to potentiate tuberculosis therapy

Drug-recalcitrant infections are a leading global-health concern. Bacterial cells benefit from phenotypic variation, which can suggest effective antimicrobial strategies. However, probing phenotypic variation entails spatiotemporal analysis of individual cells that is technically challenging, and hard to integrate into drug discovery. In this work, we develop a multi-condition microfluidic platform suitable for imaging two-dimensional growth of bacterial cells during transitions between separate environmental conditions. With this platform, we implement a dynamic single-cell screening for pheno-tuning compounds, which induce a phenotypic change and decrease cell-to-cell variation, aiming to undermine the entire bacterial population and make it more vulnerable to other drugs. We apply this strategy to mycobacteria, as tuberculosis poses a major public-health threat. Our lead compound impairs Mycobacterium tuberculosis via a peculiar mode of action and enhances other anti-tubercular drugs. This work proves that harnessing phenotypic variation represents a successful approach to tackle pathogens that are increasingly difficult to treat.

Comparison of the Effects of Pilates and Yoga Exercise on the Dynamic Balancing Ability and Functional Movement of Fencers.

This study was conducted to compare and analyze whether Pilates exercise and yoga exercise help improve the performance of female fencers and prevent injury, and the dynamic balance test (LQ-YBT) and functional movement screening (FMS) test score of the elite adult female fencers were compared and analyzed as evaluation indicators. Participants were randomly classified into Pilates (n = 10) and yoga groups (n = 10), members of which took part in 50 min of exercise (5 min of warm-up, 40 min of main exercise, and 5 min of cool-down) twice weekly for eight weeks. The results obtained from this study were analyzed via independent t-test and 2-way ANOVA. The results were as follows: LQ-YBT measures (reaching distance) increased significantly for both groups, as did FMS scores (deep squat, hurdle step, inline lunge, shoulder mobility, active straight-leg raise, trunk-stability push-up, and rotary stability). These results suggest that Pilates exercise and yoga exercise might be likely effective in improving the performance of adult female fencers and injury prevention by increasing their dynamic balance ability and functional movement.

Biolayer-Interferometry-Guided Functionalization of Screen-Printed Graphene for Label-Free Electrochemical Virus Detection.

Additive manufacturing holds promise for rapid prototyping and low-cost production of biosensors for diverse pathogens. Among additive manufacturing methods, screen printing is particularly desirable for high-throughput production of sensing platforms. However, this technique needs to be combined with carefully formulated inks, rapid postprocessing, and selective functionalization to meet all requirements for high-performance biosensing applications. Here, we present screen-printed graphene electrodes that are processed with thermal annealing to achieve high surface area and electrical conductivity for sensitive biodetection via electrochemical impedance spectroscopy. As a proof-of-concept, this biosensing platform is utilized for electrochemical detection of SARS-CoV-2. To ensure reliable specificity in the presence of multiple variants, biolayer interferometry (BLI) is used as a label-free and dynamic screening method to identify optimal antibodies for concurrent affinity to the Spike S1 proteins of Delta, Omicron, and Wild Type SARS-CoV-2 variants while maintaining low affinity to competing pathogens such as Influenza H1N1. The BLI-identified antibodies are robustly bound to the graphene electrode surface via oxygen moieties that are introduced during the thermal annealing process. The resulting electrochemical immunosensors achieve superior metrics including rapid detection (55 s readout following 15 min of incubation), low limits of detection (approaching 500 ag/mL for the Omicron variant), and high selectivity toward multiple variants. Importantly, the sensors perform well on clinical saliva samples detecting as few as 103 copies/mL of SARS-CoV-2 Omicron, following CDC protocols. The combination of the screen-printed graphene sensing platform and effective antibody selection using BLI can be generalized to a wide range of point-of-care immunosensors.

Molecular Dynamic Simulation and 3d-pharmacophore Modeling of Alpha Mangostin and Its Derivatives against Estrogen Alpha Receptor

Background: Human estrogen receptor alpha (ERα), which is known to play a role in mediating cell proliferation, metastasis, and resistance to apoptosis, is one of the targets of breast cancer therapies. Alpha mangostin (AM) is an active xanthone compound from Garcinia mangostana L. which has activity as an ERα inhibitor. Objectives: This research aims to predict the pharmacokinetic and toxicity, and to study the molecular interactions of AM derivatives with the ERα using computer-aided simulation approaches through molecular docking, molecular dynamic, and pharmacophore screening to develop novel anti-breast cancer agents. Methods: Marvinsketch and Chimera programs were used to design and optimize the structure of AM and its derivatives. For screening the pharmacokinetic and toxicity profiles, the PreADMET web was used. The AutoDockTools 1.5.6 and LigandScout 4.4.3 Advanced software were used to conduct the molecular docking simulation and pharmacophore screening, respectively, while the molecular dynamic simulation was performed using AMBER 16. The results were visualized by Biovia Discovery Studio. Results: Molecular docking using Autodock showed that FAT10 derivate has lower binding free energy (ΔG) (-12.04 kcal/mol) than AM (-8.45 kcal/mol) when docking to ERα and both performed the same hydrogen bond with Thr347. These support the results of the MMPBSA calculation on dynamic simulation which shows FAT10 (-58.4767 kcal/mol) has lower ΔG than AM (-42.7041 kcal/mol) and 4-OHT (- 49.0821 kcal/mol). The pharmacophore screening results also showed that FAT10 fitted the pharmacophore with a fit score of 47.08. Conclusion: From the results, it can be suggested that FAT10 has promising activity as ERα antagonist. Further in vitro and in vivo experiments should be carried out to support these in silico studies.

Self Consistent Modeling of Relativistic Runaway Electron Beams Giving Rise to Terrestrial Gamma‐Rays Flashes

AbstractTerrestrial Gamma Ray Flashes (TGFs) are short bursts of gamma rays occurring during thunderstorms. They are believed to be produced by Relativistic Runaway Electron Avalanches (RREAs). In this paper, we present a new numerical model based on the Particle‐In‐Cell (PIC) method to simulate the interactions between the electromagnetic fields and the electron avalanche self‐consistently. The code uses a cylindrical Yee lattice to numerically solve the electromagnetic fields, a Monte Carlo approach to simulate collisions with air molecules, and a plasma fluid model to calculate the effects of low‐energy electrons and ions. The model is first tested through the reproduction of dispersion relations in a hot plasma. RREAs propagating under a homogeneous background electric field are then simulated. Owing to the self‐consistent nature of this description, we report here new physical properties such as saturation processes in the electron density and in the number of high‐energy electrons, detailed dynamical screening of the electric field in the ion trail of the avalanche, and the associated electric currents. We find that the saturation of RREAs is obtained when the numbers of high‐energy electrons and photons is consistent with those believed to be representative of TGF sources.

Gas–Liquid Two-Phase Flow Measurement Based on Optical Flow Method with Machine Learning Optimization Model

Gas–Liquid two-phase flows are a common flow in industrial production processes. Since these flows inherently consist of discrete phases, it is challenging to accurately measure the flow parameters. In this context, a novel approach is proposed that combines the pyramidal Lucas-Kanade (L–K) optical flow method with the Split Comparison (SC) model measurement method. In the proposed approach, videos of gas–liquid two-phase flows are captured using a camera, and optical flow data are acquired from the flow videos using the pyramid L–K optical flow detection method. To address the issue of data clutter in optical flow extraction, a dynamic median value screening method is introduced to optimize the corner point for optical flow calculations. Machine learning algorithms are employed for the prediction model, yielding high flow prediction accuracy in experimental tests. Results demonstrate that the gradient boosted regression (GBR) model is the most effective among the five preset models, and the optimized SC model significantly improves measurement accuracy compared to the GBR model, achieving an R2 value of 0.97, RMSE of 0.74 m3/h, MAE of 0.52 m3/h, and MAPE of 8.0%. This method offers a new approach for monitoring flows in industrial production processes such as oil and gas.

DP2 receptor activity sensor suited for antagonist screening and measurement of receptor dynamics in real-time

The DP2 receptor is a G-protein coupled receptor involved in allergic inflammation and is the target of recently developed antagonists already being tested in clinics. To get insights into DP2 receptor dynamics and to study its pharmacology on the level of the receptor, we constructed a fluorescence resonance energy transfer-based conformation sensor. The sensor reflects the selectivity profile of the DP2 receptor-wt and is suited for screening of agonists and antagonists due to its robust response. Furthermore, the sensor enables the direct measurement of DP2 receptor dynamics in real-time and revealed markedly distinct on- and off-rates of prostaglandin D2 between DP2 and DP1 receptors, suggesting a different mechanism of ligand receptor interaction.