Rare events are occurrences that take place with a significantly lower frequency than more common, regular events. These events can be categorized into distinct categories, from frequently rare to extremely rare, based on factors like the distributio...
Hellinger distance has been widely used to derive objective functions that are alternatives to maximum likelihood methods. While the asymptotic distributions of these estimators have been well investigated, the probabilities of rare events induced by...
We report on the development of scintillating bolometers based on lithium molybdate crystals that contain molybdenum that has depleted into the double-
A good deal of molecular dynamics simulations aims at predicting and quantifying rare events, such as the folding of a protein or a phase transition. Simulating rare events is often prohibitive, especially if the equations of motion are high-dimensio...
Rare, but important, transition events between long-lived states are a key feature of many molecular systems. In many cases, the computation of rare event statistics by direct molecular dynamics (MD) simulations is infeasible, even on the most powerf...
Background: Many rare events meta-analyses of randomized controlled trials (RCTs) have lower statistical power, and real-world evidence (RWE) is becoming widely recognized as a valuable source of evidence. The purpose of this study is to investigate...
Immune checkpoint inhibitors (ICIs) have been approved for the treatment of many cancers, either in adjuvant or metastatic settings. Regarding safety, endocrine adverse events (AEs) are some of the most common AEs in ICI-treated patients, with thyroi...
Classical binomial interval methods often exhibit poor performance when applied to extreme conditions, such as rare-event scenarios or small-sample estimations. Recent frequentist and Bayesian approaches have improved coverage in small samples and ra...
Statistical distributions play a crucial role in water resources management and civil engineering, particularly for analyzing data variability and predicting rare events with extremely long return periods (e.g., T = 1000 years, T = 10,000 years). Amo...
This paper addresses the cold-start problem and rare event prediction challenges in Olympic medal forecasting by proposing a predictive framework that integrates multi-granularity transfer learning with extreme value theory. The framework comprises t...
With the growing robustness of modern power systems, the occurrence of load curtailment events is becoming lower. Hence, the simulation of these events constitutes a challenge in adequacy indices assessment. Due to the rarity of the load curtailment...
Background: Tuberculosis (TB) can seriously affect the hematopoietic system, with involvement of both myeloid and lymphoid cell lines as well as plasma components. These hematological changes act as a marker for the diagnosis, prognosis and response...
Amyloid fibrils are thought to grow by a two-step dock-lock mechanism. However, previous simulations of fibril formation (i) overlook the bi-molecular nature of the docking step and obtain rates with first-order units, or (ii) superimpose the docked...
This study develops a chance–constrained open–loop optimal control (CC–OC) framework capable of handling rare event probabilities. Therefore, the framework uses the generalized polynomial chaos (gPC) method to calculate the probabil...
Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.) is a fast-growing conifer with great forestation value and prefers outcrossing with high inbreeding depression effect. Previously, we captured a special Chinese fir parent clone named as ‘cx56...
A rare event of mixed biomass-burning and polluted dust aerosols was observed over Athens, Greece (37.9° N, 23.6° E), during 21–26 May 2014. This event was studied using a synergy of a 6-wavelength elastic-Raman-depolarization lidar mea...
The paraneoplastic syndrome referred in the literature as non-islet-cell tumor hypoglycemia (NICTH) and extra-pancreatic tumor hypoglycemia (EPTH) was first reported almost a century ago, and the role of cancer-secreted IGF-II in causing this blood g...
Public key infrastructures (PKIs) are the cornerstone for the security of the communication layer of online services relying on certificate-based authentication, such as e-commerce, e-government, online banking, cloud services, and many others. A PKI...
Central among the tools and approaches used for ligand discovery and design are Molecular Dynamics (MD) simulations, which follow the dynamic changes in molecular structure in response to the environmental condition, interactions with other proteins,...
Stock trading has tremendous importance not just as a profession but also as an income source for individuals. Many investment account holders use the appreciation of their portfolio (as a combination of stocks or indexes) as income for their retirem...
This paper uses the Extreme Value Theory (EVT) to model the rare events that appear as delivery delays in road transport. Transport delivery delays occur stochastically. Therefore, modeling such events should be done using appropriate tools due to th...
This paper shows that one cannot learn the probability of rare events without imposing further structural assumptions. The event of interest is that of obtaining an outcome outside the coverage of an i.i.d. sample from a discrete distribution. The pr...
Mycosis fungoides and nodal classic Hodgkin lymphoma (cHL) have been reported to occur concurrently or sequentially in the same patient. A long-lasting mycosis fungoides more often precedes the onset of nodal cHL, although few cases of nodal cHL foll...
Fault detection and diagnosis is one of the most critical components of preventing accidents and ensuring the system safety of industrial processes. In this paper, we propose an integrated learning approach for jointly achieving fault detection and f...
Probabilistic prediction models exist to reduce surprise about future events. This paper explores the evaluation of such forecasts when the event of interest is rare. We review how the family of Brier-type scores may be ill-suited to evaluate predict...
Manufacturers are struggling to use data from multiple products production lines to predict rare events. Improving the quality of training data is a common way to improve the performance of algorithms. However, there is little research about how to s...
Meta-analysis aggregates information across related studies to provide more reliable statistical inference and has been a vital tool for assessing the safety and efficacy of many high-profile pharmaceutical products. A key challenge in conducting a m...
We propose the Hybrid Spatio-Temporal Transformer with Multi-Branch CNN/RNN and Extreme-Event Head (HST–MB–CREH), a hybrid spatio-temporal deep learning architecture for joint short-term photovoltaic (PV) power forecasting and the detecti...
Inorganic crystal scintillators play a crucial role in particle detection for various applications in fundamental physics and applied science. The use of such materials as scintillating bolometers, which operate at temperatures as low as 10 mK and de...
Festuca and Lolium grass species are used for Festulolium hybrid variety production where they display trait complementarities. However, at the genome level, they show antagonisms and a broad scale of rearrangements. A rare case of an unstable hybrid...
The Scintillating Bubble Chamber (SBC) collaboration is developing liquid-noble bubble chambers for the detection of sub-keV nuclear recoils. These detectors benefit from the electron recoil rejection inherent in moderately-superheated bubble chamber...
Background and Clinical Significance: Zoledronic acid (ZA) is a widely used bisphosphonate for the prevention of skeletal-related events in patients with metastatic bone disease. While it is generally well tolerated, rare immune-mediated complication...
Tornado occurrence and detection are well established in mesoscale meteorology, yet the application of deep learning (DL) to radar-based tornado detection remains nascent and under-validated. This study benchmarks DL approaches on TorNet, a curated d...
The ability to characterize and predict extreme events is a vital topic in fields ranging from finance to ocean engineering. Typically, the most-extreme events are also the most-rare, and it is this property that makes data collection and direct simu...
Rhabdomyolysis is caused by extensive damage to skeletal muscles resulting in elevated creatine phosphokinase (CPK), Lactate dehydrogenase (LDH), and aspartate aminotransferase (AST), leading to life-threatening consequences like acute renal failure,...
Longitudinal data is encountered frequently in many healthcare research areas to include the critical care environment. Repeated measures from the same subject are expected to correlate with each other. Models with binary outcomes are commonly used i...
Forecasting stock market crashes is difficult because such events are rare, highly nonlinear, and shaped by latent structural and behavioral forces. This study introduces a calibrated and interpretable Random Forest framework for detecting pre-crash...
Coincidences are rare unexpected events that can fascinate, but their typical post hoc discovery and haphazard nature also have the potential to confuse and to confound correct scientific analysis. Mathematically, they can sometimes be modeled by bir...
This study investigates the use of adaptive cluster sampling (ACS) for estimating bark stripping damage in forests, employing the Hansen–Hurwitz (HH) and Horvitz–Thompson (HT) estimators. Through simulations, we analysed the total, summer...
Copy number variations (CNV) of the RET gene have been described in 30% of Medullary Thyroid Cancer (MTC), but no information is available about their role in this tumor. This study was designed to clarify RET gene CNV prevalence and their potential...
The geochemical composition of rare earth elements (REE) in the bottom sediments of two Dominican reservoirs and in soils from their catchments was studied to identify possible sources of the deposited materials. Knowledge of the origin of the sedime...
Bugs, especially those in concurrent systems, are often hard to reproduce because they manifest only under rare conditions. Testers frequently encounter failures that occur only under specific inputs, often at low probability. We propose an approach...
The presence of adipocytes within thyroid glands is a rare finding seen in thyrolipoma, diffuse lipomatosis, or thyroid teratoma. Although some cases present with multinodular goiter or autoimmune thyroiditis, the exact cause has not yet been elucida...
Down syndrome (DS) is the most common chromosome abnormality with a unique cancer predisposition syndrome pattern: a higher risk to develop acute leukemia and a lower incidence of solid tumors. In particular, brain tumors are rarely reported in the D...
Turnovers in the National Football League (NFL) occur whenever a team loses possession of the ball due to a fumble, or an interception. Turnovers disrupt momentum of the offensive team, and represent lost opportunities to advance downfield and score....
Searching for neutrinoless double beta decay is a top priority in particle and astroparticle physics, being the most sensitive test of lepton number violation and the only suitable process to probe the Majorana nature of neutrinos. In order to increa...
We consider the problem of estimating tail probabilities of random sums of scale mixture of phase-type distributions—a class of distributions corresponding to random variables which can be represented as a product of a non-negative but otherwis...
Parallel cascade selection molecular dynamics (PaCS-MD) is a rare-event sampling method that generates transition pathways between a reactant and product. To sample the transition pathways, PaCS-MD repeats short-time MD simulations from important con...
The WRF-Solar Ensemble Prediction System (WRF-Solar EPS) and a calibration method, the analog ensemble (AnEn), are used to generate calibrated gridded ensemble forecasts of solar irradiance over the contiguous United States (CONUS). Global horizontal...
A boosting-based machine learning algorithm is presented to model a binary response with large imbalance, i.e., a rare event. The new method (i) reduces the prediction error of the rare class, and (ii) approximates an econometric model that allows in...
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