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The increasing volume of suspicious emails, commonly known as spam, has created a critical need for more reliable and robust anti-spam filters. These suspicious emails can be dangerous and can lead to the loss of personal information, underscoring the necessity for an effective spam filtering system. The application of machine learning methods has enhanced system security and improved the detection of suspicious messages. This research evaluates the effectiveness of seven machine learning algorithms for classifying suspicious email messages: random forest, support vector machine, artificial neural network, decision tree, gradient boosting classifier, and k-nearest neighbor. The primary focus of this evaluation is the accuracy achieved by each algorithm in identifying spam emails. Our analysis revealed that the random forest algorithm outperformed the other evaluated algorithms in terms of accuracy for spam email classification, achieving a remarkable 95%. The accuracy percentages of the various methods ranged from 88% to 93%. Copyright 2025. The Korean Institute of Information Scientists and Engineers.

Measurements of the variation of anisotropic flow-plane angles (Ψn) with rapidity, commonly known as the flow-plane decorrelation, provide important insights into the initial conditions of the matter produced in heavyion collisions. In this paper, using data collected by the STAR experiment, we report the first measurement of the four-plane correlator observable (Formula presented.), where superscripts a, b, c, and d denote sequential pseudorapidity (η) regions with a corresponding to the most backward region, b and c close to midrapidity with nb < 0 and nc > 0, and d being the most forward. The measurement is performed for the elliptic and triangular flow (i.e., n = 2 and 3) in Au + Au and isobar (Ru + Ru, Zr + Zr) collisions at (Formula presented.) = 200 GeV. The goal of calculating the correlation of the flow-plane angle variations from backward to midcentral, and from midcentral to forward regions, is to probe the systematic variation of flow angle over a wide П range. In midcentral collisions (10-30 % centrality), we find T2{ba; dc} = —0.004 ± 0.001 (stat) ± 0.002(syst) independent of the collision system. Such a small value of T2 favors a “random-walk” variation of the flow-plane angles, where the rapidity correlation length is smaller than the entire region under study. These measurements provide new information on the decorrelation patterns in the system and offer a quantitative estimate of possible systematic variations in anisotropic flow angles such as “twist” between forward and backward regions. This opens new opportunities for understanding the three-dimensional structure and the time evolution of the quarkgluon plasma created in heavy-ion collisions. © 2026 American Physical Society

The correlation between the mean transverse momentum, [p T], and the squared anisotropic flow, vn2, on an event-by-event basis has been suggested to be influenced by the initial conditions in heavy-ion collisions. We present measurements of the variances and covariance of [p T] and vn2, along with their dimensionless ratio, for Au+Au collisions at various beam energies: sNN = 14.6, 19.6, 27, 54.4, and 200 GeV. Our measurements reveal a distinct energy-dependent behavior in the variances and covariances. In addition, the dimensionless ratio displays a similar behavior across different beam energies. We compare our measurements with hydrodynamic models and similar measurements from Pb+Pb collisions at the Large Hadron Collider (LHC). These findings provide valuable insights into the beam energy dependence of the specific shear viscosity (η / s) and initial-state effects, allowing for differentiating between different initial-state models. © 2026 The Authors.

Traditional physical biometrics - such as fingerprints, facial recognition, and iris scans - have long been utilized for user identification in areas like border control, military operations, law enforcement, and public safety. However, the rise of smartphone technology has introduced new avenues for security research. One emerging area is behavioral biometrics, particularly the use of touchscreen interaction data as a more accessible and user-friendly identification method. In this context, our study focuses on a novel form of touchscreen input: capacitive swipe gestures for user identification. We compiled a comprehensive dataset of capacitive swipe gestures collected over multiple sessions from 30 participants. To evaluate this modality, we conducted thorough experiments using established machine learning algorithms, including Support Vector Machine, Random Forest, and XGBoost. Additionally, we developed a new preprocessing algorithm tailored for capacitive swipe data. Our findings reveal that this algorithm significantly enhances identification performance compared to existing methods. Overall, our results highlight the strong potential of capacitive swipe gestures as a viable biometric modality for user identification. © 2025 IEEE.

Philosophers have long speculated that individual differences in temperament influence philosophical thinking, yet empirical research has rarely explored the role of neurodivergent traits in this domain. In this large online study (N = 1,254), we investigated whether participants with training in philosophy differ from the general population when it comes to six psychological traits–autism, ADHD, aphantasia, anendophasia, anauralia, and representational manipulation–and also whether these traits correlate with responses to two widely studied philosophical thought experiments: the “trolley problem” and the “rollback deterministic universe.” Compared to the general population, participants with training in philosophy had higher scores on measures of ADHD, internal verbalization, and representational manipulation, but lower scores on measures of visual imagery. These cognitive traits were also correlated with participants’ moral and metaphysical judgments (independent of their level of philosophical training)–e.g. participants who scored higher in visualization were less likely to judge that hitting the switch in the trolley problem is permissible but not obligatory, and also less likely to attribute free will and moral responsibility to agents in the rollback universe. Finally, we employed machine learning to develop predictive models that classify a randomly selected participant as either a philosopher or a non-philosopher. Models trained solely on responses to measures for neurodivergent traits achieved better performance than models trained solely on responses to philosophical thought experiments. This suggests that stable, trait-level neurodivergent characteristics may be more diagnostic of philosophical interest, aptitude, or training than judgments philosophers make on domain-relevant problems. © 2026 Informa UK Limited, trading as Taylor & Francis Group.

Learn to make friends and stop scaring people away with this clever book inspired by the hit manga Komi Can’t Communicate.Do you find it hard to sp...

Abelisauridae were medium to large-bodied carnivorous dinosaurs with short, ornamented skulls, poorly recurved ziphodont teeth, and reduced forelimbs. They were the dominant terrestrial carnivores in many Gondwanan ecosystems during the Cretaceous. Their Jurassic origin, primarily based on the putative abelisaurid Eoabelisaurus from the Early Jurassic of Patagonia, remains debated, with many authors considering Abelisauridae as a strictly Cretaceous theropod radiation. Here, we describe several historically and stratigraphically important isolated theropod teeth from Gondwana, identified as belonging to abelisaurids using new cladistic and machine learning methods. Dental evolution in Abelisauridae was additionally explored using an updated version of a dentition-based data matrix focused on ceratosaurs. Results of this study show that the evolution of the dentition in abelisaurids was marked by a decrease in size of the mesialmost dentary teeth and the displacement of the tallest crowns towards the middle part of the maxilla. Two isolated abelisaurid teeth from the Late Cretaceous of India and Patagonia were also identified as the earliest published record of a non-avian theropod in Asia and an abelisaurid in Argentina, respectively. More importantly, isolated theropod teeth confidently referred to Abelisauridae from the Middle Jurassic of Madagascar provide additional support for the emergence of this clade in Gondwana before the Late Jurassic and reveal that the acquisition of abelisaurid dental traits occurred early in the evolutionary history of one of the most successful radiations of non-avian theropods from Europe and the Southern Hemisphere. © 2025 Asociación Paleontológica Argentina (APA)

Tomato plant diseases pose a significant threat to agricultural productivity, resulting in substantial economic losses. Early and accurate diagnosis is crucial for effective disease management. This paper describes the design and implementation of expert systems for tomato disease detection using the CLIPS (C Language Integrated Production System) platform. The tool is designed to help farmers and agronomists accurately identify diseases affecting tomato crops by simulating knowledge from professional experts. We carefully developed a set of rules to distinguish leaf blight symptoms from those of other tomato diseases and provided recommendations to minimize crop losses and maximize yields. The expert system was developed using a forward-chaining inference engine, and its performance was evaluated through a set of real-world test cases, demonstrating a high level of accuracy and consistency in decision-making. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.

With the increasing interest in natural language processing, text summarization has become essential for condensing large volumes of data into concise and meaningful summaries. Extractive summarization, which involves selecting key sentences based on textual features, has gained attention due to its efficiency and effectiveness. This research explores extractive summarization using multiple machine learning classifiers, including Support Vector Machines (SVM), Logistic Regression (LR), Decision Trees (DT), K-Nearest Neighbors (KNN), and Random Forest (RF). Our findings indicate that the Random Forest model achieved the highest accuracy, reaching 80% in classifying sentences for summary generation. Additionally, we evaluated text classification on the same BBC dataset using ChatGPT, which attained an accuracy of 62%. Furthermore, comparisons with results from prior research confirm the competitive performance of our approach, reinforcing the potential of machine learning models in extractive summarization. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.

High-energy, heavy-ion collisions can create local domains of chirality-imbalanced quarks, reflecting the topological features of quantum chromodynamics. The chiral magnetic effect (CME) predicts an electric charge separation of quarks in such topological domains along the magnetic field (B) generated by the passing of two high-Z nuclei. We use a correlation observable Δγ112 between charged meson pairs to detect the CME-induced charge separation and a novel event shape selection (ESS) method to mitigate the background effects related to elliptic flow (v2). The ESS method classifies events based on the emission pattern of final-state particles and determines Δγ(Formula presented) from the zero-flow limit. We reconstruct the B field direction from the spectator nucleons, which minimizes backgrounds unrelated to the collective motion of the system. In this work, we report the measurements of Δγ112 and a background indicator Δγ132 in Au + Au collisions from the Brookhaven National Laboratory Relativistic Heavy Ion Collider (RHIC) Beam Energy Scan phase II and at the top RHIC energy. After background suppression, Δγ(Formula presented) aligns with zero, and Δγ(Formula presented) is reduced to no more than 20% of Δγ112. We observe a finite residual charge separation with 2.5σ, 3σ, and 3.2σ significance in the 20-50% centrality range of Au + Au collisions at 11.5, 14.6, and 19.6 GeV. The results at 17.3 and 27 GeV also show positive values but with a lower significance of 1.3σ and 1.1σ, respectively. The corresponding ΔγΈ5ΕΕ values at 7.7, 9.2, and 200 GeV are consistent with zero within uncertainties. © (2026), (American Physical Society). All right reserved.

Rapidity-odd directed flow v 1 measurements are presented for K ± and KS0 in Au + Au collisions for sNN from 3.0 to 3.9 GeV with the STAR experiment. For comparison, v 1 of π ± , protons, and Λ from the same collisions are also discussed. The mid-rapidity v 1 slope dv1/dy|y=0 for protons and Λ is positive in these collisions. On the other hand, v 1 slope of kaons exhibits a strong pT dependence: negative at pT< 0.6 GeV/ c and positive at higher pT. A similar pT dependence is also evident for the v 1 slope of charged pions. Compared to the spectator-removed calculations in Au+Au collisions at sNN= 3.0–3.9 GeV, the JAM model demonstrates a pronounced shift of the v 1 slopes of mesons towards the negative direction. It suggests that the shadowing effect of the spectators plays an important role in the observed kaon anti-flow at low pT in the high baryon density region of non-central collisions. © 2026 The Authors.

We use SrTiO3/Si as a model system to elucidate the effect of the interface on ferroelectric behavior in epitaxial oxide films on silicon. Using both first-principles computations and synchrotron x-ray diffraction measurements, we show that structurally imposed boundary conditions at the interface stabilize a fixed (pinned) polarization in the film but inhibit ferroelectric switching. We demonstrate that the interface chemistry responsible for these phenomena is general to epitaxial silicon-oxide interfaces, impacting on the design of silicon-based functional oxide devices. © 2026 by World Scientific Publishing Co. Pte. Ltd.

Abstract NASA’s TESS mission has unveiled a plethora of eclipsing binaries (EBs), among them hundreds of triples and higher-order, hierarchical systems. These complex targets require follow-up observations to enable full characterization of system architectures and identify the most compact multiples expected to undergo the most dramatic dynamical evolution. We report first results from a long-term effort to perform such follow-up, focusing here on multiband speckle imaging of a majority (57) of the sample of 97 quadruple- and higher-order eclipsing binaries (Q+EBs) identified via TESS light curves by V. B. Kostov et al. Diffraction-limited imaging with the Differential Speckle Survey Instrument on the Astrophysical Research Consortium 3.5 m telescope and HRCam on the Southern Astrophysical Research 4.1 m telescope reveals nearly 60% of the 57 to resolve into two sources separated by ≥0 <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mover accent="true"> <mml:mi>.</mml:mi> <mml:mi>″</mml:mi> </mml:mover> </mml:math> 03. For these partly resolved systems, we report derived characteristics (e.g., relative position angle, angular separation, and magnitude differences in multiple passbands) from the speckle imaging. We find those Q+EBs partly resolved with 4 m class telescopes to have significantly inflated Gaia parallax errors and large Gaia renormalized unit weight errors, particularly for systems with separations comparable to Gaia’s resolution limit (∼0 <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mover accent="true"> <mml:mi>.</mml:mi> <mml:mi>″</mml:mi> </mml:mover> </mml:math> 6). For unresolved systems we report upper limits on angular and linear projected separations. We find two partly resolved Q+EBs with wide linear separations having eclipse timing variations that are therefore candidates of higher-than-quadruple multiplicity. Finally, we demonstrate how speckle imaging of resolved Q+EBs during an eclipse can clarify which speckle-resolved Q+EB subsystem is associated with a particular set of TESS eclipses.