Anomalous Features Research Articles

The fuzzy MAD stroke conjecture, using fuzzy C means to classify multimodal apparent diffusion for ischemic stroke lesion stratification

BackgroundIn conjunction with an epidemiologically determined treatment window, current radiological acute ischemic stroke practice discerns two lesion (stage) types: core (dead tissue, identified by diffusion-weighted imaging (DWI)) and penumbra (tissue region receiving just enough blood flow to be potentially salvageable, identified by the perfusion diffusion mismatch). However, advancements in preclinical and clinical studies have indicated that this approach may be too rigid, warranting a more fine-grained patient-tailored approach. This study aimed to demonstrate the ability to noninvasively provide insights into the current in vivo stroke lesion cascade. MethodsTo elucidate a finer-grained depiction of the acute focal ischemic stroke cascade in vivo, we retrospectively applied our multimodal apparent diffusion (MAD) method to multi-b-value DWI, up to a b-value of 10,000 s/mm2 in 34 patients with acute focal ischemic stroke. Fuzzy C Means was used to cluster the MAD parameters. ResultsWe discerned 18 clusters consistent with normal appearing tissue (NAT) types and 14 potential ischemic lesion (stage) types, providing insights into the variability and aggressiveness of lesion progression and current anomalous stroke-related imaging features. Of the 529 ischemic stroke lesion instances previously identified by two radiologists, 493 (92 %) were autonomously identified; 460 (87 %) were identified as efficaciously or better than the radiologists. ConclusionsThe data analyzed included a small number of clinical patients without follow-up or contemporaneous histology; therefor, the findings and theorizing should be treated as conjecture. Nevertheless, each identified NAT and lesion type is consistent with the known underpinnings of physiological tissues and pathological ischemic stroke lesion (stage) types. Several findings should be considered in current clinical imaging: WM fluid accumulation, BBB compromise conundrum, b1000 identified core may not be dead tissue, and a practical reason for DWI (pseudo) normalization.

The cross‐linguistic uses of proper names

AbstractA distinctive and widely recognized feature of proper names is that, unlike other words, names can be used across languages without modification. Yet, this feature of names—the prevalence and acceptability of their ‘cross‐linguistic’ uses—has been mostly overlooked within philosophy. This article highlights the theoretical importance of the cross‐linguistic uses of names in the debate concerning their syntax and semantics. It identifies an anomalous phonological feature of names in their cross‐linguistic uses and argues that the source of the anomaly is the widespread view that proper names are syntactically simple. It also argues that such uses provide evidence for the syntactic view that the phonological articulation of a name is mentioned and not used in the syntax—a view that is consistent with some but not all semantic views of names. By examining the hitherto overlooked cross‐linguistic uses of names, this article provides new evidence in favour of a certain variety of metalinguistic views concerning the syntax and semantics of names.

Theoretical Determination of Intensity of Satellite Structure of the Tungsten (W) Lα1, 2 X-Ray Spectrum

The tungsten Lα1,2 x-ray spectrum contains anomalous satellite feature Lα', thus receiving special attention. The theoretical attempt at determining the intensity of this feature is highly discrepant from the experimental result. This discrepancy has been the subject of much discussion. In the present work it has been shown theoretically that by extending the Bohm-Pines Hamiltonian and using many-body theory, satellite intensity thus obtained is in good agreement with the experiment; hence resolving the discrepancy.

Rectification of high-frequency artifacts in EIS data of three-electrode Li-ion cells

The use of a reference electrode and the analysis of Electrochemical Impedance Spectroscopy (EIS) data recorded in three-electrode configuration are beneficial for understanding the underlying electrochemical reaction mechanisms in Li-ion batteries. However, analysis of EIS data recorded both in two-electrode and especially three-electrode configurations is prone to misinterpretation due to presence of unidentified artifacts. Using the commercially available instrument (Biologic VMP3), EIS data is recorded simultaneously for both working and counter electrodes in three-electrode five-wire configuration and are algebraically summed to obtain the data for two-electrode configuration. This data is then compared to that recorded in two-electrode configuration. This arrangement of instrument helps in identifying the otherwise hidden and anomalous features, such as a high-frequency arc and extended solid electrolyte interphase (SEI) region, in the three-electrode configuration and the reason for their absence in the two-electrode configuration. Moreover, these additional features are found State-of-Charge (SoC) i.e., cell-electrochemistry dependent and can be highly influenced by the resistance of current/potential measuring leads. Additionally, a new methodology is established to rectify the EIS data and obtain ‘artifact-free’ electrochemical data.

The temperature evolution of the atomic structure and the influence of the local environment of atoms on the optical properties of the NA2SIF6 crystal

Crystals of sodium hexafluorosilicate Na2SiF6 millimeter size were grown by the hydrothermal method. According to X-ray diffraction analysis, it was revealed that Na2SiF6 samples are twinned according to the merohedral law and crystallize in sp. gr. P321 with unit cell parameters equal at 295 K a = 8.8582(12), c = 5.0396(11) Å, V = 342.47(17) Å3 on average the results of repeated measurements. A multi-temperature diffraction study of Na2SiF6 was carried out, based on the results of which the temperature dynamics of the optical properties of crystals was calculated. The structural similarity of Na2SiF6 crystals with crystals of the langasite family La3Ga5SiO14 was found. This made it possible to explain the optical activity of Na2SiF6 by considering electron density spirals similar to langasite, twisted around a triple axis of symmetry passing through the origin of the Na2SiF6 cell. The fractures in the temperature dependences of the refractive indices and rotation of the plane of polarization of light are explained by taking into account the anomalous features of interatomic interactions along the triple axis of the crystal cell passing through the Si2(2d) position with coordinates (1/3, 2/3, z). It was found that the main factor influencing the temperature dynamics of optical parameters is the Si2(2d)–F2(6g) distance, which increases abnormally with cooling.

Earthquake Magnitude Correlations Expose Short-Term Catalog Incompleteness

Abstract The independence of earthquake magnitudes is a fundamental assumption and limitation in earthquake forecasting. To assess its validity, we examine correlations between the magnitude of successive earthquakes. We first investigate the 2019 Ridgecrest foreshock sequence and find a significant magnitude correlation as well as an unusually low Gutenberg–Richter b-value (≈0.7 using moment magnitudes). We demonstrate that these anomalous features are not indicative of a precursory phase, but a consequence of short-term incompleteness (STI) that is not detected by conventional methods to estimate catalog completeness. Synthetic simulations of this sequence support this explanation: imposing STI leads to significant magnitude correlation and biased b-value estimates. Expanding our investigation to seismicity across southern California reveals pervasive magnitude correlation due to STI, not limited to sequences with large earthquakes. Our findings suggest that magnitude correlation is the most effective indicator of STI, rather than a characteristic of the underlying earthquake-generating process.

Inversion of downhole resistivity properties through infrared spectroscopy and whole‐rock geochemistry using machine‐learning

AbstractThe electrical properties of rocks are widely used in the geophysical exploration of natural resources, such as minerals, hydrocarbons and groundwater. In mining exploration, the primary goal is to map electrically anomalous geological features associated with different mineralization styles, such as clay alteration haloes, metal oxides and sulphides, weathered crystalline rocks or fractured zones. As such, the reconciliation of geophysical data with geological information (geochemistry, mineralogy, texture and lithology) is a critical step and can be performed based on petrophysical properties collected either on core samples or as downhole measurements. Based on data from 189 diamond drill cores collected for uranium exploration in the Athabasca Basin (Saskatchewan, Canada), this paper presents a case study of reconciliation of downhole resistivity probing with core sample geochemistry and short‐wave infrared spectroscopy (350–2500 nm) through three successive steps: (i) multivariate analysis of resistivity and other petrophysical properties (porosity, density) against geochemical and infrared spectroscopy information to characterize electrical properties of rocks with respect to other physical parameters, (ii) a machine‐learning workflow integrating geochemistry and spectral signatures in order to infer synthetic resistivity logs along with uncertainties. The best model in the basin was Light Gradient‐Boosting Machine with pairwise log‐ratio, which yielded a coefficient of determination R2 = 0.80 (root mean square error = 0.16), and in the basement, support vector regression with data fusion of infrared spectroscopy and pairwise log‐ratios on geochemistry yielded R2 = 0.82 (root mean square error = 0.35); (iii) the best model was then fitted on an area that was excluded from the original dataset (Getty Russell property) in order to infer synthetic resistivity logs for that zone. Software code is publicly available. This workflow can be re‐used for the valorization of legacy datasets.

Introduction of a modified anomalous vortex beam with self-focusing properties.

This study introduces and experimentally demonstrates the concept of a modified anomalous vortex beam (MAVB), which carries orbital angular momentum (OAM) and exhibits unique self-focusing properties. By utilizing holographic techniques and customizing phase masks, we precisely control the beam's phase and intensity distribution, enhancing self-focusing behavior while preserving traditional anomalous vortex beam features. We derive an analytical formula to describe MAVB propagation within a paraxial ABCD optical system. The self-focusing characteristics are influenced by initial parameters such as beam order, quantum number, beam waist, wavelength, and the modification parameter. Additionally, we simulate MAVB propagation and their OAM spectrum in maritime atmospheric turbulence. Through comprehensive theoretical analysis and experimental validation, we show how MAVBs achieve controlled self-focusing, leading to enhanced beam control and stability. Our study explores the mechanisms, design principles, and practical implications of MAVBs, emphasizing their potential to revolutionize optical applications.

Exotic spin-Hall effect in non-Hermitian optical systems

Abstract We systematically explore the origin and evolution of the exceptional points (EP) when a light beam is scattered by a parity-time (PT)-symmetric system using a scattering matrix approach and a full-wave theory. It is demonstrated that the PT-symmetric system switches between symmetry and symmetry-breaking phases at the EPs, giving rise to singular features in the Fresnel coefficients and causing the spin-Hall effect (SHE) near the EPs to exhibit anomalous features such as significantly enhanced transverse spin-Hall shifts and additional in-plane spin-Hall shifts. This exotic SHE can be explained by the significant beam intensity distortion caused by the destructive interference between the spin-maintained normal modes and the spin-reversed abnormal modes in the scattered light. This phenomenon can further be understood in terms of vortex mode decomposition, wherein it can be interpreted as the competition and superposition of three vortex modes with topological charges of −1, 0, and 1, respectively. These findings elucidate the mechanism of the unusual SHE around the EPs and offer potential avenues for EP-based sensing and structured light manipulation.

Adjacent Image Augmentation and Its Framework for Self-Supervised Learning in Anomaly Detection.

Anomaly detection has gained significant attention with the advancements in deep neural networks. Effective training requires both normal and anomalous data, but this often leads to a class imbalance, as anomalous data is scarce. Traditional augmentation methods struggle to maintain the correlation between anomalous patterns and their surroundings. To address this, we propose an adjacent augmentation technique that generates synthetic anomaly images, preserving object shapes while distorting contours to enhance correlation. Experimental results show that adjacent augmentation captures high-quality anomaly features, achieving superior AU-ROC and AU-PR scores compared to existing methods. Additionally, our technique produces synthetic normal images, aiding in learning detailed normal data features and reducing sensitivity to minor variations. Our framework considers all training images within a batch as positive pairs, pairing them with synthetic normal images as positive pairs and with synthetic anomaly images as negative pairs. This compensates for the lack of anomalous features and effectively distinguishes between normal and anomalous features, mitigating class imbalance. Using the ResNet50 network, our model achieved perfect AU-ROC and AU-PR scores of 100% in the bottle category of the MVTec-AD dataset. We are also investigating the relationship between anomalous pattern size and detection performance.

Limited arc magmatism and seismicity due to extensive mantle wedge serpentinization in the Makran subduction zone

Subduction processes usually involve extensive seismicity and create voluminous magmatic arcs by mantle wedge melting caused by dehydration of the subducting slab, but the Makran subduction zone has anomalously low seismicity and magmatism. Here we explain these anomalous features by 60–65% serpentinization in the peridotitic shallow mantle wedge based on our new integrated seismic, magnetic, gravity and isostatic model across the Makran subduction zone. The low-angle, slow Makran subduction provides ample time for the slab to release sufficient amounts of fluids for creating a large volume of rheologically weak serpentinite. This reduces seismicity by lowering the friction between the slab and surrounding rocks. Further, very little fluid is left in the slab when it reaches the melting depth, which explains the limited arc magmatism. Around 100 km depth, the subduction switches from low-angle to almost vertical. Our model demonstrates the combined effects of subduction rate and dip on mantle serpentinization with implication for assessment of seismic and volcanic hazards in subduction systems.

Towards more reliable photovoltaic energy conversion systems: A weakly-supervised learning perspective on anomaly detection

With the increasing popularity of photovoltaic (PV) systems, both academia and industry have been paying growing attention to fault prediction and health management. Although deep learning has achieved remarkable results in this field, the high cost of labeled data acquisition has become a bottleneck for its application. While unsupervised methods can reduce this cost, they fail to effectively utilize the prior knowledge of anomalous samples. To address this issue, this paper innovatively proposes a weakly-supervised anomaly detection network based on feature map conversion and hypersphere transformation (FMC-HT). Firstly, PV electroluminescence (EL) images are input into the feature extraction layer based on feature map conversion, which can reduce redundancy, enhance information density, and achieve efficient feature extraction through feature map conversion. Subsequently, inverse squared norm loss is set to utilize the knowledge of unlabeled sample features and labeled anomalous sample features, and backpropagation is performed separately to train the hypersphere transformation network, ultimately achieving effective distinction between normal and anomalous samples. On real PV EL datasets, this model exhibits impressive performance and remains stable under different prior knowledge and anomaly rates. This study not only provides a new solution for anomaly detection in PV systems but also expands new directions for the application of deep learning in scenarios with limited labeled data.

Retracted] MicroRNA‑30e inhibits adhesion, migration, invasion and cell cycle progression of prostate cancer cells via inhibition of the activation of the MAPK signaling pathway by downregulating CHRM3.

Following the publication of the above article, a concerned reader drew to the Editor's attention that certain of the Transwell invasion assay data shown in Fig. 7B on p. 451 were strikingly similar to data that had appeared in Fig. 3D in a previously published paper written by different authors at a different research institute, which had been received at the journal Cancer Letters at around the same time, and which has subsequently been retracted [Gu J, Wang Y, Wang X, Zhou D, Shao C, Zhou M and He Z: Downregulation of lncRNA GAS5 confers tamoxifen resistance by activating miR‑222 in breast cancer. Cancer Lett 434: 1‑10, 2018]. In addition, there were potentially anomalous features associated with the western blot and cell cycle data in this paper. In view of the fact that certain of the data in the above article were also submitted to a different journal within the space of a few days, the Editor of International Journal of Oncology has decided that this paper should be retracted from the publication. The authors were asked for an explanation to account for these concerns, but the Editorial Office did not receive a reply. The Editor apologizes to the readership for any inconvenience caused. [International Journal of Oncology 54: 443‑454, 2019; DOI: 10.3892/ijo.2018.4647].

Complex system anomaly detection via learnable temporal-spatial graph with degradation tendency segmentation

To guarantee the safety and reliability of equipment operation, such as liquid rocket engine (LRE), carrying out system-level anomaly detection (AD) is crucial. However, current methods ignore the prior knowledge of mechanical system itself, and seldom unite the observations with the inherent relation in data tightly. Meanwhile, they neglect the weakness and nonindependence of system-level anomaly which is different from component fault. To overcome above limitations, we propose a separate reconstruction framework using worsened tendency for system-level AD. To prevent anomalous feature being attenuated, we first propose to divide single sample into two equal-length parts along the temporal dimension. And we maximize the mean maximum discrepancy (MMD) between feature segments to force encoders to learn normal features with different distributions. Then, to fully explore the multivariate time series, we model temporal-spatial dependence by temporal convolution and graph attention. Besides, a joint graph learning strategy is proposed to handle prior knowledge and data characteristics simultaneously. Finally, the proposed method is evaluated on two real multi-sensor datasets from LRE and the results demonstrate the effectiveness and potential of the proposed method on system-level AD.

Effects of Stray Magnetic Field on Transition-Edge Sensors in Gamma-Ray Microcalorimeters

Superconducting transition-edge sensors (TESs) used in X-ray and γ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\gamma$$\\end{document}-ray microcalorimeters suffer degraded performance if cooled in a magnetic field B sufficient to trap flux in the sensors. We report measurements of γ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\gamma$$\\end{document}-ray TESs before and after implementing measures to reduce stray B fields from sources inside and outside the cryostat. These measurements showed a correlation between anomalous features in TES current–voltage (IV) curves and degraded energy resolution. After reducing internal sources of stray B field and improving shielding against external sources, both IV curves and energy resolution improved. Finally, we placed magnetized screws with remnant fields ∼\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\sim$$\\end{document} 10 μT\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\upmu \ extrm{T}$$\\end{document} near similar γ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\gamma$$\\end{document}-ray TESs in a different type of detector package and observed the same effects.

Prevalence of sacral spina bifida occulta with lumbosacral transitional vertebra in a skeletal collection of a South African population

In this study, complete Sacral Spina Bifida Occulta (SSBO) and Lumbosacral Transitional Vertebrae (LSTV) with their various subtypes based on the Castellvi classification were appraised in a South African population sample. Adult human skeletons representing the three largest South African population groups, namely South African African, South African of Mixed Ancestry; South African of European descent; both biological sexes; and age range between 21 and 90 years at death were evaluated for both spinal anomalies.The number of preselected skeletons (n = 1798) from the largest collection in Africa of modern human skeletons (N = 2630) provided a strong representative South African sample. The observational study looked at lumbar and sacral vertebrae in each skeleton and any anomalous features were captured in an Excel spreadsheet.Complete SSBO with no LSTV was observed in eight subjects (8/1798; 0.44 %), while incomplete SSBO was observed in one subject (1/1798; 0.06 %), and one individual (1/1798; 0.06 %) exhibiting complete SSBO with LSTV (Type IIIB, Castellvi classification). No significant differences were observed when comparing the prevalence of the LSTV with SSBO in the male and female groups of the different population affinity groups. The number of individuals with SSBO was found in more South African Africans than in the other population groups with no significant difference between groups.This research revealed the simultaneous presence of two morphological anomalies (SSBO and LSTV) at the same vertebral segment that could result in low back pain. Variant morphology awareness is crucial for clinicians across all modalities to prevent misdiagnosis, leading to better treatment plans, and avoiding injury.

Semantic Coarse-to-Fine Granularity Learning for Two-Stage Few-Shot Anomaly Detection

Anomaly detection is critical in industrial inspection, where identifying defects significantly impacts product quality and safety. Existing models, primarily based on convolutional neural networks (CNNs), struggle with noise sensitivity and insufficient resolution for fine-grained feature discrimination. To address these issues, we propose a two-stage few-shot anomaly detection network that enhances semantic feature granularity and generalization. The network includes a coarse-grained anomaly detection module, a multi-scale channel attention module, and a fine-grained detection module. The coarse-grained module identifies abnormal regions, serving as the initial filter. The multi-scale channel attention module focuses on anomalous features, enhancing sensitivity to fine-grained characteristics. This step overcomes limitations in discerning subtle yet critical anomalies. The fine-grained detection module refines feature maps, enhancing generalization. Experimental results on the MVTec dataset show an image-level Area under the region of convergence (AUROC) of 92.3% and a pixel-level AUROC of 95.3%, a 1% to 2% improvement over leading FSAD methods.

Anomalous Characteristics of Water Vapor Budget on the Tibetan Plateau under the Influence of Tropical Cyclones over the Bay of Bengal during Early Summer

Abstract Early summer is a peak time for tropical cyclone (TC) activities over the Bay of Bengal (BoB) and a period of South Asian monsoon onset, and the TCs during this time have a significant impact on the water vapor transport associated with monsoons. This study investigates the anomalous characteristics of the dynamic–thermal atmospheric circulation structure and water vapor budget over the Tibetan Plateau (TP) under the influence of BoB TCs generated in May from 1979 to 2020 with JTWC best track data and ERA5 data. Results reveal that a significant southerly water vapor channel forms from the BoB to the southeastern TP with a water vapor convergence near the Yarlung Zangbo Grand Canyon. A part of the water vapor is transported directly to the TP by deep southerly jet, while the other part is lifted by TCs and then climbs upward to the TP by two uplift processes occurring on the southern slope of the TP and over the TP respectively, which makes the whole troposphere over the southeastern TP warmer and wetter. It is found that anomalous southeasterly airflow in the northeast of TC circulation turns to anomalous southwesterly airflow forming an abnormal anticyclonic circulation over the southern TP in the middle and upper troposphere due to the diabatic heating effect. In this process, the TP acts as an anomalous water vapor sink with remarkable water vapor inflow through its southern boundary, with the main water vapor outflow through the eastern boundary, but a weak easterly water vapor backflow to the eastern TP in the lower troposphere. Significance Statement This study attempts to investigate the anomalous features of the water vapor budget over the Tibetan Plateau (TP) under the influence of the Bay of Bengal (BoB) tropical cyclones (TCs) during early summer. Results show that a significant southerly water vapor channel forms from the BoB to the southeastern TP with a water vapor convergence near the Yarlung Zangbo Grand Canyon. The TP acts as an anomalous water vapor sink with more and higher water vapor inflows through the southern boundary of the TP. A positive temperature and humidity anomaly can be found over the southeastern TP extending upward into the middle and upper troposphere. The results are helpful to understand how the BoB TCs affect the weather process over the TP.

Nonlinear phenomena in charge transport properties of a hole-doped organic spin-liquid compound

The nonlinear electric conductivity of κ-(BEDT-TTF)4Hg2.89Br8, which is known as a hole-doped spin liquid, has been observed by single crystal transport measurements using dc and ac excitations. This compound is known as a charge transfer complex with strong magnetic fluctuations accompanied by electron mass enhancement at ambient pressure. We discuss the nonlinear dc conductivity drastically emerging below 100 K. We also performed ac impedance measurements of this compound and compared the results with those of a typical dimer-Mott compound of deuterated κ-(d8-BEDT-TTF)2Cu[N(CN)2]Br, located just near the Mott boundary. The analyses of the Nyquist plots of κ-(d8-BEDT-TTF)2Cu[N(CN)2]Br and κ-(BEDT-TTF)4Hg2.89Br8 reveal qualitatively different features. The former shows a behavior pertinent to the inhomogeneous distribution of domains due to a mixing of metal and insulating phases, taking into account the influence of the proximity effect, while the doped spin liquid has a distinct semicircle-type frequency dependence in its Nyquist plot in the whole temperature range studied. We conclude that the nonlinear conductivity is intrinsically peculiar to the doped dimer Mott system, where the charge degrees of freedom dominate the itinerancy. We attribute the anomalous features, such as non-Fermi liquid behavior, heat capacity enhancement, and strong antiferromagnetic fluctuations in κ-(BEDT-TTF)4Hg2.89Br8, to a kind of charge confinement effect retained in the hole-doped spin-liquid state.

OGLE-2023-BLG-0836L: The sixth microlensing planet in a binary stellar system

Aims. Light curves of microlensing events occasionally deviate from the smooth and symmetric form of a single-lens single-source event. While most of these anomalous events can be accounted for by employing a binary-lens single-source (2L 1S) or a single-lens binary-source (1L2S) framework, it is established that a small fraction of events remain unexplained by either of these interpretations. We carried out a project in which data collected by high-cadence microlensing surveys were reinvestigated with the aim of uncovering the nature of anomalous lensing events with no proposed 2L 1S or 1L 2S models. Methods. From the project we found that the anomaly appearing in the lensing event OGLE-2023-BLG-0836 cannot be explained by the usual interpretations, and we conducted a comprehensive analysis of the event. From thorough modeling of the light curve under sophisticated lens-system configurations, we arrived at the conclusion that a triple-mass lens system is imperative to account for the anomalous features observed in the lensing light curve. Results. From the Bayesian analysis using the measured observables of the event timescale and angular Einstein radius, we determined that the least massive component of the lens has a planetary mass of 4.36−2.18+2.35 MJ. This planet orbits within a stellar binary system composed of two stars with masses 0.71−0.36+0.38 M⊙ and 0.56−0.28+0.30 M⊙. This lensing event signifies the sixth occurrence of a planetary microlensing system in which a planet belongs to a stellar binary system.