Abstract: The accuracy of dynamics parameters in the transmission system is essential for high-performance motion trajectory planning and stable operation of heavy-duty ser-vo presses. To mitigate the performance degradation and potential overload risks caused by deviations between theoretical and actual parameters, this paper proposes a dynamics model accuracy enhancement method that integrates multi-objective global sensitivity analysis and ant colony optimization-based calibration. First, a nonlinear dynamics model of the eight-bar mechanism was constructed based on Lagrange's equations, which systematically incorporates generalized external force models con-sistent with actual production, including gravity, friction, balance force, and stamping process load. Subsequently, six key sensitive parameters were identified from 28 sys-tem parameters using Sobol global sensitivity analysis, with response functions defined for torque prediction accuracy, transient overload risk, thermal load, and work done. Based on the sensitivity results, a parameter calibration model was formulated to minimize torque prediction error and transient overload risk, and solved by the ant colony algorithm. Experimental validation shows that, after calibration, the root mean square error between predicted and measured torque decreases significantly from 1366.9 N·m to 277.7 N·m (a reduction of 79.7%), the peak error drops by 72.7%, and the servo motor’s effective torque prediction error was reduced from 7.6% to 1.4%. In an automotive door panel stamping application on a 25,000 kN heavy-duty servo press, the production rate increases from 11.4 to 11.6 strokes per minute, demonstrating en-hanced performance without compromising operational safety. This study provides a theoretical foundation and an effective engineering solution for high-precision model-ing and performance optimization of heavy-duty servo presses.

Abstract: This paper initiates a dual-route derivations of Hubble's Law within standard relativistic and Newtonian frameworks, grounded in the intrinsic perfect symmetry of the local inertial frame. This reveals that the fundamental aim of a local inertial frame's motion is to restore Poincaré symmetry, from which it follows that the flow velocity of a strong gravitational field equals its gravitational acceleration multiplied by one second. Thus the standard theories inherently contain the seed of dynamic field theory. Mass Complex Space Theory (MCST) is the guidance to push the standard theories toward full dynamization and higher-dimensionalization. MCST introduces the “Quadruple State of the Planck Quantum ☯(h, Φ_ih, Φ_h, ih )” as the elementary complex-space generating element, whose hyper-cycle dynamically unifies matter and spacetime. A key finding is that gravitational field space is constituted by diverging negative-energy “positron state ( )”. Consequently, dark matter and dark energy are unified as field effects of hyper-cycling mass complex space. Emergent from this framework is a gravitational circulation field ( ). This field makes the apparent Keplerian mass exhibits a counter-intuitive monotonic decrease (mass inversion) in the outer halo of the Milky Way (22.5–26.5 kpc). Moreover, owing to its intrinsic “negative-energy positron state” property, naturally generates huge magnetic field toriods, the structure of which aligns remarkably with the observed galactic magnetic field, thereby achieving a preliminary structural unification of gravitation and electromagnetism on galactic scales without additional assumptions, and further providing theoretical foundation for the quantization research on the unification at the subatomic scale.

Abstract: Drug discovery faces significant obstacles posed by unpredictable pharmacokinetic and safety properties, necessitating a complex, multiparameter optimization process. ADMET (Absorption, Distribution, Metabolism, Excretion, Toxicity) issues remain the primary reason for failure in drug development, with over 90% of discovery compounds failing basic ADME standards and unexpected ADMET problems causing around 30% of clinical setbacks. Conventional approaches that mainly rely on broad molecular properties offer limited guidance because they lack detailed insight into the atomic-level interactions between drugs and the body’s complex systems. Transforming small-molecule drug discovery requires a systematic, detailed understanding of the "Avoid-ome": the broad set of proteins that influence ADME and toxicity characteristics. The Avoid-ome includes a finite, manageable set of enzymes, transporters, receptors, and channels, which must be treated as "anti-targets" and avoided during the design process. OpenADMET (https://openadmet.org), an international open-science initiative, aims to fill the critical ADMET data gap by creating pre-competitive, open datasets covering metabolism, transport, distribution, and toxicity. The initiative is developing platforms that make compound synthesis, measurements (using technologies like scaled mass spectrometry and synthetic biology), and data analysis more affordable and capable of high-throughput processing. This approach uses high-throughput structural biology to ensure models are based on mechanistic, atomistic understanding, helping to clarify the structural basis of outliers, species differences, and genetic variation. Additionally, an active learning workflow is used across diverse chemical spaces to select compounds that are the most informative for building generalizable predictive models. OpenADMET includes blind community challenges, inspired by CASP and SAMPL, to evaluate predictive models with unreleased data, encouraging rigorous assessment and ongoing improvement within the research community. By systematically studying the Avoid-ome and creating open, structural, and mechanistic datasets, OpenADMET establishes a foundation for a new era of rational drug design, demonstrating that the most effective way to improve drug discovery is to stop avoiding the Avoid-ome and instead study it directly.

Abstract: This study provides a comprehensive overview of research and advancements on carbon materials with regard to practical targets for hydrogen storage in terms of gravimetric and volumetric capacities. For the sake of clarity, only the most relevant references on hydrogen storage by adsorption are presented, although the study was conducted in the same exhaustive manner as the one initially carried out by Anne C. Dillon and Michael J. Heben [Appl. Phys. A 2001, 72, 133–142] with a particular emphasis on emerging technologies and potential applications in various sectors, and focusing on the importance of carbon-based materials with high specific surface areas and porous structures optimised to maximise adsorption — including at high pressure —, while primarily limiting references herein to experimentally validated results. It therefore offers insights into the porous materials as well as the methodologies — including a fully comprehensive and so far proven highly transferable intermolecular hydrogen model combining van-der-Waals's and Coulomb's forces — used to improve hydrogen solid storage efficiency.

Abstract: External causes of death contribute to over four million annual global fatalities, with drug use representing a significant risk factor. However, the true national impact and regional variations of psychoactive substance use in these deaths remains unde-fined in Brazil. To address this critical knowledge gap, this pioneering four-region study sought to elucidate the influence of alcohol and drug use on external cause mor-tality. We collected post-mortem blood from 3,577 victims of violent death across four distinct Brazilian regions using a standardized protocol to identify alcohol, illicit drugs, and psychoactive medicines. Analysis revealed a predominantly male cohort (89.7%; 56.0% aged 30 years or more), with homicide as the primary manner of death (67.3%). Critically, over half of the victims (53.0%) were positive for at least one psy-choactive substance prior to death, most commonly cocaine (29.6%) and alcohol (27.7%). Substance consumption was highest among homicide victims (55.7%), pre-dominantly cocaine (36.0%), and in self-harm cases (26.4%), which showed high ben-zodiazepine rates (20.0%). Consumption patterns varied regionally: alcohol-related deaths were more common in the Northeast, drug-only deaths concentrated in the Southeast and North, and the South showed a higher prevalence of alcohol use versus drug use. This widespread, regionally heterogeneous prevalence underscores the ur-gent need for targeted, region-specific interventions. By critically linking psychoactive substance use to various modes of violent death, these data provide crucial forensic and public health insights to inform tailored preventive strategies.

Abstract: Time remains one of the most elusive concepts in physics, lying at the intersection of quantum mechanics, relativity, and thermodynamics. This work proposes a reformulation in which time arises as a local informational field rather than as a universal coordinate. Temporal direction is identified with gradients in stored information, linking geometry and entropy through an informational potential that generates both curvature and the arrow of time. The resulting field Ta(x)=∂aSinfo(x) defines causal order and temporal flow through local information exchange, unifying dynamical evolution and entropic asymmetry within a single framework. The formulation preserves general relativity in the macroscopic limit while extending its validity to microscopic regimes where information dynamics supersede geometric structure. It thus offers a coherent physical basis for temporal asymmetry, a bridge between quantum and gravitational descriptions, and a platform for simulating time as an observable field.

Abstract:

The article presents an integrated framework for robust control and cybersecurity of an industrial robot, combining Quantitative Feedback Theory (QFT), Digital Twin (DT) technology, and PLC-based architecture aligned with the requirements of the NIS2 Directive. The proposed concept, denoted as Cyber-Physical Digital Twin with QFT & NIS2 Security (CPDTQN), unifies control, observability, synchronization, and traceability mechanisms within a single cyber-physical structure. The study employs the five-axis industrial manipulator FANUC M-430iA/4FH, modeled as a set of SISO servo-axis channels subject to parametric uncertainty and external disturbances. For each axis, QFT controllers and prefilters are synthesized, and the system performance is evaluated using joint-space and TCP-space metrics, including maximum error, RMS error, and 3D positional deviation. A CPDTQN architecture is proposed in which the QFT controllers are executed in MATLAB, a Siemens PLC (CPU 1215C, FW v4.5) provides deterministic communication via Modbus TCP, OPC UA, and NTP/PTP synchronization, and the digital twin implemented in FANUC ROBOGUIDE reproduces the robot’s kinematics and dynamics in real time. This represents one of the first architectures that simultaneously integrates QFT control, real PLC-in-the-loop execution, a synchronized digital twin, and NIS2-oriented mechanisms for observability and traceability. Simulation results using nominal and worst-case dynamic models, as well as scenarios with externally applied torque disturbances, demonstrate that the system maintains robustness and tracking accuracy within the prescribed performance criteria. Furthermore, the study analyzes how the proposed CPDTQN architecture supports key NIS2 principles, including command traceability, disturbance resilience, access control, and mechanisms for forensic reconstruction in robotic manufacturing systems.

Abstract: Replication stress (RS) is a primary driver of genomic instability in cancer, yet the contribution of transcription-coupled repair to this process remains poorly understood. Here, we investigate how the TC-NER factor ERCC6 (CSB) shapes mutational landscapes under RS. We demonstrate that ERCC6 deficiency impairs replication restart and biases early damage signaling toward a 53BP1-mediated response, ultimately leading to senescence. Conversely, ERCC6-proficient cells prioritize survival and proliferative recovery but at the cost of distinct genomic alterations. Whole-exome sequencing reveals that ERCC6 drives the retention of stress-induced mutations specifically within coding regions of transcriptionally active loci, whereas ERCC6-deficient cells accumulate variants primarily in intergenic regions. These findings uncover a survival-mutagenesis trade-off: ERCC6 safeguards transcriptional continuity during replication stress but promotes mutational burdens in functional genomes. This mechanism parallels bacterial adaptive mutagenesis, identifying ERCC6 as a context-dependent driver of somatic evolution and tumor heterogeneity.

Abstract: Flexible biosensors offer rapid and low-cost diagnostics but are often limited by the mechanical and electrochemical instability of polymer-based designs in biological media. Here, we introduce a metallic flexible sensing platform that exploits the intrinsic deformability of superelastic nickel–titanium (NiTi) for label-free impedimetric detection. Mechanical bending of NiTi wires spontaneously generates martensitic-phase microcracks whose metal–gap–metal geometry forms the active transduction sites, where functional interfacial layers and captured analytes modulate the local dielectric environment and governing the impedance response. Functionalization with thiolated monolayers and Escherichia coli-specific antibodies enables these microdomains to modulate interfacial charge transfer in response to analyte binding, creating a direct coupling between mechanical deformation and resulting impedance signal. The γ-bent NiTi sensors achieved stable and quantitative detection of E. coli ATCC 25922 in sterile human urine, with a detection limit of 53 CFU mL⁻¹ within 45 minutes, without redox mediators, external labels, or amplification steps. This work establishes the first use of self-healing martensitic microcracks in a superelastic alloy as functional transduction elements, defining a new class of metallic flexible biosensors that integrate mechanical robustness, analytical reliability, and scalability for point-of-care biosensing.

Abstract: Background/Objectives: The current strategy for seasonal influenza prophylaxis relies on updating the vaccine components annually to account for the rapid antigenic drift of viruses and the low cross-protective efficacy of available vaccines. Mutant influenza viruses with truncated or deleted NS1 protein are known to stimulate cross-specific T-cell immune response and provide protection against heterosubtypic influenza A and B viruses. Methods: We generated NS1ΔC influenza A and B viruses with C-terminal NS1 deletions by reverse genetics. In a mouse model, we assessed the safety and immunogenicity of the B/Lee/NS1ΔC strain upon intranasal administration, as well as the mechanism of its cross-protective efficacy against sublethal B/Victoria and B/Yamagata challenge. We then investigated the potential of the intranasal Flu/UniVec vaccine–a trivalent formulation of NS1ΔC A/H1N1, A/H3N2, and B influenza viruses–to protect mice from lethal influenza infection with homologous, heterologous, and antigenically drifted influenza A and B viruses. Results: Intranasal immunization with the B/Lee/NS1ΔC strain was safe in mice. It activated cross-specific T-cell responses in the lungs and protected animals against heterologous challenge by reducing viral load, inflammation, and lung pathology. Immunization with the trivalent Flu/UniVec vaccine formulation improved survival and reduced weight loss and viral load upon challenge with A/H1N1pdm, A/H2N2, A/H5N1, and B/Victoria viruses. Conclusions: The trivalent intranasal replication-deficient Flu/UniVec influenza vaccine is a promising tool to improve seasonal influenza protection and preparedness for an influenza pandemic.

Abstract: Lactic acid bacteria (LAB) and yeasts constitute functionally important components of cheese microbiota, contributing to acidification, aroma formation, prolonged shelf life and microbial safety. This study investigated the antimicrobial activity, antibiotic susceptibility, and growth kinetics of LAB and yeasts isolated from selected ripened Ugandan cheese varieties in order to evaluate their suitability as starter or adjunct cultures. Isolates were identified through morphological, biochemical, and molecular approaches. Antimicrobial activity against Staphylococcus aureus, Escherichia coli, and Pseudomonas aeruginosa was assessed using agar well diffusion following established protocols. Antibiotic susceptibility was determined using disc diffusion in accordance with EUCAST and CLSI guidelines. Growth kinetics across pH gradients were monitored using a Bioscreen C automated microplate reader. The cheeses harbored diverse microbial communities, with considerable variation in antimicrobial activity among isolates. Pediococcus pentosaceus exhibited clear inhibition of S. aureus, whereas most isolates demonstrated limited antagonistic effects. Antibiotic susceptibility testing revealed multidrug resistance in Pediococcus acidilactici and in some opportunistic contaminants, emphasizing the need for careful safety assessments. Growth analysis showed that LAB grew optimally at moderately acidic pH (4.5–5.5), while Yarrowia lipolytica and Staphylococci preferred near-neutral conditions (pH 6.5–7.5). These findings highlight the presence of technologically valuable strains in Ugandan cheeses while underscoring the importance of antibiotic resistance screening in artisanal dairy systems. Select LAB strains, particularly P. pentosaceus and Lactiplantibacillus plantarum, show potential for starter culture development following genomic safety verification.

Abstract:

Bacteriophages, traditionally viewed solely as antibacterial agents, are increasingly being studied for their immunomodulatory properties. In this study, we demonstrate that PM16 phage therapy not only effectively controls subcutaneous Proteus mirabilis infection in mice, but also induces long-term specific humoral immunity against subsequent reinfection. This immunomodulatory effect was dose-dependent. In vitro, PM16 directly activates macrophages, leading to increased production of proinflammatory cytokines (tumor necrosis factor-α and interleukin-1β) and inducible nitric oxide synthase, and enhances macrophage bactericidal activity against P. mirabilis. We assume that the enhancement of the adaptive immune response is mediated not by the phage acting as a classical antigenic adjuvant, but by its ability to prime innate immune cells, specifically macrophages. This priming leads to more efficient bacterial clearance, antigen presentation, and the formation of protective immunological memory.

Abstract: Fusarium head blight (FHB) is a serious concern for wheat production worldwide. The current study was conducted to identify morpho-phenological traits that contribute to passive resistance against FHB. For this purpose, a set of 332 spring wheat genotypes from different origins was used. Eight morpho-phenological traits and FHB severity were evaluated using spray inoculation under field conditions in 2022 and 2023. A non-parametric test was performed to evaluate genotypic variation for all studied traits, revealing significant differences among genotypes across the three years. Correlation analysis demonstrated a strong negative association between phenological traits and FHB severity and a low to medium negative correlation between spike length, spikelets per spike, and FHB resistance. Furthermore, there was a significant negative but weak association between anther extrusion and FHB severity. Random forest regression analysis demonstrated that a complex of eight morpho-phenological traits predicted FHB severity with an accuracy of 65% in 2023 and 57% across two years. According to permutation importance analysis, days to flowering, heading, and anther extrusion had the highest contribution to FHB severity, and all three traits had a significant effect on FHB prediction.

Abstract: The P = NP problem is one of the most consequential unresolved questions in mathematics and theoretical computer science. It asks whether every problem whose solutions can be verified in polynomial time can also be solved in polynomial time. The implications extend far beyond theory: modern global cryptography, large-scale optimization, secure communication, finance, logistics, and computational complexity all depend on the assumption that NP-hard problems cannot be solved efficiently. Among these, the Spin-Glass ground-state problem represents a canonical NP-hard benchmark with an exponentially large configuration space. A constructive resolution of P = NP would therefore reshape fundamental assumptions across science and industry. While evaluating new methodological configurations, I encountered an unexpected behavior within a specific layer-cluster. Subsequent analysis revealed that this behavior was not an artifact, but an information-geometric collapse mechanism that consistently produced valid Spin-Glass ground states. With the assistance of Frontier LLMs Gemini-3, Opus-4.5, and ChatGPT-5.1, I computed exact ground states up to N = 24 and independently cross-verified them. For selected system sizes between N=30 and N=70, I validated the collapse-generated states using Simulated Annealing, whose approximate minima consistently matched the results. Beyond this range, up to N = 100, the behavior follows not from algorithmic scaling but from the information-geometric capacity of the layer clusters, where each layer contributes exactly one spin dimension. These findings indicate a constructive mechanism that collapses exponential configuration spaces into a polynomially bounded dynamical process. This suggests a pathway by which the P = NP problem may be reconsidered not through algorithmic search, but through information-geometric state collapse.

Abstract:

This study examines how Generation Z’s digital practices on TikTok and Instagram shape their music festival experiences, focusing on event perception, engagement, and the development of collective identity. The aim is to identify key factors connecting online and offline aspects of festival participation. The research adopts a quantitative approach based on an online survey of 248 respondents born between 1995 and 2010 from various regions of Serbia. Data were analysed in SPSS 26.0 using Spearman correlation, quantile regression, and the Mann–Whitney test. Findings show that frequent social media use has a positive but limited effect on how important these platforms are perceived for the festival experience. However, user-generated content created by attendees plays a more significant role in shaping engagement and attitudes than influencer content. Influencer credibility also influences how festivals are interpreted digitally. The interplay between online interaction and offline participation motivates content sharing and reinforces a sense of community. Overall, the study concludes that social media and digital narratives are central to Generation Z’s festival experience. Authentic, attendee-created content strongly contributes to collective identity, helping bridge digital and physical dimensions – insights valuable for festival organisers, influencers, and cultural tourism.

Abstract: Professor Min Chao of Zhejiang University, in his paper ‘Marx's Study of the French Revolution of 1848 and the Concrete Turn of the Materialist Conception of History’ published in the January 2025 issue of Marxism Studies, reinterprets Marx's texts on the French Revolution before and after 1848, centring on the core proposition of ‘the concrete turn of the materialist conception of history’ and its ‘triple dimensions’ (Min Chao, 2025). This article conducts a systematic review and critical assessment of the aforementioned paper within the framework of the four axiomatic laws of formal logic (the law of identity, the law of non-contradiction, the law of the excluded middle, and the law of sufficient reason), alongside the fundamental facts of Marxism's development and world historical realities. The article identifies three principal issues: Firstly, the core proposition of the ‘concrete turn of the materialist conception of history’ exhibits evident circular reasoning within its argumentative structure, lacking sufficient justification. Secondly, key concepts such as ‘historical concreteness’ versus ‘living history’ and ‘social formation’ versus ‘state formation’ are defined inconsistently throughout, constituting self-negation in terms of the law of identity and the law of non-contradiction. Thirdly, the absolute elevation of the study of the 1848 French Revolution as a watershed moment for the ‘concretisation of the materialist conception of history’ contradicts the temporal logic and textual context of works such as The German Ideology, The Communist Manifesto, and the Introduction to the Critique of Political Economy (Marx & Engels, 1845/1968; Marx & Engels, 1848/1969; Marx, 1857/1976); Fourthly, while methodologically professing opposition to abstract dogmatism, the paper in practice repackages established historical facts through abstract discourses such as the ‘triple dimension,’ presenting a self-irony of ‘naming the concrete with the abstract.’ Taken together, the paper exhibits fatal flaws in logical rigour, historical accuracy, and Marxist theoretical coherence that cannot be overlooked. Its narrative of a ‘concretisation turn’ is untenable.

Abstract: Background There is a high correlation between a trauma history and development of mental health conditions. By providing safe and containing (trauma-informed) working relationships, mental health nurses can validate mental distress, reduce re-traumatisation and support recovery. Trauma informed education (TIE) has become commonplace in nurse education however, little is known about students’ experience of this and its impact on their practice. Purpose This study aimed to evaluate and explore student mental health nurses’ perspectives on TIE and its impact on their practice to contribute to the knowledge and evidence base that informs nurse and broader healthcare education. Methods This qualitative, phenomenological study used focus group interviews (n=3) with 11 mental health nursing students, reported using SRQR Checklist. Analysis Data generated was analysed using Braun and Clarke’s (2013) Reflective Thematic Analysis. Findings Three themes were identified: 1. A compass for practice; 2. Mental Health Nursing: Between paradigms; 3. Supporting personal development and wellbeing. Integrating TIE within nurse education can support students to adopt the principles of trauma-informed care (TIC) personally and in their practice. Improved self-awareness, recognition of trauma and adopting self-care strategies were valuable in supporting personal resilience and wellbeing, valuable in managing the challenges of mental health practice. Recommendations TIE has the potential to have a positive impact on wellbeing therefore integration should be considered for all healthcare programmes. Further interprofessional research is needed to establish the longer-term impact of TIE as students’ progress into their professional career. Limitations This is an initial small-scale study with self-selecting students which limits generalisability. Exploring sustained impact through longitudinal study may be valuable.

Abstract: The blue economy aims to bring prosperity to coastal communities whilst also pro-tecting natural ocean resources for future generations. But how can this vision be put into practice, especially in communities in which dependancy on natural resources is high and food and livelihood security are key concerns? This paper examines two cases of community-led nature based enterprise in Kenya in a search for solutions to this challenge. I use a ‘diverse economies’ perspective to delve into the heterogeneous relations at work and in search of insights that can be applied in multiple contexts. The analysis reveals a complex assemblage of institutions, knowledges, technologies and practices within which enterprises operate. Whilst the enterprises featured are still relatively new and developing, they suggest a direction of travel for a community-led sustainable blue economy which both supports and benefits from nature recovery. The insights gained from this diverse economies analysis lead us to appreciate a sustainable blue economy as a rediscovered and reinvigorated relationship of reci-procity between society and nature. One that nurtures place-based nature-based livelihoods and nature recovery, together, and which embodies a set of values and ethics shared by government, communities, and business.

Abstract: The nationalization of De Javasche Bank (DJB) into Bank Indonesia (BI) via Law No. 11 of 1953 was fundamental to establishing Indonesia's monetary sovereignty. This study argues that the success of this high-stakes political decision was critically dependent on the micro-level administrative competence realized at strategically vital regional nodes. Focusing on the DJB Surabaya branch—the principal clearing center for Eastern Java—we utilize a qualitative historical methodology employing both macro-level institutional reports and localized archival sources to trace the implementation process. Our analysis posits that the swift and non-disruptive integration of the branch was a defining expression of professional patriotism, where national dedication was channeled into bureaucratic efficiency rather than military action. This success was executed through three synchronized strategic maneuvers: (1) Physical Asset Securitization and Symbolic Repurposing (securing reserves and rebranding the colonial structure); (2) Systemic Operational Continuity (seamlessly maintaining the regional credit clearing mechanism); and crucially, (3) Rapid Human Resource Decolonization (accelerated promotion and technical training of indigenous staff). The Surabaya case provides empirical validation of the newly independent Republic’s state capacity to manage complex central banking operations, underscoring the vital, yet often overlooked, role of regional administrative elites in post-colonial state-building.

Abstract: : Due to the lack of in-situ observations in mountainous locations, the use of remote sensing data is an alternative to analyze rainfall distribution patterns during the passage of major hurricanes. In this work, gridded precipitation data from the CHIRPS database are evaluated by comparing with observations from weather stations during the passage of category 3–5 hurricanes for the period 1980–2024. The comparison between estimated and observed values is performed by regression analysis and the use of the K and K0 coefficients. An advantage of using K-ratio and K0-ratio is the identification of overestimated or underestimated precipitation in the pixel records. The distribution of daily precipitation helped in a more concise way to better understand how well CHIRPS reproduced the observed rainfall patterns. Results show that correlations between observations and database estimates are in the range of 0.42–0.67, for eastern Pacific hurricanes, and 0.29–0.74 for Atlantic hurricanes all of which are statistically significant; however, these results do not imply congruence between observations and estimates since CHIRPS fails to adequately reproduce the position of the highest precipitation core. In the initial stages of a tropical cyclone, near- zero correlations between observations and estimates indicate that CHIRPS is not able to reproduce the observed rainfall. It is recommended to use CHIRPS with caution when the focus is on analyzing rainfall patterns during the development of intense tropical cyclones.