In this paper, a semi-analytical model for forced vibration of the thin-walled hard-coating cylindrical shell with arbitrary uniform circular perforations based on the energy superposition principle is proposed, in which the structural damping variation induced by arbitrary perforations is considered by the developed equivalent Rayleigh damping. The first-order shear deformation theory, second-kind Chebyshev polynomials, and artificial spring technique are employed to derive the governing equations used for forced vibration of the composite shell. Referring to the experimental natural frequencies and resonance response amplitudes of the perforated shell with NiCoCrAlY hard coating, the developed equivalent Rayleigh damping coefficients within a wider frequency band of interest are identified by the pattern search algorithm. The comparation between the experimental and semi-analytical amplitude-frequency curves of resonance exhibits the reliability and effectiveness of the semi-analytical model. Furthermore, a systematic analysis is conducted on the influence of perforation number and radius on the forced vibration characteristics of the shell, which can provide valuable theoretical support for vibration reduction design of complex perforated shell structures in aviation power equipment.

To address the limitations of the standard Sparrow Search Algorithm (SSA) in complex optimization problems—such as insufficient convergence accuracy and susceptibility to local optima—this paper proposes a Composite Strategy Sparrow Search Algorithm (CSSA) for multidimensional optimization. The algorithm first employs chaotic mapping during initialization to enhance population diversity; second, it integrates coordinate axis pattern search to strengthen local exploitation capabilities; third, it applies intelligent crossover operations to promote effective information exchange among individuals; and finally, it introduces an adaptive vigilance mechanism to dynamically balance exploration and exploitation throughout the optimization process. Compared with seven state-of-the-art algorithms, CSSA demonstrates superior performance in both 30-dimensional low-dimensional and 100-dimensional high-dimensional test scenarios. It achieves optimal solutions in three real-world engineering applications: thermal management of electric vehicle battery packs, photovoltaic power system configuration, and data center cooling systems. Wilcoxon rank-sum tests further confirm the statistical significance of these improvements. Experimental results show that CSSA significantly outperforms mainstream optimization methods in terms of convergence accuracy and speed, demonstrating substantial theoretical value and practical engineering significance.

Trends in Search Patterns and Public Interest in Vaping, Cigarette Products, and Oral & Oropharyngeal Cancer: An Infodemiology Analysis

Atomic density distributions in proteins: structural and functional implications.

Interleaved hybrid simulated annealing and pattern search for time-optimal feedrate scheduling in multi-axis CNC machining

The increasing sophistication of cyber threats necessitates the development of more robust cryptographic systems. This paper introduces African Vulture Optimization- Enhanced RSA (AVO-RSA), a novel hybrid cryptosystem that integrates the African Vulture Optimization Algorithm (AVOA) with the traditional RSA algorithm to enhance security in data communication. AVO-RSA optimizes prime number selection and key generation using bio-inspired heuristics, making it more resistant to brute-force and factorization attacks. The proposed algorithm dynamically adjusts key parameters based on communication patterns, ensuring adaptive security. Experimental results demonstrate that AVO-RSA improves key strength while maintaining computational efficiency. This work contributes to the field of bio-inspired cryptography by introducing a nature-based optimization technique to strengthen asymmetric encryption. By optimizing prime selection using mathematical modelling and AI-driven search patterns, the proposed system significantly strengthens the resilience of RSA against modern cryptographic attacks. Experimental results demonstrate improvements in key unpredictability, encryption efficiency, and overall security, making it highly suitable for secure data communication.

This study examines consumer behavior patterns through comprehensive search pattern analysis across three major e-commerce platforms. The research analyzed 127,543 search sessions from 12,847 unique users over six months using Latent Dirichlet Allocation (LDA) and K-means clustering. Data collection involved clickstream analysis, query pattern extraction, and behavioral tracking across mobile, desktop, and tablet devices. Statistical methods included hierarchical linear modeling, ANOVA, and chi-square tests. The analysis identified five distinct consumer segments: Exploratory Browsers (32.4%), Systematic Researchers (23.8%), Direct Purchasers (18.7%), Deal Seekers (15.3%), and Uncertain Seekers (9.8%). Results reveal significant behavioral variations across customer journey stages, with query length increasing from 2.84 to 4.89 words and brand mentions rising from 15.2% to 71.3% from awareness to retention stages. Mobile devices dominated usage (63.4%), with distinct behavioral patterns across demographics and temporal factors. These findings enable businesses to develop targeted marketing strategies, optimize user experience design, and implement personalized recommendation systems. This research contributes original insights by integrating quantitative behavioral analytics with qualitative thematic analysis, providing a comprehensive framework for understanding digital consumer decision-making processes in contemporary e-commerce environments.

Among the issues raised internationally that relate to the protection of cultural heritage, increasing attention is being paid to the individual responsibility of perpetrators of crimes against cultural property. The aim to harmonise the level of criminal law protection of cultural property in national legal systems is seen as one of the most important factors that could reduce crime in this area. Legislative initiatives undertaken by countries in order to strengthen the criminal law protection of cultural property focus primarily on two groups of problems: the development of a catalogue of offences against cultural property and the determination of the type and amount of sanctions with which these offences should be threatened. In the search for an optimal pattern of penalisation, the article identifies the norms of international law influencing the scope of penalisation of behaviours violating the principles of protection of cultural property in the national legal orders and analyses the legislative achievements so far obtained within the framework of international cooperation at the universal and regional (European) level. The considerations were concentrated around three key issues, which were considered to be: the notion of just punishment, the analysis of the scope of criminal law protection of cultural property set out in the documents of UNESCO and the Council of Europe, and the type and amount of sanctions that should be applied to behaviour directed against cultural property under legal protection. The last part of the article consists of the final conclusions formulated after an autonomous assessment of the regulations adopted in the two systems of international cooperation on the criminal law protection of cultural heritage indicated above.

Within the context of the education system, the opportunity for schoolchildren to acquire fundamental philosophical knowledge is intrinsically linked to the school social studies curriculum. The teaching of social studies disciplines poses modern teachers with a number of challenges in terms of interdisciplinarity and the necessity to harmonize the theoretical material of the disciplines and to consider current social issues in their dynamics. Social studies, as a system of social science disciplines, represents a complex body of knowledge that is fundamentally integral in nature. It discusses issues of anthropology, law, political science, economic theory, sociology and social philosophy, religious studies, axiology, and a number of philosophical disciplines. In order to successfully master social studies, it is necessary to delve into the origins of many issues (for example, theories of the origin of the state and law, for example, through understanding the connection between the genesis of law as a constitutive element of the state structure from the perspective of social philosophy). Conversely, in order to track transformations in legislation and identify those events in the modern world that clearly illustrate the mechanisms for implementing theoretical principles, is also necessary. However, it is imperative to recognize that a comprehensive understanding of the theoretical underpinnings of the processes and phenomena that define the discipline of social studies is fundamental to achieving a profound comprehension of the intricacies inherent in the study and interpretation of society and its constituents. A systematic understanding of society is of particular importance for life in the future: the search for patterns of social development is linked to the possibilities of choosing one’s own educational and professional development path and, furthermore, understanding the cause-and-effect relationships in society as a system can become a starting point for the formation of one’s own personal qualities in harmony with the generally accepted goals of society. Philosophy, as a meta-subject area, is well-positioned to facilitate the formulation of answers (or the elucidation of extant questions) that underpin the formation of a worldview, so this worldview is predicated on the integration of diverse perspectives on the perception of reality, thereby rendering this reality more vivid and accentuating its problematic aspects.

Abstract Introduction Peyronie’s Disease (PD) is a progressive condition characterized by acquired fibrous plaques within the tunica albuginea leading to deformity and curvature of the penis. The prevalence of PD is estimated to be up to 7-13% of men, which is likely an underestimate given the reluctance of men to report symptoms and seek treatment. In 2013, the Food and Drug Administration (FDA) approved Xiaflex, an intralesional collagenase injection, for adults with PD. On October 25, 2021, Endo released its first Xiaflex advertisement campaign using the “bent carrot” to raise awareness for PD. Objective We aimed to assess the impact of this advertisement campaign by examining public interest in PD before and after its release according to internet search patterns from a major internet search engine. Methods Google trends were queried to analyze public interest levels in PD before and after the “bent carrot” commercial from 1/1/2020 to 10/1/2024. Relative interest across the United States was determined by Google Trends reporting using the terms “Xiaflex,” “bent carrot,” and “Peyronie’s disease.” Relative search volume (RSV) was reported on a scale from 0 to 100. Trends were analyzed and compared over the time period. Regional interest was also examined at the state level. Results The search terms “Xiaflex,” “bent carrot,” and “Peyronie’s disease” rose in search volume after the introduction of the bent carrot commercial (Figure 1). The terms “Xiaflex” and “bent carrot” reached their peak search volume the week of 12/19-12/25/2021 and “Peyronie’s disease” reached its peak search volume on 2/13/2022, which corresponds to the date of the 2022 Super Bowl. The average search volume for each term was significantly higher when comparing the four months prior to the four months after the commercial debuted (p<0.05). States with the highest search volume for each term are shown in Table 1, and Figure 2 shows a visual depiction of regional interest in Peyronie’s disease. Conclusions Google searches for Peyronie’s disease search terms increased after the introduction of the Xiaflex “bent carrot” commercial. The estimated prevalence of PD is thought to be low due to lack of awareness, patient embarrassment, and hesitation in seeking treatment. Our results show that marketing campaigns can increase interest in PD, but may drop with lack of marketing. Therefore, advertisements such as this serve a critical role in reaching patients, raising awareness, and normalizing PD. Additionally, these campaigns can help patients find providers and understand the possible treatment options for PD. Disclosure Any of the authors act as a consultant, employee or shareholder of an industry for: Stanton Honig - Coloplast, Endo pharmaceuticals, Fellow, Posterity Health, HIMS, Haleon, WIN fertility

Panoramic radiographs (PANs) are a commonly used dental imaging modality and are complex to evaluate. This study aimed to use mouse-tracking technology to identify the visualization characteristics of experienced Oral & Maxillofacial Radiology (OMR) faculty when reviewing PANs and to assess relationships with detection accuracy. Seventeen OMR faculty in U.S. dental schools with 5 to 38 years of experience were recruited. Participants were shown 17 PANs (5 "Normal" and 12 "Pathology") over Zoom and instructed to move their mouse cursor in sync with their eye movements. Data collection was based on video recordings with X, Y coordinates auto-detected using mouse-tracking algorithms. Parameters collected included detection accuracy, time taken, completeness of search coverage, revisits and search patterns used. Most common search patterns were Dental to Periphery (41.5%) and Periphery to Dental (37.7%). The mean accuracy score for all cases with pathology was 84.6%. Except for 2 cases with subtle findings (condylar fracture and fibrous dysplasia), mean accuracy scores ranged from 76.5% to 100%. There were no associations between search patterns and detection accuracy. Participants took longer durations and performed more complete searches with more revisits on "Normal" cases. They were more likely to use shorter search times with smaller coverage and perform single searches when correctly detecting lesions. Experienced OMRs were able to detect lesions without scanning the entire PAN and within a single search, regardless of the search pattern used. This is the first study using mouse-tracking algorithms to evaluate visualization patterns on PANs. Experienced OMRs can conduct efficient and accurate reviews of PANs regardless of search strategy.

Abstract Collision avoidance is a crucial aspect of autonomous ground vehicles (AGVs). One of the most common algorithms is called the dynamic window approach (DWA). The algorithm enables AGVs to operate with high performance in an unknown environment with a particular emphasis on achieving maximum linear and angular acceleration. However, DWA requires high computational effort to examine all possibilities with high resolution, and then select the best possible pair of control signals, i.e., linear and angular velocities. In this paper, the Pattern Search (PS) optimization algorithm is used to reduce the computational requirement of the DWA. Instead of calculating the DWA objective function for each possibility, the PS is used for algorithmically selecting the next examined pair of control signals. The results obtained demonstrate that a similar resolution of control signals can be achieved with almost two times less computational effort. The proposed approach has been examined in the MATLAB environment, while the source code is available on the MathWorks FileExchange.

Reverse total shoulder arthroplasty (RTSA) is increasingly used for a variety of complex shoulder abnormalities, particularly in patients with rotator cuff deficiency. Design improvements with better biomechanics have led to improved clinical outcomes, but the radiographic appearance and complication profile of contemporary RTSA implants differ from those of a decade ago. Plain radiographs can be used to identify whether the prosthesis is medialized (primarily older prostheses) or lateralized. A standardized imaging protocol and a reporting checklist are vital for the identification of complications. Although most complications can be identified with standard radiography, CT and MRI performed with dedicated protocols to reduce metallic artifacts are helpful problem-solving adjuncts. US can be used to assess the surrounding muscles before and after RTSA, to evaluate for postoperative complications such as fluid collections, and to provide guidance for aspiration. Complications such as periprosthetic fracture, instability, loosening, scapular notching, and implant failure require focused search patterns for identification. More chronic complications such as stress fractures and tuberosity fragmentation require comparison with previously acquired images. Implant disassembly, rarely seen with other arthroplasties, can occur and requires familiarity with the expected appearance of the prosthesis components. A downloadable checklist for imaging evaluation of the prosthesis is provided, and imaging examples of common and uncommon complications are presented. After reviewing this article, the reader will have an improved understanding of the RTSA prosthesis and will be able to recognize the normal and abnormal imaging appearances of this increasingly popular type of shoulder replacement. ©RSNA, 2025 Supplemental material is available for this article.

The article presents the development and formalization of an algorithm for pattern matching in graph representations of textual data as a core component of syntactic-semantic transformations for ontology construction from text documents. The study aims to bridge the gap between natural language processing and formal logic by introducing a universal SPARQL-based approach for executing transf- ormation rules directly on graph database servers. The proposed method integrates RDF data repre- sentation with formal graph transformation techniques, including Double Pushout (DPO), ensuring correctness and mathematical rigor. Through the use of graph indexing schemes such as SPO, POS, and OSP, the proposed approach transforms the computationally expensive subgraph isomorphism task from exponential to practical polynomial complexity. The implementation achieves up to 73% runtime reduction during repeated executions due to server-side caching. The research contributes a flexible, formalized, and scalable mechanism for automatic ontology construction, facilitating deep semantic ana- lysis and causal reasoning from textual sources. The algorithm’s extensibility allows dynamic rule introduction without recompilation, making it suitable for applications in semantic web systems, kno- wledge extraction, and AI-driven natural language understanding. Within the scope of this research, an algorithm was developed and analyzed for identifying homomorphic and isomorphic matches of pattern subgraphs within syntactic graphs, leveraging RDF representations and SPARQL queries enhanced with filter generation algorithms for shape-based mat- ching. The study demonstrates that the complexity of pattern search can be effectively mitigated through graph database indexing strategies, such as SPO, POS, and OSP indexes, reducing exponential complexity to polynomial levels for practical text block sizes. Experimental evaluation confirmed the scalability and efficiency of the proposed approach, revealing substantial runtime reductions during repeated executions as a result of server-side caching. The work contributes flexible, formalized, and efficient methods for automatic ontology construction from natural language texts, enabling deep semantic analysis and causal reasoning. The approach supports extensibility and dynamic rule introduction without code recompilation, making it suitable for real-world semantic web and knowledge extraction systems. The results have implications for NLP, ontology engineering, and applications requiring interpretability and scalability in processing complex textual data.

To explore the effect of simulation technology in the training of flexible fiberoptic intubation for undergraduate students. The research subjects were 39 students majoring in dentistry at Air Force Medical University, including 22 males and 17 females with an average age of 20.62 years. The study subjects were randomly divided into two groups, with 19 in experimental group and 20 in control group. There were no significant differences in gender and age distribution. The experimental group used the flexible fiberoptic bronchoscopy to perform 5 times in endoscopic operation training module, while the control group was only familiar with flexible fiberoptic bronchoscopy without simulation training. The two groups were evaluated for their skills after training. The evaluation included the duration of placing the fiberoptic bronchoscope into the airway and the time to find the target pattern. The duration of placing and finding the target pattern were compared between two groups. The Global rating scale(GRS) was used to evaluate the proficiency of positioning, operation and direction. The students gave self-confidence feedback before and after the training, and the rating was based on the Liker five-level scale. The experimental group of students had a bronchoscopy insertion time of 18.0 (18.0, 20.0) s and a target pattern search time of 20.0 (17.0, 21.0) s, both of which were significantly faster than the control group's times of 30 (36.0, 47.0) s and 39.0 (30.0, 41.0) s, respectively, P<0.001. The experimental and control groups' GRS scores for task proficiency were 3.0 (3.0, 4.0) and 3.0 (3.0, 4.0), respectively, which were substantially higher than those in the control group (2.0, 1.0, 2.0) and 2.0 (1.0, 2.0) (P<0.001). There was no statistically significant difference in confidence feedback between the two groups prior to training, according to the results of the trainees' feedback on operational confidence. The control group had a confidence feedback score of 2.0 (1.0, 2.0) after training, while the experimental group earned a feedback score of 3.0 (2.0, 3.0), showing a substantial gain in student confidence (P<0.001). Fiberoptic bronchoscopy intubation simulation training is excellent for novices to quickly understand this technology, increase their academic performance and confidence, and provide an effective reference for undergraduate teaching of this technology.

In additive manufacturing, the optimisation of process parameters to simultaneously enhance both mechanical and geometrical properties remains a significant challenge. This study presents a comparative analysis between two distinct approaches to multi-response optimisation: a hybrid method combining Artificial Neural Networks with Pattern Search Algorithm, and the traditional Response Surface Methodology. Both methods were applied to optimise the process parameters of Fused Filament Fabrication using Polylactic Acid. The hybrid ANN + PSA model was used to predict process outputs and optimise printing parameters, while RSM employed a statistical approach to identify optimal parameter combinations through designed experiments. Results show that ANN + PSA achieved better outcomes with a maximum tensile strength of 61.88 MPa and dimensional deviations within 3%, compared to RSM's tensile strength of 53.05 MPa and deviations up to 4%. The ANN + PSA model demonstrated higher predictive accuracy with an R 2 of 94.34% during training and 91.34% during evaluation, versus RSM’s R 2 of 90.5% for tensile strength prediction. Additionally, ANN + PSA consistently required fewer experimental trials due to its integration with the Pattern Search Algorithm, improving computational efficiency. The findings demonstrate that ANN + PSA is computationally efficient for scenarios with fewer experimental trials, while RSM offers a more detailed understanding of interaction effects. The comparative insights from this study contribute to enhanced multi-response optimisation strategies in additive manufacturing.

Traditional controllers frequently perform poorly when managing complex industrial systems because they must balance multiple goals like cost, pollution, and efficiency. For higher performance and efficiency, model predictive controller addresses this but necessitates efficient cost function tuning, which is currently frequently enhanced utilising metaheuristic algorithms. This work aims to develop and validate a data-driven weight optimisation method for multivariable model predictive controller in a DC microgrid comprising photovoltaic panels, battery, supercapacitor, grid, and load—by systematically balancing control effort and accuracy. Four algorithms—particle swarm optimization, genetic algorithm, pareto search, and pattern search-selected for their capacity to resolve complex, multi-objective problems are used in this study’s automated, set-point tracking-based weight optimisation approach. The results show that incorporating parameter interdependency reduces genetic algorithm’s power load tracking error from 16% to 8%, while particle swarm optimization achieves an error of under 2% even without considering interdependency. Fast convergence and trade-offs are supported by pareto and pattern search, but they are less responsive to sudden changes. These methods provide a feasible, repeatable way to boost model predictive controller performance.

Transcranial direct current stimulation (tDCS) is a noninvasive form of brain stimulation that involves passing a weak electrical current between electrodes on the scalp to modulate underlying neural tissue. TDCS has been shown to modulate cognition in a variety of domains, including memory, attention, and visual processing. Prior work from our laboratory has shown positive effects of tDCS on learning to detect target objects hidden in complex naturalistic visual scenes and learn rules for categorizing images, though the mechanism for these benefits remains unknown. One possibility is that tDCS optimizes visual search by modulating visual attention or via the reduction in search errors. One method of quantifying visual attention is to use eye tracking to record search patterns to determine if and how visual search is adjusted under verum stimulation conditions. Eye tracking data allows classification of errors into error types, including sampling errors (failing to look in the relevant region), recognition errors (looking at the critical portion of a scene, but failing to recognize it as such as evidenced by visual fixation), and decision-making errors (fixating on the relevant portion of a scene, but making the wrong determination). Our results indicate that the benefit tDCS confers on visual search for targets stems from the reduction in decision-making errors when targets are present (Cohen’s d = 0.86). Also reported is a replication of previous findings showing a tDCS-dependent improvement in learning this task, learning score (Cohen’s d = 0.88); d’ (Cohen’s d = 1.00). This provides support for moving tDCS into the application space by pairing it with analysts who are concerned with the type of search error that is corrected via stimulation.

The digital echo of war and the influence of tactical combat casualty care on google search patterns in Ukraine

SummaryBehavioral laterality is a prominent Bilateria feature, where motor functions are performed with a directional preference. Underlying such behaviors is thought to be hemispheric specializations that improve behavioral performance. Despite the prevalence, how behavioral lateralization is modulated throughout evolution is poorly understood. Comparative approaches are a powerful strategy for addressing fundamental biological questions from individual to evolutionary scales. Previously, we described a robust visuomotor asymmetry in larval zebrafish search pattern behavior. Here, we compare visuomotor asymmetry across several larval teleost species, demonstrating that general motor patterns are variable while behavioral asymmetry is conserved across sighted teleosts, yet not naturally blind cavefish. Our data indicate that visuomotor asymmetry in larval teleosts is a conserved behavior that can be modulated by natural selection against vision. This establishes larval teleosts as a powerful system for dissecting the molecular and evolutionary forces that govern behavioral lateralization, bridging the gap between mechanism and adaptation.