Search Results (907)

This Data Descriptor provides an open, anonymized dataset describing anthropometric and physical fitness outcomes in undergraduate students enrolled in a Physical Activity and Sport Sciences degree program. The dataset included 156 participants (28 females and 128 males) and reported sex, age, body mass, stature, and body mass index, alongside standardized field-based tests covering flexibility, muscular endurance, strength, and jump performance. Hip flexibility was assessed using the Thomas test on both sides. Trunk extensor endurance was measured using the Biering–Sørensen test, and upper-body strength–endurance was assessed using a dead-hang test. Upper limb strength was recorded as elbow flexion strength. Lower limb power was evaluated using vertical jump tests, including Abalakov, squat jump, and countermovement jump, and a derived indicator (IE) was provided to facilitate comparisons across jump modalities. The data are distributed as a machine-readable CSV file accompanied by a detailed data dictionary describing the variables, units, and missingness. The dataset is intended to support the reproducible reporting of normative fitness profiles in sports science students, facilitate teaching and benchmarking in exercise science contexts, and enable secondary analyses exploring associations between anthropometry and physical performance. For reproducible inferential comparisons, users may apply Welch’s two-sample t-test for sex-based differences. Full article

LED lamps have not been demonstrating the durability claimed by their manufacturers. One hypothesis is that switching transients may contribute to this. This study investigated switching-induced transients in LED lamps operated through dry contacts: manual switches and contactors. Using an oscilloscope, automated acquisition of waveform records was performed while several lamps were switched on in a 220 V_RMS/60 Hz electrical network. LED lamps of different models and manufacturers, one incandescent lamp, and a group of 48 LED lamps, subdivided into six sets of eight lamps, were all switched simultaneously. A total of 56 waveform-record files were obtained from the oscilloscope, comprising 2920 captured screens and 170 measurements. Transient voltage peaks of 380 and 391 V at the supply side, and 357 and 370 V at the lamp side, as well as voltage slew rates of up to 12 and 13 V/µs at the supply side and up to 16 and 19.5 V/µs at the lamp side, were measured, without considering statistical variations, which may indicate values exceeding the ordinary sinusoidal voltage peak (≅311 V) and its typical worst-case slew rate (≅0.12 V/µs). Future studies are suggested, such as tests in real installations, investigations of transient amplification or attenuation within electrical networks, assessment of the effects of wiring and impedance discontinuities, switch bounce, and semiconductor degradation, among others, to continue these studies. Full article

This dataset presents a real-world lipidomics resource for developing and benchmarking quality control methods, batch effect detection algorithms, and data validation workflows. The data originates from a cross-sectional clinical study of psoriatic arthritis (PsA) patients (n = 81) and healthy controls (n = 26), matched for age, sex, and body mass index, which was collected at a tertiary university rheumatology center. Subtle laboratory irregularities were detected only through advanced unsupervised analysis, after passing conventional quality control and standard analytical methods. Blood samples were processed using standardized protocols and analyzed using high-resolution and tandem mass spectrometry platforms. Both targeted and untargeted lipid assays captured lipids of several classes (including carnitines, ceramides, glycerophospholipids, sphingolipids, glycerolipids, fatty acids, sterols and esters, endocannabinoids). The dataset is organized into four comma-separated value (CSV) files: (1) Box–Cox-transformed and imputed lipidomics values; (2) outlier-cleaned and imputed values on the original scale; (3) metadata including clinical classifications, biological sex, and batch information for all assay types and control sample processing dates; and (4) a variable-level description file (readme.csv). The 292 lipid variables are named according to LIPID MAPS classification and standardized nomenclature. Complete batch documentation and FAIR-compliant data structure make this dataset valuable for testing the robustness of analytical pipelines and quality control in lipidomics and related omics fields. This unique dataset does not compete with larger lipidomics quality control datasets for comparisons of results but provides a unique, real-life lipidomics dataset displaying traces of the laboratory sample processing schedule, which can be used to challenge quality control frameworks. Full article

Cybersecurity teams rely on signature-based scanners such as Loki, a command-line tool for scanning malware, to identify Indicators of Compromise (IOCs), malicious artifacts, and YARA-rule matches. However, the raw Loki log output delivered as CSV or plaintext is challenging to interpret without additional visualization and correlation tools. Therefore, this research discusses the creation of a web-based dashboard that displays results from the Loki scanner. The project focuses on processing and displaying information collected from Loki’s scans, which are available in log files or CSV format. DIGITRACKER was developed as a proof-of-concept (PoC) to process this data and present it in a user-friendly, visually appealing way, enabling system administrators and cybersecurity teams to monitor potential threats and vulnerabilities effectively. By leveraging modern web technologies and dynamic data visualization, the tool enhances the user experience, transforming raw scan results into a well-organized, interactive dashboard. This approach simplifies the often-complicated task of manual log analysis, making it easier to interpret output data and to support low-budget or resource-constrained cybersecurity teams by transforming raw logs into actionable insights. The project demonstrates the dashboard’s effectiveness in identifying and addressing threats, providing valuable tools for cybersecurity system administrators. Moreover, our evaluation shows that DIGITRACKER can process scan logs containing hundreds of IOC alerts within seconds and supports multiple concurrent users with minimal latency overhead. In test scenarios, the integrated Loki scans were achieved, and the end-to-end pipeline from the end of the scan to the initiation of dashboard visualization incurred an average latency of under 20 s. These results demonstrate improved threat visibility, support structured triage workflows, and enhance analysts’ task management. Overall, the system provides a practical, extensible PoC that bridges the gap between command-line scanners and operational security dashboards, with new scan results displayed on the dashboard faster than manual log analysis. By streamlining analysis and enabling near-real-time monitoring, the PoC tool DIGITRACKER empowers cyber defense initiatives and enhances overall system security. Full article

The exponential growth of digital data and the escalating sophistication of cyber threats have intensified the demand for secure yet computationally efficient encryption methods. Conventional algorithms (e.g., AES-based schemes) are cryptographically strong and widely deployed; however, some implementations can face performance bottlenecks in large-scale or real-time workloads. While many modern systems seed from hardware entropy sources and employ standardized cryptographic PRNGs/DRBGs, security can still be degraded in practice by weak entropy initialization, misconfiguration, or the use of non-cryptographic deterministic generators in certain environments. To address these gaps, this study introduces FileCipher. This novel file-encryption framework integrates a chaos-enhanced Cryptographically Secure Pseudorandom Number Generator (CPRNG) based on the State-Based Tent Map (SBTM). The proposed design achieves a balanced trade-off between security and efficiency through dynamic key generation, adaptive block reshaping, and structured confusion–diffusion processes. The SBTM-driven CPRNG introduces adaptive seeding and multi-key feedback, ensuring high entropy and sensitivity to initial conditions. A multi-threaded Java implementation demonstrates approximately 60% reduction in encryption time compared with AES-CBC, validating FileCipher’s scalability in parallel execution environments. Statistical evaluations using NIST SP 800-22, SP 800-90B, Dieharder, and TestU01 confirm superior randomness with over 99% pass rates, while Avalanche Effect analysis indicates bit-change ratios near 50%, proving strong diffusion characteristics. The results highlight FileCipher’s novelty in combining nonlinear chaotic dynamics with lightweight parallel architecture, offering a robust, platform-independent solution for secure data storage and transmission. Ultimately, this paper contributes a reproducible, entropy-stable, and high-performance cryptographic mechanism that redefines the efficiency–security balance in modern encryption systems. Full article

Background: Nickel–titanium (NiTi) endodontic instruments have undergone significant improvements in heat treatment processing and geometric design, aimed at enhancing flexibility, cutting efficiency, and fatigue strength. Reciprocating motion was introduced to increase cyclic fatigue resistance, which remains the predominant mode of failure in NiTi endodontic file systems. Although these instruments are widely used in both clinical practice and research, few comparative studies have integrated geometric, metallurgical and mechanical evaluations of the most commonly used reciprocating systems. Methods: In the present study, four single-file reciprocating NiTi systems (Reciproc Blue, WaveOne Gold, EdgeOne Fire, and Easy-File Flex) were evaluated for their geometric design, metallurgical composition, and cyclic fatigue strength. Stereomicroscopy and scanning electron microscopy were employed to assess active blade length, spiral configuration, and surface finish, while elemental composition and phase transformation temperatures were analyzed using energy-dispersive X-ray spectroscopy and differential scanning calorimetry. Ten instruments from each group were tested for cyclic fatigue using a standardized curved stainless-steel canal at room temperature, and the time to fracture was recorded. Fatigue data were statistically analyzed using Mood’s median test, with significance set at p < 0.05. Results: Reciproc Blue exhibited the longest active blade length, highest spiral density, and superior surface finish. R-phase start and finish temperatures were highest in WaveOne Gold and lowest in Easy-File Flex. Reciproc Blue demonstrated the higher cyclic fatigue strength, whereas Easy-File Flex showed the lowest. Conclusions: These findings suggest that the metallurgical and geometric characteristics of the Reciproc Blue file significantly enhance its strength to cyclic fatigue compared with the other instruments evaluated. Full article

Pull request templates are used to reduce inconsistencies in information included in submitted pull requests in GitHub. A few studies have explored the effectiveness of employing pull request template. However, there is still a lack of how to evolve PR templates during software development. Knowledge is crucial to efficiently manage PR templates. To address this gap, we conducted a study on the organisation and evolution of pull request template initial content. For the study, 2689 target PR template files from 2614 public GitHub repositories were collected and 7 PR content categories including Description, Checklist, Reference, Test, Type, Additional Info, and Other were manually defined from the target files. Based on the defined categories, a pull request content classifier was built. By using the target dataset and the classifier, initial content organisation and its evolution were investigated. The results showed that 68% of target pull request templates organise their initial content with only two or fewer categories, and the initial content organisation remains in 71% of the entire pull request templates. Full article

We present a combined ML/NLP (Machine Learning, Natural Language Processing) pipeline for protecting cloud-based APIs (Application Programming Interfaces), which works both at the level of individual HTTP (Hypertext Transfer Protocol) requests and at the access log file reading mode, linking explicitly technical anomalies with business risks. The system processes each event/access log through parallel numerical and textual branches: a set of anomaly detectors trained on traffic engineering characteristics and a hybrid NLP stack that combines rules, TF-IDF (Term Frequency-Inverse Document Frequency), and character-level models trained on enriched security datasets. Their results are integrated using a risk-aware policy that takes into account endpoint type, data sensitivity, exposure, and authentication status, and creates a discrete risk level with human-readable explanations and recommended SOC (Security Operations Center) actions. We implement this design as a containerized microservice pipeline (input, preprocessing, ML, NLP, merging, alerting, and retraining services), orchestrated using Docker Compose and instrumented using OpenSearch Dashboards. Experiments with OWASP-like (Open Worldwide Application Security Project) attack scenarios show a high detection rate for injections, SSRF (Server-Side Request Forgery), Data Exposure, and Business Logic Abuse, while the processing time for each request remains within real-time limits even in sequential testing mode. Thus, the pipeline bridges the gap between ML/NLP research for security and practical API protection channels that can evolve over time through feedback and retraining. Full article

This paper introduces a cybersecurity framework that combines a deception-based ransomware detection system, called the Intrusion and Ransomware Detection System for Cloud (IRDS4C), with a blockchain-enabled Cyber Threat Intelligence platform (CTIB). The framework aims to improve the detection, reporting, and sharing of ransomware threats in cloud environments. IRDS4C uses deception techniques such as honeypots, honeytokens, pretender network paths, and decoy applications to identify ransomware behavior within cloud systems. Tests on 53 Windows-based ransomware samples from seven families showed an ordinary detection time of about 12 s, often quicker than tralatitious methods like file hashing or entropy analysis. These detection results are currently limited to Windows-based ransomware environments, and do not yet cover Linux, containerized, or hypervisor-level ransomware. Detected threats are formatted using STIX/TAXII standards and firmly shared through CTIB. CTIB applies a hybrid blockchain consensus of Proof of Stake (PoS) and Proof of Work (PoW) to ensure data integrity and protection from tampering. Security analysis shows that an attacker would need to control over 71% of the network to compromise the system. CTIB also improves trust, accuracy, and participation in intelligence sharing, while smart contracts control access to erogenous data. In a local prototype deployment (Hardhat devnet + FastAPI/Uvicorn), CTIB achieved 74.93–125.92 CTI submissions/min, The number of attempts or requests in each test was 100 with median end-to-end latency 455.55–724.99 ms (p95: 577.68–1364.17 ms) across PoW difficulty profiles (difficulty_bits = 8–16). Full article

The Transport Layer Security (TLS) protocol is widely used nowadays to create secure communications over TCP/IP networks. Its purpose is to ensure confidentiality, authentication, and data integrity for messages exchanged between two endpoints. In order to facilitate its integration into widely used applications, the protocol is typically implemented through libraries, such as OpenSSL, BoringSSL, LibreSSL, WolfSSL, NSS, or mbedTLS. These libraries encompass functions that execute the specialized TLS handshake required for channel establishment, as well as the construction and processing of TLS records, and the procedures for closing the secure channel. However, these software libraries may contain vulnerabilities or errors that could potentially jeopardize the security of the TLS channel. To identify flaws or deviations from established standards within the implemented TLS code, a specialized tool known as TLS-Anvil can be utilized. This tool also verifies the compliance of TLS libraries with the specifications outlined in the Request for Comments documents published by the IETF. TLS-Anvil conducts numerous tests with a client/server configuration utilizing a specified TLS library and subsequently generates a report that details the number of successful tests. In this work, we exploit the results obtained from a selected subset of TLS-Anvil tests to generate rules used for anomaly detection in Suricata, a well-known signature-based Intrusion Detection System. During the tests, TLS-Anvil generates .pcap capture files that report all the messages exchanged. Such files can be subsequently analyzed with Wireshark, allowing for a detailed examination of the messages exchanged during the tests and a thorough understanding of their structure on a byte-by-byte basis. Through the analysis of the TLS handshake messages produced during testing, we develop customized Suricata rules aimed at detecting TLS anomalies that result from flawed implementations within the intercepted traffic. Furthermore, we describe the specific test environment established for the purpose of deriving and validating certain Suricata rules intended to identify anomalies in nodes utilizing a version of the OpenSSL library that does not conform to the TLS specification. The rules that delineate TLS deviations or potential attacks may subsequently be integrated into a threat detection platform supporting Suricata. This integration will enhance the capability to identify TLS anomalies arising from code that fails to adhere to the established specifications. Full article

In flight tests, to meet the requirements of consistent acquisition and storage of multiple targets, multiple systems, and multiple data types, various data types are processed into Pulse Code Modulation (PCM) data streams using PCM encoding for storage. Aiming at the requirement of real-time storage of high-bit-rate PCM data streams, a large-capacity storage system based on Serial Advanced Technology Attachment 3.0 (SATA3.0) is designed. The system uses the Kintex 7 series Field-Programmable Gate Array (FPGA) as the control core, receives PCM data streams through the Low-Voltage Differential Signaling (LVDS) low-voltage differential interface, stores the received PCM data streams into the mSATA disk via the SATA3.0 transmission bus, and transmits the stored data back to the host computer through the USB3.0 interface for analysis. Meanwhile, to solve the problem of complex data export, the storage system constructs a FAT32 file system through the MicroBlaze soft core to optimize the management and operation of the large-capacity storage system. Test results show that the storage system can perform stable high-rate storage at −40 °C~80 °C. Full article

Background/Objectives: Keratoconus, a condition in which the cornea becomes thinner and steeper, can cause visual problems, particularly when it is progressive. Early diagnosis is important for preserving visual acuity. Raw data, unlike preprocessed data, are unaffected by software modifications. They retain their native structure across versions, providing consistency for analytical purposes. The objective of this study was to design a deep learning-based graphical user interface for predicting the corneal ectasia score using raw optical coherence tomography data. Methods: The graphical user interface was developed using Tkinter, a Python library for building graphical user interfaces. The user is allowed to select raw data from the cornea/anterior segment optical coherence tomography Casia2, which is generated in the 3dv format, from the local system. To view the predicted corneal ectasia score, the user must determine whether the selected 3dv file corresponds to the left or right eye. Extracted optical coherence tomography images are cropped, resized to 224 × 224 pixels and processed by the modified EfficientNet-B0 convolutional neural network to predict the corneal ectasia score. The predicted corneal ectasia score value is displayed along with a diagnosis: ‘No detectable ectasia pattern’ or ‘Suspected ectasia’ or ‘Clinical ectasia’. Performance metric values were rounded to four decimal places, and the mean absolute error value was rounded to two decimal places. Results: The modified EfficientNet-B0 obtained a mean absolute error of 6.65 when evaluated on the test dataset. For the two-class classification, it achieved an accuracy of 87.96%, a sensitivity of 82.41%, a specificity of 96.69%, a positive predictive value of 97.52% and an F1 score of 89.33%. For the three-class classification, it attained a weighted-average F1 score of 84.95% and an overall accuracy of 84.75%. Conclusions: The graphical user interface outputs numerical ectasia scores, which improves other categorical labels. The graphical user interface enables consistent diagnostics, regardless of software updates, by using raw data from the Casia2. The successful use of raw optical coherence tomography data indicates the potential for raw optical coherence tomography data to be used, rather than preprocessed optical coherence tomography data, for diagnosing keratoconus. Full article

This study evaluated the effect of clockwise reciprocation motion used in the original Optimum Torque Reverse kinematics, compared with clockwise continuous rotation, on the cyclic fatigue strength of nickel–titanium rotary instruments (NiTi) with different metallurgical characteristics. A total of 120 instruments, ProFile and EndoSequence in sizes 25/.04, 30/.04, and 35/.04, were tested under continuous rotation or reciprocation motions (n = 10 per subgroup). Instruments were examined by optical and scanning electron microscopy to exclude manufacturing defects. Phase transformation temperatures were determined by differential scanning calorimetry, and cyclic fatigue testing was conducted using a custom device simulating a curved canal with a 6 mm radius and an 86° curvature. The time to fracture was recorded, and the number of cycles to fracture was calculated. Statistical comparisons were performed using the Mann–Whitney U test with a significance level of p < 0.05. Differential scanning calorimetry showed that ProFile instruments were fully austenitic at the test temperature, while EndoSequence instruments exhibited a mixed R-phase and austenitic structure. Clockwise reciprocation motion significantly increased cyclic fatigue resistance in all groups compared with clockwise continuous rotation. Time to fracture increased by 241.3% to 337.5%, and EndoSequence instruments consistently demonstrated higher fatigue resistance. The greatest relative improvement was observed in ProFile 35/.04, with a 422.4% increase in the number of cycles to fracture. Overall, the reciprocation motion markedly enhanced cyclic fatigue strength irrespective of metallurgical phase composition, indicating a practical mechanical benefit that may reduce the risk of instrument separation during endodontic procedures. Full article

Background and Objectives: The anatomically demanding structure of curved root canals increases the technical difficulty of retreatment procedures. This study aimed to evaluate the retreatment efficacy of various rotary and reciprocating instruments in curved root canals obturated with cold and warm techniques regarding root canal filling material removal, apical transportation, and retreatment time. Materials and Methods: Sixty-four curved mesial root canals of mandibular molars with Vertucci type IV morphology were prepared using the ProTaper Gold system and obturated with AH Plus sealer using either the single-cone (SC) (n = 32) or continuous wave vertical compaction (CWC) (n = 32) technique. Each group was divided into four subgroups (n = 8) and retreated using MicroMega Remover (MM Remover), ProTaper Universal Retreatment (PTUR), Reciproc (Rec), and Hedstrom file systems. Micro-computed tomography was used to assess residual filling material volume and apical transportation. The time required for retreatment was recorded. The level of statistical significance was set at p < 0.05. Results: Across both obturation techniques, the MM Remover and PTUR groups demonstrated shorter retreatment times compared with the CWC–Hedstrom group (p < 0.05). No statistically significant differences were observed among the file systems in terms of filling material removal and apical transportation (p > 0.05). Conclusions: All tested instruments effectively preserved root canal anatomy within clinically acceptable apical transportation limits. The MM Remover and PTUR systems achieved significantly shorter retreatment times, indicating clinical advantages in efficiency. None of the evaluated systems achieved complete removal of the filling materials in either obturation technique. This study provides one of the first comparative evaluations of the MM Remover system, supporting its applicability in complex canal configurations. Full article

Sports mouthguards play a crucial role in preventing orofacial injuries. Vacuum thermoforming with ethylene-vinyl acetate is the most common fabrication method; however, digital workflows and 3D printing have introduced promising alternatives. This in vitro study aimed to compare mouthguards produced by vacuum thermoforming and 3D printing in terms of precision, trueness and impact resistance. A maxillary plaster model was used to fabricate two groups: thermoformed mouthguards (GTherm, n = 3; Playsafe Triple Light, Erkodent™) and 3D-printed mouthguards (GPrint, n = 3; high-impact polystyrene via fused deposition modeling). The internal surfaces were scanned with a Medit T500, and precision and trueness were assessed by superimposing STL files using Geomagic software. Ten specimens of each material underwent Charpy impact testing. Data were analyzed with GraphPad Prism. The GPrint group exhibited higher precision (median RMS = 57.8 µm) than GTherm (median RMS = 812 µm), although the difference was not statistically significant (p = 0.10). Trueness in GPrint was within acceptable limits (median RMS = 118 µm). In the Charpy test, impact strength was significantly higher in thermoformable-based specimens than in printed ones (mean 17.33 ± 1.96 vs. 14.33 ± 0.65 kJ/m², respectively). Within the study’s limitations, 3D-printed HIPS mouthguards showed superior precision and acceptable trueness, whereas thermoformed mouthguards demonstrated significantly greater impact resistance. Full article