Search Results (3,674)

The transformation of trade structures represents a core dimension of economic integration in Central and Eastern Europe, particularly following EU accession and deeper participation in global value chains. Romania and Poland, despite similar institutional frameworks, have exhibited distinct trade trajectories in terms of specialisation patterns, intra–industry trade intensity and external balance. Understanding these differences is essential for assessing the quality of integration, competitiveness and structural upgrading in emerging European economies. Existing empirical studies often focus on single indicators or shorter time horizons, leaving room for a comprehensive, long–run comparative assessment based on multiple trade dimensions. The purpose of this article is to compare the evolution of trade specialisation, intra–industry trade and trade balance in Romania and Poland over the period 2002–2024. The study aims to identify similarities and divergences in their trade structures and to evaluate whether trade expansion has been accompanied by qualitative improvements and external rebalancing. By adopting a comparative perspective, the article seeks to contribute to the literature on trade integration and structural transformation in Central and Eastern Europe. The analysis is based on annual sectoral data on imports and exports for Romania and Poland covering the period 2002–2024. Three complementary indicators are employed: a symmetric Balassa–type revealed comparative advantage index (RSCA), the Grubel–Lloyd intra–industry trade index, and an export–import coverage ratio used as a proxy for sectoral trade balance. Descriptive analysis is complemented by linear trend estimation and structural break tests in order to capture long–run dynamics and identify major shifts associated with EU accession and post–crisis adjustments. The results show that while both countries experienced substantial trade expansion, Poland achieved a significantly stronger qualitative outcome, characterised by higher intra–industry trade intensity and convergence towards aggregate trade balance by 2024. Romania, although recording improvements in trade composition, maintained a persistent trade deficit. The article adds value by providing a long–run, indicator–based comparative framework that integrates specialisation, intra–industry trade and external balance into a single empirical analysis. Full article

In this paper, a new type of soft group called the soft symmetric difference group (SSD-group) is introduced and systematically developed. This structure is constructed by integrating soft set theory with group theory through the symmetric difference operation and set inclusion. Fundamental concepts such as characteristic soft symmetric difference groups, soft symmetric difference subgroups, normal soft symmetric difference subgroups, soft normalizers, and soft cosets are defined, and their essential algebraic properties are investigated. Several characterizations of soft normality are also established through these concepts. Various axiomatic results are obtained, providing necessary and sufficient conditions for a soft set to form an SSD-group. Furthermore, soft quotient (factor) groups of SSD-groups are introduced and their structural properties are examined in detail. The relationship between SSD-group theory and classical group theory is also established through several corresponding concepts. Illustrative examples are provided to demonstrate the applicability and internal consistency of the proposed framework. Overall, the results obtained in this study extend existing soft group structures and contribute to the development of algebraic theory within the context of soft sets, while also providing a foundation for further generalizations to other algebraic frameworks such as semigroups, rings, and fields. Full article

Pyrrole derivatives are natural organic molecules that are important to the pharmaceutical industry due to their occurrence in nature and their use in a wide range of medical applications. In general, non-symmetric, 1,2,5-triaryl-substituted pyrroles are prepared either by Paal–Knorr condensation or cycloaddition that present synthetic challenges particularly if late-stage functionalization is required. The present study describes a modular approach to synthesizing 1,2,5-triarylpyrroles containing three different arene substituents. Using pyrrole ester building blocks, a sequence of decarboxylative cross-coupling and C–H arylation provides unsymmetrical 1,2,5-triarylpyrroles in a regioselective, stepwise manner; the scope and limitations of the sequence are disclosed. Full article

Computational simulation is a valuable tool for advancing personalized ergonomics. This study evaluated the ability of musculoskeletal simulation to estimate individual lumbar loading during manual lifting tasks representative of construction activities. Fifty-six Colombian adults were recruited to reflect national anthropometric distributions and grouped by BMI and stature. Participants performed two standardized lifting tasks with a 10 kg load: symmetric lifting from the floor to xiphoid height and lateral lifting from a 0.40 m surface to shoulder height with contralateral transfer. Whole-body kinematics and ground reaction forces were processed in OpenSim software using the validated model to estimate L5–S1 compression and shear forces. Results showed a moderate association between lumbar compression and body weight, while shear forces exhibited low correlations with kinematic variables. Subject-specific scaled models revealed substantial inter-individual differences in lumbar loading related to lifting technique and anthropometric characteristics, highlighting the potential of musculoskeletal simulation for personalized risk assessment in construction. Full article

Harmonics and interharmonics have a significant impact on the safe operation of power systems, and accurately identifying interharmonics in power systems is the basis of harmonic suppression. The accuracy with which interharmonic components in power systems are detected is easily affected by mode aliasing and noise; to address this issue, a method of detecting them based on an adjusted Fourier-based synchrosqueezing transform (AFSST) and the three-point symmetric difference energy operator (DEO3S) is proposed. First, in order to reduce the influence of endpoint effects on detection accuracy, an improved waveform feature-matching extension method is utilized to reduce endpoint effects generated during the FSST decomposition process. Then, because it is difficult to adaptively determine the number of ridges in the FSST decomposition process, the energy difference and normalized cross-correlation coefficient are utilized as the criterion for determining the number of modal decompositions in the FSST, thereby improving the accuracy of the ridge number. Finally, using AFSST, the harmonic/interharmonic signals are decomposed into a set of intrinsic mode functions (IMFs). The instantaneous frequency and amplitude of each component are extracted using DEO3S, enabling the accurate detection of harmonics and interharmonics in the power system. Experimental analysis was conducted using simulation data, arc furnace experimental system data, and hardware experimental platform data. The results showed that the proposed method can accurately detect harmonic/interharmonic parameters under different levels of noise interference. Compared with the FSST, EMD, EEMD, and CEEMDAN methods, the amplitude detection accuracy of the proposed method is improved by 0.21%, 0.78%, 0.64%, and 0.75%, respectively, and the amplitude detection accuracy is improved by 1.39%, 3.31%, 2.04%, and 3.14%, respectively. Full article

Designing linear conveyor feeders with passive fences for automated part orientation remains largely trial and error because the final orientation distribution is difficult to predict reliably before physical testing. We present a simulation-driven deep learning pipeline that predicts the full distribution of final in-plane orientations for extruded, z-axis-symmetric parts interacting with linear feeders containing up to two straight or curved fences. Using Bullet physics-based simulation in CoppeliaSim, we generate 1048 main part–feeder samples across 38 part geometries, plus 78 fence generalization and 110 unseen part samples for a total of 1236 (41 unique parts), and train regression networks and a Variational Autoencoder, or VAE, to predict 360-bin orientation probability distributions. On known parts, the regression model achieves high accuracy on held-out test configurations, $R^2$ on circular CDFs $=0.97\pm 0.05$, and on unseen fence combinations, $R^2$ on circular CDFs = 0.89 ± 0.11. Generalization to previously unseen part geometries is more challenging, with $R^2$ on circular CDFs = 0.75 ± 0.18, indicating that geometric representation and dataset diversity are primary limitations. We also evaluate VAE reconstruction on datasets generated from simulations at different iteration counts: 5–100% of 1000 iterations in 5% increments. While within-level reconstruction remains high, cross-convergence evaluation shows that partial-iteration PMFs are far from fully converged labels in this dataset (overall CDF $R^2$ = 0.01 at 5%, 0.32 at 50%, and 0.87 at 75%), so reduced-iteration simulations do not substitute for full convergence here. Overall, the proposed approach provides a data-driven foundation for feeder analysis and design, with future work focusing on improved geometric generalization and physical validation for industrial deployment. Full article

Intelligence metrics based on benchmark performance or population norms are useful for measuring comparative ability within defined test environments, but they do not directly evaluate the structural coherence of an agent’s trajectory across time, domains, and perturbations. This article introduces Reflexive Signature Intelligence (RSI) as a bounded theoretical framework for addressing that different problem. RSI is developed within a causal-symmetric informational perspective in which intelligence is understood as the capacity of a system to maintain and restore alignment with a structurally constrained invariant without collapsing the open gradient of development. On this basis, the paper formulates the Principle of Bounded Subjectivity and the Prohibition of Finality as framework-level principles, arguing that intelligence should be assessed not as arrival at a completed end state but as the quality of an asymptotic trajectory. The framework is then operationalized on two coupled levels: a micro-level proposed as a future measurement program linked heuristically to resilience and prediction-error dynamics, and a macro-level expressed through five dimensions of structural integrity, including reflexive regulation, cross-domain integration, internal consistency, stabilization, and signature-setting. The article concludes by outlining implications for AI evaluation and alignment, with particular relevance for distinguishing full agents, partial systems, and human–AI composite configurations. Full article

Recently, the adaptive regularized proximal quasi-Newton (ARPQN) method has demonstrated a strong performance in solving composite optimization problems over the Stiefel manifold. However, its reliance on first-order information limits its applicability to scenarios where gradient and Hessian evaluations are unavailable or costly. In this paper, we propose a zeroth-order adaptive regularized proximal quasi-Newton method (ZO-ARPQN) for black-box composite optimization over Riemannian manifolds, particularly the Stiefel and symmetric positive definite (SPD) manifolds. The proposed method estimates the Riemannian gradient and curvature information through randomized one-point finite-difference approximations and adaptively updates a regularized quasi-Newton matrix to capture the local manifold geometry. Theoretically, we established global convergence and complex analyses under mild assumptions. More importantly, by incorporating curvature-aware regularization and random perturbations in the proximal quasi-Newton framework, we proved that ZO-ARPQN can escape strict saddle points with a high probability. This guarantees convergence to a stationary point, even in the absence of explicit gradients. Extensive numerical experiments were conducted on manifold-constrained problems, including sparse PCA and robot stiffness tuning. These demonstrated that ZO-ARPQN shows a competitive convergence behavior compared with other state-of-the-art Riemannian optimization methods, while requiring only function evaluations. Full article

In recent years, the refinement of bounding box representations has emerged as a major research focus in remote sensing. Nevertheless, mainstream detection algorithms typically ignore the disruptive impacts induced by the diverse morphologies and arbitrary orientations of high-aspect-ratio aerial objects throughout model training, thereby giving rise to several critical technical challenges: (1) Anisotropic information distribution: Target features are highly concentrated in one spatial dimension but sparse in the other, with significant feature differences across bounding box parameters, breaking the symmetry of feature distribution. (2) Missing high-quality positive samples: IoU-based assignment strategies fail to adequately capture the symmetric structural characteristics of elongated targets, resulting in incomplete coverage of critical features. (3) Loss function gradient instability: Small deviations in large-aspect-ratio bounding boxes cause drastic loss value fluctuations, as the asymmetric gradient changes hinder stable optimization directions during training. To address the challenges, we propose a Spatial Orthogonal and Boundary-Aware Network (SOBA-Net) for rotated and elongated target detection, leveraging symmetry-aware designs to enhance feature representation. Specifically, spatial staggered convolutions are constructed to fuse local and directional contextual features, effectively modeling long-range symmetric information across multiple spatial scales and reducing background noise interference. Secondly, the designed Symmetric-Constrained Label Assignment (SC-LA) introduces an IoU-weighted function, ensuring high-quality samples with symmetric structural features are classified as positive samples. Ultimately, the designed Gradient Dynamic Equilibrium Loss Function mitigates the problem of unstable gradients associated with high-aspect-ratio objects by enforcing symmetrical gradient regulation across samples with negligible localization deviations. Comprehensive evaluations across three representative remote sensing benchmarks—DOTA, UCAS-AOD, and HRSC2016—sufficiently corroborate the superiority of symmetry-aware enhancement schemes, which boast straightforward implementation and efficient inference deployment. Full article

Polymer electrolytes have been explored as an alternative to conventional aqueous electrolytes in zinc-ion batteries, particularly for flexible and wearable applications. Despite the increasing interest in polymer electrolyte-based zinc-ion batteries (ZIBs), their development is still in its early stages due to various challenges. In this study, we investigated three promising polymer electrolytes: CSAM (carboxyl methyl chitosan with acrylamide monomer), PAM (polyacrylamide monomer hydrogel electrolyte), and p-PBI (phosphate-doped polybenzimidazole solid electrolyte) with Zn(ClO₄)₂ and Zn(OTf)₂, as electrolytes for zinc-ion batteries. The p-PBI solid electrolyte showed high mechanical stability and improved resistance to short-circuiting during cycling. The presence of carboxyl groups in CSAM and the existence of O-H bonding facilitated ion movement, resulting in enhanced ionic conductivity and preventing dendrite formation. Incorporating these hydrogels with high-performance zinc salts, such as zinc triflate (Zn(OTf)₂), resulted in stable symmetric cell cycling over 4000 h with a uniform voltage profile under 1 mA/cm² and a low overpotential of around 53 mV cycling with CSAM. Rate-dependent full-cell testing showed that the PBI solid electrolyte delivers higher capacity retention at different current densities, whereas CSAM exhibits markedly better long-term stability, even at low voltages, owing to its effective dendrite suppression, which helps preserve cathode performance over extended cycling. Full article

In this study, we evaluated the performance of the Advanced Encryption Standard (AES)-128, AES-256, and Blowfish algorithms on WearOS for messages ranging from 8 to 128 bytes, which are typical message sizes for contemporary smartwatch applications. Using a WearOS emulator, we measured encryption time, memory usage, central processing unit (CPU) utilization, and battery consumption across 16 messages sizes with 10 repetitions over each configuration. The AES-128 algorithm consistently outperformed the others with approximately 1.0 ms of encryption time at 128 bytes, less than 6 KB memory, and less than 39% peak CPU utilization. The AES-256 algorithm added 25–30% processing overhead and higher energy consumption with negligible extra memory cost. The Blowfish algorithm consumed approximately three times more memory and exhibited the highest battery consumption per operation. It also scales poorly due to its 64-bit block size and large key scheduling approach. In addition, all performance differences are highly statistically significant (p < 0.001). Given the widespread hardware AES acceleration on WearOS devices and memory constraints, AES-128 is recommended as the default symmetric encryption algorithm for confidentiality in smartwatch applications. Full article

The scarcity of global wind field data limits the accuracy of numerical weather prediction. The currently operational spaceborne Doppler lidar (the European Space Agency’s Aeolus) measures only a single line-of-sight (LOS) wind component, which leads to discrepancies between the measured results and the real wind field. The systems of the United States and Japan have provided additional LOS wind measurements. Yet residual errors in correcting for the satellite’s own velocity can still degrade the accuracy of the retrieved wind vectors. To enhance the accuracy and timeliness of global wind observations, we propose a dual-spaceborne Doppler lidar wind measurement system. Two satellite orbits with different inclinations each provide a LOS wind; combining these components at each crossover yields the horizontal wind vector. Thereby, within 12 h, the crossovers blanket the globe, yielding a global horizontal wind-vector field. Orbital simulations show that inclinations summing to 180° produce the most uniform crossover-point distribution. As Satellite-1’s inclination (prograde orbit) increases, the latitudinal coverage of crossover points expands accordingly. The preferred configuration is when the two satellites have inclinations of 70° and 110°, respectively. Their ground tracks cover nearly all major global landmasses, with a symmetrical distribution of intersection points and a balanced grid resolution. As satellite technology further matures, this dual-spaceborne approach is expected to supplement global horizontal wind-field data. Full article

Background and Objectives: Anterior cruciate ligament (ACL) reconstruction (ACLR) is widely performed to restore knee stability and facilitate return to activity. However, recovery of muscle strength, balance, functional performance, and patient-reported outcomes does not occur uniformly over time. The longitudinal recovery trajectory across various functional areas during the first year after ACLR remains insufficiently characterized. Materials and Methods: We included 107 patients who underwent isolated unilateral ACLR using a hamstring autograft. Isokinetic knee extensor and flexor strength, postural stability, Y-Balance Test (YBT) performance, and subjective knee function scores were assessed post-injury (approximately six weeks after ACL injury and prior to ACLR) and at 3, 6, and 12 months postoperatively. All patients followed a standardized postoperative rehabilitation protocol. Results: Knee extensor strength deficit worsened at 3 months and remained present at 12 months. In contrast, knee flexor strength deficit decreased progressively and reached near-symmetrical values by 12 months. Sway path length decreased significantly over time in both limbs. In the operated limb, improvements plateaued after 6 months, and limb symmetry indices approached symmetry by 12 months. YBT limb symmetry indices demonstrated a non-linear recovery pattern. Anterior, posterolateral, and composite scores decreased at 3 months, recovered to post-injury levels by 6 months, and showed significant improvement at 12 months. Posteromedial reach did not decline at 3 months and improved significantly only at 12 months. Subjective knee function scores (Lysholm and IKDC) did not differ significantly between post-injury and 3-month assessments, but improved significantly from 6 months onward. Tegner activity scores gradually increased and returned to pre-injury levels by 12 months. Conclusions: Recovery after ACLR is prolonged and non-synchronous. Quadricep strength remains incompletely restored at 12 months, whereas hamstring strength recovers more favorably. Balance, functional performance, and subjective outcomes improve mainly after 6 months. These findings support the need for prolonged rehabilitation and serial, multidimensional functional assessments beyond time-based criteria. Full article

High-performance difference patterns (DPs) are critical for compact and integrated microwave array systems, particularly in monopulse tracking and beam-scanning applications. However, the design of monopulse phased arrays with steep slopes, high directivity, low sidelobes, and symmetric main lobes remains challenging due to constraints imposed by the array aperture and radome structure. In this paper, a novel design method is proposed to maximize the DP directivities for monopulse linear and planar phased arrays composed of microstrip patch antennas. The DP synthesis problem is first formulated as a nonconvex optimization model for directivity maximization. By fixing the reference phase of the DP slope and applying a first-order Taylor expansion of the quadratic function, the original problem is decomposed into a sequence of convex subproblems that can be solved efficiently. The proposed method fully exploits the flexibility of the phased array feed network, enabling directivity enhancement without altering the geometric configuration of the monopulse array. Finally, three numerical examples employing a radome-enclosed linear array, a uniform planar array, and a radome-enclosed planar array are presented to demonstrate the effectiveness of the proposed method in achieving the monopulse array DP synthesis with high directivity and symmetric main lobes. Full article

Objective: External apical root resorption is a frequent complication of orthodontic treatment, and the response of endodontically treated teeth remains controversial. This study aimed to compare external apical root resorption (EARR) in endodontically treated teeth and vital teeth following fixed orthodontic treatment in patients with Angle Class I, II, and III malocclusions using digital panoramic radiography. Methods: This retrospective longitudinal study included 60 patients (mean age: 16.3 ± 2.4 years) who underwent non-extraction fixed orthodontic treatment. A paired contralateral within-subject design was used, whereby each patient contributed one endodontically treated tooth and its symmetrical untreated vital counterpart. Root length was measured on calibrated panoramic radiographs obtained before (T0) and after treatment (T1). Differences were analyzed using the Wilcoxon signed-rank and Kruskal–Wallis tests (p < 0.05). Results: Both endodontically treated and vital teeth exhibited statistically significant reductions in root length between T0 and T1 (mean reduction: 1.02 ± 1.36 mm and 1.11 ± 1.79 mm, respectively; p < 0.001). No significant difference was observed between the two tooth types regarding the magnitude of resorption. Similarly, no significant differences were detected among Angle Class I, II, and III malocclusion groups. The observed mean reduction of approximately 1 mm suggests limited apical shortening within the range generally considered clinically moderate. Conclusions: Endodontically treated teeth exhibited a degree of EARR comparable to that of vital teeth following fixed orthodontic treatment, suggesting that properly treated endodontic teeth do not pose an increased risk of clinically relevant apical root resorption during orthodontic therapy. Full article