Search Results (218)

This paper establishes some links between Sturm–Liouville problems and the well-known controllability property in linear dynamic systems, together with a control law design that allows any prefixed arbitrary final state finite value to be reached via feedback from any given finite initial conditions. The scheduled second-order dynamic systems are equivalent to the stated second-order differential equations, and they are used for analysis purposes. In the first study, a control law is synthesized for a forced time-invariant nominal version of the current time-varying one so that their respective two-point boundary values are coincident. Afterward, the parameter that fixes the set of eigenvalues of the Sturm–Liouville system is replaced by a time-varying parameter that is a control function to be synthesized without performing, in this case, any comparison with a nominal time-invariant version of the system. Such a control law is designed in such a way that, for given arbitrary and finite initial conditions of the differential system, prescribed final conditions along a time interval of finite length are matched by the state trajectory solution. As a result, the solution of the dynamic system, and thus that of its differential equation counterpart, is subject to prefixed two-point boundary values at the initial and at the final time instants of the time interval of finite length under study. Also, some algebraic constraints between the eigenvalues of the Sturm–Liouville system and their evolution operators are formulated later on. Those constraints are based on the fact that the solutions corresponding to each of the eigenvalues match the same two-point boundary values. Full article

To solve the fundamental problem of excessive consumption of classical resources and the simultaneous security vulnerabilities in semi-quantum dialogue systems, a multi-party controlled semi-quantum dialogue protocol based on hyperentangled Bell states is proposed. A single controlling party is vulnerable to information compromise due to tampering or betrayal; the multi-party controlled mechanism (Charlie₁ to Charlie_n) in this protocol establishes a distributed trust model. It mandates collective authorization from all controlling parties, significantly enhancing its robust resilience against untrustworthy controllers or collusion attacks. The classical participant Bob uses an adaptive Huffman compression algorithm to provide a framework for information transmission. This encoding mechanism assigns values to each character by constructing a Huffman tree, generating optimal prefix codes that significantly optimize the storage space complexity for the classical participant. By integrating the “immediate measurement and transmission” mechanism into the multi-party controlled semi-quantum dialogue protocol and coupling it with Huffman compression coding technology, this framework enables classical parties to execute encoding and decoding operations. The security of this protocol is rigorously proven through information-theoretic analysis and shows that it is resistant to common attacks. Furthermore, even in the presence of malicious controlling parties, this protocol robustly safeguards secret information against theft. The efficiency analysis shows that the proposed protocol provides benefits such as high communication efficiency and lower resource consumption for classical participants. Full article

Low Earth orbit (LEO) satellites offer a revolutionary potential for positioning, navigation, and timing (PNT) services due to their stronger signal power and rapid geometric changes compared to traditional global navigation satellite systems (GNSS). However, dedicated LEO navigation systems face high costs, so opportunity navigation based on LEO satellites is a potential solution. This paper presents an orthogonal frequency division multiplexing (OFDM)-based LEO navigation system and analyzes its navigation performance. We use 5G new radio (NR) as the satellite transmitting signal and introduce the NR signal components that can be used for navigation services. The LEO NR system and a novel zero-padding correlation (ZPC) are introduced. This ZPC receiver can eliminate cyclic prefix (CP) and inter-carrier interference, thereby improving tracking accuracy. The power spectral density (PSD) for the NR navigation signal is derived, followed by a comprehensive analysis of tracking accuracy under different NR configurations (bandwidth, spectral allocation, and signal components). An extended Kalman filter (EKF) is proposed to fuse pseudorange and pseudorange rate measurements for real-time positioning. The simulations demonstrate an 80% improvement in ranging precision (3.0–4.5 cm) and 88.3% enhancement in positioning accuracy (5.61 cm) compared to conventional receivers. The proposed ZPC receiver can achieve centimeter-level navigation accuracy. This work comprehensively analyzes the navigation performance of the LEO NR system and provides a reference for LEO PNT design. Full article

This paper presents a comprehensive synchronic and diachronic analysis of the Sino-Vietnamese negative prefixes bất (Chinese 不 bù), vô (無 wú), and phi (非 fēi), examining their historical development and modern usage in Vietnamese, with a comparative perspective on their Chinese equivalents. By investigating the interaction between these prefixes and Vietnamese sentential negators—such as the native chẳng and the Chinese-derived không—the study explores the evolution of negation in Vietnamese over several centuries. The research draws on a corpus of three bilingual Classical Chinese–Vietnamese translations of Confucius’s Analects from the 17th, 19th, and 21st centuries, two written in traditional Nôm script and one in the modern Quốc ngữ alphabet. This corpus provides valuable insights into linguistic shifts driven by language contact in Vietnam. The findings reveal that in the 17th century, the Sino-Vietnamese prefixes bất, vô, and phi were largely absent, with native chẳng dominating. By the 19th century, chẳng persisted, but không emerged as a sentential negator, and bất appeared, both reflecting Chinese forms and demonstrating innovative uses. In the 21st century, không became the dominant negator, with bất and vô seeing increased usage, reflecting broader trends of linguistic modernization. This study situates these changes within the broader context of 20th-century East Asian literacy expansion, where Japan played a pivotal role in disseminating modernized Chinese-based vocabulary. By examining the selective adaptation and integration of Sino-Vietnamese elements, this paper contributes to a deeper understanding of language contact, syntactic influence, and lexical innovation in the evolving Vietnamese lexicon. Full article

High-precision indoor positioning technology is increasingly prominent in its application value in emerging fields such as the Industrial Internet of Things, smart cities, and autonomous driving. 5G networks can transmit large-bandwidth signals and have the capability to transmit and receive signals with multiple antennas, enabling the simultaneous acquisition of angle and distance observation information, providing a solution for high-precision positioning. Differences in the types and quantities of observation information in complex environments lead to positioning scenarios having a multimodal nature; how to propose an effective observation model that covers multimodal scenarios for high-precision robust positioning is an urgent problem to be solved. This paper proposes a three-stage time–frequency synchronization method based on group peak time sequence tracing. Timing coarse synchronization is performed through a group peak accumulation timing coarse synchronization algorithm for multi-window joint estimation, frequency offset estimation is based on cyclic prefixes, and finally, fine timing synchronization based on the primary synchronization signal (PSS) sliding cross-correlation is used to synchronize 5G signals to chip-level accuracy. Then, a tracking loop is used to track the Positioning Reference Signal (PRS) to within-chip accuracy, obtaining accurate distance information. After obtaining distance and angle information, a high-precision positioning method for multimodal scenarios based on 5G heterogeneous measurement combination is proposed. Using high-precision angle observation values as intermediate variables, this algorithm can still solve a closed-form positioning solution under sparse observation conditions, enabling the positioning system to achieve good positioning performance even with limited redundant observation information. Full article

This study offers a detailed comparative analysis of the reflexes of Proto-Bantu noun class prefixes within nine Gabonese languages belonging to the B50, B60, and B70 groups of Guthrie’s referential inventory of the Bantu languages. Genealogically speaking, all of them are part of the Kwilu-Ngounie subclade of the Bantu family’s West-Coastal Bantu branch. Starting out from a robust dataset comprising over 4000 lexical items collected through fieldwork and existing descriptions, the Comparative Method is used to distinguish changes in noun class morphology due to regular sound shifts from those emerging from analogical reanalysis and levelling. The comparative study shows a systematic reduction and reorganization of the inherited Proto-Bantu noun class system, notably the loss of classes 12/13 and 19 across all languages, variable retention and loss of classes 7/8 and 11, and complex patterns of reshuffling involving classes 5, 9/10, and 1/2. Key innovations, potentially reinforcing lexicon-based hypotheses of phylogenetic subgrouping within Kwilu-Ngounie, include the development of a class 7 allomorphy conditioned by stem-initial segments in the B50 languages and the emergence of vocalic prefixes restricted to the B60 and B70 languages. Full article

The Automatic Modulation Classification (AMC) for underwater acoustic signals enables more efficient utilization of the acoustic spectrum. Deep learning techniques significantly improve classification performance. Hence, they can be applied in AMC work to improve the underwater acoustic (UWA) communication. This paper is based on the adoption of Hough Transform (HT) and Edge Detection (ED) to enhance modulation classification, especially for a small dataset. Deep neural models based on basic Convolutional Neural Network (CNN), Visual Geometry Group-16 (VGG-16), and VGG-19 trained on constellation diagrams transformed using HT are adopted. The objective is to extract features from constellation diagrams projected onto the Hough space. In addition, we use Orthogonal Frequency Division Multiplexing (OFDM) technology, which is frequently utilized in UWA systems because of its ability to avoid multipath fading and enhance spectrum utilization. We use an OFDM system with the Discrete Cosine Transform (DCT), Cyclic Prefix (CP), and equalization over the UWA communication channel under the effect of estimation errors. Seven modulation types are considered for classification, including Phase Shift Keying (PSK) and Quadrature Amplitude Modulation (QAM) (2/8/16-PSK and 4/8/16/32-QAM), with a Signal-to-Noise Ratio (SNR) ranging from −5 to 25 dB. Simulation results indicate that our CNN model with HT and ED at perfect channel estimation, achieves a 94% classification accuracy at 10 dB SNR, outperforming benchmark models by approximately 40%. Full article

This paper proposes a generalized maximum access delay time (MADT) estimation method for orthogonal frequency division multiplexing (OFDM) systems operating over multipath fading channels. The proposed approach derives a novel log-likelihood ratio (LLR) formulation by exploiting the correlation characteristics introduced by the cyclic prefix (CP) in received OFDM symbols, thereby enabling the efficient approximation of the maximum likelihood (ML) MADT estimation. A key contribution of this study is represented by the unification and generalization of existing MADT estimation methods by explicitly formulating the bias term associated with the geometric mean. Within this framework, a previously reported scheme is shown to be a special case of the proposed method. The effectiveness of the proposed MADT estimator is evaluated in terms of correct and good detection probabilities, illustrating not only improved detection accuracy but also robustness across varying channel conditions, in comparison with existing methods. Furthermore, the estimator is applied to both noise-canceling channel estimation (NCCE) and time-domain least squares (TDLS) methods, and its practical effectiveness is verified in IEEE 802.11p/OFDM system scenarios relevant to vehicle-to-everything (V2X) communications. Simulation results confirm that when integrated with NCCE and TDLS, the proposed estimator closely approaches the performance bound of ideal MADT estimation. Full article

Satellite Internet is the key to integrated air–space–ground communication, while the design of waveforms with high spectrum efficiency is an intrinsic requirement for high-speed data transmission in satellite Internet. Time-domain synchronous orthogonal frequency division multiplexing (TDS-OFDM) technology can significantly improve spectrum utilization efficiency by using PN sequences instead of traditional CP cyclic prefixes. However, it also leads to time-domain aliasing between PN sequences and data symbols, posing a serious challenge to channel estimation. To solve this problem, a compressive sensing-based coding iterative channel estimation method for the TDS-OFDM system is proposed in this paper. This method innovatively combines compressive sensing channel estimation technology with the Reed–Solomon low-density parity-check cascade coding (RS-LDPC) scheme, and achieves performance improvements as follows: (1) Construct the iterative optimization mechanism for the compressive sensing algorithm and equalization feedback loop. (2) RS-LDPC cascaded coding is employed to enhance the anti-interference and error correction capability of system. (3) Design the recoding link of error-corrected data to improve the accuracy of sensing matrix. The simulation results demonstrate that compared with conventional methods, the proposed method can obviously converge on the mean squared errors (MSEs) of channel estimation and significantly reduce the bit error rate (BER) of the system. Full article

This paper presents a highly linear two-stage InGaP/GaAs power amplifier integrated circuit (PAIC) using a dynamic predistorter for 5G small-cell applications. The proposed predistorter, based on a diode-connected transistor, utilizes a supply voltage to accurately control the linearization characteristics by adjusting its dc current. It is connected in parallel with an inter-stage of the two-stage PAIC through a series configuration of a resistor and an inductor, and features a shunt capacitor at the base of the transistor. These passive components have been optimized to enhance the linearization performance by managing the RF signal’s coupling to the diode. Using these optimized components, the AM−AM and AM−PM nonlinearities arising from the nonlinear resistance and capacitance in the diode can be effectively used to significantly flatten the AM−AM and AM−PM characteristics of the PAIC. The proposed predistorter was applied to the 2.6 GHz two-stage InGaP/GaAs HBT PAIC. The IC was tested using a 5 × 5 mm² module package based on a four-layer laminate. The load network was implemented off-chip on the laminate. By employing a continuous-wave (CW) signal, the AM−AM and AM−PM characteristics at 2.55–2.65 GHz were improved by approximately 0.05 dB and 3°, respectively. When utilizing the new radio (NR) signal, based on OFDM cyclic prefix (CP) with a signal bandwidth of 100 MHz and a peak-to-average power ratio (PAPR) of 9.7 dB, the power-added efficiency (PAE) reached at least 11.8%, and the average output power was no less than 24 dBm, achieving an adjacent channel leakage power ratio (ACLR) of −40.0 dBc. Full article

Background: Digital twin (DT) technology, integrated with artificial intelligence (AI) and machine learning (ML), holds significant potential to transform oncology care. By creating dynamic virtual replicas of patients, DTs allow clinicians to simulate disease progression and treatment responses, offering a personalized approach to cancer treatment. Aim: This narrative review aimed to synthesize existing review studies on the application of digital twins in oncology, focusing on their potential benefits, challenges, and ethical considerations. Methods: The narrative review of reviews (NRR) followed a structured selection process using a standardized checklist. Searches were conducted in PubMed and Scopus with a predefined query on digital twins in oncology. Reviews were prioritized based on their synthesis of prior studies, with a focus on digital twins in oncology. Studies were evaluated using quality parameters (clear rationale, research design, methodology, results, conclusions, and conflict disclosure). Only studies with scores above a prefixed threshold and disclosed conflicts of interest were included in the final synthesis; seventeen studies were selected. Results and Discussion: DTs in oncology offer advantages such as enhanced decision-making, optimized treatment regimens, and improved clinical trial design. Moreover, economic forecasts suggest that the integration of digital twins into healthcare systems may significantly reduce treatment costs and drive growth in the precision medicine market. However, challenges include data integration issues, the complexity of biological modeling, and the need for robust computational resources. A comparison to cutting-edge research studies contributes to this direction and confirms also that ethical and legal considerations, particularly concerning AI, data privacy, and accountability, remain significant barriers. Conclusions: The integration of digital twins in oncology holds great promise, but requires careful attention to ethical, legal, and operational challenges. Multidisciplinary efforts, supported by evolving regulatory frameworks like those in the EU, are essential for ensuring responsible and effective implementation to improve patient outcomes. Full article

Psychology is a core discipline in understanding why and how individuals choose to engage in sustainable action. This paper uses social representations theory to explore the rising use of eco/green prefixes for psychology concepts through a critical analysis of the concept of eco/green fatigue. It argues that this term, which originated in the world of popular online news media, has typically been treated in academic psychology discussions using existing psychology concepts in the same way as eco-anxiety and eco-grief, which hides important features of the phenomenon that need to be better understood. The paper presents an analysis of eco-fatigue based on a critical review of the existing psychology literature, qualitative online archival analyses, and an exploratory quantitative survey study. The survey study was conducted with a sample of 182 students and non-students and analysed using principal components and cluster analysis. The paper provides evidence that simply adding an eco/green prefix to an existing psychology concept without a systematic empirical investigation into the phenomenon can result in overly simplistic conceptual frameworks that do not lead to sound practical conclusions. A preliminary empirical examination of the social representation of eco-fatigue in the public arena suggested that inappropriate sustainability messaging and bad business behaviour may be more of a barrier to sustainability action than the beliefs or attitudes held by individuals. Full article

The Movement Disorders Society recommends the DYT/PARK prefix for genes where dystonia and parkinsonism are prominent in approximately half or more of patients. This systematic review explores the genotype–phenotype correlations of GLB1, SLC6A3, SLC30A10, PLA2G6, and SLC39A14—recently classified as DYT SLC39A14 and historically linked to dystonia-parkinsonism. We searched PubMed and the Human Gene Mutation Database using standardized terms, including English-language, peer-reviewed publications up to February 2024. Following the MDSGene protocol, we extracted individual-level data on patients with biallelic pathogenic variants and at least one movement disorder. Features were marked “missing” if not explicitly reported. Of 1828 articles, 128 were eligible. We identified 386 patients and 262 variants. The median age at onset was 3 years for GLB1, 3 months for SLC6A3, 2.5 years for SLC30A10, 1.5 years for SLC39A14, and 16 years for PLA2G6. Missing data may reflect underreporting of negative findings. Case reports/serie, may bias toward atypical presentations. Our analysis showed dystonia-parkinsonism predominates in SLC6A3 and PLA2G6, while GLB1, SLC30A10, and SLC39A1 show predominantly dystonic phenotypes with a low frequency of parkinsonism. Ataxia was common in GLB1 and PLA2G6. Awareness of these phenotypes is essential for early diagnosis and intervention, particularly in treatable conditions like SLC30A10 or SLC39A14. The predominantly dystonic phenotype in GLB1, SLC30A10, and SLC39A14 suggest that the DYT prefix may be more appropriate, highlighting the need to reconsider their nomenclature, and the importance of systematic reviews. Full article

Modern large language models (LLMs) achieve state-of-the-art performance through architectural advancements but require high computational costs for inference. Post-training quantization is a widely adopted approach to reduce these costs by quantizing weights and activations to lower precision, such as INT8. However, we identify a critical challenge in activation quantization for GLU (Gated Linear Unit) variants, which are commonly used in the feed-forward networks of modern LLMs like the LLaMA family. Specifically, severe local quantization errors arise due to excessively large activation magnitudes, which we refer to as activation spikes, leading to significant degradation in model performance. Our analysis reveals a systematic pattern of these spikes: they predominantly occur in the FFN (feed-forward network) layers at the early and late layers of the model and are concentrated on a small subset of tokens rather than being uniformly distributed across a token sequence. To mitigate this issue, we propose two empirical methods: Quantization-free Module (QFeM) and Quantization-free Prefix (QFeP), which isolate activation spikes during quantization. Extensive experiments demonstrated that our methods effectively improve activation quantization, particularly in coarse-grained quantization schemes, enhancing the performance of LLMs with GLU variants and addressing the limitations of existing quantization techniques. The code for implementing our methods and reproducing the experiments is publicly available our GitHub repository. Full article

The study of the hypocenter distribution of seismic events related to fault structures is a crucial topic since it is linked to the geological features and to the dynamics of an investigated area. The hypocenter spatial distribution of earthquakes is used in a novel algorithmic method to clusterize earthquakes to accurately identify the strike and the dip parameters of seismogenic faults. Our algorithm works as a fast and efficient explorer in a five-dimensional space (x, y, z, τ, ϕ). It randomly selects several seismic events (pivots) and counts in all angular directions, for each pivot, how many hypocenters can be included in a prefixed volume (two dimensions larger than the third). The result is a volume that contains the maximum number of earthquakes occurring within a minimum distance from a flat area corresponding to the searched fault. With this volume is associated a hypocenter occurrence density angular diagram and a likelihood function. The likelihood function is useful to individuate the best value of the fault thickness and to test the hypothesis of fault flatness. Our algorithm was tested on simulated data and then successfully applied to the real case of the 2009 Mw6.1 L’Aquila (Central Italy) seismic sequence. Full article