Search Results (65)

In imitation learning with the embodiment gap, directly transferring human motions to robots is challenging due to differences in body structures. Therefore, it is necessary to reconstruct human motions in accordance with each robot’s embodiment. Our previous work focused on the right arm of a humanoid robot, which limited the generality of the approach. To address this, we propose Cross-Embodiment Kinematic Behavioral Cloning (X-EKBC), an imitation learning framework that enables movement-level imitation on a one-to-one basis between humans and multiple robots with embodiment gaps. We introduce a joint matrix that represents the structural correspondence between the human and robot bodies, and by solving kinematics based on this matrix, the system can efficiently reconstruct motions adapted to each robot’s embodiment. Furthermore, by employing Implicit Behavioral Cloning (IBC), the proposed method achieves both imitation learning of the reconstructed motions and quantitative evaluation of embodiment gaps using energy-based modeling. As a result, motion reconstruction through the joint matrix became feasible, enabling both imitation learning and quantitative embodiment evaluation based on reconstructed behaviors. Future work will aim to extend this framework toward motion-level imitation that captures higher-level behavioral outcomes. Full article

The proliferation of drones across precision agriculture, disaster response operations, and delivery services has accentuated the critical need for secure communication frameworks. Due to the limited computational capabilities of drones and the fragility of real-time wireless communication networks, the cellular connected drones confront mounting cybersecurity threats. Traditional authentication mechanisms, such as public-key infrastructure-based authentication, and identity-based authentication, are centralized and have high computational costs, which may result in single point of failure. To address these issues, this paper proposes a blockchain-enabled authentication and key agreement scheme for cellular-connected drones. Leveraging identity-based cryptography (IBC) and the Message Queuing Telemetry Transport (MQTT), the scheme flow is optimized to reduce the communication rounds in the authentication. By integrating MQTT brokers with the blockchain, it enables drones to authenticate through any network node, thereby enhancing system scalability and availability. Additionally, cryptographic performance is optimized via precompiled smart contracts, enabling efficient execution of complex operations. Comprehensive experimental evaluations validate the performance, scalability, robustness, and resource efficiency of the proposed scheme, and show that the system delivers near-linear scalability and accelerated on-chain verification. Full article

Implantable technologies targeting the cerebral cortex and deeper brain structures are increasingly utilised in human–machine interfacing, advanced neuroprosthetics, and clinical interventions for neurological conditions. These systems require highly efficient and low-power methods for exchanging information between the implant and external electronics. Traditional approaches often rely on inductively coupled data transfer (ic-DT), where the same coils used for wireless power are modulated for communication. Other designs use high-frequency antenna-based radio systems, typically operating in the 401–406 MHz MedRadio band or the 2.4 GHz ISM band. A promising alternative is intrabody communication (IBC), which leverages the bioelectrical characteristics of body tissue to enable signal propagation. This work presents a theoretical investigation into two schemes—inductive coupling and galvanically coupled IBC (gc-IBC)—as applied to cortical data links, considering frequencies from 1 to 10 MHz and implant depths of up to 7 cm. We propose a hybrid solution where gc-IBC supports data transmission and inductive coupling facilitates wireless power delivery. Our findings indicate that gc-IBC can accommodate wider bandwidths than ic-DT and offers significantly reduced path loss, approximately 20 dB lower than those of conventional RF-based antenna systems. Full article

Supernovae (SNe) are among the most energetic and transient events in the universe, offering crucial insights into stellar evolution, nucleosynthesis, and cosmic expansion. Optical observations have historically played a central role in the discovery, classification, and physical interpretation of SNe. In this review, we summarize recent progress in the optical study of SNe, with a focus on advancements in time-domain surveys and photometric and spectroscopic follow-up strategies. High-cadence optical monitoring is pivotal in capturing the diverse behaviors of SNe, from early-time emission to late-phase decline. Leveraging data from ARIES telescopes and national/international collaborations, we systematically investigate various SN types, including Type Iax, IIP/L, IIb, IIn/Ibn and Ib/c events. Our analysis includes light curve evolution and spectral diagnostics, providing insights into early emission signatures (e.g., shock breakout), progenitor systems, explosion mechanisms, and circumstellar medium (CSM) interactions. Through detailed case studies, we demonstrate the importance of both early-time and nebular-phase observations in constraining progenitor and CSM properties. This comprehensive approach underscores the importance of coordinated global efforts in time-domain astronomy to deepen our understanding of SN diversity. We conclude by discussing the challenges and opportunities for future optical studies in the era of wide-field observatories such as the Vera C. Rubin Observatory (hereafter Rubin), with an emphasis on detection strategies, automation, and rapid-response capabilities. Full article

Regulatory T cells (Tregs) are a specialized subset of CD4+ T lymphocytes essential for maintaining immune tolerance and preventing autoimmunity. However, in breast cancer, tumors exploit Tregs to establish an immunosuppressive microenvironment that enables immune evasion, accelerates progression, and contributes to therapeutic resistance. This review synthesizes current evidence on the role of Tregs in invasive breast cancer (IBC), highlighting their prognostic significance across molecular subtypes, mechanisms of immune suppression, and impact on treatment response. We integrated mechanistic and clinical insights to discuss opportunities for Treg-targeted therapeutic strategies, with attention paid to challenges such as autoimmunity, compensatory resistance, and subtype-specific heterogeneity. Finally, we outline future directions, including biomarker-driven precision medicine, novel therapeutic combinations, advanced preclinical models, as well as potential artificial intelligence-assisted approaches that aim to selectively disrupt tumor-promoting Treg functions while preserving the systemic immune balance. Full article

Microgrids have emerged as a crucial solution for addressing environmental concerns, such as reducing greenhouse gas emissions and enhancing energy sustainability. By incorporating renewable energy sources like solar and wind, microgrids improve energy efficiency and offer a cleaner alternative to conventional power grids. Among various microgrid architectures, DC microgrids are gaining significant attention due to their higher efficiency, reduced reactive power losses, and direct compatibility with renewable energy sources and energy storage systems. However, DC microgrids face stability challenges, particularly due to the presence of constant power loads (CPLs), which exhibit negative incremental impedance characteristics. These loads can destabilize the system, leading to oscillations and performance degradation. This paper explores various control strategies designed to enhance the stability and dynamic response of DC microgrids, with a particular focus on interleaved boost converters (IBCs) interfaced with CPLs. Traditional control methods, including proportional–integral (PI) and sliding mode control (SMC), have shown limitations in handling dynamic variations and disturbances. To overcome these challenges, this paper proposes a novel RST-based control strategy for IBCs, offering improved stability, adaptability, and disturbance rejection. The efficacy of the RST controller is validated through extensive simulations tests, demonstrating competitive performance in maintaining DC bus voltage regulation and current distribution. Key performance indicators demonstrate competitive performance, including settling times below 40 ms for voltage transients, overshoot limited to ±2%, minimal voltage deviation from the reference, and precise current sharing between interleaved phases. The findings contribute to advancing the stability and efficiency of DC microgrids, facilitating their broader adoption in modern energy systems. Full article

Partial shading condition (PSC) for photovoltaic (PV) arrays complicates the operation of PV systems at peak power due to the existence of multiple peak points on the power–voltage (P–V) characteristic curve. Identifying the global peak among multiple peaks presents challenges, as the system may become trapped at a local peak, potentially resulting in significant power loss. Power generation is reduced, and hot-spot issues might arise, which can cause shaded modules to fail, under the partly shaded case. In this paper, instead of focusing on local peaks, several effective, precise, and dependable maximum power point tracker (MPPT) systems monitor the global peak using a fuzzy logic controller. The suggested method can monitor the total of all PV array peaks using an interleaved boost converter DC/DC (IBC), not only the global peaks. A DC/DC class boost converter (CBC), the current gold standard for traditional control methods, is pitted against the suggested converter. Four PSC-PV systems employ three-phase inverters to connect their converters to the power grid. Full article

In this paper, a robust optimized controller is implemented in the photovoltaic generator system (PVGS). The PVGS is composed of individual photovoltaic (PV) cells, which convert solar energy to electrical energy. To optimize the efficiency of the PVGS under variable solar irradiance and temperatures, a maximum power point tracking (MPPT) controller is necessary. Additionally, the PVGS output voltage is typically low for many applications. To achieve the MPPT and to gain the output voltage, an increasing boost converter (IBC) is employed. Then, two issues should be considered in MPPT. At first, a smooth control signal for adjusting the duty cycle of the IBC is important. Another critical issue is the PVGS and IBC unknown sections, i.e., the total system uncertainty. Therefore, to address the system uncertainties and to regulate the smooth duty cycle of the converter, a robust dynamic sliding mode control (DSMC) is proposed. In DSMC, a low-pass integrator is placed before the system to suppress chattering and to produce a smooth actuator signal. However, this integrator increases the system states, and hence, a sliding mode observer (SMO) is proposed to estimate this additional state. The stability of the proposed control scheme is demonstrated using the Lyapunov theory. Finally, to demonstrate the effectiveness of the proposed method and provide a reliable comparison, conventional sliding mode control (CSMC) with the same proposed SMO is also implemented. Full article

The main goal of this paper is to present a new numerical algorithm for solving two models of one-dimensional fractional partial differential equations (FPDEs) subject to initial conditions (ICs) and integral boundary conditions (IBCs). This paper builds a modified shifted Chebyshev polynomial of the second kind (MSC2Ps) basis function that meets homogeneous IBCs, named IMSC2Ps. We also introduce two types of MSC2Ps that satisfy the given ICs. We create two operational matrices (OMs) for both ordinary derivatives (ODs) and Caputo fractional derivatives (CFDs) connected to these basis functions. By employing the spectral collocation method (SCM), we convert the FPDEs into a system of algebraic equations, which can be solved using any suitable numerical solvers. We validate the efficacy of our approach through convergence and error analyses, supported by numerical examples that demonstrate the method’s accuracy and effectiveness. Comparisons with existing methodologies further illustrate the advantages of our proposed technique, showcasing its high accuracy in approximating solutions. Full article

In trans-border data (data transferred or accessed across national jurisdictions) exchange scenarios, identity authentication mechanisms serve as critical components for ensuring data security and privacy protection, with their effectiveness directly impacting the compliance and reliability of transnational operations. However, existing identity authentication systems face multiple challenges in trans-border contexts. Firstly, the transnational transfer of identity data struggles to meet the varying data-compliance requirements across different jurisdictions. Secondly, centralized authentication architectures exhibit vulnerabilities in trust chains, where single points of failure may lead to systemic risks. Thirdly, the inefficiency of certificate verification in traditional Public Key Infrastructure (PKI) systems fails to meet the real-time response demands of globalized business operations. These limitations severely constrain real-time identity verification in international business scenarios. To address these issues, this study proposes a trans-border distributed certificate-free identity authentication framework (STALE). The methodology adopts three key innovations. Firstly, it utilizes email addresses as unique user identifiers combined with a Certificateless Public Key Cryptography (CL-PKC) system for key distribution, eliminating both single-point dependency on traditional Certificate Authorities (CAs) and the key escrow issues inherent in Identity-Based Cryptography (IBC). Secondly, an enhanced Elliptic Curve Diffie–Hellman (ECDH) key-exchange protocol is introduced, employing forward-secure session key negotiation to significantly improve communication security in trans-border network environments. Finally, a distributed identity ledger is implemented, using the FISCO BCOS blockchain, enabling decentralized storage and verification of identity information while ensuring data immutability, full traceability, and General Data Protection Regulation (GDPR) compliance. Our experimental results demonstrate that the proposed method exhibits significant advantages in authentication efficiency, communication overhead, and computational cost compared to existing solutions. Full article

Background and Objectives: The assessment of HER2 status in invasive breast carcinomas (IBCs) is critical for determining treatment strategies. The aim of this study was to evaluate the FICTION technique as a potential method for assessing HER2 status and to compare it with the standard sequential immunohistochemistry (IHC)–in situ hybridization (ISH) assays. Materials and Methods: This study included 49 patients diagnosed with invasive breast carcinomas. HER2 status was assessed using both IHC+FISH and FICTION techniques, and the results were compared. Results: Comparative analysis demonstrated an 83.67% categorical agreement between IHC and IF using the ASCO/CAP system. The percentage of cells showing any degree of HER2 protein expression was higher with IF (73.77%) than with IHC (60.71%) (p = 0.00026). The in situ hybridization assays showed an excellent agreement, with a 90% or higher concordance. The concordance of the ASCO/CAP group classification of cases using both ISH assays (FICTION and standard FISH) was high (85, 7%). Agreement was 100% for the final classification of cases (Her2 positive/negative). Conclusions: We compared standard tests for Her2 protein expression and the gene copy number with a modified FICTION protocol. The study showed moderate agreement between IHC and IF for Her2 protein and excellent agreement between FISH and FICTION ISH for the gene copy number. Final Her2 status was unaffected by low IF IHC concordance. Optimizing the FICTION protocol could improve results. Combining protein and gene assays may enhance IBC patient stratification. Full article

With the accelerating global transition toward sustainable energy, the role of battery energy storage systems (ESSs) becomes increasingly prominent. This study employs the isothermal battery calorimetry (IBC) measurement method and computational fluid dynamics (CFD) simulation to develop a multi-domain thermal modeling framework for battery systems, spanning from individual cells to modules, clusters, and ultimately the container level. Experimental validation confirms the model’s accuracy, with the simulated maximum cell temperature of 36.2 °C showing only a 1.8 °C deviation from the measured value of 34.4 °C under real-world operating conditions. Furthermore, by integrating on-site calibrated thermodynamic parameters of the container, a battery system energy efficiency model is established. Combined with the battery aging engineering model, a coupled lifetime–energy efficiency model is constructed. Six different control strategies are simulated and analyzed to quantify the system’s comprehensive lifecycle benefits. The results demonstrate that the optimized control strategy enhances the overall energy storage station revenue by 2.63%, yielding an additional cumulative profit of CNY 13.676 million over the entire lifecycle. This research provides an effective simulation framework and decision-making basis for the thermal management optimization and economic evaluation of battery ESSs. Full article

This paper presents an advanced Adaptive Sliding Mode Control (ASMC) strategy, specifically developed for a hydrogen production system based on a Proton Exchange Membrane electrolyzer (PEM electrolyzer). This work utilized a static model of the PEM electrolyzer, characterized by its V-I electrical characteristic, which was approximated by a linear equation. The ASMC was designed to estimate the coefficients of this equation, which are essential for designing an efficient controller. The primary objective of the proposed control strategy is to ensure the overall stability of the integrated system comprising both an interleaved buck converter (IBC) and PEM electrolyzer. The control framework aims to maintain the electrolyzer voltage at its reference value despite the unknown coefficients while ensuring equal current distribution among the three parallel legs of the IBC. The effectiveness of the proposed approach was demonstrated through numerical simulations in MATLAB-SIMULINK and was validated by the experimental results. The results showed that the proposed ASMC achieved a voltage tracking error of less than 2% and a current distribution imbalance of only 1.5%. Furthermore, the controller exhibited strong robustness to parameter variations, effectively handling fluctuations in the electrolyzer’s ohmic resistance (R_ohm) (from ±28.75% to ±40.35%) and in the reversible voltage (E_rev) (from ±28.67% to ±40.19%), highlighting its precision and reliability in real-world applications. Full article

Background: Inflammatory breast cancer (IBC) is a rare subtype of breast cancer accounting for 7% of breast cancer-related fatalities. There is an urgent need to develop new targeted treatments for IBC. The progression of IBC has been associated with alterations in growth factor and cytokine signaling; however, the function of the LIF (leukemia inhibitory factor)/LIFR (leukemia inhibitory factor receptor) cytokine pathway in the progression of IBC remains unknown. This study evaluated the role of LIFR signaling and tested the efficacy of the LIFR inhibitor EC359 in treating IBC. Methods: The utility of using LIFR inhibition as a treatment strategy in IBC was tested using cell survival, apoptosis, colony formation, invasion, and pre-clinical KPL4 xenografts. Western blotting, siRNA, RT-qPCR, and lipid peroxidation assays were used to establish the mechanism of EC359 therapy. Results: The reduction in LIFR levels using siRNA markedly decreased growth in colony formation assays and reduced the invasion of IBC cells. Pharmacological inhibition of LIFR with EC359 effectively reduced cell survival and the clonogenic capacity of IBC cells. RT-qPCR assays revealed that EC359 markedly decreased the expression of the LIFR target genes. Western blot analyses confirmed that EC359 treatment suppressed downstream LIF/LIFR signaling pathways and promoted apoptosis. Treatment of cells with the ferroptosis inhibitor Fer-1 negated the capacity of EC359 to induce apoptosis. Mechanistic investigations demonstrated that EC359 predominantly triggered ferroptosis by inhibiting the glutathione antioxidant defense system through the downregulation of Glutathione peroxidase 4 (GPX4) levels. EC359 (5 mg/kg/day) was effective in reducing the growth of the IBC KPL4 xenograft tumors. Conclusion: These findings demonstrates that LIFR inhibition promote ferroptosis-mediated cell death in IBC and that EC359 represent novel therapeutic for IBC treatment. Full article

In recent years, governments have regarded blockchain technology as a key breakthrough in independent innovation of core technologies and have attached great importance to its development. In current blockchain solutions, the elliptic curve digital signature algorithm (ECDSA) is usually combined with the Keccak Hash Algorithm 256-bit Variant (keccak256) to generate blockchain addresses. Although the ECDSA algorithm is based on the Public Key Infrastructure (PKI) system, which has prominent issues such as complex deployment processes, high operation and maintenance costs, low efficiency, and difficulties in adapting to a large number of users, it still holds an important position and has a broad application foundation in the field of cryptography. This paper aims to circumvent the existing flaws of the PKI system rather than discarding the strong and well-proven PKI system. Instead, it endeavors to explore the application of the Identity-Based Cryptography (IBC) system in blockchain and reduce dependence on foreign cryptographic algorithms. This study adopts the SM9 algorithm based on the IBC and combines it with the SM3 algorithm to generate blockchain addresses. Considering users’ use, this paper improves the original SM9 algorithm based on the original SM9 algorithm, enabling users to perform functions such as signing and encryption with just a single pair of public and private keys. Experimental results indicate that the time consumed by this proposed scheme in blockchain address generation is 1.29 times that of the existing schemes, and the length of the blockchain addresses generated is the same as that of the existing ones. Full article