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A secure and efficient image encryption scheme based on chaotic systems and nonlinear transformations
Abstract The exponential growth of digital imagery and the widespread adoption of automation and IoT technologies have heightened the need for robust image encryption techniques. Traditional encryption methods such as AES and DES, though effective for textual data, struggle with the high redundancy of images and real-time processing constraints. To address these challenges, this article proposes a novel multi-image encryption scheme integrating a 5D hyperchaotic system, Arnold’s Cat Map, and Langton’s Ant to achieve high security, efficiency, and resistance to attacks. The encryption process consists of four stages: (1) key generation using a 5D hyperchaotic system, (2) byte substitution using a newly designed S-box, (3) pixel scrambling via Langton’s Ant-based diffusion, and (4) transformation using Arnold’s Cat Map. The proposed method achieves a high key space of $$2^{52822}$$ , low correlation between encrypted pixels, and fast encryption times of 0.1602s for a $$256\times 256$$ image, making it suitable for real-time applications. Comprehensive security analyses, including histogram analysis, correlation coefficient evaluation, entropy measurement, differential attack resistance (NPCR and UACI), and NIST randomness tests, confirm the robustness of the encryption scheme. The results demonstrate that the proposed method outperforms existing chaotic and hybrid encryption techniques in terms of security, efficiency, and resistance to cryptographic attacks.
Retraction: Anthropological responses to environmental challenges in SAARC nations: A comparative analysis
Tunneling magnetoresistance in altermagnetic tunnel junctions with the half-metal electrode
As a critical component of high-efficiency and low-power memory devices, the development of magnetic tunnel junctions (MTJs) with large tunneling magnetoresistance (TMR) is highly demanded. Altermagnets, a particular magnetic system, with zero net magnetizations and non-spin-degenerate conductance due to momentum-dependent spin polarization, can generate TMR when used to replace ferromagnetic and traditional antiferromagnetic electrodes. In this study, we present a ferromagnet/insulator barrier/altermagnet junction that exhibits large intrinsic TMR. In this system, the ferromagnetic electrode is a half-metallic alloy with a unidirectional Fermi surface. We demonstrate that a large TMR can be obtained in V0.5Cr0.5O2/TiO2/RuO2 through first-principles calculations and quantum transport calculations. However, the TMR ratio is almost zero when the ferromagnetic electrode is replaced with pristine VO2 or CrO2. This behavior can be attributed to the unidirectional conduction channel rather than transport direction. Our work presents an efficient approach to realize large TMR ratio in ferromagnet/insulator barrier/altermagnet MTJs, which could contribute to the potential development of altermagnet-based spintronic devices.
Research on supply chain resilience mechanism of AI-Enabled manufacturing enterprises -based on organizational change perspective
Abstract Artificial intelligence (AI) is fundamentally reshaping supply chain operation modes and innovation paths, which has a significant impact on the development of supply chain resilience. This study utilizes panel data of Chinese A-share listed manufacturing companies from 2013 to 2022 to measure the application of AI through textual analysis and construct firm-level supply chain resilience indicators using factor analysis. The main findings suggest that AI greatly enhances supply chain resilience in the Chinese manufacturing industry, and this result holds in a series of robustness tests. Second, AI improves supply chain resilience through changes in organizational structure and improvements in internal control systems. Further, the impact of AI on supply chain resilience varies by industry characteristics and firms’ position in the supply chain. Finally, the technological maturity and depth of AI application within a firm also affects supply chain resilience differently. This study contributes to the research on the application of AI in supply chain management and the theory of supply chain resilience, as well as provides a theoretical foundation and practical insights for manufacturing firms to enhance their own resilience in the face of increasing global uncertainty and complexity.
Village health work in the primary healthcare of Zimbabwe: Health workers’ perspectives
Migration and poor performance of healthcare workers in Zimbabwe hinder primary healthcare delivery. This has compelled the country to exploit the potential of village health workers in primary healthcare. The Village Health Worker Strengthening Plan was never operationalised owing to unclear roles and limited coordination. The study aimed to explore the roles, challenges, and strategies as informed by setting and context to improve the effectiveness and efficiency of Village Health Workers in service delivery. The study was conducted in the Beitbridge district, Matabeleland South Province, Zimbabwe. A qualitative exploratory survey with semi-structured interview guides was administered to 36 participants, comprising Village Health Workers, nurses, environmental health practitioners, and medical doctors. Three main themes were analysed, and 15 subthemes were found. The role of Village Health Workers was to promote health, prevent and control disease, diagnose and treat minor ailments, and conduct community-based disease surveillance and referrals for complicated cases to primary healthcare facilities. Challenges were inadequate logistical supplies, allowances, knowledge and skills, mobility, and personal protective equipment. Optimal stocking of the medical and equipment supplies, improving allowances, community health integration into the healthcare system, embracing mobile health technology, capacity building, and supportive supervision were sub-themes on suggested strategies to improve service delivery. The study helped clarify the roles and challenges and suggested strategies by health service providers, as informed by empirical findings, to improve the effectiveness and efficiency of Village Health Workers in service delivery. It is recommended that needs assessments be conducted on village health work to enhance their capacity and support.
Significant ballistic thermal transport across graphene layers: Effect of nanoholes and lithium intercalation
Porous graphene and graphite are increasingly utilized in electrochemical energy storage and solar-thermal applications due to their unique structural and thermal properties. In this study, we conduct a comprehensive analysis of the lattice thermal transport and spectral phonon characteristics of holey graphite and multilayer graphene. Our results reveal that phonon modes propagating obliquely with respect to the graphene basal planes are the primary contributors to cross-plane thermal transport. These modes exhibit a predominantly ballistic nature, resulting in an almost linear increase in cross-plane thermal conductivity with the number of layers. The presence of nanoholes in graphene induces a broadband suppression of cross-plane phonon transport, whereas lithium-ion intercalation shows potential to enhance it. These findings provide critical insights into the mechanisms governing cross-plane heat conduction in key graphene-based structures, offering valuable guidance for thermal management and engineering of van der Waals materials.
Enhanced Active Hydrogen Absorption and Stabilized Cu(I) Species Over Cu‐O‐Ce Bridges Boosting Electrocatalytic CO <sub>2</sub> Reduction to Ethylene
Abstract Rational design of water activation center to promote active hydrogen (*H) generation and stabilize Cu(I) species are significant for the formation of multicarbon (C 2+ ) products over Cu‐based catalysts in electrocatalytic CO 2 reduction reaction (CO 2 RR). Herein, CeO 2 nanograins and CuO nanothorns were selectively deposited on the edges of Cu 2 O cubes through the seed‐mediated growth method. The as‐synthesized Cu x O–CeO 2 composites exhibit enhanced Faradaic efficiency and partial current density of C 2 H 4 compared with Cu 2 O cubes. In situ spectroscopies and theoretical calculations confirm that the Cu–O–Ce bridges in Cu x O–CeO 2 composite can effectively enhance *H absorption and stabilize Cu(I) species, facilitating subsequent C–C coupling and further protonation into the key *COCHO intermediate of C 2 H 4 . This work provides new insights into modulating *H absorption and stabilizing Cu(I) species for boosting CO 2 to C 2+ products.
A novel machine learning framework for stroke type identification in resource constrained settings with robustness to missing data
Community volunteer participation and its determinants during respiratory infectious disease outbreaks in China: A cross-sectional study across multiple provinces
Background Community volunteering plays a crucial role in strengthening public health emergency response, particularly during respiratory infectious disease outbreaks. However, limited research has examined the extent of resident participation and the factors influencing engagement in such efforts. This study investigated the prevalence and determinants of community volunteering during the COVID-19 pandemic and other respiratory infectious disease outbreaks in China. Method We conducted a cross-sectional online survey and included data from 1,023 residents residing in five provinces in China (Beijing, Guangdong, Heilongjiang, Hubei, and Yunnan) between early 2020 and March 2023. Participants reported their sociodemographic factors, volunteer activities, related motivations and barriers during the pandemic. We used logistic regression models to identify factors associated with volunteering. Results Of the respondents, 65.9% participated in community volunteering during the pandemic, with the most common roles related to nucleic acid testing. The primary motivation for volunteering was value expression. Main barriers to participation included a lack of time, limited professional skills, and concerns about the risk of infection. Higher odds of participation were observed among respondents who held at least a bachelor’s degree (AOR = 2.58, 95% CI: 1.21–5.48), worked in community (AOR = 4.32, 95% CI: 2.56–7.28) or health‑care roles (AOR = 2.48, 95% CI: 1.31–4.67), were Communist Party members (AOR = 1.68, 95% CI: 1.07–2.64), or had volunteered regularly before 2020 (AOR = 3.02, 95% CI: 2.51–3.64), while single/divorced/widowed individuals had lower odds of participation (AOR = 0.60, 95% CI: 0.39–0.94) (all p < 0.05). Conclusion Community volunteering could constitute a substantial auxiliary workforce during respiratory epidemics in China. Integrating volunteers into emergency preparedness may require institutionalized training programs, transparent management structures, as well as legal and policy safeguards that recognize volunteers’ contributions and mitigate perceived risks. Such measures are likely to strengthen community resilience in future public‑health emergencies.
Characterization of ferroelectric switching in 43 nm Y-36 lithium niobate films
Lithium niobate (LN) is a promising ferroelectric material used for emerging memories and radio frequency (RF) micromechanical resonators. The ferroelectric behavior of the bulk properties of LN has been well studied, and investigations on thin films have shown promising performance. However, the macroscopic ferroelectric properties of LN films that are sub-100 nm thick, which are desired to truly harness the advantages and scalability of the material, have not been explored. Here, we report the ferroelectric properties of 43 nm ultra-thin films of Y-36 LN sandwiched between two metal electrodes. Y-36 is a particularly promising cut for RF microacoustics, but can also be employed for integrated memories and photonics. Switching occurred with an average positive coercive field (+Ec) of 0.92 MV cm−1 and an average −Ec of 0.39 MV cm−1, resulting in the ability to switch the film polarization with &lt; 2 V. The 43 nm film maintains a large positive remanent polarization (+PR) of 58 μC·cm−2 and a -PR of 55 μC·cm−2. The thin film shows excellent endurance, maintaining a stable PR value after 1 billion polarization switching cycles. Retention characteristics also show stable PR value after 100 s. Additionally, findings indicate a power series relationship of Ec∝ Fβ with β value at 0.253 and 0.053 for +Ec and −Ec, respectively. Overall, the characterization of these ultra-thin films of LN showcase its potential for miniaturization and application to tunable RF acoustics or emerging memories.
Reduction of CO <sub>2</sub> Accompanying ATP Synthesis in Polydopamine Microreactors Covered by Lipid Bilayers with ATPase
Abstract Global energy and environmental crises have stimulated increased efforts toward converting CO 2 into valuable chemicals or energy substance. Inspired by natural chloroplasts and mitochondria, we build an innovative polydopamine‐armored multiple enzyme microreactor for co‐immobilizing glyceraldehyde‐3‐phosphate dehydrogenase (GAPDH), 3‐phosphoglyceric phosphokinase (PGK), formate dehydrogenase (FDH), and ATPase‐incorporating proteoliposome, providing spatially confined microenvironments akin to natural systems. Within this microreactor, GAPDH and PGK catalyze the conversion of glyceraldehyde 3‐phosphate to 3‐phosphoglyceric acid, reducing β‐nicotinamide adenine dinucleotide (NAD + ) to NADH and generating a proton influx that drives ATP synthesis. The microreactor possesses strong affinity for CO 2 , combined with FDH, facilitates the reduction of CO 2 to formic acid, oxidizing NADH back to NAD + and enabling the recycling of the NAD + /NADH redox couple. This process further boosts ATP production by contributing additional protons. Such microreactor adeptly orchestrates the chloroplast's enzymes to fix CO 2 and the mitochondrion's enzymes to synthesize ATP into a unified artificial biomimetic system, effectively replicating the glycolysis process to simultaneously achieve CO 2 fixation, NADH regeneration, and ATP synthesis. This strategy not only holds great potential to inspire significant design innovations for more efficient ATP synthesis from low‐value substances but also greatly expands the application scenarios for biomolecular motors.
An examination of the decoupling effect and influential mechanisms of energy consumption and economic growth in Chinese urban areas
STIL-TA: A new model of traffic flow forecasting based on spatiotemporal interactive learning and temporal attention
Accurate traffic flow forecasting plays a critical role in alleviating urban road congestion. Despite the success of existing models (e.g., graph-based or attention-based methods), three key limitations persist: (1) inflexible spatial dependency modeling, where static graph structures fail to adapt to dynamic traffic patterns; (2) decoupled spatiotemporal learning, where spatial and temporal correlations are processed separately, leading to information loss; and (3) limited long-term trend awareness, as traditional attention mechanisms overlook local contextual cues (e.g., rush-hour fluctuations). To address this, a new model of traffic flow forecasting based on Spatiotemporal Interactive Learning and Temporal Attention (STIL-TA) is proposed. This model effectively enhances the accuracy of traffic flow predictions by jointly modeling the spatiotemporal characteristics of road networks. Specifically, STIL-TA consists of two key components: (1) an interactive learning module built upon interactive dynamic graph convolution, which adopts a divide-and-conquer strategy to synchronize interactions and share the dynamically captured spatiotemporal features across different time periods, and (2) a temporal multi-head trend-aware self-attention mechanism, which utilizes local contextual information to transform the numerical sequence, enabling the capture of dynamic temporal dependencies in traffic flow and improving long-term prediction accuracy. Experimental results on four real-world traffic datasets demonstrate that the proposed STIL-TA model outperforms existing approaches, achieving significant improvements in forecasting accuracy.
Large thermoelectricity and Nernst effect at low temperature in quasi-one-dimensional <i>A</i>Mn6Bi5 (<i>A</i> = alkali metals)
Searching for promising materials that show large thermoelectricity or the Nernst effect at low temperatures is critical for cryogenic refrigeration applications. In this work, we investigated systematically the electrical and thermal transport properties of quasi-one-dimensional (Q1D) antiferromagnet AMn6Bi5 (A = Na, Rb, and Cs) and find some significant differences among them. All of them exhibit large thermopowers and considerable power factors at low temperature, but interestingly, the sign of thermopower changes from negative to positive with decreasing temperature for NaMn6Bi5. The low-temperature thermal conductivity of NaMn6Bi5 is also lower than those of RbMn6Bi5 and CsMn6Bi5, which is attributed to the high-density defects and stronger scattering. In addition, sufficiently large Nernst coefficients were observed in RbMn6Bi5 and CsMn6Bi5 but not in NaMn6Bi5. It was deduced that the dramatic change in thermoelectric characteristics observed in AMn6Bi5 was due to a large difference in their ionic sizes, leading to a complex interaction among the spin, charge, lattice, and one-dimensionality. Our work provides a unique example of the influences of alkali ions on the thermoelectric properties of Q1D-magnetic alkali metal compounds and can serve as a guide into the future direction for the improvement of the performance of the title compounds.
Improving learning from the complex multi-class imbalanced and overlapped data by mapping into higher dimension using SVM++
Retraction: Intimate but not intimate: The perils of workplace romance in fostering knowledge sabotage
Inversion of the internal electric field using delta doping in Al0.3Ga0.7N/GaN heterostructures
Controlling the internal electric field in III-nitride heterostructures is essential for optimizing device performance. These fields, arising from polarization effects, impact carrier confinement, wavefunction overlap, and band structure. In LEDs and lasers, reducing the field mitigates the quantum-confined Stark effect, enhancing efficiency. This study explores n-type delta doping in AlN/GaN and Al0.3Ga0.7N/GaN heterostructures to engineer and even invert locally the internal electric field. Simulations predict that inversion should be possible for Al0.3Ga0.7N layers inserting a delta doping concentration above 1.4 × 1013 cm−2. Off-axis electron holography experiments have been used to measure the electrostatic potential and have confirmed the electric field inversion obtained through Si delta doping. On the contrary, Ge doped layers did not show any inversion of the electric field due to Ge migration. Therefore, Si is more suitable for donor electric field engineering via delta doping.
Porous Organic Cages as Building Blocks for Framework Materials
Abstract Confined nanospaces play a fundamental role in nature, inspiring synthetic analogues that emulate biological precision and efficiency. Among these, porous crystalline materials such as covalent organic frameworks (COFs), metal‐organic frameworks (MOFs), and molecular cage compounds have emerged as powerful platforms for catalysis, separation, and energy storage. Recent developments highlight the potential of porous organic cages (POCs) as modular building blocks for the construction of advanced materials. In this Minireview, their integration into extended frameworks, such as Cage‐COFs and Cage‐MOFs, is described, as they allow precise control over porosity and enhance chemical robustness. These hybrids merge the structural regularity of COFs with the discrete functionality of cages, enabling the design of lightweight, hierarchically organised materials. In addition, cage‐containing polymers and supramolecular frameworks are discussed. Collectively, these developments position POCs as versatile synthons for next‐generation porous materials, unlocking pathways toward functional, adaptive, and recyclable architectures.
Single‐Molecule Electrochemiluminescence Imaging of Plasmonic Hot Spot Reactivity
Abstract Localized surface plasmon resonance (LSPR), an important optical property of noble metal nanomaterials, is extensively applied in electrochemistry. However, the specific LSPR effects on metallic nanoparticles are difficult to unravel and evaluate, owing to simultaneous factors like intrinsic electroactivity and surface interactions. Herein, we designed a series of shell‐isolated nanostructures, with mesoporous silica shells and plasmonic Au Nanorod cores (AuNR@mSiO 2 ), for precisely investigating both LSPR and nanoconfinement effects. Single‐molecule electrochemiluminescence (ECL) imaging was employed to monitor the in situ turnover frequency (TOF) of photon emissions on individual plasmonic nanoamplifiers to determine the dominant factors influencing LSPR and nanoconfinement effects. TOF heatmaps and super‐resolution ECL images unveiled distinct hot spot distributions along the plasmonic nanostructures. Our approach provides insight into and in‐depth understanding of plasmonic effects during electrochemical reactions, thereby facilitating precise electrocatalyst design based on the physiochemical properties of LSPR.