Search Results (42,794)

V₂CT_x MXene is a promising anode material for lithium-ion batteries due to its high electrical conductivity and abundant active sites. However, the spatial environment within its layers restricts the function of its energy storage electrode. Herein, V₂CT_x MXene was synthesized via an NH₄F–HCl-assisted hydrothermal etching method, followed by electrochemical pre-intercalation of Mn²⁺ using a three-electrode system. Structural characterizations confirm that Mn²⁺ pre-intercalation effectively modulates the interlayer environment, reduces surface F terminations, and maintains a stable layered structure. Electrochemical measurements demonstrate that the Mn²⁺-intercalated V₂CT_x MXene delivers an enhanced reversible capacity of 313.6 mAh·g⁻¹ after 200 cycles, outperforming pristine V₂CT_x MXene. The improved rate capability and reduced charge transfer resistance indicate accelerated ion/electron transport kinetics. This study provides an effective interlayer engineering strategy for improving MXene-based lithium-ion storage performance. Full article

High-resolution marine gravity fields are critical for interpreting seafloor structure, investigating marine geodynamics, and enabling gravity-aided navigation. However, sparse shipborne observations, heterogeneous multi-source geodetic datasets, and the inability of conventional methods to handle nonlinear inversion limit accurate gravity recovery. To overcome these limitations, we propose a spectral physics-informed constraint deep-learning framework based on a multi-channel Swin Transformer to reconstruct high-resolution marine gravity anomaly fields. The model ingests multi-source geodetic inputs organized as 64 × 64 grid patches centered near each computation point and fuses them to predict the target gravity anomaly. We adopt a remove–compute–restore (RCR) strategy that isolates residual gravity signals, which improves numerical stability and accelerates training. Inputs include satellite-altimetry-derived vertical gravity gradients, vertical deflections, mean sea surface height, and topography; the model is trained on over 430,000 shipborne gravity samples from the South China Sea (0–30° N, 105–125° E). To enforce physical consistency, we embed a spectral-domain physics constraint derived from potential-field theory into the loss function; this constraint helps recover short-wavelength gravity signals. We also introduce an adaptive multi-domain multi-scale feature fusion module (AMAMFF) to improve the integration of heterogeneous inputs, and we demonstrate its benefits in experiments across complex terrain. Validation against independent shipborne gravity checkpoints yields an RMS error of 3.09 mGal, indicating a substantial performance advantage over existing deep-learning approaches and conventional gravity-field models. Full article

Digitalization and decarbonization are unfolding in parallel, yet firm-level evidence on whether digital economy development delivers substantive low-carbon performance remains mixed. Using a 2008–2022 panel of Chinese listed firms matched to a city-level digital economy index, we estimate lagged fixed-effects models and examine capability and governance channels through firm digital transformation and ESG disclosure. The local digital economy is positively associated with the green transition level (GT ) and transition speed (GTS ), and it significantly increases digital transformation (DT ) and ESG disclosure (ESG ), consistent with partial mediation. By contrast, effects on carbon intensity are small and become insignificant once year effects are included, indicating that short-run emissions outcomes are dominated by macro energy conditions and potential rebound forces. Overall, digital development appears to accelerate strategic transition and disclosure capacity more quickly than operational emissions efficiency. Policy implications are twofold: align digital infrastructure with ESG data governance and verification, and coordinate digitalization with energy-system reforms to enable sustained emissions reductions. Full article

Multi-tenancy is essential for scalable IoT–Cloud systems; however, it introduces complex security vulnerabilities at the intersection of shared cloud infrastructures and resource-constrained IoT environments. This systematic review evaluates next-generation security frameworks designed to enforce tenant isolation without violating the strict latency (<10 ms) and energy bounds of lightweight sensors. Adhering to PRISMA guidelines, we analyze selected high-quality studies to categorize intersectional threats, including cross-tenant data leakage, side-channel attacks, and privilege escalation. Our analysis identifies a critical, unresolved conflict: existing mitigation strategies often incur a 12% computational and communication overhead, creating a significant barrier for real-time applications. Furthermore, we critically analyze emerging technologies, including Zero Trust Architectures (ZTA), adaptive Artificial Intelligence (AI), blockchain, and Post-Quantum Cryptography (PQC). We find that direct PQC deployment is currently infeasible for LPWAN protocols due to key-size constraints (1.6 KB) that exceed typical payload limits. To address these challenges, we propose a novel multi-layer security design principle that offloads heavy isolation and cryptographic workloads to hardware-accelerated edge gateways, thereby maintaining tenant isolation without compromising real-time performance. Finally, this review serves as a roadmap for future research, highlighting federated learning and hardware enclaves as essential pathways for securing next-generation multi-tenant IoT ecosystems. Full article

Lateral flow assays (LFAs) are among the most successful technologies for point-of-care and at-home testing, but further advances are needed to reduce costs and accelerate development. Alpaca-derived nanobodies (Nbs), single-domain antibody fragments, are promising immunoassay reagents across diverse applications. Their small size and ease of recombinant production make them particularly well suited for diagnostics. Here, we present a paper-based LFA targeting the SARS-CoV-2 nucleocapsid (N) protein that exclusively uses Nbs for direct antigen detection. We also demonstrate in-house synthesis of Nb-coated gold nanoparticles, enabling instrument-free visual readout and detection of N protein down to 40 ng/mL. This design avoids components that require mammalian cell culture and can be produced entirely from in-house reagents, simplifying manufacturing and lowering component costs. Because the assay is read visually without an external reader, it is well suited for deployment in resource-limited settings. Together, these results highlight the speed and practicality of developing Nb-based LFAs and suggest a broadly applicable strategy for detecting other clinically important disease biomarkers. Full article

Objectives: This study examined whether 8 weeks of unilateral flywheel resistance training (FRT) enhances eccentric neuromuscular characteristics and change-of-direction (COD) performance in male soccer players, and whether these adaptations transfer to sport-specific dribbling and match-play demands. Methods: Twenty-four male soccer players were randomized to a unilateral flywheel training group (EXT, n = 12) or a traditional resistance training control group (CON, n = 12). Both groups completed unilateral lower-limb strength training twice weekly for 8 weeks. Eccentric knee extensor and flexor peak torque (60°·s⁻¹), eccentric-to-concentric (E:C) ratio, and inter-limb asymmetry were assessed using isokinetic testing. Performance measures included a 10 m sprint, modified 505, COD deficit, a dribbling-based COD test (AFL), and GPS-derived high-intensity acceleration and deceleration metrics during matches. Results: Compared with CON, the EXT group showed greater increases in knee extensor (+0.54 Nm·kg⁻¹) and flexor (+0.46 Nm·kg⁻¹) eccentric peak torque, a higher E:C ratio, and reduced inter-limb asymmetry (all p < 0.05). While 10 m sprint performance remained unchanged, EXT improved modified 505 performance and reduced COD deficits (up to −0.06 s). In addition, AFL completion time decreased and match-play high-intensity acceleration and deceleration events increased in EXT compared with CON (p < 0.05). Conclusions: Unilateral FRT effectively enhances eccentric braking-related capacity and COD efficiency, with clear transfer to soccer-specific technical performance and high-intensity match-play demands. Full article

Against the backdrop of China’s “Dual Carbon” strategy, transitioning to high-quality energy development (HQED) is imperative for balancing decarbonization with economic resilience. This study explores the transformative role of the digital economy as a primary driver of this transition. Using provincial panel data from 2013 to 2023, we employ a two-way fixed effects model to quantify the impact of digital economy on high-quality energy development. Our empirical results demonstrate that the digital economy significantly bolsters high-quality energy development, a finding that holds across rigorous robustness and endogeneity checks. Mechanism analysis reveals three critical transmission pathways: fostering technological innovation, accelerating industrial structure upgrading, and promoting industrial sophistication. Furthermore, heterogeneity analysis indicates a pronounced positive effect in the Eastern and Central regions, whereas the impact in the Western region remains limited, highlighting a “digital divide” in energy transition. These findings suggest that policymakers should prioritize digital infrastructure in lagging regions and leverage digital tools to bridge the gap between industrial upgrading and energy efficiency. Full article

The increasing integration of electric vehicles (EVs) and renewable energy sources has accelerated the adoption of DC microgrids, where maintaining voltage stability and effective power sharing remains a critical challenge. Hybrid energy storage systems (HESS), combining batteries and supercapacitors, are commonly employed to address dynamic power variations. However, conventional proportional–integral (PI)-based control strategies for HESS can exhibit performance limitations under nonlinear and varying operating conditions. To overcome this drawback, this paper presents an adaptive neuro-fuzzy inference system (ANFIS)-based control strategy for HESS located in a DC microgrid, with comparative evaluation against both conventional PI and traditional Fuzzy Logic controller (FLC) schemes. The proposed approach is evaluated using a detailed MATLAB/Simulink R2024a model of a DC microgrid including EVs. Simulation results show that, under normal operating conditions, the ANFIS-based control demonstrates improved transient response, reduced voltage fluctuations, and effective coordination between the battery and supercapacitor during renewable power variations, compared to PI and FLC-controlled systems. In addition to nominal performance assessment, this work investigates the vulnerability of the ANFIS controller to cyber-attacks. Two representative attack scenarios, false data injection (FDI) and denial-of-service (DoS), are applied to critical measurement and control signals of HESS. Simulation results reveal that, although the DC-bus voltage regulation is largely maintained during attack intervals, cyber manipulation significantly disrupts the intended HESS power-sharing behavior. Full article

Addressing climate change necessitates coordinated efforts across multiple sectors, with agriculture representing a significant source of greenhouse gas (GHG) emissions. This requires sophisticated mitigation strategies at the farm level. Digital decision support tools (DSTs) tailored for this purpose play a crucial role in accelerating farm-level decarbonization. Ensuring the reliability and accuracy of these DSTs mandates thorough model robustness validation. This study validates a farm-level GHG accounting and decarbonization DST using Sobol and Morris global sensitivity analyses to evaluate output robustness and to identify key input parameters critical for reliable mitigation planning. Both sensitivity analysis methods provide a comprehensive assessment of the tool’s robustness and highlight parameters most influencing farm-level GHG emission outcomes. Results show consistent outcomes across sensitivity approaches, reinforcing confidence in the tool’s application for emission reduction planning. The sensitivity analysis results indicate that the tool delivers reliable outcomes across various sensitivity analysis methods, thereby enhancing confidence in its suitability for decarbonization planning. Furthermore, the findings of this study provide a methodological foundation for future advancements and expanded use within the agriculture sector. This supports the DST’s effectiveness in prioritizing mitigation strategies and planning emission reduction pathways at the farm scale, while providing a transparent template to guide future tool improvements and broader agricultural applications. Full article

Purpose of Review—sleep disturbance is the main complaint associated with patients who suffer acute postoperative pain. Sleep disturbance may also increase the pain sensitivity and contribute to the development and maintenance of chronic pain. The pathophysiology of pain is complex; management of perioperative pain and preventing chronic pain are challenges in clinical. Use of opioids for pain management are still a therapeutic mainstay and generally safe when taken, in a short time, for severe postoperative pain relief. For long-term use tolerance may be developed, and for their euphoric property, addiction, overdose incidents, and even death may be the social problems. Therefore, the opioid-sparing multimodal analgesia (MMA) for pain management is recommended in current postoperative pain management. The successful MMA for pain management will enhance patient recovery after surgery with less chronic CPSP and long-term opioid use disorder (OUD). The present review discusses all currently used analgesics actions and interactions, and opioid-sparing or opioid-free analgesia in perioperative pain management. Acute pain following major trauma or surgery may originate from both nociceptive and neuropathic mechanisms. Approximately 10–50% of surgical patients develop chronic postoperative pain, which not only causes persistent discomfort but also leads to functional limitations and psychological distress. Growing evidence highlights a close and bidirectional relationship between sleep and pain: pain disrupts sleep architecture, while sleep deprivation intensifies pain sensitivity and impairs recovery. This reciprocal interaction forms a vicious cycle that poses challenges for effective pain management. Melatonin—a neurohormone secreted by the pineal gland—plays a crucial role in regulating circadian rhythm and sleep–wake cycles. Beyond its chronobiotic action, melatonin exhibits anti-nociceptive, anti-inflammatory, and opioid-sparing properties. Recent preclinical studies have demonstrated that exogenous melatonin can attenuate nociceptive responses to noxious stimuli and enhance morphine analgesia while attenuating morphine tolerance. Moreover, environmental light manipulation preserving the circadian rhythm has been shown to synergistically maintain melatonin secretion, improve sleep quality, and modulate neuroimmune responses involved in pain regulation. Together, these findings suggest that circadian alignment and melatonin supplementation may represent a promising integrative approach for improving both pain control and sleep health in perioperative and chronic pain conditions. Chronic pain patients frequently experience opioid tolerance during long-term therapy, resulting in diminished analgesic efficacy and a need for escalating doses. Our recent work revealed that constant light exposure suppresses endogenous melatonin, heightens pro-inflammatory cytokines (TNF-α, IL-1β), reduces IL-10, and accelerates morphine tolerance in a neuropathic pain model. In contrast, maintaining circadian light–dark cycles or supplementing melatonin preserves melatonin rhythm, reduces glial activation, and sustains morphine antinociception. Melatonin’s co-administration not only attenuates morphine tolerance but also enhances morphine efficacy through the modulation of inflammatory and glial pathways. These findings underscore melatonin’s multifaceted role as both a chronotherapeutic and neuroprotective agent, integrating circadian regulation with pain modulation. Clinically, the application of melatonin or circadian-aligned strategies could guide personalized pain and sleep management, offering safer and more effective multimodal analgesic protocols with reduced opioid dependence and improved quality of life. Full article

Low-maturity shale is a prime target for in situ conversion (ICP), yet heating window selection remains largely empirical because pore evolution and hydrocarbon generation are rarely quantified in tandem. Nenjiang Formation shale from the Songliao Basin (TOC = 8.91%; R_o,max = 0.54%) was subjected to closed-system pyrolysis at 300–500 °C (20 °C h⁻¹; 72 h per step). Released oil and gas and residual chloroform-extractable bitumen (“A”) were quantified, and pore evolution was characterized using 2D low-field NMR, SEM, micro-CT, and low-pressure N₂ adsorption. Fractal dimensions (D_s and D_p) were derived from Frenkel–Halsey–Hill (FHH) fitting. Oil yield and bitumen “A” increased sharply above 350 °C and peaked at 375 °C, whereas gas generation accelerated above 400 °C and continued to increase to 500 °C. NMR indicates a temperature-dependent shift in retained hydrocarbons toward weaker confinement and higher mobility, with enhanced expulsion/mobility signals near 375 °C. At 375 °C, BJH pore volume and average pore diameter reached maxima (0.0675 cm³ g⁻¹ and 15.36 nm), while D_s and D_p reached minima (2.343 and 2.444). The coincidence of peak oil expulsion with minimum fractal complexity suggests that FHH-based fractal indices provide a quantitative metric for comparing ICP heating windows in low-maturity shale. Full article

Fruit ripening and color change form a complex physiological and biochemical process involving the accumulation and breakdown of a series of metabolites. Brassinolide plays an important role in the regulation of fruit ripening. In this study, the effects of exogenous EBR (2,4-epibrassinolide) and BRZ (Brassinazole, an inhibitor of BR biosynthesis) on fruit color change were investigated using ‘Micro-Tom’ tomatoes (Solanum lycopersicum L.) as an experimental material. The experiment was set up with five treatments: CK (distilled water + 0.01% Tween-80) and T1–T4 (0.05, 0.1, 0.15, 0.2 mg/L EBR). In addition, a BRZ-treated group (4 μmol/L BRZ + 0.01% Tween-80) was set up in a follow-up experiment. The results showed that different concentrations of EBR treatments significantly increased the carotenoid and lycopene contents and decreased the chlorophyll contents in fruits compared with CK, with the T3 treatment (0.15 mg/L EBR) showing the most significant effect. Simultaneously, EBR induced the expression of the carotenoid metabolism genes SlGGPPS, SlPSY, SlPDS and SlZDS and promoted carotenoid accumulation. On the 20th day, compared with the CK and BRZ treatments, chlorophyll a and chlorophyll b contents were significantly reduced by 20.06% and 46.03% respectively; the expression of the chlorophyll degradation-related genes SlNYC, SlSGR1, SlPPH, and SlPAO was upregulated under a 0.15 mg/L EBR treatment, accelerating chlorophyll degradation. Furthermore, the EBR treatment reduced fruit brightness (L*) and increased fruit red saturation (a*), while yellow saturation (b*) showed an increasing and then decreasing trend; on the 20th day, compared with CK and BRZ, the red saturation of the EBR treatment group increased by 125.57% and 67.37% respectively, while the brightness decreased significantly by 24.28% and 23.83% respectively. In conclusion, exogenous application of 0.15 mg/L EBR significantly accelerated fruit ripening and color transformation by promoting the accumulation of carotenoids and the degradation of chlorophyll. Full article

Background/Objective: Effective topical delivery of 4-phenylbutyric acid (4-PBA) for arsenical vesicant-induced skin injury requires nanocarrier systems that maintain physicochemical and chemical stability during extended storage. This study systematically evaluated the six-month stability of five 4-PBA-loaded micro/nanoparticulate formulations—chitosan nanoparticles (N31, N35), emulsomes (E2), microsponges (MSs), and PLGA nanoparticles (P1)—to identify lead candidates suitable for field deployment and foam integration. Methods: Formulations were subjected to ICH-accelerated stability testing at 25 °C/60% RH and 40 °C/75% RH, with monthly evaluation of particle size, polydispersity index, zeta potential, drug content by HPLC, and chemical/thermal stability by FTIR and DSC. Results: N31 demonstrated superior colloidal stability, maintaining particle size within acceptable limits at both conditions despite progressive surface charge neutralization. E2 showed consistent drug content retention and preserved chemical integrity, though moderate vesicle fusion occurred. MS underwent complete physical degradation at 40 °C within the first month, while P1 exhibited hydrolytic degradation with substantial drug loss. N35 showed severe aggregation indicating colloidal instability. Conclusions: N31 and E2 emerged as lead candidates: N31 is recommended for field deployment where environmental control is limited, while E2 is suitable for controlled storage settings prioritizing drug loading capacity. Full article

Buildings account for nearly 40% of global energy use and 36% of CO₂ emissions, positioning Net-Zero Energy Buildings (NZEBs) as vital for climate mitigation. However, large-scale adoption remains limited by technical, economic, and policy barriers. This study systematically reviews 1285 peer-reviewed articles (2015–2025) from Scopus and Web of Science, following PRISMA guidelines and thematic analysis to assess renewable energy integration and efficiency strategies. Results indicate that 70% of studies highlight emissions reduction and cost savings as key NZEB benefits, while 60% cite high storage costs and 45% report grid integration challenges. Only 30% of studies address policy dependency, revealing a research gap. Effective measures include passive solar design (up to 25% heating load reduction), high-performance envelopes (15–40% energy savings), and smart energy management (10–20% efficiency gains). Persistent obstacles involve high upfront costs, renewable variability, and rapid technological obsolescence. Achieving NZEB viability requires integrating energy-efficient design, affordable renewables, advanced storage, and coherent policy frameworks to accelerate the transition toward a sustainable, NZEB-built environment. Full article

In response to issues such as insufficient bias in random sampling, low convergence efficiency, inadequate path search efficiency, and lack of path smoothness encountered by the traditional RRT* algorithm during path planning, an improved algorithm is proposed. First, a dynamic ellipsoidal sampling strategy is introduced, which accelerates the exploration of the path space by adaptively adjusting the sampling region. Additionally, a bidirectional RRT* algorithm is employed, establishing two alternately growing search trees to perform bidirectional search, thereby effectively enhancing the convergence speed of the algorithm. Second, a dynamic goal-biased strategy is adopted, which greedily guides the random tree to grow rapidly toward the goal point, thereby improving planning efficiency. A heuristic search scheme is integrated with the RRT* algorithm to further increase convergence speed. A random sampling expansion strategy is utilized to guide the tree to expand into unexplored regions, avoiding local minima while ensuring global search capability. Local reconnection optimization is applied to reduce the cumulative path cost of new nodes while balancing path length, smoothness, and safety. To reduce the number of iterations, an improved artificial potential field method is incorporated into the growth process of the bidirectional random search trees, providing directional guidance for their expansion. Finally, path pruning techniques are applied to eliminate redundant nodes from the initial path, and a cubic B-spline interpolation algorithm is used to smooth the pruned path, generating a final trajectory with continuous curvature suitable for tracking. Quantitative analysis of simulation experiments in three-dimensional space shows that in both simple and complex environments, compared with the RRT, GB-RRT, BI-RRT, APF-RRT, and BI-APF-RRT* algorithms, the improved RRT* algorithm reduces planning time by approximately 58–90%, decreases the number of path nodes by about 31–91%, and shortens path length by around 8–20%, demonstrating the superiority of the proposed algorithm. Full article