Search Results (8,033)

Serving large language models (LLMs) on cloud spot and preemptible instances reduces costs by 60 to 90 percent compared to on-demand pricing, but unpredictable instance preemptions cause request failures, KV-cache state loss, and degraded user experience. We present MorphCloud-LLM, an elastic LLM serving system designed to achieve the reliability properties of on-demand serving at spot-instance pricing. MorphCloud-LLM integrates three synergistic components: (1) an asynchronous incremental KV-cache checkpointing engine that streams only delta state to disaggregated persistent storage with less than 3% throughput overhead, enabling sub-second KV-cache delta streaming and reconstruction for KV-cache sizes up to 32 GB on replacement instances (total end-to-end migration latency: 1390 ms); (2) a gradient-boosted preemption prediction model trained on spot market telemetry that achieves 89% recall at a 30-s prediction horizon, providing sufficient lead time for proactive migration before forced eviction; and (3) a speculative decoding continuity engine that offloads draft model token generation to on-demand fallback nodes during migration windows, bounding the user-visible interruption to a sub-second buffering pause. MorphCloud-LLM is deployed and evaluated on AWS and GCP using LLaMA-70B and Mixtral-8x7B across 521 trace-injected preemption events, achieving up to 76% cost reduction under active-serving accounting (69.8% for LLaMA-70B; 67% including warm standby fallback capacity) with only 2.1% p99 latency overhead and zero dropped requests. Extensive ablation studies confirm the contribution of each component to overall system resilience. Note that preemption events are reproduced via a trace-driven simulation framework built on empirical AWS and GCP spot interruption traces rather than fully uncontrolled live production preemptions. Production generalizability under uncontrolled preemption—including simultaneous multi-node failures, network congestion, storage contention, and replacement-instance scarcity remains subject to future validation in sustained live deployments. Full article

Greenhouse agriculture in semi-arid regions faces persistent challenges from unpredictable thermal variability, frost events, and seasonal drought stress that are difficult to manage without anticipatory climate information. This paper presents the design, implementation, and validation of an end-to-end intelligent greenhouse monitoring and temperature forecasting system deployed in Donovan, San Luis Province, Argentina. The proposed platform integrates a three-layer IoT architecture with cloud-based statistical forecasting to support real-time decision making under semi-arid climatic conditions. The system integrates sensor nodes, a push-MQTT gateway co-located at the Universidad Nacional de San Luis to bypass regional API geo-restrictions, and a cloud application layer. Three forecasting strategies with a six-hour prediction horizon were evaluated: a univariate SARIMA baseline (Model 1), a SARIMAX model using four neighboring meteorological stations as individual exogenous regressors (Model 2), and a SARIMAX model employing a single correlation-weighted synthetic exogenous index (Model 3). The models were assessed using MAE, RMSE, and Diebold–Mariano statistical significance tests. The results show that directly incorporating multiple correlated exogenous variables does not improve forecast accuracy because of multicollinearity, whereas the proposed correlation-weighted synthetic index preserves the spatial predictive signal while reducing model complexity and achieving performance comparable to the baseline overall, with statistically significant improvement during the overnight block. Additional benchmarking against Random Forest, Support Vector Regression, Temporal Convolutional Networks, and Long Short-Term Memory models demonstrates that increasing model complexity does not necessarily translate into improved predictive performance for short-horizon greenhouse temperature forecasting. Together, the proposed IoT architecture and forecasting framework provide an operationally validated solution for intelligent greenhouse monitoring and predictive decision support in resource-constrained semi-arid environments. Full article

Thermokarst lakes are sensitive components of Arctic permafrost landscapes and important methane sources, yet aquatic vegetation change is rarely examined together with lake water dynamics. We used Landsat observations to quantify water area, aquatic vegetation occurrence frequency, and maximum vegetation extent for 32,439 lakes in Northeast Siberia from 2000 to 2025. Long-term trends, rapid events, event-centered trajectories, and water–vegetation coupling were analyzed at regional and individual-lake scales, while a same-lake case–control design examined climate anomalies associated with rapid vegetation increases. Regional lake water area showed a net increase of only 0.05% between the 2000–2004 and 2021–2025 mean periods because gains in small lakes were offset by losses in large lakes. Over the same two periods, maximum aquatic vegetation extent increased by 172.5%, and 47.4% of lakes showed a significant increase. Stable water area combined with increasing vegetation extent in 39.9% of all lakes, indicating substantial long-term decoupling. Rapid lake contraction was followed by gradual vegetation increases, whereas rapid vegetation increases generally occurred without systematic lake-area change. Event years were more often associated with a positive growing-season water balance and reduced May–July snowmelt, although these relationships varied among years. Aquatic greening therefore represents substantial ecological reorganization within Arctic lake basins that is only partly captured by conventional surface water monitoring. Full article

This study establishes a field-measurement-based wideband modeling and station-level simulation framework for conducted high-frequency (HF) disturbance studies in modular multilevel converter-based high-voltage direct-current (MMC-HVDC) stations. Full-scale engineering-site frequency-response measurements are used to identify kHz-to-MHz terminal models of the arm reactor and the valve-side winding of the converter transformer. The arm reactor is fitted in the admittance domain by vector fitting and synthesized as a passive parallel network containing the main inductive path and multiple damped resistor–inductor–capacitor (RLC) branches. The transformer valve-side winding is represented by a Foster I/II hybrid $\pi$-type terminal network reconstructed from two single-phase port-impedance measurements. The validated equipment models are integrated into a representative Power Systems Computer-Aided Design (PSCAD) station model. A 2 ms valve-side source sequence, constructed from nearest-level-control switching instants and a parameterized switching-transient template, is applied in paired injection and zero-injection simulations. For the representative event, the source peak is 605.6 V. Over the first 4 $\mathsf{\mu }$s, the arm-reactor terminal reaches 972.6 V, while the direct-current (DC)-side, valve-side alternating-current (AC), and point-of-common-coupling (PCC) responses reach 534.2, 438.4, and 151.9 V, respectively. The corresponding peak changes relative to the source are $+4.11$, $-1.09$, $-2.81$, and $-12.01$ dB. The DC-side response contains a dominant damped oscillation near 0.61 MHz, and the AC/PCC transfer varies markedly across 0.2–2.0 MHz. In a separate control-identical comparison over the first 2.5 $\mathsf{\mu }$s, the field-identified and lumped models give DC-side peaks of 171.9 and 1.23 V and PCC peaks of 121.4 and 3.93 V under the same excitation. The framework connects field-identified equipment terminal behavior with station-level time-domain propagation analysis and provides a modeling basis for broadband resonance screening and conducted electromagnetic-interference (EMI) assessment. Full article

A coaxial twin-rotor helicopter features a compact structure by eliminating the tail rotor. Although offering advantages in lift capability and maneuverability, the design presents challenges from its mechanical complexity and the aerodynamic interference between the counter-rotating rotors. During blade intersection, the collision risk of the blades depends not only on the blade-tip distance, but also on the intersection phase and the blade-tip position. In our study, we defined a blade collision warning parameter, d, to represent a fused safety clearance in coaxial twin-rotor helicopters, and proposed a correlated uncertainty propagation model for the measurement chain. The proposed model incorporates uncertainty sources from radar ranging, phase determination, geometric consistency, phase-synchronized triggering, sensor-point substitution, and model discrepancy through covariance terms. Experimental validation is performed on a single-rotor blade-intersection platform under controlled conditions. With the simulated blade rotated at 420 r/min, the combined standard uncertainty ranges from 0.677 to 0.996 mm over the reference warning parameter range of 99–990 mm. The event-level residual-compatibility rate is 86.8%, with localized non-compatibility observed at several reference points. Additional tests at 300 and 600 r/min demonstrated millimeter-level stability. Our uncertainty analysis identified radar ranging as the dominant contributor, followed by model discrepancy and sensor-point substitution uncertainty. Full article

Early-stage offshore wind development in the Gulf of Tonkin (Bac Bo Gulf) requires environmental information beyond conventional wind-resource mapping. Waves, currents, directional relationships, and extreme conditions all affect structural loading, operability, and the reliability of preliminary feasibility assessments. Wind, wave, current, and bathymetric data for 1993–2024 were analysed at three representative fixed-bottom screening sites: northern Gulf of Tonkin (NGT), central Gulf of Tonkin (CGT), and southern Gulf of Tonkin (SGT). The analysis characterises long-term conditions, seasonal variability, directional misalignment, wind-conditioned sea states, and marginal extremes with quantified uncertainty. The central site was the most energetic, with a mean wind speed of 7.97 m s⁻¹ at 150 m and a 50-year marginal wind return level of 37.67 m s⁻¹; the southern site had the strongest background current and the most persistent wind–wave misalignment. These differences do not follow a simple north–south gradient, so a single regional environmental description would misrepresent at least one of the three sites. The resulting conditional, directional, event-associated, and marginal-extreme statistics were organised into an IEC-oriented screening framework rather than treated as completed design-load-case inputs. This framework gives developers a basis for comparing site-specific environmental conditions before committing to costly site investigations. However, joint environmental modelling, water levels, tidal and storm currents, site measurements, and load-response analysis remain necessary before detailed design and certification. Full article

Background/Objectives: The lactate/albumin ratio (LAR) integrates tissue hypoperfusion and nutritional reserve into a single dimensionless index. As a late-course measurement (last available value before the primary outcome), it may reflect terminal metabolic deterioration rather than early prognostic signal. We examined the association of the final LAR with in-hospital mortality after adjustment for validated severity scores (APACHE II, SOFA) in critically ill patients receiving CRRT, and evaluated its incremental value beyond lactate alone. Methods: A single-centre retrospective observational study was conducted, including 110 adult patients treated with CRRT/CVVHDF at Konya City Hospital (January 2024–January 2026). Multivariable logistic regression was performed across four hierarchically adjusted models. APACHE II was designated the primary adjustment covariate. ROC analyses compared the final LAR with final lactate and albumin alone. Results: In-hospital mortality was 70.9% (78/110); complete paired final lactate and albumin values were available for 109/110 patients (78 non-survivors, 31 survivors). After APACHE II adjustment, each 0.1-unit increase in the late-course LAR remained significantly associated with in-hospital mortality (OR 1.70; 95% CI 1.16–2.49; p = 0.007), a finding replicated in the ICU-stay sensitivity cohort (n = 100, 73 events; OR 1.63; 95% CI 1.09–2.42; p = 0.016). The LAR trajectory (ΔLAR; AUC 0.725) was significantly greater in non-survivors (+0.104 vs. −0.060; p < 0.001); however, ΔLAR did not significantly outperform the lactate trajectory alone (Δlactate; AUC 0.706; p = 0.212), and lost statistical significance after severity-score adjustment. Furthermore, the association was attenuated and non-significant after SOFA adjustment (OR 1.35; p = 0.077), and the final LAR did not provide statistically significant discriminative advantage over lactate alone (AUC 0.768 vs. 0.761; LRT p = 0.435). Conclusions: The late-course LAR remained significantly associated with mortality after APACHE II adjustment. Three qualifications temper this finding: the association was attenuated after SOFA adjustment, the final LAR did not outperform lactate alone, and the measurement design is susceptible to reverse causality. The LAR trajectory (ΔLAR; AUC 0.725) showed comparable discrimination to the final LAR but did not significantly outperform the lactate trajectory alone (Δlactate; AUC 0.706; p = 0.212) and lost statistical significance after severity-score adjustment, so it should likewise be regarded as hypothesis-generating rather than confirmatory; prospective evaluation with time-stamped serial measurements and landmark analyses in multi-centre CRRT cohorts is warranted. Full article

Background/Objectives: Regional HPV genotype data for the Yangtze River Delta remain scarce, limiting evidence-based vaccine and screening policies. This study characterised the HPV genotype distribution, the vaccine protection gaps, and the co-infection network structure among clinical women in Wuxi, a prefecture-level city in the Yangtze River Delta region of Jiangsu Province, China. Methods: We retrospectively analysed all 8515 cervical HPV genotyping records from Xishan People’s Hospital of Wuxi City (January 2024–June 2025) using a 23-type fluorescent PCR panel classified by the International Agency for Research on Cancer (IARC) criteria. Results: The overall HPV prevalence was 22.83% (1944/8515; 95% CI 21.9–23.8%). The five leading types were HPV52 (4.82%), HPV58 (3.14%), HPV16 (2.96%), HPV53 (2.50%), and HPV42 (2.08%); HPV18 (0.74%) ranked below two unvaccinated carcinogens, HPV51 (1.76%, IARC Group 1) and HPV68 (1.68%, Group 2A). The age-stratified prevalence was U-shaped (χ² = 123.27, p < 0.001), peaking at ≤20 years (52.94%; exploratory, n = 51) and ≥61 years (34.66%). Among the 1944 women with positive results, 43.0% were completely unprotected by the nonavalent vaccine, and 60.4% harboured at least one non-9vHPV type; HPV51 and HPV68 together accounted for 15.08% of the positive cases. In the co-infection network (n = 585 multiple-type infections), HPV52 achieved the highest degree centrality (281 co-infection events; normalised degree = 0.0218) and appeared in 8 of the 15 most frequent dual-type pairs, with observed/expected ratios of 6.5–14.8-fold. Conclusions: These findings reveal a clinically substantial vaccine protection gap and support the prioritisation of HPV51 and HPV68 in next-generation vaccine design. Full article

Lung cancer is currently the most frequently diagnosed malignancy worldwide, accounting for approximately 12.4% of all cancers and, despite major advances in molecularly targeted therapies and immunotherapy, represents the leading cause of cancer-related mortality, In recent years, antibody–drug conjugates (ADCs) have emerged as a novel therapeutic strategy, combining the specificity of monoclonal antibodies with the potent cytotoxic activity of highly active payloads to selectively target tumor cells while limiting systemic toxicity. This narrative review summarizes the current role of ADCs in lung cancer, with particular focus on their structural components, mechanisms of action, and the biological features that determine treatment efficacy. We discuss the rationale for targeting established and emerging antigens in non-small cell and small cell lung cancer, including HER2, TROP2, c-MET, HER3, CEACAM5, DLL3, and other promising targets currently under clinical investigation. The principal mechanisms of primary and acquired resistance are also reviewed, including antigen modulation, altered intracellular trafficking, lysosomal dysfunction, drug efflux, tumor microenvironment-mediated immune suppression, and intratumor heterogeneity. In addition, we provide an overview of the safety profile of ADCs, highlighting the most clinically relevant adverse events and their underlying biological mechanisms. We also examine the evolving landscape of predictive biomarkers beyond antigen expression, including genomic, transcriptomic, proteomic, and liquid biopsy-based approaches, together with emerging spatial and single-cell technologies that may improve patient selection. Finally, we discuss future directions in the field, including novel payloads, next-generation linker technologies, bispecific ADCs, combination strategies, and personalized ADC development. Overall, ADCs are rapidly reshaping the therapeutic landscape of lung cancer. Continued optimization of drug design, biomarker-driven patient selection, and a deeper understanding of resistance mechanisms will be essential to fully realize their clinical potential. Full article

Internet of Vehicles (IoV) security mechanisms often classify isolated messages or assign node-level trust scores, yet these decisions do not explain whether a malicious but authenticated event has distorted the intended evolution of traffic. This paper proposes IntentProv-IoV, a causally grounded provenance framework for traffic-intent preservation in V2X environments. Traffic intent is modeled as the short-horizon collective state expected under non-adversarial conditions, and deviation is measured between predicted and observed traffic states. The framework constructs temporal provenance graphs linking vehicles, roadside units (RSUs), cooperative perception outputs, prediction nodes, and traffic-control decisions. To remove the ambiguity of marginal contribution, node contribution is formalized as an interventional effect in a structural causal model and estimated through Monte Carlo counterfactual edge-weight attenuation, with a linear sensitivity fallback for real-time edge deployment. A calibrated composite score integrates anomaly evidence, traffic-intent deviation, trust risk, and provenance contribution. The evaluation design compares IntentProv-IoV with detection, trust, blockchain trust, graph anomaly, Granger causal, structural causal, and counterfactual GNN baselines and includes predictor sensitivity, adaptive adversaries, prediction noise, packet loss, trajectory-only real-data validation, and edge overhead. Simulation-scale results indicate improved attribution precision, stronger traffic-intent deviation reduction, and edge-suitable latency. By shifting V2X security from message-level detection to causally explainable traffic-intent assurance, IntentProv-IoV provides a more accountable security objective for cooperative vehicular systems. Full article

Precision livestock farming (PLF) integrates sensing technologies, data acquisition (DAQ) systems, and machine learning (ML) frameworks to continuously monitor individual animals and support welfare assessment through physiological and behavioral observations. Advances in infrared thermography, radar sensing, vision-based systems, acoustic monitoring, and wearable technologies have substantially expanded the ability to collect high-resolution data describing animal responses to internal and external stimuli. However, despite considerable technological progress, a persistent gap remains between sensing performance demonstrated under controlled experimental conditions and reliable deployment within commercial livestock environments. This gap is characterized by environmental variability, unrestricted animal movement, and operational constraints within commercial environments. Using a structured review methodology, this review examines sensing modalities, embedded DAQ architectures, communication strategies, ML methodologies, data privacy, farmer adoption, and an illustrative engineering workflow through the lens of welfare-relevant physiological characteristics. Emphasis placed on the distinction between direct sensor measurements and the biological processes they represent. Sensor outputs do not directly quantify welfare, stressors, or management outcomes; rather, they provide measurements of physiological and behavioral responses that require appropriate biological context for meaningful interpretation. As a result, welfare assessment does not depend solely on the ability to acquire data, but also on the ability to accurately relate those data to underlying physiological mechanisms. Within this framework, ML serves as a critical bridge between measurement and interpretation by enabling the analysis of complex, multimodal datasets. Future advancement of welfare-oriented PLF systems will require stronger alignment among sensing methodologies, physiological understanding, and practical deployment realities to generate meaningful, scalable, and biologically grounded welfare assessments. Full article

This study reassesses whether China’s 2018 Supply Chain Innovation and Application Pilot Policy changed corporate green innovation. The policy designated both 55 pilot cities and 266 pilot enterprises. To resolve ambiguity in treatment assignment, firms headquartered in pilot cities constitute the primary treatment group, while official pilot-enterprise status is analyzed separately. The updated panel contains 33,473 firm-year observations for 4265 A-share listed firms from 2011 to 2023; the main specification links covariates at year t to patent applications at t + 1, so outcomes extend through 2024. Firm and year fixed effects are included, and inference is clustered by city in the pilot-city design. Pilot-city exposure is associated with a 0.050 increase in log(1 + green invention patents) (p = 0.037), equivalent to a 5.16% change in one plus patent counts, or approximately 0.271 additional patents at the post-policy control mean. The corresponding pilot-city coefficient for utility model patents is −0.041 (p = 0.060). A joint event-study test does not reject equal pre-policy trends (p = 0.653), although the invention effect attenuates in the latest outcome cohort. Official pilot-enterprise exposure is associated with positive coefficients for both patent types. Robustness is mixed: the pilot-city invention result is directionally consistent under negative-binomial estimation and entropy balancing, but is not significant under PPML, industry-by-year fixed effects, or propensity-score matching. Exploratory channel tests do not support talent structure, lagged technology novelty, or information transparency as candidate pathways. Pilot-city exposure is associated with a higher share of cited patents but not with significantly lower environmental protection costs. The evidence therefore supports a narrow conclusion: the pilot-city estimates are consistent with a modest reallocation toward invention-oriented and more frequently cited green innovation, but the average causal magnitude and causal channels remain uncertain. Full article

Offshore wind power has expanded rapidly in recent decades and is expected to continue growing through the deployment of larger turbines in deeper waters. The safe and stable operation of offshore wind turbines (OWTs) depends critically on foundation performance, which is severely threatened by seabed scour. To better understand these threats, this paper reviews recent studies on the effects of seabed scour on the structural performance and safety of fixed-bottom offshore wind turbine foundations (OWTFs), focusing on four aspects: (1) the changes induced by scour in both the seabed morphology and the soil mechanical state, which form the basis for the subsequent analyses; (2) the effects of scour on the bearing capacity and natural frequency of the foundation, covering both its static and dynamic performance; (3) the behavior of scoured foundations under long-term cyclic loading during normal operation and under transient seismic action during extreme events; and (4) the role of scour protection in enhancing structural safety. Several future research directions are also highlighted. This review offers helpful insights for assessing scour-induced risk and for designing scour protection from a structural safety perspective, thereby supporting the safe operation of OWTs. Full article

Background/Objectives: This study evaluated the real-world effectiveness and safety of intranasal esketamine plus oral antidepressants compared with venlafaxine-based oral antidepressant therapy in adults with moderate-to-severe treatment-resistant depression (TRD). Methods: This retrospective cohort study used electronic medical records from a mental health hospital between January 2023 and December 2025. Adults with moderately severe or severe major depressive disorder who had not responded adequately to at least two antidepressant trials received esketamine plus oral antidepressants or venlafaxine-based therapy. The outcomes were changes in the Patient Health Questionnaire-9 (PHQ-9) score, remission, response, minimal clinically important difference (MCID) without response or remission, and documented adverse events at 28 days, 3 months, and 6 months. Propensity score matching was used for continuous follow-up of the PHQ-9 outcomes. Results: The analytic baseline cohort included 82 patients treated with intranasal esketamine-based therapy and 87 treated with venlafaxine-based therapy. The esketamine group had greater baseline depression severity and more previous antidepressant failures. At 3 months, no patients who continued treatment in either group met the remission criterion, one esketamine-treated patient achieved a response, and 37/61 (60.7%) esketamine-treated patients and 23/72 (31.9%) venlafaxine-treated patients achieved MCID without response or remission. At 6 months, remission remained absent; 27/61 (44.3%) esketamine-treated patients and 9/72 (12.5%) venlafaxine-treated patients met the response criterion, whereas 34/61 (55.7%) and 63/72 (87.5%) achieved MCID without response or remission, respectively. In propensity score-matched analyses, follow-up PHQ-9 scores were 1.02 points lower at 3 months (average treatment effect [ATE], −1.02; 95% CI, −1.70 to −0.35; p = 0.003) and 1.94 points lower at 6 months (ATE, −1.94; 95% CI, −3.17 to −0.71; p = 0.002) in the esketamine group than in the venlafaxine group. Dissociation and dizziness were documented more often in the esketamine group, whereas sexual dysfunction was documented more often in the venlafaxine group. Conclusions: In this retrospective routine care cohort, esketamine was used in patients with more complex TRD and was associated with modestly lower matched follow-up PHQ-9 scores. The observational design, baseline imbalance, and attrition precluded causal conclusions. Full article

Background: Type 2 diabetes mellitus (T2DM) is a chronic metabolic disorder characterized by impaired glucose homeostasis, insulin resistance, and progressive β-cell dysfunction. Increasing evidence suggests that glucose homeostasis is regulated not only by peripheral metabolic organs but also by central nervous system and autonomic pathways. Photobiomodulation (PBM) has been reported to modulate mitochondrial function, oxidative stress, vascular responses, and neural activity; however, its potential influence on glycemic outcomes remains largely unexplored. Objective: This prospective pilot study aimed to evaluate the feasibility of applying multi-wavelength LED irradiation to a predefined cranial region and to explore preliminary glycemic outcomes in individuals with T2DM. Methods: Seven participants with physician-diagnosed T2DM receiving stable antidiabetic medication regimens were enrolled. Multi-wavelength LED irradiation (660, 850, and 940 nm) was applied bilaterally to the predefined S3 region of the skull. Irradiation parameters included an irradiance of 5 mW/cm² (0.005 W/cm²), an energy density of 4.5 J/cm², and an exposure duration of 900 s per session. Treatments were administered three times weekly for four weeks (12 sessions). Primary outcome measures included fasting blood glucose (Glucose AC) and glycated hemoglobin (HbA1c). Secondary outcomes included mean blood glucose, fasting insulin, C-peptide, homeostasis model assessment of insulin resistance (HOMA-IR), lipid profile, and C-reactive protein (CRP). Exploratory paired statistical analyses were performed following assessment of data normality using the Shapiro–Wilk test. Results: Following the four-week intervention, fasting blood glucose and mean blood glucose were significantly reduced (p = 0.026 and p = 0.044, respectively), whereas HbA1c demonstrated a borderline reduction (p = 0.051). Changes in fasting insulin, C-peptide, HOMA-IR, lipid profile, and CRP were variable and did not reach statistical significance. No intervention-related adverse events were observed, and all participants completed the study protocol. Conclusions: Multi-wavelength LED irradiation applied to the predefined S3 region of the skull was feasible, safe, and well tolerated in individuals with T2DM. The observed preliminary glycemic outcomes support the feasibility of further investigation in larger randomized controlled trials. However, because of the small sample size, absence of a control group, and exploratory study design, the present findings should be interpreted cautiously and should not be considered evidence of clinical efficacy or causal effects. Full article