Search Results (140)

As renewable penetration in data-center power supply increases, stochastic renewable output can cause tie-line power fluctuations between data centers (DCs) and the utility grid. This paper proposes a privacy-preserving multi-time-scale tie-line power smoothing method for multiple DCs. A two-stage first-order low-pass filter decomposes tie-line fluctuations into high- and low-frequency regulation targets. Server task shifting tracks the high-frequency target, while uninterruptible power supply (UPS) regulation compensates the low-frequency residual under practical energy and power constraints. Second, a federated adaptive proximal policy optimization (Fed-AdaPPO) framework is developed. Proximal policy optimization (PPO) provides stable policy optimization in the continuous action space, and the upper confidence bound (UCB)-guided adaptive exploration improves task-shifting exploration. Critically, only Critic gradients are aggregated across DCs; Actor networks, raw workload data, and user-sensitive information remain local. This design reduces the risk of exposing local state-action mappings. Results show that coordinated server-cluster and UPS regulation reduces the standard deviation of tie-line power by at least 33.4% while maintaining service quality and data privacy. Full article

This study develops a bottom-up cost optimization model (DC-DECOM) to evaluate decarbonization pathways for Japan’s data center industry, targeting carbon neutrality of the information and communications technology (ICT) sector by 2040. The model represents Power Usage Effectiveness (PUE) as a dynamic function of ambient temperature and cooling technology, and integrates technology selection, regional energy supply, and carbon pricing within a single cost-minimization framework. Three scenarios are compared: a reference case (REF), a centralized carbon-neutral scenario (C-CN) that restricts new capacity to metropolitan areas, and a regional decentralization scenario (R-CN) that allows for nationwide siting. Input parameters are calibrated against data from the International Energy Agency (IEA), the Uptime Institute, Japan’s Ministry of Internal Affairs and Communications (MIC) White Papers, and the Japan Science and Technology Agency (JST). The R-CN scenario achieves the 2040 net-zero target at 18–23% lower total system cost than C-CN. The cost gap decomposes into four channels (cooling-energy reduction ∼35%, lower regional renewable procurement cost ∼30%, lower carbon cost ∼25%, and lower siting-related cost ∼10%). Sensitivity analysis identifies the carbon-price trajectory and the hardware-efficiency improvement rate as the most influential parameters; the R-CN advantage remains positive across all $\pm 1\sigma$ parameter variations and across two combined-scenario stress tests. Full article

While drones play important roles in areas such as communication and logistics delivery, they have certain limitations in emergency rescue scenarios due to their inability to carry passengers. Building on mature drone technologies such as autonomous flight and environmental perception, unmanned passenger Electric Vertical Take-off and Landing (eVTOL) aircraft are designed with a manned cabin, enabling them to operate without an onboard pilot while rapidly transporting injured people. Consequently, eVTOLs can play a significant role in emergency rescue that cargo-only drones cannot fulfill, as they are capable of rapidly reaching emergency scenes, effectively overcoming the delays caused by traditional ground traffic congestion. Despite their potential, eVTOLs still face several critical obstacles, including signal disruption, limited coverage of dispatching centers, mutual authentication among entities, and concerns related to security and privacy preservation. As a remedy, this paper presents a lightweight authentication protocol leveraging drone assistance to overcome these challenges for unmanned eVTOL emergency rescue. In scenarios where an unmanned eVTOL experiences signal blockage due to dense urban high-rise structures, neighboring drones can serve as a transmission relay to assist the unmanned eVTOL and the dispatch center (DC) in completing mutual authentication and session key negotiation, thereby enabling the unmanned eVTOL to safely complete its mission. To enhance security, physical unclonable functions (PUFs) are integrated into unmanned eVTOLs, drones, and the DC, safeguarding sensitive data against side-channel and physical capture attacks while preserving the confidentiality of unmanned eVTOL identities to mitigate privacy risks. Our protocol achieves provable security in the random oracle model while exhibiting strong resistance to various well-known attacks. Comparative analysis with the existing drone authentication and drone-assisted emergency rescue authentication protocols reveals that our protocol not only provides stronger security guarantees but also maintains a low computational overhead. Full article

Because smart microgrids can flexibly integrate distributed energy resources and support grid-connected and islanded operation modes, they enhance power supply reliability and promote the efficient utilization of renewable energy. However, the open communication environment and physically exposed infrastructure introduce critical security challenges, including risks of physical hijacking and data leakage. Many existing authentication protocols either fail to address these threats or rely on heavyweight cryptographic operations such as bilinear pairings and modular exponentiation, resulting in high computational and communicational overhead. To address these issues, a lightweight authentication and key agreement (AKA) protocol for smart microgrids is proposed. The protocol symmetrically integrates Physical Unclonable Functions (PUFs) into the smart meter (SM) and smart microgrid control center (SMC) to protect stored secret information against capture attacks. Meanwhile, the SM and SMC register with the data center (DC) in a symmetric manner. During the AKA phase, the DC only assists in authenticating the identities of the SM and SMC online in a symmetric way, without participating in session key computation, thereby reducing the trust burden and computational load on the smart meters and control center. Formal security proof and informal security analysis demonstrate that the proposed protocol can resist known attacks such as physical hijacking and data leakage. Compared with existing smart microgrid authentication protocols, the proposed protocol has performance advantages and the lowest computational cost, confirming its suitability for resource-constrained microgrid environments. Full article

As the core of digital infrastructure, the exceptionally rapid development of data centers (DCs) faces serious challenges due to their high electricity costs. Traditional approaches treat computational task scheduling separately from different physical control mechanisms, such as server group management, overlooking the synergistic potential between the two aspects. To address this problem, this paper proposes a computational–physical collaborative optimization model that realizes spatiotemporal task migration on the computational side and adaptive parameter regulation of IT equipment and cooling devices on the physical side. In response to the lack of global coordination in conventional distributed optimization, a two-layer partially observable Markov game (POMG) is constructed to unify global cooperative decision-making and local autonomous control. On this basis, the hierarchical multi-agent deep deterministic policy gradient (H-MADDPG) algorithm is designed by introducing task priority ranking and a variable-dimension action mask mechanism, which effectively handles the discrete–continuous hybrid action space and adapts to the dynamic variation in action dimensions caused by uncertain task arrivals. Comparative experiments with various benchmark schemes are conducted to verify the effectiveness and superiority of the proposed strategy in total cost, power usage effectiveness (PUE), resource utilization, and load balancing. Full article

AI data-center (DC) growth is increasingly constrained by limited deliverable electricity, interconnection capacity, and cooling demand. This study develops a boundary-consistent screening framework for waste-to-energy (WtE)-coupled AI DC cooling, treating cooling as an energy service that can be supplied through grade matching rather than solely through electricity-driven mechanical chilling. The framework translates plant-side exportable heat into corridor-level planning objects by explicitly accounting for thermal attenuation, absorption-based conversion, and parasitic electricity associated with delivery and auxiliaries. Three results structure the analysis. First, a reference-case energy-service ledger shows how a representative regulated WtE plant with municipal solid-waste throughput of 1500 t/day and lower heating value of 10 MJ/kg yields ~78.1 MWth of exportable driving heat and, at a 20 km corridor, ~53.0 MWcool of delivered cooling and ~8.0 MWe of net avoided cooling electricity after parasitic debiting. Second, the coupled system is governed by operating regimes, not a single efficiency score. Under the baseline package, full thermal coverage is maintained up to ~20.9 km, the stricter quality-adjusted criterion remains positive to ~22.9 km, and the electricity–relief criterion remains positive to ~44.7 km. Third, deployment-scale translation for a 1 GW IT campus ($u=0.70$, $L=5 \mathrm{k}$m) implies a net grid relief of ~116.9–264.4 MW across scenario packages, while the required WtE footprint ranges from roughly three to 148 equivalent representative plants, or about 0.6–40 full-load-equivalent plants at a 25% displacement target. The contribution is a siting-ready planning framework that identifies when WtE-coupled cooling remains corridor-feasible, when it becomes hybrid and marginal, and when infrastructure scale rather than thermodynamic benefit becomes the binding constraint. It is intended as a screening tool for planning and comparison, not as a project-specific hydraulic or plant-cycle design. Full article

DC distribution systems are increasingly utilized in data centers, electric vehicle charging infrastructures, and microgrids due to their superior power conversion efficiency compared to AC systems. In DC networks, the protection coordination of overcurrent relays (OCRs) is essential for selectively isolating faults and maintaining operational stability. However, the integration of distributed energy resources (DERs), such as photovoltaics, introduces significant challenges by altering the magnitude and rate of change of fault currents. This study conducts a comprehensive analysis of various scenarios by varying both the fault location and the points of common coupling (PCC) for DER. The simulation results reveal that specific configurations lead to critical instances of protection mis-operation and failure to operate, which cause coordination failures and compromised coordination time intervals (CTIs). These findings demonstrate that conventional protection strategies may fail to ensure reliability in DER-integrated DC systems due to the dynamic nature of fault current characteristics. In this paper, these diverse scenarios and the resulting vulnerabilities in protection coordination were modeled and verified using PSCAD/EMTDC V5.0. Full article

Background/Objectives: Critical limits define quantitative thresholds for life-threatening diagnostic test results that require immediate clinician notification and may prompt urgent intervention to prevent adverse outcomes. This study aims to (1) characterize point-of-care (POC) critical limits for adults and newborns using a comprehensive U.S. national database, (2) identify POC instruments associated with these limits, and (3) support harmonization of point-of-care testing (POCT) practices. Methods: We gathered critical limit notification lists from 417 hospitals across all 50 states and Washington D.C., comprising university hospitals, trauma and heart centers, centers of excellence, community hospitals, and network hospitals. We extracted POC and central laboratory critical limits (at hospitals with POC), adult international normalized ratio (INR) data, and instrument usage. Results: Low and high glucose critical limits were the most frequently listed POC thresholds, with median values of 50 and 450 mg/dL, respectively, reported by 73 hospitals (17.5%). Troponin was listed by ten hospitals, specified as troponin (n = 4), troponin I (n = 5), or “troponin TnI” (n = 1). A few hospitals assigned instrument-specific critical limits for the same analyte, and 55 hospitals did not specify instrument usage for any measurand. Median differences in matched pairs of laboratory versus POC critical limits differed significantly (Wilcoxon signed-rank, p < 0.05) for low and high ionized calcium (n = 21), low hemoglobin (n = 23) and high INR critical limits for adults (n = 27) and newborns (n = 10). In some cases, matched pair analytes demonstrated identical critical limits. Conclusions: Harmonizing critical limit notification thresholds across point-of-care testing and different devices may improve consistency in clinical decision-making and patient outcomes. Despite the potential of POCT to shorten time to urgent intervention, relatively few hospitals currently include POCT critical limits on notification lists. Establishing standards, annual updating, and enforcing risk mitigation could enhance adoption and reliability. Broader inclusion and transparent sharing of POCT critical values could harmonize practices across institutions, facilitate inter-institutional collaboration, and promote more timely and reliable responses to life-threatening diagnostic results. Full article

This study presents a GIS-driven multi-criteria decision analysis (MCDA) framework for regional suitability screening of data center (DC) development in the United Kingdom. The methodology integrates spatial exclusion of constrained zones, raster standardization of climate and infrastructure indicators, Analytic Hierarchy Process (AHP) weighting, and Weighted Linear Combination (WLC) to generate a national suitability surface at 1 km resolution. Climate indicators (temperature, air frost days, humidity, and solar radiation) and infrastructure and environmental constraint indicators (grid access, transport proximity, environmental protections, and population distribution) were standardized and combined within a GIS-based decision framework. Hard constraints such as protected areas and flood zones were applied through binary exclusion, while climatic and infrastructure factors were evaluated using weighted suitability scoring. Five candidate regions were identified from the suitability analysis: the Scottish Highlands, Northeast England, Southwest England (Cornwall), Northwest England, and Eastern England. These regions were further evaluated against key requirements including power infrastructure accessibility, workforce and connectivity availability, and exposure to environmental and hydro-climate constraints. The final comparison identified Lincolnshire as the most suitable region due to strong grid accessibility, favorable composite climate suitability, adequate population proximity, and limited overlap with protected areas. The proposed framework demonstrates how climate-driven cooling suitability can be integrated with infrastructure accessibility and environmental constraints within a unified spatial decision model for national-scale digital infrastructure planning. Full article

A photovoltaic (PV) and battery-based energy system can provide the necessary and sufficient electric power to off-grid power system networks due to the technological advancements in both performance improvement and lower system cost. The absence of reactive power in direct current (DC) power system networks has several advantages over corresponding alternating current (AC) power system networks. In this paper, we have investigated a case study for the PV farm coupled with a battery energy storage system (BESS) as a stand-alone power system network in the Red Sea New City, Kingdom of Saudi Arabia. The study consists of two cases, which are the DC battery coupling configuration for the AC power network system and the end-to-end DC (EEDC) configuration for the power network system. Using the same size of solar PV farm and battery storage, we have compared the performance of the two case configurations of different power system networks after thirty years of operation. The results show that implementing the EEDC power system network has a major advantage in improved energy efficiency of the power system (directly related to cost-effectiveness) and lower capital investment of the power system that includes electric power generation, transmission, distribution, and utilization for all applications, including artificial intelligence-based data centers. Full article

The infield transport of harvested sugarcane stalks (transshipment operation) during mechanized harvesting is widely recognized as the operation with the greatest potential to induce soil compaction. Nevertheless, there is still a lack of experimental data on the effect of compaction resulting from transshipment vehicles on soil physical functionality. We assessed the effects of realistic infield traffic from different transshipment configurations on soil structural and functional properties and their effects on crop yield. Three transshipment systems under controlled traffic farming system were evaluated: a tractor pulling one four-axle trailer unit with 21 Mg carrying capacity (1T/21), a tractor pulling two axle trailer units with 10 Mg carrying capacity (2T/10), and an autonomous truck with four axles and one trailer with 20 Mg carrying capacity (1TT/20). Several analyses were conducted, including degree of compaction (DC), macroporosity (MaP), air-filled porosity (ε_a10), soil air permeability (k_a10), and saturated hydraulic conductivity (Ks). Soil samplings were performed in surface and subsurface layers of an Oxisol in southeastern Brazil at the planting row and inter-row, and at the midpoint between these positions, over two consecutive sugarcane harvests. Although machine traffic occurred at low soil water content, all transshipment configurations promoted soil compaction during the first harvest, with the greatest changes in soil physical attributes in the 0–10 and 10–20 cm layers in the inter-row center and, in some cases, at the midpoint. However, all treatments preserved soil conditions in the planting row. The 1TT/20 transshipment induced the greatest compaction, with significant effects on DC, MaP, and ε_a10 in the inter-row and midpoint positions. Despite structural alterations, no significant differences were observed among treatments for k_a10 and Ks. However, after the first harvest, k_a10 frequently reached critical thresholds of low permeability in trafficked areas, indicating functional degradation of soil aeration. Sugarcane yield was not affected by the transshipment configurations. The absence of productivity differences reflects the effectiveness of controlled traffic in confining compaction to the inter-row center and midpoint while preserving the planting row. Although short-term yield was not affected, structural degradation in trafficked areas and the persistence of high subsoil compaction indicate the potential for cumulative long-term impacts. Continuous monitoring and integrated soil management strategies remain essential to mitigate progressive compaction under mechanized sugarcane harvesting. Full article

The exponential growth in demand for data storage and computing has led to a rapid expansion in the energy consumption and carbon emissions of data centers (DCs). Hybrid energy systems that integrate renewable energy sources are regarded as a sustainable and low-carbon solution for powering the DCs. This study proposes an optimal cooperation scheduling strategy for the hybrid energy system powering the DC and electric vehicles (EVs). The strategy is based on load transferring and operates within a carbon trading mechanism, explicitly addressing the coupling between computational loads and power consumption. An optimization model is constructed that considers economic objectives, including operational cost and a stepped carbon trading cost, to obtain optimal energy dispatch and computational task allocation strategies. This framework ensures the economic interests of EVs’ owners while satisfying the energy demands of both the DC and the EVs. The results of a case study based in Shanghai demonstrate that the proposed hybrid energy system with multiple sources has significant economic and environmental advantages in spite of operational complexity. Furthermore, the collaborative strategy further enhances the cost reduction and carbon emission reduction. Specifically, the cooperative strategy achieves a 5.21% reduction in total cost compared to Case 1 (without V2G) and a 22.80% reduction compared to Case 2 (without computing task transferring). By adopting the optimal scheduling solution, carbon emissions can be reduced by 16.74% relative to Case 1 while remaining at a level comparable to Case 2. Furthermore, the impact of the carbon trading mechanism on the system’s cost and carbon emissions is analyzed. The results indicate that while a stricter carbon trading mechanism leads to an increase in the total cost, it also results in a reduction in carbon emission from the DC’s hybrid energy system. Full article

Background: The prognosis of glioblastoma (GBM) patients remains poor. Dendritic cell (DC) vaccination has been investigated as an immunotherapy option, mainly in early-phase clinical studies. Herein, we report the feasibility, safety, and descriptive clinical and radiological outcomes of a retrospective series of newly diagnosed GBM patients treated with standard radio-chemotherapy and autologous DC vaccination as compassionate use. Methods: We retrospectively reviewed the medical and radiological records of patients with newly diagnosed GBM who received autologous tumor lysate–pulsed DC vaccination in addition to standard-of-care treatment at a tertiary academic center between 2009 and 2017. Clinical data, treatment characteristics, adverse events, survival outcomes, and radiological responses were collected and analyzed descriptively. Results: Twenty-four patients were included. All patients underwent surgical resection and were further treated with autologous tumor lysate–DC vaccination and standard radio-chemotherapy. Histology of GBM was confirmed in all patients. The first vaccine was administered in 75% of patients after a median of 21 days (range: 6–30 days) following surgery and prior to radiotherapy initiation. DC vaccination was continued following radiotherapy at specific time points, with no observed significant adverse events. Median OS was 21.1 months (95% CI, 27.9–75.0 months), and median PFS was 10.3 months (95% CI, 15.6–26.6 months). Presence of O6-methylguanine DNA methyltransferase (MGMT) promoter methylation was associated with longer survival and higher 12-month PFS rates, consistent with its established prognostic value. Radiological responses were retrospectively assessed according to RANO and RANO 2.0 criteria. Conclusions: In this retrospective single-center series, autologous DC vaccination administered as compassionate use in combination with standard radio-chemotherapy was feasible and safe in routine clinical practice. Survival and radiological outcomes are reported descriptively and should be interpreted with caution given the absence of a control cohort. These findings support further prospective controlled studies to properly assess the clinical role of DC vaccination in newly diagnosed GBM. Full article

The stochastic fluctuations of AI computational loads inject harmonic currents into the DC bus, amplifying bus voltage ripples and weakening the power quality. Existing strategies typically rely on high-gain control strategies to minimize harmonic output impedance, aiming at full absorption of harmonic currents. However, such designs rarely consider engineering constraints such as capacity and current boundaries, which impose inherent limits on harmonic absorption. To address these issues, this paper proposes an adaptive harmonic impedance control and flexible compensation method for AI data centers. By integrating DC bus voltage feedforward with output current feedback, a virtual harmonic impedance control channel is constructed to enable real-time impedance shaping. Then, an adaptive gain regulation mechanism is developed to adjust harmonic impedance according to the available capacity and current margin. Compared with traditional strategies relying on fixed high gains or resonant links, the proposed method allows for the continuous regulation of harmonic impedance over a wide range. This enables the dynamic matching of harmonic absorption capability with the available capacity, effectively suppressing the risks of overcurrent, saturation, and stability degradation. Simulation and 8 kW experimental results verify the correctness and effectiveness of the proposed analysis and control strategy. Full article

The Australian public and broader society have little awareness of the seminal relationship between water supply and data usage/storage. Most data centers (DCs) consume large volumes of water to operate servers that supply digital society’s instantaneous 24/7 information communication systems. DC water consumption is a global issue that lacks transparency, sustainable management, and effective governance. This article analyzes current Australian legislation, policies, and industry sustainability plans to examine whether and in what ways the absence of clear water governance requirements for DC may contribute to state and national water insecurity. It shows how academic and applied discourses conceptualize, research, and respond to DC sustainability as an energy issue. This conceptualization masks the relevance of DC water usage/security. The results show that Australian legislation, policy, planning, and management lack sufficient transparency and state governance regarding the industry’s water use and accountability. Global and national DC certifications are discussed, and policy solutions are recommended to mitigate future DC pressure on water supply and related consequences. Our conclusions advocate the necessity of improving public awareness, industry accountability, and government management strategies (policy and legislation) for sustainable water practices in Australia, as artificial intelligence increases DC quantity and size, exacerbating supply and consumption in local environments that legislate against nuclear energy alternatives. Full article