Search Results (12,278)

Traditional evaluation of Networks-on-Chip is based on aggregate metrics. Most of these metrics (latency, throughput, hop count, packet loss, energy consumption, buffer occupancy, thermal or reliability summaries) compress detailed execution traces into a few scalar values. This dimensionality reduction hides spatial, temporal, and resource-level differences between simulations. This paper introduces an Entropic Structural Observability framework for routing-independent post-simulation analysis of NoC traces. The main idea of the framework is to convert typed packet-level events into probability distributions over used resources, including routers, directed links, time windows, and critical resources. As a final report, the method builds a structural signature. This signature includes normalized entropy, effective support, concentration, spatiotemporal mutual information, distribution drift, topology-aware spatial statistics, buffer-pressure measures, and classical imbalance indicators. The analysis does not modify simulation traces; it operates as a diagnostic layer. It reveals activity distribution, temporal dependence, spatial evolution, resource pressure, and structural imbalance. The framework is evaluated on 256-router 2D and 3D mesh topologies using deterministic and adaptive routing policies under diverse traffic patterns and injection rates, enabling its structural signatures to be examined across different network dimensionalities. The results reveal distinct structural regimes: deterministic dimension-order routing shows broad spatial and temporal dispersion, DyAD exhibits stronger time-space coupling and drift, and Fully-Adaptive presents an intermediate profile with high dispersion but moderate temporal variation. Full article

Versatile nanostructured materials based on electrochemically etched porous silicon (pSi) are being developed, which have tuneable pore morphology and unique optical and electrochemical properties that enable their effective biosensing applications. It has been shown that fabrication parameters critically influence pore formation and sensor performance, yet challenges remain in reproducible synthesis, structural stability and device integration. Here we review the electrochemical etching synthesis of pSi and recent advances in pSi-based optical and electrochemical biosensors for detecting bacteria, biomolecules, and viruses. We highlight strategies such as surface functionalisation, incorporation of nanomaterials, and integration with microfluidic and lab-on-a-chip technologies that enhance sensitivity and response times by addressing mass transfer limitations. These developments highlight pSi’s potential as a low-cost, adaptable biosensing material with applications in clinical diagnostics and environmental monitoring, while mapping future directions to overcome current fabrication and stability challenges. Full article

Background: The zebrafish model is extensively utilized for phenotypic screening, particularly in heart failure research. However, traditional photography-based data collection requires tricaine methanesulfonate (MS-222) anesthesia, which can suppress cardiac function and introduce artifacts. This study presents a microfluidic platform designed to facilitate anesthesia-free, noninvasive in vivo photography of zebrafish heart failure models. Methods: Isoproterenol (ISO) induced heart failure in 1 day post-fertilization (dpf) zebrafish embryos. Larvae were assigned to three groups: Control (E3 embryo medium only), Model (1 mM ISO for 48 h from 1 dpf), and Positive (1 mM ISO + 10 μM propranolol for 48 h from 1 dpf). Subsequently, a microfluidic chip featuring tapered immobilization channels was adopted. The chip facilitated the photography and collection of cardiac function parameters from lateral and supine positions, including cardiac output (CO), blood flow velocity (BFV), ejection fraction (EF), stroke volume (SV), and fractional shortening (FS). All imaging was performed in completely independent parallel experiments, with no individual larva shared between the two imaging methods. Data obtained under hydrodynamic confinement were compared with those acquired under MS-222 anesthesia. Results: Cardiac parameters measured using the microfluidic platform were significantly higher than those under MS-222 anesthesia: CO (0.339 ± 0.032 vs. 0.279 ± 0.023 nL/s, p < 0.001), BFV (681 ± 53 vs. 604 ± 38 μm/s, p < 0.001), EF (10.3 ± 0.7% vs. 6.6 ± 0.7%, p < 0.001), SV (184,519 ± 12,822 vs. 97,979 ± 5306 μm³, p < 0.001), and FS (7.3 ± 1.8% vs. 3.7 ± 0.9%, p < 0.001). Strong correlations (R² > 0.85, p < 0.0001) revealed that anesthesia underestimated parameters by 11.3–49.3%. Conclusions: Compared with the traditional anesthesia-based method, the microfluidic platform enables more precise cardiac parameter collection in a zebrafish heart failure model than when anesthesia is used, offering a reliable tool for phenotypic screening of zebrafish embryos. Full article

The rapid growth of artificial-intelligence (AI) and high-performance computing workloads has reshaped the power-delivery requirements of high-bandwidth memory (HBM), neural processing units (NPUs), and advanced systems-on-chip (SoCs). These platforms draw large currents that vary rapidly at aggressively scaled supply voltages, so their on-chip regulators must combine high current density, nanosecond-scale settling with minimal droop, wideband power-supply rejection (PSR), and stable capacitor-less operation, while also mitigating issues such as power supply-induced jitter (PSIJ) in high-speed clock and data paths. On-chip low-dropout (LDO) regulators have become the key building block at the point of load, and a wide range of architectures have emerged to meet these demands. This paper reviews on-chip LDOs for HBM and SoC power integrity. We translate application-level power-integrity requirements, including PSIJ, into circuit specifications; organize the design space into fast-transient, wideband high-PSR, high-current and distributed, and capacitor-less and digital/hybrid architectures; benchmark representative state-of-the-art designs using both conventional and application-relevant metrics such as data rate, jitter, and eye margin; and distill the resulting technology trends. Full article

Edge inference on resource-constrained embedded nodes demands accelerators that are energy-efficient and compact. This paper presents Versat-AI, an open-source compiler that accepts a standard Open Neural Network Exchange (ONNX) model and generates a complete, synthesisable RISC-V System-on-Chip (SoC) with an embedded CGRA accelerator. The key innovation is applying a known hardware merge strategy to collapse structurally compatible neural network operators into a physical CGRA instance. The Versat-AI compiler also derives memory-mapped interconnects, firmware drivers, and RISC-V application software co-generated by the Py2HWSW SoC framework, eliminating the manual hardware/software co-design effort that previously tied this accelerator’s own design lineage to a single target network. The next phase of the project is to extend this same automatic derivation from sizing the operator vocabulary to sizing per-operator parallel instancing and bandwidth, following the bandwidth-matched scaling principle already demonstrated, by hand, in this accelerator’s own design lineage. The current phase of the project has succeeded in creating a sound automation flow that produces an accelerator that maps each operator onto a single physical datapath instance and occupies 8763 LUTs, 9833 flip-flops, 4 DSPs, and 202 BRAMs on a Xilinx Kintex UltraScale field-programmable gate array (FPGA)—a footprint unchanged across all evaluated models regardless of size—and draws 0.65 W (1.96 W for the complete SoC including the DDR4 controller, by Vivado post-implementation power estimation), achieving $2.3\times$ to $9\times$ speedup over the software-only baseline produced by the same flow on four MLPerf Tiny benchmark tasks. The paper further examines the design choices that delimit this first phase—single-precision arithmetic, a single datapath instance per operator, and the block-RAM cost of the accelerator’s streaming buffers—and sets out the path to quantised integer support and parallel operator instancing. A condensed account of the two-decade lineage of reconfigurable accelerators and open-source SoC platforms that motivated Versat-AI’s design is also given. Full article

Near-ultraviolet-excitable red phosphors with high thermal stability are desirable for phosphor-converted LED applications, including potential plant-lighting applications. Herein, Sm³⁺- and Eu³⁺-activated Na₃YB₈O₁₅ phosphors were synthesized by a high-temperature solid-state reaction. Among the investigated compositions, the optimal activator contents were identified as x = 0.02 for Na₃YB₈O₁₅:xSm³⁺ and y = 0.70 for Na₃YB₈O₁₅:yEu³⁺, with concentration quenching in both series mainly governed by dipole–dipole interactions. In the Sm³⁺/Eu³⁺ co-doped phosphors, the emission color shifted from orange-red toward red as the Eu³⁺ content increased. At 433 K, the Sm³⁺-doped, Eu³⁺-doped, and Sm³⁺/Eu³⁺ co-doped samples retained 119.7%, 93.4%, and 102.3% of their room-temperature integrated emission intensities, respectively. The high thermal stability may be attributed to the structural characteristics of the host, its wide optical band gap, and the temperature-dependent redistribution of Stark and phonon-assisted emission components. A phosphor-converted LED fabricated using Na₃YB₈O₁₅:0.02Sm³⁺,0.01Eu³⁺ and a commercial 400–405 nm, 5 W near-UV LED chip produced multiband emission that partially overlapped with the absorption bands of both chlorophylls and the P_R and P_FR forms of phytochrome. These results suggest that Sm³⁺/Eu³⁺-activated Na₃YB₈O₁₅ is a promising thermally robust, spectrum-adjustable red phosphor for LED applications. Full article

Boosting requirements for portable and wearable electronic systems have substantially stimulated sustainable advancement of high-performance flexible planar microsupercapacitors (MSCs). However, the low comprehensive electrochemical performance of flexible planar MSCs proves to be the major hurdle to practicality. Herein, the scalable manufacturing of integrated flexible planar MSCs based on graphene quantum dots (GQDs) with tandem-interdigitated architecture was demonstrated through modified liquid–air interfacial self-assembly and photolithography methods. These flexible planar MSCs exhibit exceptional overall electrochemical performance with an areal specific capacitance of 6.35 mF cm⁻², areal energy density of 3.53 μWh cm⁻², areal power density of 8.10 mW cm⁻², excellent cyclic stability maintaining 93.61% of their initial capacitance following 10,000 cycles of cyclic voltammetry operations, and outstanding mechanical flexibility, which attributes to the synergistic effects of GQD active materials, tandem-interdigitated microelectrodes and bendable flexible polyethylene terephthalate substrate. This work unveils a straightforward and scalable process for fabricating high power density, all-solid-state, and integrated flexible planar MSCs with rapid frequency response. Considering their practical utility, these devices hold significant promise as on-chip micro-power sources for portable electronics and wearable microsystems. Full article

Conventional in vitro drug evaluation relies largely on static concentration–response assays that fail to reproduce the dynamic pharmacokinetic (PK) profiles observed in vivo, contributing to the gap between preclinical findings and clinical outcomes. Recent advances in microphysiological systems (MPSs), particularly microfluidic organ-on-chip platforms, enable programmable concentration–time profiles that more closely mimic physiological drug exposure. These PK-informed platforms allow systematic investigation of schedule dependency, time-dependent pharmacodynamics (PD), and exposure-driven efficacy under controlled flow conditions. Spatially resolved analytical approaches further reveal heterogeneous drug penetration and metabolic responses within tissues, emphasizing the importance of spatiotemporal PK–PD coupling. Integration of multi-organ and vascularized chip systems with physiologically based pharmacokinetic (PBPK) modeling increasingly supports quantitative in vitro–in vivo translation. This review outlines how PK-informed MPSs can generate dynamic in vitro exposure and response data that inform PBPK modeling, thereby supporting quantitative in vitro–in vivo translation of drug disposition and response. Full article

Background/Objectives: Postoperative thirst is a common and distressing symptom among surgical patients; however, standardized management guidelines remain limited. Oral care interventions using cold stimulation (e.g., ice chips, popsicles, and menthol-infused products) may relieve postoperative thirst, but variation in intervention protocols and outcome measures has so far precluded clear clinical recommendations. This protocol outlines a systematic review evaluating the effectiveness of cold-stimulation oral care interventions in reducing thirst intensity among adult surgical patients during the immediate postoperative period, defined as the first 6 h after emergence from general anesthesia. Methods: Randomized controlled trials (RCTs) comparing cold-stimulation oral care with standard care will be included; as pre-specified at registration, quasi-randomized trials will be considered only if fewer than three eligible RCTs are identified (appraised with ROBINS-I and reported separately). MEDLINE, Cochrane Library, EMBASE, CINAHL Plus and trial registries were searched. Risk of bias will be assessed using the Cochrane Risk of Bias tool version 2.0. The primary outcome is change in thirst intensity; secondary outcomes are oral dryness, patient satisfaction, and adverse events. Continuous outcomes will be pooled as mean differences, or as standardized mean differences across differing scales, and dichotomous outcomes as risk ratios, with 95% confidence intervals. Random-effects meta-analysis will be performed in R where appropriate, otherwise narrative synthesis, with pre-specified subgroup and sensitivity analyses. Certainty of evidence will be rated using GRADE. Conclusions: This protocol was developed in accordance with PRISMA-P and prospectively registered in PROSPERO (CRD420251139881). The review will clarify the effectiveness and safety of cold-stimulation oral care for postoperative thirst and support perioperative nursing practice. Full article

This paper proposes an on-chip time-to-digital converter (TDC) named pulse delay and capture circuit (PDCC), dedicated to single-event transient (SET) pulse measurement for radiation characterization of flash-based FPGAs. To address the inherent trade-offs of mainstream vernier delay line (VDL) and snapshot TDC schemes, the proposed PDCC employs a 16-stage single-chain self-triggering capture circuit with a SET indicator flip-flop, incorporates heterogeneous-cell ring-oscillator-based process-voltage-temperature (PVT) calibration, and avoids the need for resource-intensive first-in-first-out (FIFO) buffers. Implemented on a 130 nm A3PE600 flash-based FPGA, the PDCC achieves a nominal theoretical resolution of 640 ps and a nominal theoretical dynamic range of 0.64–10.24 ns, with 53.5% lower logic resource overhead than the VDL benchmark. Heavy-ion irradiation experiments validate the measurement capability and reveal asymmetric SET pulse propagation evolution characterized by positive-pulse broadening and negative-pulse attenuation, as well as sensitivity disparities among logic gates, which are attributed to the physical implementation of internal transistor networks within the VersaTile. A multi-criteria assessment based on the Simple Additive Weighting (SAW) method, evaluating resolution, dynamic range, logic resource overhead, and measured SET pulse width, yields an overall performance score (OPS) of 1.43, corresponding to a 43% higher score relative to the VDL baseline. Full article

Blood donation sustains an estimated 118 million annual donations worldwide, and while advances in infectious disease screening have greatly reduced recipient risk, the long-term health of repeat donors has received comparatively less attention. This cumulative review synthesises current evidence on the principal acquired complications of regular blood donation across all modalities—whole blood, plasmapheresis, and plateletpheresis—addressing iron deficiency, plasma protein depletion, apheresis-related lymphopenia, clonal haematopoiesis of indeterminate potential (CHIP), and micronutrient deficiency. Iron deficiency affects 15–36% of frequent whole blood donors and is systematically underdetected by haemoglobin-based screening alone; ferritin-guided interval adjustment and oral supplementation are effective countermeasures. Regular plasmapheresis depletes immunoglobulins (IgG below normal in 5–15% of high-frequency donors), albumin, and coagulation factors, compounded by cumulative citrate-mediated hypocalcaemia. Plateletpheresis causes measurable subset-selective T-cell and NK-cell depletion, with CD4⁺ counts below clinically significant thresholds in a minority of the most frequent donors, an observation of unknown significance. Emerging molecular data indicate that repeated haematopoietic stress selectively enriches low-risk, EPO-responsive DNMT3A clonal variants without increasing malignant risk. Regular blood donation if properly applied is a safe process. Across all domains, current eligibility criteria based on haemoglobin alone turn out to be inadequate; a shift to multiparameter, individualised and targeted donor monitoring—integrating ferritin, serum proteins, differential leucocyte counts, and micronutrient profiling—is both evidence-suggested and ethically worth considering to sustain the long-term health of voluntary donor populations. Full article

This article discusses the intelligent analysis of multisensory biogas data obtained from an experimental dataset generated by a Lab-on-Chip platform. The relevance of this work stems from the need for real-time monitoring of biogas quality and biomass condition under anaerobic digestion conditions, where changes in the concentrations of methane, carbon dioxide, hydrogen sulfide, oxygen, and temperature directly affect the stability of the technological process and the energy efficiency of the plant. This study utilizes a multisensor Lab-on-Chip/biosensor platform designed for rapid analysis of small samples of biogas, biomass, and biomix. The platform integrates gas, liquid, and optical sensor channels, as well as a module for transmitting data to the cloud. The experimental data obtained are processed using intelligent data analysis methods, including statistical analysis, correlation analysis, anomaly detection, and assessment of the relationships between monitored parameters. The scientific significance of this work lies in the application of an integrated approach to the analysis of multichannel experimental data obtained from the ESP32 microcontroller, which enables a more accurate and timely assessment of the state of the biogas process. The practical significance lies in the ability to use the proposed approach for remote monitoring, early detection of anomalies, and improving the efficiency of biogas plant management. Full article

Ti6Al7Nb biomedical alloy is difficult to machine because its low thermal conductivity and high chemical reactivity promote heat accumulation, high cutting loads, and poor surface quality. This study evaluated the side milling performance of Ti6Al7Nb under dry machining, vortex tube cooling, and MWCNT-assisted nanoparticle minimum quantity lubrication (NMQL) to identify a more sustainable and effective machining strategy. Experiments were conducted using two cutting speeds and three feed rates, and machinability was assessed in terms of cutting temperature, resultant cutting force, surface roughness, Tol wear and tool life, chip morphology, and multi-criteria ranking. Compared with dry machining, vortex tube cooling provided the strongest thermal control, reducing cutting temperature by 25–36% compared with dry conditions, owing to the cold air stream generated by the Ranque–Hilsch effect. MWCNT-NMQL produced the greatest reductions in cutting force and surface roughness, with improvements of 7–28% and 10–20%, respectively, compared with dry conditions, due to improved lubrication, reduced adhesion, possible tribofilm formation, rolling/sliding effects of MWCNTs, and enhanced heat transfer. Chip morphology observations confirmed that both assisted environments improved chip formation compared with dry machining. The overall ranking identified vortex tube cooling at Vc = 30 m/min and f = 0.08 mm/rev as the best overall condition, while NMQL was more favorable for force reduction and surface finish improvement. The findings of this study provide practical guidance for the selection of sustainable and effective cutting strategies in the precision machining of biomedical titanium alloys. Full article

The rate of pulping of spruce wood depends on the pretreatment of wood chips. Current pretreatment methods that are being investigated and applied appear to be time-consuming and energy intensive. These drawbacks can be minimized by pretreating the chips through compression, perpendicular to the fibre direction. In the maceration process, it is currently very difficult to measure pulp characteristics in real time; therefore, different treatment times were selected for uncompressed and compressed chips. Maceration was carried out by boiling the chips in a solution of acetic acid and hydrogen peroxide mixed in a 1:1 ratio. Subsequently, the colour and lignin content of the maceration product were measured to demonstrate the accelerated maceration of compressed chips compared with uncompressed ones. The colour of the product obtained from compressed chips after 25 min of pulping was similar to that of holocellulose, while the lignin content was at the detection limit. Given the same pulping time, the product obtained from uncompressed chips was darker, more saturated, and contained a significantly higher amount of lignin. The compression of wood chips proved to be a promising pretreatment method for accelerating the maceration of spruce wood. Full article

Modern scientific and technological developments are driving major advances in drug research and development. This narrative review, based on a structured search of PubMed, Scopus, and Web of Science (2018–2026), examines how artificial intelligence (AI) and machine learning (ML) are accelerating a historically prolonged and expensive process, alongside pharmacogenomics, organ-on-a-chip systems, three-dimensional (3D) bioprinting, and nanotechnology. In benchmark studies, deep learning techniques have achieved an area under the receiver operating characteristic curve (AUROC) of over 0.85 for a subset of absorption, distribution, metabolism, excretion, and toxicity (ADMET) endpoints. AI-powered models show promising, albeit platform-dependent, accuracy in predicting candidate drug properties. Pharmacogenomics enables personalized medicine by tailoring therapies according to patients’ genetic profiles, whereas organ-on-a-chip systems and 3D bioprinting provide physiologically relevant human tissue models for preclinical evaluation. In a blinded benchmark study, the Emulate Liver-Chip showed 87% sensitivity and 100% specificity for drug-induced liver injury, outperforming animal models in that specific comparison. Nanotechnology is advancing drug delivery through the use of nanoparticle systems, such as Doxil^® and Onpattro^®. Obstacles remain, including regulatory constraints, ethical considerations, data quality limitations, and the need for stronger validation, although ongoing funding, interdisciplinary collaboration, and evolving regulatory frameworks may support further development. Overall, these technologies show meaningful potential to shorten development time and improve treatment safety, although further prospective validation is required before realizing this potential at scale. Full article