Search Results (3,498)

Background/Objectives: Multidrug-resistant (MDR) bacterial colonization poses a significant risk for subsequent infections, especially within hospital environments. Healthcare workers can inadvertently transmit these MDR bacteria to vulnerable patients, exacerbating the problem. This study aimed to determine the colonization rates of MDR bacteria among patients and healthcare workers in a rural Ethiopian hospital with limited resources. Methods: Between 26 May and 6 June 2024, nasal, rectal, vagino-rectal exudate, and stool samples were collected from patients (n = 78) and healthcare workers (n = 11) at Gambo General Hospital (Oromia Region, Ethiopia). Samples were cultured on chromogenic media selective for methicillin-resistant Staphylococcus aureus (MRSA), vancomycin-resistant Enterococcus spp. (VRE), and carbapenemase-producing Enterobacteriaceae (CPE). Bacterial identification was performed using MALDI-TOF mass spectrometry (Bruker), antimicrobial susceptibility testing using the MicroScan WalkAway system (Beckman Coulter), and genotypic characterization with the MDR Direct Flow Chip kit (Vitro). Results: MRSA nasal colonization was detected in 43.3% of patients (13/30; 95% CI: 27.4–60.8%) and 27.3% of healthcare workers (3/11; 95% CI: 6.0–61.0%) (p = 0.73). Rectal (or stool) colonization by MDR bacteria was significantly higher in pediatric patients (85.0%, 17/20; 95% CI: 62.1–96.8%) than in adults (14.3%, 4/28; 95% CI: 5.7–31.5%) (p < 0.001). Notably, a high proportion of pediatric patients harbored Escherichia coli strains co-producing NDM carbapenemase and CTX-M ESBL, and VRE strains were also predominantly isolated in this group. Conclusions: This study reveals a concerningly high prevalence of MRSA and MDR Enterobacteriaceae, especially among children at Gambo Hospital. The VRE prevalence was also substantially elevated compared to other studies. These findings underscore the urgent need for strengthened infection control measures and antimicrobial stewardship programs within the hospital setting. Full article

This study develops a high-accuracy indoor positioning system using ultra-wideband (UWB) technology and the time-of-arrival (TOA) method. The system is built using Arduino Nano microcontrollers and DW1000 UWB chips to measure distances between anchor nodes and a mobile tag. Three positioning algorithms are tested: the triangle centroid algorithm (TCA), inner triangle centroid algorithm (ITCA), and the proposed intersection midpoint algorithm (IMA). Experiments conducted in a 732 × 488 × 220 cm indoor environment show that TCA performs well near the center but suffers from reduced accuracy at the edges. In contrast, IMA maintains stable and accurate positioning across all test points, achieving an average error of 12.87 cm. The system offers low power consumption, fast computation, and high positioning accuracy, making it suitable for real-time indoor applications such as hospital patient tracking and shopping malls where GPS is unavailable or unreliable. Full article

Introduction: Scattering of kernels due to angular dehiscence is a key bottleneck in mechanized harvesting of oilseed rape. Materials and Methods: In this study, a dual-track “genotype–phenotype” screening strategy was established by innovatively integrating high-throughput KASP molecular marker technology and a standardized random collision phenotyping system for the complex quantitative trait of angular resistance. Results: Through the systematic evaluation of 634 oilseed rape hybrid progenies, it was found that the KASP marker S12.68, targeting the cleavage resistance locus (BnSHP1) on chromosome C9, achieved a 73.34% introgression rate (465/634), which was significantly higher than the traditional breeding efficiency (<40%). Phenotypic characterization screened seven excellent resources with cracking resistance index (SRI) > 0.6, of which four reached the high resistance standard (SRI > 0.8), including the core materials NR21/KL01 (SRI = 1.0) and YuYou342/KL01 (SRI = 0.97). Six breeding intermediate materials (44.7–48.7% oil content, mycosphaerella resistance MR grade or above) were created, combining high resistance to chipping and excellent agronomic traits. For the first time, it was found that local germplasm YuYou342 (non-KL01-derived line) was purely susceptible at the S12.68 locus (SRI = 0.86), but its angiosperm vascular bundles density was significantly increased by 37% compared with that of the susceptible material 0911 (p < 0.01); and the material 187308 (SRI = 0.78), although purely susceptible at S12.68, had a 2.8-fold downregulation in expression of the angiosperm-related gene, BnIND1, and a 2.8-fold downregulation of expression of the angiosperm-related gene, BnIND1. expression was significantly downregulated 2.8-fold (q < 0.05), indicating the existence of a novel resistance mechanism independent of the primary effector locus. Conclusions: The results of this research provide an efficient technical platform and breakthrough germplasm resources for oilseed rape crack angle resistance breeding, which is of great practical significance for promoting the whole mechanized production. Full article

In Network-on-Chip (NoC) research, the task mapping problem has attracted considerable attention as a core issue influencing system performance. As an NP-hard problem, it remains challenging, and existing algorithms exhibit limitations in both mapping quality and computational efficiency. To address this, a method named ET (Enhanced Coati Optimization Algorithm) is proposed, which leverages the nature-inspired Coati Optimization Algorithm (COA) for task mapping. An incremental hill-climbing strategy is integrated to improve local search capabilities, and a dynamic mechanism for adjusting the exploration–exploitation ratio is designed to better balance global and local searches. Additionally, an initial mapping strategy based on spectral clustering is introduced, which utilizes inter-task communication strength to cluster tasks, thereby improving the quality of the initial population. To evaluate the effectiveness of the proposed algorithm, the performance of the ET algorithm is compared and analyzed against various existing algorithms in terms of communication cost, energy consumption, and latency, using both real benchmark task maps and randomly generated task maps. Experimental results demonstrate that the ET algorithm consistently outperforms the compared algorithms across all performance metrics, thereby confirming its superiority in addressing the NoC task mapping problem. Full article

In recent years, the traditional orchard sprayer has had problems, such as waste of liquid agrochemicals, low target coverage, high manual dependence, and environmental pollution. In this study, an automatic swing-arm sprayer for orchards was developed based on the standardized pear orchard in Pinggu, Beijing. Firstly, the structural principles of a crawler-type traveling system and swing-arm sprayer were simulated using finite element software design. The combination of a diffuse reflection photoelectric sensor and Arduino single-chip microcomputer was used to realize real-time detection and dynamic spray control in the pear canopy, and the sensor delay compensation algorithm was used to optimize target recognition accuracy and improve the utilization rate of liquid agrochemicals. Through the integration of innovative structural design and intelligent control technology, a vertical droplet distribution test was carried out, and the optimal working distance of the spray was determined to be 1 m; the nozzle angle for the upper layer was 45°, that for the lower layer was 15°, and the optimal speed of the swing-arm motor was 75 r/min. Finally, a particle size test and field test of the orchard sprayer were completed, and it was concluded that the swing-arm mode increased the pear tree canopy droplet coverage by 74%, the overall droplet density by 21.4%, and the deposition amount by 23% compared with the non-swing-arm mode, which verified the practicability and reliability of the swing-arm spray and achieved the goal of on-demand pesticide application in pear orchards. Full article

A novel nanomaterial photoelectrochemical aptamer sensor based on CdS@NiMoS heterojunction nanocomposites was constructed for highly sensitive detection of chloramphenicol (CAP) in antibiotic residues. Through optimization of the material synthesis process, the optimal doping ratio of MoS₂ to Ni³⁺ (70% MoS₂ and 10% Ni³⁺) was identified, which significantly enhanced the photogenerated carrier separation efficiency. In thin-film preparation, comparative analysis of four film-forming methods led to the determination of an optimal process with stability. To achieve highly specific CAP detection, the nanocomposite chip was integrated with nucleic acid aptamer biorecognition elements within a standard three-electrode detection system. Experimental results demonstrated a linear response (R² = 0.998) in the 0.1–2 μM concentration range, with a detection limit of 3.69 nM (3σ/S). Full article

Lung cancer remains one of the main causes of cancer-related death globally and a significant global health concern. There is an urgent need for safer and more effective therapeutic alternatives despite notable progress in therapy; issues such as drug resistance, side effects, metastasis, and recurrence still affect patient outcome and quality of life. The aim of this review is to examine recent developments in the application of herbal-drug-loaded nanoparticles as a new strategy for treating lung cancer. A thorough examination of different drug delivery systems based on nanoparticles is provided, highlighting their function in improving the solubility, bioavailability, and targeted delivery of herbal compounds. In addition, the review evaluates the biomarkers used for targeted therapy and examines how new personalised treatment approaches like wearable electronic patches, robotics-assisted interventions, smartphone-enabled therapies, AI-driven diagnostics, and lung-on-a-chip technologies can be integrated to improve the accuracy and effectiveness of lung cancer treatment. In conclusion, the combination of personalised medicine and nanotechnology may lead to revolutionary changes in lung cancer treatment in the future. Full article

We propose a hybrid-integrated III–V-silicon optical-phased-array (OPA) based on passive alignment flip–chip bonding technology and provide new solutions for LiDAR. To achieve a large range of vertical beam steering in a hybrid-integrated OPA, a multi-lines OPA in a single chip is introduced. The system allows parallel hybrid integration of multiple dies onto a single wafer, achieving a multi-fold improvement in tuning efficiency. In order to increase the range of horizontal beam steering, we propose a half-wavelength pitch waveguide emitter with non-uniform width to reduce the crosstalk, which can remove the higher-order grating lobes in free space. In this work, we simulate OPA individually for four-lines and eight-lines. As a result, we simultaneously achieved a beam steering with nearly ±90° (horizontal) × 17.2° (vertical, when four-line OPA) or 39.6° (vertical, when eight-line OPA) field of view (FOV) and a high tuning efficiency with 1.13°/nm (when eight-line OPA). Full article

The research on ultra-thin inorganic chips is an important field in the development of inorganic flexible electronics. By thinning the inorganic (mainly silicon-based) chip to less than 50 μm, it will gain a certain degree of flexibility. After the ultra-thin chip is integrated into the flexible substrate, it is bent repeatedly during the operation of the system. When the bending angle is excessively large, the chip and substrate will debond, or the chip will break. In this process, whether the chip can be stably adhered to the substrate depends on many factors, and debonding can only be reduced by continuously adjusting the process parameters. From an energy method perspective, this study divides the bending process of flexible silicon-based chips and flexible films into two states: debonding and non-debonding. A debonding mechanical model of flexible chips is established, and the regulatory relationship between the adhesion coefficient between the chip and film, chip geometric size, and material parameters was established. Experiments were also conducted to verify the relevant theoretical results. The theoretical results show that the risk of chip debonding decreases with a reduction in chip thickness, an increase in interface adhesion, and an increase in bending radius. Improving the interface adhesion during the bending process can effectively stabilize the adhesion of flexible chips. This paper provides a theoretical basis for the integration and bending of ultra-thin flexible chips and flexible substrates, promoting the practical assembly and application of ultra-thin chips. Full article

Background/Objectives: Circulating tumor cells (CTCs) are important biomarkers for predicting prognosis and evaluating treatment efficacy in cancer. We developed the “CTC-Chip” system based on microfluidics, enabling highly sensitive CTC detection and prognostic assessment in lung cancer and malignant pleural mesothelioma. However, the final identification and enumeration of CTCs require manual intervention, which is time-consuming, prone to human error, and necessitates the involvement of experienced medical professionals. Medical image recognition using machine learning can reduce workload and improve automation. However, CTCs are rare in clinical samples, limiting the training data available to construct a robust CTC image recognition system. In this study, we established a highly accurate artificial intelligence-based CTC recognition system by pre-training convolutional neural networks using images from lung cancer cell lines. Methods: We performed transfer learning of convolutional neural networks. Initially, the models were pre-trained using images obtained from lung cancer cell lines. The model’s accuracy was improved by training with a limited number of clinical CTC images. Results: Transfer learning significantly improved the CTC classification accuracy to an average of 99.51%, compared to 96.96% for a model trained solely on pre-trained cell lines (p < 0.05). This approach showed notable efficacy when clinical training images were limited, achieving statistically significant accuracy improvements with as few as 17 clinical CTC images (p < 0.05). Conclusions: Overall, our findings demonstrate that pre-training with cancer cell lines enables rapid and highly accurate automated CTC recognition even with limited clinical data, significantly enhancing clinical applicability and potential utility across diverse cancer diagnostic workflows. Full article

Bacterial blight (BB) caused by Xanthomonas oryzae pv. oryzae (Xoo) is a major threat to global rice productivity. Although hybrid rice breeding has significantly enhanced yields, persistent genetic vulnerabilities within restorer lines continue to compromise BB resistance. This study addresses this challenge by implementing functional marker-assisted selection (FMAS) to pyramid two broad-spectrum resistance (R) genes, Xa21 and Xa23, into the elite, yet BB-susceptible, restorer line K608R. To enable precise Xa23 genotyping, we developed a novel three-primer functional marker (FM) system (IB23/CB23/IR23). This system complements the established U1/I2 markers used for Xa21. This recombination-independent FMAS platform facilitates simultaneous, high-precision tracking of both homozygous and heterozygous alleles, thereby effectively circumventing the linkage drag limitations typical of conventional markers. Through six generations of marker-assisted backcrossing followed by intercrossing, we generated K608R2123 pyramided lines harboring both R genes in homozygous states, achieving a recurrent parent genome recovery rate of 96.93%, as determined by single nucleotide polymorphism (SNP) chip analysis. The pyramided lines exhibited enhanced resistance against six virulent Xoo pathogenic races while retaining parental yield performance across key agronomic traits. Our FMAS strategy overcomes the historical trade-off between broad-spectrum resistance and the preservation of elite phenotypes, with the developed lines exhibiting resistance coverage complementary to that of both introgressed R genes. This integrated approach provides breeders with a reliable molecular tool to accelerate the development of high-yielding, disease-resistant varieties, demonstrating significant potential for practical deployment in rice improvement programs. The K608R2123 germplasm represents a dual-purpose resource suitable for both commercial hybrid seed production and marker-assisted breeding programs, and it confers synergistic resistance against diverse Xoo races, thereby providing a pivotal breeding resource for sustainable BB control in epidemic regions. Full article

This review explores optical technologies for non-invasive glucose monitoring (NIGM) using aqueous humor (AH) as media, addressing the limitations of traditional invasive methods in diabetes management. It analyzes key techniques such as Raman spectroscopy, polarimetry, and mid- and near-infrared spectral methods, highlighting their respective challenges, alongside emerging hybrid approaches like photoacoustic spectroscopy and optical coherence tomography. Crucially, the practical realization of these optical methods for portable NIGM hinges on advanced instrumentation. Therefore, this review also details progress in compact NIR spectrometers. While conventional systems often lack suitability, significant advancements in on-chip technologies—including miniaturized dispersive spectrometers and various on-chip Fourier transform systems (e.g., spatial heterodyne, stationary wave integral, and temporally modulated FT systems)—utilizing integration platforms like SOI and SiN are promising. Such innovations offer the potential for high spectral resolution, large bandwidth, and miniaturization, which are essential for developing practical AH-based NIGM systems to improve diabetes care. Full article

The success of checkpoint inhibitors in improving cancer patient survival has demonstrated the therapeutic potential of immunotherapies. This advancement has reshaped oncology treatment and driven interest in harnessing immune modulation for a wider range of diseases. However, developing drugs that modulate immune activity presents unique challenges. A major limitation in preclinical research is the inefficiency of testing human-specific immune targets in animal models, which often fail to translate to clinical outcomes. Additionally, conventional in vitro systems lack immune reactivity due to their static and monocellular nature, limiting their predictive value. Advanced in vitro models can bridge this gap by offering increasingly relevant human physiology for testing drug efficacy and safety, along with absorption, distribution, metabolism, and excretion (ADME). In particular, immune-competent spheroids, organoids, and organs-on-a-chip (OoC) have emerged as promising tools. Although still in their infancy, these microphysiological systems (MPSs) have demonstrated the feasibility of replicating immune responses ex vivo, providing a new avenue for studying immune-targeting drugs with higher translational potential. In this review, we explore recent advances in immune-competent organoid and OoC models, highlighting their capabilities and limitations. We provide a perspective on their applications for cancer drug testing, discussing how these systems could refine preclinical immuno-oncology research and accelerate the development of next-generation immunotherapies. Full article

Stealthy chip-level tamper attacks, such as hardware Trojan insertions or security-critical circuit modifications, can threaten modern microelectronic systems’ security. While traditional inspection and side-channel methods offer potential for tamper detection, they may not reliably detect all forms of attacks and often face practical limitations in terms of scalability, accuracy, or applicability. This work introduces a non-invasive, contactless tamper detection method employing a complementary split-ring resonator (CSRR). CSRRs, which are typically deployed for non-destructive material characterization, can be placed on the surface of the chip’s package to detect subtle variations in the impedance of the chip’s power delivery network (PDN) caused by tampering. The changes in the PDN’s impedance profile perturb the local electric near field and consequently affect the sensor’s impedance. These changes manifest as measurable variations in the sensor’s scattering parameters. By monitoring these variations, our approach enables robust and cost-effective physical integrity verification requiring neither physical contact with the chips or printed circuit board (PCB) nor activation of the underlying malicious circuits. To validate our claims, we demonstrate the detection of various chip-level tamper events on an FPGA manufactured with 28 nm technology. Full article

For data-intensive applications like edge AI and image processing, we present a new reconfigurable 8T SRAM-based in-memory computing (IMC) macro designed for high-performance and energy-efficient operation. This architecture mitigates von Neumann limitations through numerous major breakthroughs. We built a new architecture with an adjustable capacitance array to substantially increase the multiply-and-accumulate (MAC) engine’s accuracy. It achieves 10–20 TOPS/W and >95% accuracy for 4–10-bit operations and is robust across PVT changes. By supporting binary and ternary neural networks (BNN/TNN) with XNOR-and-accumulate logic, a dual-mode inference engine further expands capabilities. With sub-5 ns mode switching, it can achieve up to 30 TOPS/W efficiency and >97% accuracy. In-memory Hamming error correction is implemented directly using integrated XOR circuitry. This technique eliminates off-chip ECC with >99% error correction and >98% MAC accuracy. Machine learning-aided co-optimization ensures sense amplifier dependability. To ensure CMOS compatibility, the macro may perform Boolean logic operations using normal 8T SRAM cells. Comparative circuit-level simulations show a 31.54% energy efficiency boost and a 74.81% delay reduction over other SRAM-based IMC solutions. These improvements make our macro ideal for real-time AI acceleration, cryptography, and next-generation edge computing, enabling advanced compute-in-memory systems. Full article