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81
Novel Genomic Regions and Gene Models Controlling Copper and Cadmium Stress Tolerance in Wheat Seedlings
Published 2024-12-01Get full text
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82
DRBD-YOLOv8: A Lightweight and Efficient Anti-UAV Detection Model
Published 2024-11-01“…Achieving real-time detection with high accuracy, while accommodating the limited resources of edge-computing devices poses a significant challenge for anti-UAV detection. …”
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83
SOURCES OF FINANCING INDUSTRIAL COMPLEX ENTERPRISES
Published 2016-08-01“…Subject article is relevant because It is devoted to description of sources of financing of defense enterprises and peculiarities of selection of sources of financing enterprises of the military-industrial complex. …”
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84
Vehicle detection method based on multi-layer selective feature for UAV aerial images
Published 2025-07-01“…The approach also surpasses mainstream models such as YOLO11s with significantly fewer parameters, confirming its effectiveness and practical value in resource-constrained low-altitude UAV-based detection tasks.…”
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85
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86
Cookware as source of toxic metals: An overview
Published 2024-10-01“… Cookware assumes a pivotal function in cooking, however, there are concerns about potential health hazards associated with the release of toxic metals into food. …”
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87
Cookware as source of toxic metals: An overview
Published 2024-10-01“… Cookware assumes a pivotal function in cooking, however, there are concerns about potential health hazards associated with the release of toxic metals into food. …”
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88
Segmentation-Based Detection for Luffa Seedling Grading Using the Seg-FL Model
Published 2024-10-01Get full text
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89
Analysis of Facial Cues for Cognitive Decline Detection Using In-the-Wild Data
Published 2025-06-01“…Video-based analysis offers a promising, low-cost alternative to resource-intensive clinical assessments. This paper investigates visual features (eye blink rate (EBR), head turn rate (HTR), and head movement statistical features (HMSFs)) for distinguishing between neurodegenerative disorders (NDs), mild cognitive impairment (MCI), functional memory disorders (FMDs), and healthy controls (HCs). …”
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90
Metal surface defect detection using SLF-YOLO enhanced YOLOv8 model
Published 2025-04-01“…Abstract This paper addresses the industrial demand for precision and efficiency in metal surface defect detection by proposing SLF-YOLO, a lightweight object detection model designed for resource-constrained environments. …”
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91
Rationale for obtaining protein concentrate of industrial hemp seeds of Cannabis sativa L. of modern selection based on mathematical modeling and its application in food production
Published 2024-01-01“…In general, the studies have shown the feasibility of using protein concentrates from industrial hemp seeds of Cannabis Sativa L of modern selection in food products as a functional and technological ingredient.…”
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92
Seasonal Characteristics of Long-Range Transport and Potential Associated Sources of Particulate Matter (Pm<sub>10</sub>) Pollution at the Station Elk, Poland, on 2021-2022 Data
Published 2023-10-01“…In this study, the NOAA HYSPLIT_4 trajectory model, potential source contribution function (PSCF), and concentration-weight trajectory (CWT) were employed to investigate the origin of the measured PM10 mass at a receptor site. …”
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93
Sources of Life Strengths Appraisal Scale: A Multidimensional Approach to Assessing Older Adults’ Perceived Sources of Life Strengths
Published 2014-01-01“…A 24-month followup of a randomly selected sample confirmed that the nine-scale appraisal measure (SLSAS) is a promising instrument for appraising older adults’ sources of life strengths in dealing with stresses of daily life’s functioning and also a robust measure for predicting outcomes of resilience, autonomy, and well-being for this age group. …”
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95
Analysis of the Relationship Between Assimilate Production and Allocation and the Formation of Rice Quality
Published 2025-05-01“…Correlation analysis indicated that dry matter mass and net photosynthetic rate were significantly positively correlated with yield, but not with taste quality, highlighting the complexity of taste quality formation. Using a membership function comprehensive evaluation method (combines the outputs of multiple membership functions into a single composite value using specific rules (e.g., weighted average, extremum, logical operations) to produce a new membership degree.), a rice variety selection system balancing yield and quality was constructed, and three varieties (Zhongzheyou 8, Huazheyou 261, and Quanyousimiao) were identified as having both high yield and excellent quality. …”
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96
An Optimized FPGA-Based FDIR System for Sensor Fault Detection in Satellite Attitude Estimation
Published 2025-01-01“…To solve this problem, a Fault Detection, Isolation, and Recovery (FDIR) was proposed, which integrates an adaptive unscented Kalman filter (AUKF), a radial basis function (RBF) neural network for fault detection, and a QUEST-based estimator. …”
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KronNet a lightweight Kronecker enhanced feed forward neural network for efficient IoT intrusion detection
Published 2025-07-01“…Abstract The rapid expansion of Internet of Things (IoT) networks necessitates efficient intrusion detection systems (IDS) capable of operating within the stringent resource constraints of IoT devices. …”
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99
Nanotechnologies associated to floral resources in agri-food sector
Published 2018-01-01Get full text
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100
YOLOv11-GSF: an optimized deep learning model for strawberry ripeness detection in agriculture
Published 2025-08-01“…To overcome these limitations, this paper introduces YOLOv11-GSF, a real-time strawberry ripeness detection algorithm based on YOLOv11, which incorporates several innovative features: a Ghost Convolution (GhostConv) convolution method for generating rich feature maps through lightweight linear transformations, thereby reducing computational overhead and enhancing resource utilization; a C3K2-SG module that combines self-moving point convolution (SMPConv) and convolutional gated linear units (CGLU) to better capture the local features of strawberry ripeness; and a F-PIoUv2 loss function inspired by Focaler IoU and PIoUv2, utilizing adaptive penalty factors and interval mapping to expedite model convergence and optimize ripeness classification. …”
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