City of Muskogee Animal Control Supervisor Phil Blair is known for his devotion to animals,but his quick thinking this week took that commitment to a whole new level-saving the life of an unborn baby deer after a trag...City of Muskogee Animal Control Supervisor Phil Blair is known for his devotion to animals,but his quick thinking this week took that commitment to a whole new level-saving the life of an unborn baby deer after a tragic accident.Blair was called to the scene of a deer struck by a car.Upon arrival,he found the mother deer had suffered four broken legs and sadly had to be put down to prevent further suffering.展开更多
This study introduces a lightweight deep learning model and a novel synthetic dataset designed to restore damaged one-dimensional(1D)barcodes and Quick Response(QR)codes,addressing critical challenges in logistics ope...This study introduces a lightweight deep learning model and a novel synthetic dataset designed to restore damaged one-dimensional(1D)barcodes and Quick Response(QR)codes,addressing critical challenges in logistics operations.The proposed solution leverages an efficient Pix2Pix-based framework,a type of conditional Generative Adversarial Network(GAN)optimized for image-to-image translation tasks,enabling the recovery of degraded barcodes and QR codes with minimal computational overhead.A core contribution of this work is the development of a synthetic dataset that simulates realistic damage scenarios frequently encountered in logistics environments,such as low contrast,misalignment,physical wear,and environmental interference.By training on this diverse and realistic dataset,the model demonstrates exceptional performance in restoring readability and decoding accuracy.The lightweight architecture,featuring a U-Net-based encoder-decoder with separable convolutions,ensures computational efficiency,making the approach suitable for real-time deployment on embedded and resource-constrained devices commonly used in logistics systems.Experimental results reveal significant improvements:QR code decoding ratios increased from 14%to 99%on training data and from 15%to 68%on validation data,while 1D barcode decoding ratios improved from 7%to 73%on training data and from 9%to 44%on validation data.By providing a robust,resource-efficient solution for restoring damaged barcodes and QR codes,this study offers practical advancements for enhancing the reliability of automated scanning systems in logistics operations,particularly under challenging conditions.展开更多
In today's fast-paced modern life, whether for fitness training, outdoor adventures, or daily commutes, we all yearn for quick-dry apparel that can rapidly wick away moisture and keep our bodies dry and comfortabl...In today's fast-paced modern life, whether for fitness training, outdoor adventures, or daily commutes, we all yearn for quick-dry apparel that can rapidly wick away moisture and keep our bodies dry and comfortable. As a standout in functional textiles, quick-dry fabrics are becoming the top choice for more and more people, thanks to their exceptional moisture-wicking performance and rapid drying capabilities.展开更多
Ammonia is a key industry raw material for fertilizers and the electro-reduction of N_(2)(NRR)can be served as a promising method.It is urgently needed to discover advanced catalysts while the lack of design principle...Ammonia is a key industry raw material for fertilizers and the electro-reduction of N_(2)(NRR)can be served as a promising method.It is urgently needed to discover advanced catalysts while the lack of design principles still hinders the high-throughput screen of efficient candidates.Herein,we have provided an up-to-date review of NRR catalysts mainly on theoretical works and highlighted the latest achievements on descriptors,which can be served as valid guidance of optimal catalysts.The descriptors are classified with adsorption energy and the corresponding derived ones,which can screen the NRR catalysts from various aspects.Finally,the challenges and opportunities in the descriptor field are presented.展开更多
QR codes are widely used in applications such as information sharing,advertising,and digital payments.However,their growing adoption has made them attractive targets for malicious activities,including malware distribu...QR codes are widely used in applications such as information sharing,advertising,and digital payments.However,their growing adoption has made them attractive targets for malicious activities,including malware distribution and phishing attacks.Traditional detection approaches rely on URL analysis or image-based feature extraction,whichmay introduce significant computational overhead and limit real-time applicability,and their performance often depends on the quality of extracted features.Previous studies in malicious detection do not fully focus on QR code securitywhen combining convolutional neural networks(CNNs)with recurrent neural networks(RNNs).This research proposes a deep learning model that integrates AlexNet for feature extraction,principal component analysis(PCA)for dimensionality reduction,and RNNs to detect malicious activity in QR code images.The proposed model achieves both efficiency and accuracy by transforming image data into a compact one-dimensional sequence.Experimental results,including five-fold cross-validation,demonstrate that the model using gated recurrent units(GRU)achieved an accuracy of 99.81%on the first dataset and 99.59%in the second dataset with a computation time of only 7.433 ms per sample.A real-time prototype was also developed to demonstrate deployment feasibility.These results highlight the potential of the proposed approach for practical,real-time QR code threat detection.展开更多
[ Objective] The aim was to seek a simple and quick method of extracting genomic DNA from wheat leaves. [ Method] Taking tender leaves of wheat as test materials, total DNA of transgenic wheat was extracted by using m...[ Objective] The aim was to seek a simple and quick method of extracting genomic DNA from wheat leaves. [ Method] Taking tender leaves of wheat as test materials, total DNA of transgenic wheat was extracted by using modified CTAB method. The extracted DNA was detected by 0.8% agarose gel electrophoresis. [ Result] DNA purity of extracted genome DNA from wheat was high and no degradation phenomenon using modified CTAB method, and was suitable for carrying out normal PCR amplification. [ Conclusion] This study provides a simple and quick method for extracting DNA from wheat with a spot of material.展开更多
文摘City of Muskogee Animal Control Supervisor Phil Blair is known for his devotion to animals,but his quick thinking this week took that commitment to a whole new level-saving the life of an unborn baby deer after a tragic accident.Blair was called to the scene of a deer struck by a car.Upon arrival,he found the mother deer had suffered four broken legs and sadly had to be put down to prevent further suffering.
基金supported by the Scientific and Technological Research Council of Turkey(TÜB˙ITAK)through the Industrial R&D Projects Grant Program(TEYDEB)under Project No.3211077(grant recipient:Metin Kahraman)。
文摘This study introduces a lightweight deep learning model and a novel synthetic dataset designed to restore damaged one-dimensional(1D)barcodes and Quick Response(QR)codes,addressing critical challenges in logistics operations.The proposed solution leverages an efficient Pix2Pix-based framework,a type of conditional Generative Adversarial Network(GAN)optimized for image-to-image translation tasks,enabling the recovery of degraded barcodes and QR codes with minimal computational overhead.A core contribution of this work is the development of a synthetic dataset that simulates realistic damage scenarios frequently encountered in logistics environments,such as low contrast,misalignment,physical wear,and environmental interference.By training on this diverse and realistic dataset,the model demonstrates exceptional performance in restoring readability and decoding accuracy.The lightweight architecture,featuring a U-Net-based encoder-decoder with separable convolutions,ensures computational efficiency,making the approach suitable for real-time deployment on embedded and resource-constrained devices commonly used in logistics systems.Experimental results reveal significant improvements:QR code decoding ratios increased from 14%to 99%on training data and from 15%to 68%on validation data,while 1D barcode decoding ratios improved from 7%to 73%on training data and from 9%to 44%on validation data.By providing a robust,resource-efficient solution for restoring damaged barcodes and QR codes,this study offers practical advancements for enhancing the reliability of automated scanning systems in logistics operations,particularly under challenging conditions.
文摘In today's fast-paced modern life, whether for fitness training, outdoor adventures, or daily commutes, we all yearn for quick-dry apparel that can rapidly wick away moisture and keep our bodies dry and comfortable. As a standout in functional textiles, quick-dry fabrics are becoming the top choice for more and more people, thanks to their exceptional moisture-wicking performance and rapid drying capabilities.
基金supported by the National Natural Science Foundation of China(No.21603109)the Henan Joint Fund of the National Natural Science Foundation of China(No.U1404216)+2 种基金the Special Fund of Tianshui Normal University,China(No.CXJ2020-08)the Scientific Research Program Funded by Shaanxi Provincial Education Department(No.20JK0676)supported by Natural Science Basic Research Program of Shanxi(Nos.2022JQ-108,2022JQ-096).
文摘Ammonia is a key industry raw material for fertilizers and the electro-reduction of N_(2)(NRR)can be served as a promising method.It is urgently needed to discover advanced catalysts while the lack of design principles still hinders the high-throughput screen of efficient candidates.Herein,we have provided an up-to-date review of NRR catalysts mainly on theoretical works and highlighted the latest achievements on descriptors,which can be served as valid guidance of optimal catalysts.The descriptors are classified with adsorption energy and the corresponding derived ones,which can screen the NRR catalysts from various aspects.Finally,the challenges and opportunities in the descriptor field are presented.
基金funded by the Deanship of Scientific Research(DSR)at King Abdulaziz University Jeddah,under grant no.(GPIP:1168-611-2024)The authors acknowledge the DSR for financial and technical support.
文摘QR codes are widely used in applications such as information sharing,advertising,and digital payments.However,their growing adoption has made them attractive targets for malicious activities,including malware distribution and phishing attacks.Traditional detection approaches rely on URL analysis or image-based feature extraction,whichmay introduce significant computational overhead and limit real-time applicability,and their performance often depends on the quality of extracted features.Previous studies in malicious detection do not fully focus on QR code securitywhen combining convolutional neural networks(CNNs)with recurrent neural networks(RNNs).This research proposes a deep learning model that integrates AlexNet for feature extraction,principal component analysis(PCA)for dimensionality reduction,and RNNs to detect malicious activity in QR code images.The proposed model achieves both efficiency and accuracy by transforming image data into a compact one-dimensional sequence.Experimental results,including five-fold cross-validation,demonstrate that the model using gated recurrent units(GRU)achieved an accuracy of 99.81%on the first dataset and 99.59%in the second dataset with a computation time of only 7.433 ms per sample.A real-time prototype was also developed to demonstrate deployment feasibility.These results highlight the potential of the proposed approach for practical,real-time QR code threat detection.
基金Supported by National GMO Cultivation of New Varieties of Major Projects "Anti-reverse to Cultivate New Varieties of Genetically Modified Wheat," a Major IssueNational Science and Technology Support Program Topics (2006BAD01A02-8)National System of Industrial Science and Technology of Modern Wheat Comprehensive Experimental Station in Shanxi Province and National public Service Sector(Agriculture) Research Project (Shanxi Province)(nycytx-03)~~
文摘[ Objective] The aim was to seek a simple and quick method of extracting genomic DNA from wheat leaves. [ Method] Taking tender leaves of wheat as test materials, total DNA of transgenic wheat was extracted by using modified CTAB method. The extracted DNA was detected by 0.8% agarose gel electrophoresis. [ Result] DNA purity of extracted genome DNA from wheat was high and no degradation phenomenon using modified CTAB method, and was suitable for carrying out normal PCR amplification. [ Conclusion] This study provides a simple and quick method for extracting DNA from wheat with a spot of material.
