Molecular detection of clarithromycin-resistant Helicobacter pylori in stool samples using real-time PCR by Menna allah Mohamed, Rania Abdel Halim, Névine Kassem, Eman kamel, sally saber, Engy Elsayed, samar rashad

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PRRSV RNA Detection and Predictive Values Between Different Sow and Neonatal Litter Sample Types by Peng Li, Isadora Machado, Thomas Petznick, Emily Pratt, Jinnan Xiao, Chris Sievers, Paul Yeske, Swami Jayaraman, Daniel C. A. Moraes, Guilherme Cezar, Mafalda Mil-Homens, Hao Tong, Kelly Will, Darwin Reicks, Jason Kelly, Onyekachukwu H. Osemeke, Gustavo S. Silva, Daniel C. L. Linhares

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Association of Molecular Detections of Microsporidia in Stool Samples with Clinical and Immunological Parameters in Ghanaian HIV Patients by Hagen Frickmann, Fred Stephen Sarfo, Betty Roberta Norman, Albert Dompreh, Shadrack Osei Asibey, Richard Boateng, Edmund Osei Kuffour, Konstantin Tanida, Veronica Di Cristanziano, Torsten Feldt, Kirsten Alexandra Eberhardt

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In-House Immunoglobulin Y-Based Immunoassay for Detecting Benzo[a]pyrene in Grilled Pork Samples by Peerapong Jeeno, Sumed Yadoung, Marninphan Thongkham, Pichamon Yana, Udomsap Jaitham, Sakaewan Ounjaijean, Zhen-Lin Xu, Korawan Sringarm, Surat Hongsibsong

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Impact and compensation of sample clock offset in I-CFDMA uplink by Dan DING, Nai-ping CHENG, Yu-rong LIAO

“…To achieve the sample clock synchronization in the interleaved code and frequency division multiple access(I-CFDMA)uplink,the I-CFDMA uplink model was established,and the disturbance of the sample clock offset(SCO)on the system model was discussed,in addition,the signal time shift,phase rotation,multi-user interference(MUI)and inter-carrier interference(ICI)caused by SCO were analyzed quantitatively.On this basis,a compensation method of multi-user SCO was proposed.For one thing,the relevant metric function was modified considering the SCO of each user; for another thing,a multi-user detection(MUD)algorithm based on harmony search was proposed.This algorithm has a higher efficiency than the commonly-used genetic algorithm(GA),as well as a performance approximate to that of optimal detection without SCO but with <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML"> <mfrac> <mn>1</mn> <mrow> <mn>64</mn></mrow> </mfrac> </math></inline-formula> computational burden.The computer simulation results validate the conclusions obtained.…”
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Detection of cutaneous leishmaniasis in three communities of Oti Region, Ghana. by Richard Akuffo, Carmen Sanchez, Carmen Chicharro, Eugenia Carrillo, Naiki Attram, Mba-Tihssommah Mosore, Clara Yeboah, Nana Konama Kotey, Daniel Boakye, Jose-Antonio Ruiz-Postigo, Javier Moreno, Michael Wilson, Bismark Sarfo, Francis Anto

“…In Ghana, some studies in the Volta region have detected Leishmania parasites among persons with skin ulcers.…”
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SmartAnchor3DLane: Towards monocular 3D lane detection with anchor proposal by Jianhao Zhang, Tingting Ru, Chenxiao Cai

“…Anchor3DLane improves the performance of lane detection by directly sampling the front-view feature map. …”
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Triplet Spatial Reconstruction Attention-Based Lightweight Ship Component Detection for Intelligent Manufacturing by Bocheng Feng, Zhenqiu Yao, Chuanpu Feng

“…Experimental validation on a small-scale actual ship component dataset demonstrates that the improved network achieves 88.7% mean Average Precision (mAP), 84.2% precision, and 87.1% recall, representing improvements of 3.5%, 2.2%, and 3.8%, respectively, compared to the original YOLOv8n algorithm, requiring only 2.6 M parameters and 7.5 Giga Floating-point Operations per Second (GFLOPs) computational cost, achieving a good balance between detection accuracy and lightweight model design. …”
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A Method for Auto Generating a Remote Sensing Building Detection Sample Dataset Based on OpenStreetMap and Bing Maps by Jiawei Gu, Chen Ji, Houlin Chen, Xiangtian Zheng, Liangbao Jiao, Liang Cheng

“…To evaluate its effectiveness, we selected three publicly available datasets—WHU, INRIA, and DZU—and conducted three types of experiments using the following four representative object detection models: SSD, Faster R-CNN, DETR, and YOLOv11s. …”
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YOLO-LPSS: A Lightweight and Precise Detection Model for Small Sea Ships by Liran Shen, Tianchun Gao, Qingbo Yin

“…We propose YOLO-LPSS, a novel model designed to significantly improve small ship detection accuracy with low computation cost. The characteristics of YOLO-LPSS are as follows: (1) Strengthening the backbone’s ability to extract and emphasize features relevant to small ship objects, particularly in semantic-rich layers. (2) A sophisticated, learnable method for up-sampling processes is employed, taking into account both deep image information and semantic information. (3) Introducing a post-processing mechanism in the final output of the resampling process to restore the missing local region features in the high-resolution feature map and capture the global-dependence features. …”
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DETECTION OF LUMPY SKIN DISEASE VIRUS GENOME IN FIELD SAMPLES COLLECTED FROM CATTLE IN THE RUSSIAN FEDERATION by A. V. Kononov, A. V. Sprygin, S. V.  Kononova, A. A.  Nesterov, P. V.  Prutnikov, Ye. Ye. Artyukhova, Ye. S.  Kostrova, I. N. Shumilova

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A comparative study evaluating three line immunoassays available for serodiagnosis of equine Lyme borreliosis: Detection of Borrelia burgdorferi sensu lato-specific antibodies in serum samples of vaccinated and non-vaccinated horses by Cornelia V. Broeckl, Stephanie Hiereth, Reinhard K. Straubinger

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A comparative study evaluating three line immunoassays available for serodiagnosis of equine Lyme borreliosis: Detection of Borrelia burgdorferi sensu lato-specific antibodies in serum samples of vaccinated and non-vaccinated horses. by Cornelia V Broeckl, Stephanie Hiereth, Reinhard K Straubinger

“…In this study, three LIAs available for detection of antibodies in equine serum samples were evaluated and compared. …”
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Quantifying thermal‐imager effectiveness for detecting bird nests on farms by Matthew D. Stephenson, Lisa A. Schulte, Robert W. Klaver

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Adversarial detection based on feature invariant in license plate recognition systems by ZHU Xiaoyu, TANG Peng, ZHANG Haochen, QIU Weidong, HUANG Zheng

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Fast Analysis of Water Samples for Trace Amount of Crystal Violet Dye Based on Solid Phase Extraction Using Nanoporous SBA-3 prior to Determination by Fiber Optic-Linear Array Detection Spectrophotometry by Azam Azarkohan, Farzaneh Shemirani, Mahrouz Alvand

“…A solid phase preconcentration procedure using SBA-3 nanosorbent for the fast separation and preconcentration of crystal violet (CV) in water samples by fiber optic-linear array detection spectrophotometry (FO-LADS) is presented. …”
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Diagnostic utility of auramine O smear microscopy for the detection of non-tuberculous mycobacteria vs Mycobacterium tuberculosis complex in adult clinical samples: a 3-year retrospective cohort study (2019-2021) by Dr Leong Tung Ong, Dr Azwani Abdullah, Dr Thian Chee Loh, Dr Chandramathi Samudi Raju, Ms Jennifer Chong, Dr Nadia Atiya

“…The sensitivity, specificity, PPV and NPV of auramine O smear microscopy for detecting NTM vs MTBC were 3.8% (95% CI 2.7-5.3) vs 52.2% (95% CI 48.6-55.8), 92.2% (95% CI 91.5-92.9) vs 99% (95% CI 98.7-99.2), 7.2% (95% CI 5.1-10) vs 87.7% (95% CI 84.3-90.5) and 85.7% (95% CI 84.8-86.6) vs 93.7% (95% CI 93.1-94.4) Discussion: Auramine O smear microscopy demonstrated low sensitivity and a low PPV (<90%) but high specificity (≥90%) for the detection of NTM and MTBC in clinical samples. …”
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Points2Model: a neural-guided 3D building wireframe reconstruction from airborne LiDAR point clouds by Perpetual Hope Akwensi, Akshay Bharadwaj, Ruisheng Wang

Subjects: “…3D reconstruction…”
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Enhancing fraud detection in imbalanced motor insurance datasets using CP-SMOTE and Random Under-Sampling by Pornpawee Komsrimorakot, Thitirat Siriborvornratanakul

“…Abstract Detecting fraudulent claims in motor insurance remains a critical challenge due to the severe class imbalance between fraudulent and legitimate cases. …”
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Determination of Polycyclic Aromatic Hydrocarbons in Tea Infusions Samples by High Performance Liquid Chromatography with Fluorimetric Detection by Anna Maria Girelli, Azzurra Apriceno, Anna maria Tarola, Francesca Tortora

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