bluuebunny/crossref_metadata_2025_split huggingface dataset:
Deep learning of echocardiography distinguishes between presence and absence of late gadolinium enhancement on cardiac magnetic resonance in patients with hypertrophic cardiomyopathy
Authors: Akita Keitaro , Kusunose Kenya , Haga Akihiro , Shimomura Taisei , Kosaka Yoshitaka , Ishiyama Katsunori , Hasegawa Kohei , Fifer Michael A. , Maurer Mathew S. , Shimada Yuichi J. 
Published: October 2024

Abstract
Background
Hypertrophic cardiomyopathy (HCM) can cause myocardial fibrosis, which can be a substrate for fatal ventricular arrhythmias and subsequent sudden cardiac death. Although late gadolinium enhancement (LGE) on cardiac magnetic resonance (CMR) represents myocardial fibrosis and is associated with sudden cardiac death in patients with HCM, CMR is resource-intensive, can carry an economic burden, and is sometimes contraindicated. In this study for patients with HCM, we aimed to distinguish between patients with positive and negative LGE on CMR using deep learning of echocardiographic images.

Methods
In the cross-sectional study of patients with HCM, we enrolled patients who underwent both echocardiography and CMR. The outcome was positive LGE on CMR. Among the 323 samples, we randomly selected 273 samples (training set) and employed deep convolutional neural network (DCNN) of echocardiographic 5-chamber view to discriminate positive LGE on CMR. We also developed a reference model using clinical parameters with significant differences between patients with positive and negative LGE. In the remaining 50 samples (test set), we compared the area under the receiver-operating-characteristic curve (AUC) between a combined model using the reference model plus the DCNN-derived probability and the reference model.

Results
Among the 323 CMR studies, positive LGE was detected in 160 (50%). The reference model was constructed using the following 7 clinical parameters: family history of HCM, maximum left ventricular (LV) wall thickness, LV end-diastolic diameter, LV end-systolic volume, LV ejection fraction < 50%, left atrial diameter, and LV outflow tract pressure gradient at rest. The discriminant model combining the reference model with DCNN-derived probability significantly outperformed the reference model in the test set (AUC 0.86 [95% confidence interval 0.76–0.96] vs. 0.72 [0.57–0.86], P = 0.04). The sensitivity, specificity, positive predictive value, and negative predictive value of the combined model were 0.84, 0.76, 0.78, and 0.83, respectively.

Conclusion
Compared to the reference model solely based on clinical parameters, our new model integrating the reference model and deep learning-based analysis of echocardiographic images demonstrated superiority in distinguishing LGE on CMR in patients with HCM. The novel deep learning-based method can be used as an assistive technology to facilitate the decision-making process of performing CMR with gadolinium enhancement.
Specificity in the commonalities of inhibition control: using meta-analysis and regression analysis to identify the key brain regions in psychiatric disorders
Authors: Wan Li , Pei Pingting , Zhang Qinghui , Gao Wenxiang 
Published: October 2024

Abstract

Background
The differential diagnosis of psychiatric disorders is relatively challenging for several reasons. In this context, we believe that task-based magnetic resonance imaging (MRI) can serve as a tool for differential diagnosis. The aim of this study was to explore the commonalities in brain activities among individuals with psychiatric disorders and to identify the key brain regions that can distinguish between these disorders.

Methods
The PubMed, MEDLINE, EMBASE, Web of Science, Scopus, PsycINFO, and Google Scholar databases were searched for whole-brain functional MRI studies that compared psychiatric patients and normal controls. The psychiatric disorders included schizophrenia (SCZ), bipolar disorder (BD), major depressive disorder (MDD), obsessive–compulsive disorder, attention-deficit/hyperactivity disorder (ADHD), and autism spectrum disorder (ASD). Studies using go–nogo paradigms were selected, we then conducted activation likelihood estimation (ALE) meta-analysis, factor analysis, and regression analysis on these studies subsequently.

Results
A total of 152 studies (108 with patients) were selected and a consistent pattern was found, that is, decreased activities in the same brain regions across six disorders. Factor analysis clustered six disorders into three pairs: SCZ and ASD, MDD and BD, and ADHD and BD. Furthermore, the heterogeneity of SCZ and ASD was located in the left and right thalamus; and the heterogeneity of MDD and BD was located in the thalamus, insula, and superior frontal gyrus.

Conclusion
The results can lead to a new classification method for psychiatric disorders, benefit the differential diagnosis at an early stage, and help to understand the biobasis of psychiatric disorders.
The Efficacy and Safety of Intravenous Tocilizumab to Treat Graves’ Ophthalmopathy: A Systematic Review and Single-arm Meta-analysis
Authors: Sun Aimin , Wang Xing , Qu Jinfeng , Wu Yuan 
Published: October 2024

Abstract

Purpose
This study aims to evaluate the efficacy and safety of intravenous (IV) tocilizumab (TCZ) in the treatment of Graves’ ophthalmopathy (GO).

Methods
A comprehensive search was conducted across the Web of Science, PubMed, Embase, Cochrane Library, World Health Organization International Clinical Trials Registry Platform, and ClinicalTrials.gov databases from inception to April 2024. Randomized controlled trials and cohort studies that used IV TCZ for treating GO were included.

Results
Twelve studies encompassing 219 patients with active, steroid-resistant GO were analyzed. The meta-analysis demonstrated significant improvements in Clinical Activity Score (CAS) response (effect size [ES] = 0.98; 95% confidence interval [CI], 0.93-1.00), proptosis response (ES = 0.50; 95% CI, 0.27-0.73), and diplopia response (ES = 0.48; 95% CI, 0.24-0.74). The ES for adverse events was 0.27 (95% CI, 0.22-0.33), with only 3 severe cases necessitating treatment discontinuation, and a low reactivation rate (ES = 0.01; 95% CI, 0.00-0.04). TCZ treatment led to a mean CAS reduction of 4.60 points (95% CI, 3.88-5.32) across 10 studies, a mean proptosis reduction of 2.04 mm (95% CI, 1.42-2.65) across 7 studies, and a mean decrease in TSH receptor antibodies levels of 10.62 IU (95% CI, 4.67-10.62) across 5 studies.

Conclusion
This meta-analysis provides robust evidence supporting the efficacy and safety of IV TCZ in patients with GO who are resistant to glucocorticoid therapy. The results highlight TCZ's comparable efficacy to glucocorticoids and suggest that TCZ could significantly expand clinical management options for GO. In the future, more high-quality, large-scale randomized controlled trials are still needed to confirm these findings.
Drosophila require both green and UV wavelengths for sun orientation but lack a time-compensated sun compass
Authors: Pae Haneal , Liao Jingzhu , Yuen Nicole , Giraldo Ysabel Milton 
Published: October 2024

ABSTRACT
Celestial orientation and navigation are performed by many organisms in contexts as diverse as migration, nest finding and straight-line orientation. The vinegar fly, Drosophila melanogaster, performs menotaxis in response to celestial cues during tethered flight and can disperse more than 10 km under field conditions. However, we still do not understand how spectral components of celestial cues and pauses in flight impact heading direction in flies. To assess individual heading, we began by testing flies in a rotating tether arena using a single green LED as a stimulus. We found that flies robustly perform menotaxis and fly straight for at least 20 min. Flies maintain their preferred heading directions after experiencing a period of darkness or stopping flight, even up to 2 h, but reset their heading when the LED changes position, suggesting that flies do not treat this stimulus as the sun. Next, we assessed the flies' responses to a UV spot alone or a paired UV–green stimulus – two dots situated 180 deg apart to simulate the solar and antisolar hemispheres. We found that flies respond to UV much as they do to green light; however, when the stimuli are paired, flies adjust for sudden 90 deg movements, performing sun orientation. Lastly, we found no evidence of a time-compensated sun compass when we moved the paired stimuli at 15 deg h−1 for 6 h. This study demonstrates that wavelength influences how flies respond to visual cues during flight, shaping the interpretation of visual information to execute an appropriate behavioral response.
Staged Nipple Delay Procedure Expands Candidacy for Nipple-Sparing Mastectomy
Authors: Wang Xuanji , Jackson Jordan , Weed Christina , Boyle Marissa K. , Amersi Farin F. , Mirocha James , Giuliano Armando E. , Chung Alice P. 
Published: October 2024

Abstract
Background
Nipple delay (ND) is a staged procedure that improves nipple-areolar complex (NAC) viability in nipple-sparing mastectomy (NSM) patients who are high-risk for NAC or skin-flap necrosis. This study compared postoperative outcomes and risk factors between patients treated with ND-NSM and NSM alone.

Methods
Patient demographics, risk factors for NAC or skin-flap necrosis, tumor characteristics, and operative outcomes were compared between ND-NSM and NSM groups from 2009 to 2023. Univariate and multivariate analyses were performed to identify significant variables associated with NAC or skin-flap necrosis.

Results
Overall, 71 ND-NSM patients and 537 NSM patients were compared. ND-NSM patients had larger breasts (p < 0.01), body mass index ≥ 30 (p = 0.01), prior breast/chest wall radiation (XRT) [p < 0.01], prior breast operations (p < 0.01), less axillary surgery (p < 0.01), more autologous tissue reconstruction over implant-based reconstruction compared with NSM patients (p = 0.02), and more prophylaxis (p < 0.01). There were no statistically significant differences between groups in regard to infection, skin-flap necrosis, NAC necrosis, seromas, and hematomas. No patients in the ND-NSM group had NAC necrosis and 1 patient had skin-flap necrosis, compared with 17 and 13 patients in the NSM group, respectively (p = 0.24). On univariate analysis, prior XRT was associated with increased risk for skin-flap necrosis (p = 0.02). Multivariate analysis showed XRT was associated with skin-flap necrosis (p = 0.02) and any necrosis (p = 0.01). Breast size was associated with NAC or skin-flap necrosis (p = 0.04).

Conclusion
Larger breasts and XRT were risk factors for NAC or skin-flap necrosis; however, despite having more risk factors, ND-NSM patients had very low rates of necrosis. Notably, no nipples were lost. A shared decision should be made with patients regarding the risks and benefits of ND-NSM.
APest-YOLO: A Multi-Scale Agricultural Pest Detection Model Based on Deep Learning
Authors: Fang Hao , Shi Binbin , Sun Yongpeng , Xiong Neal , Zhang Lijuan 
Published: October 2024

HighlightsWe propose a APest-YOLO model, an innovative agricultural pest detection model founded on a lightweight approach, thus improving the efficiency of pest detection while also reducing the model’s dimensions.The model incorporates a novel grouping atrous spatial pyramid pooling fast module with four convolution layers to enhance multi-scale pest feature representation, aiming for improved detection accuracy. Additionally, it utilizes a convolutional block attention module to reduce noise and complexity in background images, facilitating the extraction of more refined and smoother pest features for accurate detection.We conducted experiments on agricultural pest detection using a comprehensive multi-pest dataset. The APest-YOLO model surpasses existing detection models in terms of mAP0.5, mAP0.5:0.95.Abstract. Crop pests and diseases pose a significant threat to smart agriculture, making pest detection a critical component in agricultural applications. However, current detection methods often struggle to effectively identify multi-scale pest data. In response, we present a novel agricultural pest detection model (APest-YOLO) based on a lightweight approach. The APest-YOLO model enhances pest detection efficiency while reducing model size, which is different from the baseline models. Our model features an original grouping atrous spatial pyramid pooling fast module, comprising four convolution layers with varying rates to capture multi-scale and multi-level pest characteristics. Additionally, we incorporate a convolutional block attention module to extract smoother features from pest images with noisy and complex backgrounds. We evaluated the APest-YOLO model on a large-scale multi-pest dataset encompassing 37 pest species. Furthermore, the APest-YOLO model achieved 99.3% mAP0.5 and found that it outperforms baseline models, demonstrating effective pest species detection capabilities. Keywords: Attention mechanism, Convolutional neural network, Intelligent agriculture, Pest detection, YOLO.
LFA-YOLO: Detection of Lychee Fruit Anthracnose Based on UAV Images and Deep Learning
Authors: Chen JiaSheng , Liu Mei , Li JingShun , Chen JiaXin 
Published: October 2024

HighlightsMulti-path coordinated attention mechanism incorporating salient information is proposed.LeanNet, a backbone network based on depth-separable convolution, is proposed.Channel grouping multiscale fusion convolution is proposed and applied in C2f and detection head.Deployed LFA-YOLO in edge devices for real-time applications.Abstract. Anthracnose is a communicable agricultural disease with a high incidence and significant damage, posing as a major threat to litchi production. In this article, we propose a lightweight target detection method called LFA-YOLO to address the problem of leakage and misdetection in the detection of lychee fruit anthracnose due to the complexity of the agricultural environment. Our method incorporates a Multipath Coordinate Attention (MCA) mechanism into the YOLOv8 algorithm to mitigate detection errors caused by mutual occlusion between fruits. Additionally, in order to reduce the number of model parameters, we utilize the more efficient LeanNet to replace the backbone network of the baseline model. Moreover, we propose a more efficient channel grouping multi-scale fusion convolution (CGMF convolution) and apply it to the C2f module and decoupled detection head. Experimental results on the lychee fruit anthracnose (LFA) dataset demonstrate that the proposed LFA-YOLO model achieves a mAP50 of 88.61, with precision and recall rates of 90.18 and 82.77, respectively. Furthermore, the number of model parameters and floating-point operations (FLOPs) of the new method decreases to 61% and 48% of that of the baseline network, while the frames per second (FPS) improves to 90.3. Finally, we deploy the proposed LFA-YOLO on the NVIDIA Jetson Nano edge computing device to provide vision support for agricultural unmanned aerial vehicles (UAVs). Keywords: Attention mechanism, Lychee fruit anthracnose, Object detection, YOLOv8.
Ultrafine GGBS and Fly Ash as Cement Replacement for Sustainable Concrete
Authors: Harshit Saxena  , Vikas Srivastava  , Ashish Kumar Yadav  , Ashok Kumar Tiwari  
Published: October 2024

The construction industry is one of the major contributors to environmental degradation. Hence, it requires eco-friendly practices to make concrete more sustainable. This can be achieved by addition of mineral admixtures as a cement replacement. This process helps the environment in two ways: by reducing the carbon dioxide emission through cement replacement and by utilizing mineral admixtures such as fly ash, Ground Granulated Blast Furnace Slag (GGBS), metakaolin, rice husk ash and silica fume, which are all industrial wastes or by-products. Hence, this approach lowers the greenhouse effect and global warming by reducing carbon dioxide emissions and prevents environmental contamination by utilizing industrial wastes. This experimental study aims to find the perfect combination of mineral admixtures such as fly ash and ultrafine GGBS to maximize cement replacement in concrete without compromising its mechanical properties and achieving a more sustainable concrete for day-to-day practice. For this study, the fly ash percentage was maintained at 20% for all trials, with the ultrafine GGBS percentage varying from 15% to 30%.
Keywords: Sustainable Concrete; Ultrafine GGBS; Fly ash; Mineral Admixture.
An Investigation into the Impact of Nano-Additives on the Performance and Emission Levels of a Diesel Engine Fuelled by Nahar Biodiesel
Authors: R. Rohith Renish  , Selvam Amala Justus 
Published: October 2024

Research on alternative fuels has been intense due to rising energy needs, fossil fuel depletion, rising fuel consumption rates, and the generation of toxic pollutants. The production of biodiesel included the use of nahar oil by acid esterification, followed by a trans-esterification process. 20% volume of nahar biodiesel blend (NME20) was blended with diesel considering it to be the optimized blend ratio. Nanoparticles such as titanium dioxide (TiO2) and aluminium oxide (Al2O3) were used to improve the properties of fuel. The additives were included into the biodiesel mix at concentrations of 25, 50, 75, and 100 parts per million (ppm), respectively. This research aims to evaluate the efficacy and ecological footprint of a diesel engine that utilises a blend of nahar biodiesel with the incorporation of nano additives. An experimental setup was implemented on a diesel engine with a single cylinder to assess its performance and emissions at various engine loads. The tests demonstrated that the use of a biodiesel mix NME20 containing 100 ppm nano Al2O3, (NME20Al100), resulted in a significant increase of 12.48% in thermal efficiency when compared to the other fuels tested. The addition of Al2O3 to the NME20 with 100ppm also resulted with the reduction of 22.85%, 23.07% and 27.59% of CO, HC and smoke emissions, respectively. Despite the fact that NOx levels tend to rise when nano additions are used, SME20Al100 stands out as the best nano additive compared to SME20Ti100 because of its exceptional engine performance.
Dilation framing camera with the dual-pulse excitation technique
Authors: Cai Houzhi , Du Zhuoming , Luo Qiuyan , Ma Youlin , Liu Jinyuan , Xiang Lijuan 
Published: October 2024

In an inertial confinement fusion (ICF) ultrafast diagnostic system that is based on electron beam time-dilation, an ultrafast electrical pulse is used to excite a microstrip photocathode (PC), which generates a varying PC voltage to obtain a photoelectron velocity that varies with emission time. The photoelectron beam achieves time-dilation through the drift process and is then detected by a time-resolved sensor, thereby increasing the temporal resolution of the diagnostic system. A pulse time-dilation diagnostic system is simulated, while the sensor is a gated microchannel plate (MCP) detector with a temporal resolution of 100 ps and an excitation pulse on a PC with a slope of 3 V/ps; the diagnostic system achieves a temporal resolution of 11.12 ps. However, the excitation pulse creates a voltage difference across the PC. A voltage difference of 900 V can be acquired for a PC length of 60 mm, which yields a nonuniform spatial resolution ranging from 30.4 µm to approximately 3000 µm. Furthermore, the voltage difference across the PC also limits the frame size to 2.2 mm along the pulse propagation direction according to the simulation results. To achieve a uniform spatial resolution and a larger frame size, a dual-pulse excitation technique on a PC is presented, which is the technique to symmetrically apply voltage pulses at both ends of the PC microstrip. The theoretical results show that this technique will improve the uniformity of the PC voltage spatial distribution. When the PC pulse slope is 3 V/ps and the dual-pulse excitation technique is employed, the diagnostic system has a temporal resolution of 5.91 ps and a uniform spatial resolution of 30.4 µm. Furthermore, the frame size along the pulse propagation direction is improved to the effective length of the microstrip PC.
Risk factors of thromboembolic events in patients with scrub typhus
Authors: Ki Young Jae , Kim Sung Soo , Seo Jun-Won , Kim Da Young , Yun Na Ra , Kim Choon-Mee , Kim Dong-Min 
Published: October 2024

Background
Thromboembolic events are a well-recognized cause of in-hospital deaths of patients with infectious diseases. However, thromboembolic events in patients with scrub typhus, caused by Orientia tsutsugamushi have rarely been reported. This study aimed to assess risk factors associated with thromboembolic events in patients with scrub typhus.

Methods
All 93 scrub typhus patients’ diagnoses were confirmed serologically or by positive nested polymerase chain reaction (PCR). The clinical and laboratory findings from 12 scrub typhus patients with thromboembolic events and 81 scrub typhus patients with nonthromboembolic events were retrospectively studied. To determine the factors implicated in thromboembolic events, we performed multivariate logistic regression analysis using the six independent factors identified by the univariate analysis.

Findings
The mean age of the patients in the thromboembolic group was 76.4 years (median, 76 years), and in nonthromboembolic group it was 64.6 years (median, 65 years) (P<0·001). Thromboembolic events were observed in 12 patients. These events included acute coronary syndrome (n = 5), acute limb ischemia (n = 4), ischemic stroke (n = 1), deep vein thrombosis combined with pulmonary thromboembolism (n = 1), and left common iliac artery aneurysm with a thrombus (n = 1). According to multivariate analysis, the following four factors were significantly associated with the thromboembolic events: 1) treatment with rifampin (OR = 57.63; P = 0.039; CI 1.230–2700.27)., 2) Taguchi genotype (OR = 41.5; P = 0.028; CI 1.5–1154.6), 3) atrial fibrillation (OR = 9.4; P = 0.034; CI 1.2–74.0), and 4) age (OR = 1.1; P = 0.046; CI 1.0–1.3).

Conclusions
Our study suggests that clinicians should be cautious when managing patients with scrub typhus to avoid the development of thromboembolic events, especially in patients with risk factors such as treatment with rifampin, Taguchi genotype, atrial fibrillation, and advanced age.