bluuebunny/crossref_metadata_2025_split huggingface dataset:
Enhancing autonomous vehicle navigation using SVM-based multi-target detection with photonic radar in complex traffic scenarios
Authors: Chaudhary Sushank , Sharma Abhishek , Khichar Sunita , Meng Yahui , Malhotra Jyoteesh 
Published: July 2024

AbstractEfficient transportation systems are essential for the development of smart cities. Autonomous vehicles and Intelligent Transportation Systems (ITS) are crucial components of such systems, contributing to safe, reliable, and sustainable transportation. They can reduce traffic congestion, improve traffic flow, and enhance road safety, thereby making urban transportation more efficient and environmentally friendly. We present an innovative combination of photonic radar technology and Support Vector Machine classification, aimed at improving multi-target detection in complex traffic scenarios. Central to our approach is the Frequency-Modulated Continuous-Wave photonic radar, augmented with spatial multiplexing, enabling the identification of multiple targets in various environmental conditions, including challenging weather. Notably, our system achieves an impressive range resolution of 7 cm, even under adverse weather conditions, utilizing an operating bandwidth of 4 GHz. This feature is particularly crucial for precise detection and classification in dynamic traffic environments. The radar system's low power requirement and compact design enhance its suitability for deployment in autonomous vehicles. Through comprehensive numerical simulations, our system demonstrated its capability to accurately detect targets at varying distances and movement states, achieving classification accuracies of 75% for stationary and 33% for moving targets. This research substantially contributes to ITS by offering a sophisticated solution for obstacle detection and classification, thereby improving the safety and efficiency of autonomous vehicles navigating through urban environments.
Evaluating prompt engineering on GPT-3.5’s performance in USMLE-style medical calculations and clinical scenarios generated by GPT-4
Authors: Patel Dhavalkumar , Raut Ganesh , Zimlichman Eyal , Cheetirala Satya Narayan , Nadkarni Girish N , Glicksberg Benjamin S. , Apakama Donald U. , Bell Elijah J. , Freeman Robert , Timsina Prem , Klang Eyal 
Published: July 2024

AbstractThis study was designed to assess how different prompt engineering techniques, specifically direct prompts, Chain of Thought (CoT), and a modified CoT approach, influence the ability of GPT-3.5 to answer clinical and calculation-based medical questions, particularly those styled like the USMLE Step 1 exams. To achieve this, we analyzed the responses of GPT-3.5 to two distinct sets of questions: a batch of 1000 questions generated by GPT-4, and another set comprising 95 real USMLE Step 1 questions. These questions spanned a range of medical calculations and clinical scenarios across various fields and difficulty levels. Our analysis revealed that there were no significant differences in the accuracy of GPT-3.5's responses when using direct prompts, CoT, or modified CoT methods. For instance, in the USMLE sample, the success rates were 61.7% for direct prompts, 62.8% for CoT, and 57.4% for modified CoT, with a p-value of 0.734. Similar trends were observed in the responses to GPT-4 generated questions, both clinical and calculation-based, with p-values above 0.05 indicating no significant difference between the prompt types. The conclusion drawn from this study is that the use of CoT prompt engineering does not significantly alter GPT-3.5's effectiveness in handling medical calculations or clinical scenario questions styled like those in USMLE exams. This finding is crucial as it suggests that performance of ChatGPT remains consistent regardless of whether a CoT technique is used instead of direct prompts. This consistency could be instrumental in simplifying the integration of AI tools like ChatGPT into medical education, enabling healthcare professionals to utilize these tools with ease, without the necessity for complex prompt engineering.
Prevalence and incidence of venous thromboembolism in geriatric patients admitted to long-term care hospitals
Authors: Wagner Gernot , Steiner Daniel , Ohrenberger Gerald , Smeikal Michael , Gisinger Christoph , Moertl Deddo , Nopp Stephan , Gartlehner Gerald , Pabinger Ingrid , Ay Cihan 
Published: July 2024

AbstractThe risk of venous thromboembolism (VTE) increases with age. However, the risk of VTE in the setting of long-term care hospitals is understudied. Our objective was to provide data on the prevalence and incidence of VTE in older adults admitted to long-term care hospitals. In this retrospective cohort study, we collected data about chronically ill and multimorbid patients aged 65 years and older from two long-term care hospitals. The primary endpoint of this study was the lifetime prevalence of VTE, and the secondary endpoint was VTE incidence during residency in long-term care hospitals. We analysed data from 1148 patients with a mean age of 84.1 ± 7.9 years, of whom 74.2% were women. The lifetime prevalence of VTE at baseline was 9.6% (95% CI 7.9–11.4). Cumulative incidence of VTE at 1, 2, and 3 years from baseline was estimated at 3.5% (95% CI 2.5–4.7), 4.2% (95% CI 3.1–5.5), and 5.4% (95% CI 4.1–7.0), respectively. Overall, the incidence rate of VTE in our study was 2.82 (95% CI 2.18–3.66) per 100 person-years. The study indicated a considerably high lifetime prevalence and incidence of VTE during residence in long-term care hospital settings, requiring further evaluation in larger prospective studies.
Identification of novel toxins associated with the extracellular contractile injection system using machine learning
Authors: Danov Aleks , Pollin Inbal , Moon Eric , Ho Mengfei , Wilson Brenda A , Papathanos Philippos A , Kaplan Tommy , Levy Asaf 
Published: July 2024

AbstractSecretion systems play a crucial role in microbe-microbe or host-microbe interactions. Among these systems, the extracellular contractile injection system (eCIS) is a unique bacterial and archaeal extracellular secretion system that injects protein toxins into target organisms. However, the specific proteins that eCISs inject into target cells and their functions remain largely unknown. Here, we developed a machine learning classifier to identify eCIS-associated toxins (EATs). The classifier combines genetic and biochemical features to identify EATs. We also developed a score for the eCIS N-terminal signal peptide to predict EAT loading. Using the classifier we classified 2,194 genes from 950 genomes as putative EATs. We validated four new EATs, EAT14-17, showing toxicity in bacterial and eukaryotic cells, and identified residues of their respective active sites that are critical for toxicity. Finally, we show that EAT14 inhibits mitogenic signaling in human cells. Our study provides insights into the diversity and functions of EATs and demonstrates machine learning capability of identifying novel toxins. The toxins can be employed in various applications dependently or independently of eCIS.
The construction of stance in English and Arabic newspaper editorials: a case study
Authors: Alghazo Sharif , Al-Anbar Khulood , Rabab’ah Ghaleb , Abusalim Nimer , Rayyan Mohammad 
Published: July 2024

AbstractThis study explores the construction of authorial stance in English and Arabic newspaper editorials. To achieve this objective, the study examines a corpus of 80 newspaper editorials retrieved from two newspapers: The first publishes in English (The Guardian, the UK), and the second publishes in Arabic (Addustour, Jordan). The study adopts Hyland’s taxonomy of stance, which includes features of hedges, boosters, attitude markers and self-mentions. To analyse the data, the study follows a mixed-methods approach to identify differences, if any, in the construction of authorial stance in the two languages in the editorial genre. A functional analysis is carried out to capture these markers within contexts. The results reveal that the most frequently used stance devices in Arabic editorials are the attitude markers, followed by boosters, hedges and self-mentions. Contrariwise, the findings showcase that the most frequently used stance device is hedging, followed by attitude markers, boosters, and self-mention. The study concludes that the two languages differ in the way they construct stance in editorials, a conclusion that provides implications for second-language professional writing teachers and students. The findings provide insights that might enhance the skills of argumentative writing in English for media courses.
Enhanced phase sensitivity in a feedback-assisted interferometer
Authors: Jiao Gao-Feng 
Published: July 2024

Abstract
The topology of feedback optical parametric amplifier (FOPA) renders a number of significant advantages over the topology of traditional optical parametric amplifier (TOPA) such as a higher degree of quantum correlation, all-phase entanglement enhancement, and the robustness of the losses. Here, we propose a feedback-assisted interferometer based on the topology of FOPA for quantum metrology. We theoretically study the phase sensitivity with the method of homodyne detection and product detection. By manipulating the feedback strength of the FOPA, the phase sensitivity can be further enhanced, and approach the quantum Cramér-Rao bound. Furthermore, we demonstrate that our proposal is superior to the SU(1,1) interferometer based on the topology of TOPA.
ClusterMatch aligns single-cell RNA-sequencing data at the multi-scale cluster level via stable matching
Authors: Ba Teer , Miao Hao , Zhang Lirong , Gao Caixia , Wang Yong 
Published: July 2024

Abstract

Motivation
Unsupervised clustering of single-cell RNA sequencing (scRNA-seq) data holds the promise of characterizing known and novel cell type in various biological and clinical contexts. However, intrinsic multi-scale clustering resolutions poses challenges to deal with multiple sources of variability in the high-dimensional and noisy data.

Results
We present ClusterMatch, a stable match optimization model to align scRNA-seq data at the cluster level. In one hand, ClusterMatch leverages the mutual correspondence by canonical correlation analysis and multi-scale Louvain clustering algorithms to identify cluster with optimized resolutions. In the other hand, it utilizes stable matching framework to align scRNA-seq data in the latent space while maintaining interpretability with overlapped marker gene set. Through extensive experiments, we demonstrate the efficacy of ClusterMatch in data integration, cell type annotation, and cross-species/timepoint alignment scenarios. Our results show ClusterMatch’s ability to utilize both global and local information of scRNA-seq data, sets the appropriate resolution of multi-scale clustering, and offers interpretability by utilizing marker genes.

Availability and implementation
The code of ClusterMatch software is freely available at https://github.com/AMSSwanglab/ClusterMatch.
Community context influences the conjugation efficiency of Escherichia coli
Authors: Bustamante Misshelle , Koopman Floor , Martens Jesper , Brons Jolanda K , DelaFuente Javier , Hackl Thomas , Kuipers Oscar P , van Doorn G Sander , de Vos Marjon G J 
Published: July 2024

Abstract
In urinary tract infections (UTIs), different bacteria can live in a polymicrobial community consisting of different species. It is unknown how community members affect the conjugation efficiency of uropathogenic Escherichia coli. We investigated the influence of individual species often coisolated from urinary infections (UTI) on the conjugation efficiency of E. coli isolates in artificial urine medium. Pairwise conjugation rate experiments were conducted between a donor E. coli strain containing the pOXA-48 plasmid and six uropathogenic E. coli isolates, in the presence and absence of five different species commonly coisolated in polymicrobial UTIs to elucidate their effect on the conjugation efficiency of E. coli. We found that the basal conjugation rates of pOXA-48, in the absence of other species, are dependent on the bacterial host genetic background. Additionally, we found that bacterial interactions have an overall positive effect on the conjugation rate of pOXA-48. Particularly, Gram-positive enterococcal species were found to enhance the conjugation rates towards uropathogenic E. coli isolates. We hypothesize that the nature of the coculture and physical interactions are important for these increased conjugation rates in an artificial urine medium environment.
The Hawkmoth Proboscis: An Insect Model for Sensorimotor Control of Reaching and Exploration
Authors: Stöckl Anna , Deora Tanvi 
Published: July 2024

Synopsis
Reaching and inspecting objects is an intricate part of human life, which is shared by a diversity of animals across phyla. In addition to appendages like legs and antennae, some insects use their mouthparts to reach and inspect targets. Hawkmoths of the family Sphingidae (Lepidoptera) use their extremely long and straw-like proboscis to drink nectar from flowers. As they approach flowers, hawkmoths uncoil their proboscis and explore the floral surface while hovering to target the proboscis to the nectary hole. Several sensory modalities provide feedback to control and guide these extremely versatile proboscis movements. The control task faced by the hawkmoths’ nervous system during such behaviors is not unlike that of an animal guiding limbs or a robotic agent guiding a manipulator to a target. Hawkmoths perform these reaching maneuvers while simultaneously hovering, and hence require rapid and continuous coordination between the proboscis, neck, and flight motor systems, thereby providing a unique invertebrate model for studying appendage guidance and reaching. Here, we review what is known about how hawkmoths use their proboscis for floral inspection and nectar discovery, as well as the role of various sensors in proboscis guidance. We give a brief overview of the morphology and muscular apparatus of the hawkmoth proboscis, and discuss how multimodal sensory feedback might be turned into motor action for appendage guidance.
Advanced hierarchical planning and design for low-carbon landscape architecture leveraging virtual reality technology
Authors: Zhu Fangda , Chen Yaling 
Published: July 2024

Abstract
The incorporation of sophisticated artificial intelligence technologies and data mining methodologies is critical for the planning and design of low-carbon landscape architectural environments. To enhance the three-dimensional reconstruction capabilities and visual esthetics of hierarchical planning and design within low-carbon landscape architectural environments, this study introduces a novel methodology predicated on virtual reality (VR) technology. This approach harnesses the diverse pictorial structure feature distribution inherent to low-carbon landscape architectural environments, amalgamated with VR's feature structure reorganization and enhancement techniques. Furthermore, we propose methodologies for joint measurement and multi-level integration to refine the hierarchical planning and design process within these environments. Simulation outcomes demonstrate the efficacy of this method in achieving superior three-dimensional reconstruction and visual representation, thereby augmenting the planning and design quality within the domain of low-carbon landscape architecture.
Research on the application of lightweight deep learning model in automatic identification of electricity-related public safety hazards in distribution lines
Authors: Feng Bin , Wei Jie 
Published: July 2024

Abstract
In view of the current problems of low speed, high network complexity, and difficulty in accurately detecting small target defects in insulator defect detection methods, this study proposes a lightweight insulator defect detection model. First, by enhancing both the convolutional block (CBL) and the efficient long-range aggregation network (ELAN-S) within the feature extraction network, the extraction capability for defect features is significantly augmented. Secondly, the CA-Tiny Spatial Pyramid Pooling (SPP) module was crafted by seamlessly integrating the coordinate attention mechanism with Tiny SPP, enabling the model to prioritize insulator defect characteristics and thereby enhancing defect detection accuracy. Finally, utilizing the positioning loss function WIoUv3 loss for loss calculation, a smaller gradient gain is assigned to low-quality anchor boxes, minimizing harmful gradients and enhancing the model’s positioning performance. Experimental outcomes demonstrate that the enhanced YOLOv7-tiny model excels in rapid and precise defect detection. In comparison to the original YOLOv7-tiny model, the proposed version is well-suited for edge device deployment, enabling real-time insulator defect detection.
H i content at cosmic noon – a millimetre-wavelength perspective
Authors: Messias Hugo , Guerrero Andrea , Nagar Neil , Regueiro Jack , Impellizzeri Violette , Orellana Gustavo , Vioque Miguel 
Published: July 2024

ABSTRACT
In order to understand galaxy growth evolution, it is critical to constrain the evolution of its building block: gas. Mostly comprised by Hydrogen in its neutral (H i) and molecular (H$_2$) phases, the latter is the one mostly directly associated to star formation, while the neutral phase is considered the long-term gas reservoir. In this work, we make use of an empirical relation between dust emission at millimetre wavelengths and total gas mass in the interstellar medium (M$_{\rm HI}$ plus M$_{\rm H_2}$) in order to retrieve the H i content in galaxies. We assemble an heterogeneous sample of 335 galaxies at $0.01\lt z\lt 6.4$ detected in both mm-continuum and carbon monoxide (CO), with special focus on a blindly selected sample to retrieve H i cosmological content when the Universe was $\sim 2-6\,$ Gyr old ($1\lt z\lt 3$). We find no significant evolution with redshift of the M$_{\rm HI}$/M$_{\rm H_2}$ ratio, which is about $1-3$ (depending on the relation used to estimate M$_{\rm HI}$). This also shows that M$_{\rm H_2}$-based gas depletion times are underestimated overall by a factor of $2-4$. Compared to local Universe H i mass functions, we find that the number density of galaxies with M$_{\rm HI}\gtrsim 10^{10.5}\,$M$_\odot$ significantly decreased since 8–12 Gyr ago. The specific sample used for this analysis is associated to 20–50 per cent of the total cosmic H i content as estimated via Damped Lyman-$\alpha$ Absorbers. In IR luminous galaxies, H i mass content decreases between $z\sim 2.5$ and $z\sim 1.5$, while H$_2$ seems to increase. We also show source detection expectations for SKA surveys.
The PARSEC view of star formation in galaxy centres: from protoclusters to star clusters in an early-type spiral
Authors: Prieto Almudena , Gladis Magris C , Bruzual Gustavo , Fernández-Ontiveros Juan A , Burkert Andreas 
Published: July 2024

ABSTRACT
Understanding star formation in galaxies requires resolving the physical scale on which star formation often occurs: the scale of star clusters. We present a multiwavelength, eight-parsec resolution study of star formation in the circumnuclear star cluster and molecular gas rings of the early-type spiral NGC 1386. The cluster ring formed simultaneously ∼4 Myr ago. The clusters have similar properties in terms of mass and star formation rate, resembling those of H ii regions in the Milky Way disc. The molecular CO gas resolves into long filaments, which define a secondary ring detached from the cluster ring. Most clusters are in CO voids. Their separation with respect to the CO filaments is reminiscent of that seen in galaxy spiral arms. By analogy, we propose that a density wave through the disc of this galaxy may have produced this gap in the central kpc. The CO filaments fragment into strings of dense, unresolved clouds with no evidence of a stellar counterpart. These clouds may be the sites of a future population of clusters in the ring. The free-fall time of these clouds, ∼10 Myr, is close to the orbital time of the CO ring. This coincidence could lead to a synchronous bursting ring, as is the case for the current ring. The inward spiralling morphology of the CO filaments and co-spatiality with equivalent kpc-scale dust filaments are suggestive of their role as matter carriers from the galaxy outskirts to feed the molecular ring and a moderately active nucleus.
Adaptation of the protein misfolding cyclic amplification (PMCA) technique for the screening of anti‐prion compounds
Authors: Do Katherine , Benavente Rebeca , Catumbela Celso S. G. , Khan Uffaf , Kramm Carlos , Soto Claudio , Morales Rodrigo 
Published: July 2024

AbstractPrion diseases result from the misfolding of the physiological prion protein (PrPC) to a pathogenic conformation (PrPSc). Compelling evidence indicates that prevention and/or reduction of PrPSc replication are promising therapeutic strategies against prion diseases. However, the existence of different PrPSc conformations (or strains) associated with disease represents a major problem when identifying anti‐prion compounds. Efforts to identify strain‐specific anti‐prion molecules are limited by the lack of biologically relevant high‐throughput screening platforms to interrogate compound libraries. Here, we describe adaptations to the protein misfolding cyclic amplification (PMCA) technology (able to faithfully replicate PrPSc strains) that increase its throughput to facilitate the screening of anti‐prion molecules. The optimized PMCA platform includes a reduction in sample and reagents, as well as incubation/sonication cycles required to efficiently replicate and detect rodent‐adapted and cervid PrPSc strains. The visualization of PMCA products was performed via dot blots, a method that contributed to reduced processing times. These technical changes allowed us to evaluate small molecules with previously reported anti‐prion activity. This proof‐of‐principle screening was evaluated for six rodent‐adapted prion strains. Our data show that these compounds targeted either none, all or some PrPSc strains at variable concentrations, demonstrating that this PMCA system is suitable to test compound libraries for putative anti‐prion molecules targeting specific PrPSc strains. Further analyses of a small compound library against deer prions demonstrate the potential of this new PMCA format to identify strain‐specific anti‐prion molecules. The data presented here demonstrate the use of the PMCA technique in the selection of prion strain‐specific anti‐prion compounds.