bluuebunny/crossref_metadata_2025_split huggingface dataset:
Enhanced Balanced-Generative Adversarial Networks to Predict Pedestrian Injury Types
Authors: Somvanshi Shriyank , Antariksa Gian , Das Subasish 
Published: June 2024

Abstract

Pedestrians are at a significantly higher risk of suffering serious injuries or death in road traffic incidents. In 2021 alone there were 7,388 pedestrian fatalities and 60,577 injuries. Addressing this critical issue, our study introduced a novel methodology for predicting the severity of pedestrian crashes. This method leveraged advanced deep learning models such as Inception-ResNet-v2, Inception-v3, and Xception applied to synthetic data generated by Generative Adversarial Networks (GANs). This study analyzed data related to pedestrian crash severity in Louisiana spanning five years (2016–2021), encompassing forty variables that include pedestrian demographics, accident location, and vehicle specifics. The severity of crashes was categorized into three categories: injury, no injury, and fatal. To combat the challenge of data imbalance, our study implemented a novel method that combined traditional sampling methods with GANs. This integrated methodology facilitated the generation of synthetic data utilizing the Conditional Tabular GAN (CTGAN) model and the attainment of balanced datasets by employing under-sampling via the Random Under Sampler (RUS) technique and over-sampling through the Synthetic Minority Over-sampling Technique (SMOTE). Thereafter, the DeepInsight technique was employed to transform numerical and categorical crash data into image format, making it compatible with the deep learning models utilized. The findings reveal that the models demonstrated improved predictive capabilities when applied to the over sampled dataset, which was achieved by increasing the number of instances in the minority class to balance the distribution of classes, as evidenced by various performance metrics including accuracy, precision, recall, and F1 score. Specifically, the Inception-ResNet-v2, Inception-v3, and Xception models recorded predictive accuracies of 82.73%, 84.75%, and 69.07% respectively, with the over sampled dataset, which was the highest among the three sampling categories of data considering all the metrics. The insights derived from this research have practical applications for urban planners, city engineers, safety professionals, transportation authorities, emergency service providers, vehicle manufacturers, and traffic management centers.
Reinforcement Learning Recommendation Algorithm Based on Environmental Information Exploration
Authors: Jia Junjie , Wang Huijuan , Wang Fen , Li Tianle , Liu Shilong 
Published: June 2024

Abstract

Most of the current recommendation algorithms based on reinforcement learning are biased towards the design of exploration strategies at the model level, ignoring the full use of environmental state information and the impact of action exploration (recommendation behaviour) on the user experience, which leads to closed-loop information and user turnover caused by the decline in the long-term effectiveness of the recommendation system. In order to efficiently "use" the state to "explore" the action, this paper proposes a reinforcement learning recommendation algorithm based on environmental information exploration(RLEEA). The algorithm organises the state space according to the principle of satisfying user preferences, using the preference preference strategy to improve the full use of environmental information, and guides the exploration direction of the model according to the environmental state representation and user experience by considering the integrated rewards inside and outside the environment, so that the model is more inclined to continuously learn the recommended actions in line with the users’ preferences. The experimental results show that the proposed method achieves obvious effect improvement in various indicators of recommendation performance, which verifies the effectiveness of the proposed algorithm.
Exploration of Anomuran crabs from the intertidal zone of Kadmat and Amini Islands of the Lakshadweep Archipelago, India
Authors: NM Naseem , KJ Jayalakshmi , Nihal Davood , Kumar Akshay A 
Published: June 2024

Abstract

A first hand study regarding the Anomuran crabs in the intertidal zone of Kadmat and Amini islands of Lakshadweep was carried out during November 2021 to June 2022 by monthly sampling from six stations of Kadmat and Amini islands. The study recorded a total nine species of Anomuran crabs, contributed by eight species of hermit crabs belongs to three genera and two families of superfamily Paguroidea and single species of mole crab of superfamily Hippoidea. The hermit crabs namely Coenobita perlatus, C. clypeatus, Calcinus laevimanus, C. latens, C. elegans, Dardanus megistos, D. guttatus and D. deformis. The single species of mole crab is Hippa adactyla. The spatial and temporal variations with respect to abundance and distribution were assessed. The peak average abundance of Anomurans was recorded in the month of April and lowest values during December. Northern part of Kadmat Island had the highest total abundance of the Anomurans and east side of Kadmat had the lowest abundance. The most dominant species was Hippa adactyla with maximum records in the month of April. Among hermit crabs the dominant species was C. perlatus. The least abundant species among Anomuran was D. megistos. The distribution and abundance of species differed based on habitat variability. Traditionally these crabs are used by the local inhabitants of Lakshadweep as a bait for fishery rarely as food and for medicinal purposes. An interesting traditional usage of hermit crab as laxative agent to prevent theft of ‘Neera’. Nowadays unscientific coastal protection structures and other anthropogenic interventions become a serious threat to these Anomuran crabs.
Conceptualization of Digital Twin-Enabled New Product Design Framework for the Automotive Industry
Authors: Muthappan Chandrasekaran , PK Rajesh 
Published: June 2024

Abstract

The digital twin (DT) has created various opportunities for product development businesses to exploit data obtained from the physical model. Ideally, many companies are strengthening their use cases by incorporating obtained physical data into a virtual model. Emerging communication technologies, such as the 5th generation mobile network (5G), the Internet of Things (IoT), Industrial Internet of Things (IIoT) sensors, and so on, enable the collection of data from physical products and its transmission to cloud computing, also known as big data. With the lack of standard architecture, many businesses use their own big data to develop their digital models without any roadmap. This research provides a novel DT-enabled new product design framework allowing interaction between the DT and product design environments. This system will enable data to be taken from various physical entities, stored in a centralized location, and then fed into a digital entity, which processes the data and converts it into information for decision-making. The digital entity employs various technologies to transform data into information, including artificial intelligence (AI) and machine learning (ML) models, mathematical models, and simulation models. These models generate processed synthetic or DT data, which is then used for control/monitoring and visualization/interaction reasons. In this research, data classed as visualization and interaction is integrated with the new product design framework at all four design stages, namely concept design, detailed design, design verification, and redesign, with varied data contributions to the design. A case study that used DT data processed using the AI / ML model throughout the conceptual design phase was presented. Using synthetic data, the design concept of the medium-duty truck frame assembly was iteratively tested using ten load instances before being finished. The results are encouraging since the overall weight of the frame assembly was reduced by 9% while maintaining the frame assembly's strength and safety factor. The design iterations have come down to 3 iterations from 6 iterations, which is a 50% improvement over the traditional product development processes.
Probing the Scalar WIMP-Pion Coupling with the first LUX-ZEPLIN data
Authors: Eriksen Sam , Qie Yufan , Boxer Billy 
Published: June 2024

Abstract

Weakly interacting massive particles (WIMPs) may interact with a virtual pion that is exchanged between nucleons.
This interaction channel is important to consider in models where the spin-independent isoscalar channel is suppressed.
Using data from the first science run of the LUX-ZEPLIN dark matter experiment, containing 60 live days of data in a 5.5~tonne fiducial mass of liquid xenon, we report the results on a search for WIMP-pion interactions.
We observe no significant excess and set an upper limit of $1.5\times10^{-46}$~cm$^2$ at a 90\% confidence level for a WIMP mass of 33~GeV/c$^2$ for this interaction.
Home-made lateral flow test strip versus POC-CCA assay for detection of active schistosomiasis in Egypt
Authors: Kamel Manal , Salah Faten , Demerdash Zeinab , Maher Sara , El-Baz Hanan , Yousef Nahla , Abu-Shady Rania , Rezk Amany , Hassan Salwa , Aziz Doaa Abdel 
Published: June 2024

Abstract

For years, the Kato-Katz (KK) technique has been considered the gold standard for diagnosing schistosomiasis. The aim of this study was to compare the effectiveness of our previously developed gold nanoparticle-based lateral flow test strip (AuNPs-LFTS) for diagnosing active Schistosoma mansoni with that of the commercially available point-of-care Circulating Cathodic Antigen detection (POC-CCA) kit. In this study, we collected sixty positive and twenty negative urine samples from patients in endemic hot spots in the Nile Delta, as well as from patients visiting the internal medicine clinic at Theodor Bilharz Research Institute (TBRI). We produced monoclonal antibodies (MAbs) against S. mansoni soluble egg antigen (SEA) from cloned hybridoma cells (4D/1D). These MAbs were conjugated with gold and mesoporous silica nanoparticles, and used to develop the LFTS. The LFTS demonstrated a limit of detection (LoD) of 3 ng/ml. The sensitivity and specificity of the developed LFTS were found to be 96.7% and 95%, respectively, compared to 85% and 90% for the POC-CCA detection kit. The cases were divided into groups based on egg count in the stool, categorized as light, moderate, and heavy infections. The sensitivity of the LFTS in the group with light infection was higher than that of the POC-CCA. When using the KK technique (eggs per gram of stool sample [EPG]) as the reference test, the kappa value for the nano-based strips was 0.902, compared to 0.672 for the CCA strips, indicating an almost perfect agreement between KK and our developed LFTS. These results confirm the reliability and effectiveness of the LFTS compared to commercially available kits for rapid, sensitive, and early diagnosis of schistosomiasis. However, it is recommended to conduct further assessments of the developed strip on a larger scale with a broader range of cases before considering its introduction to local or international markets
The Vibrating Capsule- Safety and Tolerability in Patients with Chronic Idiopathic Constipation
Authors: Curtin Bryan F , Quigley Eamonn M.M. , Chey William D. , Lembo Anthony J. , Brenner Darren M. , Spiegel Brennan M.R. , Rao Satish S.C. 
Published: June 2024

Abstract

BACKGROUND
Chronic Idiopathic Constipation (CIC) remains a significant problem globally with increasing estimates for disease burden. The Vibrating Capsule was recently shown in a Phase 3 Placebo-Controlled Trial to be effective in treating CIC. The safety and tolerability of the novel Vibrating Capsule system has not been described in detail.
METHODS
We analyzed data from six trials spanning the development of the Vibrating Capsule, including safety, dose-ranging and pivotal studies. The incidence of adverse events, treatment discontinuation, tolerability and satisfaction were assessed.
RESULTS
A total of 800 patients from 6 studies were included in this analysis. The most common adverse gastrointestinal events were bloating (2.9%), abdominal pain (2.9%), nausea (2.3%) and diarrhea (1.9%). A sensation of vibration was reported in 11.7% of patients. The rates of these adverse events were low, and most were categorized by the investigators as not related to the treatment. There were no serious adverse events requiring endoscopic or surgical removal of retained capsules and no patients stopped therapy early due to adverse effects. The majority of patients (83%) found the system convenient and the overall satisfaction rate with therapy was 71%.
CONCLUSIONS
The first in class Vibrating Capsule was found to be safe and well tolerated in clinical trials involving individuals with CIC. No patients discontinued treatment early due to adverse events.
SpineWave: Harnessing Fish Spinal Kinematics in Biomimetic Robotics for Enhanced Aquatic Exploration
Authors: Li Weikun , He Qu , Dai Guangmin , Chen Hao , Liu Qimeng , Tian Xiaoqing , You Jie , Cui Weicheng , Triantafyllou Michael , Fan Dixia 
Published: June 2024

Abstract

Fish have endured millions of years of evolution, and their distinct rigid-flexible body structures have offered limitless inspiration for developing biomimetic robots. The current paper introduces a fish spine-like rigid-flexible transition structure and thus leads to scalable prototypes of biomimetic robotic fish. Inspired by fish anatomy, the structure incorporates expandable fishbone-like ribs with adjustable magnets to emulate the stretch and recoil of fish muscles, thus balancing the easy implementation of rigid actuators with enhanced flexibility. Notably, such a structure is capable of full-body modular packaging, allowing for rapid expansion and adaptation to different fish shapes and swimming modes. To optimize the hydrodynamics of the robot, we employed an evolutionary algorithm, resulting in a significant enhancement in free swimming performance. At last, we demonstrate the robustness of the constructed biomimetic robotic fish in a natural water environment, showing its real-world monitoring capabilities.
Comparison of hypotension between propofol and remimazolam-propofol combinations sedation for day-surgery hysteroscopy: a prospective, randomized, controlled trial
Authors: Tan Hua , Lou Aifei , Wu Jianer , Chen Xinzhong , Qian Xiaowei 
Published: June 2024

Abstract

Background
A combination of remimazolam and propofol could produce more stable sedation. A good medication regimen should consider not only efficacy but also safety, especially hypotension. The aim of the current study was to compare the incidence and amount of hypotension by propofol versus remimazolam-propofol combinations in day-surgery hysteroscopy.
methods
Patients were randomly assigned to receive either propofol (Group P, n = 125) or remimazolam-propofol combinations (Group RP, n = 125) at a 1:1 ratio. Intravenous injection of sufentanil 0.1ug/kg were administered before sedative medication. In group P, a bolus of 2.5 mg/kg propofol was administered. In group RP, Intravenous anesthesia was commenced with 0.125mg/kg remimazolam and 1mg/kg propofol. After loss of consciousness, propofol was maintained at 6mg/kg/h. The primary outcomes were the incidence and amount of hypotension during surgery. Hypotension was defined as a MAP less than 65mmHg for at least 1min. The amount of hypotension was assessed by time-weighted average intraoperative MAP under a threshold of 65 mmHg. The secondary outcomes were various anesthesia related parameters and some adverse events.
Results
In group P, 25 patients (20.0%) experienced hypotensive during hysteroscopy compared with 9 patients (7.2%) in group RP, for a difference of 12.8% (RR 2.778, 95%CI [1.352–5.709]). The combination of remimazolam and propofol resulted in significantly lower TWA threshold 0.14 (0.10–0.56) mmHg in group RP compared to 0.31 (0.15–0.67) mmHg in group P. The total dose of propofol was nearly double in group P compared to group RP. A significantly higher frequency of injection pain and low oxygen saturation was observed in the group P than that of the group RP. Hiccup was observed only in group RP. The incidences of body movement, bradycardia and vomit were no significant difference between groups.
Conclusion
The incidence and amount of hypotension by remimazolam-propofol combinations was significantly less than that by propofol sedation in day-surgery hysteroscopy. The optimization of medication regimen would attenuate the harm of hypotension and contribute to patients’ rapid recovery in day surgery.
Trial registration :
Chinese Clinical Trial Registry, ChiCTR2400079888 (date: 15/01/2024),
Love-C relations for elastic hybrid stars
Authors: Dong Zoey Zhiyuan , Faggert Joshua Cole , Lau Shu Yan , Yagi Kent 
Published: June 2024

Abstract

Neutron stars (NSs) provide a unique laboratory to study matter under extreme densities. Recent observations from gravitational and electromagnetic waves have enabled constraints on NS properties, such as tidal deformability (related to the tidal Love number) and stellar compactness. Although each of these two NS observables depends strongly on the stellar internal structure, the relation between them (called the Love-C relation) is known to be equation-of-state insensitive. In this study, we investigate the effects of a possible crystalline phase in the core of hybrid stars (HSs) on the mass-radius and Love-C relations, where HSs are a subclass of NS models with a quark matter core and a nuclear matter envelope with a sharp phase transition in between. We find that both the maximum mass and the corresponding radius increase as one increases the stiffness of the quark matter core controlled by the speed of sound, while the density discontinuity at the nuclear-quark matter transition effectively softens the equations of state. Deviations of the Love-C relation for elastic HSs from that of fluid NSs become more pronounced with a larger shear modulus, lower transition pressure, and larger density gap and can be as large as 60%. These findings suggest a potential method for testing the existence of distinct phases within HSs, though deviations are not large enough to be detected with current measurements of the tidal deformability and compactness.
Detection of vinblastine and related bioactive compounds from culture extracts of endophytic fungi of Catharanthus roseus
Authors: Khan Uzma , Gond Surendra Kumar 
Published: June 2024

Abstract

This study investigates the synthesis of vinblastine by endophytic fungi Alternaria alternata (CRL 17), Curvularia lunata (CRL 28), Aspergillus terrus (CRL 52), and Aspergillus clavatonanicus (CRL 22), isolated from the leaf of Catharanthus roseus. The initial screening for secretion of plant alkaloids (vinca alkaloids) by fungi was performed by utilizing biochemical tests and thin-layer chromatography (TLC) which resulted total of 10 potential endophytes. Out of these ten, only four fungal extracts showed positive results for presence of vinblastine at same retention time (10 min.) compared to reference compound on HPLC analysis. The detected concentration of vinblastine was maximum (17 µg/ml) in Aspergillus clavatonanicus (CRL 22). The presence of vinblastine was further validated through ultra-high-performance liquid chromatography coupled with high-resolution accurate mass spectrometry (HRMS) analysis. The identification of anhydrovinblastine was validated through mass spectrometry, where molecular ions were observed at m/z 793.4185. The intermediate compounds which are involved in biosynthetic pathway of vinblastine were also identified in extract of Alternaria alternata (CRL 17). The study demonstrates that not only vinblastine but several other compounds of host origin have also been identified supporting the presence of biosynthetic pathway in endophytic fungus.
Dream Content Discovery from Social Media Using AI
Authors: Das Anubhab , Scepanovic Sanja , Aiello Luca Maria , Mallett Remington , Barrett Deirdre , Quercia Daniele 
Published: June 2024

Abstract

Dreaming is a fundamental but not fully understood part of human experience. Traditional dream content analysis practices, while popular and aided by over 130 unique scales and rating systems, have limitations. Often based on retrospective surveys or lab studies, and sometimes on in-home dream reports collected over some days, they struggle to be applied on a large scale or to show the importance and connections between different dream themes. To overcome these issues, we developed a new, data-driven mixed-method approach for identifying topics in free-form dream reports through natural language processing. We applied this method on 44,213 dream reports from Reddit's \rdreams subreddit, where we uncovered 217 topics, grouped into 22 larger themes: the most extensive collection of dream topics to date. We validated our topics by comparing it to the widely-used Hall and van de Castle scale. Going beyond traditional scales, our method can find unique patterns in different dream types (like nightmares or recurring dreams), understand topic importance and connections (like finding a greater predominance of indoor location settings in Reddit dreams than what was in general stipulated by previous work), and observe changes in collective dream experiences over time and around major events (like the COVID-19 pandemic and the recent Russo-Ukrainian war). We envision that the applications of our method will provide valuable insights into the complex nature of dreaming and its interplay with our waking experiences.