bluuebunny/crossref_metadata_2025_split huggingface dataset:
Factors Associated with the Chance of Carrying out a Primary Cesarean in a University Hospital
Authors: Wender Maria Celeste Osório , Duarte Rafaela Girardi , Muller Gabriel Cardozo , Cavalheiro Rosaura Rolim , Silva Yanick Adolfo Leal Correia , Carboni Cristiane , Valério Edimárlei Gonsales 
Published: June 2022

Abstract
Objective The present study seeks to identify the associated factors that increased primary cesarean delivery rates.
Methods This was a cross-sectional study that evaluated the number of primary cesarean sections performed in the years 2006 and 2018 at the Hospital de Clínicas de Porto Alegre (HCPA, in the Portuguese acronym), through the collection of data from the medical records of the patients.
Results Advanced maternal age, twin pregnancy, and higher body mass index (BMI) became more frequent in 2018 in comparison with 2006. To mitigate the impact of confounding in comparisons among groups, we made an adjustment by propensity scores and detected significant differences when comparing both age groups on twin pregnancy rates, gestational diabetes mellitus, and thyroid disease.
Conclusion Data from the present study can be used to prevent and improve the management of morbidities, impacting on better outcomes in obstetrical practice.
Fibromuscular Dysplasia: A Rare Case with Multiple Vascular Beds Involvement
Authors: Yiek Siew-Hong 
Published: June 2022

AbstractFibromuscular dysplasia (FMD) is an idiopathic, noninflammatory, and nonatherosclerotic vascular disease of small to medium-sized arteries. It can occur in almost all arteries and most commonly involving the cervicocranial and renal arteries. FMD is commonly presents as renovascular hypertension and affects mostly young ladies. However, this case demonstrates a casuistically rare form of multiple arterial beds involvement at different sites, that is, vertebral, coronary, hepatic, and lumbar arteries, with the conjunction of both bilateral renal and cervicocranial arteries.
Does Midcarpal Joint Structure Affect Development of Arthritis in the Wrist
Authors: Tesoriero Paul , Becker Jacob , Passano Brandon , Huang Shengnan , Petchprapa Catherine , Wollstein Ronit 
Published: June 2022

Abstract
Background Degenerative wrist arthritis develops in specific patterns because of forces acting on existing structural configurations. The most common pattern of wrist osteoarthritis is scapholunate advanced collapse (SLAC). Other patterns include isolated scaphotrapezial trapezoid (STT) joint and isolated midcarpal or radiolunate joint arthritis. One predictor of degeneration pattern is the structure of the wrist.
Questions/Purposes Our purpose was to evaluate the relationship between midcarpal joint structure and the pattern of degenerative arthritis. We hypothesized that a wrist type 2 will preferentially develop SLAC degeneration.
Patients and Methods We retrospectively evaluated 195 degenerative wrist radiographs. Radiographs were reviewed for lunate/wrist type, degeneration pattern, ulnar variance, radial and volar tilt, inclination, carpal height, scapholunate angle, gap, and presence of thumb carpometacarpal (CMC) joint, STT joint, and midcarpal joint arthritis.
Results We had 158 radiographs with SLAC degeneration and 37 with atypical patterns, 154 type 2 and 41 type 1 wrists. There was a significant correlation between wrist type and the pattern of wrist degeneration (p = 0.02). SLAC degeneration developed in wrists with type 2 lunate while isolated midcarpal arthritis was associated with type 1 wrist. Isolated midcarpal joint arthritis was associated with STT arthritis, p < 0.01. Radial height, inclination, volar tilt, and ulnar variance, and scapholunate gap and angle were not associated with wrist type. Ulnar variance was associated with thumb CMC and STT joint arthritis while radial height was associated with isolated midcarpal joint arthritis.
Conclusion This study found significant relationships between midcarpal joint structure and pattern of degeneration. This contributes to understanding the development of degeneration and can aid in future prevention of arthritis.
Level of Evidence This is a Level IV, diagnostic study.
Dual-axis thrust stand for the direct characterization of electrospray performance
Authors: Gilpin Matthew R. , McGehee Will A. , Arnold N. Ivan , Natisin Michael R. , Holley Zachary A. 
Published: June 2022

A dual-axis torsional thrust stand was successfully demonstrated at the Air Force Research Laboratory, enabling direct simultaneous thrust and mass loss measurement for the Air Force Electrospray Thruster Series 2 passively fed electrospray thruster. The dual-axis system is effectively two nulled torsional thrust stands sharing a single dual-axis gimbal with a thrust and mass resolution of ±0.2 µN and ±0.04 mg, respectively. The development of this system was inspired by a need for direct efficiency characterization of electrosprays via in situ mass measurements, and performance was compared to thruster masses measured pre- and post-testing using an analytical balance. Mass consumption data captured via the dual-axis stand, which is calibrated to a traceable uncertainty of 1.6%, varied between −5% and 18% as compared to analytical balance measurements throughout a multi-month testing effort highlighting the limitations in pre/post-weighing as a method for capturing propellant consumption due to absorption of atmospheric moisture when thrusters are removed from vacuum. Thrust stand tests were limited to short term operation with a daily available testing window of ∼5 h due to thrust stand drift following the 24 h cyclic temperature variations of the testing facility. A thorough investigation into the root cause of ambient thermal drift suggests that the thermal response of commercial flex-pivot bearings is directly producing spurious torques on the order of 10 μN m/°C. Additionally, unresolved charging effects on thrust stand hardware currently limit thrust stand operation to tests operating with a positive thruster polarity. Further development and long duration test stability require both a targeted investigation into flex-pivot thermal response and minimization of facility effects.
The downside of metabolic diversity: Postingestive rearrangements by specialized insects
Authors: Heiling Sven , Li Jiancai , Halitschke Rayko , Paetz Christian , Baldwin Ian T. 
Published: June 2022

SignificanceHigher plants produce specialized metabolites to cope with biotic and abiotic challenges faced in natural environments. The diversity and complexity of specialized metabolism is often beneficial, providing functional synergisms and evolutionary stability when metabolic solutions to ecological problems are deployed as mixtures. These benefits of diversity have recently been realized in the deployment of antibiotics, insecticides, fungicides, and herbicides. However, the functional downside of metabolite diversity is rarely studied, in part because the mechanisms of post-ingestive metabolite interactions are largely unknown. Here we showed that larvae of the tobacco hornworm,Manduca sexta, rearrange key constituents of two distinct defense pathways in its wild tobacco host plant,Nicotiana attenuata, to thwart the defensive properties of both pathways.
Nontrivial band topology coupled thermoelectrics in VSe2/MoSe2 van der Waals magnetic Weyl semimetal
Authors: Mohanty Saransha , Deb Pritam 
Published: June 2022

Abstract
The correlation between topological and thermoelectrics promotes numerous interesting electronic phenomena and sets the stage for efficient thermopower devices. Herein, we report nontrivial band topology of 1T–VSe2/1H–MoSe2 van der Waals system and also probe its thermoelectric (TE) characteristics on the basis of first-principle calculations. The crossover of bands, which creates a close loop near Fermi level along M–K high symmetry points, gets inverted at former crossing points of bands, under spin–orbit coupling effect. The calculated Chern Number C = 1 supports the nontrivial band topology whereas the broken time reversal symmetry asserts its magnetic Weyl semimetallic behavior. The nontrivial band topology falls under the category of Type-I Weyl band crossing. We delve into the TE characteristics of the proposed topological material by employing constant relaxation time approximation. The heterostructure shows high electrical conductivity of order 106 S m−1 at both 300 K and 1200 K, and a low magnitude of Seebeck coefficient (S) value of 79.3 μV K−1 near room temperature. Such interplay between the topological phase and TE characteristics can lay foundation for next-generation topological-TE devices.
A modified dielectric dissipation factor measurement technique for transformer insulating oil
Authors: Sur Ujjal 
Published: June 2022

Abstract
This paper proposes a low cost mechanism to accurately measure the dissipation factor and its allied effect over transformer insulating oil. The measuring circuit is a modified De Sauty bridge network where the accurate parameter measurement can been performed. The effect of stray capacitance over dielectric loss and dissipation factor has been nullified by the application of operational amplifier in the circuit. Different samples of transformer insulating oil have been tested based on their aging and moisture content to check the reliability of the proposed measuring technique. Experimental result shows the efficacy of the proposed method when compared to existing IEC and ASTM standard procedures and commercial measuring devices. Measurement error analysis with repeatability and uncertainty calculation shows promising result and is within the acceptable limits.
Multi-sensor information fusion-based prediction of remaining useful life of nonlinear Wiener process
Authors: Wu Bin , Zeng Jianchao , Shi Hui , Zhang Xiaohong , Shi Guannan , Qin Yankai 
Published: June 2022

Abstract
The use of multi-sensor information fusion techniques is essential for condition monitoring and prediction in large complex systems. In this paper, a new distributed model fusion method is proposed to predict the remaining useful life (RUL) of a nonlinear Wiener process. First, the state–space model of the nonlinear Wiener process is established, based on multi-sensor monitoring, and the distributed Kalman filtering algorithm is used to filter and fuse the measurement data received from multiple sensors. Next, the parameters and degradation states of the state–space model are estimated and updated online in real time using the expectation maximum and smoothing filter algorithms. Moreover, the distribution of the system’s RUL is obtained according to the estimated state–space model considering the random failure threshold factor. Finally, numerical experiments are conducted to elucidate the accuracy of the adopted distributed fusion method, and the adaptability and effectiveness of the proposed method are verified using the FD001 data of the C-MPASS dataset as an example.
A survey on IoT-based smart agriculture to reduce vegetable and fruit waste
Authors: Pal Himanshu , Tripathi Sweta 
Published: June 2022

Abstract
Agriculture automation is a top focus and developing area for a number of countries right now. We are seeing a surge in demand for Internet of Things (IoT) in various industries these days. One of the most essential applications of IoT is agriculture. Today, we notice that the world’s population is quickly rising, and an agro product plays a critical part in this population’s existence. We are conscious of the fact that resources are limited. If we continue to farm in the traditional manner, it will be extremely difficult for the rising population to survive. Due to improper fertilizers, quantity of water, chemicals and huge amount of pesticides decreases the fertility of land. There is a need for smart agriculture to monitor all these factors which affect the fertility of soil. When the fertility is decreasing it will impact on the growth of fruits and vegetables. In this paper we are going to study how we can manage our resources through Internet of Things, multispectral camera, hyper spectral camera, and thermal camera and RGB camera. Plant diseases, pesticide control, weed control, proper irrigation, and water management are all problems in agriculture that can be readily solved with the various automated and control approaches stated above.
Comparison of different Classification techniques for the detection of Speech affected due to Respiratory disorders
Authors: Shrivastava Poonam , Tripathi Neeta 
Published: June 2022

Abstract
Respiratory disorders are one of the common chronic disorders across the world. Any malfunctioning in the respiration process affects speech as speech and respiration go hand in hand. Analysis of speech parameter variation due to respiratory disorders is a prime research area in today’s scenario. In this paper, an efficient approach using a machine learning paradigm was used to detect the speech affected due to respiratory disorders. Various speech parameters were extracted (F1, F2, F3… etc.) using PRAAT software along with MFCC and LPC coefficients. Statistically, significant features were obtained to determine the predominant parameters. The extracted features were applied to different machine learning paradigms then different classification techniques were analyzed and compared to distinguish between normal and affected speech.5-fold,10-fold cross-validation, and hold-out data division protocols were used for evaluating the classification results. To evaluate the performance of the proposed methodology, Accuracy, sensitivity, specificity, and the area under receiver operating characteristics (AUC) were used. The result demonstrates that the speech parameters (F1, F2, F3…etc.) extraction method and the LPC method achieved a significantly higher classification accuracy, sensitivity, and specificity of 100% and AUC of 1, under the holdout method. While MFCC method achieved the highest classification accuracy of 83%, sensitivity of 100%, specificity of 67%, and AUC of 0.83.
Testing some grouping methods to achieve a low error quantile estimate for high resolution (0.25° x 0.25°) precipitation data
Authors: Sahu Ramgopal T. , Verma Shashikant , Kumar Kislay , Verma Mani Kant , Ahmad Ishtiyaq 
Published: June 2022

Abstract
The study focuses on the estimation of a technique, a method for developing a phenomenon, to obtain a quantile with minimal or low error (AR and R-RMSE bias). To arrive at such a solution, a case study of the Mahanadi River system (Mahanadi Basin) was conducted along with the integration of various techniques available in past and present literature, to come up with a novel solution. Which could answer practical questions in water resource planning and management for addressing a wide range of problems such as meteorological draught analysis, agricultural planning, precipitation forecasting and downscaling, design of water control and conveyance structures, and land-use planning and management. A gridded rainfall data set of resolution 0.25° x 0.25° (1901 – 2017) obtained from IMD Pune is used to calculate the statistics that will be used for the regionalization of precipitation. Other attributes or variables used for regionalization are seasonality measurements and location parameters (latitude, longitude, and elevation). The L-moment statistics are computed from the time series rainfall data and the ratios of the L-coefficient of variance and the L-coefficient of skewness, i.e., the L-moment ratio, are the main components in computing quantile estimates of selected regions for effective regional frequency analysis. To determine potential scenarios for homogeneous regions, the use of seasonal extreme precipitation will serve as a basis for regionalization.
Elcare: Elderly Care With Fall Detection
Authors: Jawale Chirag Dilip , Joshi Keval Ashok , Gogate Swaroop Kusumakar , Badgujar Chetana 
Published: June 2022

Abstract
Continuous growth in the aged population over the years around the globe suggests advancements in medical facilities to ensure good medical health of people. The elder population is vulnerable to many medical problems as the immune system as well as the musculoskeletal system weakens with time. Falls are the major cause leading to serious medical conditions such as paralysis or even death for elders. Early fall detection can help in reducing the severity of these accidents and provide immediate medical assistance. To detect falls this paper discusses the use of pose estimation and sensor-based mobile devices. The system makes use of MediaPipe’s Pose Detection method to form a skeletal structure of the person. Exploiting the features such as drastic change in coordinate axes, angle of inclination while falling, and the sudden change in velocity during a fall helps to verify the authenticity of the fall. The sensor-based method makes use of mobile sensors and records the change in their values to decide whether the activity is a fall or not. The combination of both these methods allows for an accurate fall detection mechanism where the system finally notifies the concerned authorities via real-time feedback techniques such as text, message, or push notification.
Characterization and driving of polymer-dispersed liquid-crystal sheet for smarthome applications
Authors: Uranus Henri P. 
Published: June 2022

Abstract
A commercial polymer-dispersed liquid-crystal (PDLC) sheet sample was characterized for its basic optical and electrical properties under DC and AC excitation. The results give driving voltage for 90% of transmittance for the PDLC of 10 V for DC excitation, and 9.5 Vrms for 50 Hz AC excitation. The measured contrast ratio of the PDLC is 2.55 and 2.47 under DC and AC excitation, respectively, which is suitable for smart window in a smarthome application. While it has rather similar optical properties under DC and AC excitation, it has significantly different electrical properties for DC and AC excitation. The PDLC exhibits a capacitive property which has capacitance per unit area of 18.5 μF/m2, indicating that DC excitation will give benefit compared to AC excitation which will scale with area of the PDLC. Based on these results, a DC driving circuit employing boost converter was designed to make a microcontroller-compatible driving circuit. The system was then integrated into a miniature smarthome demonstrator model exhibiting contrast ratio of 2.05 under switching from 0 to 100% of duty cycle of pulse width modulation (PWM) control signal from the microcontroller executed through voice command in an internet of things (IoT) platform.
Scheduling optimization researchs considering AGV operation conflicts with different loads
Authors: Tang Li-min , Wang Jun-wang , Wu Dan 
Published: June 2022

Abstract
With the increase in the volume of container trading, automated container terminals have gradually become the target of the world’s largest port construction. In order to improve the efficiency of the automated AGV container terminal and gantry cranes, the possible conflicts in the horizontal AGV transportation area under different load conditions and speeds have been resolved. The problem is to create a comprehensive scheduling model that minimizes the total AGV execution time through prediction and solved by genetic algorithm. Experimental data analysis shows that after optimization, the total execution time and conflict timeout of multiple AGVs are reduced, which improves the work efficiency of AGVs.
Intelligent video surveillance of sand mining based on object detection and tracking
Authors: Gao Yueming , Lin Qinghua , Xu Chaoyang , Li Wentong 
Published: June 2022

Abstract
In order to improve the regulatory capability of sand mining and make full use of the video resources collected by video surveillance systems, an object detection and tracking algorithm that combines YOLOv4 and Kalman filter is proposed to identify sand dredgers. Initially, an object detection dataset of common ships is finely established through camera capture, manual and automatic annotation, and data augmentation. Then, the obtained dataset is used to train YOLOv4. The results show that the trained YOLOv4 achieves a mean Average Precision of 92.26% over all classes. Although Kalman filter does not increase the precision of YOLOv4, it supplements the association information between images in an frame stream, so as to solve the target loss problem of YOLOv4 caused by occlusion. Finally, the proposed algorithm is deployed in edge computing terminal devices to form an intelligent video surveillance system for sand dredgers. The intelligent system realizes the 24-hour real-time monitoring of sand mining, which can help to stop illegal sand mining in time, and provide strong technical support for relevant departments to fulfill their management obligations.
Database Modeling Technology Research Based on Requirement Ontology
Authors: Litao Li , Jingyu Yang 
Published: June 2022

Abstract
Aiming at the complexity and uncertainty of large-scale system requirements, this paper introduces the concept of ontology, through the requirement ontology model, the system requirements are formed into a unified modular unit, and each modular unit has a structured logical relationship. Finally, the structured and modularized requirement model will form a complete requirement management platform in the DOORS tool, which will realize the basis of civil aircraft requirement management and improve the capability and efficiency of civil aircraft product design.
Research on the evolution law of incidental traffic congestion based on CTM
Authors: Peng Lang , Wang Qiu-ping , Zhou Shuai-qi , Tian Zhun 
Published: June 2022

Abstract
This paper takes the urban road network as the research object to study the temporal and spatial characteristics and evolution mechanism of incidental traffic congestion. Firstly, the improved cell transmission model (CTM) is proposed considering the traffic flow delay phenomenon and the boundary conditions of the cell at the intersection. Secondly, considering the delay time of vehicles at the intersection, the A
* path-finding algorithm is proposed, and a dynamic path selection model based on real-time road impedance is established. Finally, combined with the improved CTM and dynamic path selection model, starting from the severity of the incident and the frequency of information induction and update, the traffic flow is simulated by MATLAB software to simulate the traffic flow in the road network under different conditions and analyze the diffusion characteristics of congestion under sudden events. The simulation results show that during the simulation time period, when the traffic capacity caused by the severity of the incident is only 1/2, 1/4 and 1/8 of the original, the maximum number of congestion cells in the network is 9, 26 and 35, and the maximum delay per unit time stepping is 290, 1.31*103 and 2.41*103 vehicles, and the total delay in the road network is 2.73*105, 7.19*105, and 1.50*106 vehicles, after 320δ, 578δ and 588δ the congestion cells in the road network completely disappear. At the information induced update time of 30s, 120s and 600s, the maximum number of congestion cells in the road network is 5, 10 and 23, the maximum number of delayed vehicles is 162, 254 and 985 vehicles - time stepping, the total delay is 1.25*105, 1.68*105 and 5.84*105 vehicles. The findings of the study can provide reference for urban road network design and traffic management.