bluuebunny/crossref_metadata_2025_split huggingface dataset:
PENGARUH PERFORMA VIDEO TERHADAP JUMLAH VIEWS VIDEO REGULER DI YOUTUBE MENGGUNAKAN ANALISIS JALUR
Authors: Ashar Muhammad Adam , Farid Fuad Muhajirin , Annisa Selvi 
Published: September 2023

YouTube is a video-sharing website which is one of the media for deployment information that is of great interest to the public in Indonesia. Being the most visited website in the world, YouTube has had a significant impact on modern society. Many people in Indonesia have utilized YouTube as a platform to share their thoughts and creativity through the video they create, as well as to make income. Creative content will usually get more responses from the audience. Creating a regression model for use in path analysis enables the investigation of causal links between various variables. The intention of this study is to specify the path's structure and analyze what variables effect YouTube video views. The exogenous variables used to observe the influence of views are impressions, CTR and watch time. This study uses path analysis to examine how video performance impacts views both directly and indirectly using path diagrams. Considering the outcomes of this study, the variables that affect views are impressions and CTR. Impressions have an indirect effect on Watch Time and Views but smaller than the direct effect, so the best path to increase views is the direct effect path of impressions. Impressions have a direct effect of 1,214 while CTR has a direct effect on views of 1,077. Keywords: YouTube, Views, Path Analysis, Direct Effect
The Structure of Semiconic Idempotent Commutative Residuated Lattices
Authors: Chen Wei 
Published: September 2023

In this paper, we study semiconic idempotent commutative residuated lattices. After giving some
properties of such residuated lattices, we obtain a structure theorem for semiconic idempotent com-
mutative residuated lattices. As an application, we make use of the structure theorem to prove that
the variety of strongly semiconic idempotent commutative residuated lattices has the amalgamation
property.
Nonmetallic Anterior Hemiepiphysiodesis of the Distal Femur with a Low-Profile, Pretensioned Implant
Authors: Weltsch Daniel , Talathi Nakul S. , Thompson Rachel M. 
Published: September 2023

Case:
A 14-year-old adolescent boy with left-sided spastic hemiplegic cerebral palsy presented with a 14° left knee flexion contracture and resultant gait disturbance in the setting of an open distal femoral physis. He underwent subsequent anterior distal femur hemiepiphysiodesis with a suture anchor–based, nonmetallic implant. He achieved full correction at the 1-year follow-up and underwent uncomplicated implant removal.

Conclusion:
A low-profile, suture-based implant used for pediatric knee flexion deformity may allow surgeons to control growth in a reversible fashion by tensioning the physis while possibly avoiding some of the complications associated with currently used implants.
Spinal Melorheostosis
Authors: Serttas Muhammed Fatih , Saglam Fevzi , Kochai Alauddin , Cakir Aslı , Kantarci Fatih , Dervişoğlu Sergülen 
Published: September 2023

Case:
A 22-year-old female patient was referred to the orthopaedic department for further examination after a radiopaque area was observed in the T6 vertebra in her chest radiograph. Computed Tomography (CT) showed a sclerotic mass with smooth borders, involving the entire body of the T6 vertebra, left posterior elements, posterior of the rib past the left zygapophyseal joint, and a “flowing candle wax” image toward the T7 vertebra. Spinal melorheostosis was considered radiologically in the patient, but malignancy could not be completely excluded. Thereupon, open biopsy was performed under general anesthesia.

Conclusion:
Spinal melorheostosis is a rare condition. Histological examination should be considered in cases where the diagnosis remains suspicious after clinical and radiological evaluations.
Evaluating ChatGPT Performance on the Orthopaedic In-Training Examination
Authors: Kung Justin E. , Marshall Christopher , Gauthier Chase , Gonzalez Tyler A. , Jackson J. Benjamin 
Published: September 2023

Background:
Artificial intelligence (AI) holds potential in improving medical education and healthcare delivery. ChatGPT is a state-of-the-art natural language processing AI model which has shown impressive capabilities, scoring in the top percentiles on numerous standardized examinations, including the Uniform Bar Exam and Scholastic Aptitude Test. The goal of this study was to evaluate ChatGPT performance on the Orthopaedic In-Training Examination (OITE), an assessment of medical knowledge for orthopedic residents.

Methods:
OITE 2020, 2021, and 2022 questions without images were inputted into ChatGPT version 3.5 and version 4 (GPT-4) with zero prompting. The performance of ChatGPT was evaluated as a percentage of correct responses and compared with the national average of orthopedic surgery residents at each postgraduate year (PGY) level. ChatGPT was asked to provide a source for its answer, which was categorized as being a journal article, book, or website, and if the source could be verified. Impact factor for the journal cited was also recorded.

Results:
ChatGPT answered 196 of 360 answers correctly (54.3%), corresponding to a PGY-1 level. ChatGPT cited a verifiable source in 47.2% of questions, with an average median journal impact factor of 5.4. GPT-4 answered 265 of 360 questions correctly (73.6%), corresponding to the average performance of a PGY-5 and exceeding the corresponding passing score for the American Board of Orthopaedic Surgery Part I Examination of 67%. GPT-4 cited a verifiable source in 87.9% of questions, with an average median journal impact factor of 5.2.

Conclusions:
ChatGPT performed above the average PGY-1 level and GPT-4 performed better than the average PGY-5 level, showing major improvement. Further investigation is needed to determine how successive versions of ChatGPT would perform and how to optimize this technology to improve medical education.

Clinical Relevance:
AI has the potential to aid in medical education and healthcare delivery.
A 3-D-printed precision sediment feed
Authors: Fleming Monte 
Published: September 2023

Abstract
Reproducible and regulated sediment feed rates are necessary for many flume experiments. A sediment feed mechanism capable of precisely providing a wide range of feed rates was developed for this purpose. It was constructed using wood, aluminum, and 3-D-printed components. It is powered by a stepper motor and controlled by an Arduino, and is easily programmable. Commercially available sediment feeds use augers or vibrating trays to move sediment; in contrast, this feed employs the novel design of a slotted wheel. While some commercially available sediment feeds can handle a wider variety of grain sizes, the error of their output (vol/t) tends to be slightly higher than the error of this feed's output, and this feed can deliver sediment over a much wider range of delivery rates. The most notable advantage of this sediment feed is that the cost of materials is only about $300 U.S.
Assessing Geological Deformation Across Spatial and Temporal Scales Using Distributed Fiber Optic Sensing
Authors: Busetti S. , Kazei V. , Merry H. 
Published: September 2023

Summary
This work presents a conceptual framework for assessing geological deformation using distributed fiber-optic sensing (DFOS) that is applicable to several common sources of strain encountered during the reservoir life cycle. Common applications include strain associated with seismic and aseismic fault motion, natural and hydraulic fracture dilation and closure, and poroelastic strain evolution during injection and production. We briefly review common geological sources of strain observed in reservoir settings, then discuss the main fiber-based techniques for recording strain with attention to key deformation characteristics at different spatial and temporal resolutions. The relationships between common acquisition parameters, such as spatial resolution, data sampling rate, ability to measure relative and absolute strain, and a priori knowledge of geological strain including geomechanical models, and the availability of baseline measurements are discussed. Finally, a few examples are shown from experimental studies at the Aramco Research Center in Houston, Texas, USA. The facilities host a shallow vertical well instrumented with fiber as well as a surface fiber network embedded in a cement pad. We highlight several data sets acquired using Brillouin and Rayleigh frequency shift (BFS and RFS), low-frequency distributed acoustic sensing (LF-DAS), and DAS interrogation techniques, with a focus on concepts helpful for interpreting field strain. Using these insights as a conceptual framework for assessing geological deformation leads to more informed decisions when planning DFOS acquisitions and interpreting associated strain data.
Polymer Gel for Water Shutoff in Complex Oil and Gas Reservoirs: Mechanisms, Simulation, and Decision-Making
Authors: Jia Hu , Li Pengwu , Zhang Yufei 
Published: September 2023

Summary
Gel treatment is often used for water shutoff in high water-cut oil or gas wells. Although the properties and usage methods of gel have been well documented by different investigators, gel treatment performance is not always satisfactory in field application, especially in oil or gas reservoirs with complex conditions, such as strong bottomwater reservoirs, high-permeability-ratio oil reservoirs, and fractured gas reservoirs. In this work, we attempt to improve gel treatment application in complex situations according to the causes of disappointing performance, including unreliable numerical simulation and the misapplication of experiences. We propose a new numerical simulation method of gel treatment mechanisms and verify it by improving the acquiring method of inaccessible pore volume (IAPV), dynamic polymer adsorption (DPA), and the simulation method of disproportionate permeability reduction (DPR). The performance and optimization measures of gel treatment in different types of complex oil and gas reservoirs are discussed extensively. Moreover, the dominant influencing factor of the gel treatment effect is determined by gray relation analysis to provide more direct and effective suggestions for field application.
The results suggest that the improved access methods for IAPV and DPA can help to obtain more precise parameters easily to construct a numerical gel model. In addition, the new DPR simulation method, which considers oil or gas blocking, reduces the overestimation of gel DPR ability obtained with the conventional method. The misapplication of gel treatment experience probably causes a disappointing response, for example, gel treatment time had opposite influences on water shutoff in strong bottomwater reservoirs and high-permeability-ratio oil reservoirs, and the experience of reservoir thickness in oil reservoirs was not suitable for gas reservoirs. Furthermore, the major factors of gel treatment are varied in different oil and gas reservoirs, demonstrating that primary evaluation indicators for candidate wells are not permanent.
Prediction on Filtration Period of Granular Bed Filter Used in Purifying Produced Water in Oil Field
Authors: Wang Ke , Li Changjun , Jia Wenlong , Chen Yong 
Published: September 2023

Summary
The granular bed filter can purify the water produced in the crude oil production process by adsorbing oil droplets and suspended solids. A regeneration operation is needed to clean the granular media and recover filtration capacity after a certain operation duration. Currently, filtration models are mainly used for one type of particle removal, with few applications in the filtration system of produced water containing oil droplets and suspended solids. However, the different deposition morphologies of oil droplets and suspended solids in the filter bed can affect the prediction of the filtration process. In this work, we develop a transient filtration model based on the multiphase system transport equations coupled with the filtration rate and momentum exchange equations to predict simultaneously the effluent concentration and the pressure drop buildup, which considers the effect of deposition morphologies of oil droplets and suspended solids on filtration behaviors. The model hypothesizes that particle removal occurs through deep bed filtration mechanisms, and initial filtration coefficients are predicted by trajectory analysis without relying on experimental data. After that, we propose a method for predicting the filtration period, and analyze the effect of particle size and water temperature on the filtration process. Results show that the filtration process can be divided into two major stages—the main filtration zone migration, followed by the saturation front migration. With an S-shape increase in the effluent concentration, the pressure drop of the filter bed increases in a parabolic shape. When the diameter median of suspended solids is 5 μm, and the water temperature is 20°C, the filtration period was determined to be 24 hours to meet both water quality and maximum usable pressure drop of 20 kPa. With the increase in non-Brownian suspended solid size, the interception and gravitational forces increase the removal efficiency of suspended solids, which results in a slight decrease in the removal efficiency of oil droplets and an increase in the pressure drop of the filter bed. As the water temperature increases, the viscosity of the produced water decreases, and the oil droplets and suspended solids are more easily removed, but the pressure drop of the filter bed increases. In this work, we provide new ideas and methods to properly design, operate, and manage filters in a sustainable and energy-efficient way.
On Statistical Convergence of Set Sequences in Fuzzy Anti-normed Linear Space
Authors: Pandit Shailendra , Esi Ayhan 
Published: September 2023

Abstract
In this article, we have studied the fuzzy α− anti Wijsman convergence, fuzzy α−anti Wijsman statistical convergence, and fuzzy α−anti Hausdorrf statistical convergence where 0 < α < 1, of set sequences of non-empty closed sets in fuzzy anti-normed linear spaces (M, ψ, ⋄) with regard to the fuzzy anti norm(FAN) ψ. Furthermore, certain important theorems and examples based on the notion were presented.
Design and analysis of rehabilitation hand based on segmented multi-chamber actuator
Authors: Zheng Huadong , Bai Wei , Wang Caidong , Wang Xinjie , Liu Linxiao 
Published: September 2023

Abstract

The soft rehabilitation hand has become a research hotspot in the field of robotics due to its good environmental adaptability and coupling safety. To make the soft rehabilitation hand have a large degree of freedom and strong driving force, as well as being comfortable and lightweight to wear, this paper designs a segmented multi-chamber actuator soft rehabilitation glove based on the principle of bionics. The actuators of different finger types and bone segments, which are also various in shape and size, are assembled in parallel to realize diverse movement forms of fingers. The motion deformation mechanism of the rehabilitation hand is studied, and the driving effect of the soft finger is analyzed with the help of ABAQUS finite element analysis software. 3D printing technology and pouring molding technology were used to make segmented soft rehabilitation finger physical prototype. The accuracy of the simulation model was verified by comparison and analysis of simulation data and experimental data.
The effects of CPET-guided cardiac rehabilitation on exercise tolerance in older persons with CHD after PCI
Authors: Shen Tao , Wang Yuwei , Ren Chuan , Song Yanxin , Gao Wei , Liu Fen , Li Gang , Wei Zhimin , Wang Peng , Zhao Wei 
Published: September 2023

Abstract
Background: Prescribing appropriate exercise is an important means to improve the safety and efficacy of cardiac rehabilitation. Improper exercise may induce an increased cardiovascular risk in older persons with coronary heart disease. Cardiopulmonary exercise testing (CPET)-guided cardiac rehabilitation could be helpful for providing clinical evidence for cardiac rehabilitation therapy in older persons after percutaneous coronary intervention (PCI). Methods: We retrospectively included older persons who underwent PCI and cardiac rehabilitation based on CPET at the Cardiac Rehabilitation Center of XXX Hospital from January 2014 to December 2019. Patients' baseline and follow-up clinical data were collected. Results: A total of 403 older persons after PCI were included in the study. The mean age was 80.5±4.3. The mean follow-up time was 12±2 months. During the follow-up period, no significant exercise-related adverse events occurred, and the peak oxygen uptake (VO2peak) increased compared with baseline (15.5±3.8 ml/min/kg vs. 17.3±4.1 ml/min/kg). Among the 90 patients (22.2%) without exercise habits at baseline who started regular exercise during follow-up, the improvement in VO2peak was most significant, at 3.2±0.4 ml/min/kg. Conclusions: Cardiac rehabilitation based on CPET improved exercise habits and exercise tolerance in older persons with coronary heart disease after PCI.
Effect of microplastic particles on viability of the selected ciliated protozoa
Authors: Fyda Janusz , Budziak Martyna 
Published: September 2023

Abstract
Microplastics (MPs) due to their microsize, which overlaps with the typical food size of various aquatic organisms, can be ingested and move up the food chain, accumulating in the bodies of organisms at higher trophic levels. Few studies have focused on the uptake of MPs by ciliates, which are an important element of the microbial cycle. Three different ciliate species were used in the study: Blepharisma japonicum, Euplotes sp. and Spirostomum teres, and two types of polystyrene beads with a diameters of 1 and 2 µm in two concentrations (106 and 107 beads × mL− 1). The results of the experiments showed that microplastics have a variable, species-specific effect on the population growth rate of ciliates, which is directly dependent on their density in the environment (p < 0.01). It was also observed that the number of MPs ingested changed over time, depending on their density and size. On average, the highest number of ingested MPs (883.11 ± 521.47) was recorded after 60 min exposure to a low concentration of smaller beads in B. japonicum. The lowest number of beads was observed after 5 min exposure to a low concentration of larger beads in the same species. The rate of uptake of MPs by ciliate species was significantly dependent on their density, exposure time and size (p < 0.001). The highest clearance rate was observed in ciliates shortly after the start of the experiments in the environment with the lowest density of MPs.
The role of oral microbiota in the development of oral mucositis in pediatric oncology patients treated with antineoplastic drugs: A systematic review
Authors: Filetici Pierfrancesco , Gallottini Sofia Germana , Corvaglia Andrea , Amendolea Martina , Sangiovanni Roberta , Nicoletti Fabrizio , D’Addona Antonio , Dassatti Leonardo 
Published: September 2023

Abstract
Background
Oral mucositis as a consequence of chemotherapy in the pediatric oncology population is a highly prevalent complication and strongly affects both the quality of life and treatment possibilities of the patients. Etiopathological mechanisms carrying to its development are not fully understood. A possible role of oral disbiosis has previously been investigated with unclear conclusions. Aim of this systematic review was to assess the available evidence on the role of microbiota in the development of oral mucositis.
Methods
Systematic literature search was performed following PRISMA guidelines. Three electronic databases were searched up until April 2023. A following manual search included the reference lists of the included studies and reviews. Studies reporting microbiological and clinical data of pediatric patients treated by antineoplastic drugs were included.
Results
Thirteen studies met the inclusion criteria, reporting an average mucositis prevalence of 55%. Candida albicans infection was frequently observed in studies performing microbiological analysis on oral lesions, in contrast with the low rate detection of Herpes simplex viruses. Bacterial species such as coagulase-negative Staphylococcus aureus and Streptococcus viridans were more frequently detected on lesion sites. Studies reporting a quantitative analysis of the general flora did not show comparable results. Risk of bias assessment among studies was generally considered high or very high.
Conclusions
While the specific role of certain microbiological agents, such as Candida albicans, was frequently reported among studies, data regarding the general dynamics of oral microbiota in the development of oral mucositis are lacking in the current literature and more studies are needed to provide the knowledge required in order to improve protocols for the prevention and treatment of this threatening complication.
Automatic Segmentation of Ameloblastoma on CT Images using Deep Learning with Limited Data
Authors: Xu Liang , Qiu Kaixi , Li Kaiwang , Ying Ge , Huang Xiaohong , Zhu Xiaofeng 
Published: September 2023

Abstract
Background
Ameloblastoma, a common benign tumor found in the jaw bone, necessitates accurate localization and segmentation for effective diagnosis and treatment. However, the traditional manual segmentation method is plagued with inefficiencies and drawbacks. Hence, the implementation of an AI-based automatic segmentation approach is crucial to enhance clinical diagnosis and treatment procedures.
Methods
We collected CT images from 79 patients diagnosed with ameloblastoma and employed a deep learning neural network model for training and testing purposes. Specifically, we utilized the Mask RCNN neural network structure and implemented image preprocessing and enhancement techniques. During the testing phase, cross-validation methods were employed for evaluation, and the experimental results were verified using an external validation set. Finally, we obtained an additional dataset comprising 200 CT images of ameloblastoma from a different dental center to evaluate the model's generalization performance.
Results
During extensive testing and evaluation, our model successfully demonstrated the capability to automatically segment ameloblastoma. The DICE index achieved an impressive value of 0.874. Moreover, when the IoU threshold ranged from 0.5 to 0.95, the model's AP was 0.741. For a specific IoU threshold of 0.5, the model achieved an AP of 0.914, and for another IoU threshold of 0.75, the AP was 0.826. Our validation using external data confirms the model's strong generalization performance.
Conclusion
In this study, we successfully developed a neural network model based on deep learning that effectively performs automatic segmentation of ameloblastoma. The proposed method offers notable advantages in terms of efficiency, accuracy, and speed, rendering it a promising tool for clinical diagnosis and treatment.