Largest Category Research Articles

Investigating Runway Incursion Incidents at United States Airports

According to the Federal Aviation Administration (FAA), the number of runway incursions is increasing. Over the last two decades, the number of runway incursions at U.S. airports has increased from 987 in 2002 to 25,036 in 2020. Runway incursions are a major threat to aviation safety, causing major delays and financial consequences for airlines, as well as injury or death through incidents such as aircraft collisions. The FAA promotes the implementation of runway safety technology, infrastructure, procedural methods, alterations to airport layouts, and training practices to reduce the frequency of runway incursions. In this paper, the relationship between airport geometry factors, mitigating technologies, and the number of runway incursions at large hub airports in the United States was investigated using a random effects Poisson model for analyses of panel data. Airport operations data from the FAA Air Traffic Activity System, runway incursion data from the FAA Aviation Safety Information Analysis and Sharing System from 2002 to 2020, and airport geometry data created using airport geometry features from the FAA airport diagrams were collected. Thirty large hub airports with FAA-installed mitigating technologies were investigated. The model identified significant variables that correlate with runway incursions for large hub airport categories defined by the National Plan of Integrated Airport Systems (NPIAS). The model results indicate that airports with significant numbers of runway-to-runway intersection points increase runway incursion rates and mitigating technologies Runway Status Lights (RWSLs) and Airport Surface Detection Equipment, Model X (ASDE-X), can help reduce runway incursions at severity levels A and B.

Emerging and legacy perfluoroalkyl and polyfluoroalkyl substances (PFAS) in surface water around three international airports in China

Perfluoroalkyl and polyfluoroalkyl substances (PFAS) are a large category of crucial environmental contaminants of global concerns. There are limited data on PFAS in surface water around international airports in China. The present study investigated the concentrations, distributions, and sources of emerging and legacy PFAS in surface waters around Beijing Capital International Airport (BC), Shanghai Pudong International Airport (SP), and Guangzhou Baiyun International Airport (GB) in China. Twenty-seven target compounds were quantified. The Σ27PFAS concentrations ranged from 19.0 to 62.8 ng/L (mean 36.1 ng/L) in BC, 25.6–342 ng/L (mean 76.0 ng/L) in SP, 7.35–72.7 ng/L (mean 21.6 ng/L) in GB. The dominant compound was perfluorooctanoic acid (PFOA), which accounted for an average of 27% (5%–65%) of the Σ27PFAS concentrations. The alternatives with –C6F12- group had detection frequencies ranging from 72% to 100%. The partition coefficient results indicate that the longer chain PFAS (C > 8) tend to be more distributed in the particle phase. Fifty suspect and nontarget PFAS were identified. In GB, 44 PFAS were identified, more than SP of 39 and BC of 38. An ultra short-chain (C = 2) precursor, N-methylperfluoroethanesulfonamido acetic acid (MeFEtSAA), was identified and semi-quantified. Domestic wastewater discharges might be the main sources around BC, while industrial and aviation activities might be the main sources around SP and GB.

Exploring objective versus subjective social ties using entrepreneurs’ gmail data

It is intuitively appealing and common in the literature to describe social ties as one large category that represents multiple constructs which have similar relations across operationalizations. However, that approach does not capture the nuance in the literature and might obscure notable differences between subjective and objective network tie measures, and how those differences extend to relations with venture-level outcomes. Drawing upon novel objective measures of network ties derived from analyses of entrepreneurs’ Gmail data, we offer an empirical assessment of subjective social ties relative to objective social ties. In examining how those assessments relate to multiple metrics of venture performance, we look at both subjective and objective measures. We find that objective network measures predict overall subjective (but not objective) venture performance at an average of r = .31 (for network size) and r = .29 (for network engagement). We delve into the implications of our work, and discuss how future research can progress more effectively and efficiently with an eye towards the practical usefulness of our findings for entrepreneurs and entrepreneurship service organizations.

Meta-Analysis of the Effect of the Application of the Problem-Based Learning Model on the Mathematical Problemsolving Ability of Students in Mathematics Learning

Students' problemsolving abilities can be improved in one way, namely by choosing the right mathematics learning model. One learning model that can be used is the problembased learning model. The aim of this research is to re-analyze the influence of the problembased learning model on students' mathematical problemsolving abilities by reviewing, summarizing data and analyzing several research results that have been published on Google Scholar as many as 14 articles using statistical methods. The type of research in this article is meta-analysis research. The research steps include data collection, coding, calculating the increase in problem solving abilities and effect size, and drawing conclusions. Based on the research results, the average effect size is 2.02 in the very large category. Based on the average effect size, it can be concluded that the problembased learning model influences students' mathematical problemsolving abilities.

Fuels reduction can directly improve spotted owl foraging habitat in the Sierra Nevada

Wildfire has been an important force in shaping biological diversity in forests of western North America. Patterns of reburning helped to maintain heterogenous landscapes with low tree densities that naturally limited the extent of severe stand-replacing fires. However, anthropogenic impacts over the past two centuries have dramatically altered fire activity and its ecological function, creating conditions that promote large and intense fires with no historical analog. Fuels reduction treatments represent proven methods to mitigate extreme fire events, but there is controversy over their potential effects to sensitive wildlife species. The California spotted owl (Strix occidentalis occidentalis) is a forest species that evolved under a frequent-fire regime. Controversy over how spotted owls may be impacted by fuels reduction is one of numerous contributing factors that has limited the pace and scale of implementation. To examine the relationships between spotted owls and fuels reduction treatments, we studied breeding season nocturnal foraging habitat selection related to fuel structural metrics of 159 GPS-tagged California spotted owls across the Sierra Nevada bioregion. Spotted owls selected for higher canopy base height, lower ladder fuel density, and lower canopy bulk density, which represent synergies between fuels reduction treatments and owl space use. Spotted owls also selected for higher surface fuels and higher canopy layer counts, representing potential trade-offs between fuels reduction goals and spotted owl space use. We overlaid the probability of space use by foraging spotted owls with relative stand density index (SDI), a measure of forest resilience, to classify Sierra Nevada landscapes into four groups: low management priority (low owl use/high forest resilience), fuels reduction priority (low owl use/low forest resilience), potential conflict zones (high owl use/low forest resilience), and habitat retention priority (high owl use/high forest resilience). Fuels reduction priority (34.4%) was the largest category, suggesting that potential impacts of fuels reduction on spotted owl foraging habitat may be less widespread in the Sierra Nevada than previously believed. Our results suggest that fuels reduction treatments, especially those focused on mutually beneficial goals such as increasing canopy base height, reducing ladder fuels, and reducing canopy bulk density may directly improve spotted owl foraging habitat while also mitigating the effects of large and severe wildfires on forest species and forest ecosystems.

Exploration of Argumentation and Scientific Reasoning Ability in Phenomenon-Based Argument-Driven Inquiry Learning in Newton's Law Material

The ability of argumentation and scientific reasoning is part of scientific literacy which is a requirement for learning science. Students get knowledge according to the understanding of scientists, which is important for students to have, especially in Newton's law material, but learning in the classroom currently has not developed argumentation and scientific reasoning skills properly. This study used a mixed method design with an embedded experimental design carried out offline. This research design was used in order to obtain an in-depth picture of students' argumentation and scientific reasoning abilities. The results showed that students' argumentation and scientific reasoning abilities increased significantly after being given the phenomenon-based Argument-Driven Inquiry (ADI) learning model. This learning has a moderate effect on argumentation skills and a very large one on students' scientific reasoning. Even though students' argumentation abilities have increased significantly, on average students still have difficulty in associating a phenomenon with the appropriate Newton's Laws. Scientific reasoning students also experience positive changes. This is evidenced by the increase in post-test scores and effect sizes which are in the very large category

CHARACTERISTICS OF ADULT PULMONARY TUBERCULOSIS PATIENTS UNDERGOING HOSPITALIZATION AT SONDOSIA REGIONAL HOSPITAL, BIMA REGENCY PERIOD JANUARY - JUNE 2023

Pulmonary tuberculosis (TBC) is a disease caused by an aerobic germ, Mycobacterium tuberculosis, which can live mainly in the lungs and various other organs of the body. The type of research is quantitative descriptive. The population in this study was 53 patients of Pulmonary TBC patients who underwent hospitalization at Sondosia Hospital. Sampling in this study used a total sampling technique where the study used the entire population into a research sample, so that the number of samples in this study was 53 people. This research was conducted at Sondosia Hospital, Bima Regency in January - June 2023. The results of this study showed that patients with the most gender were male 66% and female 34%. Based on age, the most age category is the age of >60 years, which is 43.3%,. Based on education, the highest level of education is elementary school level 34%. Based on occupacy, the largest category was working as a farmer 35.8%. Symptoms of TBC disease experienced by patients, most experienced cough as much as 100%, those who experienced shortness of breath was 56.6%, patients who experienced fever was 17%, who experienced night sweats 22.6% while those who experienced weight loss was 11.3%. Based on disease status,it was found that 75.5% new cases, 13.2% dropped out and 11.3% relapsed. Based on comorbidities, type 2 diabetes mellitus was 13.2% and hypertension 11.3%. Based on smoking history, patients with a history of smoking as much as 50.9%. Based on the most nutritional status with normal nutritional status 79.2%.

Regarding the Use of Finite Element Modeling for Propulsion System Sizing in V.T.O.L. Drones

At the moment, VTOL drones have proven their efficiency in several areas, for this reason, they have become indispensable tools for a large category of applications. This paper presents aspects related to the dimensioning stage of the propulsion system of a drone based on finite element modeling, to establish the traction force necessary to ensure sustentation.

Fiscal Policy and Resilience of the Tourism Industry Against the COVID-19 Pandemic

The tourism sector is encountering a global crisis as a consequence of the COVID-19 pandemic. This article aimed to identify and analyze the implementation and impact of fiscal policy on the resilience and sustainability of tourism industry businesses in Indonesia amid the COVID-19 pandemic. An exploratory descriptive qualitative method was used in this research through in-depth interviews with tourism sector business actors in Yogyakarta City, Sleman Regency, Bantul Regency, and Magelang Regency on the implementation of fiscal policy of tax relief for relevant tourism business during the pandemic. The results of the research identified the impact of implementing fiscal policy on business resilience in the tourism sector which is more befitting for medium and large business categories, whilemicro and small businesses could only take advantage of fiscal policy in the form of tax relief, which according to participants is transparent, easy to implement, and does not have a detrimental impact on future. This research contributes to theory, practice, and policy by providing an overview of the impact of environmental factors on the sustainability of tourism sector businesses, the government's response to the crisis, the impact of fiscal policy implementation on the resilience of tourism sector businesses, and input for the government in making future policy.

Functional (Re)Development of SYNTAX Score II 2020: Predictive Performance and Risk Assessment.

The present study investigates the prognostic value of the Syntax Score II 2020 corrected for flow-limiting lesions and its ability to better address treatment by benefit prediction among patients with left main or multivessel disease. We analyzed 1274 patients from the HALE-BOPP cohort and integrated the Syntax Score II 2020 with the result of the fractional flow reserve (FFR) evaluation. Absolute risk difference (ARD) between surgical and percutaneous revascularization was calculated for anatomic and functional Syntax Score II 2020 predicted mortality. The ARD allowed to stratify the population into two large categories: "coronary artery bypass graft (CABG) better" with ARD ≥ 4.5% and "CABG-percutaneous coronary intervention (PCI) equipoise" with ARD < 4.5%. The mean global anatomical Syntax Score was 15.5 ± 9.2, whereas the functional one was 9.5 ± 10 (p < 0.01). Using the anatomic Syntax Score II 2020, 881 patients had a CABG-PCI equipoise. This number increased to 1041 after considering only flow-limiting lesions by FFR (p < 0.001); therefore, 40% of CABG better patients were reclassified within the CABG-PCI equipoise category. Kaplan-Maier curves showed similar actual survival rates for patients originally with CABG-PCI equipoise and those reclassified, in both cases higher than those from CABG better patients (p < 0.01). The integration between Syntax Score II 2020 and physiology is feasible, and merging clinical, anatomic and functional data allows for better risk prediction and therapeutic guidance.

Using Digital Flashcards (DFs) as a Learning Media to Enhance Students’ Speaking Skill

The aim of this study was to investigated the effect of using Digital Flashcards (DFs) on improving junior high school students’ speaking skill. This study employed pre-experimental design method in one group pre-test and post-test design. The researcher gathered the data by providing pre-test and post-test which are formulated the sepaking test about describing person. The sample of this study was seventh grade of junior high school in Gresik. The test was tabulated and analyzed by using SPSS 23. The results of this study showed that the use of Digital Flashcards is effective to improve students’ speaking skill in junior high school. It was proven by the result of the data that there was a significant difference between the pre-test and post-test scores. The mean score was 38.15 in the pre-test and 49.57 in the post-test, thus the average found is in the large effect category (0.625). The results also showed significant progress among four criteria assessment by IELTS under investigation, pronunciation (0.629) and lexical resource (0.623) were the most noticebly increased after the treatment of Digital Flashcards. In conclusiom, the current study suggests the Digital Flashcards media can be applied towards junior high school level to improve students’ speaking skill.

Traffic Sign Detection Based on the Improved YOLOv5

With the advancement of intelligent driving technology, researchers are paying more and more attention to the identification of traffic signs. Although a detection method of traffic signs based on color or shape can achieve recognition of large categories of signs such as prohibitions and warnings, the recognition categories are few, and the accuracy is not high. A traffic sign detection algorithm based on color or shape is small in computation and good in real-time, but the color features are greatly affected by light and weather. For the questions raised above, this paper puts forward an improved YOLOv5 method. The method uses the SIoU loss function to take the place of the loss function in the YOLOv5 model, which optimizes the training model, and the convolutional block attention model (CBAM) is fused with the CSP1_3 model in YOLOv5 to form a new CSP1_3CBAM model, which enhances YOLOv5’s feature extraction ability and improves the accuracy regarding traffic signs. In addition, the ACONC is introduced as the activation function of YOLOv5, which promotes YOLOv5’s generalization ability through adaptive selection of activation by linear–nonlinear switching factors. The research results on the TT100k dataset show that the improved YOLOv5 precision rate increased from 73.2% to 81.9%, an increase of 8.7%; the recall rate increased from 74.2% to 77.2%, an increase of 3.0%; and the mAP increased from 75.7% to 81.9%, an increase of 6.2%. The FPS also increased from 26.88 to 30.42 frames per second. The same training was carried out on the GTSDB traffic sign dataset, and the mAP increased from 90.2% to 92.5%, which indicates that the algorithm has good generalization ability.

Farmers' perception of the ecosystem services provided by diurnal raptors in arid Rajasthan.

Farmers are the most important stakeholders in wildlife conservation in the agricultural landscape. Understanding the farmer's perceptions, attitude, behaviour, and knowledge toward conservation is critical in developing an effective conservation programme in human-dominated landscapes. We conducted semi-structured face-to-face interviews with 373 farmers to understand the farmer's perception of ecosystem services provided by diurnal raptors in the arid region of Rajasthan from July 2020 to February 2021 and from August 2021 to January 2022. We grouped ecosystem services and disservices into larger categories and estimated the correlation between them, finding that disservices are negatively correlated with benefits. Raptors were perceived as beneficial for their role in controlling rodents and pests, but negatively for poultry predation. In addition, we built a binomial generalised linear model with a logit function to better understand the factors that influence farmers' perceptions of raptors (positive or negative). We observed that males and females have different attitudes toward the ecosystem services provided by raptors. It is critical to understand social perceptions in order to conserve species that are rare on a global scale but may face negative perceptions on a local scale. Our study connects ecological information with socio-demographic factors, which can be useful in developing policy measures for raptor conservation.

Exploring Zero-Shot Semantic Segmentation with No Supervision Leakage

Zero-shot semantic segmentation (ZS3), the process of classifying unseen classes without explicit training samples, poses a significant challenge. Despite notable progress made by pre-trained vision-language models, they have a problem of “supervision leakage” in the unseen classes due to their large-scale pre-trained data. For example, CLIP is trained on 400M image–text pairs that contain large label space categories. So, it is not convincing for real “zero-shot” learning in machine learning. This paper introduces SwinZS3, an innovative framework that explores the “no-supervision-leakage” zero-shot semantic segmentation with an image encoder that is not pre-trained on the seen classes. SwinZS3 integrates the strengths of both visual and semantic embeddings within a unified joint embedding space. This approach unifies a transformer-based image encoder with a language encoder. A distinguishing feature of SwinZS3 is the implementation of four specialized loss functions in the training progress: cross-entropy loss, semantic-consistency loss, regression loss, and pixel-text score loss. These functions guide the optimization process based on dense semantic prototypes derived from the language encoder, making the encoder adept at recognizing unseen classes during inference without retraining. We evaluated SwinZS3 with standard ZS3 benchmarks, including PASCAL VOC and PASCAL Context. The outcomes affirm the effectiveness of our method, marking a new milestone in “no-supervison-leakage” ZS3 task performance.

Analysis of Major Selection Under the Background of Enrollment in Large Category

By using questionnaire survey and Logit regression analysis, this paper explores the influencing factors of students' major choice under the background of enrollment in large category, and draws the following conclusions: personal professional endowment, family, teacher guidance and major construction level have significant influence on students' major choice, and there are great differences between comprehensive universities and local professional universities. Some suggestions are put forward in shaping personal qualities and environment, strengthening professional construction, and expanding the space for professional selection.

Automatic Catfish Sorter and Counter Based on Weight Classification

Catfish is one of the main raw materials in the fisheries sector which also supports the Indonesian economy. However, manual sorting of catfish makes the weight of catfish not uniform when marketed. Therefore, tools and machines are needed that automatically sort catfish in large quantities, making it more effective and easier for catfish breeders to use. In this study the process of making the system was realized in 3 stages, namely needs analysis, implementation, and testing of tools. The purpose of this system is to be able to classify the weight of catfish in the large category with fish weighing &gt; 140 grams, medium with fish weighing 80-140 grams and small with fish weighing 20-80 grams. From the system test results, the average accuracy is 99.56. % and a precision of 98.75% for load cell sensor readings, while for E18 infrared sensor readings the results are always known, but data is not always sent and displayed on the LCD screen. Classification of fish categories carried out by the system has worked well, where the system is able to sort and count correctly 14 times out of 15 tests with an accuracy of 93%. The average computing time required for this tool is 3.67 seconds for 15 tests.

Medical Directors, Facilities, and Finances: Resource Deficiencies in Accredited Paramedic Programs

Background Initial paramedic education must have sufficient rigor and appropriate resources to prepare graduates to provide lifesaving prehospital care. Despite required national paramedic accreditation, there is substantial variability in paramedic pass rates that may be related to program infrastructure and clinical support. Our objective was to evaluate US paramedic program resources and identify common deficiencies that may affect program completion. Methods We conducted a cross-sectional mixed methods analysis of the 2018 Committee on Accreditation of Educational Programs for the Emergency Medical Services Professions annual report, focusing on program Resource Assessment Matrices (RAM). The RAM is a 360-degree evaluation completed by program personnel, advisory committee members, and currently enrolled students to identify program resource deficiencies affecting educational delivery. The analysis included all paramedic programs that reported graduating students in 2018. Resource deficiencies were categorized into ten categories: faculty, medical director, support personnel, curriculum, financial resources, facilities, clinical resources, field resources, learning resources, and physician interaction. Descriptive statistics of resource deficiency categories were conducted, followed by a thematic analysis of deficiencies to identify commonalities. Themes were generated from evaluating individual deficiencies, paired with program-reported analysis and action plans for each entry. Results Data from 626 programs were included (response rate = 100%), with 143 programs reporting at least one resource deficiency (23%). A total of 406 deficiencies were identified in the ten categories. The largest categories (n = 406) were medical director (14%), facilities (13%), financial resources (13%), support personnel (11%), and physician interaction (11%). The thematic analysis demonstrated that a lack of medical director engagement in educational activities, inadequate facility resources, and a lack of available financial resources affected the educational environment. Additionally, programs reported poor data collection due to program director turnover. Conclusion Resource deficiencies were frequent for programs graduating paramedic students in 2018. Common themes identified were a need for medical director engagement, facility problems, and financial resources. Considering the pivotal role of EMS physicians in prehospital care, a consistent theme throughout the analysis involved challenges with medical director and physician interactions. Future work is needed to determine best practices for paramedic programs to ensure adequate resource availability for initial paramedic education.

Assessment of the cultural-natural importance of the scenic spots from a network perspective

A scenic spot within a natural landscape is not only a spatial carrier of biodiversity but also an indispensable spatial element of culture. In the lower reaches of large river basins, natural conservation and cultural development are both important. Taking the scenic spots in the lower reach of the Yellow River as study objects, we used minimum cumulative resistance, circuit theory, and igraph package to build a cultural network, natural network and cultural-natural network to assess the importance of scenic spots based on connectivity. The scenic spots were grouped into four categories (based on the relative importance of habitat connectivity and tourism connectivity) and three optimization scenarios (including the cultural, natural, and cultural-natural approaches) were set to indicate the impact of population, resistance and publicity on the importance of scenic spots. We found that important nodes in each of the networks were clustered in different parts of the region. Only 2 of the 18 nodes belonged to the category in which habitat connectivity is not important and tourism connectivity is important, and 7 nodes belonged to the category in which habitat connectivity is not important and tourism connectivity is not important, which is the largest category. The cultural-natural optimization method and the natural optimization method are respectively the best in terms of the degree of the importance of the value of the optimization objects and the number of the importance of optimization objects. The network-based assessment method we provide can support landscape planning from a cultural-natural perspective and provide a potential ranking for landscape connectivity optimization that considers both ecological connectivity and social connectivity.

Implementation of socio-scientific issues learning to improve students critical thinking skills

This study aims to describe the implementation of socio-scientific issues learning, critical thinking skills, and student learning responses. This research is quantitative. This pre-experimental study used the One Group Pretest Post-test Design. The subjects in this study were 23 students of class VIII B at UNESA YDWP Laboratory Middle School. The instruments used were observation sheets of learning implementation, critical thinking skills test sheets, and response questionnaire sheets. Data analysis techniques on learning implementation sheets and response questionnaires were calculated based on the mode value, then on critical thinking skills using t-test analysis and effect size. The study results showed that learning socio-scientific issues can be carried out in very good categories. Students' critical thinking skills have increased as indicated by the acquisition of the t-test of critical thinking skills tcount &gt; ttable or 18.852 &gt; 2.074 with a significance level of 0.000 &lt;0.05, so H0 is rejected, and Ha is accepted. So, it shows a significant difference in value between the pretest and post-test scores. Calculating the effect size of critical thinking skills was also carried out with a value of 3.924 in the very large category so that socio-scientific issues learning effectively influenced critical thinking skills. The results of student responses agree on learning socio-scientific issues that are interesting, easy to understand, and useful for everyday life. Thus, there is an increase in students' critical thinking skills after applying socio-scientific issues learning.

“Why do people do sex?” an analysis of middle school students’ anonymous questions about sexual health

ABSTRACT Sexual health education should meet the needs of all students. One strategy educators can use to ensure instruction meets students’ needs is to encourage the submission of anonymous questions, allowing students to gain information without fear of instructor or peer reactions. We investigated anonymous questions submitted by middle school (7th-grade, ages 12-13) students during a sexual health education curriculum in Ohio, USA. Questions (n=893) were organised into 12 categories: reproductive anatomy (n=186), LGBTQ+ topics (n=130), sexual behaviour (n=120), class-related questions (n=99), pregnancy (n=78), slang (n=52), STIs (n=44), protection/birth control (n=33), relationships (n=19), consent (n=14), health services (n=9), abstinence (n=1), and unrelated questions/comments (n=108). After categorising questions, we conducted thematic analysis with the three largest categories (reproductive anatomy, LGBTQ+ topics, sexual behaviour). Results revealed students wanted to know about the normality of the processes and functions of their bodies. Students also expressed concern and had internalised social norms about LGBTQ+ topics. Student questions about sexual behaviour suggested they wanted to learn more about the purposes and processes of sex, e.g., how people have intercourse. Findings underscore the need for inclusive, comprehensive and medically accurate sexual health education for early adolescents. We discuss implications for student health/well-being, educator development, and school staff.