Pre-existing Data Research Articles

δ18O variability in guanaco bone bioapatite in Southern Patagonia: Implications for paleoecological and paleoenvironmental studies

The guanaco (Lama guanicoe) is the largest and the most widely distributed ungulate in South America since the Pleistocene and constituted the main prey for hunter-gatherers in Southern Patagonia (Argentina) in the past. An isomorphic relationship has been suggested between the mobility of these animals and that of human groups that inhabited the region, which presents altitudinal differences. On the one hand, we seek to understand the spatial dynamics of guanaco populations and their interaction with hunter-gatherer societies. On the other hand, to evaluate the utility of archaeological herbivores' values as paleoenvironmental proxies that allow addressing the environmental variations during the Holocene in the region. We present the results of the analysis of δ18O in bioapatite of Lama guanicoe bone specimens from the area located in the central-western area of the province of Santa Cruz, between 70 and 72 degrees west longitude. We analyzed 41 samples. 22 of them correspond to modern individuals, while the remaining 19 were recovered from Holocene archaeological sites. The carbonate-phosphate and estimated water equations will be used to compare with pre-existing data of δ18O in the waters of the region. Results showed that the mean value of δ18O of the pooled samples was −6.5 ‰ ± 1 ‰. Even though some differences were detected, both, between archaeological vs. modern and between highlands vs. lowlands samples, no statistically significant differences were obtained in either case. In general terms, the data respond to what was expected regarding the complex nature of the water intake behaviors of these animals. The data presented in this paper constitutes a first approximation to the expected values of δ18O for guanacos in the region, its relationship with the hydrological cycle and human populations.

The bank lending behaviour: Does non-performing loans matter? Evidence from the top-ten banks in the Arab world

This essay examines the third increase in non-performing loans (NPLs) in the Arab World, which the COVID-19 epidemic may have contributed to. This increase follows two previous waves that occurred in 1990 and after 2008. The primary aim is to analyze bank lending behavior, particularly examining the influence of firm-specific determinants on banks' lending activities and the impact of NPLs on this behavior. Utilizing secondary data from 2016 to 2020, this research focuses on the top ten national banks in the Arab region. The methodology incorporates panel data derived from audited financial statements and employs OLS regression (Pooled) for analysis. The findings reveal a significant negative impact of NPLs and capital adequacy ratios on bank lending behavior, while bank size and deposit growth positively influence lending activities. Additionally, the study notes an insignificant relationship between profitability, equity as a percentage of total assets, and lending behavior. These results provide practical insights for banking sector decision-makers, emphasizing the management of NPLs through maintaining adequate capital, enhancing deposits, and increasing bank assets. From a social perspective, the study suggests that banks should prioritize lending to investors likely to fulfil their obligations, potentially limiting credit availability for smaller entities and individuals without guarantees. This approach aims to mitigate the risks associated with NPLs. This work's originality lies in its concentration on a condensed sample that accounts for more than 70% of the banking resources in the Arab region, making it a significant contribution to applied research in this area that stands out for its reliance on pre-existing data.

Geotechnical information system employs spatial analysis to utilize information gathered from Cone Penetration Testing (CPT)

Surakarta has diverse structures, including malls, shopping centers, hotels, offices, markets, hospitals, colleges, and schools. However, the Regional Government lacks a comprehensive data information system about the Cone Penetration Test (CPT). Such a system benefits investors seeking to develop new infrastructure in Surakarta. In order to tackle this problem, a research study was carried out to develop an Information System based on CPT data regarding the depth of hard soil throughout the city. The investigation analyzed pre-existing CPT data, its compilation, and cartographic representation. However, the arbitrary allocation of CPT data presents a challenge. Results of the study indicate that the most predominant depth of compacted soil qc 250 kg/cm2 in Surakarta is 3-5 meters below the surface. Moreover, comparing the depth of CPT soil in the field with GIS at multiple observation points indicates findings that mostly conform to GIS predictions and those of in situ tests. Combining CPT data with ArcGIS software has been a highly successful approach in identifying projects and providing robust geotechnical information.

Data-driven control of oscillator networks with population-level measurement.

Controlling complex networks of nonlinear limit-cycle oscillators is an important problem pertinent to various applications in engineering and natural sciences. While in recent years the control of oscillator populations with comprehensive biophysical models or simplified models, e.g., phase models, has seen notable advances, learning appropriate controls directly from data without prior model assumptions or pre-existing data remains a challenging and less developed area of research. In this paper, we address this problem by leveraging the network's current dynamics to iteratively learn an appropriate control online without constructing a global model of the system. We illustrate through a range of numerical simulations that the proposed technique can effectively regulate synchrony in various oscillator networks after a small number of trials using only one input and one noisy population-level output measurement. We provide a theoretical analysis of our approach, illustrate its robustness to system variations, and compare its performance with existing model-based and data-driven approaches.

Heat generating impact on radiative nanofluid flow via exponential expanding surface with convective conditions: Mesh independence examination

The current article aims to inspect existence of electrical field in magnetohydrodynamics stream of nanofluid toward nonlinear via various thicknesses of symmetric extended surface. This examination is distinctive in that it analyses influences of Joule heating, thermal radiation, and chemical reaction on heat and mass transport. Electric field and variable thickness phenomena are used to study thermophysical properties. Asymmetry technique is used to describe geometric model. Governed differential equations are changed over into dimensionless ordinary differential equations by applying similarity changes and solutions are obtained by bvp4c in MATLAB. Augmentation in velocity and temperature, together with suppression of concentration is caused by occurrence of electric field. Parameters of magnetized force, thermal radiation, and Eckert number are responsible for enhancing variations in temperature and thermal boundary layer thickness. These variations are reduced with rising Prandtl number and electric field. This research compares new findings with preexisting data in limited cases.

Development of a Tool to Measure Student Perceptions of Equity and Inclusion in Medical Schools

Creating an inclusive and equitable learning environment is a national priority. Nevertheless, data reflecting medical students' perception of the climate of equity and inclusion are limited. To develop and validate an instrument to measure students' perceptions of the climate of equity and inclusion in medical school using data collected annually by the Association of American Medical Colleges (AAMC). The Promoting Diversity, Group Inclusion, and Equity tool was developed in 3 stages. A Delphi panel of 9 members identified survey items from preexisting AAMC data sources. Exploratory and confirmatory factor analysis was performed on student responses to AAMC surveys to construct the tool, which underwent rigorous psychometric validation. Participants were undergraduate medical students at Liaison Committee on Medical Education-accredited medical schools in the US who completed the 2015 to 2019 AAMC Year 2 Questionnaire (Y2Q), the administrations of 2016 to 2020 AAMC Graduation Questionnaire (GQ), or both. Data were analyzed from August 2020 to November 2023. Student race and ethnicity, sex, sexual orientation, and socioeconomic status. Development and psychometric validation of the tool, including construct validity, internal consistency, and criterion validity. Delphi panel members identified 146 survey items from the Y2Q and GQ reflecting students' perception of the climate of equity and inclusion, and responses to these survey items were obtained from 54 906 students for the Y2Q cohort (median [IQR] age, 24 [23-26] years; 29 208 [52.75%] were female, 11 389 [20.57%] were Asian, 4089 [7.39%] were multiracial, and 33 373 [60.28%] were White) and 61 998 for the GQ cohort (median [IQR] age, 27 [26-28] years; 30 793 [49.67%] were female, 13 049 [21.05%] were Asian, 4136 [6.67%] were multiracial, and 38 215 [61.64%] were White). Exploratory and confirmatory factor analyses of student responses identified 8 factors for the Y2Q model (faculty role modeling; student empowerment; student fellowship; cultural humility; faculty support for students; fostering a collaborative and safe environment; discrimination: race, ethnicity, and gender; and discrimination: sexual orientation) and 5 factors for the GQ model (faculty role modeling; student empowerment; faculty support for students; discrimination: race, ethnicity, and gender; and discrimination: sexual orientation). Confirmatory factor analysis indicated acceptable model fit (root mean square error of approximation of 0.05 [Y2Q] and 0.06 [GQ] and comparative fit indices of 0.95 [Y2Q] and 0.94 [GQ]). Cronbach α for individual factors demonstrated internal consistency ranging from 0.69 to 0.92 (Y2Q) and 0.76 to 0.95 (GQ). This study found that the new tool is a reliable and psychometrically valid measure of medical students' perceptions of equity and inclusion in the learning environment.

Pacific seafloor in the 40–52 Myr old portion of the Molokai to Murray corridor

A detailed study of the character of 40–52 Myr old Northeast Pacific seafloor illustrates how volcanism that occurs outside a spreading center axial zone contributes to the morphology of a region. A compilation of new and pre-existing multibeam sonar data forms the basis of our study, which lies within the spreading corridor bounded by Molokai and Murray fracture zones and does not include a major volcanic chain. The broad structure is consistent with constant crustal thickness and lithospheric cooling with age, and our analyses focus on the deviations from this ‘reference’ model. We find three types of volcanic features where typical abyssal hill fabric is generally not observed: 1) volcanic ridges that have a length of 30–120 km and a height of 1–2 km; 2) moderate seamounts that have a diameter of 8–15 km and a height of several 100's m; and 3) fields of very small seamounts, which extend several 10's km and are more common at ∼25% coverage than in other Pacific regions away from major volcanic chains. Gravity analysis suggests that the volcanic ridges and a few of the moderate seamounts are associated with local crustal thickening whereas the fields of very small seamounts do not display a distinct mass anomaly. Quantifying the distribution of past volcanism in this section of the Pacific plate during its evolution after initial accretion helps illustrate the degree of off-axis magmatism. Although we interpret the volcanic ridges as presently inactive, their formation on lithosphere older than at least a few Myr likely had an impact on the local seismic structure.

Decision regret, and other mental health outcomes, following fertility preservation in the transgender individual compared to the cisgender woman.

This study aimed to (1) determine differences in depression, anxiety, body image, quality-of-life (QOL), and decision regret scale (DRS) scores in transgender individuals undergoing fertility preservation (FP) compared to those who decline and (2) determine if DRS score following FP varies between transgender individuals and cisgender women. Sixteen transgender birth-assigned (BA) females and 13 BA males, undergoing FP consultation at an academic center between January 2016 and November 2019, were compared to each other and cisgender cohorts with pre-existing data: 201 women undergoing elective oocyte cryopreservation (EOC) between 2012 and 2016 and 44 women with cancer undergoing FP between 1993 and 2007. Outcomes included demographics; validated scales for depression, anxiety, body image, QOL (see below) in the trans cohort; DRS score in all three cohorts. Of 29 transgender individuals participating, 10 BA females (62%) and 12 BA males (92%) underwent FP. Beck Depression Inventory II, Hospital Anxiety and Depression Scale, Body Image Scale for Transsexuals, Satisfaction with Life Scale, Short Form Health Survey-36, and DRS scores were not significantly different between trans individuals who underwent FP and those who declined. On univariate modeling, regret was significantly lower in transpeople undergoing FP compared to those who did not (OR 0.118, p = 0.03). BA female and BA male transpatients undergoing FP reported DRS median scores 5 (mean 9) and 7.5 (mean 15), respectively, both were not significantly different from cisgender women (p = 0.97, p = 0.25) nor from each other (p = 0.43). Depression, anxiety, body image, and QOL, in a group of individuals presenting for FP consultation, appear similar between transpeople undergoing FP and not, while regret is significantly lower in those choosing FP. FP is an option for transgender individuals without significant differences in regret compared to cisgender women.

The digital divide between primary and secondary care: An analysis using SARS-CoV-2 hospital admissions.

Using data from two ED. departments of 773 patients admitted with SARS-CoV-2, ICD-10 codes derived from the General Practitioner - Summary Care Record (GP-SCR) and Emergency Department (ED.) records were analysed for code discrepancies and whether this related to increased mortality. The average number of ICD-10 codes in both GP-SCR and ED. records was higher for patients who died than patients who survived (all p < .0001). Pre-existing GP digital data provides a better prediction of mortality than data collected manually during admission clerking in the ED. Up to 78.47% of GP-SCR codes were missed in the ED. records and up to 45.49% of the ED. record codes were not in the GP-SCR. A subset of missed ICD-10 codes were identified as being able to predict outcome; a trend towards increasing death rate as the proportion of missed codes increases. Initiatives to make the GP-SCR available to the wider healthcare community should improve patient care and reduce bias during development of machine learning based algorithms.

Microwave spectra of the leading and trailing hemispheres of Iapetus

The leading hemisphere of Saturn’s synchronous moon Iapetus is covered by a low-albedo material, contrasting with its bright trailing hemisphere. This dichotomy is also apparent in radar and microwave radiometry observations, which are sensitive to the properties of the near subsurface. To better understand the regional properties of Iapetus and their variations with depth, we assemble the microwave spectra of its leading and trailing hemispheres. Pre-existing data are combined with new millimetric and centimetric observations acquired with the IRAM 30-meter dish, IRAM NOEMA interferometer, and VLA interferometer. These data, interpreted with the help of a model with vertically uniform thermal properties, reveal complex variations in structure and/or composition with depth on the leading side. Meanwhile, the trailing side emissivity is found to be especially low at all observed frequencies, indicating efficient scattering processes on subsurface structures, as observed on Saturn’s other icy moons. We also report the first observations of Saturn’s retrograde moon Phoebe at these frequencies, which has an emissivity higher than that of the trailing hemisphere of Iapetus and similar to its dark leading side, consistent with the theory that Phoebe is the source of the dark material on Iapetus.

Contemporary definitions of infant growth failure and neurodevelopmental and behavioral outcomes in extremely premature infants at two years of age

BackgroundAssociations of 2-year neurodevelopmental and behavioral outcomes with growth trajectories of preterm infants are unknown.MethodsThis secondary analysis of a preterm cohort examined in-hospital and discharge to 2-year changes in anthropometric z-scores. Two-year follow-up included Bayley Scales of Infant Development (BSID-III) and Child Behavior Checklist.ResultsAmong 590 infants, adjusted in-hospital growth was not associated with any BSID-III subscale. Occipitofrontal circumference (OFC) growth failure (GF) in-hospital was associated with increased adjusted odds of attention problems (aOR 1.65 [1.03, 2.65]), aggressive behavior (aOR 2.34 [1.12, 4.89]), and attention-deficit-hyperactivity symptoms (aOR 1.86 [1.05, 3.30]). Infants with OFC GF at 2 years had lower adjusted BSID-III language scores (−4.0 [−8.0, −0.1]), increased odds of attention problems (aOR 2.29 [1.11, 4.74]), aggressive behavior (aOR 3.09 [1.00, 9.56]), and externalizing problems (aOR 3.01 [1.07, 8.45]) compared to normal OFC growth cohort.ConclusionInfants with OFC GF are at risk for neurodevelopmental and behavioral impairment.Clinical trial registrationThis study is a secondary analysis of pre-existing data from the PENUT Trial Registration: NCT01378273.

Reputation-surveillance model of mate guarding: community size and religious veiling

Abstract The mate guarding theory of conservative clothing posits that veiling reduces women's physical allure and sexual attractiveness, thereby diminishing men's attraction towards them and deterring potential rivals for a woman's partner. This theory argues that the importance of veiling is influenced by ecological factors in a way that it is of higher importance to control women's sexuality in harsher environments to secure paternal investment. A prediction of this theory is that the importance of veiling should be influenced by community size, where individuals’ reputations, specifically men's, might have different weightings, and their perceived sense of controlling a partner's activity may differ. Using pre-existing data from seven countries encompassing over 9000 individuals, the current study explored the association of town size and importance of veiling for women. Results showed a U-shaped relationship where in small towns and large cities, individuals, specifically men, give more importance to the veiling of women. This finding not only has multiple implications in terms of the effect of community size on male policing behaviours of women and sexual restrictions, but it also might point to a wider relationship regarding the association of community size and moral values.

CLINICAL AND FUNCTIONAL EVALUATION OF WRISTS AND HANDS OF SPINAL CORD INJURED PATIENTS.

The inability of the spinal cord to propagate sensory and motor stimuli as a result of the disruption of the nerve tracts is called spinal cord injury. This study analyzes clinically and radiologically the hands and wrists of spinal cord injured patients, evaluating their motor and sensitive functionality, in order to determine if these patients are more likely to develop degenerative alterations. 14 patients (8 paraplegics and 6 tetraplegics) were evaluated, undergoing anamnesis and clinical examination - a scale of muscular strength (MRC - Medical Research Council) and the amplitude measurement of the movement with a manual goniometer (ROM), were used for objective evaluation - and x-ray exams. The results were compared with pre-existing data from other studies. When asked, only one of the 14 observed patients complained about constant wrist pain, described as level 3 (weak to moderate), based on the visual analog scale (VAS). The motor evaluation, MRC and ROM divided the group of patients into two subgroups: paraplegic and tetraplegic patients. The x-ray analysis showed, based on Kellgren and Lawrence classification, that all exam images fit grades 1 or 2 of osteoarthritis and osteoarthrosis. In conclusion, spinal cord injured patients showed none or minimal clinical and radiological signs of osteoarthritis on hands or wrists. Overall, the hands and wrists of spinal cord-injured patients behave similarly to noninjured patients. Level of Evidence III; Retrospective Comparative Study.

Approaches to Enhancing Semi-Supervised Learning using Process Data Augmentation via Self-Labeling and Generative Adversarial Networks

Augmentation of limited data with additional new data has been of major importance in fields where available data is scarce or expensive to acquire, and this is achieved via either the generation of new synthetic data or the labelling of pre-existing unlabelled data. Data generation using generative adversarial networks (GANs) and their variants have been widely reported to produce useful synthetic data. Self-labeling of unlabelled data has also been successfully implemented to provide labels to augment the training set of limited datasets. In this work, we explore these approaches for improving the new data quality (either generated or self-labeled) for regression and classification problems using various experiments with a specific focus on froth flotation data. Our work proposes a combination of regressor and classifier networks with shared network layers both for generation of new data and self-labeling of unlabeled data. We show that this approach provides superior performance in comparison to just using a classifier network.

Body Mass Index and Blood Pressure Profile of Newly Enrolled Health Sciences Students in a Medical University of Karachi, Pakistan

Objectives: To measure the Body Mass Index (BMI) and Blood pressure (BP) of newly enrolled undergraduate students in a medical university in Karachi, Pakistan, and to assess any association between BMI and BP levels among them. Methods: A cross-sectional study was conducted on pre-existing three-year data of 1403 students. The age, gender, BMI, and BP were recorded. The BMI of students was classified according to the Asian cutoff and BP was categorized using the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure (JNC) classification. Data was analyzed using SPSS version 24. Descriptive statistics were used to present quantitative and qualitative variables. The association was measured using the Chi-square test of significance. A p-value of &lt; 0.05 was taken as significant. Results: Total n= 1403 students with a mean age of 19 + 1.4 years students were enrolled including 397 (28.3%) males and 1006 (71.7%) females. A total of 667 (47.5%) students had a normal weight while 216 (15.4%) students were underweight, and 512 (36.5%) were either overweight or obese. Mean systolic BP was 111.42 + 10.7 mmHg and mean diastolic BP was 73.45 + 7.96 mmHg. Most students had normal systolic BP 901 (64.2%) while 501 (35.7%) had prehypertension or stage- I or II hypertension (HTN). The majority of the students had normal diastolic BP 1357 (96.7%) and 45 (3.3%) had stage- I or II HTN. There was a significant association between BMI and BP (0.0001). Conclusion: A significant number of the students are either under or overweight. There is a significant relationship between BMI and BP levels.

Assessment of Municipal and Industrial Wastewater Impact on Yamuna River Water Quality in Delhi

Delhi's Yamuna River serves as a notable illustration of an ecologically compromised system that has undergone a transition into a conduit for sewage due to pervasive pollution and escalating anthropogenic influences. Delhi, being the primary contributor to pollution, is responsible for over 70% of the total pollutant load in the Yamuna. The city's drainage systems discharge a substantial Biological Oxygen Demand load into the river daily, resulting in severe pollution. This research utilizes pre-existing data to examine diverse factors, evaluating the quality of water at distinct observation locations along the Yamuna. The utilization of correlation analysis aids in recognizing connections among elements influencing the pollution of river water. The outcomes of the correlation analysis disclose a notable link between COD-BOD factors, whereas the connections among alternative factors like BOD-DO, BOD-pH, COD-DO, COD-pH, and DOpH range from moderate to negligible. The majority of observed parameters exceed hazardous levels deemed acceptable for river water utilization. The evaluation of Sewage Treatment Plants highlights the imperative to augment capacity in terms of treatment, storage, reactivation of closed plants, and efficient operation to meet the growing demand for fresh water. Additionally, there is a pressing need to generate demand for wastewater in diverse urban sectors.

Metoda ANFIS za klasifikaciju EEG signala pri zamišljanju pokreta različitih zglobova istog ekstremiteta

Introduction: The experimental area of brain-computer interfaces (BCIs) is expanding to include movement actions, which play a crucial part in deciphering cognitive processes. Without the need for any kind of exterior stimulation, motor imagining (MI) can be used as a powerful model for braincomputer interfaces (BCIs). A natural method of operating exterior devices is to imagine moving various joints in the same arm. These envisioned motions have similar spatial images in the motor brain, making it difficult to differentiate MI of various joints of the same leg based on EEG data. Method: A pre-existing data collection of 25 participants was utilized in this study. The participants visualized using their right limbs to carry out three different activities: visualize yourself manipulating your right hand, visualize bending your right arm, and close your eyes while you relax. To assign categories to these impulses, we turned to the adaptive neuro-fuzzy reasoning system. Results: The average level of accuracy was 90%. Conclusion: The findings demonstrate that this technique is crucial for correctly categorizing EEG data. The data collection used in this investigation consists of EEG measurements of the same limb used in muscular imaging. The new categorization method will be applied to these signals to draw conclusions.

Assessment of knowledge, attitude, and behaviors of undergraduate medical students about sedentary lifestyle and lifestyle modifications – A facility based descriptive study

Abstract: INTRODUCTION: A sedentary lifestyle has become very common in the medical student leading to obesity. MBBS training period of 5½ years is extensive and very challenging. To cope with time and course curriculum, medical students adapt to multiple unhealthy lifestyle arrays. Many scientific articles have reported that medical students develop numerous health diseases over due to their unbalanced schedules and routines. With limited preexisting data on lifestyle patterns of medical students, this study was planned to assess the knowledge, attitude, and behaviors of 1st year undergraduate medical students about sedentary lifestyle and lifestyle modifications at Jawaharlal Nehru Medical College, KAHER, Belagavi, Karnataka state, India. METHODOLOGY: This is a facility-based descriptive study done among 200 first-year medical undergraduate students in the Department of Physiology, Jawaharlal Nehru Medical College, KLE Academy of Higher Education and Research, Belagavi. A predesigned structured questionnaire was circulated by Google Forms and responses were coded and entered into a Microsoft Excel sheet. The data analysis was done using percentages (%). Ethical clearance was obtained from the institutional ethical committee for human’s subject’s research of the medical college. RESULTS: Among 200 medical students, 192 (96%) of them responded to the questionnaire. About 174 (87%) of the students were practicing physical activity, about 52 (26%) of them did it five times per week, 70 (35%) did three times a week, and 50 (25%) did only once a week, whereas 26 (13%) of the students did not perform physical activity at all. During free time, the students had varied behavior about 59 (29.6%) of students spent time in one or another form of physical activity, 44 (21.8%) enjoyed music, 45 (22.3%) were active in social networking, 23 (11.4%) liked reading and creativity, and 29 (14.5%) of them did not respond to this question. About 110 (54.7%) strongly agreed to include training modules on the prevention of lifestyle disorders in undergraduate medical curriculum. CONCLUSION: More than half of the students told that 60 min of moderate-to-vigorous activity should be done regularly. Nearly two-thirds of them knew about the prevalence of obesity and listed the diseases caused by lifestyle diseases. Majority of the students practiced physical activity and knew about lifestyle diseases and were able to identify sedentary behavior. Nearly half of them told that a training module on the prevention of lifestyle diseases is required. There is an utmost important need to include a component of physical fitness in the undergraduate medical curriculum. This will help medical students to decrease stress and improve mental health.

Characteristic Attribute Organization System (CAOS): Identifying Classification Rules Based on Phylogenetically Organized Sequences.

Classification is a technique that labels subjects based on the characteristics of the data. It often includes using prior learned information from preexisting data drawn from the same distribution or data type to make informed decisions per each given subject. The method presented here, the Characteristic Attribute Organization System (CAOS), uses a character-based approach to molecular sequence classification. Using a set of aligned sequences (either nucleotide or amino acid) and a maximum parsimony tree, CAOS will generate classification rules for the sequences based on tree structure and provide more interpretable results than other classification or sequence analysis protocols. The code is accessible at https://github.com/JuliaHealth/CAOS.jl/ .

Identification of Advantages and Limitations of Current Risk Assessment and Hazard Analysis Methods when Applied on Autonomous Agricultural Machineries

Highlights The three main types of risk assessment and hazard analysis techniques applied on autonomous agricultural machines are: (1) Informal Group Analysis; (2) Hazard Analysis and Risk Assessment (HARA); and (3) Failure Mode and Effects Analysis (FMEA). Replicability is the main advantage of FMEA and HARA, while cost effectiveness is the main advantage of Informal Group Analysis. Subjectivity and the requirement for prior knowledge (data) are the main weaknesses of FMEA, HARA, and Informal Group Analysis when applied to novel and revolutionary autonomous agricultural machines. Abstract. In the last ten years, the development of automated agricultural machinery has seen noteworthy advancements. Nevertheless, the successful commercialization of these technologies depends critically on their ability to operate safely. This study evaluated the advantages and limitations of current risk assessment and hazard analysis methods currently used to ensure the safety of autonomous agricultural machines. An online survey containing 18 questions was distributed to 711 participants identified as potential individuals who are currently working or have worked on autonomous agricultural machines to determine the type and frequency of risk assessment and hazard analysis methods applied on autonomous agricultural machines, examine the advantages and limitations of each method, and investigate the perceived effectiveness of each method. Frequency analysis was used to determine the most and least utilized risk assessment and hazard analysis methods. The advantages and limitations of each risk assessment and hazard analysis approach were compared. Descriptive statistics (counts, means, medians, percent) and frequency analysis of the variables were used. The three main types of risk assessment and hazard analysis techniques applied to autonomous agricultural machines. The methods are (a) Informal Group Analysis (e.g., Brainstorming), (b) Hazard Analysis and Risk Assessment (HARA), and (c) Failure Mode and Effects Analysis (FMEA). Replicability is perceived as the main advantage of FMEA and HARA, while cost-effectiveness is the main advantage of Informal Group Analysis. The need to have pre-existing data of the autonomous agricultural machine at hand to be able to perform risk assessment and subjectivity are the main limitations of FMEA, HARA, and Informal Group Analysis dealing with novel and revolutionary autonomous agricultural machines. Industry experts do not believe that the risk assessment and hazard analysis procedures now used are reliable and efficient enough to guarantee the safety of autonomous agricultural tractors. This study reveals important information about the current state of risk assessment and hazard analysis methods in the context of autonomous agricultural machinery. This knowledge can inform future research, policy development, and industry practices to ensure the safety of autonomous agricultural machines. Keywords: Agricultural machine, Autonomous, FMEA, HARA, Hazard analysis, Informal Group Analysis, Risk assessment, Safety, Survey.