Estimation of Position and Size of a Contaminant in Aluminum Casting Using a Thin-Film Magnetic Sensor

Advanced manufacturing processes require an in-line full inspection system. A nondestructive inspection system able to detect a contaminant such as tool chipping was utilized for the purpose of detecting a defective product as well as damaged machine tools used to fabricate the product. In a previous study, a system able to detect magnetic tool steel chipping in conductive material such as aluminum was developed and tested. In this study, a method of position and size estimation for magnetic chipping was investigated and is described. An experimental confirmation of the proposed method was also carried out using an actual prototype system.

Association between organ donation awareness and willingness among Saudi university students

Background: As the global incidence of end-stage organ failure increases, the gap between organ donors and recipients continues to widen. This study was conducted to determine the association between organ donation awareness and organ donation willingness among students of a Saudi university.Design and methods: This analytical cross-sectional study was conducted in King Faisal University, Al-Ahsa, Saudi Arabia. Multi-stage stratified random sampling was used to select the required 723 sample size. Estimation of proportion of students who were aware about organ donation and those who were willing to donate their organs was performed using EpiInfo© Version 7. Association between organ donation awareness and willingness was determined using multivariate logistic regression.Results: Nearly 98% of the participants were aware that organ donation saves lives (95% CI: 96.27%-98.53%); 84.09% were aware that Islam allows organ donation (95% CI: 81.25%-86.58%); 64.87% were aware that organ donation is successfully done in Saudi Arabia (95% CI: 61.32%-68.26%); 32.64% were aware that the government gives incentives to the family of an organ donor (95% CI: 29.32%-36.14%). Over half (56.71%) of the students (95% CI: 53.07 - 60.28%) expressed willingness to donate their organs. Positive association was found between awareness on the position of Islam on organ donation (OR=2.7023, p<0.0001) and awareness of that organ donation can be successfully performed in Saudi Arabia (OR=1.9447, p=0.0001).Conclusion: Awareness that Islam allows organ donation and awareness that organ donation is successfully done in Saudi Arabia increased the students’ willingness to donate.

Evaluating Moderating Effect of Growth Need Intent on Relationship between Job Characteristics and Job Satisfaction amongst Garments Industry Workers in Pakistan

Purpose: The purpose of this research is to analyze the correlation between the job characteristics and satisfaction among production workers in the garments sector assembly line and also to examine the moderating impact of growth need intent on both variables. The five job characteristics were employed in this research. Design/Methodology/Approach: This research was carried out in seven garment factories in Lahore. Data has been collected from production workers of different departments; cutting, sewing, pattern making, washing, pressing, packaging, and quality checking of randomly selected factories. A structured questionnaire was used for data collection. Considering the sample size estimation, the ratio has not to be below 1:5. (Hair, Black, Babin & Anderson, 2010) and 125 have been selected by a convenient method of sampling. Smart PLS has been used as a statistical tool for data processing and testing the hypothesis. Findings: The research suggests two important findings. Firstly, the job characteristics significantly affect job satisfaction. Secondly, it shows that the relationship between job characteristics and satisfaction is significantly moderated by growth need intent. Implications/Originality/Value: This research will add value to the existing knowledge base and serve as a guideline for HR policymakers in the textile & garments industry to recognize the needs for the development of their workers.

Estimation of aggregate size of red blood cell by introducing reference power spectrum measured for hemispherical ultrafine wire

Noninvasive measurement of the degree of red blood cell (RBC) aggregation is useful for evaluating blood properties. In the present paper, we proposed a method to estimate the size of RBC aggregates without using the power spectrum of the posterior wall by introducing a reference scattering spectrum. The reference power spectra were calculated using the power spectrum measured for an ultrafine wire with a hemispherical tip. They were applied to the size estimation of microparticles simulating RBC aggregates. The estimated sizes were close to the true values, which shows that the calculated reference power spectra were suitable for accurate size estimation. The proposed method was also applied to in vivo measurements, and the estimated sizes between at rest and in RBCs aggregated by avascularization were successfully differentiated. This demonstrates that the proposed method will be useful for estimating the size of RBC aggregates.

From Coastal to Montane Forest Ecosystems, Using Drones for Multi-Species Research in the Tropics

Biodiversity monitoring is crucial in tackling defaunation in the Anthropocene, particularly in tropical ecosystems. However, field surveys are often limited by habitat complexity, logistical constraints, financing and detectability. Hence, leveraging drones technology for species monitoring is required to overcome the caveats of conventional surveys. We investigated prospective methods for wildlife monitoring using drones in four ecosystems. We surveyed waterbird populations in Pulau Rambut, a community of ungulates in Baluran and endemic non-human primates in Gunung Halimun-Salak, Indonesia in 2021 using a DJI Matrice 300 RTK and DJI Mavic 2 Enterprise Dual with additional thermal sensors. We then, consecutively, implemented two survey methods at three sites to compare the efficacy of drones against traditional ground survey methods for each species. The results show that drone surveys provide advantages over ground surveys, including precise size estimation, less disturbance and broader area coverage. Moreover, heat signatures helped to detect species which were not easily spotted in the radiometric imagery, while the detailed radiometric imagery allowed for species identification. Our research also demonstrates that machine learning approaches show a relatively high performance in species detection. Our approaches prove promising for wildlife surveys using drones in different ecosystems in tropical forests.

Estimation of Maximum Hail Diameters from FY-4A Satellite Data with a Machine Learning Method

The magnitude of damage caused by hail depends on its size; however, direct observation or indirect estimation of hail size remains a significant challenge. One primary reason for estimations by proxy, such as through remote sensing methods, is that empirical relationships or statistical models established in one region may not apply to other areas. This study employs a machine learning method to build a hail size estimation model without assuming relations in advance. It uses FY-4A AGRI data to provide cloud-top information and ERA5 data to add vertical environment information. Before training the model, we conducted a principal component analysis (PCA) to analyze the highly influential factors on hail sizes. A total of 18 features, composed of four groups, namely brightness temperature (BT), the difference in BT (BTD), thermodynamics, and dynamics groups, were chosen from 29 original features. Dynamic and BTD features show superior performance in identifying large hail. Although the selected features are more closely correlated to hail sizes than unselected ones, the relationships are complicated and nonlinear. As a result, a two-layer regression back propagation neural network (BPNN) model with powerful fitting ability is trained with selected features to predict maximum hail diameter (MHD). The linear fitting R2 between predicted and observed MHDs is 0.52 on the test set, which signifies that our model performs well compared with other hail size estimation models. We also examine the model concerning all three hail cases in Shanghai, China, between 2019 and 2021. The model attained more satisfactory results than the radar-based maximum estimated hail size (MEHS) method, which overestimates the MHDs, thus further supporting the operational applications of our model.

Rasprostranjenost i najmanja veličina populacije euroazijskog risa (Lynx lynx) u Hrvatskoj u razdoblju 2018.–2020.

Scientific data on distribution and abundance of endangered species are the foundation for their effective conservation and management. In this paper, we present results of the first scientifically – based estimation of lynx population size in Croatia. The goal of the study was to determine the area of lynx distribution and to estimate the minimum size of lynx population in Croatia in the period 2018 - 2020. To determine lynx distribution, 902 signs of lynx presence were collected in the period from the beginning of May 2018 until the end of April 2020. Out of those, 92.8% of lynx observations were categorized as C1, 2.8% as C2 and 4.4% as C3. Permanent lynx presence was confirmed in Primorsko – Goranska and Ličko – Senjska county, in southern part of Karlovac county and north-eastern part of Zadar county on the total surface of 7200 km2. For the minimum population size estimation, 804 camera trap photographs led to identification of 89 – 108 adult lynxes. Among 108 identified individuals there were 29 females, 22 males, while for 7 animals the sex was not determined. During the two reproductive seasons, we photographed 44 cubs in 25 litters. Future important steps in lynx population monitoring are correcting the deficiencies identified in this study and implementation of methodology that will allow us to use spatial capture recapture models for estimation of lynx abundance in Croatia.

Genomics Confirm an Alarming Status of the Genetic Diversity of Belgian Red and Belgian White Red Cattle

Genetic diversity is increasingly important for researchers and society. Small and local populations deserve more attention especially, as they may harbor important characteristics. Moreover, small populations are at greater risk and their genetic management is often more challenging. Likewise, European red cattle populations are threatened, as they are outcompeted by more specialized cattle breeds. In this study, we investigate the genetic diversity of two local Belgian red cattle breeds: Belgian Red and Belgian White Red cattle. A total of 270 animals were genotyped via medium density SNP arrays. Genetic diversity was assessed using runs of homozygosity screening, effective population size estimation and Fst analyses. Genomic inbreeding coefficients based on runs of homozygosity were estimated at 7.0% for Belgian Red and 6.1% for Belgian White Red cattle, and both populations had a low effective population size (68 and 86, respectively). PCA, Fst and admixture analyses revealed the relationship to 52 other international breeds, where they were closest related to some Belgian, French, Scandinavian and Dutch breeds. Moreover, Fst analyses revealed for Belgian Red cattle a signature of selection on BTA6, adjacent to the KIT gene. This study gains important knowledge on the genetic diversity of these two small local red cattle breeds, and will aid in their (genetic) management.