Miracle-dz/UniFAR-FTUs huggingface dataset:
Application and Future Prospects of Computational Human Models in Conjunction with Monte Carlo Simulations in Radiation Dosimetry

: In the field of radiation dosimetry research, the combination of computer-based human models and Monte Carlo simulation methods has proven to be indispensable and enables a differentiated and detailed approach to studying radiation exposure and its effects. This article examines in depth the application of radiation dosimetry to computer-aided human models combined with Monte Carlo simulations in assessing ionizing radiation doses and illustrates its critical role in this field. This article systematically analyses three main techniques for assessing ionizing radiation dose: direct measurement, phantom model measurement and the advanced method using computer-aided human models with Monte Carlo simulations, highlighting the notable advantages of the latter method. In addition, this article introduces a variety of software tools and discusses the basic principles and wide-ranging applications of computational human models based on Monte Carlo simulations, highlighting their adaptability and effectiveness in this area. Finally, the paper provides a visionary outlook on the evolving landscape and future possibilities of integrating computer-based human models with Monte Carlo simulation methods for radiation dose estimation and predicts significant advances in the field.
Lower Output Voltage Harmonics With Optimum Switching Angles of Single PV-Source Based Reduced Switch Multilevel Inverter Using BWO Algorithm

This paper presents a technique of harmonic minimization from output voltage waveform of a reduced switch Multilevel Inverter (MLI) through an efficient bio inspired metaheuristic algorithm called Black widow optimization (BWO). The proposed reduced switch 13- level MLI scheme uses a single Photovoltaic (PV) source which can be suitable for grid integration. The proposed BWO algorithm minimizes the Total Harmonic Distortion (THD) of output voltage with low operational time compared to other existing nature based algorithms considering large searching area. The weighted THD (WTHD) of the output voltage is also minimized in order to reduce the effect of lower order harmonics from the output voltage in a greater extent. The convergence rate and level of accuracy of BWO algorithm is compared with two different bio inspired algorithms for justification. The MLI operation is carried out with fundamental frequency, minimizing the switching stress while lowering the power loss compared to PWM or Sinusoidal PWM switching schemes. A single PV panel with multi winding flyback converter is used for medium voltage application through reduced switch MLI, serving the purpose of both isolation and reduction of energy sources. Simulation and experimental analysis are carried out with online control technique using a three phase 13-level reduced MLI to validate the proposed concept on a practical system.
Production of Fuel-Based Carbon Footprint Distribution Map Using Spatial Interpolation Methods Based on GIS

The Earth is a complex system where living and non-living elements coexist in a delicate balance. Climate change is the primary factor responsible for the degradation of this system over time. The far-reaching consequences of climate change impact various aspects of our lives, including the physical environment, urban settings, human activities, economy, technology, agriculture, food production, access to clean water, and public health, all of which are widely acknowledged. Human-induced greenhouse gas emissions in these areas significantly trigger global climate change. Hence, addressing and mitigating the environmental damage from these emissions and the interconnected climate change phenomena is imperative. This situation is where the concept of "carbon footprint" gains prominence in assessing the extent of this damage. Carbon footprint serves as an essential measure in managing and curbing climate change. This study focused on controlling and mitigating carbon emissions, one of the primary greenhouse gasses responsible for climate change, by implementing spatial interpolation techniques based on Geographic Information Systems (GIS). The investigation targeted the Beşirli neighborhood in the Ortahisar district of Trabzon province. Data concerning electricity and natural gas usage were acquired from relevant institutions to perform carbon footprint calculations. Subsequently, carbon footprint calculations were conducted utilizing the acquired data within the specified region. The resulting outputs were systematically organized, integrated into the GIS environment, and linked to their respective geographical locations. Eventually, region-specific carbon footprint distribution maps were generated using selected spatial interpolation methods. These maps enabled a spatial observation of points exhibiting variability in terms of carbon emissions, thereby highlighting the carbon footprints evident in the region. The ultimate goal of this endeavor is to propose practical measures for minimizing the adverse environmental impacts by suggesting strategies to reduce and prevent carbon footprints associated with carbon emissions in the relevant areas.
Development of real-time reference evapotranspiration at the regional scale using satellite-based observations

ABSTRACT Real-time data of reference evapotranspiration (ET0) at different space-time scales are essential to regional agricultural drought assessment, water accounting at the watershed to basin scale, and provide irrigation advisory to farmers. Here, we present a data-fusion approach that integrates satellite-based insolation product (8 km) from an Indian geostationary satellite (Kalpana-1) sensor (VHRR; Very High Resolution Radiometer) and high-resolution (~ 5 km) short-range weather forecast into an FAO56 model based on the classical Penman–Monteith (P-M) formulation. Five year (2009–2013) mean monthly estimates from the daily ET0 product over the Indian landmass were found to vary between 10 and 350 mm. It increased from January to May (70–350 mm), followed by a decrease to reach the lowest in November (10–140 mm), thus typically showing unimodal distribution. The comparison of daily space-based and station-based estimates (at six ground stations) produced a root mean square deviation (RMSD) ranging from 21% to 38% for 977 paired data sets with the correlation coefficient (r) varying from 0.32 to 0.82. The error was reduced from 25% to 10% with an increase in ‘r’ from 0.43 to 0.98 for daily to 10 day summation period. Spatial grid-to-grid comparison of monthly ET0 estimates with Global Data Assimilation System (GDAS) potential evapotranspiration (PET) showed RMSD within a range of 1.4–18.4% for most of the months, except for two. Further ET0 analysis over normal and drought years showed that it could be used for comprehensive drought assessment with other existing indicators.
Analysis Of The Influence Of Clinical Pathway In Hospitals On Length Of Stay: A Scoping Review

Clinical pathway is a management tool used in healthcare to coordinate patient care efficiently, thereby reducing the length of stay required by patients in hospitals. The purpose of this study was to determine the effect of Clinical Pathway in hospitals on Length of Stay. This study was a scoping review using the PRISMA diagram. Article search was conducted based on the eligibility criteria of the PICO Model: P: Hospital Patients, I: Clinical Pathway, C: -, O: Length of Stay. The articles used were from 4 databases, namely: Google Scholar, Research Gate, PubMed, and Elsevier. With keywords including "Clinical pathway" AND "Length of Stay" AND "hospital". The implementation of clinical pathway is one of the strategies that can be used to reduce patient length of stay. Clinical pathway can help improve efficiency, quality, and compliance with healthcare standards. Based on the results of the study, the researchers recommend that effective socialization and training be conducted to improve the understanding and compliance of healthcare professionals with clinical pathway, develop clinical pathway based on strong scientific evidence, and conduct periodic monitoring and evaluation to ensure the effectiveness and suitability of the clinical pathway implemented.
Testing the Tropical Niche Conservatism Hypothesis: Climatic Niche Evolution of Escallonia Mutis ex L. F. (Escalloniaceae)

We assess the Tropical Niche Conservatism Hypothesis in the genus Escallonia in South America using phylogeny, paleoclimate estimation and current niche modelling. We tested four predictions: (1) the climatic condition where the ancestor of Escallonia grew is megathermal; (2) the temperate niche is a derived condition from tropical clades; (3) the most closely related species have a similar current climate niche (conservation of the phylogenetic niche); and (4) there is a range expansion from the northern Andes to high latitudes during warm times. Our phylogenetic hypothesis shows that Escallonia originated 52.17 ± 0.85 My, in the early Eocene, with an annual mean temperature of 13.8 °C and annual precipitation of 1081 mm, corresponding to a microthermal to mesothermal climate; the species of the northern and central tropical Andes would be the ancestral ones, and the temperate species evolved between 32 and 20 My in a microthermal climate. The predominant evolutionary models were Brownian and Ornstein–Uhlenbeck. There was phylogenetic signal in 7 of the 9 variables, indicating conservation of the climatic niche. Escallonia would have originated in the central and southern Andes and reached the other environments by dispersion.
Evaluation study of Lactobacillus acidophilus drying

Lactobacillus acidophilus is a type of probiotic Lactic Acid Bacteria (LAB) which produce more organic acids than other types of LAB. Organic acids produced by probiotics LAB can reduce pH and breaks several molecular bonds. They have the effects of functional foods. Lactobacillus acidophilus can be said as a probiotic if the amount in food products reaches a minimum of 107 CFU/mL. Encapsulation is a process of probiotics coating to maintain the viability in final products due to food processing. The aim of this study wasto determine the viability of encapsulated Lactobacillus acidophilus through freeze and spray drying methods with the same encapsulation material. The study was conducted using Randomized Block Design (RBD) with three replicates. The research was conducted in Padjadjaran University and Indonesian Education University during August to October 2018. The results showed that solvents with Pasteurized milk can produce better viability and yield than distilled water. Pasteurized milk can further increase the amount of Lactobacillus acidophilus because the main substrate of the bacteria is lactose. The viability of freeze dried culture was not significantly different from the viability of spray dried culture but the yield value is significantly different.
Ranking and determination of Iran status in the Middle East region on the development indicator of tourism during the development plan with Topsis method

Today, tourism economy has a crucial role as one of the main principles of commercial economy in global economy. Present study tries to answer to the question that regarding economic indicators of this industry what is Iran`s position compared to other middle-east countries? In addition, Iran`s position is investigated during economic development plans. To study Iran`s position, totally nine indicators are selected: 1) indicator of total participation of tourism industry in GDP, 2) total participation of tourism industry in jobs created, 3) internal travel and tourism expenses, 4) government expenses, 5) tourist export, 6) domestic consumption of tourist, 7) travel, tourism and commercial expenses, 8) holiday travel and tourism expenses and finally, 9) investment indicator in tourism sector. TOPSIS method is used to compose said indicators. Results show that during economic development plans, Iran has gained these ratings respectively: 6 rating in 1989, 6 rating in 1996, 4 rating in 2000, 5 rating in 2005, 5 rating in 2011, and 5 rating in 2013 among middle-east countries.
LSI Far Infrared Pedestrian Dataset

The database consists of FIR images collected from a vehicle driven in outdoors urban scenarios. Images were acquired with an Indigo Omega imager, with a resolution of 164x129 pixels, a grey-level scale of 14 bits, and focal length of 318 pixels. The camera was mounted on the exterior of the vehicle, to avoid infrared filtering of the windshield. Recorded images were manually annotated, where each pedestrian is labelled as a bounding box. To prevent bias introduced by border artifacts their height is subsequently upscaled by 5%. The pedestrians appear in an up-right position. The dataset is divided in two: (i) Classification dataset: positives and randomly sampled negatives with a fixed height-width ratio of (1/2) and rescaled to 64x32 pixels, and (ii) Detection Dataset: Original positive and negative images with annotations
Study on Fuzzy Catastrophe Risk Model Based on Fuzzy Theory

I n this paper, we analyzed the essential meaning of the catastrophe risk on the basis of many results that is the bottleneck of the catastrophe risk analysis is complex. One way to resolve or alleviate this problem is to analyze the risk from the viewpoint of fuzzy logic-fuzzy catastrophic risk (FCR) analysis. We propose the concept of synthetic effect, present its axiomatic foundation, and further establish a FCR model based on synthetic effect as well as the general solution model. Finally, we specify the model by considering catastrophe risk in Shanghai. The results indicate that the method is not only accommodates the existing fuzzy decision-making methods, but also successfully incorporates the decision preference into the optimization process. Therefore, the FCR model can be widely used in many fields such as complex systems optimization and decision-making.
Welcome to Eduardo Cazap, Editor-in-Chief, ecancer

Copyright: © the authors; licensee ecancermedicalscience. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http:// creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The rebirth of ecancer.org within the new charity ecancer Global Foundation is a timely moment for Eduardo Cazap, the distinguished medical oncologist from Argentina, to take control of the journal. And few folk are as global as he, having been president of UICC, among many other prestigious appointments!
Comparison of Deep Learning Models for Melody Generation.

Generative deep learning models have been proposed in various media fi elds, and their generative quality has been improving yearly. The quality of generative models in music generation has been improved, such as “ the number of examples of sound generation that deviate from music theory has been reduced ” and “ melodies that take context into account can be generated. ” However, it is di ffi cult to evaluate the “ quality of the generated results ” in the case of music generation. In this study, by implementing various generative deep learning models, we do not evaluate the quality of the generated results but rather make an objective comparison of each model.
Animated Movie Product to Train Ablution Practice

Background. This study aims to analyze the use of learning media at SDN 1 DANGDEUR and develop Capcut-based animated videos as an alternative to interesting learning media Purpose. The results of the initial analysis show that although the school has provided several learning media, the teachers tend to rely more on the blackboard and textbooks. Method. Learning media has an important role in facilitating the learning process and improving students' understanding. Therefore, this research encourages teachers to be more creative in using existing learning media. Results. , This research involves the stages of needs analysis, material content adaptation, learning media design, and Capcut-based animation video development. The results of this study show that the use of Capcut-based animated videos in learning has a significant effect on student learning achievement. Conclusion. There is a significant increase in students' average score after using this learning media
CHARACTERIZATION OF SOME AROMATIC AND MEDICINAL PLANTS SPECIES BASED ON UAV IMAGES

The study used imaging analysis to characterize several species of aromatic and medicinal plants. UAV images were taken on five aromatic and medicinal plants species, cultivated by SCDA Lovrin, Timis county, Romania. The biological material was represented by Lavandulua x intermedia (Lavandin), P1; Hyssopus officinalis L. , P2, P6; Origanum vulgare L. , P3; Thymus serpyllum L. , P4; Salvia officinalis L. , P5 (P1 to P6 species code in the article). The images were analyzed (four repetitions) and the values of the RGB color parameters were obtained. The ANOVA test confirmed the presence of variance and the safety of the data (F>F crit, p<0.001; Alpha=0.001). The correlation analysis highlighted positive and negative correlations of different intensity levels between RGB parameters and calculated ratios (R/G, R/B, G/R, G/B, B/R, B/G). The variation of G in relation to R was described by a polynomial equation of degree 3 (R2=0.956), and the variation of B in relation to R was described by a polynomial equation of degree 2 (R2=0.736). High variability was recorded in the case of parameter B (CVB=23.44534), plant P3 (Origanum vulgare L.), and low variability was recorded in the case of color parameter G (CVG=2.66030), plant P2 (Hyssopus officinalis L.). Based on PCA, the distribution diagram of plant species in relation to RGB color parameters and calculated ratios, as biplot, was obtained. PC1 explained 66.037% of variance, and PC2 explained 33.095% of variance in relation to RGB, and PC1 explained 58.923% of variance, and PC2 explained 36.46% of variance in relation to the calculated ratios. The cluster analysis facilitated the grouping of plant species (P1 to P6) based on similarity in relation to the RGB color parameter values (Coph.corr. = 0.959).
Efficient pollinators of threatened taxa, Sarpagandha (Rauvolfia serpentina) under North Indian conditions

An experiment was carried out to investigate the diversity, abundance and pollination efficiency of different insect visitors/pollinators of Rauvolfia serpentina (Sarpagandha) during 2014 and 2015. This experiment was conducted at Medicinal Section, Department of G and PB, CCSHAU, Hisar. Sarpagandha flowers attracted wide varieties of insects belonging to 4 orders, 10 families, 16 genera and 17 species. Among them nine belongs to order Lepidoptera, one Coleoptera, two Diptera, and two Hymenoptera. Lepidopterans came out to be the most abundant pollinators of this crop. Peak abundance of major insect pollinators was recorded at 1000h-1200h while minimum abundance was recorded at 0600h -0800h. Amegilla zonata had the highest number of loose pollen grains, 23.50 (‘000), sticking to its body followed by Papilio demoleus and Pieris sp. Papilio demoleus was reported as most efficient pollinator followed by Amegilla zonata and Pieris sp. based on the pollination index. Long proboscis of lepidopterans i.e., Papilio demoleus and small sized hymenopterans i.e., Amegilla zonata plays key role in pollination of Sarpagandha. Conservation of these pollinators in natural ecosystem is must for pollination of these threatened taxa.
The Open Journal of Occupational Therapy The Open Journal of Occupational Therapy

Abstract Effective occupational therapist and occupational therapy assistant partnerships are essential for the provision of quality patient care and satisfactory intraprofessional working relationships. Providing OT and OTA students with collaborative educational experiences can enhance students’ understanding and appreciation of each other’s roles, as well as set the groundwork for successful future work experiences. This project describes the experience of a graduate OT master’s degree program and an associate degree OTA program in a northeastern metropolitan city. Faculty from both programs worked together to design and implement a collaborative learning experience during the Covid-19 pandemic, conducted via Zoom. The purpose of this collaborative class was to develop a generic format for an OT and OTA joint class that can be easily adopted and embedded in any of the courses in the established curriculum. This article describes a pilot implementation of this OT and OTA class. For the majority of students, this was their first experience collaborating with their counterparts. Feedback was overwhelmingly positive via the qualitative content analysis, with many students indicating that they looked forward to more of these intraprofessional classes in future courses.
Interferometric Synthetic Aperture Radar Statistical Inference in Deformation Measurement and Geophysical Inversion: A review

With the rapid advancements in synthetic aperture radar (SAR) satellites and associated processing algorithms over recent decades, interferometric SAR (InSAR) has emerged as a routine method for monitoring large-scale ground deformation and interpreting geophysical processes. Statistical inference serves as a major component in InSAR technique developments and applications. This article provides an overview of InSAR deformation measurement and InSAR-constrained geophysical inversion, using a statistical inference point of view. Its objectives are to facilitate understanding of the method by addressing its underlying mathematical challenges. We begin by introducing the concept of statistical inference and the structure of our content organization framework. Next, we investigate the distinct concerns associated with statistical inference in InSAR deformation measurement and InSAR-constrained geophysical inversion. Finally, we propose several significant directions for future research. Table 1 includes abbreviations used throughout this article. Additionally, we highlight relevant resources, such as mathematical background, open source codes, and data repositories, in an appendix, which is available as supplementary material at https://doi.org/10.1109/MGRS.2023. 3344159.
IMPLEMENTASI DAN ANALISA JARINGAN SARAF TIRUAN DENGAN FEATURE NORMALIZATION DAN PRINCIPAL COMPONENT ANALYSIS UNTUK DIGIT CLASSIFIER

Digit classifier yang dikembangkan, digunakan untuk mengklasifikasikan angka dari tulisantangan. Sudah banyak sekali digit classifier yang dikembangkan dengan berbagai algoritmamachine learning, salah satu yang populer dan terus berkembang adalah jaringan saraf tiruan.Dengan motivasi tersebut, penulis juga membangun digit classifier menggunakan jaringan saraftiruan yang dipadukan dengan teknik optimisasi. Jenis arsitektur jaringan saraf tiruan yang akandigunakan adalah feedforward dan back propagation. Teknik optimisasi feature normalization danprincipal component analysis (PCA) juga akan digunakan untuk meningkatkan performa model.Set data yang digunakan untuk melatih model merupakan data Mixed National Institute ofStandards and Technology (MNIST). Dengan memadukan jaringan saraf tiruan dan teknik-teknikoptimisasi tersebut diharapkan dapat meningkatkan performa dan akurasi untukmengklasifikasikan angka serta memberikan pemahaman baru bagi penulis.