Miracle-dz/UniFAR-FTUs huggingface dataset:
A review of quadrotor control methods

Quadrotor play an increasingly important role in emergency rescue and other comparable missions. However, external disturbances such as wind gusts and turbulence have a great impact on the stability of quadrotor, which means the control system of the vehicle needs to have a strong capability of anti- disturbance. This paper discuss the latest research on quadrotor control methods, and analyzes their characteristics and application. Traditional methods are improved and enhanced in order to attain better control performance. Meanwhile, artificial intelligence and hybrid control methods have garnered extensive research in the realm of quadrotor.
Modeling and parameter identification for agricultural machines

A series of technical and social aspects have led the pressure to increase energy efficiency and reduce the level of environmental impact in agricultural production. Crop producers and equipment manufacturers have identified computerized assistance in operation management as an indispensable tool to optimize agricultural processes. A central place is occupied in this regard by the so called digital twins, computer models of a specific instance of an object or system, which are also capable of exchanging data with the physical counterpart and updating their state accordingly. The core of a digital twin is given by the digital mock‐up, or offline digital twin, that is the computer model of the system's physics. The goal of this work is to present the development of an offline digital twin for a novel gantry‐tractor type autonomous agricultural machine. The peculiarity of this system resides in its until now scarcely adopted mechanical design, and its ability to perform a range of processes by attaching different modules to its frame. After a brief introduction into the characteristics of a gantry‐type tractor and its role in the context of precision autonomous agriculture and controlled traffic farming, different components of the machine and dynamic phenomena are separately investigated and mathematically modeled. Particular focus is placed thereby on the study of the vehicle's longitudinal dynamics. Based on the software implementation of the mathematical models, the unknown parameters of the system model are estimated by means of nonlinear optimization techniques, using sensor data collected during field operation as the measurement reference. The accuracy of different estimation methods is then evaluated against experimental samples collected by sensors.
THE WAVE CLIMATE OF SOUTH-EAST AUSTRALIA AND FUTURE WAVE PROJECTION BY THE END OF 21ST CENTURY

In this study, high-resolution unstructured ocean wave datasets based on a third-generation wave model (WAVEWATCH III, WW3) were developed for south-east Australia. Through this study, we aim to understand the wave climate based on hindcast model datasets and develop future wave projections by the end of the 21st century.
Potential distribution of the critically endangered dragonfly Libellula angelina (Odonata: Libellulidae) under shared socio‐economic pathways

Libellula angelina is an endangered dragonfly species that is native to East Asia. Recently, their population has become severely reduced through habitat loss. To protect L. angelina populations, we need to understand which factors determine their distribution and how their potential habitats will change in the future. In this study, the habitat preference of L. angelina was identified through field surveys, and the potential distribution of L. angelina and the impact of integrated climate–land cover changes were simulated using the MaxEnt model. Furthermore, the wetland loss scenario was applied to areas where the current trend in wetland loss will continue in the future. The field survey identified that L. angelina prefers small inland wetlands: permanent freshwater, ponds; permanent rivers, ponds; irrigated land; and estuarine waters. From the MaxEnt results, altitude was the variable with the greatest contribution and distance from wetlands was the most unique variable. MaxEnt described the geographic pattern of occurrences under the current climate well, with few areas requiring any further survey. In the future projection, the potential habitat area was increased by up to 48.8% and 30.6% in the 2050s and 2080s, respectively. However, potential habitat loss was expected if wetlands continue to decline as they have done in the last 20 years. The wetland loss scenario resulted in potential habitat losses of 1.9%–2.3% and 4.5%–6.1% in the 2050s and 2080s, respectively. Therefore, to protect L. angelina populations we must minimize the loss of current populations, secure wetlands and strengthen the connectivity between wetlands.
ANALISIS PENERIMAAN APLIKASI MYPERTAMINA MENGGUNAKAN METODE TECHNOLOGY ACCEPTANCE MODEL (TAM)

In an effort to protect and maintain customer loyalty, PT Pertamina introduced a loyalty program called MyPertamina. This application allows customers to make non-cash transactions through LinkAja! Meanwhile, the government is currently testing official transactions for fuel oil (BBM), diesel and pertalite subsidies, through this program. The objective of this research is to recognize the determinants that influence the public's acceptance of the MyPertamina application. In this study, the Technology Acceptance Model (TAM) approach is utilized to gauge the extent to which users accept technology based on their behavior. There are four variables in TAM that are used, namely Perceived Usefulness, Perceived Ease of Use, Behavioral Intention to Use, and Actual System Use. As many as 160 respondents who are users of the MyPertamina application are the subject of this study, selected using the Lemeshow formula. The results showed that after the primary data was processed using the SPSS application, hypothesis testing was carried out using Structural Equation Modeling (SEM). In addition, Perceived Ease of Use also has a positive and significant effect on Behavioral Intention to Use and Actual System Use. However, there is no positive and significant effect between Behavioral Intention to Use and Actual System Use.
POTENTIAL APPLICATION OF MICROENCAPSULATION IN THE FOOD INDUSTRY.

Dayane de Melo Barros 1 , Erilane de Castro Lima Machado 2 , Danielle Feijó de Moura 1 , Maria Heloisa Moura de Oliveira 3 , Tamiris Alves Rocha 4 , Silvio Assis de Oliveira Ferreira 4 , Roberta de Albuquerque Bento da Fonte 2 and Ranilson de Souza Bezerra 5 . 1. Mestre em Saúde Humana e Meio Ambiente – Centro Acadêmico de Vitória, Universidade Federal de Pernambuco, CAV/UFPE – Pernambuco. 2. Doutora em Nutrição – Universidade Federal de Pernambuco – Pernambuco. 3. Discente de bacharelado em Nutrição – Centro Acadêmico de Vitória, Universidade Federal de Pernambuco, CAV/UFPEPernambuco. 4. Mestre em Bioquímica e Fisiologia – Universidade Federal de Pernambuco – Pernambuco. 5. Doutor em Ciências Biológicas – Universidade Federal de Pernambuco – Pernambuco. Manuscript Info Abstract . Manuscript History Received: 16 October 2018 Final Accepted: 18 November 2018 Published: December 2018
Independent COL17A1 Variants in Cats with Junctional Epidermolysis Bullosa

Epidermolysis bullosa (EB), characterized by defective adhesion of the epidermis to the dermis, is a heterogeneous disease with many subtypes in human patients and domestic animals. We investigated two unrelated cats with recurring erosions and ulcers on ear pinnae, oral mucosa, and paw pads that were suggestive of EB. Histopathology confirmed the diagnosis of EB in both cats. Case 1 was severe and had to be euthanized at 5 months of age. Case 2 had a milder course and was alive at 11 years of age at the time of writing. Whole genome sequencing of both affected cats revealed independent homozygous variants in COL17A1 encoding the collagen type XVII alpha 1 chain. Loss of function variants in COL17A1 lead to junctional epidermolysis bullosa (JEB) in human patients. The identified splice site variant in case 1, c.3019+1del, was predicted to lead to a complete deficiency in collagen type XVII. Case 2 had a splice region variant, c.769+5G>A. Assessment of the functional impact of this variant on the transcript level demonstrated partial aberrant splicing with residual expression of wildtype transcript. Thus, the molecular analyses provided a plausible explanation of the difference in clinical severity between the two cases and allowed the refinement of the diagnosis in the affected cats to JEB. This study highlights the complexity of EB in animals and contributes to a better understanding of the genotype-phenotype correlation in COL17A1-related JEB.
Translation Service Implementation in Cloud: Automation Trends in English Translation Industry

INTRODUCTION: The development of information technology has led to the renewal of teaching methods, and cloud translation combining offline and online learning has become a trend in higher education. OBJECTIVES: It is becoming increasingly apparent that the "surface issues" of blended learning are being addressed, especially the lack of consistency in online task development, which leads to inefficiencies in deep understanding. METHODS: Through literature research, the factors affecting task planning in cloud translation are analyzed, and a cloud computing task planning model is established based on task learning theory. RESULTS: The results show that task-based cloud translation can increase students' learning engagement and that targeted group task design is critical in improving students' interest and translation skills. CONCLUSION: Using complex task modeling can improve the academic level of translation students and increase their involvement in translation projects.
Measurement of the Dependence of the Hadron Production Fraction Ratios f_{s}/f_{u} and f_{d}/f_{u} on B Meson Kinematic Variables in Proton-Proton Collisions at sqrt[s]=13  TeV.

The dependence of the ratio between the B_{s}^{0} and B^{+} hadron production fractions, f_{s}/f_{u}, on the transverse momentum (p_{T}) and rapidity of the B mesons is studied using the decay channels B_{s}^{0}→J/ψϕ and B^{+}→J/ψK^{+}. The analysis uses a data sample of proton-proton collisions at a center-of-mass energy of 13 TeV, collected by the CMS experiment in 2018 and corresponding to an integrated luminosity of 61.6 fb^{-1}. The f_{s}/f_{u} ratio is observed to depend on the B p_{T} and to be consistent with becoming asymptotically constant at large p_{T}. No rapidity dependence is observed. The ratio of the B^{0} to B^{+} meson production fractions, f_{d}/f_{u}, is also measured, for the first time in proton-proton collisions, using the B^{0}→J/ψK^{*0} decay channel. The result is found to be within 1 standard deviation of unity and independent of p_{T} and rapidity, as expected from isospin invariance.
A Low-Profile Varactor-Tunable Bandpass Frequency Selective Surface With Angular Stability Property

A low-profile varactor-tunable bandpass frequency selective surface (FSS) with angular stability is presented in this article. The FSS comprises two metallic layers printed on the opposite sides of a thin substrate. The rotationally symmetrical meandered metal patch in each layer in combination with metallic vias is the feed network of the varactor diodes, which has been optimized to achieve miniaturization and obtain suitable coupling capacitance Cs. Moreover, the feed network is arranged to be rotationally symmetrical to ensure polarization independence. An equivalent circuit model and the synthesis procedure are provided to simplify the design of the FSS. The designed resonance frequency is tuned from 3 to 4.55 GHz when the bias voltage varies from 6 to 20 V. The thickness of the structure is 0.005 λ0, where λ0 represents the wavelength of the lowest resonance frequency. Furthermore, the effect of structural parameters on the angular stability of the FSS has been reported. The proposed FSS is angularly stable at 3–4.55 GHz for the incident angle up to 70° under both TE and TM waves. A prototype is manufactured, and the measured S-parameters under normal and oblique incidence verify the effectiveness of the proposed design.
Overcoming personal information protection challenges involving real-world data to support public health efforts in China

In the information age, real-world data-based evidence can help extrapolate and supplement data from randomized controlled trials, which can benefit clinical trials and drug development and improve public health decision-making. However, the legitimate use of real-world data in China is limited due to concerns over patient confidentiality. The use of personal information is a core element of data governance in public health. In China’s public health data governance, practical problems exist, such as balancing personal information protection and public value conflict. In 2021, China adopted the Personal Information Protection Law (PIPL) to provide a consistent legal framework for protecting personal information, including sensitive medical health data. Despite the PIPL offering critical legal safeguards for processing health data, further clarification is needed regarding specific issues, including the meaning of “separate consent,” cross-border data transfer requirements, and exceptions for scientific research. A shift in the law and regulatory framework is necessary to advance public health research further and realize the potential benefits of combining real-world evidence and digital health while respecting privacy in the technological and demographic change era.
Sorghum as a Model Crop for Drought Stress Tolerance

: Sorghum is one of the most significant C4 cereal crops grown in dry and semi-arid regions of the world. It is a major staple crop for millions of people in Sub-Saharan Africa and South Asia. Drought is an important constraint on agricultural production and productivity around the world. It has a significant impact on plant growth, development, and yields. Drought stress risks food security by having a substantial impact on sorghum growth and development, grain yields, and nutritional quality. Sorghum has become known as a drought-tolerant model crop when compared with many other crops. Its ability to withstand extreme environmental conditions makes it a feasible model crop for studying abiotic stress responses and developing stress-tolerant crops. Sorghum response and/or tolerance mechanisms include morphological, physiological, and molecular changes. Drought stress tolerance mechanisms in sorghum include drought escape, early flowering, stay-green, drought avoidance, leaf area, osmotic adjustment, stomata-mediated drought responses, cuticular wax production, root characteristics, and drought tolerance. Biotechnology and its advanced approaches, such as QTL, marker-assisted backcrossing, genetic engineering, and others, are used for screening drought-tolerant genotypes that can withstand drought stress. Therefore, focusing on the drought-tolerant genotypes will boost the speed of the sorghum breeding program, which will feed millions of people worldwide, particularly in Sub-Saharan Africa.
Reliability Evaluation of Wind Power Converter Under Fault-tolerant Control Scheme with Quantification of Temperature and Humidity Effects

Wind power converter (WPC) is a key part of a wind power unit which delivers electric energy to power grid. Because of a large number of semiconductors, WPC has a high failure rate. This paper proposes a method to accurately evalu‐ ate the reliability of WPC, which is crucial for the design and maintenance of wind turbines. Firstly, the index of effective tem‐ perature (ET) is presented to quantify the effects of tempera‐ ture and humidity on the semiconductor operation. A novel method is proposed to evaluate the lifetime and calculate the ag‐ ing failure rates of the semiconductors considering the fluctua‐ tions of ET. Secondly, the failure mode and effect analysis (FMEA) of WPC is investigated based on the topology and con‐ trol scheme. The conventional two-state reliability model of the WPC is extended to the multi-state reliability model where the partial working state under the fault-tolerant control scheme is allowed. Finally, a reliability evaluation framework is estab‐ lished to calculate the parameters of the WPC reliability model considering the variable failure rates and repair activities of semiconductors. Case studies are designed to verfify the pro‐ posed method using a practical wind turbine.
The Short-Timescale Behavior of Glacial Ice

Glaciers are often assumed to deform only at slow (i.e., glacial) rates. However, with the advent of high rate geodetic observations of ice motion, many of the intricacies of glacial deformation on hourly and daily timescales have been observed and quantified. This thesis explores two such short timescale processes: the tidal perturbation of ice stream motion and the catastrophic drainage of supraglacial meltwater lakes. Our investigation into the transmission length-scale of a tidal load represents the first study to explore the daily tidal influence on ice stream motion using three-dimensional models. Our results demonstrate both that the implicit assumptions made in the standard two-dimensional flow-line models are inherently incorrect for many ice streams, and that the anomalously large spatial extent of the tidal influence seen on the motion of some glaciers cannot be explained, as previously thought, through the elastic or viscoelastic transmission of tidal loads through the bulk of the ice stream. We then discuss how the phase delay between a tidal forcing and the ice stream’s displacement response can be used to constrain in situ viscoelastic properties of glacial ice. Lastly, for the problem of supraglacial lake drainage, we present a methodology for implementing linear viscoelasticity into an existing model for lake drainage. Our work finds that viscoelasticity is a second-order effect when trying to model the deformation of ice in response to a meltwater lake draining to a glacier’s bed. The research in this thesis demonstrates that the first-order understanding of the short-timescale behavior of naturally occurring ice is incomplete, and works towards improving our fundamental understanding of ice behavior over the range of hours to days.
Miniaturized Planar Pattern-Reconfigurable Antenna for Smart Wi-Fi Applications

A single-layer planar printed antenna with four endfire unidirectional patterns is proposed. The antenna consists of four reconfigurable electric dipoles and two combined Z-shaped strips as a magnetic dipole printed on the upper and lower surfaces of the substrate. Four directional radiation modes are achieved by switching the PIN diodes to excite different electric dipoles. Based on the Huygens principle, the endfire directional patterns with a high front-to-back (F/B) ratio and wide beamwidth covering the entire azimuthal plane in four states are obtained. The fabricated antenna features a compact size of 0. 33λ0 × 0. 33λ0 × 0. 016λ0 (λ0 represents the free space wavelength at 2.45 GHz). A prototype operating at 2.4 GHz WLAN band (2.40–2.48 GHz) was fabricated and tested. The measured bandwidth achieves 7.3% (2.36–2.54 GHz) and 5.0% (2.36–2.48 GHz) with |S11| < −10 dB and F/B ratio >15 dB, respectively. The measured peak gain and radiation efficiency of the proposed endfire pattern diversity antenna are higher than 3.20 dBi and 72% in the operating frequency band. The proposed antenna is well-suitable for space-limited intelligent Wi-Fi communication systems.
COMPARISON OF RECREATIONAL FISH CATCH TRENDS TO ENVIRONMENT-SPECIES RELATIONSHIPS AND FISHERY-INDEPENDENT DATA IN THE SOUTHERN CALIFORNIA BIGHT, 1980-2000

Although southern California recreational fish catches have changed in recent years, their relationship to environmental change is not well described. This study describes the relationship of recreational fish catch trends (all modes, 1980‐2000) to environment-species interactions and fishery-independent population data. We used oceanic temperature and upwelling data as indicators of environmental trends, and power-generatingstation data on fish impingement as indicators of fishery-independent population trends. Twenty-one dominant species showed significant changes in average catch from the 1980s to 1990s, with three species (shore-caught grass rockfish, Sebastes rastrelliger; boat-caught Pacific bonito, Sarda chiliensis, and olive rockfish, Sebastes serranoides) decreasing significantly both for landings and catch per unit of effort. These declines generally corresponded to a strong negative population response to temperature or a strong positive response to upwelling in southern California, with temperature being more important. Overall, 61% of 44 species examined had catch or population trends significantly correlated with environmental variables. Fishery-dependent and fishery-independent data trends were similar, with the former lagging the latter by one or more years. Cross-correlation analysis at lags of 0‐7 years between the two data sets revealed significant correlations for two croakers and five rockfishes. The results in this study provide a basis for forecasting fish species responses to natural environmental change and thus may facilitate more adaptive management of recreational fisheries.
Segmentation and Phenotype Calculation of Rapeseed Pods Based on YOLO v8 and Mask R-Convolution Neural Networks

Rapeseed is a significant oil crop, and the size and length of its pods affect its productivity. However, manually counting the number of rapeseed pods and measuring the length, width, and area of the pod takes time and effort, especially when there are hundreds of rapeseed resources to be assessed. This work created two state-of-the-art deep learning-based methods to identify rapeseed pods and related pod attributes, which are then implemented in rapeseed pots to improve the accuracy of the rapeseed yield estimate. One of these methods is YOLO v8, and the other is the two-stage model Mask R-CNN based on the framework Detectron2. The YOLO v8n model and the Mask R-CNN model with a Resnet101 backbone in Detectron2 both achieve precision rates exceeding 90%. The recognition results demonstrated that both models perform well when graphic images of rapeseed pods are segmented. In light of this, we developed a coin-based approach for estimating the size of rapeseed pods and tested it on a test dataset made up of nine different species of Brassica napus and one of Brassica campestris L. The correlation coefficients between manual measurement and machine vision measurement of length and width were calculated using statistical methods. The length regression coefficient of both methods was 0.991, and the width regression coefficient was 0.989. In conclusion, for the first time, we utilized deep learning techniques to identify the characteristics of rapeseed pods while concurrently establishing a dataset for rapeseed pods. Our suggested approaches were successful in segmenting and counting rapeseed pods precisely. Our approach offers breeders an effective strategy for digitally analyzing phenotypes and automating the identification and screening process, not only in rapeseed germplasm resources but also in leguminous plants, like soybeans that possess pods.
Accurate Floating Point Product

Several different techniques and softwares intend to improve the accuracy of results computed in a fixed finite precision. Here we focus on a method to improve the accuracy of the product of floating point numbers. We show that the computed result is as accurate as if computed in twice the working precision. The algorithm is simple since it only requires addition, subtraction and multiplication of floating point numbers in the same working precision as the given data. Such an algorithm can be useful for example to compute the determinant of a triangular matrix and to evaluate a polynomial when represented by the root product form. It can also be used to compute the power of a floating point number.