Miracle-dz/UniFAR-FTUs huggingface dataset:
Modified SLM scheme of FBMC signal in satellite communications

In this study, a segment-selected mapping (SSLM) scheme is proposed to reduce the peak-to-average power ratio (PAPR) of the filter bank multi-carrier (FBMC) signal in satellite communications. The standard selected mapping (SLM) scheme is suggested to reduce the PAPR of the traditional multi-carrier signals. However, it cannot be directly applied to the FBMC signal due to the overlapping nature of the FBMC signal. In the proposed method, each symbol in the FBMC signal is divided into several segments to solve the overlapping problem. Each segment is regarded as an independent unit, and rotates a suitable phase to minimise the PAPR in the frequency domain. The authors simulated the FBMC signal in the satellite communications by introducing the influence of the high power amplifiers and the Doppler frequency shift. The simulation results from complementary cumulative distribution function of the PAPR show that the proposed scheme can achieve about 0.3 dB PAPR performance compared to the existing dispersive SLM scheme, with lower complexity.
Assessment of multidimensional self-concept in the area of physical education: validation of a scale

Introduction Self-concept is a person's perception of him/herself and how he/she performs in different situations. This aspect must be developed during the formative stages and Physical Education is a fundamental area due to its enormous methodological possibilities. Aim Therefore, the aim of this study is to evaluate the factor structure and reliability of an instrument that allows to analyze the multidimensional self-concept of high school students in the context of Physical Education. Method The sample consisted of 1,155 secondary school students from public schools in the Autonomous Community of Extremadura, Spain. After the exploratory and confirmatory analyses, a structure composed of 30 items divided into 5 factors was. Results This design showed excellent goodness-of-fit indices as well as good internal reliability indicators (Cronbach's Alpha = 0.76 – 0.88). Conclusion Therefore, this scale can be considered as a tool to assess the self-concept of high school students in a quick and easy way.
Impact of land use change on organic carbon sequestration in Arenosol

Conversion of arable soils into other land uses can stabilize and increase accumulation of soil organic carbon (SOC) and in addition prevent deterioration in its properties. The data has shown changes in SOC sequestration in Ap horizon after arable land conversion (1995–2015) into managed grassland, abandoned and pine afforested. SOC in Arenosol topsoil was positively affected by long term fallow and conversion into grassland. Abandoned land and fertilised managed grassland accumulated significantly more SOC, 48% and 38% respectively compared with arable land. In unfertilised managed grassland SOC stocks decreased 2.3% during 21 years, but losses were lower than in fertilised arable land. Pine afforestation of loamy sand helped to reduce the intensity of SOM mineralization compared to arable land. The Ap horizon thickness in pine forest soil increased from 28 to 31 cm during 21 years period. However, SOC stock decreased by 1% due to reduction in carbon concentration.
Study of Threshold Segmentation Algorithm for Infrared Images

Target segmentation is a basic and critical technology in the fields of image processing, computer vision and artificial intelligence.It aims at providing evidence for the subsequent identification, classification,tracking and retrieval.Because infrared images have the features of low contrast,high noise, blurring,etc,the genetic algorithm is used in the threshold segmentation of them.In this paper,the threshold segmentation algorithms for infrared images are overviewed.The research on the application of genetic algorithms in segmentation of infrared images,the research status and new technologies are presented.The algorithm is used in the processing of infrared images and a good result is obtained.
Simulation of Image-Guided Microwave Ablation Therapy Using a Digital Twin Computational Model

Emerging computational tools such as healthcare digital twin modeling are enabling the creation of patient-specific surgical planning, including microwave ablation to treat primary and secondary liver cancers. Healthcare digital twins (DTs) are anatomically one-to-one biophysical models constructed from structural, functional, and biomarker-based imaging data to simulate patient-specific therapies and guide clinical decision-making. In microwave ablation (MWA), tissue-specific factors including tissue perfusion, hepatic steatosis, and fibrosis affect therapeutic extent, but current thermal dosing guidelines do not account for these parameters. This study establishes an MR imaging framework to construct three-dimensional biophysical digital twins to predict ablation delivery in livers with 5 levels of fat content in the presence of a tumor. Four microwave antenna placement strategies were considered, and simulated microwave ablations were then performed using 915 MHz and 2450 MHz antennae in Tumor Naïve DTs (control), and Tumor Informed DTs at five grades of steatosis. Across the range of fatty liver steatosis grades, fat content was found to significantly increase ablation volumes by approximately 29–l42% in the Tumor Naïve and 55–60% in the Tumor Informed DTs in 915 MHz and 2450 MHz antenna simulations. The presence of tumor did not significantly affect ablation volumes within the same steatosis grade in 915 MHz simulations, but did significantly increase ablation volumes within mild-, moderate-, and high-fat steatosis grades in 2450 MHz simulations. An analysis of signed distance to agreement for placement strategies suggests that accounting for patient-specific tumor tissue properties significantly impacts ablation forecasting for the preoperative evaluation of ablation zone coverage.
Chest Pain Risk Stratification in the Emergency Department: Current Perspectives

Abstract Chest pain is the second leading cause of all emergency department (ED) visits in adults in the United States, with nearly 11 million encounters yearly. While identifying low-risk patients is crucial for early discharge, identifying high-risk patients in ED is vital in timely and appropriate acute coronary syndrome (ACS) management. Traditional methods such as physical examination, cardiac markers, or imaging tests cannot reliably confirm or rule out ACS; they cannot be singularly incorporated to risk stratify patients. Various clinical risk scores have been proposed to address this challenge for risk stratification in patients being evaluated for suspected ACS. The ideal risk score should demonstrate high sensitivity and specificity to accurately differentiate between patients with varying levels of risk, particularly in identifying those at high risk for major adverse cardiovascular events. Simultaneously, an ideal scoring system should also be able to compute information for other non-coronary etiologies of chest pain that require time-sensitive interventions and workups (eg, aortic dissection and pulmonary embolism). In this review, we have assembled major risk scores used for risk stratification in patients with acute chest pain in ED. We have abbreviated their salient features to assist readers in their clinical decision-making.
Laser Rangefinder Methods: Autonomous-Vehicle Trajectory Control in Horticultural Plantings

This article presents a developed motion control system for a robotic platform based on laser-ranging methods, a graph traversal algorithm and the search for the optimal path. The algorithm was implemented in an agricultural building and in the field. As a result, the most efficient algorithm for finding the optimal path (A*) for the robotic platform was chosen when performing various technological operations. In the Rviz visualization environment, a program code was developed for planning the movement path and setting the points of the movement trajectory in real time. To find the optimal navigation graph in an artificial garden, an application was developed using the C# programming language and Visual Studio 2019. The results of the experiments showed that field conditions can differ significantly from laboratory conditions, while the positioning accuracy is significantly lower. The statistical processing of the experimental data showed that, for the movement of a robotic platform along a given trajectory in the field, the most effective conditions are as follows: speed: 2.5 km/h; illumination: 109,600 lux; distance to the tree: 0.5 m. An analysis of the operating parameters of the LiDAR sensor showed that it provides a high degree of positioning accuracy under various lighting conditions at various speeds in the aisles of a garden 3 m wide with an inter-stem distance of 1.5 m and a tree crown width of 0.5 m. The use of sensors—rangefinders of the optical range—allows for the performance of positional movements of the robotic platform and ensures the autonomous performance of the basic technological operations of the units in intensive gardens with a deviation from the specified trajectory of no more than 8.4 cm, which meets the agrotechnical requirements.
Identification of the Orientation and the Role of Industry and Geographical Region in International Entrepreneurial Opportunity Researches

International Entrepreneurship (IE) research is growing rapidly encompassing many industries and regions all over the world. IE is the discovery, enactment, evaluation, and exploitation of opportunities—across national borders—to create future goods and services. In addition, Opportunity is the main pillar of entrepreneurship. Hence, the importance of International Entrepreneurial Opportunity (IEO) becomes obvious. Since each of previous researches have been done in IEO areas were about specific industries and geographical regions, this paper intends to find out which industries and geographical regions have been taken into consideration more by investigating recent studies and in what areas there are research gaps. The main purpose of this research is to identify the orientation of researches related to international entrepreneurial opportunity area, which has done on published articles since year 2000 up to now in valid English-language journals and find the role of industry and geographical region on it by systematic review and meta-synthesis research methodology. Firstly, two variables have identified from articles, which include industry and geographical region where the process of IEO investigation has done. Then the trend of researches explored during defined periods in order of frequency, recognized. Finally, we found that about 43% of IEO previous researches discussed manufacturing industry and about two third of them focus on developed countries. The previous researches in IEO area were in Western Europe’s manufacturing industry. Most researches in knowledge-based area have done in Australia and New Zealand while there was no such research in Asia. In this research, the extracted data analysis has been performed to summarize and categorize the identified aspects and variables in related researches with opportunity subject that are provided in six tables and then the orientation of identified aspects and variables in researches related to the subject in time trend analysis has been reviewed.
Design and fabrication of a continuous tunable microstrip lowpass filter with wide stopband and sharp response

Tunable microstrip lowpass filters (LPFs) with a good performance are used in most telecommunication systems. In this article, a third‐order circuit with stepped impedance resonator is used to design LPF, and suppression cells are used to improve the performance of the filter in stopbands up to 20 GHz. The −3 dB cut‐off frequency can be controlled in the range of 0.35 to 1 GHz with the tuning range of 96%. Rejection stopbands of 30 dB (type‐I) and 20 dB (type‐II) can be extended to more than 20 GHz. For the passband, the insertion loss variations are in the range of 0.35 to 2.12 dB. The proposed tunable LPF has a sharp roll‐off rate (42‐96 dB/GHz). The varactor‐tuned microstrip LPF is designed, simulated, fabricated, and measured. The results of simulation and measurement for the proposed LPF are in good agreement. The size of the proposed tunable LPF is small and the filter dimensions are equal to 0. 267λg × 0. 13λg.
Development and application of a large flood regionalisation model for Australia

Estimation of large to rare floods is imperative in planning and designing large hydraulic structures. Due to the limited availability of observed flood data, the estimation of large to rare flood frequencies requires significant extrapolation beyond the available flood and rainfall data. Notable methods for estimation of large to rare floods include rainfall-runoff models and empirical approaches. This paper presents the further development of a simple Large Flood Regionalisation Model (LFRM) based on observed flood data which in practice will be relatively easier to apply. The LFRM assumes that the maximum observed flood data over a large number of sites in a region can be pooled together by accounting for the at-site variations in the mean and coefficient of variation (CV). The LFRM builds on previous research by adding a spatial dependence model which accounts for the net information available for regional analysis (i.e. number of independent sites Ne). The LFRM can be been applied to ungauged Australian catchments for the estimation of floods with AEPs up to 1 in 3000. It shows little bias and compares very well to the World model.
Dynamic Event-Triggered Adaptive Neural Network Decentralized Output-Feedback Control for Nonlinear Interconnected Systems With Hybrid Cyber Attacks and Its Application

In this article, a dynamic event-triggered adaptive neural network decentralized nonrecursive output-feedback control scheme for nonlinear interconnected systems under hybrid cyber attacks is first proposed, where the hybrid cyber attacks, containing deception attacks and denial-of-service (DoS) attacks, obey Bernoulli distribution. Taking into account the restrictions imposed by network transmission, a dynamic event-triggered mechanism is introduced to fulfill the analysis and design task. A decentralized linear observer is established to estimate the unknown states. Meanwhile, a decentralized adaptive output-feedback controller is developed in a nonrecursive method with the help of neural network technology. The proposed control scheme can ensure that all signals in the closed-loop system are bounded. Furthermore, Zeno phenomenon can be effectively avoided. Finally, simulation results validate the feasibility of the proposed control scheme.
One Year Outcomes Following Transplantation with COVID-19-Positive Donor Hearts: A National Database Cohort Study

The current understanding of the safety of heart transplantation from COVID-19+ donors is uncertain. Preliminary studies suggest that heart transplants from these donors may be feasible. We analyzed 1-year outcomes in COVID-19+ donor heart recipients using 1:3 propensity matching. The OPTN database was queried for adult heart transplant recipients between 1 January 2020 and 30 September 2022. COVID-19+ donors were defined as those who tested positive on NATs or antigen tests within 21 days prior to procurement. Multiorgan transplants, retransplants, donors without COVID-19 testing, and recipients allocated under the old heart allocation system were excluded. A total of 7211 heart transplant recipients met the inclusion criteria, including 316 COVID-19+ donor heart recipients. Further, 290 COVID-19+ donor heart recipients were matched to 870 COVID-19− donor heart recipients. Survival was similar between the groups at 30 days (p = 0.46), 6 months (p = 0.17), and 1 year (p = 0.07). Recipients from COVID-19+ donors in the matched cohort were less likely to experience postoperative acute rejection prior to discharge (p = 0.01). National COVID-19+ donor heart usage varied by region: region 11 transplanted the most COVID-19+ hearts (15.8%), and region 6 transplanted the fewest (3.2%). Our findings indicate that COVID-19+ heart transplantation can be performed with safe early outcomes. Further analyses are needed to determine if long-term outcomes are equivalent between groups.
Prospect of applying remote sensing to tobacco planting monitoring and management

The changing trend of tobacco planting areas and yields during 1978-2012 were analyzed. The application of remote sensing technology in tobacco planting monitoring and field management was of more and more urgency as it boasted higher accuracy than traditionally ground-based surveys and statistical reports. Recent developments in remote sensing and its application in crop monitoring and management in maize, a similar crop as tobacco, were reviewed. Prospective application of remote sensing in tobacco planting monitoring and field management was discussed.
Whole-Genome Sequencing of Two Canine Herpesvirus 1 (CaHV-1) Isolates and Clinicopathological Outcomes of Infection in French Bulldog Puppies

Canine herpesvirus 1 (CaHV-1) infects dogs, causing neonatal death and ocular, neurological, respiratory, and reproductive problems in adults. Although CaHV-1 is widespread in canine populations, only four studies have focused on the CaHV-1 whole genome. In such context, two CaHV-1 strains from both the kidney and spleen of 20-day-old deceased French Bulldog puppies were recently isolated in Sardinia, Italy. The extracted viral DNA underwent whole-genome sequencing using the Illumina MiSeq platform. The Italian CaHV-1 genomes were nearly identical (>99%), shared the same tree branch, and clustered near the ELAL-1 (MW353125) and BTU-1 (KX828242) strains, enlarging the completely separated clade discussed by Lewin et al., in 2020. This study aims to provide new insights on the evolution of the CaHV-1, based on high-resolution whole-genome phylogenetic analysis, and on its clinicopathological characterization during a fatal outbreak in puppies.
ICNP® terminological subset for preventing falls in the elderly in primary care

ABSTRACT Objective: Build and validate a terminological subset of ICNP® for the prevention of falls in the elderly in the context of primary health care, in light of the Self-Care Deficit Theory. Method: Methodological study developed in accordance with ICN recommendations and the Brazilian method for constructing terminological subsets, in two stages: 1) construction of ICNP® statements of nursing diagnoses, outcomes, and interventions; 2) content validation of statements by specialist nurses. Results: A total of 182 diagnoses/outcomes and 321 nursing interventions were constructed, which were subjected to content validation by 28 experts, being validated with a Content Validity Index ≥ 0.80. After validation, the statements were organized according to self-care requirements and the majority of diagnoses/outcomes (51.6%) and interventions (52.7%) were classified under health deviation requirements. Conclusion: It was possible to construct and validate a terminological subset of ICNP® with a predominance of statements related to health deviation requirements, standing out for being the first terminological subset for the prevention of falls in the elderly in the context of primary care.
Recent development of vertical GaN power devices

Gallium nitride (GaN) is an attractive material for high-frequency and high-power devices. Due to the availability of relatively high-quality free-standing bulk GaN substrates, the research and development of vertical GaN devices on GaN substrates has made significant progress in recent years, and various transistors and diodes based on vertical GaN with excellent characteristics have been reported. This paper reviews the current status and recent progress of vertical GaN power device development reported from companies and research institutions, which includes the technological development of our recent research results of Schottky barrier diodes and trench MOSFETs. Key remaining issues for practical applications are also described.
Provably Secure Public-Key Steganography Based on Elliptic Curve Cryptography

Steganography is the technique of hiding secret messages within seemingly harmless covers to elude examination by censors. Despite having been proposed several decades ago, provably secure steganography has not gained popularity among researchers due to its rigorous data requirements. Recent advancements in generative models have enabled these researchers to provide explicit data distributions, which has contributed to the development of provably secure steganography methods. However, these methods depend on the assumption of a preshared key. In practical settings, these methods face various challenges, including key agreement, key updating, and user expansion. Although public-key steganography provides a viable solution, existing public-key steganography approaches are burdened with inefficiency and complex implementation in practical scenarios. In this paper, we proposes a practical public-key steganography method based on elliptic curve cryptography and a generative model. This method is the first comprehensive and practical approach to public-key steganography and steganographic key exchange. Additionally, we provide a specific instance to illustrate the proposed method. The security of the proposed construction is also proven based on computational complexity theory. Further experiments have demonstrated the security and efficiency of the proposed method.
Identification of Volatile Compounds and Terpene Synthase (TPS) Genes Reveals ZcTPS02 Involved in β-Ocimene Biosynthesis in Zephyranthes candida

Zephyranthes candida is a frequently cultivated ornamental plant containing several secondary metabolites, including alkaloids, flavonoids, and volatile organic compounds (VOCs). However, extensive research has been conducted only on non-VOCs found in the plant, whereas the production of VOCs and the molecular mechanisms underlying the biosynthesis of terpenes remain poorly understood. In this study, 17 volatile compounds were identified from Z. candida flowers using gas chromatography–mass spectrometry (GC-MS), with 16 of them being terpenoids. Transcriptome sequencing resulted in the identification of 17 terpene synthase (TPS) genes; two TPS genes, ZcTPS01 and ZcTPS02, had high expression levels. Biochemical characterization of two enzymes encoded by both genes revealed that ZcTPS02 can catalyze geranyl diphosphate (GPP) into diverse products, among which is β-ocimene, which is the second most abundant compound found in Z. candida flowers. These results suggest that ZcTPS02 plays a vital role in β-ocimene biosynthesis, providing valuable insights into terpene biosynthesis pathways in Z. candida. Furthermore, the expression of ZcTPS02 was upregulated after 2 h of methyl jasmonate (MeJA) treatment and downregulated after 4 h of the same treatment.