bluuebunny/crossref_metadata_2025 huggingface dataset:
Influences of Software Changes on Oxycodone Prescribing at an Australian Tertiary Emergency Department: A Retrospective Review
Authors: Barrington Giles , Davis Katherine , Aandahl Zach , Hose Brodie-Anne , Arthur Mitchell , Tran Viet
Published: March 2024

Opioid prescribing and dispensing from emergency departments is a noteworthy issue given widespread opioid misuse and diversion in many countries, contributing both physical and economic harm to the population. High patient numbers and the stochastic nature of acute emergency presentations to emergency departments (EDs) introduce challenges for prescribers who are considering opioid stewardship principles. This study investigated the effect of changes to electronic prescribing software on prescriptions with an auto-populated quantity of oxycodone immediate release (IR) from an Australian tertiary emergency department following the implementation of national recommendations for reduced pack sizes. A retrospective review of oxycodone IR prescriptions over two six-month periods between 2019 and 2021 was undertaken, either side of a software adjustment to reduce the default quantities of tablets prescribed from 20 to 10. Patient demographic details were collected, and prescriber years of practice calculated for inclusion in linear mixed effects regression modelling. A reduction in the median number of tablets prescribed per prescription following the software changes (13.5 to 10.0, p < 0.001) with little change in the underlying characteristics of the patient or prescriber populations was observed, as well as an 11.65% reduction in the total number of tablets prescribed. The prescriber’s years of practice, patient age and patient sex were found to influence increased prescription sizes. Reduced quantity of oxycodone tablets prescribed was achieved by alteration of prescribing software prefill parameters, providing further evidence to support systems-based policy interventions to influence health care providers behaviour and to act as a forcing function for prescribers to consider opioid stewardship principles.
A Deep Learning-Based Preprocessing Method for Single Interferometric Fringe Patterns
Authors: Zhu Xueliang , Zhang Di , Hao Yilei , Liu Bingcai , Wang Hongjun , Tian Ailing
Published: March 2024

A novel preprocessing method based on a modified U-NET is proposed for single interference fringes. The framework is constructed by introducing spatial attention and channel attention modules to optimize performance. In this process, interferometric fringe maps with an added background intensity, fringe amplitude, and ambient noise are used as the input to the network, which outputs fringe maps in an ideal state. Simulated and experimental results demonstrated that this technique can preprocess single interference fringes in ~1 microsecond. The quality of the results was further evaluated using the root mean square error, peak signal-to-noise ratio, structural similarity, and equivalent number of views. The proposed method outperformed U-NET, U-NET++, and other conventional algorithms as measured by each of these metrics. In addition, the model produced high-quality normalized fringes by combining objective data with visual effects, significantly improving the accuracy of the phase solutions for single interference fringes.
Spatial Fluctuations of Optical Turbulence Strength in a Laboratory Turbulence Simulator
Authors: Li Yanling , Mei Haiping , Ye Shuran , Tao Zhiwei , Deng Hanling , Wu Xiaoqing , Rao Ruizhong
Published: March 2024

Controlled turbulence simulators in the laboratory have been extensively employed to investigate turbulence effects on light propagation in the atmosphere, driven by some advanced optical engineering such as remote sensing, energy-delivery systems, and free-space optical communication systems. Many studies have achieved rich results on the optical turbulence intensity, scintillation index, and power spectral density characteristics of the light propagation path in the center of a turbulence simulator, but a comprehensive analysis of the optical turbulence characteristics for different spatial locations is still lacking. We simulate turbulence with air as the medium in a classical convective Rayleigh–Bénard turbulence simulator through high-resolution computational fluid dynamics methods, the three-dimensional refractive index distribution is obtained, and the optical properties are analyzed comprehensively. It is found that the hot and cold plumes and the large-scale circulation strongly influence the inhomogeneity of Cn2 in the turbulence tank, making it weak in the middle and strong near the boundary. The refractive index power spectral density at different heights is centrally symmetric, with the slope gradually deviating from the −5/3 scaling power with increasing distance from the central region. Under the log-log plot, the variation of the refractive index variance with height exhibits a three-segmented feature, showing in order: a stable region, a logarithmic profile, and a power-law profile, in the region close to the boundary. These results will contribute to the construction of a suitable turbulence simulator for optical engineering applications.
Large Angular Momentum States in a Graphene Film
Authors: Corso Pietro Paolo , Cricchio Dario , Fiordilino Emilio
Published: March 2024

At energy lower than 2 eV, the dispersion law of the electrons in a graphene sheet presents a linear dependence of the energy on the kinetic momentum, which is typical of photons and permits the description of the electrons as massless particles by means of the Dirac equation and the study of massless particles acted upon by forces. We analytically solve the Dirac equation of an electron in a graphene disk with radius of 10,000 atomic units pierced by a magnetic field and find the eigenenergies and eigenstates of the particles for spin up and down. The magnetic field ranges within three orders of magnitude and is found to confine the electron in the disk. States with a relatively large total angular momentum exist and can be considered in a vorticose condition; these states are seen to peak at different distances from the disk centre and can be used to store few bit of information.
OsUGT88C3 Encodes a UDP-Glycosyltransferase Responsible for Biosynthesis of Malvidin 3-O-Galactoside in Rice
Authors: Zhao Sihan , Fu Shuying , Cao Zhenfeng , Liu Hao , Huang Sishu , Li Chun , Zhang Zhonghui , Yang Hongbo , Wang Shouchuang , Luo Jie , Long Tuan
Published: March 2024

The diversity of anthocyanins is largely due to the action of glycosyltransferases, which add sugar moieties to anthocyanidins. Although a number of glycosyltransferases have been identified to glycosylate anthocyanidin in plants, the enzyme that catalyzes malvidin galactosylation remains unclear. In this study, we identified three rice varieties with different leaf color patterns, different anthocyanin accumulation patterns, and different expression patterns of anthocyanin biosynthesis genes (ABGs) to explore uridine diphosphate (UDP)-glycosyltransferases (UGTs) responsible for biosynthesis of galactosylated malvidin. Based on correlation analysis of transcriptome data, nine candidate UGT genes coexpressed with 12 ABGs were identified (r values range from 0.27 to 1.00). Further analysis showed that the expression levels of one candidate gene, OsUGT88C3, were highly correlated with the contents of malvidin 3-O-galactoside, and recombinant OsUGT88C3 catalyzed production of malvidin 3-O-galactoside using UDP-galactose and malvidin as substrates. OsUGT88C3 was closely related to UGTs with flavone and flavonol glycosylation activities in phylogeny. Its plant secondary product glycosyltransferase (PSPG) motif ended with glutamine. Haplotype analysis suggested that the malvidin galactosylation function of OsUGT88C3 was conserved among most of the rice germplasms. OsUGT88C3 was highly expressed in the leaf, pistil, and embryo, and its protein was located in the endoplasmic reticulum and nucleus. Our findings indicate that OsUGT88C3 is responsible for the biosynthesis of malvidin 3-O-galactoside in rice and provide insight into the biosynthesis of anthocyanin in plants.
Genetic Analyses of Flower Main Traits from Two Pitayas and Their Progenies: A Cactus Plant
Authors: Zhang Tiantian , Xing Kangmin , Chen Jiayi , Sabir Irfan Ali , Shah Kamran , Chen Jiaxuan , Zhang Zhike , Zhao Jietang , Hu Guibing , Qin Yonghua
Published: March 2024

Elucidation of the genetic foundation governing crucial traits in pitaya flowers is imperative for enhancing both the ornamental and economic values. In this study, the dynamic variation in flower genetics, segregation variation patterns, and a mixed inheritance model of the major and multigene flower traits of ‘Dahong’ and ‘Honghuaqinglong’ pitayas and their progenies were explored. The results showed that the main traits of flowers exhibited varying degrees of variation among the reciprocal F1 hybrids, with the data exhibiting the characteristics of quantitative traits. The betalain content, petal number, and stigma number exhibited values below the median values of the parents, suggesting a genetic inclination towards lower values. Perianth width, calyx tube width, petal number, and stigma number had the same genetic effects and significant correlation. Stigma-related traits had a clear maternal inheritance tendency. The heritability of flower length, stigma relative to anther distance, and petal betalain content was governed by two pairs of additive-dominant major genes. Perianth width, calyx tube width, petal number, and stigma number all conformed to the model of two pairs of equal-additive-dominant major genes. This study provides valuable information for parental selection, cross-breeding, and the enhancement of pitaya varieties to meet market preferences and environmental conditions.
How Can We Strengthen the Global Genetic Resources’ Conservation and Use System?
Authors: Engels Johannes M. M. , Ebert Andreas W.
Published: March 2024

Genetic resources serve as the foundation of our food supply and are building blocks for the development of new crop varieties that support sustainable crop production in the face of climate change, as well as for the delivery of healthy diets to a continuously growing global population. With the encouragement of the FAO and with technical guidance and assistance from the International Board for Plant Genetic Resources (IBPGR), almost 2000 genebanks have been established worldwide for the ex situ conservation of genetic resources since the middle of the last century. The global genetic resources’ conservation and use system has evolved over several decades and presents apparent weaknesses, without a clear blueprint. Therefore, a Special Issue (SI) of Plants on ‘A Critical Review of the Current Approaches and Procedures of Plant Genetic Resources Conservation and Facilitating Use: Theory and Practice’ was initiated. This SI comprises 13 review and research papers that shed light on the history and the political dimensions of the global system; its current strengths, weaknesses, and limitations; and how the effectiveness and efficiency of the system could be improved to satisfy the germplasm users (plant breeders, researchers) and benefit consumers and society at large. This SI provides insight into new approaches and technical developments that have revolutionised ex situ conservation and the use of germplasm and related information. It also reflects on complementary conservation approaches (in situ, on-farm, home gardens) to ex situ genebanks, as well as how—through new forms of collaboration at national, regional, and global levels and through stronger links between public genebanks—synergies between the private breeding sector and botanic garden community could be achieved to strengthen the global conservation and use system. Special attention has also been given to the governance of genetic resources and access and benefit-sharing issues that increasingly hamper the needed access to a wide range of genetic resources that is essential for plant breeders to fulfil their mission.
Analysis of the Spatial-Temporal Distribution Characteristics of Climate and Its Impact on Winter Wheat Production in Shanxi Province, China, 1964–2018
Authors: Wang Donglin , Guo Mengjing , Feng Xuefang , Zhang Yuzhong , Dong Qinge , Li Yi , Gong Xuewen , Ge Jiankun , Wu Feng , Feng Hao
Published: March 2024

The possible influence of global climate changes on agricultural production is becoming increasingly significant, necessitating greater attention to improving agricultural production in response to temperature rises and precipitation variability. As one of the main winter wheat-producing areas in China, the temporal and spatial distribution characteristics of precipitation, accumulated temperature, and actual yield and climatic yield of winter wheat during the growing period in Shanxi Province were analysed in detail. With the utilisation of daily meteorological data collected from 12 meteorological stations in Shanxi Province in 1964–2018, our study analysed the change in winter wheat yield with climate change using GIS combined with wavelet analysis. The results show the following: (1) Accumulated temperature and precipitation are the two most important limiting factors among the main physical factors that impact yield. Based on the analysis of the ArcGIS geographical detector, the correlation between the actual yield of winter wheat and the precipitation during the growth period was the highest, reaching 0.469, and the meteorological yield and accumulated temperature during this period also reached its peak value of 0.376. (2) The regions with more suitable precipitation and accumulated temperature during the growth period of winter wheat in the study area had relatively high actual winter wheat yields. Overall, the average actual yield of the entire region showed a significant increasing trend over time, with an upward trend of 47.827 kg ha−1 yr−1. (3) The variation coefficient of winter wheat climatic yield was relatively stable in 2008–2018. In particular, there were many years of continuous reduction in winter wheat yields prior to 2006. Thereafter, the impact of climate change on winter wheat yields became smaller. This study expands our understanding of the complex interactions between climate variables and crop yield but also provides practical recommendations for enhancing agricultural practices in this region
Exergy-Based Improvements of Sustainable Aviation Fuels: Comparing Biorefinery Pathways
Authors: Silva Ortiz Pablo , de Oliveira Silvio , Mariano Adriano Pinto , Jocher Agnes , Posada John
Published: March 2024

The aeronautical sector faces challenges in meeting its net-zero ambition by 2050. To achieve this target, much effort has been devoted to exploring sustainable aviation fuels (SAF). Accordingly, we evaluated the technical performance of potential SAF production in an integrated first- and second-generation sugarcane biorefinery focusing on Brazil. The CO2 equivalent and the renewability exergy indexes were used to assess environmental performance and impact throughout the supply chain. In addition, exergy efficiency (ηB) and average unitary exergy costs (AUEC) were used as complementary metrics to carry out a multi-criteria approach to determine the overall performance of the biorefinery pathways. The production capacity assumed for this analysis covers 10% of the fuel demand in 2020 at the international Brazilian airports of São Paulo and Rio de Janeiro, leading to a base capacity of 210 kt jet fuel/y. The process design includes sugarcane bagasse and straw as the feedstock of the biochemical processes, including diverse pre-treatment methods to convert lignocellulosic resources to biojet fuel, and lignin upgrade alternatives (cogeneration, fast pyrolysis, and gasification Fischer-Tropsch). The environmental analysis for all scenarios shows a GHG reduction potential due to a decrease of up to 30% in the CO2 equivalent exergy base emissions compared to fossil-based jet fuel.
Polyelectrolyte Platforms with Copper Nanoparticles as a Multifunctional System Aimed at Healing Process Support
Authors: Lipko Agata , Grzeczkowicz Anna , Antosiak-Iwańska Magdalena , Strawski Marcin , Drabik Monika , Kwiatkowska Angelika , Godlewska Ewa , Granicka Ludomira H.
Published: March 2024

(1) Purpose: The aim of the study was to develop a nanocomposite with copper nanoparticles constituting a bacteriostatic surface to maintain human lung cell function. (2) Methods: A polyelectrolyte layer coating that incorporated copper nanoparticles was designed. As a bacteriostatic factor, copper nanoparticles were applied as a colloidal solution of copper nanoparticles (ColloidCuNPs) and a solution of copper nanoparticles (CuNPs). The influence of the polyelectrolytes on selected Gram (+) and Gram (−) strains was examined. The function and morphology of the human adenocarcinoma A549 cell line, comprising human epithelial lung cells cultured in the presence of nanocomposite layer coatings, were evaluated. We applied fluorescence and scanning electron microscopies, as well as flow cytometry, for these studies. Furthermore, the layer coating material was characterized by atomic force microscopy (AFM) and energy dispersive X-ray analysis (EDX). (3) Results: It was observed that the polyelectrolytes polyethyleneimine (PEI) and poly-L-lysine (PLL) did not induce proliferation of the E. coli strain. However, they did induce the proliferation of the S. aureus strain. Due to the effectiveness of the CuNPs against the E. coli strain, CuNPs were selected for further research. The designed coatings of proper NPs shared the sustained function of human lung cells within 10 days of culture. The AFM and EDX characterization confirmed the presence of copper in the layer coating nanomaterial. The presence of CuNPs in polyethyleneimine-based nanocomposite deepened the bacteriostatic effect on E. coli compared with PEI alone. Meanwhile, incorporating CuNPs in PLL allowed A549 cell maintenance but did not exert a bacteriostatic influence on the examined strain. (4) Conclusions: The platform based on polyelectrolytes, incorporated with copper nanoparticles, that ensures the growth and appropriate morphology of the human lung epithelial cells, might be considered an element of a system for medical devices used to maintain the function of human lung cells.
Early Change in Quality of Life in the Treatment of Anorexia Nervosa
Authors: Newton Eliza D. , Liu Liquan , Conti Janet , Touyz Stephen , Arcelus Jon , Madden Sloane , Pike Kathleen , Hay Phillipa
Published: March 2024

This study aimed to examine whether early change in self-reported quality of life (QoL) was a predictor of outcomes in the treatment of anorexia nervosa (AN). Given suggestions that people with AN overestimate their QoL when unwell, we hypothesised that any early change in self-reported QoL, be it an early improvement or early worsening, would predict better outcomes in terms of end-of-treatment body mass index (BMI), eating disorder (ED) psychopathology, and QoL. Participants were 78 adult outpatients engaged in cognitive behaviour therapy for anorexia nervosa (CBT-AN) either with or without the embedded compulsive exercise module “compuLsive Exercise Activity TheraPy” (LEAP). Polynomial regression was utilised to examine the effects of varying combinations of baseline and 10-week self-reported physical-health-relatedr QoL (SF-12; PHRQoL subscale), mental-health-related QoL (SF-12; MHRQoL subscale), and eating-disorder-specific QoL (EDQoL; global, psychological, cognitive/physical, financial, and school/work subscales) on end-of-treatment BMI, ED psychopathology, and QoL. Greater magnitudes of early change in global EDQoL scores, both positive and negative, predicted better MHRQoL but not BMI or ED psychopathology at the end of treatment. Psychological EDQoL ratings also accounted for 38.1% of the variance in end-of-treatment ED psychopathology, although tests examining the 6ratings may be meaningful in predicting treatment outcomes. The positive impact of early worsening in QoL ratings suggests that early QoL ratings are inflated due to denial and poor insight. Clinicians should be reassured that early QoL decline does not indicate treatment failure.
Calculations of the Radiation Dose for the Maximum Hormesis Effect
Authors: Kino Katsuhito
Published: March 2024

To date, the radiation-adaptive response has been reported as a low-dose-related phenomenon and has been associated with radiation hormesis. Well-known cancers are caused by non-radiation active reactants, in addition to radiation. A model of suppression for radiation-specific cancers was previously reported, but the model did not target radiation-nonspecific cancers. In this paper, we describe kinetic models of radiation-induced suppressors for general radiation non-specific cancers, estimating the dose M that induces the maximum hormesis effect while satisfying the condition that the risk is approximately proportional to a dose above NOAEL (No Observed Adverse Effect Level). The radiation hormesis effect is maximal when the rate constant for generation of a risk-reducing factor is the same as the rate constant for its decomposition. When the two rate constants are different, the dose M at which the radiation hormesis effect is maximized depends on both rate constants, but the dose M increases as the two rate constants approach each other, reaching a maximum dose. The theory proposed in this paper can only explain existing experiments with extremely short error bar lengths. This theory may lead to the discovery of unknown risk-reducing factor at low doses and the development of risk-reducing methods in the future.
Comparison between SARS-CoV-2-Associated Acute Disseminated Encephalomyelitis and Acute Stroke: A Case Report
Authors: Jiang Yu-Xuan , Chen Ming-Hua , Lin Yen-Yue , Kao Yung-Hsi , Liao Ting-Wei , Chiu Chih-Chien , Hsiao Po-Jen
Published: March 2024

The neurological manifestations of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection are underrecognized. Ischemic stroke and thrombotic complications have been documented in patients with SARS-CoV-2 infection. Acute disseminated encephalomyelitis (ADEM) associated with coronavirus disease 2019 (COVID-19) is rare but can occur; the incidence of COVID-19-associated ADEM is still not clear due to the lack of reporting of cases. ADEM may have atypical stroke-like manifestations, such as hemiparesis, hemiparesthesia and dysarthria. The treatment strategies for ADEM and acute stroke are different. Early identification and prompt management may prevent further potentially life-threatening complications. We report a patient with SARS-CoV-2 infection presenting with stroke-like manifestations. We also make a comparison between demyelinating diseases, COVID-19-associated ADEM and acute stroke. This case can prompt physicians to learn about the clinical manifestations of SARS-CoV-2-associated ADEM.
Navigating Inflation Challenges: AI-Based Portfolio Management Insights
Authors: Bareith Tibor , Tatay Tibor , Vancsura László
Published: March 2024

After 2010, the consumer price index fell to a low level in the EU. In the euro area, it remained low between 2010 and 2020. The European Central Bank has even had to take action against the emergence of deflation. The situation changed significantly in 2021. Inflation jumped to levels not seen for 40 years in the EU. Our study aims to use artificial intelligence to forecast inflation. We also use artificial intelligence to forecast stock index changes. Based on the forecasts, we propose portfolio reallocation decisions to protect against inflation. The forecasting literature does not address the importance of structural breaks in the time series, which, among other things, can affect both the pattern recognition and prediction capabilities of various machine learning models. The novelty of our study is that we used the Zivot–Andrews unit root test to determine the breakpoints and partitioned the time series into training and testing datasets along these points. We then examined which database partition gives the most accurate prediction. This information can be used to re-balance the portfolio. Two different AI-based prediction algorithms were used (GRU and LSTM), and a hybrid model (LSTM–GRU) was also included to investigate the predictability of inflation. Our results suggest that the average error of the inflation forecast is a quarter of that of the stock market index forecast. Inflation developments have a fundamental impact on equity and government bond returns. If we obtain a reliable estimate of the inflation forecast, we have time to rebalance the portfolio until the inflation shock is incorporated into government bond returns. Our results not only support investment decisions at the national economy level but are also useful in the process of rebalancing international portfolios.
Double-Layer RRT* Objective Bias Anytime Motion Planning Algorithm
Authors: Esmaiel Hamada , Zhao Guolin , Qasem Zeyad A. H. , Qi Jie , Sun Haixin
Published: March 2024

This paper proposes a double-layer structure RRT* algorithm based on objective bias called DOB-RRT*. The algorithm adopts an initial path with an online optimization structure for motion planning. The first layer of RRT* introduces a feedback-based objective bias strategy with segment forward pruning processing to quickly obtain a smooth initial path. The second layer of RRT* uses the heuristics of the initial tree structure to optimize the path by using reverse maintenance strategies. Compared with conventional RRT and RRT* algorithms, the proposed algorithm can obtain the initial path with high quality, and it can quickly converge to the progressive optimal path during the optimization process. The performance of the proposed algorithm is effectively evaluated and tested in real experiments on an actual wheeled robotic vehicle running ROS Kinetic in a real environment.
Sea Level Rise, Land Subsidence, and Flood Disaster Vulnerability Assessment: A Case Study in Medan City, Indonesia
Authors: Lumban-Gaol Jonson , Sumantyo Josaphat Tetuko Sri , Tambunan Efendy , Situmorang David , Antara I Made Oka Guna , Sinurat Maya Eria , Suhita Ni Putu Asri Ratna , Osawa Takahiro , Arhatin Risti Endriani
Published: March 2024

Global sea level rise (SLR) has emerged as a pressing concern because of its impacts, especially increased vulnerability of coastal urban areas flooding. This study addresses the pressing concern of SLR and flood vulnerability in the East Coast of North Sumatra (ECNS) and Medan City. We employ a data-driven approach integrating multicriteria analysis, analytical hierarchy process (AHP)-based weighting, and spatial modeling within a geographic information system framework. The analysis considers crucial factors such as slope, land use, soil type, SLR, and land deformation. The study expands the existing framework by incorporating SLR and land subsidence, acknowledging their significant roles in exacerbating flood vulnerability. Future flood-intensity scenarios are simulated based on SLR projections. Data for spatial analysis primarily originated from multisensor satellite imagery, secondary sources from published literature, and field surveys. We validated the consistency of the variable weightings assigned for vulnerability analysis using a consistency ratio threshold (<0.1). Finally, the established flood vulnerability model was validated by comparing its predictions with recorded flood events in the ECNS and Medan City. The ECNS and Medan City areas were classified as very high and highly vulnerable to flooding, respectively.
A Novel SV-PRI Strategy and Signal Processing Approach for High-Squint Spotlight SAR
Authors: Hu Yuzhi , Wang Wei , Wu Xiayi , Deng Yunkai , Xiao Dengjun
Published: March 2024

High-resolution and high-squint spaceborne spotlight synthetic aperture radar (SAR) has significant potential for extensive application in remote sensing, but its swath width effectiveness is constrained by a critical factor: severe range cell migration (RCM). To address this, pulse repetition interval (PRI) variation offers a practical scheme for raw data reception. However, the current designs for continuously varying PRI (CV-PRI) exhibit high complexity in engineering. In response to the issue, this paper proposes a novel strategy of stepwise varying PRI (SV-PRI), which demonstrates higher reconstruction accuracy compared with CV-PRI. Furthermore, confronting the azimuth non-uniform sampling characteristics induced by the PRI variation, this paper introduces a complete uniform reconstruction processing based on the azimuth partitioning methodology, which effectively alleviates the inherent contradiction between resolution and swath width. The processing flow, utilizing the temporal point remapping (TPR) concept, ensures the uniformity and coherence of dataset partitioning and reassembly in the context of the interpolation on non-uniform grids. Finally, according to the simulation results, the point target data, processed through the processing flow proposed in this study, have demonstrated effective focusing results.
Pansharpening Low-Altitude Multispectral Images of Potato Plants Using a Generative Adversarial Network
Authors: Modak Sourav , Heil Jonathan , Stein Anthony
Published: March 2024

Image preprocessing and fusion are commonly used for enhancing remote-sensing images, but the resulting images often lack useful spatial features. As the majority of research on image fusion has concentrated on the satellite domain, the image-fusion task for Unmanned Aerial Vehicle (UAV) images has received minimal attention. This study investigated an image-improvement strategy by integrating image preprocessing and fusion tasks for UAV images. The goal is to improve spatial details and avoid color distortion in fused images. Techniques such as image denoising, sharpening, and Contrast Limited Adaptive Histogram Equalization (CLAHE) were used in the preprocessing step. The unsharp mask algorithm was used for image sharpening. Wiener and total variation denoising methods were used for image denoising. The image-fusion process was conducted in two steps: (1) fusing the spectral bands into one multispectral image and (2) pansharpening the panchromatic and multispectral images using the PanColorGAN model. The effectiveness of the proposed approach was evaluated using quantitative and qualitative assessment techniques, including no-reference image quality assessment (NR-IQA) metrics. In this experiment, the unsharp mask algorithm noticeably improved the spatial details of the pansharpened images. No preprocessing algorithm dramatically improved the color quality of the enhanced images. The proposed fusion approach improved the images without importing unnecessary blurring and color distortion issues.
Inkjet-Printed Multiwalled Carbon Nanotube Dispersion as Wireless Passive Strain Sensor
Authors: Benchirouf Abderrahmane , Kanoun Olfa
Published: March 2024

In this study, a multiwalled carbon nanotube (MWCNT) dispersion is used as an ink for a single-nozzle inkjet printing system to produce a planar coil that can be used to determine strain wirelessly. The MWCNT dispersion is non-covalently functionalized by dispersing the CNTs in an anionic surfactant, namely sodium dodecyl sulfate (SDS). The fabrication parameters, such as sonication energy and centrifugation time, are optimized to obtain an aqueous suspension suitable for an inkjet printer. Planar coils with different design parameters are printed on a flexible polyethylene terephthalate (PET) polymer substrate. The design parameters include a different number of windings, inner diameter, outer diameter, and deposited layers. The electrical impedance spectroscopy (EIS) analysis is employed to characterize the printed planar coils, and an equivalent electrical circuit model is derived based on the results. Additionally, the radio frequency identification technique is utilized to wirelessly investigate the read-out mechanism of the printed planar MWCNT coils. The complex impedance of the inductively coupled sensor undergoes a shift under strain, allowing for the monitoring of changes in resonance frequency and bandwidth (i.e., amplitude). The proposed wireless strain sensor exhibits a remarkable gauge factor of 22.5, which is nearly 15 times higher than that of the wireless strain sensors based on conventional metallic strain gauges. The high gauge factor of the proposed sensor suggests its high potential in a wide range of applications, such as structural health monitoring, wearable devices, and soft robotics.
Vision-Based On-Road Nighttime Vehicle Detection and Tracking Using Improved HOG Features
Authors: Zhang Li , Xu Weiyue , Shen Cong , Huang Yingping
Published: March 2024

The lack of discernible vehicle contour features in low-light conditions poses a formidable challenge for nighttime vehicle detection under hardware cost constraints. Addressing this issue, an enhanced histogram of oriented gradients (HOGs) approach is introduced to extract relevant vehicle features. Initially, vehicle lights are extracted using a combination of background illumination removal and a saliency model. Subsequently, these lights are integrated with a template-based approach to delineate regions containing potential vehicles. In the next step, the fusion of superpixel and HOG (S-HOG) features within these regions is performed, and the support vector machine (SVM) is employed for classification. A non-maximum suppression (NMS) method is applied to eliminate overlapping areas, incorporating the fusion of vertical histograms of symmetrical features of oriented gradients (V-HOGs). Finally, the Kalman filter is utilized for tracking candidate vehicles over time. Experimental results demonstrate a significant improvement in the accuracy of vehicle recognition in nighttime scenarios with the proposed method.
GPU-Based Parallel Processing Techniques for Enhanced Brain Magnetic Resonance Imaging Analysis: A Review of Recent Advances
Authors: Kirimtat Ayca , Krejcar Ondrej
Published: March 2024

The approach of using more than one processor to compute in order to overcome the complexity of different medical imaging methods that make up an overall job is known as GPU (graphic processing unit)-based parallel processing. It is extremely important for several medical imaging techniques such as image classification, object detection, image segmentation, registration, and content-based image retrieval, since the GPU-based parallel processing approach allows for time-efficient computation by a software, allowing multiple computations to be completed at once. On the other hand, a non-invasive imaging technology that may depict the shape of an anatomy and the biological advancements of the human body is known as magnetic resonance imaging (MRI). Implementing GPU-based parallel processing approaches in brain MRI analysis with medical imaging techniques might be helpful in achieving immediate and timely image capture. Therefore, this extended review (the extension of the IWBBIO2023 conference paper) offers a thorough overview of the literature with an emphasis on the expanding use of GPU-based parallel processing methods for the medical analysis of brain MRIs with the imaging techniques mentioned above, given the need for quicker computation to acquire early and real-time feedback in medicine. Between 2019 and 2023, we examined the articles in the literature matrix that include the tasks, techniques, MRI sequences, and processing results. As a result, the methods discussed in this review demonstrate the advancements achieved until now in minimizing computing runtime as well as the obstacles and problems still to be solved in the future.
Assessing the Match Physical Responses of International Referees for Footballers with Cerebral Palsy: A Tournaments and Halves Comparative Analysis
Authors: Henríquez Matías , Ozaeta Eñaut , Castillo Daniel , Reina Raúl , Cornejo María Isabel , Iturricastillo Aitor , Arthur-Banning Skye , Yanci Javier
Published: March 2024

Similar to conventional football, the modality dedicated to footballers with cerebral palsy (CP) requires referees who cope with the physical demands imposed during competitive matches to apply the rules of the game. While a significant body of research has explored the physical demands on referees in mainstream football, there is a noticeable lack of data regarding CP football. This study aimed to examine the physical response of international referees participating in different levels of world competitions for footballers with CP. Thirteen international referees, who officiated 49 matches in the men’s 2022 World Cup (1st to 15th ranked teams) and 2022 World Championships (16th to 30th ranked teams), participated in this study. A cross-sectional design was used to determine the physical responses and compare the 1st and 2nd halves and the performance in the different tournaments, recording physical variables throughout the matches. Significant higher physical responses were observed in the World Cup in comparison to the World Championship. Overall, high-level tournaments have been shown to elicit more intense physical responses from referees officiating CP football matches compared to lower-level tournaments. For the World Cup, a significantly higher number of accelerations and decelerations were registered in the 1st half compared to the 2nd half. This information may be useful for the strength and conditioning coaches of referees to plan weekly training sessions more specifically and adjust the periodical training load and post-match recovery protocols.
CTAB-Modulated Electroplating of Copper Micropillar Arrays for Non-Enzymatic Glucose Sensing with Improved Sensitivity
Authors: Yao Wenhao , He Hu , Wang Fuliang
Published: March 2024

Micropillar array electrodes represent a promising avenue for enhancing detection sensitivity and response current. However, existing methods for depositing electrode materials on micropillar arrays often result in uneven distribution, with the thin sidewall layer being less conductive and prone to corrosion. In addressing this issue, this study introduces electroplating to enhance the copper layer on the sidewall of micropillar array electrodes. These electrodes, fabricated through standard microelectronics processes and electroplating, are proposed for non-enzymatic glucose detection, with the copper layer deposited via electroplating significantly enhancing sensitivity. Initially, the impact of cetyltrimethylammonium bromide (CTAB) concentration as an inhibitor on the surface morphology and sensitivity of the plated layer was investigated. It was discovered that CTAB could decrease surface roughness, hinder the development of large and coarse grains, generate small particles, and boost sensitivity. Compared to the uncoated electrode and plating without CTAB, sensitivity was elevated by a factor of 1.66 and 1.62, respectively. Subsequently, the alterations in plating morphology and detection performance within a range of 0.3 ASD to 3 ASD were examined. Sensitivity demonstrated a tendency to increase initially and then decrease. The electrode plated at 0.75 ASD achieved a maximum sensitivity of 3314 μA·mM−1·cm−2 and a detection limit of 15.9 μM. Furthermore, a potential mechanism explaining the impact of different morphology on detection performance due to CTAB and current density was discussed. It was believed that the presented effective strategy to enhance the sensitivity of micropillar array electrodes for glucose detection would promote the related biomedical detection applications.
Deep Interpolation of Remote Sensing Land Surface Temperature Data with Partial Convolutions
Authors: Huber Florian , Schulz Stefan , Steinhage Volker
Published: March 2024

Land Surface Temperature (LST) is an important resource for a variety of tasks. The data are mostly free of charge and combine high spatial and temporal resolution with reliable data collection over a historical timeframe. When remote sensing is used to provide LST data, such as the MODA11 product using information from the MODIS sensors attached to NASA satellites, data acquisition can be hindered by clouds or cloud shadows, occluding the sensors’ view on different areas of the world. This makes it difficult to take full advantage of the high resolution of the data. A common solution to interpolating LST data is statistical interpolation methods, such as fitting polynomials or thin plate spine interpolation. These methods have difficulties in incorporating additional knowledge about the research area and learning local dependencies that can help with the interpolation process. We propose a novel approach to interpolating remote sensing LST data in a fixed research area considering local ground-site air temperature measurements. The two-step approach consists of learning the LST from air temperature measurements, where the ground-site weather stations are located, and interpolating the remaining missing values with partial convolutions within a U-Net deep learning architecture. Our approach improves the interpolation of LST for our research area by 44% in terms of RMSE, when compared to state-of-the-art statistical methods. Due to the use of air temperature, we can provide coverage of 100%, even when no valid LST measurements were available. The resulting gapless coverage of high resolution LST data will help unlock the full potential of remote sensing LST data.
Exploring the Possibility of Photoplethysmography-Based Human Activity Recognition Using Convolutional Neural Networks
Authors: Ryu Semin , Yun Suyeon , Lee Sunghan , Jeong In cheol
Published: March 2024

Various sensing modalities, including external and internal sensors, have been employed in research on human activity recognition (HAR). Among these, internal sensors, particularly wearable technologies, hold significant promise due to their lightweight nature and simplicity. Recently, HAR techniques leveraging wearable biometric signals, such as electrocardiography (ECG) and photoplethysmography (PPG), have been proposed using publicly available datasets. However, to facilitate broader practical applications, a more extensive analysis based on larger databases with cross-subject validation is required. In pursuit of this objective, we initially gathered PPG signals from 40 participants engaged in five common daily activities. Subsequently, we evaluated the feasibility of classifying these activities using deep learning architecture. The model’s performance was assessed in terms of accuracy, precision, recall, and F-1 measure via cross-subject cross-validation (CV). The proposed method successfully distinguished the five activities considered, with an average test accuracy of 95.14%. Furthermore, we recommend an optimal window size based on a comprehensive evaluation of performance relative to the input signal length. These findings confirm the potential for practical HAR applications based on PPG and indicate its prospective extension to various domains, such as healthcare or fitness applications, by concurrently analyzing behavioral and health data through a single biometric signal.
Flexible Matrices for the Encapsulation of Plant Wearable Sensors: Influence of Geometric and Color Features on Photosynthesis and Transpiration
Authors: Lo Presti Daniela , Cimini Sara , De Tommasi Francesca , Massaroni Carlo , Cinti Stefano , De Gara Laura , Schena Emiliano
Published: March 2024

The safeguarding of plant health is vital for optimizing crop growth practices, especially in the face of the biggest challenges of our generation, namely the environmental crisis and the dramatic changes in the climate. Among the many innovative tools developed to address these issues, wearable sensors have recently been proposed for monitoring plant growth and microclimates in a sustainable manner. These systems are composed of flexible matrices with embedded sensing elements, showing promise in revolutionizing plant monitoring without being intrusive. Despite their potential benefits, concerns arise regarding the effects of the long-term coexistence of these devices with the plant surface. Surprisingly, a systematic analysis of their influence on plant physiology is lacking. This study aims to investigate the effect of the color and geometric features of flexible matrices on two key plant physiological functions: photosynthesis and transpiration. Our findings indicate that the negative effects associated with colored substrates, as identified in recent research, can be minimized by holing the matrix surface with a percentage of voids of 15.7%. This approach mitigates interference with light absorption and reduces water loss to a negligible extent, making our work one of the first pioneering efforts in understanding the intricate relationship between plant wearables’ features and plant health.
Construction of High-Activity Nano-NiTiO3/g-C3N4 Composite Catalysts for Enhanced Photodegradation Activities under Visible Light
Authors: Li Da , Yang Zhan , Wang Kun , Zhang Lan , Shi Linglong , Qadeer Abdul , Dong Jiao , Ren Haoyu
Published: March 2024

Nickel titanate (NiTiO3) semiconductors and graphitic carbon nitride (g-C3N4) have attracted great attention as photocatalysts in the degradation of environmental pollutants because of their visible-light-driven activity. But the utilizations of both semiconductors are limited by their low specific surface area. In this study, a nano-NiTiO3/g-C3N4 photocatalyst was successfully synthesized by optimizing the preparation method of photocatalyst precursors. Compared with the bulk g-C3N4 and bulk NiTiO3/g-C3N4 composite photocatalysts, the nano-NiTiO3/g-C3N4 composite catalyst displayed a larger specific surface area, a more abundant pore size structure, and superior carrier separation capabilities. According to the pseudo-first-order, the degradation rate of MB was more than 2.5–19.7 times higher than that of previous studies. The superoxide radicals (·O2−) and holes (h+) played significant roles in the photocatalytic reaction of MB. This study provides a new idea for the synthesis of photocatalysts and the improvement in photocatalytic performance.
COVID-19, Race, and Crime: An Early Look at Racial Disparities in U.S. Arrest Data throughout the COVID-19 Pandemic
Authors: Proffit Calvin , Feldmeyer Ben
Published: March 2024

Background: This study explores how arrests changed in response to the COVID-19 pandemic across race. Daily life changed for everyone across the country with the onset of the pandemic, and early works have shown that crime changed in this period. Method: Official arrest data were pulled from the Indiana State Police database for several violent and property crimes covering 26 counties. Data were gathered from 2017 to 2021 for a comparison of pre-COVID-19 versus after the onset of COVID-19 (2020–2021). An OLS regression was run to assess differences in these patterns of arrests across Black and White populations. Results: This analysis finds that Black homicide, White homicide, and total Black violent crime arrests were significantly related to COVID-19 measures after controlling for other variables. The COVID-19 measures indicate that these crimes saw an increase in arrest after the onset of the pandemic and that these effects may not have been identical across race. Conclusions: The COVID-19 pandemic was linked to crime across race in the state of Indiana. Moving forward, it is important to uncover how crime changed across race in other locales and exactly what mechanisms may have driven these changes.