bluuebunny/crossref_metadata_2025 huggingface dataset:
Quadruple Plasmon-Induced Transparency and Dynamic Tuning Based on Bilayer Graphene Terahertz Metamaterial
Authors: Zhang Jiayu , Li Junyi , Chen Shuxian , Wen Kunhua , Liu Wenjie
Published: September 2023

This study proposes a terahertz metamaterial structure composed of a silicon–graphene–silicon sandwich, aiming to achieve quadruple plasmon-induced transparency (PIT). This phenomenon arises from the interaction coupling of bright–dark modes within the structure. The results obtained from the coupled mode theory (CMT) calculations align with the simulations ones using the finite difference time domain (FDTD) method. Based on the electric field distributions at the resonant frequencies of the five bright modes, it is found that the energy localizations of the original five bright modes undergo diffusion and transfer under the influence of the dark mode. Additionally, the impact of the Fermi level of graphene on the transmission spectrum is discussed. The results reveal that the modulation depths (MDs) of 94.0%, 92.48%, 93.54%, 96.54%, 97.51%, 92.86%, 94.82%, and 88.20%, with corresponding insertion losses (ILs) of 0.52 dB, 0.98 dB, 1.37 dB, 0.70 dB, 0.43 dB, 0.63 dB, 0.16 dB, and 0.17 dB at the specific frequencies, are obtained, achieving multiple switching effects. This model holds significant potential for applications in versatile modulators and optical switches in the terahertz range.
The Potential of Trichoderma-Mediated Nanotechnology Application in Sustainable Development Scopes
Authors: Tomah Ali , Zhang Zhen , Alamer Iman , Khattak Arif , Ahmed Temoor , Hu Minjun , Wang Daoze , Xu Lihui , Li Bin , Wang Yanli
Published: September 2023

The environmental impact of industrial development has been well-documented. The use of physical and chemical methods in industrial development has negative consequences for the environment, raising concerns about the sustainability of this approach. There is a growing need for advanced technologies that are compatible with preserving the environment. The use of fungi products for nanoparticle (NP) synthesis is a promising approach that has the potential to meet this need. The genus Trichoderma is a non-pathogenic filamentous fungus with a high degree of genetic diversity. Different strains of this genus have a variety of important environmental, agricultural, and industrial applications. Species of Trichoderma can be used to synthesize metallic NPs using a biological method that is environmentally friendly, low cost, energy saving, and non-toxic. In this review, we provide an overview of the role of Trichoderma metabolism in the synthesis of metallic NPs. We discuss the different metabolic pathways involved in NP synthesis, as well as the role of metabolic metabolites in stabilizing NPs and promoting their synergistic effects. In addition, the future perspective of NPs synthesized by extracts of Trichoderma is discussed, as well as their potential applications in biomedicine, agriculture, and environmental health.
Nanocontainers for Energy Storage and Conversion Applications: A Mini-Review
Authors: Kordas George
Published: September 2023

Countries that do not have oil and natural gas but are forced to reduce pollution due to combustion have stimulated and developed new technologies for absorption, storage, and energy creation based on nanotechnology. These new technologies are up-and-coming because they will solve the problem without additional environmental burden. The first technology is based on phase change materials (PCMs) that store the thermal energy produced by the sun and release it when requested. In the context of this article, there is a discussion about some devices that arise from this technology. The second technology is based on light nano-traps that convert solar energy into heat, which is then stored by heating water or other methods. The third practice is to absorb solar energy from nanoparticles, producing electricity. These technologies’ principles will be discussed and analyzed to understand their perspectives.
Presurgical Decompensation in Patients Affected by Class III Dentoskeletal Malocclusion: A Comparison between Two Different Bracket Systems
Authors: Mariani Andrea , Vernucci Roberto Antonio , Guarnieri Rosanna , De Stefano Adriana , Di Giorgio Roberto , Barbato Ersilia , Galluccio Gabriella
Published: September 2023

The aim of this study was to analyse if bracket systems could affect the incisors’ decompensation in a group of patients affected by dentoskeletal Class III malocclusion and on the duration of presurgical orthodontics. A single-centre retrospective study was carried out on two groups of patients affected by dentoskeletal Class III and who underwent orthognathic surgery. Group 1, comprising 25 subjects (13 males, 12 females; mean age, 27.4 y.o.), was treated with interactive self-ligating brackets; group 2, comprising 10 subjects (5 males, 5 females; mean age, 27.2 y.o.), was treated with conventional twin brackets. Bracket prescription and archwire sequence were the same for both groups. Data were collected about age, upper incisors’ axis (UI^ANS-PNS), lower incisors’ axis (IMPA), and the total duration of presurgical orthodontics and were then compared between the two groups. The variation in the upper incisor axis and the duration of presurgical orthodontics was not significant between the groups, while the difference in the IMPA was small but significant. The use of a self-ligating bracket did not influence the decompensation of the upper incisors or the duration of presurgical orthodontics when compared with conventional ligating brackets. The difference in the IMPA was significantly different but clinically negligible.
Human Pegivirus-1 Detection and Genotyping in Brazilian Patients with Fulminant Hepatitis
Authors: da Silva Anielly Sarana , de Campos Gabriel Montenegro , Villanova Marcia Guimarães , Bezerra Rafael dos Santos , Santiago Luciana Maria Mendes , Haddad Rodrigo , Covas Dimas Tadeu , Giovanetti Marta , Alcantara Luiz Carlos Junior , Elias Maria Carolina , Sampaio Sandra Coccuzzo , Kashima Simone , Slavov Svetoslav Nanev
Published: September 2023

Fulminant hepatitis is a severe clinical disease characterized by a marked decline in liver function and encephalopathy. In a previous survey, using metagenomics in a group of 27 patients with this clinical condition, we observed an expressive quantity of reads of the Human pegivirus-1 (HPgV-1). Therefore, the objective of this study was to evaluate the frequency, molecular features, and HPgV-1 circulating genotypes in patients with fulminant hepatitis. After testing the collected plasma samples, we discovered twelve samples (44.4%) that were positive for HPgV-1 RNA (using both real-time and nested PCR). The positive samples presented a mean cycle threshold (Ct) of 28.5 (±7.3). Genotyping assignments revealed that all HPgV-1 positive samples belonged to the HPgV-1 genotype 2 (both subgenotypes 2A and 2B were identified). Although HPgV-1 is considered a commensal virus, little is known regarding its prevalence and genotypes in cases of fulminant hepatitis. More research is needed to understand whether HPgV-1 can be implicated in clinical disorders and infectious diseases.
Machine Learning for Self-Coherent Detection Short-Reach Optical Communications
Authors: Wu Qi , Xu Zhaopeng , Zhu Yixiao , Zhang Yikun , Ji Honglin , Yang Yu , Qiao Gang , Liu Lulu , Wang Shangcheng , Liang Junpeng , Wei Jinlong , Li Jiali , He Zhixue , Zhuge Qunbi , Hu Weisheng
Published: September 2023

Driven by emerging technologies such as the Internet of Things, 4K/8K video applications, virtual reality, and the metaverse, global internet protocol traffic has experienced an explosive growth in recent years. The surge in traffic imposes higher requirements for the data rate, spectral efficiency, cost, and power consumption of optical transceivers in short-reach optical networks, including data-center interconnects, passive optical networks, and 5G front-haul networks. Recently, a number of self-coherent detection (SCD) systems have been proposed and gained considerable attention due to their spectral efficiency and low cost. Compared with coherent detection, the narrow-linewidth and high-stable local oscillator can be saved at the receiver, significantly reducing the hardware complexity and cost of optical modules. At the same time, machine learning (ML) algorithms have demonstrated a remarkable performance in various types of optical communication applications, including channel equalization, constellation optimization, and optical performance monitoring. ML can also find its place in SCD systems in these scenarios. In this paper, we provide a comprehensive review of the recent progress in SCD systems designed for high-speed optical short- to medium-reach transmission links. We discuss the diverse applications and the future perspectives of ML for these SCD systems.
Research on Multi-Source Simultaneous Recognition Technology Based on Sagnac Fiber Optic Sound Sensing System
Authors: Zheng Xinyu , Tang Ruixi , Wang Jiang , Lin Cheng , Chen Jianjun , Wang Ning , Zhu Yong , Ruan Juan
Published: September 2023

To solve the problem of multiple sound recognition in the application of Sagnac optical fiber acoustic sensing system, a multi-source synchronous recognition algorithm was proposed, which combined the VMD (variational modal decomposition) algorithm and MFCC (Mel-frequency cepstral coefficient algorithm) algorithm to pre-process the photoacoustic sensing signal, and uses BP neural network to recognize the photoacoustic sensing signal. The modal analysis and feature extraction theory of photoacoustic sensing signal based on the VMD and MFCC algorithms were presented. The signal recognition theory analysis and system recognition program design were completed based on the BP neural network. Signal acquisition of different sounds and verification experiments of the recognition system have been carried out in a laboratory environment based on the Sagnac fiber optic sound sensing system. The experimental results show that the proposed optical fiber acoustic sensing signal recognition algorithm has a simultaneous recognition rate better than 96.5% for six types of sounds, and the optical acoustic signal recognition takes less than 5.3 s, which has the capability of real-time sound detection and recognition, and provides the possibility of further application of the Sagnac-based optical fiber acoustic sensing system.
Stabilizing Diamagnetic Levitation of a Graphene Flake through the Casimir Effect
Authors: Inui Norio
Published: September 2023

Graphene exhibits diamagnetism, enabling it to be lifted by the repulsive force produced in an inhomogeneous magnetic field. However, the stable levitation of a graphene flake perpendicular to the magnetic field is impeded by its strong anisotropic of magnetic susceptibility that induces rotation. A method to suppress this rotation by applying the Casimir force to the graphene flake is presented in this paper. As a result, the graphene flake can archive stable levitation on a silicon plate when the gravitational force is small.
Recent Advances in Microbial-Assisted Remediation of Cadmium-Contaminated Soil
Authors: Zulfiqar Usman , Haider Fasih Ullah , Maqsood Muhammad Faisal , Mohy-Ud-Din Waqas , Shabaan Muhammad , Ahmad Muhammad , Kaleem Muhammad , Ishfaq Muhammad , Aslam Zoya , Shahzad Babar
Published: September 2023

Soil contamination with cadmium (Cd) is a severe concern for the developing world due to its non-biodegradability and significant potential to damage the ecosystem and associated services. Industries such as mining, manufacturing, building, etc., rapidly produce a substantial amount of Cd, posing environmental risks. Cd toxicity in crop plants decreases nutrient and water uptake and translocation, increases oxidative damage, interferes with plant metabolism and inhibits plant morphology and physiology. However, various conventional physicochemical approaches are available to remove Cd from the soil, including chemical reduction, immobilization, stabilization and electro-remediation. Nevertheless, these processes are costly and unfriendly to the environment because they require much energy, skilled labor and hazardous chemicals. In contrasting, contaminated soils can be restored by using bioremediation techniques, which use plants alone and in association with different beneficial microbes as cutting-edge approaches. This review covers the bioremediation of soils contaminated with Cd in various new ways. The bioremediation capability of bacteria and fungi alone and in combination with plants are studied and analyzed. Microbes, including bacteria, fungi and algae, are reported to have a high tolerance for metals, having a 98% bioremediation capability. The internal structure of microorganisms, their cell surface characteristics and the surrounding environmental circumstances are all discussed concerning how microbes detoxify metals. Moreover, issues affecting the effectiveness of bioremediation are explored, along with potential difficulties, solutions and prospects.
Screening for Fungicide Efficacy in Controlling Blackleg Disease in Wasabi (Eutrema japonicum)
Authors: Liu Yanjun , Song Changjiang , Ren Xin , Wu Guoli , Ma Zihan , Zhao Mantong , Xie Yujia , Li Yu , Lai Yunsong
Published: September 2023

Blackleg disease is devastating for wasabi (Eutrema japonicum) production, occurring at any time and everywhere within the main production area of the Sichuan Province, China. There have been very few studies on the chemical control of this disease. In this study, we isolated and identified a local popular strain of the pathogen Plenodomus wasabiae. The isolated fungus strain caused typical disease spots on the leaves and rhizomes upon inoculation back to wasabi seedlings. The symptoms of blackleg disease developed very quickly, becaming visible on the second day after exposure to P. wasabiae and leading to death within one week. We then evaluated the efficacy of ten widely used fungicides to screen out effective fungicides. The efficacy of the tested fungicides was determined through mycelial growth inhibition on medium plates. As a result, tebuconazole and pyraclostrobin were able to inhibit the mycelial growth of P. wasabiae, and the most widely used dimethomorph in local production areas produced the lowest inhibition activity (13.8%). Nevertheless, the highest control efficacy of tebuconazole and pyraclostrobin on wasabi seedlings was only 47.48% and 39.03%, respectively. Generally, the control efficacy of spraying the fungicide before inoculation was better than that after inoculation. An increase in the application concentration of the two fungicides did not proportionately result in improved performance. We cloned the full-length sequence of sterol 14-demethylase (CYP51) and cytochrome B (CYTB) of which the mutations may contribute to the possible antifungalresistance. These two genes of the isolated fungus do not possess any reported mutations that lead to fungicide resistance. Previous studies indicate that there is a significant difference between fungicides in terms of the effectiveness of controlling blackleg disease; however, the control efficacy of fungicides is limited in blackleg control. Therefore, field management to prevent wound infection and unfavorable environmental conditions are more important than pesticide management.
Prediction of Leakage Pressure during a Drilling Process Based on SSA-LSTM
Authors: Chen Dong , He Baolun , Wang Yanshu , Han Chao , Wang Yucong , Xu Yuqiang
Published: September 2023

Drilling-fluid loss has always been one of the challenging issues in the field of drilling engineering. This article addresses the limitations of a single fluid-loss pressure mechanism model and the challenges in predicting positive drilling-fluid-loss pressure. By categorizing fluid losses of various types encountered during drilling, different geological formations associated with distinct mechanisms are considered. The actual drilling-fluid density in the wellbore at the time of fluid-loss occurrence is taken as a reference value for calculating the positive drilling-fluid-loss pressure of the already drilled well. Building upon this foundation, a combined model utilizing the Sparrow Search Algorithm (SSA) and Long Short-Term Memory (LSTM) neural network is constructed. This model effectively explores the intricate nonlinear relationship between well logging, logging engineering data, and fluid-loss pressure. By utilizing both data from the already drilled wells and upper formation data from ongoing drilling, precise prediction of positive drilling formation fluid-loss pressure can be achieved. Case studies demonstrate that the approach established in this paper, incorporating upper formation data, reduces the average absolute percentage error of fluid-loss pressure prediction to 2.4% and decreases the root mean square error to 0.0405. Through the synergy of mechanistic models and data-driven techniques, not only has the accuracy of predicting positive drilling formation fluid-loss pressure has been enhanced, but also valuable insights have been provided for preventing and mitigating fluid losses during drilling operations.
Spatial Structure Characteristics of Underground Reservoir Water Storage Space in Coal Mines Considering Shape Characteristics of Crushed Rock
Authors: Qin Xuan , Cao Zhiguo , Wei Lichang , Li Peng , Sun Hao
Published: September 2023

In order to investigate the impact of a crushed rock shape on the storage coefficient of underground reservoirs in coal mines, statistical analysis of the shape characteristics of crushed rocks was conducted, which was followed by numerical packing tests using the rigid block model. These tests aimed to investigate the spatial structure characteristics of underground reservoir water storage space in coal mines under the influence of different shapes of crushed rock. The results demonstrated the following: (1) Crushed rock exhibits a lognormal distribution in its shape characteristic parameters at different scales with a predominant discoid shape. The shape coefficient M can be utilized as a comprehensive indicator to characterize the shape characteristics of crushed rock. (2) The average storage coefficient of crushed rock increases exponentially as the shape coefficient M increases. There is a 50.1% increase in the storage coefficient from M = 1 to 3.5. (3) The spatial structure of the water storage space exhibits self-similarity, and both the void fractal dimension and the void boundary fractal dimension increase with an increase in the shape coefficient M. (4) When comparing the non-spherical particle system with the spherical particle system, it is observed that the spherical particle system has smaller water storage space, lower connectivity among voids, and more irregular void space. In the non-spherical particle system, the water storage space becomes larger as the shape of crushed rock becomes more irregular, resulting in more irregular void space. However, there is no significant effect on void connectivity.
The Processes of Aggradation and Incision in the Channels in the Terek River Basin, the North Caucasus: The Hydrological Fluvial Archives of the Recent Past
Authors: Sidorchuk Aleksey
Published: September 2023

The rates of incision and aggradation in the channels in the Terek River basin (North Caucasus) for the last 50–85 years were estimated at 18 gauging stations. The stage–discharge method (annual low water stages at the same discharges) was applied. The stability of the Terek River channel was recorded on the tectonically subsiding Tersko–Kuma Lowland. On the subsiding Kabardian Plain, channel aggradation up to 14 mm a−1 was registered. The rapid (~32 mm a−1) incision of the Terek River occurs within the antecedent valley of the rising Sunzha Ridge, causing regressive erosion and incision (~25 mm a−1) of rivers on the Ossetian Plain, despite its tectonic subsiding. The rivers in the uplifting mountains of the North Caucasus transport the sediments delivered from slopes as climatically controlled debris flows. Aggradation and incision here alternate without a visible overall trend. The rates of modern channel bed deformations are 10 to 100 times higher than the mean rates of tectonic movements. The main effect of tectonics is the changes in river channel slopes, which cause changes in the bed load transport budget and channel bed deformation. Human-made constructions induce rapid deformations in the channels but have a local effect.
Air Temperature Change at the End of the Late Holocene and in the Anthropocene in the Middle Volga Region, European Russia
Authors: Perevedentsev Yuri P. , Shantalinsky Konstantin M. , Gusarov Artyom V. , Mirsaeva Nadezhda A. , Aukhadeev Timur R. , Nikolaev Alexander A.
Published: September 2023

The temporal variability of air temperature in the Middle Volga region from 1828 to 2021 is considered according to instrumental observations at the oldest meteorological station in the east of the East European Plain (Kazan University) and throughout the Asian part of Russia against the background of long-term climate fluctuations in the Northern Hemisphere of Earth. A general trend toward an increase in air temperature was revealed. It was found that climate change in Kazan was consistent with the climatic processes that occurred in the Middle Volga region as a whole. The greatest warming for the entire observation period was observed in the winter and spring seasons of the year. In December, warming occurred at a maximum rate of 0.28 °C/10 years. At the same time, the most intense warming process was observed from 1991 to 2021. The analysis of low-frequency fluctuations in the series of monthly average air temperatures made it possible to identify different periods of change, both in type (direction) and intensity. It is shown that in the Middle Volga region, positive anomalies of air temperature have occurred more often than negative ones in recent decades. Statistical data processing was also carried out for 30-year periods, starting from the first period, i.e., 1841–1870. This made it possible to reveal long-term changes in air temperature. Comparisons of climatic parameters in two periods, i.e., 1828–1945 and 1946–2021, allowed us to reliably detect the climatic beginning of the increasingly identifiable Anthropocene epoch (since 1946), characterized by a sharp increase in air temperature, increased interannual variability of the air temperature regime, and a significant increase (by about three times) in the rate of warming in the Middle Volga region. A correlation was made between atmospheric circulation indices and air temperature fluctuations in Kazan over different periods. The closest relationship was found for the 1990–2020 period. It is shown that the contribution of global factors to air temperature variability in the Middle Volga region during the Anthropocene reached 37% in winter and 32% in summer; in annual terms, this contribution amounted to 54%.
Study on Local Power Plant Emissions Using Multi-Frequency Differential Absorption LIDAR and Real-Time Plume Tracking
Authors: Stroud Jasper R. , Dienstfrey William J. , Plusquellic David F.
Published: August 2023

We present a new fiber-amplifier-based differential absorption light detection and ranging (DIAL) system for range-resolved detection of carbon dioxide (CO2) and water vapor (H2O) over a range of a few kilometers. The fiber amplifier chain is seeded with a 7.14 kHz fast-switching high-spectral purity wavelength source near 1572 nm to cover ten different frequencies across the CO2/H2O line pair in ≈1.4 ms. We demonstrate the system in a study of CO2 emissions from a local power plant in Boulder, CO, USA. We use real-time wind information to predict the plume location for tracking and modeling of the CO2 emission rate to compare with the reported data from the power plant over a 13 h period. There is overall agreement with the reported burn rate, but we see periods of bias towards underestimation of the CO2 emission rate. We attribute the dropout periods to uncertainties between the measured and the plant’s local wind speed data that impact both the tracking location and the plume model predictions. Upcoming studies that will make use of real-time Doppler wind data are expected to significantly decrease these uncertainties.
Ultra-Wideband-Based Time Occupancy Analysis for Safety Studies
Authors: Fakhoury Salah , Ismail Karim
Published: August 2023

This study investigates the use of ultra-wideband (UWB) tags in traffic conflict techniques (TCT) for the estimation of time occupancy in a real-world setting. This study describes UWB technology and its application in the TCT framework. Many experiments were conducted to evaluate the accuracy of the occupancy time measurement using a UWB-based tag. The UWB performance was measured using data from UWB tags as well as a video camera system by subtracting the time occupancy within a conflict zone. The results show that the UWB-based system can be utilized to estimate occupancy time with a mean absolute error difference from ground truth measurements of 0.43 s in the case of using two tags and 0.06 s in the case of using one tag in an 8 m × 8 m study area with double-sided two-way communication. This study also highlights the advantages and limitations of using UWB technology in TCT and discusses potential applications and future research directions. The findings of this study suggest that the UWB-based localization of multiple tags needs further improvements to enable consistent multi-tag tracking. In future work, this technology could be utilized to estimate post-encroachment time (PET) in various traffic scenarios, which could improve road safety and reduce the risk of collisions.
A Deep Recurrent Learning-Based Region-Focused Feature Detection for Enhanced Target Detection in Multi-Object Media
Authors: Wang Jinming , Alshahir Ahmed , Abbas Ghulam , Kaaniche Khaled , Albekairi Mohammed , Alshahr Shahr , Aljarallah Waleed , Sahbani Anis , Nowakowski Grzegorz , Sieja Marek
Published: August 2023

Target detection in high-contrast, multi-object images and movies is challenging. This difficulty results from different areas and objects/people having varying pixel distributions, contrast, and intensity properties. This work introduces a new region-focused feature detection (RFD) method to tackle this problem and improve target detection accuracy. The RFD method divides the input image into several smaller ones so that as much of the image as possible is processed. Each of these zones has its own contrast and intensity attributes computed. Deep recurrent learning is then used to iteratively extract these features using a similarity measure from training inputs corresponding to various regions. The target can be located by combining features from many locations that overlap. The recognized target is compared to the inputs used during training, with the help of contrast and intensity attributes, to increase accuracy. The feature distribution across regions is also used for repeated training of the learning paradigm. This method efficiently lowers false rates during region selection and pattern matching with numerous extraction instances. Therefore, the suggested method provides greater accuracy by singling out distinct regions and filtering out misleading rate-generating features. The accuracy, similarity index, false rate, extraction ratio, processing time, and others are used to assess the effectiveness of the proposed approach. The proposed RFD improves the similarity index by 10.69%, extraction ratio by 9.04%, and precision by 13.27%. The false rate and processing time are reduced by 7.78% and 9.19%, respectively.
Radar-Camera Fusion Network for Depth Estimation in Structured Driving Scenes
Authors: Li Shuguang , Yan Jiafu , Chen Haoran , Zheng Ke
Published: August 2023

Depth estimation is an important part of the perception system in autonomous driving. Current studies often reconstruct dense depth maps from RGB images and sparse depth maps obtained from other sensors. However, existing methods often pay insufficient attention to latent semantic information. Considering the highly structured characteristics of driving scenes, we propose a dual-branch network to predict dense depth maps by fusing radar and RGB images. The driving scene is divided into three parts in the proposed architecture, each predicting a depth map, which is finally merged into one by implementing the fusion strategy in order to make full use of the potential semantic information in the driving scene. In addition, a variant L1 loss function is applied in the training phase, directing the network to focus more on those areas of interest when driving. Our proposed method is evaluated on the nuScenes dataset. Experiments demonstrate its effectiveness in comparison with previous state of the art methods.
Frequency Limits of Sequential Readout for Sensing AC Magnetic Fields Using Nitrogen-Vacancy Centers in Diamond
Authors: Ghimire Santosh , Lee Seong-joo , Oh Sangwon , Shim Jeong Hyun
Published: August 2023

The nitrogen-vacancy (NV) centers in diamond have the ability to sense alternating-current (AC) magnetic fields with high spatial resolution. However, the frequency range of AC sensing protocols based on dynamical decoupling (DD) sequences has not been thoroughly explored experimentally. In this work, we aimed to determine the sensitivity of the ac magnetic field as a function of frequency using the sequential readout method. The upper limit at high frequency is clearly determined by Rabi frequency, in line with the expected effect of finite DD-pulse width. In contrast, the lower frequency limit is primarily governed by the duration of optical repolarization rather than the decoherence time (T2) of NV spins. This becomes particularly crucial when the repetition (dwell) time of the sequential readout is fixed to maintain the acquisition bandwidth. The equation we provide successfully describes the tendency in the frequency dependence. In addition, at the near-optimal frequency of 1 MHz, we reached a maximum sensitivity of 229 pT/Hz by employing the XY4-(4) DD sequence.
Three-Dimensional (3D) Visualization under Extremely Low Light Conditions Using Kalman Filter
Authors: Kim Hyun-Woo , Cho Myungjin , Lee Min-Chul
Published: August 2023

In recent years, research on three-dimensional (3D) reconstruction under low illumination environment has been reported. Photon-counting integral imaging is one of the techniques for visualizing 3D images under low light conditions. However, conventional photon-counting integral imaging has the problem that results are random because Poisson random numbers are temporally and spatially independent. Therefore, in this paper, we apply a technique called Kalman filter to photon-counting integral imaging, which corrects data groups with errors, to improve the visual quality of results. The purpose of this paper is to reduce randomness and improve the accuracy of visualization for results by incorporating the Kalman filter into 3D reconstruction images under extremely low light conditions. Since the proposed method has better structure similarity (SSIM), peak signal-to-noise ratio (PSNR) and cross-correlation values than the conventional method, it can be said that the visualization of low illuminated images can be accurate. In addition, the proposed method is expected to accelerate the development of autonomous driving technology and security camera technology.
Towards a Sustainable and Safe Future: Mapping Bike Accidents in Urbanized Context
Authors: Jaber Ahmed , Csonka Bálint
Published: September 2023

This manuscript presents a study on the spatial relationships between bike accidents, the built environment, land use, and transportation network characteristics in Budapest, Hungary using geographic weighted regression (GWR). The sample period includes bike crash data between 2017 and 2022. The findings provide insights into the spatial distribution of bike crashes and their severity, which can be useful for designing targeted interventions to improve bike safety in Budapest and be useful for policymakers and city planners in developing effective strategies to reduce the severity of bike crashes in urban areas. The study reveals that built environment features, such as traffic signals, road crossings, and bus stops, are positively correlated with the bike crash index, particularly in the inner areas of the city. However, traffic signals have a negative correlation with the bike crash index in the suburbs, where they may contribute to making roads safer for cyclists. The study also shows that commercial activity and PT stops have a higher impact on bike crashes in the northern and western districts. GWR analysis further suggests that one-way roads and higher speed limits are associated with more severe bike crashes, while green and recreational areas are generally safer for cyclists. Future research should be focused on the traffic volume and bike trips’ effects on the severity index.
Oxidant and Antioxidant Profiling in Viscaria alpina Seed Populations Following the Temporal Dynamics of an Alpine Climate
Authors: Pagano Andrea , Doria Enrico , Mondoni Andrea , White Fiona Jane , Balestrazzi Alma , Macovei Anca
Published: September 2023

The adaptability of seed metabolism to different environmental conditions represents a crucial aspect to understand the effects of climate change on plant populations in wild environments. Among the indicators of stress and repair in seeds, tocopherols and malondialdehyde have been related to membrane stability in seed deterioration. Alpine plants constitute an interesting system to understand stress response dynamics because of the relevant climate variations challenging seed viability in alpine environments. This study considered five accessions of Viscaria alpina seeds collected over five years, highlighting significant correlations between environmental parameters such as precipitations and temperature, and several indicators of the oxidative stress response. These provide new insights on how changes in indicators of the seed stress response can reflect annual variations in temperature and precipitations affecting their parental plants, with possible implications on the current understanding of seed persistence in alpine environments threatened by climate change and on the effects of seed storage.
Numerical Calculation and 3-D Imaging of the Arrhenius Temperature Integral
Authors: Zhang Wei , Zheng Qiaoyu , Yu Xiaobing , Shen Yansong , Li Kui
Published: September 2023

The Arrhenius temperature integral is typically used in non-isothermal kinetic analysis, which is widely applied in gas–solid reactions in separation processes. In previous studies, researchers provided various methods to solve the temperature integral, but the error usually became significant when the value of x (x = Ea/RT) was too large or too small. In this paper, we present a new series method and design a computer program to calculate the temperature integral. According to the precise calculation of the temperature integral, we first reveal the relationship among the integral, the temperature, and the activation energy, and we find an interesting phenomenon in which the 3-D image of the temperature integral is of self-similarity according to fractal theory. The work is useful for mechanism and theoretical studies of non-isothermal kinetics.
Frequency of Knee Pain and Risk Factors and Its Impact on Functional Impairment: A Cross-Sectional Study from Saudi Arabia
Authors: Alyami Ali H. , Darraj Hussam , Hakami Khalid M. , Hakami Faisal , Awaf Mohammed , Bakri Nawaf , Hamdi Sulaiman , Saber Abdulaziz , Alyami Almuhanad , Khashab Mohammed , Alhazmi Abdulaziz H.
Published: September 2023

Background: Adolescents frequently self-report pain, according to epidemiological research. The knee is one of the sites wherein pain is most commonly reported. Musculoskeletal disorders play a significant role in the prolonged disability experienced by individuals, leading to substantial global personal, societal, and economic burdens. Patellofemoral pain (PFP) is a clinical knee pain commonly affecting adolescents. This study aimed to estimate the frequency of knee pain in Saudi adolescents. Methods: This cross-sectional survey was conducted from June to November 2022 and included 676 adolescents aged 10 to 18 years. The participants were questioned regarding their demographics, school habits, and the impact of these factors on back pain, musculoskeletal pain in the past 12 months, as well as quality-of-life scale and knee pain symptoms. The data were analyzed using descriptive statistics, with frequencies and percentages presented for categorical variables. Analysis of variance (ANOVA) was performed to compare means between groups, while the chi-squared test was used to compare categorical variables. Statistical significance was set at p < 0.05. Results: A total of 676 adolescents participated in the study, with 57.5% females and 42.5% males. Among the participants, 68.8% were aged between 15 and 18 years. The prevalence of knee pain was notably higher among females (26%) compared to males (19.2%). Age and BMI were identified as significant predictors of knee pain. A significant association was also found between BMI classification and knee stiffness (p-value = 0.008). Furthermore, a significant difference was observed between adolescents who engaged in physical activities during leisure time and those who experienced difficulty bending (p-value = 0.03). Conclusions: Our study highlights a high prevalence of knee pain among Saudi adolescents, emphasizing the need for increased awareness about its risk factors. Preventive measures, including conservative approaches and lifestyle/activity modifications, can effectively mitigate adolescent knee pain.
Orthonormal F Contrasts for Factors with Ordered Levels in Two-Factor Fixed-Effects ANOVAs
Authors: Rayner J. C. W. , Livingston G. C.
Published: September 2023

In multifactor fixed-effects ANOVAs, we show how to construct orthonormal F contrasts for main effects. Our primary focus is the case when the levels of the factor of interest are ordered. Likewise, in multifactor equally replicated fixed-effects ANOVAs, we show how to construct orthonormal F contrasts for interactions. The primary focus here is on interactions when both factors are ordered, although the approach also applies if just one factor is ordered. Interactions with both factors ordered may be interpreted in terms of generalised correlations.
An Intelligent System-Based Coffee Plant Leaf Disease Recognition Using Deep Learning Techniques on Rwandan Arabica Dataset
Authors: Hitimana Eric , Sinayobye Omar Janvier , Ufitinema J. Chrisostome , Mukamugema Jane , Rwibasira Peter , Murangira Theoneste , Masabo Emmanuel , Chepkwony Lucy Cherono , Kamikazi Marie Cynthia Abijuru , Uwera Jeanne Aline Ukundiwabo , Mvuyekure Simon Martin , Bajpai Gaurav , Ngabonziza Jackson
Published: September 2023

Rwandan coffee holds significant importance and immense value within the realm of agriculture, serving as a vital and valuable commodity. Additionally, coffee plays a pivotal role in generating foreign exchange for numerous developing nations. However, the coffee plant is vulnerable to pests and diseases weakening production. Farmers in cooperation with experts use manual methods to detect diseases resulting in human errors. With the rapid improvements in deep learning methods, it is possible to detect and recognize plan diseases to support crop yield improvement. Therefore, it is an essential task to develop an efficient method for intelligently detecting, identifying, and predicting coffee leaf diseases. This study aims to build the Rwandan coffee plant dataset, with the occurrence of coffee rust, miner, and red spider mites identified to be the most popular due to their geographical situations. From the collected coffee leaves dataset of 37,939 images, the preprocessing, along with modeling used five deep learning models such as InceptionV3, ResNet50, Xception, VGG16, and DenseNet. The training, validation, and testing ratio is 80%, 10%, and 10%, respectively, with a maximum of 10 epochs. The comparative analysis of the models’ performances was investigated to select the best for future portable use. The experiment proved the DenseNet model to be the best with an accuracy of 99.57%. The efficiency of the suggested method is validated through an unbiased evaluation when compared to existing approaches with different metrics.
The State of Intraoperative OCT in Vitreoretinal Surgery: Recent Advances and Future Challenges
Authors: Ciarmatori Nicolò , Pellegrini Marco , Nasini Francesco , Talli Pietro Maria , Sarti Laura , Mura Marco
Published: September 2023

Since its first introduction more than 30 years ago, optical coherence tomography (OCT) has revolutionized ophthalmology practice, providing a non-invasive in vivo cross-sectional view of the structures of the eye. Mostly employed in the clinical setting due to its tabletop configuration requiring an upright patient positioning, the recent advent of microscope-integrated systems now allows ophthalmologists to perform real-time intraoperative OCT (iOCT) during vitreoretinal surgical procedures. Numerous studies described various applications of this tool, such as offering surgeons feedback on tissue–instrument interactions in membrane peeling, providing structural images in macular hole repair, and showing residual subretinal fluid or perfluorocarbon in retinal detachment surgery. This narrative review aims at describing the state of the art of iOCT in vitreoretinal procedures, highlighting its modern role and applications in posterior segment surgery, its current limitations, and the future perspectives that may improve the widespread adoption of this technology.
Hepatitis E Virus in the Wild Boar Population: What Is the Real Zoonotic Risk in Portugal?
Authors: Abrantes Ana Carolina , Santos-Silva Sérgio , Mesquita João , Vieira-Pinto Madalena
Published: September 2023

Hepatitis E virus (HEV) is an important zoonosis in wild boar. Reported zoonotic cases are mainly associated with the consumption of raw/undercooked meat and/or liver. This study aims to determine the occurrence of HEV in the Portuguese wild boar population. During the hunting season 2021/2022, 123-matched samples (liver, faeces, and blood) were collected from hunted wild boars throughout Portugal. An RT-PCR assay tested liver and faeces samples to detect HEV-RNA. From blood samples, an ELISA test was performed. Only one liver sample was positive for HEV (0,8%) and one other from faeces. A total of 34 sera were seropositive (26.7%). At the same time, in a survey of 106 hunters, 21 consumed/ate the liver of wild boars (19.8%). Only three recognised the possibility of consuming it undercooked. Contrary to previous studies in Portugal, the prevalence of HEV in liver and faeces is low, but the seropositivity is higher. But, when analyzing in detail, it could be observed that an HEV hotspot exists in the southeast of central Portugal and that it is a zoonotic risk for hunters of this region. The data of this study reinforce the importance of including HEV in surveillance programs for wildlife diseases to expand the potential zoonotic information.
Selection and Evaluation of Porcine circovirus (PCV) 2d Vaccine Strains to Protect against Currently Prevalent PCV2
Authors: Ju Lanjeong , You Su-Hwa , Lee Min-A , Jayaramaiah Usharani , Jeong Young-Ju , Lee Hyang-Sim , Hyun Bang-Hun , Lee Nakhyung , Kang Seok-Jin
Published: September 2023

Porcine circovirus (PCV) 2d is a common genotype in South Korea, and the cross-protective ability of PCV2a-based vaccines has been reported recently. In this study, a PCV2d vaccine candidate was selected, and its protective efficacy against the PCV2d isolate was evaluated. From 2016 to 2020, 234 PCV2d isolates were phylogenetically analyzed using open reading frame 2 (ORF2) sequences and classified into four subgroups: PCV2d-1, PCV2d-2, PCV2d-3, and PCV2d-4. Except for PCV2d-4, which consisted of ungrouped isolates, the three subgroups showed distinct differences at amino acid positions 53 and 169 in the ORF2. The detection rates of PCV2d-1, PCV2d-2, and PCV2d-3 were 36.5, 37.4, and 3.7%, respectively, and representative isolates were selected from each subgroup (QIA244, QIA126, and QIA169, respectively). In the neutralization assay, QIA244 showed the lowest neutralization efficiency among the three PCV2a-based vaccines, whereas the virus-like particles of QIA244 (rQIA244) provided broader protection against the three genotypes than did those of QIA126 and rQIA169. To further evaluate rQIA244 in pigs, the experimental groups were divided into rQIA244-vaccine (2dVac), commercial PCV2a-vaccine (2aVac), and no-vaccination (noVac) groups. The 2dVac effectively reduced the copy number of PCV2d in blood and tissues, as well as in tissue lesions, compared to the effect of 2aVac. Collectively, 2dVac provided by QIA244 ORF2 successfully demonstrated protective efficacy against the currently prevalent PCV2d in vitro neutralization and in vivo assays.
Macroscopic Skin Examination Can Determine the Number of Strips Necessary to Study the stratum corneum in Dogs
Authors: Mosca Marion , Legain Mélanie , Noël Guillaume , Idée Adrien , Pin Didier
Published: September 2023

To evaluate the skin barrier, the stratum corneum (SC) must be isolated and extracted. Currently, skin biopsy is the gold standard method to investigate skin immunology and the presence of biomarkers in dogs. However, a standardized, non-invasive tool to exclusively remove the SC would be of great interest to study healthy and atopic dogs. In this study, we performed D-squames® tape stripping with standardized pressure on seven healthy beagle dogs. A control site was defined and then 25 strips, 50 strips and as many strips as needed to achieve a shiny appearance of the skin were performed on three different experimental sites. After stripping, blinded histopathological examination of a skin biopsy from each site was performed. The number of tape strips required for the skin to become shiny varied between individuals, with a mean of 40 (29–50) strips. There was no significant difference in SC depth between the control site and the site that underwent 25 tape strips. In contrast, the use of 50 strips removed almost all of the SC, with a mean remaining SC depth of 7.82 µm. These data suggest that this non-invasive method can effectively remove the SC, with individual variability, and that a shiny appearance of the skin after stripping can be used as an accurate marker of SC removal.
Comparative Study of Inhaled Fluticasone Versus Oral Prednisone in 30 Dogs with Cough and Tracheal Collapse
Authors: Talavera-López Jesús , Sáez-Mengual Oscar , Fernández-del-Palacio María-Josefa
Published: September 2023

Coughing is common in dogs with tracheal collapse (TC). The use of inhaled corticosteroids is less widespread than oral ones. This study aims to compare the effects of oral and inhaled corticosteroids in dogs with cough and TC. Thirty dogs were prospectively included and randomized to the prednisone oral group (OG, 14) or fluticasone inhaled group (IG, 16). A clinical score (CS) based on four clinical parameters (respiratory distress, cough episodes, cough frequency, tracheal sensitivity) was monitored at the hospital (enrolment and weeks 2 and 4). Water intake, urination habits, and adherence and tolerance to treatments were monitored weekly. Significant improvements in clinical parameters were identified in both groups throughout the study. Between-group (OG–IG) comparisons revealed no significant differences, indicating equivalent improvement. At the study’s endpoint, the IG dogs had a significantly lower CS (5.69 ± 0.79) than OG dogs (6.43 ± 1.02, p < 0.05). Adherence and tolerance were comparable. From weeks 2 to 4, OG dogs were significantly thirstier and urinated more frequently than IG dogs. In conclusion, fluticasone provided good tolerability and efficacy in controlling cough in dogs with TC, and they showed a lower incidence of signs of hypercortisolism compared to prednisone. These data encourage the use of inhaled fluticasone in dogs with cough and TC.