bluuebunny/crossref_metadata_2025 huggingface dataset:
Supplementation with Highly Standardized Cranberry Extract Phytosome Achieved the Modulation of Urinary Tract Infection Episodes in Diabetic Postmenopausal Women Taking SGLT-2 Inhibitors: A RCT Study
Authors: Rondanelli Mariangela , Mansueto Francesca , Gasparri Clara , Solerte Sebastiano Bruno , Misiano Paola , Perna Simone
Published: July 2024

Urinary tract infections (UTIs) are the most common bacterial infections in postmenopausal women, and women with diabetes are possibly at a higher risk. The aim of this study is to evaluate the potential benefit on the prevention of UTI episodes, assessed by urinalysis and urine culture (primary outcome) after two, four and six months, of daily oral dietary supplement (120 mg highly standardized cranberry extract phytosome), compared to placebo, in diabetic postmenopausal women taking SGLT-2 inhibitors. Forty-six subjects (mean age 72.45 ± 1.76) completed the study (23 placebo/23 supplement). Considering UTI episodes, during the six-month supplementation period, an increase of 1.321 (95% CI: −0.322; 2.9650) was observed in the placebo group, while it remained at a steady value of 0.393 (95% CI: −4.230; 5.016) in the supplemented group. Regarding UTI episodes, in both groups, interaction between times for supplementation was statistically significant (p = 0.001). In particular, at follow-up 4, 9% of the placebo group showed infection versus only 3% with cranberry supplementation. Glycaemia and glycated hemoglobin values (secondary outcomes) were not modified at the end of six months with respect to the basal values in both groups, as expected. While in terms of quality of life per the SF-12 health questionnaire, there were no differences between the two groups, an improvement in SF-12 quality of life was observed in both groups (six months vs. basal). In conclusion, highly standardized cranberry extract phytosome supplementation reduced UTI recurrence.
Evaluation of the Effect of Thickeners in Enteral Formulas on the Gastric Emptying Rate of Proteins and Carbohydrates Using a Semi-Dynamic Gastric Model
Authors: Tsukiashi Motoki , Koyama Takahiro , Iwamoto Hiroshi , Sonoki Hirofumi , Miyaji Kazuhiro
Published: July 2024

The emptying rate of specific nutrients in enteral formulas is poorly understood, despite the importance of controlling the emptying rate in tube-fed patients. Because of their viscosity, thickened formulas are widely used to avoid gastric reflux and reduce the burden on caregivers. This study examined how thickeners in enteral formulas affected the gastric emptying rates of proteins and carbohydrates. A semi-dynamic gastric model was used to prepare and digest test enteral formulas that contained either no thickeners or agar (0.2%). The amounts of protein and carbohydrates in each emptied aliquot were determined, and the emptying rate was calculated. We found that agar accelerated protein emptying, and an exploratory experiment with agar (0.5%) suggested the possibility of concentration dependence. Additionally, experiments using gellan gum (0.08%), guar gum (0.2%), or carrageenan (0.08%, 0.2%) suggested that protein emptying could vary depending on the thickener type and that carrageenan might slow it. These results could help with the appropriate selection of thickeners added to liquid foods based on the patient’s metabolic profile to manage nutrition, not only for tube-fed patients but also for those with oropharyngeal dysphagia or diabetes.
Consumption of Ultra-Processed Foods in the Brazilian Amazon during COVID-19
Authors: da Silva Oliveira Elyecleyde Katiane , Vieira Tamires dos Santos , de Souza Orivaldo Florêncio , Noll Priscilla Rayanne e Silva , Bezerra Italla Maria Pinheiro , Cavalcanti Matheus Paiva Emidio , de Abreu Luiz Carlos , Riera Andres Ricardo Perez
Published: July 2024

Background: A COVID-19 pandemic erupted, causing a global viral pneumonia outbreak, marking the most significant public health crisis of the 21st century. These changes profoundly impacted population health and well-being, leading to shifts in dietary habits. This study aimed to evaluate the consumption of ultra-processed foods in the Brazilian Amazon before, during, and after the COVID-19 pandemic. Methods: This is a secondary data analysis study derived from the Surveillance System of Risk and Protective Factors for Chronic Diseases by Telephone Survey (Vigitel, 2019–2021) of the Brazilian Ministry of Health. All statistical analyses were performed using the Stata 17 statistical program in the survey module (svy). Results: We found an increased frequency in the subgroups of consumption of ultra-processed foods in the capital of the Brazilian Amazon region between the years 2019 and 2021. In the cities of Boa Vista and Macapá, there was a significant increase in the consumption of snacks, salty snacks, cookies, and meat products. Boa Vista and Macapá showed an increase in the percentage difference in the consumption ≥5 of ultra-processed subgroups, being 30.4% (p = 0.014) and 53.7% (p = 0.014), respectively. Conclusions: The study indicated an increase in the consumption of ultra-processed foods in the Brazilian Amazon region during and after social distancing.
Impact of Optical-to-Electrical Conversion on the Design of an End-to-End Learning RGB-LED-Based Visible Light Communication System
Authors: Luna-Rivera Jose Martin , Rabadan Jose , Rufo Julio , Gutierrez Carlos A. , Guerra Victor , Perez-Jimenez Rafael
Published: July 2024

Visible Light Communication (VLC) is emerging as a promising technology to meet the demands of fifth-generation (5G) networks and the Internet of Things (IoT). This study introduces a novel RGB-LED-based VLC system design that leverages autoencoders, addressing the often overlooked impact of optical-to-electrical (O/E) conversion efficiency. Unlike traditional methods, our autoencoder-based system not only improves communication performance but also mitigates the negative effects of O/E conversion. Through comprehensive simulations, we show that the proposed autoencoder structure enhances system robustness, achieving superior performance compared to traditional VLC systems. By quantitatively assessing the impact of O/E conversion—a critical aspect previously overlooked in the literature—our work bridges a crucial gap in VLC research. This contribution not only advances the understanding of VLC systems but also provides a strong foundation for future enhancements in 5G and IoT connectivity.
A CMOS Inverter-Based Active Feedback Transimpedance Amplifier
Authors: Park Somi , Lee Sunkyung , Seo Bobin , Choi Yejin , Song Yunji , Chon Yeojin , Choi Shinhae , Park Sung-Min
Published: July 2024

This paper presents an inverter-based active feedback transimpedance amplifier (IAF-TIA), in which an active feedback is applied to a voltage-mode inverter-based TIA, and therefore, the controlled positive regeneration process enables the proposed IAF-TIA to achieve the limiting operations for input currents greater than 100 μApp. However, the active inverter feedback mechanism might be prone to instability, hence mandating a very careful optimization of the loop gain. For this purpose, a diode-connected NMOS transistor is employed as a switch in the feedback path with its gate connected to the input, which helps not only to mitigate the corresponding issue but also to accommodate large input currents up to 1.5 mApp. The proposed IAF-TIA implemented in a standard 180 nm CMOS process demonstrates a 70.5 dBΩ transimpedance gain, 1.21 GHz bandwidth, 4.3 pA/Hz noise current spectral density, 63.5 dB input dynamic range, and 23.6 mW power dissipation from a single 1.8 V supply. The chip core occupies an area of 180 × 50 μm2, including an on-chip P+/N-well/Deep N-well avalanche photodiode as an optical detector.
Broad, Tunable and Stable Single-Frequency Erbium Fiber Compound-Ring Lasers Based on Parallel and Series Structures in L-Band Operation
Authors: Lai Yu-Ting , Chen Lan-Yin , Yang Teng-Yao , Wu Tsu-Hsin , Yeh Chien-Hung , Cheng Kuan-Ming , Lin Chun-Yen , Chow Chi-Wai , Liaw Shien-Kuei
Published: July 2024

In this demonstration, we present two erbium-doped fiber (EDF) lasers, with series and parallel three sub-ring configurations, respectively, to achieve tunable channel output and stable single longitudinal mode (SLM) operation in the L-band range. Here, the fiber ring cavity contains the L-band EDF as a gain medium. Based on the measured results of the two quad-ring structures of the EDF lasers, tunable output bandwidth for the two lasers can be obtained from 1558.0 to 1618.0 nm simultaneously. All the 3 dB linewidths measured for both fiber lasers are 312.5 Hz over the effective wavelength output range. Furthermore, the related optical signal-to-noise ratio (OSNR), output power, output stabilities of the central wavelength and power, and equal output power range of the two proposed EDF lasers are also examined and discussed.
Impacts of Hydrostatic Pressure on Distributed Temperature-Sensing Optical Fibers for Extreme Ocean and Ice Environments
Authors: Tyler Scott W. , Silvia Matthew E. , Jakuba Michael V. , Durante Brian M. , Winebrenner Dale P.
Published: July 2024

Optical fiber is increasingly used for both communication and distributed sensing of temperature and strain in environmental studies. In this work, we demonstrate the viability of unreinforced fiber tethers (bare fiber) for Raman-based distributed temperature sensing in deep ocean and deep ice environments. High-pressure testing of single-mode and multimode optical fiber showed little to no changes in light attenuation over pressures from atmospheric to 600 bars. Most importantly, the differential attenuation between Stokes and anti-Stokes frequencies, critical for the evaluation of distributed temperature sensing, was shown to be insignificantly affected by fluid pressures over the range of pressures tested for single-mode fiber, and only very slightly affected in multimode fiber. For multimode fiber deployments to ocean depths as great as 6000 m, the effect of pressure-dependent differential attenuation was shown to impact the estimated temperatures by only 0.15 °K. These new results indicate that bare fiber tethers, in addition to use for communication, can be used for distributed temperature or strain in fibers subjected to large depth (pressure) in varying environments such as deep oceans, glaciers and potentially the icy moons of Saturn and Jupiter.
Repeatability of Subjective Refraction in Different Age Groups
Authors: Carpena-Torres Carlos , Batres Laura , Serramito María , Carracedo Gonzalo
Published: July 2024

Background: The purpose of this study was to assess the inter-examiner repeatability of subjective refraction across diverse age cohorts, an aspect not previously investigated. Methods: A cross-sectional, randomized study enrolled 86 participants (mean age: 37.0 ± 18.0 years), distributed into three groups: youth, non-presbyopic adults, and presbyopic adults. Each participant underwent three subjective refractions by three different optometrists on separate days. Repeatability analysis encompassed all refractive variables (M, J0, and J45). Results: There were no significant differences between optometrists in all refractive variables for either the overall sample or across age groups (p ≥ 0.05). Additionally, no correlation was found between participants’ age and the mean difference in refractive variables across optometrists (p ≥ 0.05). The 95% confidence interval of repeatability (r) for the total sample was ±0.70 D for M, ±0.29 for J0, and ±0.21 D for J45. Conclusions: Based on these findings and previous research, it is suggested to establish 95% limits of agreement of ±0.75 D for M, and between ±0.25 D and ±0.50 D for both J0 and J45 when validating new refraction systems compared to subjective refraction as the gold standard, regardless of the age of the subjects evaluated.
Efficient Preparation of Poly(allyl diglycol carbonate) (PADC) Nuclear Track Detectors: UV Photopolymerization
Authors: Zhang Guangshe , Zhang Li , Gao Wencheng , Xu Riwei , Ding Kuke
Published: July 2024

The decay of radon gas in soil and buildings produces alpha radiation, which is the second leading cause of lung cancer in humans. Therefore, by conveniently detecting radon gas in the environment, potential sources of danger can be identified early, and necessary measures can be taken to protect human health. Solid-state nuclear track detectors prepared from polyallyl diglycol carbonate (PADC) resin are the most sensitive detectors for alpha radiation released by radon gas. The traditional method of preparing PADC resin involves free radical thermal polymerization, which suffers from issues such as low polymerization efficiency, long processing time, and the occurrence of defects in the product. In this study, PADC resin was efficiently prepared using a UV initiator. Starting from the polymerization mechanism, experiments were designed using a controlled variable approach, and a rational polymerization apparatus was devised. By comparing the double bond conversion rate, transparency, hardness, and yellowness index of the polymers, the optimal initiator for PADC resin, 2-hydroxy-2-methyl-1-phenyl-1-propanone (1173), was selected. The influence of irradiation intensity, irradiation time, and UV initiator dosage was investigated. The performance of the polymers, including double bond conversion rate, optical properties, dynamic mechanical properties, etching rate, and track detection efficiency, was analyzed. The experimental conditions for preparing PADC resin were optimized: irradiation intensity of 12 mW/cm2, irradiation time of 25 min, and UV initiator dosage of 5 parts. The resulting resin polymer had a double bond conversion rate of 93.2% and a track detection efficiency of 0.714.
Exploring Polymer-Based Additive Manufacturing for Cost-Effective Stamping Devices: A Feasibility Study with Finite Element Analysis
Authors: Giolu Cristian , Pupăză Cristina , Amza Cătălin Gheorghe
Published: July 2024

This research investigates the feasibility of manufacturing stamping devices using Material Extrusion (MEX) Additive Manufacturing (AM) technology, traditionally fabricated from metal, to reduce production costs and time. This study examines polymer-based devices subjected to Finite Element Analysis (FEA) to evaluate their performance in stamping metal sheets of varying thicknesses. The findings reveal that ABS polymer devices, while demonstrating potential, operate near the material’s limit under compression forces, particularly for sheet thicknesses up to 1 mm. Specifically, differences of 0.7 mm were observed at the connection radii of 0.25 mm sheets and 1.4 mm for 0.5 mm sheets, with angular deviations of 1.5 degrees for 0.25 mm sheets and 4 degrees for 0.5 mm sheets. Additionally, devices made of Nylon were deemed suitable for reduced-thickness sheets (0.25 mm), performing better than those made of ABS. These results suggest that while ABS devices exhibit significant deviations (up to 45 degrees for 1 mm sheets), the method shows promise for small batch production and prototyping. Further optimisation through material enhancements and mechanical improvements is recommended to minimise deformations and enhance precision.
A Semi-Global Finite-Time Dynamic Control Strategy of Stochastic Nonlinear Systems
Authors: Luo Cuixian , Xue Lingrong , Liu Zhen-Guo , Ren Lifang
Published: July 2024

In the article, the semi-global finite-time control strategy for stochastic nonlinear systems is studied. Firstly, the general stochastic nonlinear system is considered and the required conditions are provided. An important theorem that helps to construct the controller directly is subsequently obtained by adopting a dynamic gain and homogeneous domination method. The equilibrium of the whole system is semi-global finite-time stable in probability (SGFSP) under the designed controller. Finally, the presented method is successfully applied to a second-order system. Simulation results indicate the effectiveness of the method.
Curvature-Adaptive Compact Triple-Band Metamaterial Uniplanar Compact Electromagnetic Bandgap-Based Printed Antenna for Wearable Wireless and Medical Body Area Network Applications
Authors: Messatfa Tarek , Berhab Souad , Chebbara Fouad , Soliman Mohamed S.
Published: July 2024

A novel, compact, monopole apple-shaped, triple-band metamaterial-printed wearable antenna backed by a uniplanar compact electromagnetic bandgap (UC-EBG) structure is introduced in this paper for wearable wireless and medical body area network (WBAN/MBAN) applications. A tri-band UC-EBG structure has been utilized as a ground plane to minimize the impact of antenna radiation on the human body and improve antenna performance for the proposed wearable antenna. Metamaterial triangular complementary split ring resonators (TCSRRs) are incorporated into the antenna and UC-EBG structure, resulting in a compact UC-EBG-backed antenna with an overall size of 39 × 39 × 2.84 mm3 (0.41 λg × 0.41 λg × 0.029 λg). The printed textile antenna operates at 2.45 GHz for the wireless local area network (WLAN), 3.5 GHz for 5G new radio (NR), and 5.8 GHz for the industrial, scientific, and medical (ISM) bands with improved gain and high-efficiency values. Furthermore, the performance of the antenna is analyzed on the human body, where three models of curved body parts are considered: a child’s arm (worst case) with a 40 mm radius, an adult’s arm with a 60 mm radius, and an adult’s leg with a 70 mm radius. The results demonstrate that the proposed antenna is an attractive candidate for wearable healthcare and fitness monitoring devices and other WBAN/MBAN applications due to its compact size, high performance, and low SAR values.
Monitoring and Reconstruction of Actuator and Sensor Attacks for Lipschitz Nonlinear Dynamic Systems Using Two Types of Augmented Descriptor Observers
Authors: Wang Hao , Gao Zhi-Wei , Liu Yuanhong
Published: July 2024

Fault data injection attacks may lead to a decrease in system performance and even a malfunction in system operation for an automatic feedback control system, which has motive to develop an effective method for rapidly detecting such attacks so that appropriate measures can be taken correspondingly. In this study, a secure descriptor estimation technique is proposed for continuous-time Lipschitz nonlinear cyber physical systems affected by actuator attacks, sensor attacks, and unknown process uncertainties. Specifically, by forming a new state vector composed of original system states and sensor faults, an equivalent descriptor dynamic system is built. A proportional and derivate sliding-mode observer is presented so that the system states, sensor attack, and actuator attack can be reconstructed successfully. The observer gains are obtained by using linear matrix inequality to secure robustly stable estimation error dynamics. Moreover, a robust descriptor fast adaptive observer estimator is presented as a complement. Finally, the efficacy levels of the proposed design approaches are validated using a vertical take-off and landing aircraft system. Comparison studies are also carried out to assess the tracking performances of the proposed algorithms.
The Complementary Nature of Financial Risk Aversion and Financial Risk Tolerance
Authors: Grable John , Rabbani Abed , Heo Wookjae
Published: July 2024

Financial risk aversion and financial risk tolerance are sometimes considered to be ‘opposite sides of the same coin’, with the implication being that risk aversion (a term describing the unwillingness of an investor to take risks based on a probability assessment) and risk tolerance (an investor’s willingness to engage in a behavior based on their subjective evaluation of the uncertainty of the outcomes) are inversely-related substitutes. The purpose of this paper is to present an alternative way of viewing these constructs. We show that risk aversion and risk tolerance act as complementary factors in models designed to describe the degree of risk observed in household investment portfolios. A series of multivariate tests were used to determine that financial risk aversion is inversely related to portfolio risk, whereas financial risk tolerance is positively associated with portfolio risk. When used in the same model, the amount of explained variance in portfolio risk was increased compared to models where one, but not the other, measure was used. Overall, financial risk tolerance exhibited the largest model effect, although financial risk aversion was also important across the models analyzed in this study.
Monitoring Water Diversity and Water Quality with Remote Sensing and Traits
Authors: Lausch Angela , Bannehr Lutz , Berger Stella A. , Borg Erik , Bumberger Jan , Hacker Jorg M. , Heege Thomas , Hupfer Michael , Jung András , Kuhwald Katja , Oppelt Natascha , Pause Marion , Schrodt Franziska , Selsam Peter , von Trentini Fabian , Vohland Michael , Glässer Cornelia
Published: July 2024

Changes and disturbances to water diversity and quality are complex and multi-scale in space and time. Although in situ methods provide detailed point information on the condition of water bodies, they are of limited use for making area-based monitoring over time, as aquatic ecosystems are extremely dynamic. Remote sensing (RS) provides methods and data for the cost-effective, comprehensive, continuous and standardised monitoring of characteristics and changes in characteristics of water diversity and water quality from local and regional scales to the scale of entire continents. In order to apply and better understand RS techniques and their derived spectral indicators in monitoring water diversity and quality, this study defines five characteristics of water diversity and quality that can be monitored using RS. These are the diversity of water traits, the diversity of water genesis, the structural diversity of water, the taxonomic diversity of water and the functional diversity of water. It is essential to record the diversity of water traits to derive the other four characteristics of water diversity from RS. Furthermore, traits are the only and most important interface between in situ and RS monitoring approaches. The monitoring of these five characteristics of water diversity and water quality using RS technologies is presented in detail and discussed using numerous examples. Finally, current and future developments are presented to advance monitoring using RS and the trait approach in modelling, prediction and assessment as a basis for successful monitoring and management strategies.
Correction: Osouli, M.; F. Samavati, F. Evaluation of Data Sufficiency for Interannual Knowledge Transfer of Crop Type Classification Models. Remote Sens. 2024, 16, 2007
Authors: Osouli Mohammadreza , F. Samavati Faramarz
Published: July 2024

The authors would like to add an acknowledgment to their paper [...]
Optical Imaging Model Based on GPU-Accelerated Monte Carlo Simulation for Deep-Sea Luminescent Objects
Authors: Han Qing , Sun Mengnan , Zheng Bing , Fu Min
Published: July 2024

Modeling and simulating the underwater optical imaging process can assist in optimizing the configuration of underwater optical imaging technology. Based on the Monte Carlo (MC) method, we propose an optical imaging model which is tailored for deep-sea luminescent objects. Employing GPU parallel acceleration expedites the speed of MC simulation and ray-tracing, achieving a three-order-of-magnitude speedup over a CPU-based program. A deep-sea single-lens imaging system is constructed in the model, composed of a luminescent object, water medium, double-convex lens, aperture diaphragm, and sensor. The image of the luminescent object passing through the imaging system is generated using the forward ray-tracing method. This model enables an intuitive analysis of the inherent optical properties of water and imaging device parameters, such as sensor size, lens focal length, field of view (FOV), and camera position on imaging outcomes in the deep-sea environment.
Early-Season Crop Mapping by PRISMA Images Using Machine/Deep Learning Approaches: Italy and Iran Test Cases
Authors: Mirzaei Saham , Pascucci Simone , Carfora Maria Francesca , Casa Raffaele , Rossi Francesco , Santini Federico , Palombo Angelo , Laneve Giovanni , Pignatti Stefano
Published: July 2024

Despite its high importance for crop yield prediction and monitoring, early-season crop mapping is severely hampered by the absence of timely ground truth. To cope with this issue, this study aims at evaluating the capability of PRISMA hyperspectral satellite images compared with Sentinel-2 multispectral imagery to produce early- and in-season crop maps using consolidated machine and deep learning algorithms. Results show that the accuracy of crop type classification using Sentinel-2 images is meaningfully poor compared with PRISMA (14% in overall accuracy (OA)). The 1D-CNN algorithm, with 89%, 91%, and 92% OA for winter, summer, and perennial cultivations, respectively, shows for the PRISMA images the highest accuracy in the in-season crop mapping and the fastest algorithm that achieves acceptable accuracy (OA 80%) for the winter, summer, and perennial cultivations early-season mapping using PRISMA images. Moreover, the 1D-CNN algorithm shows a limited reduction (6%) in performance, appearing to be the best algorithm for crop mapping within operational use in cross-farm applications. Machine/deep learning classification algorithms applied on the test fields cross-scene demonstrate that PRISMA hyperspectral time series images can provide good results for early- and in-season crop mapping.
Deep Learning-Based Detection of Oil Spills in Pakistan’s Exclusive Economic Zone from January 2017 to December 2023
Authors: Basit Abdul , Siddique Muhammad Adnan , Bashir Salman , Naseer Ehtasham , Sarfraz Muhammad Saquib
Published: July 2024

Oil spillages on a sea’s or an ocean’s surface are a threat to marine and coastal ecosystems. They are mainly caused by ship accidents, illegal discharge of oil from ships during cleaning and oil seepage from natural reservoirs. Synthetic-Aperture Radar (SAR) has proved to be a useful tool for analyzing oil spills, because it operates in all-day, all-weather conditions. An oil spill can typically be seen as a dark stretch in SAR images and can often be detected through visual inspection. The major challenge is to differentiate oil spills from look-alikes, i.e., low-wind areas, algae blooms and grease ice, etc., that have a dark signature similar to that of an oil spill. It has been noted over time that oil spill events in Pakistan’s territorial waters often remain undetected until the oil reaches the coastal regions or it is located by concerned authorities during patrolling. A formal remote sensing-based operational framework for oil spills detection in Pakistan’s Exclusive Economic Zone (EEZ) in the Arabian Sea is urgently needed. In this paper, we report the use of an encoder–decoder-based convolutional neural network trained on an annotated dataset comprising selected oil spill events verified by the European Maritime Safety Agency (EMSA). The dataset encompasses multiple classes, viz., sea surface, oil spill, look-alikes, ships and land. We processed Sentinel-1 acquisitions over the EEZ from January 2017 to December 2023, and we thereby prepared a repository of SAR images for the aforementioned duration. This repository contained images that had been vetted by SAR experts, to trace and confirm oil spills. We tested the repository using the trained model, and, to our surprise, we detected 92 previously unreported oil spill events within those seven years. In 2020, our model detected 26 oil spills in the EEZ, which corresponds to the highest number of spills detected in a single year; whereas in 2023, our model detected 10 oil spill events. In terms of the total surface area covered by the spills, the worst year was 2021, with a cumulative 395 sq. km covered in oil or an oil-like substance. On the whole, these are alarming figures.
Ship Detection in Synthetic Aperture Radar Images under Complex Geographical Environments, Based on Deep Learning and Morphological Networks
Authors: Cao Shen , Zhao Congxia , Dong Jian , Fu Xiongjun
Published: July 2024

Synthetic Aperture Radar (SAR) ship detection is applicable to various scenarios, such as maritime monitoring and navigational aids. However, the detection process is often prone to errors due to interferences from complex environmental factors like speckle noise, coastlines, and islands, which may result in false positives or missed detections. This article introduces a ship detection method for SAR images, which employs deep learning and morphological networks. Initially, adaptive preprocessing is carried out by a morphological network to enhance the edge features of ships and suppress background noise, thereby increasing detection accuracy. Subsequently, a coordinate channel attention module is integrated into the feature extraction network to improve the spatial awareness of the network toward ships, thus reducing the incidence of missed detections. Finally, a four-layer bidirectional feature pyramid network is designed, incorporating large-scale feature maps to capture detailed characteristics of ships, to enhance the detection capabilities of the network in complex geographic environments. Experiments were conducted using the publicly available SAR Ship Detection Dataset (SSDD) and High-Resolution SAR Image Dataset (HRSID). Compared with the baseline model YOLOX, the proposed method increased the recall by 3.11% and 0.22% for the SSDD and HRSID, respectively. Additionally, the mean Average Precision (mAP) improved by 0.7% and 0.36%, reaching 98.47% and 91.71% on these datasets. These results demonstrate the outstanding detection performance of our method.
Use of Non-Destructive Ultrasonic Techniques as Characterization Tools for Different Varieties of Wine
Authors: Corbacho José Ángel , Morcuende David , Rufo Montaña , Paniagua Jesús M. , Ontalba María Ángeles , Jiménez Antonio
Published: July 2024

In this work, we have verified how non-destructive ultrasonic evaluation allows for acoustically characterizing different varieties of wine. For this, a 3.5 MHz transducer has been used by means of an immersion technique in pulse-echo mode. The tests were performed at various temperatures in the range 14–18 °C. The evaluation has been carried out studying, on the one hand, conventional analysis parameters (velocity and attenuation) and, on the other, less conventional parameters (frequency components). The experimental study comprised two stages. In the first, the feasibility of the study was checked by inspecting twelve samples belonging to six varieties of red and white wine. The results showed clearly higher ultrasonic propagation velocity values in the red wine samples. In the second, nine samples of different monovarietal wine varieties (Grenache, Tempranillo and Cabernet Sauvignon) were analyzed. The results show how ultrasonic velocity makes it possible to unequivocally classify the grape variety used in winemaking with the Cabernet Sauvignon variety having the highest values and the Grenache the lowest. In addition, the wines of the Tempranillo variety are those that present higher values of the attenuation coefficient, and those from the Grenache variety transmit higher frequency waves.
An Overview of the Efficiency and Long-Term Viability of Powered Hydrogen Production
Authors: Guerrero-Rodríguez Nestor F. , De La Rosa-Leonardo Daniel A. , Tapia-Marte Ricardo , Ramírez-Rivera Francisco A. , Faxas-Guzmán Juan , Rey-Boué Alexis B. , Reyes-Archundia Enrique
Published: July 2024

This work studies the efficiency and long-term viability of powered hydrogen production. For this purpose, a detailed exploration of hydrogen production techniques has been undertaken, involving data collection, information authentication, data organization, and analysis. The efficiency trends, environmental impact, and hydrogen production costs in a landscape marked by limited data availability were investigated. The main contribution of this work is to reduce the existing data gap in the field of hydrogen production by compiling and summarizing dispersed data. The findings are expected to facilitate the decision-making process by considering regional variations, energy source availability, and the potential for technological advancements that may further enhance the economic viability of electrolysis. The results show that hydrogen production methods can be identified that do not cause significant harm to the environment. Photolysis stands out as the least serious offender, producing 0 kg of CO2 per kg of H2, while thermolysis emerges as the major contributor to emissions, with 20 kg of CO2 per kg of H2 produced.
Quantitative Carbon Emission Prediction Model to Limit Embodied Carbon from Major Building Materials in Multi-Story Buildings
Authors: Xie Qimiao , Jiang Qidi , Kurnitski Jarek , Yang Jiahang , Lin Zihao , Ye Shiqi
Published: July 2024

As the largest contributor of carbon emissions in China, the building sector currently relies mostly on enterprises’ own efforts to report carbon emissions, which usually results in challenges related to information transparency and workload for regulatory bodies, who play an otherwise vital role in controlling the building sector’s carbon footprint. In this study, we established a novel regulatory model known as QCEPM (Quantitative Carbon Emission Prediction Model) by conducting multiple linear regression analysis using the quantities of concrete, rebar, and masonry structures as independent variables and the embodied carbon emissions of a building as the dependent variable. We processed the data in the detailed quantity list of 20 multi-story frame structure buildings and fed them to the QCEPM for the solution. Comparison of the QCEPM-calculated results against the time-consuming and error-prone manual calculation results suggested a mean absolute percentage error (MAPE) of 2.36%. Using this simplified model, regulatory bodies can efficiently supervise the embodied carbon emissions in multi-story frame structures by setting up a carbon quota for a project in its approval stage, allowing the construction enterprise to carry out dynamic control over the three most important audited building materials throughout a project’s planning and implementation phase.
Cleaner Production of Cementitious Materials Containing Bioaggregates Based on Mussel Shells: A Review
Authors: de Freitas José Júlio Garcia , Vieira Carlos Maurício Fontes , Natalli Juliana Fadini , Lavander Henrique David , de Azevedo Afonso Rangel Garcez , Marvila Markssuel Teixeira
Published: July 2024

This text provides a bibliographic review on bioaggregates obtained from mussel shells and similar materials, evaluating the main properties altered with the use of this type of recycled aggregate in cementitious materials. The bibliographic analysis highlights the main problems and challenges of using bioaggregates related to the presence of organic impurities and chlorides and due to the lamellar and flat shape of the grains, which impair adhesion in the transition zone. The advantages of mussel shell bioaggregates include their limestone-based chemical composition, properties that are inert and compatible with the application, and a specific mass close to conventional aggregates. Regarding their use in cementitious materials, in general, there is a reduction in workability and an increase in incorporated air, porosity, and water absorption, resulting in a reduction in compressive strength. However, it is observed that lower replacement levels make it possible to use bioaggregates, especially fine aggregates, in cementitious materials for different applications, such as structural concrete, coating mortar, and sealing systems. The positive points are related to the promotion of thermal insulation and the reduction in density, which allow for various uses for cementitious materials with bioaggregates, such as lightweight concrete, permeable concrete, and thermal and acoustic insulation mortars. It is concluded that the use of bioaggregates in concrete and mortars is viable, but the need for more experimental work to solve the main problems encountered, such as high water absorption and low compressive strength, is highlighted.
Collaborative Pricing of Green Supply Chain of Prefabricated Construction
Authors: Zhang Xuelong , Yang Qian , Song Tingting , Xu Yuxin
Published: July 2024

In the process of carbon peak and carbon neutrality, prefabricated buildings have developed rapidly, and the concept of green and low carbon has been introduced into the field of prefabricated buildings. This paper establishes an information sharing platform based on BIM (Building Information Modeling), RFID (Radio Frequency IDentification), and GIS (Geographic Information System) technologies from the green supply chain of prefabricated buildings. On the basis of information sharing, the Stackelberg two-stage game is used to analyze and compare the overall profit of the supply chain under the centralized pricing decision and the decentralized pricing decision. Through numerical simulation, this paper analyzes the relationship between pricing and the overall profit of the supply chain, compares the difference of the overall profit of supply chain under two different pricing strategies, centralized pricing and decentralized pricing, and analyzes the influence of information sharing degree on the overall profit of the supply chain. The results show that the overall profit of the supply chain under centralized pricing decisions is significantly higher than that under decentralized pricing decisions. The higher the degree of information sharing, the greater the overall profit of the supply chain.
Optimizing Nitrogen Fertilization for Enhanced Rice Straw Degradation and Oilseed Rape Yield in Challenging Winter Conditions: Insights from Southwest China
Authors: Wang Hongni , Nabi Farhan , Sajid Sumbal , Kama Rakhwe , Shah Syed Muhammad Mustajab , Wang Xuechun
Published: July 2024

The crop straw returning to the field is a widely accepted method to utilize and remediate huge agricultural waste in a short period. However, the low temperatures and dry conditions of the winter season in Southwest China can be challenging for the biodegradation of crop straw in the field. With a similar aim, we designed a short-term study where rice straw was applied to the field with different concentrations of nitrogen (N) fertilizer while keeping phosphorus (P) constant; CK, (N0P0); T1, (N0P90); T2, (N60P90); T3, (N120P90); and T4, (N180P90) were added to evaluate its impact on straw degradation during cold weather. We found that high fertilization (T4) significantly improved crop yield, organic matter, and lignocellulose degradation under cold temperatures (21.5–3.2 °C). It also significantly improved soil nitrogen agronomic efficiency, nitrogen use efficiency, and nitrogen physiological efficiency. The yield was highest in T4 (1690 and 1399 kg/ha), while T3 acted positively on soil lignocellulolytic enzyme activity, which in turn resulted in higher degradation of OM and lignocellulosic material. Pearson’s correlation analysis revealed that total nitrogen, total phosphorus, available nitrogen, and available phosphorus were important variables that had a significant impact on soil EC, bulk density, water holding capacity, and soil enzymes. We found that nitrogen application significantly changed the soil bacterial community by increasing the richness and evenness of lignocellulolytic bacteria, which aided the degradation of straw in a short duration. This study’s finding indicates that the decomposition of crop straw in the field under cold weather stress was dependent on nutrient input, and N, in an appropriate amount (N120-180), was suitable to achieve higher yield and higher decomposition of straw in such an environment.
The Role of Renewable Energies in Combating Poverty in Brazil: A Systematic Review
Authors: da Silva Eugenia Cornils Monteiro , Lira Marcos Antonio Tavares , Gonçalves Marcelo Carneiro , da Silva Osvaldo Augusto Vasconcelos de Oliveira Lopes , Jean Wesly , dos Santos Júnior Raimundo Batista
Published: July 2024

Poverty reduction is a complex global challenge where renewable energy emerges as a promising solution, particularly in resource-rich countries like Brazil. Renewable energy can enhance conditions in vulnerable communities without exacerbating climate change. This paper reviews the scientific literature on the role of renewable energy in alleviating energy poverty, focusing on Brazil and its global partnerships. Using the Web of Science database with the keywords poverty, renewable energy, and Brazil, this study analyzes 38 articles. The inclusion criteria were broad, focusing on the relationship between poverty in Brazil and renewable energy use. Keywords such as specific types of renewable energy (e.g., solar, wind) were excluded to avoid omitting important renewable sources. This review encompasses theoretical models, discourse analyses, case studies, and systematic reviews, addressing topics from rural electrification to socio-economic factors influencing sustainable energy adoption. Despite growing interest and international collaboration, research gaps remain, highlighting the need for increased academic engagement. The objective of this study is to address the existing gap in the literature concerning the impact of renewable energies on energy poverty in Brazil. Through a comprehensive review, this work maps current knowledge, identifies gaps, and highlights trends by integrating socio-economic analyses with technical assessments for a holistic perspective.
Tapping the Conversation on the Meaning of Decarbonization: Discourses and Discursive Agency in EU Politics on Low-Carbon Fuels for Maritime Shipping
Authors: von Malmborg Fredrik
Published: July 2024

EU politics on decarbonizing shipping is an argumentative endeavor where different policy actors strive try to influence others to see problems and policy solutions according to their perspectives to gain monopoly on the framing and design of policies. This article critically analyzes, by means of argumentative discourse analysis, the politics and policy process related to the recent adoption of the FuelEU Maritime regulation, the world’s first legislation to set requirements for decarbonizing maritime shipping. Complementing previous research focusing on the roles and agency of policy entrepreneurs and beliefs of advocacy coalitions active in the policy process, this paper dives deeper into the politics of the new legislation. It aims to explore and explain the discursive framing and politics of meaning-making. By analyzing the political and social meaning-making of the concept “decarbonizing maritime shipping”, this paper helps us understand why the legislation was designed in the way it was. Different narratives, storylines and discourses defining different meanings of decarbonization are analyzed. So is the agency of policy actors trying to mutate the different meanings into a new meaning. Two discourses developed in dialectic conversation framed the policy proposals and subsequent debates in the policy process, focusing on (i) incremental change and technology neutrality to meet moderate emission reductions and maintain competitiveness, and (ii) transformative change and technology specificity to meet zero emissions and gain competitiveness and global leadership in the transition towards a hydrogen economy. Policy actors successfully used discursive agency strategies such as multiple functionality and vagueness to navigate between and resolve conflicts between the two discourses. Both discourses are associated with the overarching ecological modernization discourse and failed to include issue of climate justice and a just transition. The heritage of the ecological modernization discourse creates lock-ins for a broader decarbonization discourse, thus stalling a just transition.
Enhanced Adaptive Dynamic Surface Sliding Mode Control for Optimal Performance of Grid-Connected Photovoltaic Systems
Authors: Alnami Hashim , Hakmi Sultan H. , Abdelwahab Saad A. Mohamed , Abdellatif Walid S. E. , Hegazy Hossam Youssef , Mohamed Wael I. , Mohamed Moayed
Published: July 2024

This study presents an enhanced, adaptive, and dynamic surface sliding mode control (SMC), a cutting-edge method for improving grid-connected photovoltaic (PV) system performance. The suggested control approach uses dynamic SMC and adaptive approaches to enhance the robustness and efficiency of a system. Proportional–integral (PI) and SMC, two control systems for maximum power point tracking (MPPT) in PV systems, are compared in this paper. This study finds that the SMC system is a more effective and efficient MPPT approach for PV systems compared to the conventional PI control system. The SMC system’s unique feature is the capacity to stabilize grid voltage and attain a modulation index of less than one. An important component of power electronic system control is the index, which acts as a parameter representing the relationship between the output signal’s amplitude and the reference signal’s amplitude. The SMC method demonstrates improved robustness, efficiency, and stability, especially in dynamic operating settings with load and solar radiation changes. Compared to the PI control, the SMC exhibits a noteworthy 75% reduction in voltage fluctuations and an improvement in the power output of 5% to 10%. Regarding output power optimization, voltage stability, and accurate current tracking, the SMC system performs better than the PI control system. Furthermore, the SMC technique maintains a modulation index below one and guarantees grid voltage stability, both of which are essential for the efficiency and stability of power electrical systems.
Handheld In Situ Methods for Soil Organic Carbon Assessment
Authors: Loria Nancy , Lal Rattan , Chandra Ranveer
Published: July 2024

Soil organic carbon (SOC) assessment is crucial for evaluating soil health and supporting carbon sequestration efforts. Traditional methods like wet digestion and dry combustion are time-consuming and labor-intensive, necessitating the development of non-destructive, cost-efficient, and real-time in situ measurements. This review focuses on handheld in situ methodologies for SOC estimation, underscoring their practicality and reasonable accuracy. Spectroscopic techniques, like visible and near-infrared, mid-infrared, laser-induced breakdown spectroscopy, and inelastic neutron scattering each offer unique advantages. Preprocessing techniques, such as external parameter orthogonalization and standard normal variate, are employed to eliminate soil moisture content and particle size effects on SOC estimation. Calibration methods, like partial least squares regression and support vector machine, establish relationships between spectral reflectance, soil properties, and SOC. Among the 32 studies selected in this review, 14 exhibited a coefficient of determination (R2) of 0.80 or higher, indicating the potential for accurate SOC content estimation using in situ approaches. Each study meticulously adjusted factors such as spectral range, pretreatment method, and calibration model to improve the accuracy of SOC content, highlighting both the methodological diversity and a continuous pursuit of precision in direct field measurements. Continued research and validation are imperative to ensure accurate in situ SOC assessment across diverse environments. Thus, this review underscores the potential of handheld devices for in situ SOC estimation with good accuracy and leveraging factors that influence its precision. Crucial for optimizing carbon farming, these devices offer real-time soil measurements, empowering land managers to enhance carbon sequestration and promote sustainable land management across diverse agricultural landscapes.